Biological Conservation xxx (2011) xxx–xxx
Contents lists available at SciVerse ScienceDirect
Biological Conservation
journal homepage: www.elsevier.com/locate/biocon
Review
Seed dispersal in changing landscapes
Kim R. McConkey a,⇑, Soumya Prasad b, Richard T. Corlett c, Ahimsa Campos-Arceiz d, Jedediah F. Brodie e,
Haldre Rogers f, Luis Santamaria g
a
A.V. Rama Rao Research Foundation, 7-102/54 Sai Enclave, Habshiguda, Hyderabad 500 007, India
Centre for Ecological Sciences, Indian Institute of Science, Bangalore 560 012, India
c
Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117432, Singapore
d
School of Geography, University of Nottingham Malaysia Campus, Semenyih 43500, Selangor, Malaysia
e
Wildlife Biology Program, University of Montana, Missoula, MT 59812, USA
f
Department of Biology, University of Washington, Seattle, WA 98195, USA
g
Mediterranean Institute for Advanced Studies – IMEDEA (CSIC-UIB), Miquel Marqués 21, E07190 Esporles, Mallorca, Balearic Islands, Spain
b
a r t i c l e
i n f o
Article history:
Received 17 May 2011
Received in revised form 5 September 2011
Accepted 10 September 2011
Available online xxxx
Keywords:
Biological invasions
Climate change
Fragmentation
Hunting
Overharvesting
Seed dispersal
a b s t r a c t
A growing understanding of the ecology of seed dispersal has so far had little influence on conservation
practice, while the needs of conservation practice have had little influence on seed dispersal research. Yet
seed dispersal interacts decisively with the major drivers of biodiversity change in the 21st century:
habitat fragmentation, overharvesting, biological invasions, and climate change. We synthesize current
knowledge of the effects these drivers have on seed dispersal to identify research gaps and to show
how this information can be used to improve conservation management. The drivers, either individually,
or in combination, have changed the quantity, species composition, and spatial pattern of dispersed seeds
in the majority of ecosystems worldwide, with inevitable consequences for species survival in a rapidly
changing world. The natural history of seed dispersal is now well-understood in a range of landscapes
worldwide. Only a few generalizations that have emerged are directly applicable to conservation management, however, because they are frequently confounded by site-specific and species-specific variation. Potentially synergistic interactions between disturbances are likely to exacerbate the negative
impacts, but these are rarely investigated. We recommend that the conservation status of functionally
unique dispersers be revised and that the conservation target for key seed dispersers should be a population size that maintains their ecological function, rather than merely the minimum viable population.
Based on our analysis of conservation needs, seed dispersal research should be carried out at larger spatial scales in heterogenous landscapes, examining the simultaneous impacts of multiple drivers on community-wide seed dispersal networks.
Ó 2011 Elsevier Ltd. All rights reserved.
Contents
1.
2.
3.
4.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Disturbances to seed dispersal processes: identifying gaps in our knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.
Habitat fragmentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.
Overharvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1.
Frugivores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2.
Plants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.
Biological invasions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.
Climate change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5.
Interactions between drivers of biodiversity change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Incorporating seed dispersal knowledge into conservation management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.
Habitat fragmentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.
Overharvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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⇑ Corresponding author. Tel.: +91 40 27117175; fax: +91 40 27179149.
E-mail addresses: [email protected] (K.R. McConkey), prasadsoumya@ gmail.com (S. Prasad), [email protected] (R.T. Corlett), [email protected]
(A. Campos-Arceiz), [email protected] (J.F. Brodie), [email protected] (H. Rogers), [email protected] (L. Santamaria).
0006-3207/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.biocon.2011.09.018
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
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K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
5.
4.2.1.
Frugivores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.2.
Plants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3.
Biological invasions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4.
Facilitating adaptation to climate change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction
Linking ecological research and conservation practice is a major
challenge in conservation biology (Knight et al., 2008). Ecological
researchers usually look in detail at only a few components or processes within a system while conservation practitioners make
decisions that affect entire ecosystems (Gardner et al., 2009). Unless the lessons from detailed academic studies are synthesized
in a useable form, practitioners will continue to base their decisions on an understanding of a subset of the ecosystem. The ecology of seed dispersal is an excellent example of this failure of
communication, with a growing understanding of the processes involved having so far had little influence on conservation practice.
Although seed dispersal research is increasingly being conducted
at larger spatio-temporal scales, it has not been synthesized in a
useable form for conservation practice and many conservation-relevant gaps exist.
Seed dispersal interacts with all the major drivers of biodiversity change in the 21st century: habitat fragmentation, overharvesting, biological invasions, and climate change (Pereira et al.,
2010) (Fig. 1). In fragmented landscapes, seed dispersal has a major
influence on both plant species persistence (Farwig et al., 2006;
Herrera and Garcia, 2010; Sansevero et al., 2011) and vegetation
recovery when disturbance is reduced (Howe and Miriti, 2004).
Hunting has an obvious impact on seed dispersal by large vertebrates (Terborgh et al., 2008; Vanthomme et al., 2010) and overharvesting of plants may also disrupt dispersal mutualisms
(Ticktin, 2004). The patterns of spread of invasive plants are largely
determined by their dispersal vectors (Buckley et al., 2006; Gosper
et al., 2005). Finally, anthropogenic climate change adds to the
importance of seed dispersal, since most plant populations on
Earth will need to move long distances over the next 50–100 years
if they are to keep pace with moving climates (Chen et al., 2011).
However, large-bodied animals capable of dispersing seeds to distances required for plants to maintain this pace, are often threatened by hunting or habitat loss (Corlett, 2009). Failure to keep
pace with changing climates may lead to major biodiversity declines and a significant reduction in carbon fixation.
There is evidence for a growing, global, seed dispersal crisis,
which has so far been masked, by the long life-span of perennial
plants. Plant populations that are neither being dispersed, nor
regenerating in situ, may persist for decades in an apparently
healthy state (Guimarães et al., 2008). These ‘living dead’ are, at
least for now, still living, so their rescue is low down on the long list
of conservation priorities. At the same time, the role of ‘assisted
migration’—artificial dispersal—as a solution for expected future
problems is being debated in the conservation literature without
any clear understanding of the potential for unassisted migration
(Hoegh-Guldberg et al., 2010; Sax et al., 2009; Vitt et al., 2010). It
is apparent that improved communication between seed dispersal
researchers and conservation practitioners could benefit both sides.
Our aim here is to synthesize current understanding of the
interactions between seed dispersal and the major drivers of global
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change in order to identify key gaps that require further research
and to provide useful guidance to conservation practitioners. We
start by reviewing existing knowledge and identifying knowledge
gaps, and then follow this by suggestions for how our current
understanding of seed dispersal processes can be incorporated into
conservation planning and management.
2. Methods
The process of seed dispersal (i.e., the movement of seeds away
from parent plants), links the reproductive stage of adult plants
(pollination, fruit set) with processes regulating the establishment
of their offspring, including post-dispersal seed survival, seedling
establishment, and sapling growth (Wang and Smith, 2002). Our
review encompasses recent (mostly published post-2000) research
addressing the impacts of four major drivers of global change (habitat fragmentation, overharvesting, biological invasions, climate
change) on the seed dispersal process itself, i.e., from fruit removal
to seed deposition. Impacts on upstream (flowering, pollination,
seed set, etc.) and downstream (seed predation, germination,
etc.) processes are important, but outside the scope of this review.
Within the scope, we focus largely on findings of direct relevance
to conservation management and on conservation-relevant gaps
in existing knowledge. The review is targeted at both conservation
practitioners and seed dispersal researchers.
The aim of this review was to achieve a broad review of the
problem. This breadth means that each part is covered in a concise
manner, highlighting important insights. The impact of each driver
on seed dispersal was reviewed thoroughly to identify the main
trends that have been established and the gaps in our knowledge.
In the final review, we present recent references that address the
varying results and opinions. Where there was contradictory evidence for a particular effect, we include each scenario that has sufficient support. We used these published results to identify
generalizations that may have some applicability in conservation
management. Our suggestions for improved conservation management include novel ideas that are apparent when maintenance of
seed processes is considered, restating the objectives of some leading (but unfortunately rare) work directly using seed dispersal
knowledge in conservation management, and rethinking some
classic conservation techniques.
3. Disturbances to seed dispersal processes: identifying gaps in
our knowledge
3.1. Habitat fragmentation
In human-dominated landscapes, fragments of the original vegetation cover often remain, with varying size, quality and connectivity (Lindenmayer et al., 2008). Seed dispersal is highly variable
within and between these habitat fragments and is dependent on
factors that determine plant and frugivore persistence within
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
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Fig. 1. Effects of five drivers of global biodiversity loss on dispersal vectors (wind and animals) and the subsequent impact these changes have on seed dispersal at population
and community levels. Links proven by empirical studies are indicated by a solid line, and unproven links by a hatched line.
fragments, and the mobility of seeds between fragments (Brudvig
et al., 2009; Cramer et al., 2007; Moran et al., 2004). Under the
influence of the island biogeography theory, seed dispersal research in fragmented landscapes has been founded on the idea of
fragments as islands of native vegetation within a sea of humanmodified land-uses. Most studies have focused on patch characteristics, examining the influence that remnant area and/or isolation
have on various stages of the seed dispersal cycle. Declining habitat
area and increasing isolation have been found to reduce both the
quantity of fruit removal and seed dispersal distances within and
between fragments in most systems (Cordeiro et al., 2009; Kirika
et al., 2008; Lehouck et al., 2009; Rodriguez-Cabal et al., 2007;
Uriarte et al., 2011), although exceptions exist (Farwig et al., 2006).
The nature of the matrix surrounding habitat fragments influences seed movement between fragments through its effects on frugivore abundance and behavior, and on wind dynamics (Damschen
et al., 2008; Prevedello and Vieira, 2010). The abundance and diversity of native plant and frugivore species in fragments decreases
along a coarse gradient of matrix types, from secondary forest, agroforestry, exotic plantations, arable crops, to pasture (Gardner et al.,
2009). However, few seed dispersal studies have explicitly considered the matrix as a conduit for movement of seeds and frugivores
(Breitbach et al., 2010; Gillies et al., 2011; Watling et al., 2011).
Frugivores differ in their ability to move across a matrix and their
tolerance to habitat degradation (Prevedello and Vieira, 2010), and
it is the multiple combinations of these factors that determine the
final impact on seed dispersal. Matrix attributes alter frugivore
behavior and movement patterns (Breitbach et al., 2010; Gillies et
al., 2011; Uriarte et al., 2011; Watling et al., 2011) with variable results reported, even for species with similar diets and social organizations (Chapman et al., 2003) and across seasons (Naoe et al., 2011).
These effects may result in altered seed dispersal patterns, although
this link has rarely been explored (Magrach et al., in press; Serio-Silva and Rico-Gray, 2002). How frugivores use the matrix will be influenced by bio-physical characteristics (Breitbach et al., 2010; Gillies
et al., 2011), its disturbance history, changes in food quantity or
quality, and altered interactions with other wildlife (e.g., predation,
competition; Watling et al., 2011) and with people (e.g., hunting).
Seed movement across and into the matrix is also influenced by
the presence of structural elements such as linking corridors, live
fences, paddock trees and remnant vegetation (Tewksbury et al.,
2002; Levey et al., 2005; Pizo and Dos Santos, 2010). Most research
identifying elements that promote seed movement across and into
the matrix has focused on interactions driven by fragment-tolerant
disperser species (Galindo-González et al., 2000; Levey et al., 2005),
rather than forest-dependent frugivores (Gillies et al., 2011).
Wind circulation patterns are also altered in fragmented habitats (Damschen et al., 2008). Matrix permeability may be critical
for wind-dispersed species in some ecosystems, but studies assessing landscape connectivity for wind-dispersed species have produced variable results, and no studies have investigated the
impact matrix composition has on wind dynamics. Habitat corridors can act as wind breaks in open matrices and lead to increased
accumulation of wind-dispersed seeds (Damschen et al., 2008).
Similarly, canopy gaps can increase the deposition of seeds by
altering wind speeds, seed aerodynamics and by trapping seeds
in eddies (Schupp et al., 1989). Conversely, pasture matrices could
enhance patch isolation, since interspersed paddock trees create
obstacles to wind dispersal while failing to provide suitable habitat
for establishment (Rolim and Chiarello, 2004; Magrach et al., in
press).
Persistence of plant species in fragmented landscapes is influenced by how fruit and seed characteristics interact with disperser
attributes. Larger-seeded wind- and animal-dispersed species often experience reduced dispersal in habitat fragments compared
to smaller-fruited species in both tropical and temperate landscapes (Cramer et al., 2007; McEuen and Curran, 2004). These
fruit-size effects are probably driven by declines in frugivores
capable of handling large fruits in habitat fragments (Moran et
al., 2004) and the shorter average dispersal distances of larger
wind-dispersed fruits (Greene and Johnson, 1993). Plant species
that are dispersed by a few specialized dispersers (e.g., large fruit
size requiring large-gaped dispersers, species dispersed by deepforest frugivores) experience reduced fruit removal (Cordeiro et
al., 2009; Lehouck et al., 2009) and shortened dispersal within habitat fragments (McEuen and Curran, 2004). In contrast, plant
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
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K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
species that are dispersed by generalist frugivores or those that
still have several functional dispersers are less affected by fragmentation (Martínez-Garza and Howe, 2003; McEuen and Curran,
2004; Farwig et al., 2006). Although generalizations about fruit size
and dispersal capacity can be useful in the absence of other information (particularly for wind-dispersed plants; e.g. Thomson et al.,
2011), there is no substitute for knowledge of local dispersal natural history. We have a poor understanding of disperser redundancy
even in intact communities and there are exceptions to most generalizations (Jordano et al., 2007; Moran et al., 2004).
Our limited understanding of seed dispersal across heterogeneous fragmented landscapes reflects a major research gap. Few attempts have been made to address seed movement across
fragmented landscapes at landscape scales (Brudvig et al., 2009;
Damschen et al., 2008), to identify plant and fruit traits that characterize dispersal-limited species in fragmented landscapes, or to
identify the factors influencing the spatio-temporal variation in seed
dispersal patterns, which can have important consequences for subsequent stages of the dispersal cycle (Herrera and Garcia, 2010).
3.2. Overharvesting
3.2.1. Frugivores
Wildlife hunting, for subsistence or trade, is a major cause of decline for many frugivores, particularly mammals and large birds
(Corlett, 2007; Wright, 2003). The impacts are now most obvious
in the tropics, where hunting pressures are rapidly increasing,
but most temperate systems have previously lost species as a
result of hunting (Ellsworth and McComb, 2003; Martin and
Steadman, 1999). Hunting in tropical forests is a pervasive threat
in even the largest and most remote reserves, since it involves both
commercial harvesting of high-value species as well as harvesting
of common species for local use (Peres and Terborgh, 1995). Since
many hunted vertebrates eat fruit, their decline alters disperser
assemblages, with negative consequences for seed dispersal
(Corlett, 2007; Redford, 1992; Wright, 2003; Vanthomme et al.,
2010). These effects are intensified by the fact these animal communities are already truncated systems, following thousands of
years of hunting pressure (Corlett, 2007; Wright, 2003). The ecological consequences of hunting have been investigated most
widely in the Neotropics and island ecosystems (e.g., Chimera
and Drake, 2010; Kelly et al., 2010; Meehan et al., 2002; Peres
and Palacios, 2007; Wright, 2003), with few studies in Asia or
Africa despite unprecedented hunting levels in some regions
(Corlett, 2007; Fa and Brown, 2009; Vanthomme et al., 2010).
Selective removal of frugivores decreases overall fruit removal
from fruiting trees and seed dispersal (Wang et al., 2007; Wright
et al., 2000), ultimately causing a decrease in the reproductive success of plants (Forget and Jansen, 2007) and reduced population
growth rates for animal-dispersed plant species (Brodie et al.,
2009). Because our understanding of disperser redundancy is limited, however, it is difficult to predict the impact the decline of a
single hunted vertebrate may have. The few studies addressing
redundancy in hunted systems have generated inconsistent results,
with the effect probably dependent on traits of the plant species
(Sethi and Howe, 2009) and the diversity and evolutionary history
of local frugivore guilds. Network studies are useful for determining
the robustness and redundancy within dispersal systems and identifying the species that are most important for maintaining network
structure (i.e., ‘hubs’ are species with a large number of interactions, ‘connectors’ bind together different subgroups in the network; Mello et al., 2011b). These studies suggest dispersal
networks are robust to loss of some frugivores (Bascompte et al.,
2003; Mello et al., 2011a), but more community-wide studies are
required (Donatti et al., 2011) and the ecological and behavioral responses of surviving species are largely unknown. The lost disperser
may be partially compensated by changes in the activities of nonhunted species as a result of reduced competition. Compensatory
population increases have been widely reported (Wright, 2003),
but compensatory replacement of ecological roles has not yet been
documented (and, in some cases, it has been shown not to take
place, e.g. Staddon et al., 2010).
Hunters usually target the largest vertebrates and have done so
for millennia (Corlett, 2007; Crowley, 2010; Wright, 2003). Large
vertebrates are often associated with the dispersal of large-fruited
species (Gautier-Hion et al., 1985; Kitamura et al., 2002) and are
more central components of dispersal networks (Donatti et al.,
2011). Consequently, large-fruited, animal-dispersed, tree species
decline, often quite drastically, in overhunted forests (Peres and
Palacios, 2007; Terborgh et al., 2008). This pattern is most visible
on islands, where historic and prehistoric hunting pressure has resulted in highly simplified frugivore assemblages, with often one
(or no) animals capable of dispersing large seeds (Chimera and
Drake, 2010; Hansen and Galetti, 2009; Meehan et al., 2002), and
even these species are frequently hunted (Walker, 2007).
Differences in generation time between vertebrates and forest
trees means that there will be a time lag between animal extirpation and tree decline; forests that have been overhunted for decades
may develop an ‘extinction debt’ for their vertebrate-dispersed
trees (Brodie et al., 2009). Such debts are probably nearly universal
in tropical forests today as a result of the explosion of hunting pressure in recent decades. Defaunated forests may exhibit slow shifts
in species composition, as animal-dispersed trees are replaced by
wind- or gravity-dispersed species (Brodie et al., 2009) and largeseeded trees by those with smaller seeds (Terborgh et al., 2008).
Thus, even if at some later time we could control hunting, the reintroduction or natural recolonization of extirpated frugivores may
be hindered by the reduction in the food trees upon which the animals fed. Empirical studies testing these ideas are limited by the
long time scales involved, but systems that lost their dispersers at
a more distant time period could provide adequate test cases. For
example, some island systems that have suffered frugivore extinctions within the last few 100 years have plant species with fruit displaying characters that are not suitable for extant (or exotic)
frugivores, and these plant species appear to be suffering recruitment failure (Chimera and Drake, 2010; Griffiths et al., 2010).
Even if animals are not completely extirpated, hunting-induced
reductions in frugivore density (‘half-empty forests’) can have
important effects on seed dispersal. We have little understanding
of the functional relationship between frugivore density and seed
dispersal, but the context-dependent nature of seed dispersal
effectiveness (Schupp et al., 2010) suggests that the relationship
may often be non-linear (Redford and Feinsinger, 2001). This
non-linearity is due to at least three factors. First, animals may exhibit differences in foraging efficiency within populations, implying that the loss of particular individuals may disproportionately
affect dispersal services (Redford and Feinsinger, 2001). Second,
foraging behavior may be density-dependent. While modest declines in frugivore numbers might have minimal effects on seed
dispersal, certain species may have thresholds beyond which extant frugivore populations cease to provide effective disperser services. For example, flying foxes cease to be effective dispersers at
lower population densities due to reduced intra-specific competition (McConkey and Drake, 2006). Third, reduced competitive effects following the loss of a species from a frugivore community
may alter visitation patterns, fruit removal and dispersal distances
by other frugivore species due to altered inter-specific interactions
at fruiting trees (cf. McConkey and Drake, 2006).
3.2.2. Plants
Local markets across the tropics display an ever-changing array
of wild-collected fruits (R. Corlett pers. obs.). Wild fruit harvests
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
are less diverse and more seasonal in the temperate zone, but the
growing demand for ‘organic’ products may increase pressure on
favored species (Willer et al., 2008). A majority of the harvested
wild fruits are fleshy, so this harvest may compete with vertebrate
frugivores (Ticktin, 2004). The impact of fruit and seed harvests on
the recruitment dynamics of resource plant populations has been
examined at several sites (reviewed by Ticktin (2004)), but the impacts of fruit harvests on frugivores remains poorly researched.
Studies that have examined the demography of harvested plant
populations using matrix population models suggest that these
populations might persist even under very high levels of fruit
and seed harvest (Ticktin, 2004). However, these results might be
a consequence of the low transition probability from seeds to
adults in long-lived plant populations. Just as an ‘‘extinction debt’’
exists between plant species and hunted animals, the impact of
plant harvesting may take many years to become apparent. Several
harvested plant populations have exhibited lowered seedling densities at intensively harvested sites, which has been attributed to
lowered dispersal, fire, grazing or harvesting techniques (Ticktin,
2004). However, seedling abundance may have little effect on
overall population dynamics for long-lived trees (Brodie et al.,
2009; Pfister, 1998). Either detailed population models or very
long-term monitoring is required to determine whether reduced
seedling abundance will translate into lower adult tree density.
Fruit and seed harvests reduce food supplies for frugivore populations. The limited available evidence suggests that frugivore
populations can decline and frugivore communities may be altered
by fruit harvests (Galetti and Aleixo, 1998; Moegenberg and Levey,
2003). Harvesting of palm fruits in Amazonia and the Atlantic forests of Brazil has reduced the abundance and species richness of
avian frugivores (Moegenberg and Levey, 2003) and frugivores altered their diets when palms were removed (Galetti and Aleixo,
1998). The likelihood of resource redundancy within the diets of
frugivores, however, or the conditions under which it may occur,
is virtually unknown. Wide-ranging species that are able to track
resources are probably less susceptible to harvesting than those
with a more restricted range (Rey, 1995), unless the harvested species fruits during periods of low community-level fruit availability
(Kinnaird, 1992). In less-diverse habitats, fruit may be a limiting
factor for breeding or frugivore survival (Bronstein et al., 2007),
and harvesting-induced reductions in fruit supplies could severely
impact frugivore populations. In contrast, exotic plant species
that are planted in rural and urban landscapes for fruit harvests,
can lead to increased fruit availability for native frugivores
(McDonald-Madden et al., 2005) and altered fruit–frugivore interactions (Galetti et al., 2010; Nelson et al., 2000).
Harvesting of non-fruit plant products is also widespread and
may impact fruit supply and frugivores. Commercial logging can
reduce fruit abundance either through direct targeting of fruitproducing species for extraction (Potts, 2011) or indirect removal
of critical food resources such as strangler figs (Shanahan et al.,
2001) that tend to grow on commercial timber trees of harvestable
size (Lambert and Marshall, 1991), and thus may significantly reduce dietary diversity of important seed dispersers (Felton et al.,
2010). Small-scale extraction of large trees reduces the number
of cavities available for nesting for some avian frugivore species
(Cockle et al., 2010). At most sites, the dependence of frugivore
species on harvested tree species is poorly understood.
Long-term studies are needed to address the impacts of plant
harvests on the abundance and structure of resource populations
and frugivore communities. The consequences of harvests on the
spatial patterns of resource populations remain largely unknown,
despite having potentially critical impacts on frugivore movements. Spatial patterns of fruit availability determine which individual plants frugivores choose to feed from, as well as their
movement patterns and consequent dispersal (Carlo and Morales,
5
2008). Changes in spatial patterns of fruit availability have the potential to influence such dynamics across all diet species, yet are
entirely unstudied with respect to resource harvesting.
3.3. Biological invasions
Invasive species can alter native dispersal mutualistic networks
directly, through the establishment of novel seed dispersal interactions with the native biota; or indirectly, by influencing the abundance, distribution or behavior of native species. From a
conservation viewpoint, the outcome of these interactions is often
negative (e.g. enhancing plant invasion) although positive outcomes may also occur (e.g. enhancing dispersal of native species)
and are largely understudied (Schlaepfer et al., 2011). The impact
of invasive species in pollination networks are increasingly documented and indicate an overall erosion of connectivity amongst
native species (Aizen et al., 2008). Similar analyses would be beneficial in identifying the impact of invasive species in seed dispersal networks (Gleditsch and Carlo, 2011).
Direct interactions have been well documented, reflecting their
increasing frequency, and researchers are now attempting to provide a more generalized framework highlighting the conditions
under which alien species can become established in fruit–frugivore networks (Moran et al., 2004). It is important that such
frameworks be developed in more regions and in a greater variety
of habitats. Alien plant species often co-opt the services of native
dispersers, while alien frugivores make use of the resources provided by native plant species. The establishment of these direct
interactions between alien and native species can occur in four
ways:
(a) Native frugivores dispersing alien plant species: this can be a
major determinant for the establishment and spread of an
alien plant (Buckley et al., 2006; Gosper et al., 2005; Aslan,
2011; Gleditsch and Carlo, 2011). Frugivore movements
often have a direct effect on the dispersal patterns and success of the alien plant species (Wilson et al., 2009), creating
conservation conflicts in invasive control (Gleditsch and
Carlo, 2011), particularly when the native disperser is an
endangered species (Campos-Arceiz and Blake, in press;
Westcott et al., 2008). Invasiveness may be further facilitated by increased investment by the plant in seed dispersal
structures regardless of the dispersal mode (wind or animal
dispersed) (Murray and Phillips, 2010).
(b) Alien frugivores dispersing native plant species: the introduction of alien dispersers can be beneficial if they complement
the dispersal service provided by native dispersers or restore
dispersal services that were lost when a native disperser
became extinct (Hansen et al., 2010). However, it may have
negative effects for the plant if alien dispersers consume
fruits that would be otherwise available to more efficient,
native dispersers (Castro et al., 2008).
(c) Alien frugivores dispersing alien plants: alien plants can be
dispersed by previously-established alien dispersers, and
such interactions may be one of the triggers of invasion
meltdown processes that facilitate the entrance of new alien
species in a self-accelerating way (Simberloff and Von Holle,
1999; Green et al., 2011). Positive feedbacks between alien
dispersers and plants include the dispersal of alien plants
by introduced wild (Constible et al., 2005) or domestic
(Campbell and Gibson, 2001) herbivores and alien frugivorous birds (Mandon-Dalger et al., 2004).
(d) Native and alien animals dispersing native and alien plants: the
establishment of novel seed dispersal mutualisms between
alien and native biota often takes place in a multi-species context. These complex, yet probably very common, scenarios are
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
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characterized by seed-dispersal networks that include both
native and alien plants and dispersers (e.g. Davis et al.,
2010; Lopez-Darias and Nogales, 2008).
Alien species can also alter seed dispersal networks indirectly
by influencing the abundance, distribution or behavior of species
from the native dispersal network (Traveset and Richardson,
2006). Indirect interactions between alien and native species remain poorly understood for most animals and plants, with the
exception of alien ants. Argentine ants (Linepithema humile) can severely reduce native ant communities. Seed dispersal by these
alien ants is often less effective, with decreases in seed removal
rates and distances (Christian, 2001; Gómez and Oliveras, 2003)
or they may preferentially disperse alien plant species (Rowles
and O’Dowd, 2009). Invasive ants can also alter the behavior of vertebrate dispersers: for example, endemic frugivores from islands
have been documented avoiding plants occupied by aggressive
invasive ants (Davis et al., 2010; Hansen and Muller, 2009).
The introduction and expansion of alien vertebrates (such as
rats, cats, snakes, and mustelids) that are predators of native frugivores has been regularly documented (particularly for oceanic islands, Courchamp et al., 2003), but reports of effects on the
native flora triggered by the loss of native dispersers are confined
mainly to anecdotal evidence and occasional observation (Traveset
and Richardson, 2006), despite having potentially devastating consequences for seed dispersal mutualisms (Rodríguez-Pérez and
Traveset, 2009). Alien plants in a disperser-limited habitat could
also disrupt native mutualisms by ‘‘stealing’’ dispersers from native plants, but they could also enhance the consumption of native
fruits situated in the immediate neighborhood (Gleditsch and
Carlo, 2011; Neilan et al., 2006), or they could have a neutral effect
(Gosper et al., 2006). Finally, alien animal species are frequently
both seed dispersers and seed predators, changing the dispersal
dynamics of plant species across multiple recruitment stages
(Wotton and Kelly, 2011).
3.4. Climate change
Predicting changes in plant distributions, community composition, and ecosystem function in response to climate change is a key
priority in current ecological research, since these responses could
have a large impact on the future of both biodiversity and carbon
storage (Purves and Pacala, 2008), but the relevance of dispersal
biology to these predictions has often been ignored. A metaanalysis of species range shifts associated with warming over
recent decades estimated that the geographical ranges of species
had moved to higher latitudes at a median rate of 16.9 km per
decade, which matches expectations if species are tracking
recorded changes in temperature (Chen et al., 2011). No land
plants were included in this study, but unless plants are less sensitive to warming, they would need to move a similar distance to
keep up with the movement of thermal isotherms. This median
is large in comparison with most known dispersal capabilities for
plants (Vittoz and Engler, 2007; Aitken et al., 2008; Corlett,
2009), suggesting that seed dispersal may limit the ability of plants
to respond to climate change, even without an expected acceleration of warming (IPCC, 2007). As a result, both species losses from
communities and immigration to communities may lag behind
climate change, leading to both extinction debts and ‘immigration
credits’ (Jackson and Sax, 2010).
The data on which these estimates of latitudinal range shifts
were based is all from the temperate zone: in the tropics latitudinal temperature gradients are almost flat, so poleward migration
does not provide an escape route from rising temperatures. However, altitudinal temperature gradients in the tropics are similar
to those in the temperate zone. A global meta-analysis of altitudi-
nal range shifts found a median rate of 11.0 m increase in altitude
per decade (16.0 m for the seven plant studies included), in contrast to the 50 m per decade needed to track rising temperatures
(Chen et al., 2011). This lag in elevational response was unexpected, given the relatively short distances involved, but may
partly reflect the topographic and microclimatic complexity of
montane landscapes. In steep topography, these observed and expected vertical rates translate into horizontal movements 2–5 as
great, which are within the dispersal capabilities of many species,
suggesting that altitudinal escape, where available, is more likely
than latitudinal escape.
Most studies predicting plant distribution under changing climates use the ‘climate envelope’ approach, which couples information on current species distributions in relation to climate with
future climate scenarios, ignoring the complexity of the processes
involved when vegetation changes. In particular, they do not take
into account the ability of plant species to migrate over the distances required in the time available, or the impact of habitat fragmentation on this ability (Corlett, 2009); they predict potentially
suitable habitat for plant species rather than the potentially
colonizable habitat (Engler and Guisan, 2009). Incorporating seed
dispersal distances into predictive models will be particularly difficult in species-rich vegetation where seed dispersal distances
can vary over four or five orders of magnitude between plant-vector combinations (Vittoz and Engler, 2007; Corlett, 2009). In the
commonly used grid-based models, for example, a high resolution
(fine-grained) model is needed to incorporate short-distance dispersal (e.g. by ants or rodents) within habitat patches, while a
low resolution (coarse-grained) model is needed to incorporate
the influence of long-distance dispersal (e.g. by elephants or fruit
pigeons) in broad-scale, spatially heterogeneous landscapes.
Climate change may also affect the dispersal capabilities of
plants. Wind-dispersal will be impacted directly by changes in
wind speeds, particularly the frequency of extreme winds (Soons
et al., 2005; Nathan et al., 2011), and in some cases may be affected
by changes in plant morphology (Zhang et al., 2011). Plant responses relevant to seed dispersal by animals would include
changes in fruit quantity and quality, and in the phenology of its
production. Outside the lowland tropics, warming may lift temperature constraints, leading initially to increased fruit production and
earlier fruiting in spring-flowering species (Gordo and Sanz, 2010).
In tropical lowland rainforests, annual tree growth increments decline significantly with small increases in temperature or decreases
in rainfall (Clark et al., 2010), but the sensitivity of plant reproductive phenology is unknown. Relevant animal responses would include range shifts, and changes in the phenology of breeding
(and thus the seasonal pattern of dietary needs) and migration,
all of which have been widely reported in birds (Jones and
Cresswell, 2010), while range shifts have been reported for mammals (Chen et al., 2011). Range shifts may be a problem when dispersal agents track temperature changes, while plants lag behind.
Phenological changes will be most important if they lead to a mismatch in the timing of fruit production and frugivore presence at a
location (Gordo and Sanz, 2010; Jones and Cresswell, 2010).
3.5. Interactions between drivers of biodiversity change
There is widespread concern that different drivers of global biodiversity change will act synergistically to compound threats to
ecosystem functioning (Brook et al., 2008). However, few studies
have attempted to determine the nature (synergistic, additive or
antagonistic) or quantify the strength of interactions between drivers (Schweiger et al., 2010). Given that multiple drivers frequently
threaten fruit–frugivore interactions this is a priority area for future research. Invasive species, for example, can more easily invade
disturbed systems than those with an intact fauna and flora (King
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K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
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Table 1
Potential outcomes of two-way interactions between drivers of global biodiversity change on seed dispersal. Outcomes are noted as to whether they are additive, antagonistic or
synergistic. Research that supports the interaction effects are referenced: ⁄ indicates this has been observed for other ecological interactions and may be relevant to seed dispersal.
Drivers of biodiversity
change
Interactions
Type
Potential interaction pathways
Biological invasion
Synergistic
Additive
Synergistic
Frugivore loss
Fruit harvesting
Synergistic
Antagonistic
CC alters phenology and frugivores may be unable to track changes due to FR (⁄Tylianakis et al., 2008; Hegland et al., 2009)
Altered wind patterns and frugivore movement between fragments (Damschen et al., 2008; Prevedello and Vieira, 2010)
CC gives advantage to BI phenology and crop outputs, and can increase establishment or distribution of invasive plants
(Crossman et al., 2011) and animals (Hellman et al., 2008); Morphology of invasive plants can adapt rapidly to CC, improving
dispersal capabilities (Zhang et al., 2011)
Plant species dependent on large-bodied frugivores unable to disperse to suitable habitats under CC (⁄Corlett, 2009)
CC alters fruit abundance (Gordo and Sanz, 2010) which may make FH unviable
Climate change (CC) Fragmentation
Fragmentation (FR) Biological invasion
Frugivore loss
Synergistic
Antagonistic
Synergistic
Fruit harvesting
Synergistic
Biological invasion (BI) Frugivore loss
Synergistic
Fruit harvesting
Antagonistic
Synergistic
Additive
Frugivore loss (FL) Fruit harvesting
Additive
FR makes conditions more suitable for BI, which disrupt native dispersal networks (Chimera and Drake, 2010)
FR may slow spread of BI when long distance dispersal is rare (Alofs and Fowler, 2010)
FR increases access for hunters (Kupfer et al., 2006); large-bodied frugivores decline more in smaller FR, resulting in reduced
dispersal of large-seeded plant species (Wotton and Kelly, 2011)
FR increases access for harvesters (Kupfer et al., 2006), who prefer large fruit (S. Prasad, pers. obs)
BI more likely due to reduced competition following FL (⁄Chapin et al., 2000); Invasive seed predators target undispersed seeds
accumulated under parent plants (Wotton and Kelly, 2011)
Invasive animal species replace native animals targeted for hunting (Desbiez et al., 2011)
Invasion by alien plants more likely due to reduced seed rain of native species (⁄Chapin et al., 2000); Invasive plant species may
impede regeneration of harvested species (Ticktin et al., 2006; Rist et al., 2010)
Invasive plant species may reduce fruit production (Setty et al., 2008)
Plant species dispersed by large-bodied frugivores are often key forest produce subject to intensive harvests (Rai, 2004,
S. Prasad, pers. obs)
and Tschinkel, 2006) and the effects on seed dispersal interactions
may be compounding (Wotton and Kelly, 2011). Fragmentation
may also act synergistically with other drivers (Table 1), placing increased stress on fruit–frugivore interactions. Intensification of human use is usually associated with increased levels of animal and
plant harvesting, providing more opportunities for invasive species
to enter ecosystems. Perhaps the most significant potentially synergistic interaction involves climate change, since it may compound the effect of all other drivers of global change.
4. Incorporating seed dispersal knowledge into conservation
management
Knowledge of seed dispersal processes in human-modified
landscapes can be applied in order to slow-down habitat degradation and biodiversity decline, accelerate the recovery of degraded
areas, manage biological invasions and facilitate the adaptation
of plants and animals to climate change. A functional understanding of the seed dispersal vectors within a community can provide
an invaluable tool for addressing a range of conservation problems
– from deciding where to direct eradication methods for a biological invasion, to determining which frugivores are critical for ecosystem maintenance and safeguarding their abundance and
mobility across landscapes. Knowledge of fruit–frugivore relationships will expose gaps in the dispersal system where active management, such as re-introduction of an animal, is required for
ecosystem maintenance.
4.1. Habitat fragmentation
Understanding of dispersal interactions in a system can aid conservation managers tasked with mitigating the effects of fragmentation and restoring degraded lands. Because plant recruitment in
fragmented and degraded landscapes is often dispersal-limited
(Cordeiro et al., 2009; Herrera and Garcia, 2010; Lehouck et al.,
2009), the key actions required must increase dispersal of desirable
plant species (Appendix A). Facilitating seed movement across
fragmented landscapes or into degraded areas can accelerate ecosystem recovery and can reduce the costs of conservation efforts
addressing these concerns.
In fragmented landscapes, the preservation or creation of
habitat corridors is probably the best way to enhance landscape
connectivity for plants and their dispersal agents, particularly for
dispersers that are habitat-specialists or have low mobility
(Gilbert-Norton et al., 2010; Levey et al., 2005). However, corridor
creation often involves huge economic and social costs (Naidoo
and Ricketts, 2006) and less expensive options, such as stepping
stones created by live fences, remnant trees, windbreaks may be
adequate to enable movement of more mobile species (Estrada
and Coates-Estrada, 2001; Galindo-González et al., 2000; GilbertNorton et al., 2010; Pizo and Dos Santos, 2010). Remnant trees
and live fences also act as foci for seed rain into the matrix and
degraded areas (since they provide perching and roosting sites)
and may provide suitable conditions for seedling establishment
(Verdu and Garcia-Fayos, 1996; Pausas et al., 2006; Méndez
et al., 2008; Herrera and Garcia, 2009), thereby creating a feasible,
low-cost option for large-scale forest restoration in fallows and
pastures (Martínez-Garza and Howe, 2003; Rodrigues et al.,
2009). Perches and isolated trees could serve as ‘‘catchment areas’’
for seeds for restoration projects and reduce costs involved in seed
collection. However, small-seeded wind and bird-dispersed species
frequently dominate recruitment in areas where these strategies
have been implemented (Martınez-Garza et al., 2009; Cole et al.,
2010) and active management may be required for large-seeded
species.
Active introduction of keystone or generalist plant species
(which attract a wide range of dispersal agents) into the matrix
or degraded areas can accelerate recovery of degraded regions
(Martínez-Garza and Howe, 2003; Sansevero et al., 2011). Network
theory could aid the identification of keystone plant species which
act as hubs or connectors in seed dispersal systems (Donatti et al.,
2011; Mello et al., 2011b). Plant species that fruit during periods of
food scarcity, such as figs, are also important targets for active
planting (Lambert and Marshall, 1991). The diversity and quantity
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of seed dispersal into restoration sites could also be accelerated by
innovative techniques such as the use of essential oils from fruits
to attract frugivorous bats (Bianconi et al., 2007) or the deployment of artificial roosts (Kelm et al., 2008).
Restoration efforts should prioritize dispersal-limited plant species which may fail to arrive on their own. A functional classification of dispersal interactions within a community (Dennis and
Westcott, 2006) can help identify such dispersal limited plant species. In the absence of information on community-wide fruit–frugivore relationships, late-successional or deep-forest species should
be prioritized for restoration planting as a precautionary measure.
Introducing these species before they would arrive on their own
could attract vertebrate dispersal agents that can accelerate seed
movement into or across these regions (Martínez-Garza and Howe,
2003).
Habitat restoration could also be accelerated by protecting,
attracting, restoring or re-introducing frugivore populations
(Appendix A), given that the quantity of animal-dispersed seeds
is positively linked to frugivore abundance (Garcia et al., 2010).
Particularly important are frugivore groups with large gape size
and high mobility, thereby playing a disproportionate role in the
establishment of plant populations across breaks in habitat continuity (e.g., large fruit pigeons from Madagascar through Asia and
the Pacific, e.g. Dew and Wright, 1998; Oliveira et al., 2002; Corlett,
2009; frugivorous bats in tropical forests, e.g. Muscarella and
Fleming, 2007; Corlett, 2009; toucans in South America, Holbrook,
2011; hornbills in Africa and Asia, e.g. Lenz et al., 2010; thrushes in
Europe and the Americas, e.g. Jordano, 1993). Such key frugivore
species are often hunted, and might exist below functional densities required to maintain dispersal interactions. Because these frugivores are usually wide-ranging they have rarely been assigned
international or national protection status. Conservation priorities
need to reflect ecological function as well as the global risk of
extinction, and these large, mobile frugivores can provide key links
in fragmented systems.
Incorporating an understanding of seed dispersal of target plant
species into spatial planning of restoration efforts can provide useful insights (van Loon et al., 2011), such as identification of areas of
with high seed rain (which could be protected from livestock grazing and other threats to seedling recruitment) and areas with limited dispersal where seeds need to be actively introduced.
4.2. Overharvesting
4.2.1. Frugivores
An understanding of seed dispersal processes within communities can enable conservation managers to identify those species
that are disproportionately important for habitat maintenance.
The use of network analyses can aid identification of frugivores
that are most important (hubs and connectors) for maintaining
the structure of seed dispersal networks. Recent network studies
indicate that large frugivores, which consume a diverse range of
fruit, are frequently the strongest interactors (Donatti et al.,
2011; Mello et al., 2011a,b). In the absence of community-wide
information on fruit–frugivore interactions, large-bodied, largegaped, and wide ranging frugivorous taxa should be targeted for
conservation since these animals frequently have a disproportionate impact on ecosystem functioning (Fritz and Purvis, 2010;
Campos-Arceiz and Blake, in press).
Instead of focusing solely on their extinction risk, species prioritization for conservation action needs to reflect ecological function, and population levels for prioritized species must be
maintained at levels which can conserve their ecological function
(particularly given the risk of non-linear thresholds leading to
the cessation of ecological functioning at intermediate abundances; e.g., McConkey and Drake, 2006) (Appendix A). As our
knowledge of links between population abundance and ecological
function increases, we should seek ways to predict sustainable
population densities from ecological indicators, which can be cost
and time effective (e.g., predicting appropriate densities of large
frugivores from seedling densities of large fruited plants).
In areas where functionally important seed dispersers have become extinct, we may need to re-introduce the species from other
regions. In situations where species have become globally extinct,
alternative frugivore species have been introduced as ‘‘surrogatedispersers’’ (e.g., tortoises in Mauritius; Hansen et al., 2010). However, such approaches need to be considered judiciously because
introduced animals may provide much less effective dispersal than
their native counterparts, may aid the dispersal of invasive plants,
or may themselves become invasive (Christian, 2001; Hansen et al.,
2010). Surrogates from the local or regional fauna are likely to be
the best candidates for introduction and they could be identified
by considering functional roles at the community level.
4.2.2. Plants
Harvest levels for fruits collected by humans should be re-evaluated to ensure harvesting does not negatively impact frugivore
abundance and seed dispersal patterns (Appendix A). There are
three main scenarios in which fruit harvests could have critical
consequences for dispersal function: regions with a low diversity
of plants producing fruit, harvested species that fruit during overall
low periods of community-wide fruit availability and species that
may offer potentially keystone resources for frugivores. In these
situations, we need to find ways of ensuring that critical fruit resources are not driven to extinction by actively involving local
stake holders to develop sustainable harvest practices (e.g., regulating harvest levels, improving harvesting techniques and setting
aside populations free from harvests; Ticktin, 2004).
4.3. Biological invasions
Targeted programmes for the control of some invasive species
can be developed from a functional understanding of community-wide frugivore-plant interactions (Appendix A). This knowledge can be used to facilitate predictions on which plants or
animals are most likely to establish within an ecosystem, which
vectors will promote the spread of the species (e.g., potential seed
dispersers for invasive plants, and food sources for invasive frugivores) and where the species is likely to spread to (using dispersal
kernels based on dispersal vectors) (Gosper et al., 2005; Buckley
et al., 2006; Murphy et al., 2008; Gosper and Vivian-Smith,
2009). Most efforts to integrate seed dispersal research into invasive species management have taken place in Australia (Murphy
et al., 2008; Westcott et al., 2008; Gosper and Vivian-Smith,
2009), although invasive species are a widespread global concern.
In some cases invasive plants and animals become integrated
into native dispersal networks, and their role in these networks
may balance or even surpass their detrimental effects on native
biota. In regions that have lost most native dispersers, invasive frugivores are frequently the main seed dispersal agents of native
plants (Chimera and Drake, 2010). Widespread invasive plants
are often integral parts of native frugivore diets, and removing
these might have negative effects on native frugivore populations,
unless replaced by functionally-similar native plants (Gosper and
Vivian-Smith, 2009). It is therefore important that invasive species
control is prioritized, according to the impacts (positive, neutral or
negative) the invasive species has on ecosystem functioning; and
that their potential, negative side effects are anticipated and corrected for (e.g. by introducing native fruiting plants or frugivores)
during the control or eradication efforts.
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K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
4.4. Facilitating adaptation to climate change
We need to explicitly incorporate seed dispersal patterns into
models predicting vegetation responses to global climate change.
These models are needed for developing more robust predictions
of future carbon stocks and thus carbon-cycle feedbacks to the climate system. They could also help managers mitigate impacts of
climate change by identifying critical vector species, dispersal corridors or keystone sites that facilitate plant migration (Williams
et al., 2005) and develop better assisted migration programs for
species that may require long-distance translocations (HoeghGuldberg et al., 2010; Vitt et al., 2010).
Policy makers and resource managers will have to consider
proactive measures that are robust to the range of plausible climate scenarios in anticipation of changes that will occur decades
in the future (Heller and Zavaleta, 2009; Appendix A). The speed
of movement needed to track predicted temperature changes in
the 21st century has a global mean of 1.69 km a year or 169 km
per century (Chen et al., 2011), which is beyond the capacity of
most long-lived woody plants as well as many plants of other
life forms (Corlett, 2009; Nathan et al., 2011). Much faster movements will be required in the lowland tropics, where the temperature gradient is almost flat. In these cases, assisted
migration may be the only option (Hoegh-Guldberg et al.,
2010; Vitt et al., 2010). However, many protected areas are
established in rugged topography, where steep temperature
and rainfall gradients mean that cool and/or moist refuges may
exist within potential natural dispersal distances (which are typically 100s to 1000s of metres per generation). In such landscapes, a key strategy to facilitate seed movement is to
strengthen landscape connectivity (using approaches outlined
above) across temperature and rainfall gradients (Appendix A).
Managers can utilize knowledge of seed dispersal vectors to mimic, assist or enable species movement across gradients, thereby
allowing species to naturally rearrange their distributions as required by climate change (Millar et al., 2007).
Given the overlap of ecological, economic and social concerns
that are promoting the planting of trees at large scales (under
the Kyoto Clean Development Mechanism, REDD), multi-purpose
plantations that address biodiversity concerns, augment local
economies and sequester carbon need to be designed and implemented (Paquette and Messier, 2010). Incorporating an understanding of seed dispersal (Appendix A) into the design of such
large scale reforestation projects can aid in promoting ecological
function in these plantations, and may also accelerate the pace of
carbon sequestration (Jansen et al., 2010). This calls for active collaborations between dispersal ecologists, foresters and resource
managers.
5. Conclusions
The natural history of seed dispersal is now well-described in
a range of landscapes worldwide (e.g., South Africa, Farwig et al.,
2006; Lenz et al., 2010; Australia, Dennis and Westcott, 2006;
Brazil; Almeida-Neto et al., 2008; Donatti et al., 2011; Thailand,
Kitamura et al., 2002; Hong Kong, South China; Corlett, 2011;
Spain, Herrera and Garcia, 2010; Jordano et al., 2007). As will
be apparent from this review, however, the idiosyncrasies of
the plant and animal species involved have, at least so far, precluded many robust generalizations that can be usefully applied
for conservation management. Our recommendations for conservation management are therefore, at best, rules of thumb that
will need to be supplemented by local natural history information. Fortunately, such information is often available, at least
for large and charismatic species. Even where it is not, an aware-
ness of seed dispersal and its limitations will almost always lead
to better conservation management than the alternatives of
assuming either that plants are immobile or that they are dispersed everywhere. The needs of conservation managers should
also inspire better and more relevant ecological research. Seed
dispersal ecologists need to expand their field of view in order
to study how seeds move—or fail to move—across real (fragmented, heterogeneous) landscapes on the scales (kilometers)
that matter for the long-term survival of plant and animal diversity in a changing world.
Acknowledgements
We thank Chanpen Wongsriphuek and Andres Link for discussions and comments on the manuscript. We thank the organizers
of the 23rd Annual Meeting of the Society of Conservation Biology
at Beijing, China, where these ideas were first discussed. We also
thank three anonymous reviewers for their valuable comments
on the manuscript.
Appendix A
Incorporating seed dispersal into conservation management for
each driver of biodiversity change.
Conservation action Recommendations
Habitat fragmentation
Enhance
connectivity
Conservation
priorities
Restoration of
degraded lands
a) Linking corridors to facilitate
movement of dispersal vectors
and seeds (Levey et al., 2005; Gilbert-Norton et al., 2010)
b) Where corridors are not feasible,
maintain or create stepping-stones
(Estrada and Coates-Estrada, 2001;
Galindo-González et al., 2000; Gilbert-Norton et al., 2010; Pizo and
Dos Santos, 2010).
c) Introduce plant species that play
important functional roles in seed
dispersal networks (e.g., keystone
and generalist plant species)
(Mello et al., 2011a).
Protect wide-ranging frugivores that can
move across fragmented landscapes
a) Accelerate succession by stimulating visits by frugivores
b) Prioritize dispersal-limited plant
species and generalist plant species
for restoration (Martínez-Garza
and Howe, 2003).
c) Protect sites with a potentially high
density of seed rain (identified
using dispersal kernels) from livestock grazing
Overharvesting of animals
Conservation
a) Prioritize conservation of animals
priorities
providing unique dispersal services,
especially long-range dispersers
b) Identify minimum threshold densities for key dispersers, below which
their ecological function declines
(continued on next page)
Please cite this article in press as: McConkey, K.R., et al. Seed dispersal in changing landscapes. Biol. Conserv. (2011), doi:10.1016/j.biocon.2011.09.018
10
K.R. McConkey et al. / Biological Conservation xxx (2011) xxx–xxx
Appendix A (continued)
Conservation action Recommendations
Frugivore
reintroductions
a) Re-introduce frugivores that have
gone locally extinct, especially
those which are functionally unique
b) Consider introduction of functionally-similar frugivore species when
the frugivore species has become
globally extinct (Hansen et al., 2010)
Overharvesting of plants
Harvest policies
a) Re-evaluate harvest levels in which
frugivore populations may be
affected (e.g., in low-diverse regions
and or for key stone fruit resources)
(Galetti and Aleixo, 1998).
b) Adopt better harvesting techniques
and set-aside source populations to
ensure maintenance of dispersal
function (Ticktin, 2004)
Biological invasions
Eradication
Design eradication programs using seed
dispersal kernals to identify sites of
potential infection sites of invasive plants
(Murphy et al., 2008)
Identification
Screen fruit traits of introduced plants to
assess their potential for invasiveness
(Buckley et al., 2006)
Replacement
Screen fruit traits to identify native plants
that can replace widespread invasive
species (Gosper and Vivian-Smith, 2009)
Climate change
Enhance landscape Follow recommendations given above to
connectivity
improve connectivity across temperature
and rainfall gradients within fragmented
landscapes to enable movement of plant
dispersal vectors
Halt frugivore
Follow recommendations given above to
declines
ensure functional densities, especially for
key frugivores providing unique dispersal
services
Afforestation
Incorporate understanding of seed
policies
dispersal processes in ongoing large-scale
afforestation programs
(a) choice of species - prioritize dispersal-limited plant species and
late-successional plant species
(b) choice of sites - strengthen corridors and connectivities across temperature and rainfall gradients
Assisted migration When migration capacity is exceeded,
introduce species into potentially
suitable habitats
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Oikos 119: 514–523, 2010
doi: 10.1111/j.1600-0706.2009.17971.x,
© 2009 The Authors. Journal compilation © 2010 Oikos
Subject Editor: Jordi Bascompte. Accepted 4 September 2009
Context-dependency of a complex fruit–frugivore mutualism:
temporal variation in crop size and neighborhood effects
Soumya Prasad and R. Sukumar
S. Prasad and R. Sukumar ([email protected]), Centre for Ecological Sciences, Indian Inst. of Science, Bangalore 560012, India.
The quantity of fruit consumed by dispersers is highly variable among individuals within plant populations. The outcome
of such selection operated by frugivores has been examined mostly with respect to changing spatial contexts. The influence
of varying temporal contexts on frugivore choice, and their possible demographic and evolutionary consequences is poorly
understood. We examined if temporal variation in fruit availability across a hierarchy of nested temporal levels (interannual, intraseasonal, 120 h, 24 h) altered frugivore choice for a complex seed dispersal system in dry tropical forests of
southern India. The interactions between Phyllanthus emblica and its primary disperser (ruminants) was mediated by
another frugivore (a primate), which made large quantities of fruit available on the ground to ruminants. The direction and
strength of crop size and neighborhood effects on this interaction varied with changing temporal contexts. Fruit availability
was higher in the first of the two study years, and at the start of the season in both years. Fruit persistence on trees, determined by primate foraging, was influenced by crop size and conspecific neighborhood densities only in the high fruit
availability year. Fruit removal by ruminants was influenced by crop size in both years and neighborhood densities only in
the high availability year. In both years, these effects were stronger at the start of the season. Intraseasonal reduction in fruit
availability diminished inequalities in fruit removal by ruminants and the influence of crop size and fruiting neighborhoods. All trees were not equally attractive to frugivores in a P. emblica population at all points of time. Temporal asymmetry in frugivore-mediated selection could reduce potential for co-evolution between frugivores and plants by diluting
selective pressures. Inter-dependencies formed between disparate animal consumers can add additional levels of complexity
to plant–frugivore mutualistic networks and have potential reproductive consequences for specific individuals within
populations.
Fruit consumption by animals influences the spatial and
genetic structure of plant populations through the movement of seeds to locations away from parent plants, where
chances of survival and establishment may be higher (Nathan
and Muller-Landau 2000, Howe and Mirti 2004, Jordano
et al. 2007). The quantity of fruit consumed by animals from
individual plants is highly variable and asymmetric within
plant populations (Ortiz-Pulido and Rico-Gray 2000, Carlo
2005). The influence of such frugivore-mediated selection
on plant demography has been shown to be dependent on
the spatial patterning of fruiting resources within plant populations and landscapes (Morales and Carlo 2006, Carlo and
Morales 2008).
Two sources of spatial heterogeneity at local scales, crop
size and fruiting neighborhood densities, are the most commonly reported causes of variation in fruit removal across
dispersal systems and sites (Sargent 1990, Carlo et al. 2007,
Ortiz-Pulido et al. 2007). Frugivores are generally attracted
to trees that bear larger fruit crops (reviewed by Sargent
1990, Ortiz-Pulido et al. 2007). Plants with higher densities
of conspecific or heterospecific co-fruiting neighbors can
have higher or lower fruit removal depending on whether
there is facilitation or competition between fruiting neighbors for frugivores (reviewed by Carlo et al. 2007). Positive or
514
negative interactions between fruiting neighbors are known
to be dependent on spatial contexts such as differences in
frugivore abundance, behavior and habitat use in space (from
local to regional scales) and landscape-level aggregation of
fruiting resources (Morales and Carlo 2006, Blendinger et al.
2008, Carlo and Morales 2008). Fruit availability and frugivore abundance exhibit enormous variation in time too,
both within and across seasons, given the temporal fluctuations in ecological and climatic factors that influence them
(Herrera 1988, Jordano 1994, Herrera et al. 1998, Levey
1998, Wright et al. 1999). While we have a limited understanding of the influence of such changing temporal contexts
on crop size effects on fruit removal (Ortiz-Pulido and RicoGray 2000, Osada 2005, Forget and Jansen 2007, Hampe
2008), there have been no studies that have examined the
temporal context-dependency of neighborhood effects.
Most polycarpic woody plant populations exhibit bimodality in fruit production with alternating high and low fruit
years (Herrera et al. 1998) as well as considerable intraseasonal variation (Herrera 1988, Osada 2005, Hampe
2008). At local scales, when fruit are super abundant in certain years or at certain times in the season, frugivore satiation
could result in greater competition between fruiting trees for
frugivores. Under such conditions of fruit abundance,
frugivore choice could be structured by crop size and fruiting neighborhoods of individual trees. Compared to this,
when fruit are scarce within a population, fruit might be
removed from all trees, irrespective of crop size or neighborhood densities (Ortiz-Pulido and Rico-Gray 2000, Osada
2005, Forget and Jansen 2007, Hampe 2008). In addition,
the range of crop sizes or degree of aggregation of fruiting
neighbors may vary temporally. Hence, at the population
level the direction and strength of frugivore-mediated selection may not be constant across years or even within the
same season. Such temporal fluctuations could alter demographic and evolutionary consequences of frugivore-mediated selection (Carlo et al. 2007).
In this study, we examine factors influencing fruit removal
across a hierarchy of nested temporal levels (interannual,
intraseasonal, 120 h, 24 h) for a ruminant-dispersed tree,
Phyllanthus emblica in the dry tropical forests of southern
India. Though several authors have recognized that plants
and their primary dispersers interact with several other species (Carlo et al. 2007, Dennis and Westcott 2007), such
complexities have not been considered while studying frugivore choice. Our study system illustrates some of the complexities and interdependencies in fruit–frugivore mutualistic
networks (Carlo et al. 2007), where the plant–plant links
formed by movement of the primary disperser (ruminants) is
mediated by another frugivore (a primate), which makes
large quantities of fruit available on the ground to the primary disperser. We examine the influence of two plant attributes (crop size, fruiting neighborhoods) on different levels
within this interaction and across temporal gradients of fruit
availability in order to understand specific reproductive consequences for individuals.
Our main objectives were:
1) to examine if crop size influenced fruit persistence on
P. emblica trees and fruit removal by ruminants.
2) to understand the nature of interactions between fruiting conspecific neighbors within a P. emblica population and
its influence on fruit persistence and fruit removal by ruminants
3) to examine if temporal variation in fruit availability
(both across years and within seasons) influenced the effect
of crop size and neighborhood densities on fruit persistence
and fruit removal in a context-dependent manner.
Material and methods
Study system
Phyllanthus emblica (Euphorbiaceae, syn. Emblica officinalis)
is a medium-sized tree (10–15 m), common in South Asia’s
dry tropical forests. For species like P. emblica whose fruit are
harvested extensively by people, understanding frugivore
choice is important to develop ecologically sustainable
practices of harvest (Shahabuddin and Prasad 2004). From
October through March, P. emblica trees bear globose, greenish-yellow, drupaceous fruit (fruit length: 20–30 mm; endocarp 9–10 mm; seeds: 5–6 mm). There is considerable
interannual variation in fruit productivity of P. emblica populations, with alternating high and low years (Sinha and
Bawa 2002). Among the arboreal frugivores of P. emblica’s,
giant squirrels Ratufa indica mostly predate seeds, while the
colobine monkey Hanuman langur Semnopithecus entellus is
largely neutral with respect to seed dispersal function. Langurs feed on pulp and drop remaining fruit (with seeds)
under canopy of parent trees. Langurs also bring down vast
quantities of fruit passively, while moving and foraging on
trees. Over 95% of the fallen fruit are consumed by ruminants (chital Axis axis, barking deer Muntiacus muntjak,
mouse deer Moschiola meminna), while murid rodents
remove fruit on rare occasions (Prasad et al. 2004, 2010).
Ruminants, which are primary dispersers of P. emblica, swallow fruit whole and regurgitate viable seeds (enclosed in hard
endocarp) after retaining them in the rumen for 7–27 h
(Prasad et al. 2006).
Study site
Mudumalai (321 km2, 11°32⬘–11°43⬘N, 76°22⬘–76°45⬘E)
is part of a large, contiguous dry forest landscape in southern
India. Our study was carried out at the Mudumalai forest
dynamics plot (MFDP), where the woody plant community
composition, recruitment and mortality patterns have been
monitored since 1988 (Sukumar et al. 1992). The MFDP, 50
ha in size (0.5 ⫻ 1 km), received 1200 ⫾ 103 mm of rainfall
annually in the last decade. This region of Mudumalai has
been almost completely free from extractive uses such as
hunting, grazing, non-timber forest produce harvest or fuel
wood collection in recent decades (Sukumar et al. 2004).
Mudumalai has high densities of chital (25 ⫾ 5 animals
km-2) and langur (30 ⫾ 11 animals km-2, Sukumar unpubl.)
the two most frequent frugivores of P. emblica.
Study design
We monitored P. emblica trees for fruit removal on the
MFDP in two consecutive fruiting seasons (October to
February 2005–2006, 2006–2007). We used a replicated
regression design to select focal trees for sampling fruit
removal from a population of nearly 300 adult P. emblica
trees on the MFDP (only trees diameter at breast height ⬎
10 cm bore fruit). This design is suitable for the linear model
approach where the effect of a continuous predictor variable
(i.e. a gradient) is being tested. In this design, adjacent units
along a gradient are grouped into levels and samples
are chosen randomly from these levels (Crawley 2002,
Cottingham et al. 2005). To determine the range of gradients, crop size and conspecific neighborhood densities were
assessed for the P. emblica population on the MFDP just
before the fruit ripened in September (see Supplementary
material Appendix 1 for heterospecific neighbors). During
this initial survey, we noted crop size using abundance categories for each individual tree (nil, ⬍ 1000, 1000–2000,
2000–5000, 5000–10 000 or ⬎ 10 000; Table 1). Neighborhood densities were computed as the number of fruiting
conspecific neighbors within 50 m of a tree (see Supplementary
material Appendix 2 for choice of clumping index). The scale
of spatial sampling was based on an earlier study where it was
found that fruiting P. emblica neighbors up to 50 m of each
other had similar probabilities of fruit being removed on any
given day or night (Prasad unpubl.), implying that ruminant
foraging is spatially auto-correlated at distances of up to
515
Table 1. Number of Phyllanthus emblica trees in various crop abundance categories at the start of the fruiting season on the Mudumalai
Forest Dynamics Plot. The first study year had higher fruit availability
compared to the second (Fischer’s exact test: p-value, 0.001).
Crop abundance category
2005–2006
2006–2007
10 000
5000–10 000
2000–5000
1000–2000
⬍ 1000
nil
5
12
15
10
129
121
0
9
13
13
175
80
Total
292
290
50 m. Crop size and neighborhood gradients of the P. emblica
population were grouped into three levels (low, intermediate, high) such that each level had equal sample sizes. The
ranges for crop size (year 1: ⬍ 1000, 1000–5000, and
⬎ 5000 fruit; year 2: ⬍ 500, 500–1500, and ⬎ 1500 fruit)
and neighborhood density levels (year 1: ⬍ 4, 5–8, ⬎ 8
trees; year 2: ⬍ 2, 3–7, ⬎ 7 trees) reflect the fruiting scenario
on the MFDP that year. At least two focal trees were chosen
from each combination of crop size and neighborhood density levels (year 1: 20 trees, year 2: 22 trees, Supplementary
material Appendix 3). To exclude influence of trees outside
the plot, trees in the outermost 50 m of the plot were not
considered.
Focal trees were sampled repeatedly across the season in
both years. We monitored the quantity of fruit persisting on
the tree once every 10 days and the removal of fallen fruit by
terrestrial frugivores once every fortnight from October to
February each year.
Estimating fruit removal
Crop size was estimated precisely for focal P. emblica trees at
the start of the season in both years. Given the moderate
height of P. emblica trees and their large fruit, it was possible
to obtain fairly accurate crop size estimates with the use of
binoculars. For trees with ⬍ 500 fruit, all fruit were counted.
For trees with ⬎ 500 fruit, the number of secondary fruiting
branches on 12 randomly chosen main branches and the
number of fruit on 20 randomly chosen secondary branches
was averaged, and multiplied with total number of main
fruiting branches. Crop size estimates were loge transformed
prior to analyses since they ranged from fewer than 100 to
greater than 15 000 fruits.
On each focal tree, 5–7 accessible branches were marked
using paint and tags (49 to 278 fruit per tree; 8 ⫾ 5% of
initial crop). Branches having more than 60 fruit made precise enumeration difficult, and were not considered for monitoring. For each tree, once in ten days all fruit on the marked
branches were enumerated. Arboreal frugivore activity at
P. emblica trees was very infrequent, and there was very little
change in quantity of fruit persisting on marked branches in
24 h intervals (⬍ 2%, Prasad unpubl.) and the ten-day measure was sufficient. We also kept a note of both direct and
indirect observations (fruit with bite marks, broken branches
and dung) of arboreal frugivores at each focal tree, examined
once every 2–3 days across the season. Since fruit on a
marked branch are not independent samples, we used a treelevel measure (fruit persistence) for analyses.
516
Removal of fallen P. emblica fruit by terrestrial frugivores
was quantified once every fortnight across the fruiting season
(ensuring independence of samples, since fallen fruit were
rarely consumable beyond 5 days). The fruit-fall area (region
beneath canopy and just adjoining it) was demarcated at the
start of the season and searched consistently and carefully for
fruit each fortnight. Fallen fruit in the fruit-fall area were
marked using a pen and monitored after 24 and 120 h every
fortnight. This technique of marking fruit did not affect frugivory by terrestrial frugivores since removal rates were not
different for marked and unmarked fruit set alongside under
fruiting trees (paired Wilcoxon test; v ⬍ 0.001, p ⫽ 1;
marked ⫽ unmarked ⫽ 157 fruit, 13 trials). To avoid biases
that could arise due to accumulation of older and less attractive fruits under less-preferred trees, we considered only
green and fresh-looking fallen fruit; brown, shriveled and
rotting fruit were not taken into account for analyses. The
green fruit we chose (whose age was unknown) appeared to
be as attractive to frugivores as fruit that fell to the ground
within previous 24 h (paired Wilcoxon test; high year: v ⫽
317.5, p ⫽ 0.31, n ⫽ 68 trials; low year: v ⫽ 628.5, p ⫽
0.58, n ⫽ 69 trials). Fruit that fell within previous 24 h were
identified by monitoring for an additional 24 h before start
of sampling.
To estimate the pace of natural fruit-fall for P. emblica
trees, we computed fruit-fall rate (in 24 h) as the number of
new fallen fruit encountered in the fruit-fall area when none
of the fallen fruit marked 24 h previously at that tree was
removed (i.e. no terrestrial frugivore had visited the tree in
24 h) and there were no signs of arboreal frugivore activity
(which also bring down fruit).
To account for intraseasonal change in the predictor variables, crop size and fruiting neighborhoods, they were reevaluated across the season for each focal tree. Each fortnight,
standing crop size was computed as the product of proportion of fruit remaining on the marked braches and initial
crop size. Fruiting neighborhoods were re-evaluated once a
month by counting neighbors still bearing fruit.
We obtained an estimate of P. emblica fruit availability on
the MFDP at the start of the season from the initial survey
(Table 1) as, fruit availability ⫽ ∑ (number of trees in crop
abundance category ⫻ mean crop size for each category).
Fruit availability on the MFDP across the season was estimated as ∑ (number of trees in crop abundance category ×
average proportion of fruit remaining on focal trees of same
category).
Statistical analyses
We used two measures to summarize frugivory of P. emblica
– fruit persistence (on the tree) and fruit removal (from the
ground by terrestrial frugivores). For each focal tree, fruit persistence was calculated as number of days until less than 10%
of initial fruit remained on marked branches. The influence
of crop size and neighborhood densities on fruit persistence
was examined using generalized linear models (GLM) of the
negative binomial family and log link (Crawley 2002).
We used generalized linear mixed effect models (GLMMs)
to study the influence of the predictor variables, i.e. crop
size, conspecific neighborhood densities and intraseasonal
time, on fruit removal (binomial family, logit link), as this
dataset contained repeated measures for trees sampled every
fortnight across the season i.e. tree identity was taken as random effect (Crawley 2002, Bolker et al. 2009). We considered both proportion and number of fruit removed in the
same model, by weighing the proportion of fruit removed
(response variable) with sample sizes i.e. number of available
fruit (similar to Ortiz-Pulido and Rico-Gray 2000, OrtizPulido et al. 2007). It is especially important to factor in
fruit availability while analyzing fruit removal by terrestrial
frugivores since fruit availability in the fruit-fall area is highly
variable even within a season. We used two temporal windows to examine fruit removal in both immediate (24 h) and
longer periods (120 h). Models were fitted separately for
each year. GLMM was also used to examine the effect of
crop size, neighborhood densities and intraseasonal time on
fruit-fall rate, with Poisson error distribution and log link
Analyses were carried out using the open source software
R 2.6.2 (R Core Development Team 2008). GLMMs were
run using the lmer function from the lme4 package (Bates
and Sarkar 2008) which is capable of handling unbalanced
designs like ours (Supplementary material Appendix 3).
Explanatory variables were standardized (by subtracting
mean and dividing by one standard deviation) to make them
comparable. Models were simplified using a backward deletion process based on Akaike’s information criterion (AIC),
starting with a maximal model that included all predictors
and their possible two-way interactions. We used graphical
methods to examine departures from model assumptions by
plotting residuals versus. predicted values, explanatory variables and also for the normality assumption (Crawley 2002,
Bolker et al. 2009). Results are presented as mean ⫾ one
standard error (SE), unless otherwise indicated.
Results
The P. emblica fruiting pattern on the MFDP was different in
the two study years (Table 1). Although a greater proportion
of P. emblica trees were fruiting in the second year, most trees
bore fewer than 1000 fruit and none bore very large quantities of fruit (⬎ 10 000) unlike the first year. The total quantity
of P. emblica fruit estimated to be available for frugivores on
the MFDP was 73% higher in the first year (~ 260 000 fruit)
compared to the second (~ 150 000 fruit). The first and second study year are hereafter referred to as ‘high year’ and
‘low year’ respectively.
Fruit persistence
The change in proportion of fruit remaining on marked
branches was minimal in most 10 d intervals (⬍ 5% per
tree) and when substantial changes (⬎ 10% per tree) was
noted, it was almost always associated with evidence of
langur foraging activity at the tree. Langur foraging activity
was sporadic and infrequent at fruiting P. emblica trees, with
5 ⫾ 2 langur visits per tree (mean ⫾ SD) in both study years
across the five-month long fruiting season. Langur activity
peaked in the middle of the P. emblica fruiting season in both
years, and steeper declines in fruit crop were seen during the
mid-season (Fig. 1).
There were marked differences between the two study
years in patterns of fruit persistence on focal P. emblica trees,
which resulted from the effect of langur foraging as well as
natural fruit fall. Fruit persisted significantly longer
(Wilcoxon rank sum test, W ⫽ 2.505, p ⫽ 0.0061) on trees
during the high year (89 ⫾ 7 days, n ⫽ 20 trees) than in the
low year (65 ⫾ 6 days, n ⫽ 22 trees). Crop size and neighbourhood densities influenced fruit persistence only in the
high year (both were positive relationships, Table 2).
Fruit-fall rates were very slow in the absence of langur
activity (range: 0–14 fruit, average: 2–3 fruit per day per
tree; in both years). Fruit-fall rate was positively influenced
by crop size in both years (Table 3). Neighborhood densities
did not influence fruit-fall in either year. In the second year,
fruit-fall decreased later in the season. The relative variance
(variance of random effect/residual variance) of the random
effect (tree identity) was less than one, implying that the
variation between individual trees was not greater than the
overall unexplained variation within the dataset. There were
no significant interactions between any of the predictors
examined in any of the persistence or fruit-fall models.
Given the extremely infrequent nature of langur visits to
fruiting P. emblica trees, it was difficult to obtain an accurate
estimate of the proportion of fruit crop brought down by
langurs (L). For each tree, L was computed as the sum of
proportional change in fruit remaining on marked branches
Figure 1. Langur activity at fruiting P. emblica trees across the season during high and low fruit availability years. Average proportion of fruit
crop estimated to be dropped due to langur activity (open squares, right axes) is plotted along with fruit availability (i.e. estimated fruit crop
on P. emblica trees in the population) across the season (filled circles, left axes).
517
Table 2. Effect of crop size (FCS) and conspecific neighborhood density on persistence of P. emblica fruit on trees. Results from generalized
linear models (negative binomial family, log link) are presented.
High year (n ⫽ 20)
Low year (n ⫽ 22)
Variable
Coef. ⫾ SE
p
Coef. ⫾ SE
p
Intercept
Log(FCS)
Conspecific density
Log(FCS): conspecific density
4.45 ⫾ 0.06
0.22 ⫾ 0.06
0.19 ⫾ 0.06
0.07 ⫾ 0.16
***
***
**
ns
4.18 ⫾ 0.13
0.09 ⫾ 0.13
−0.01 ⫾ 0.13
0.02 ⫾ 0.2
***
ns
ns
ns
***p ⬍ 0.001, **p ⬎ 0.001 and ⬍0.01, ns p ⬎ 0.1.
during 10 d intervals associated with langur activity across
the season. The remainder after accounting for langur activity (high year: L ⫽ 0.79 ⫾ 0.03 low year: L ⫽ 0.83 ⫾ 0.04)
matched closely with the estimate for proportion of total
fruit crop that dropped to the ground naturally without
langur influence, D (high year: D ⫽ 0.18 ⫾ 0.03; low year:
D ⫽ 0.19 ⫾ 0.03), though these estimates were obtained
using different datasets (on-tree and on-ground). For each
tree, D was estimated as, D ⫽ fruit-fall rate ⫻ persistence/
crop size (where, fruit-fall rate ⫽ a ⫹ b ⫻ crop size; a and b
are intercept and coefficient estimates for crop size effect on
fruit-fall in the GLMM presented in Table 3).
Factors influencing fruit removal by ruminants
A total of 3092 fallen fruit were marked and monitored
for fruit removal across 42 trees and two fruiting seasons.
Compared to the slow and sporadic changes of fruit crop on
P. emblica trees (⬍ 5% reduction in 10 days), fallen P. emblica
fruit were removed rapidly by terrestrial frugivores (⬎ 80%
removed by five days). Fruit removal by ruminants in the 24 h
time window reflects upon daily foraging decisions taken by
ruminants, whether or not to remove fruit from a tree. By 120
h, over 80% of the marked fruit were removed on most occasions from the fruit-fall area. Fruit that remain under the tree
beyond five days were rarely removed by ruminants and began
to rot or show signs of insect infestation (Prasad unpubl.). The
120 h patterns thus reflect the number of fruit actually
removed by ruminants each fortnight during the fruiting season. Results for both the temporal sampling windows are presented since fruit removal was not directly scalable, i.e.
multiplying fruit removal in 24 h by 5 did not match observations after 120 h. Similarly, variability in 24 h intervals was not
extendable to fruit removal in 120 h (less variable; Fig. 2).
Table 3. Influence of crop size (FCS), conspecific neighborhood densities and time within the fruiting season on fruit-fall and fruit removal
by ruminants. Results from generalized linear mixed effect models are presented.
Fruit-fall in 24 h
High year
Variable
Intercept
Log(FCS)
Conspecific
density
Intraseasonal
time
Quadratic term
for Intraseasonal time
(Time ^ 4)
Conspecific
density: log
(FCS)
Intraseasonal
time: log
(FCS)
Intraseasonal
time:
Conspecific
density
No. of trees
No. of
observations
Relative
variance
of random
effect
(tree)
Coef. ⫾ SE
Low year
p
0.89 ⫾ 0.19 ***
0.39 ⫾ 0.16 *
⫺0.20 ⫾ 0.17 ns
0.10 ⫾ 0.10
Fruit removal in 24 h intervals
ns
High year
Coef. ⫾ SE
pP
0.61 ⫾ 0.2
0.38 ⫾ 0.19
⫺0.22 ⫾ 0.19
**
*
ns
⫺0.23 ⫾ 0.13
*
Low year
Coef. ⫾ SE
p
Coef. ⫾ SE
⫺0.10 ⫾ 0.24
ns
*
*
⫺0.55 ⫾ 0.18
0.46 ⫾ 0.20
0.40 ⫾ 0.18
0.96 ⫾ 0.12 ***
High year
p
Coef. ⫾ SE
Low year
p
Coef. ⫾ SE
p
***
***
0.58 ⫾ 0.15
⫺0.39 ⫾ 0.15 **
4.26 ⫾ 0.53 ***
1.78 ⫾ 0.40 ***
0.93 ⫾ 0.45 *
3.43 ⫾ 0.46 ***
0.19 ⫾ 0.32 ns
0.39 ⫾ 0.38 ns
0.87 ⫾ 0.10 ***
3.66 ⫾ 0.56 ***
1.13 ⫾ 0.22 ***
0.58 ⫾ 0.17 ***
0.11 ⫾ 0.16
ns
⫺0.1 ⫾ 0.11
ns
⫺0.33 ⫾ 0.13
*
0.04 ⫾ 0.11
ns
0.07 ⫾ 0.14
ns
⫺0.02 ⫾ 0.11
ns
0.08 ⫾ 0.09 ns
1.12 ⫾ 0.31 *** ⫺0.97 ⫾ 0.23 ***
⫺0.17 ⫾ 0.11
ns
0.1 ⫾ 0.13
ns
0.36 ⫾ 0.10 ***
0.35 ⫾ 0.07 ***
0.99 ⫾ 0.33 *** ⫺0.05 ⫾ 0.25
⫺0.03 ⫾ 0.11
ns
⫺0.54 ⫾ 0.23
*
0.35 ⫾ 0.29
19
72
17
48
20
101
22
97
20
101
22
97
0.5
0.38
0.86
0.49
1.53
3.47
*** p ⬍ 0.001, ** p ⬎ 0.001 and ⬍ 0.01, *p ⬎ 0.01 and ⬍ 0.01, ns p ⬎ 0.1.
518
Fruit removal in 120 h intervals
ns
ns
Figure 2. Box and whiskers plot showing intraseasonal variation in removal of fallen P. emblica fruit by ruminants in high (a, c) and low
(b, d) fruit availability year and in two time windows: 24 h (a, b) and 120 h (c, d).
Fruit removal in both 24 h and 120 h intervals increased
with intraseasonal time in both years (Fig. 2, Table 3). The
relationship between fruit removal in 120 h and intraseasonal
time was non-linear in the high year and a quadratic term
improved model fit considerably (Table 3). The inequalities
in fruit removal within the population, i.e. the coefficient of
variation, declined with intraseasonal time in both years
(Spearman’s rank correlation; n ⫽ 8 fortnights; high year:
rho ⫽ ⫺0.87 p ⬍ 0.01, low year: rho ⫽ ⫺0.88,
p ⬍ 0.01). In the first three fortnights, around 35% of the
fruit were removed within 24 h (high year: 35%; low year:
34%) and over 80% by 120 h (year 1: 84%; year 2: 87%).
Fruit removal was more rapid later in the season (last three
fortnights) with over 60% removed by frugivores within 24
h itself (year 1: 68%; year 2: 62%). There was very little
variation later in the season, with most trees experiencing
100% removal by 120 h in both years (Fig. 2).
Crop size influenced fruit removal in both time windows
and in both years. Conspecific neighborhood densities influenced fruit removal in 24 h intervals in both years and in 120
h only in the high year (Table 3). All the removal models had
two-way interactions between the predictor variables, which
implied that the effect of one variable involved in the interaction was conditioned by the level of the second variable.
Hence, the effect of individual predictors on fruit removal
has to be examined in the context of these interactions.
In the high fruit availability year, there were negative
interactions between the effect of crop size and neighborhood densities on fruit removal in both 24 and 120 h models
(Table 3). To interpret this interaction, we examined the
influence of neighborhood densities on removal separately
for three levels of crop size (high, intermediate and low, with
equal number of trees in each level and using median values
to represent each level), while keeping time at a constant
value. In both these models, removal increased more steeply
with neighborhood densities for low crop trees, while trees
bearing more fruit displayed weak positive trends and experienced a slight dip in removal at the highest neighborhood
densities (Fig. 3).
The effect of crop size on fruit removal in 120 h also varied
with intraseasonal time in both years due to significant interactions between these two predictors (Table 3). Again, to
interpret these interactions, we examined the influence of
intraseasonal time on fruit removal separately for trees in
three levels of crop size as described earlier (Fig. 4). In both
years, at the start of the season, trees bearing larger crops (high
and intermediate crop trees) had more fruit removed compared to trees with very few trees (~ 20–40% higher, Fig. 4).
Later in the season, there were no differences in fruit removal
between trees having different crop sizes, with most trees
experiencing nearly 100% removal. High and intermediate
crop trees experienced 100% fruit removal from the start in
the low fruit availability year compared to the high year where
such trees had ⬍ 70% removal at the start (Fig. 4).
The two-way interactions between intraseasonal time and
neighborhood densities in the 24 h removal models for both
years and the 120 h model for the high year were also examined graphically by inspecting the influence of intraseasonal
time on fruit removal for three levels of neighborhood densities (Table 3). Later in the season, in the shorter time window
(24 h), clumped trees had higher proportion of fruit removed
by ruminants (~ 20–40% more) in both years. However, these
519
Figure 3. Plot examining interaction between crop size (FCS) and neighborhood effects on fruit removal by ruminants. Trees bearing very
low crop (solid lines) benefited more with increasing density of conspecific neighbors compared to intermediate (dashed lines) and high
crop trees (dotted lines) in both 24 h (a) and 120 h (b) time windows. This interaction was seen only in the high fruit availability year.
differences did not persist into the longer time window (120
h), where it looked like deer visited all trees and consumed
almost all fruit available within five days irrespective of neighborhood densities later in the season (Fig. 5). In the high year,
at the start of the season, isolated trees had slightly higher
proportion of fruit removed compared to more clumped
fruiting trees (~ 10% more; Fig. 5) in 120 h intervals.
Discussion
Our results show the complex relationships of fruit removal
with crop size and neighborhood densities across a hierarchy
of nested temporal levels. Interannual variation in fruit availability had a pronounced effect on the relationships between
crop size, fruiting neighborhoods and frugivore choice. Crop
size and conspecific neighborhood densities influenced fruit
persistence on P. emblica trees only in the high fruit availability year. This could have resulted from satiation of langur
troops when fruit are abundant leading to longer fruit persistence on trees within clumps and for those bearing larger
crops. Fruit removal by ruminants (in 120 h) was influenced
by crop size in both years and by conspecific neighborhood
densities only in the high year. The effect of interannual
variation in fruit productivity on fruit removal by ruminants
was further structured by intraseasonal variation.
Inter-annual differences in crop size and neighborhoods
effects on fruit removal by ruminants were more prominent
at the start of the fruiting season, when fruit availability was
higher. Crop size had a positive effect on fruit removal by
ruminants in both years as reported by a majority of fruit
removal studies (Ortiz-Pulido and Rico-Gray 2000, OrtizPulido et al. 2007, Blendinger et al. 2008). For the first time,
we test the applicability of theory and hypothesis concerning
crop size and fruiting neighborhood effects on fruit removal
that have emerged from bird-dispersed systems (Sargent
1990, Carlo et al. 2007 and references there in) to interactions involving terrestrial frugivores such as ruminants. Unlike
arboreal frugivores which are offered a choice of trees bearing
different quantities of fruit, terrestrial frugivores are presented
with a few fruit daily on the ground across the season. This
difference in fruit presentation could lead to variation in plant
attributes that attract volant and terrestrial frugivores, especially if crop size is not related to fruit availability on the
ground. In our study system since fruit availability on the
ground through fruit-fall was a positive function of crop size
in both years, it was not surprising that trees having larger
crops experienced higher fruit removal by ruminants. At the
Figure 4. Plot examining interactions between the influence of crop size (FCS) and intraseasonal time on fruit removal by ruminants in 120 h
intervals. Intraseasonal decline in fruit crop on P. emblica trees within the population (open square) is plotted on the right axes. When fruit
were abundant at the start of the season, high (dotted lines) and intermediate (dashed lines) crop trees had greater proportion of fruit
removed than low crop trees (solid lines). Later in the season when fruit were scarce, all trees experienced complete removal by 120 h, irrespective of crop size. Intermediate and high crop trees had higher fruit removal (intercepts) at the start of the low fruit availability year (b)
compared to the high year (a).
520
Figure 5. Plot examining interaction between the effect of neighborhood densities and intraseasonal time. Intraseasonal variation in
fruit availability altered neighborhood effects on the quantity of
fruit removed by ruminants in 120 h only in the high fruit availability year. Isolated trees (solid lines) experienced stepper increase
in fruit removal with time compared to trees under intermediate
(dashed lines) and high neighborhood densities (dotted lines).
Intraseasonal decline in fruit crop on P. emblica trees within the
population (open square) is plotted on the right axes.
start when fruit are abundantly available, trees bearing fewer
than 500 fruit, which dropped just one fruit daily on an average, may not be worthwhile for ruminants to visit.
Conspecific neighborhood densities influenced fruit removal
by ruminants (in 120 h) negatively in the high year, where, at
the start, isolated trees had higher removal. This could have
resulted from competition for frugivores between fruiting
neighbors leading to lower fruit removal in clumped conditions. In addition to the intraseasonal context, interactions
between fruiting neighbors in the high year was structured by
stronger neighborhood effects for plants with low crop sizes in
both time windows. Low crop trees experienced steep rewards
by having richer neighborhoods while trees with larger crops
had a slight dip in fruit removal (in 120 h) in highly clumped
situations. Similar interaction effects with trees bearing fewer
fruit benefiting under high density fruiting neighborhoods have
been reported by Blendinger et al. (2008).
We also found that the quantity of fruit removed by
ruminants in 24 h could not be directly extended as a multiplicative effect to the longer time window (120 h). The magnitude and significance of crop size and neighborhood effects
on fruit removal were not constant across the two temporal
sampling scales. This highlights the need to examine multiple time points and avoid arbitrary definitions of temporal
sampling scales while studying frugivore choice.
Inequalities in fruit removal between individual plants in
the P. emblica population seen at the start of season did not
persist into the second half of the season when fruits were
removed almost entirely from all trees in both years, irrespective of crop size or neighborhood densities. Our results imply
that all fruiting individuals in a population are not equally
attractive to frugivores at all points of time. When fruit were
locally abundant in the P. emblica population, fruit selection
by arboreal and terrestrial frugivores was mediated by spatial
patterning of fruit resources, both in terms of concentration
of fruit on individual trees (points) and neighborhoods
(patches). Temporal fluctuations in fruit availability reduced
inequalities in fruit removal and the effect of crop size and
neighborhood densities within the population. These results
are in concordance with studies that have examined the effect
of temporal variation in fruit availability on crop size effects
(Ortiz-Pulido and Rico-Gray 2000, Osada 2005, Forget and
Jansen 2007), though ours is the first study to demonstrate
temporal-context dependency of conspecific neighborhood
effects on fruit removal. Frugivore movement and foraging
decisions could also be shaped by alternative food resources
including co-fruiting species which might also experience
temporal fluctuations (see Supplementary material Appendix
1 for effect of intraseasonal change in heterospecific neighborhoods on the P. emblica system). Indeed, this work needs
to be extended to other temporal contexts that influence frugivore choice such as co-fruiting species and frugivore abundance for a more complete understanding of the temporal
context-dependency of fruit–frugivore interactions.
Shifting asymmetries in fruit removal and temporal fluctuations in crop size and neighborhood effects within populations could alter the demographic consequences of
frugivore-mediated selection. Plant–plant links formed by frugivore movement and consequent seed deposition patterns
may differ in time when fruit productivity changes (Morales
and Carlo 2006, Carlo et al. 2007, Carlo and Morales 2008).
Temporal shifts in frugivore choice may also reduce the potential for co-evolution between frugivores and plants by diluting
selective pressures on traits such as fruit nutritional value, fruit
size or fruiting phenology (Herrera 1982, Izhaki et al. 2002,
Schaefer et al. 2003). Even if certain trees experienced lower
fruit removal at certain points of time, this could be compensated later in the fruiting season or in future years, thus reducing directionality in the selection operated by frugivores. For a
more complete understanding of demographic and evolutionary consequences of fruit–frugivore interactions, temporal
fluctuations in frugivore choice need to be modeled explicitly
for varying temporal contexts that influence fruit removal
such as fruit availability or frugivore abundance, as attempted
with spatially-explicit models (Morales and Carlo 2006, Carlo
et al. 2007, Carlo and Morales 2008).
In addition to temporal context-dependency, we found that
our study system was structurally complex with links between
the plant and its primary dispersers (ruminants) intervened by
another species (langur). Ruminants usually visit fruiting P.
emblica trees in pairs or singly for short durations (⬍ 10 min)
in search of fruit almost daily (Prasad et al. 2004). The colobine
monkey, langur, visits fruiting P. emblica trees infrequently
across a five-month long fruiting season but brings down large
quantities of fruit. When langur troops are on a tree, ruminants
(especially chital deer) aggregate under trees (up to 20 individuals) and spend hours feeding on fruit dropped by langurs (Newton 1989, Prasad et al. 2004). Similar associations between
langur, and ruminants were noted for eight other ruminantdispersed species at Mudumalai (Prasad unpubl.) and have also
been reported for 13 other plant species across the Indian subcontinent (Dinerstein 1979, Newton 1989).
521
Given the slow fruit-fall rate, langurs determine when
and where large quantities of P. emblica fruit are available on
the ground. From the plant’s perspective, the tradeoff is
between having most fruit removed in a few hours during
primate-ruminant interactions versus. a few fallen fruit
removed daily across the season by ruminants. When large
quantities of fruit are consumed in a few hours by a few animals, given that ruminants regurgitate most seeds at their
bedding sites (Prasad et al. 2006, Brodie et al. 2009), the
seed shadows generated would probably be more aggregated.
In contrast, when a few fruit are dispersed by ruminants daily
across the season, seed shadows might be less aggregated and
reach a wider array of micro-habitats. This tradeoff could be
mediated by complex density-dependent gut-passage effects
and post-dispersal processes (Nathan and Muller-Landau
2000, Bruun and Poschlod 2006, Brodie et al. 2009).
It has been proposed that fruit super abundance and consequent disperser satiation can have unfavorable reproductive
consequences for animal-dispersed species due to lowered fruit
removal (unless the species is largely dispersed by seed predators) and that this might operate against the evolution of
extremely large inter-annual fluctuations in crop sizes (Herrera
et al. 1998). In our study system, frugivores appeared to be
slightly satiated only at the start of the season, especially in the
high fruit availability year. The graduated ripening of fruit on
branches of several bird dispersed trees (Gorchov 1990) or the
slow fruit-fall rates in plants like P. emblica could be strategies
to avoid disperser satiation in time. Plants could be maximizing their dispersal potential by staggering fruit availability to
frugivores across the season. Other advantages of staggered
fruit availability in time include targeting temporally unpredictable disperser arrival (which was not the case with ruminants that visit P. emblica trees daily) and a potentially wider
spread of dispersed seeds (Gorchov 1988). This prompts questions about when primates arrived in the co-evolution between
plants and ruminants and the subsequent alterations that
might have occurred in the ruminant–plant interaction. Further research comparing ruminant-dispersed plants with and
without primate-accelerated fruit-fall could indeed provide
interesting insights into the evolution of complexities in plant–
animal mutualistic networks.
Connections between disparate animal groups add additional levels of complexity to plant–frugivore mutualistic
networks with interactions between the plant and its primary
disperser mediated by another node (Bascompte and Jordano
2007, Carlo et al. 2007). Our findings illustrate how interdependencies formed between disparate animal consumers
can have potential reproductive consequences for specific
individuals within populations. Our findings also illustrate
how reproductive consequences for individual trees are not
static across time. It is indeed very important to consider
complexity in fruit–frugivore interactions, be it within their
structure or in the spatio-temporal variation of their outcomes, for a more complete understanding of their demographic and evolutionary outcomes.
Acknowledgements This work was possible due to support from H. S.
Dattaraja, H. S. Suresh, R. P. Harisha, Raman Kumar and our field
assistants. Thanks to Sabrina Russo and Kim McConkey for help
with study design; Kavita Isvaran for statistical analyses; and Kim
McConkey, Ahimsa Campos Arceiz, Kavita Isvaran and Pierre Michel
522
Forget for help with manuscript preparation. The study was funded
by the Ministry of Environments and Forests, Government of India
and Tamil Nadu Forest Department provided research permissions.
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523
Ecol Res (2010) 25: 225–231
DOI 10.1007/s11284-009-0650-1
O R I GI N A L A R T IC L E
Soumya Prasad • André Pittet • R. Sukumar
Who really ate the fruit? A novel approach to camera
trapping for quantifying frugivory by ruminants
Received: 2 March 2009 / Accepted: 28 August 2009 / Published online: 16 October 2009
The Ecological Society of Japan 2009
Abstract Tropical forest ruminants disperse several
plants; yet, their effectiveness as seed dispersers is not
systematically quantified. Information on frequency and
extent of frugivory by ruminants is lacking. Techniques
such as tree watches or fruit traps adapted from avian
frugivore studies are not suitable to study terrestrial
frugivores, and conventional camera traps provide little
quantitative information. We used a novel time-delay
camera-trap technique to assess the effectiveness of
ruminants as seed dispersers for Phyllanthus emblica at
Mudumalai, southern India. After being triggered by
animal movement, cameras were programmed to take
pictures every 2 min for the next 6 min, yielding a sequence of four pictures. Actual frugivores were differentiated from mere visitors, who did not consume fruit,
by comparing the number of fruit remaining across the
time-delay photograph sequence. During a 2-year study
using this technique, we found that six terrestrial
mammals consumed fallen P. emblica fruit. Additionally, seven mammals and one bird species visited fruiting
trees but did not consume fallen fruit. Two ruminants,
the Indian chevrotain Moschiola indica and chital Axis
axis, were P. emblica’s most frequent frugivores and they
accounted for over 95% of fruit removal, while murid
rodents accounted for less than 1%. Plants like P.
emblica that are dispersed mainly by large mammalian
frugivores are likely to have limited ability to migrate
across fragmented landscapes in response to rapidly
Electronic supplementary material The online version of this article
(doi:10.1007/s11284-009-0650-1) contains supplementary material,
which is available to authorized users.
S. Prasad (&) Æ R. Sukumar
Centre for Ecological Sciences,
Indian Institute of Science, Bangalore 560012, India
E-mail: [email protected]
Tel.: +91-9448542902
Fax: +91-80-23602280
A. Pittet
Centre for Electronic Design and Technology,
Indian Institute of Science, Bangalore 560012, India
changing climates. We hope that more quantitative
information on ruminant frugivory will become available with a wider application of our time-delay cameratrap technique.
Keywords Deer Æ Mudumalai Æ Phyllanthus emblica Æ
Seed dispersal Æ Ungulates
Introduction
Southeast Asian large mammal declines are among the
most serious global extinction crisis (Corlett 2007; Sodhi et al. 2004). The Indian subcontinent is the last
refuge for Asian ruminants whose range extends as far
west as India, such as the hog deer and the gaur (Simon Stuart, pers. comm.; Duckworth et al. 2008;
Timmins et al. 2008). Tropical Asian ruminants have
mostly been researched as food for carnivores (Karanth
et al. 2004) and there is little information available on
the other ecological roles of these fascinating animals.
In particular, their role in seed dispersal is poorly
understood, though they are known to disperse several
large (>1 mm) as well as small-seeded species. (Chen
et al. 2001; Middleton and Mason 1992; Prasad et al.
2006). Given their large home ranges and long seed
retention times, ruminants are potential long-range
dispersers for several tropical plants (Cosyns et al.
2005; Mouissie et al. 2005; Vellend et al. 2003). Yet, the
effectiveness of ruminants as seed dispersers is poorly
understood.
Disperser effectiveness is defined as the contribution a
disperser makes to the future reproduction of a plant.
Information required to evaluate disperser effectiveness
falls into three broad categories: (a) the quantity of fruit
removed, (b) the quality of fruit handling and seed
deposition, and (c) the diversity of species dispersed
(taxonomic and seed size range) (Dennis and Westcott
2007; Schupp 1993). While the qualitative aspects of
seed dispersal by ruminants have been addressed to
some extent (Cosyns et al. 2005; Mouissie et al. 2005;
226
Prasad et al. 2006), little is known about the quantity or
diversity of dispersal services provided by ruminants.
The quantity of seed dispersal depends on the number of
visits made to the plant by a disperser and the number of
seeds removed per visit (Schupp 1993).
Understanding quantitative aspects of frugivory by
terrestrial animals such as ruminants is limited by
methodological constraints since most available techniques, such as tree watches or fruit traps, have evolved
from studies of arboreal frugivores (such as birds, bats,
or primates) and are not suitable for studying terrestrial
frugivores. Tree watches require one or two observers to
watch fruiting trees to note whether the visiting animals
consume fruit, the number of fruit they consume, and
their fruit handling behavior (for e.g., Dennis and
Westcott 2006). Large terrestrial frugivores such as
ruminants or pheasants are often nocturnal or are extremely wary of human presence and this makes it difficult to observe them directly by watching fruiting trees.
Fruit fall traps are placed beneath and around fruiting
trees to note fruit-fall rates and the proportion of fruitbearing feeding signs, from which proportion of fruit
removed by frugivores is deduced using various approaches (for e.g., Howe 1980). Placing fruit traps obstructs movement and frugivory by terrestrial frugivores
and is hence not suitable to quantify frugivory by
ruminants.
Camera traps are indeed a useful technique for
studying terrestrial frugivores and have been used
extensively for this purpose (for e.g., Babweteera et al.
2007; Beck and Terborgh 2002; Christianini and Galetti
2007; Cramer et al. 2007; Jayasekara et al. 2003; Kitamura et al. 2007; Miura et al. 1997). These previous
studies have used camera traps to identify potential
terrestrial frugivores, but they fail to distinguish frugivores from mere visitors to fruiting trees. This is because
they do not set clear criteria to distinguish confirmed
frugivory events (when fruit were actually consumed by
an animal) to situations involving animals that were
simply walking past the fruiting tree without consuming
fruit. In the absence of this distinction being made about
identifying actual frugivores using camera traps, the
study of terrestrial frugivores has been data-deficient
compared to research on arboreal frugivores. We attempted to develop a technique by which we could obtain confirmed frugivory events using a camera trap in
order to distinguish frugivores from visitors as well as
obtain data on the quantity of fruit consumed per visit
by a frugivore.
In this paper, we illustrate the use of this novel
camera-trapping technique to address the quantitative
aspects of dispersal services provided by ruminants using
the example of Phyllanthus emblica (Euphorbiaceae,
Gærtn), whose fruit are important non-timber forest
produce from Asian dry tropics. Our main objectives
were to: (1) distinguish visitors from consumers of fallen
P. emblica fruit using camera traps; (2) quantify and
compare fruit removal by ruminants with other terrestrial frugivores of P. emblica.
Materials and methods
Study area and study species
Mudumalai (321 km2; 1132¢–1143¢N, 7622¢–7645¢E)
is part of a large, contiguous dry forest track in southern
India. These forests have a diverse and abundant ruminant assemblage consisting of species such as gaur Bos
gaurus, sambar Cervus unicolor, chital Axis axis, barking
deer Muntiacus muntjak, and Indian chevrotain Moschiola indica (Varman and Sukumar 1995). This study
was carried out at the 50-ha Mudumalai forest dynamics
plot (MFDP), where the woody plant community composition, recruitment, and mortality patterns have been
monitored since 1988 (Sukumar et al. 1992). The MFDP
received 1200 ± 103 mm of rainfall annually in the last
decade.
The study tree, P. emblica bears globose, greenish,
drupaceous fruit (length 20–30 mm) from October to
February. These fruit are extensively harvested by people across its range in Asian tropics for use in food
products and cosmetics. Previous work using tree
watches has shown that P. emblica’s arboreal frugivores
are either largely seed predators (giant squirrel Ratufa
indica) or mainly pulp-feeders (Hanuman langur Semnopithecus entellus) that were neutral with respect to
dispersal action (since langur drop fruit and seed under
parent plants). However, langur facilitate frugivory by
terrestrial animals like ruminants, by making large
quantities of fruit available to them on the ground. The
terrestrial frugivores, ruminants, and murid rodents,
remove seeds from the vicinity of the parent plants
(Prasad et al. 2004). The role of rodents in this system is
poorly understood; they are known to predate seeds but
not scatter hoard them. Earlier work on the qualitative
aspects of ruminant frugivory, using gut passage trials
and germination experiments, has shown that ruminants
swallow fruit whole and disperse viable P. emblica’s
seeds through regurgitation after retaining them in the
rumen for several hours (Prasad et al. 2006). Tree
watches used in the earlier study provided a list of frugivores and their fruit-handling behavior, but the
quantity of fruit consumed by different frugivores could
not be inferred by this technique (Prasad et al. 2004).
This was because observers had to be located over 100 m
from trees since large mammalian frugivores were wary
of human presence. From these distances it was difficult
to confirm frugivory or note number of fruit removed.
Thus the quantity of P. emblica fruit removed by different ruminant species and murid rodents remains to be
addressed.
Methods
On the MFDP, we monitored frugivory of P. emblica
using four camera traps for two consecutive fruiting
seasons (15 trees in 2005–2006; 19 trees in 2006–2007).
227
These focal trees were monitored for crop size, neighborhood densities, and fruit removal as part of a larger
study examining factors influencing fruit removal. To
study frugivory, we used digital camera traps (PIRPIC04) developed by one of us (A. Pittet) at the Centre
for Electronics Design and Technology (CEDT), Indian
Institute of Science, Bangalore. These systems use passive infrared motion sensors to detect the movement of
any warm-bodied animal passing in front of them. The
sensor is connected to a micro-controller that, in turn,
can trigger the digital camera (Olympus D-380 or C-120,
2 megapixels) when required. The batteries used last for
at least 5 days, always ready to take a picture within less
than a second. The motion detector has adjustable sensitivity and is able to detect even small rodents or birds
at more than 8–10 m. However, at night, the effectiveness of the flash is a limiting factor as the clarity of the
picture is reduced significantly beyond 6 m. The camera,
sensor, and the micro-controller were together housed in
weatherproof casing and left on continuously throughout the day and night (for more details on PIRPIC04
refer Varma et al. 2006).
The principal difference from camera traps used before in frugivory studies was that our units were reprogrammed to take time-delay pictures every 2 min, for the
next 6 min after it was first triggered, yielding a sequence
of four pictures (0, 2, 4, and 6 min). By comparing the
number of fruit seen in earlier pictures with later pictures
in this sequence, we could infer whether an animal that
visited the tree had consumed fruit (for examples see
Fig. 1; Figs. S.1, S.2). When animals stayed beyond
6 min, the camera was triggered again. The time-delay
sequence helped us distinguish actual frugivores from
Fig. 1 Camera-trap pictures of
a frugivore (Chital Axis axis)
consuming fallen fruit at a
Phyllanthus emblica tree. After
being triggered by animal
movement, the camera was
programmed to take a picture
at intervals of 2 min for the
next 6 min, yielding a sequence
of four pictures (a 0, b 2nd, c
4th, d 6th min). Examining the
difference in number of fruit
seen in this time-delay sequence
of pictures reveals that the
chital consumed the four fallen
fruit set in front of the camera
within 2 min
mere visitors. This technique also yielded information
on the number of available fruit consumed by a frugivore as well as the length of time frugivores spent at
fruiting trees.
The camera-trap unit was secured to the trunk of a
focal tree and kept focused on fallen fruit beneath the
tree. Only fallen fruit were considered for camera trapping; fruit were never interchanged between trees,
though fruit from the same tree were often moved from
their original locations to be placed in front of the
camera. The camera traps were checked daily, they were
never set for more than two consecutive days at a tree
and each focal tree was sampled for a minimum of 100 h
(4 days). Each day we noted the number of pictures
taken, fruit remaining from the previous day, and fruit
placed in the front of the camera that day. Photographs
were transferred to a computer and examined closely to
check if fruit had been consumed using the time-delay
sequence. All analyses and graphs were processed in the
open-source software R 2.8.0. Results are presented as
mean ± SE.
Data collection began only after an initial trial period
to fine tune camera placement (20 days), due to which
fewer days were sampled in the first year. To check if
camera placement disrupted frugivore activity, we
monitored fruit removal in the fruit-fall region away
from the camera trap (cameras covered only a part of
the fruit-fall area) and in adjacent fruiting trees. When
fruit placed in front of the camera remained while they
were removed from elsewhere, it implied that our camera placement had disturbed frugivores. After such trials, camera placement was standardized to a height of
1.3–1.7 m, which appeared not to disrupt frugivore
228
activity probably because it kept cameras above the eye
of frequent terrestrial frugivores (but within range of our
flash). Camera units were camouflaged by painting them
green and by covering them with foliage and elephant
dung (to mask human odor). We also attempted to
quantify the bias due to flash activity at night by placing
an infrared video camera trap (Sony CCD TR511E)
along with our regular camera-trap units. The video
camera was also kept focused on fallen fruit and was
triggered by a mechanism similar to PIRPIC04. However, due to several technical problems with our sole
video camera we managed to video tape only two flashevents involving P. emblica’s most frequent nocturnal
frugivore (i.e., the Indian chevrotain). It appeared that
this frugivore was not affected by the flash. Videos shot
in infrared (which is not visible to most vertebrates)
showed that the chevrotain did not move away after the
flash and continued to feed on fruit as before.
Results
The camera traps sampled a total of 3120 hours or
130 days across 2 years and over 30 fruiting P. emblica
trees for terrestrial frugivore activity. Species that were
noted to remove fallen P. emblica fruit by comparing
pictures in the time-delay sequence generated by our
camera trap unit were classified as frugivores, while
others were noted as visitors. In this fashion, we classified six mammals as frugivores of P. emblica; this included three ruminants (chital, Indian chevrotain, and
barking deer), a rodent (black rat Rattus rattus), a primate (langur) and the elephant Elephas maximus (Table 1). Of these, the langur is a frequent arboreal
frugivore (Prasad et al. 2004) which consumed fallen
fruit on one occasion across 2 years. Seven mammal
species and one bird species were noted to visit fruiting
P. emblica trees but not consume any available fallen
fruit. The sole avian visitor was the Magpie robin Copsychus saularis (year 1 = 1, and year 2 = 0 visits). The
mammalian visitors included a ruminant (sambar, year
1 = 1, year 2 = 2 visits), a primate (bonnet macaque
Macaca radiata, year 1 = 0; year 2 = 1 visits), a rodent
(white-tailed wood rat Madromys blanfordi, year 1 = 1;
year 2 = 2 visits), the sloth bear Melursus ursinus (year
1 = 0; year 2 = 1 visits), two species of mongoose
(stripe-necked mongoose Herpestes vitticollis, year
1 = 0; year 2 = 1 visits; ruddy mongoose Herpestes
smithii, year 1 = 2; year 2 = 0 visits) and the leopard
(Panthera pardus, year 1 = 0; year 2 = 1 visits). These
visitor species were never observed to consume fruit by
camera traps, direct observations or other methods
outlined in Prasad et al. (2004). On two occasions in
both years, we obtained pictures of animals (small rodents or what appeared to be a shrew) that could not be
clearly identified and none of these unidentified animals
consumed fruit.
Frequency of visits
On average, there were 0.71 ± 0.09 (max = 5,
n = 130 days) visits per day to fruiting P. emblica trees
by its frugivorous species, while the visitor species were
less frequent (0.12 ± 0.03 visits per day). Frugivory by
the Indian chevrotain and chital, the two most frequent
frugivores, was noted within the first 12 days of cameratrap sampling and no new frugivore species were detected beyond 47 days of sampling. Thus, the second
year of camera-trap sampling (75 days) did not detect
any new frugivore species for P. emblica.
Ruminants were the most frequent terrestrial frugivores of P. emblica. The Indian chevrotain was the most
frequent frugivore species in the first year though chital
was more frequent in the second year. These two ruminant species together constituted 84% (n = 90) of frugivore visits to fruiting P. emblica trees. Among the
other ruminant species that visited fruiting P. emblica
trees, barking deer ate P. emblica fruit on rare visits
(Table 1), while sambar was never observed to consume
P. emblica fruit. The non-ruminant frugivores, which
included langur, elephant, and the black rat, were noted
to remove fallen P. emblica fruit on one occasion each
during the 2 years of sampling (Table 1). Even the frequent frugivore species did not consume available fallen
fruit on every visit (Table 1), and this was especially true
Table 1 Frequency of visits and quantity of fruit removed by different frugivores of Phyllanthus emblica as observed by camera traps (year
1 15 trees, 54 days; year 2 19 trees, 76 days)
Frugivore
Chital
Indian chevrotain
Black rat
Langur
Barking deer
Elephant
Frequency of visits
Average proportion
of fruit consumed per visit
Relative fruit removal
Average visit length
(min)
Year 1
Year 2
Year 1 (%)
Year 2 (%)
Year 1 (%)
Year 2 (%)
Year 1
Year 2
14
33
9
1
1
1
19 (14)
10 (10)
–
1 (0)
–
–
70 ± 11
80 ± 6
1±1
40
33
100
72 ± 10
65 ± 13
–
0
–
–
29 (86/300)
66 (197/300)
0.3 (1/300)
1 (4/300)
1 (2/300)
3 (10/300)
53 (66/125)
47 (59/125)
–
0 (0)
–
–
4.6 ± 1.3
4.8 ± 0.7
2.7 ± 0.7
5
2
2
3.8 ± 0.9
3.6 ± 0.5
–
2
–
–
(11)
(27)
(1)
(1)
(1)
(1)
Results are mean ± SE. Relative fruit removal is the ratio of number of fruit removed by a frugivore across the entire fruiting season to
the total number of P. emblica fruit consumed by all frugivores. Figures in parentheses for the ‘frequency of visits’ column represent the
number of visits where fruit were actually removed by a frugivore
229
for the black rat, which removed fruit only once across
nine visits.
up to 52 min (year 1) when they were following langur
foraging activity at fruiting P. emblica.
Proportion of fruit removed by different frugivores
Discussion
On average, the Indian chevrotain and chital consumed
around 70% of the available fallen fruit per visit. On one
occasion across 2 years, barking deer, langur, and elephants consumed considerable proportions of available
fallen fruit (33, 40, and 100%, respectively). Over 95%
of the total P. emblica fruit removed by frugivores and
having the potential to be dispersed were consumed by
ruminants (year 1, 285 of 300 fruit; year 2, 125 of 125
fruit removed by frugivores). There was a shift in the
relative proportion of fruit removed by the chevrotain
and chital from the first to the second year. The P
relative
proportion of fruit removed
by
the
chevrotain
(
fruit
P
removed by chevrotain/
fruit removed by all frugivores) declined by 19% (Table 1; v2 test with continuity
correction, v2 = 11.80, P-value <0.001) while the relative proportion of fruit removed by chital increased by
24% in the second year (v2 = 21.33, P-value <0.001).
From two fruiting seasons and over 3000 hours of
camera-trap observations using the time-delay technique, for the first time we report quantitative information on frugivory by terrestrial animals. With our
time-delay camera-trap technique we could obtain pictures that differentiated events when fallen fruit were
actually removed by frugivores compared to mere visits.
The time-delay camera-trap technique showed that
ruminants were the most frequent terrestrial frugivores
of P. emblica and that they accounted for over 95% of
the fallen fruit removed by frugivores. From earlier
studies, it is known that P. emblica’s arboreal frugivores
are largely neutral or predatory in dispersal action, while
ruminants disperse viable seeds through regurgitation
(Prasad et al. 2004, 2006). Thus, based on results from
our camera-trap work, we can now say that ruminants
remove the largest proportion of P. emblica’s fruit and
are P. emblica’s principal primary disperser.
In the second year, a higher proportion of fruit was
removed by chital compared to the first year where
chevrotain removed more fruit. Though we sampled
more days in the second year, there were fewer species
recorded to consume fallen P. emblica fruit. The fruiting
scenario on the MFDP differed between the two study
years with the estimated quantity of P. emblica fruit
available to frugivores being 73% higher in the first
year(260,000 fruit) compared to the second (150,000
fruit) (Prasad, unpublished data). Given that chital is a
larger animal (40–100 kg) compared to the Indian
chevrotain (2–4 kg, Menon 2002), it is possible that it is
a superior competitor when resources are scarce, as
during the second P. emblica fruiting season. It is also
possible that the chevrotain visits declined in the second
year since it was not worthwhile for smaller animals like
them to expend effort in searching when very few fallen
fruit were available. Shifts in resource usage due to
possible competitive exclusion when resources are lim-
Frugivore visitation pattern
Chital visits to fruiting P. emblica trees were largely
diurnal, peaking in the early morning and evening hours,
with a few rare visits during night hours (Fig. 2). In
contrast, the chevrotain frequented fruiting P. emblica
trees only during the night hours, with most of the visits
occurring between 1900 and 1400 hours. The black rat
too was nocturnal, with visits spread between 1900 and
0600 hours. Visits by other frugivore species that consumed fallen P. emblica were too infrequent to characterize visitation patterns. The duration of visit to fruiting
P. emblica trees as noted by the camera trap (obtained
by the number of times an animal appeared in the timedelay sequence) was similar in the 2 years for the three
frequent frugivores (Table 1). Chital spent generally
between 2 and 8 min per visit searching for P. emblica
fruit. On one rare occasion, chital were noted to spend
Fig. 2 Activity patterns of the
three frequent frugivore species
of Phyllanthus emblica at
fruiting trees. Chital deer Axis
axis frequented fruiting P.
emblica trees largely in the daytime (0600–1800 hours), while
the Indian chevrotain
Moschiola indica and the
rodent, Black rat Rattus rattus,
visited the fruiting tree only at
night (1800–0600 hours)
230
iting has been documented for other ruminant species
(Bagchi et al. 2004; Gordon and Illius 1989; Stewart
et al. 2002). The higher diversity of frugivore assemblage
in the first year could also possibly be due to the super
abundant fruit attracting several animals that might
otherwise rarely consume these fruit (such as barking
deer and the elephant).
Through camera trapping, three species were added
to the previously known list of P. emblica’s frugivores
that was obtained from direct observations of fruiting
trees (Prasad et al. 2004). This included the Indian
chevrotain, the elephant, and the black rat. While the
elephant and the black rat were noted to remove P.
emblica fruit only on one rare occasion each, the chevrotain was a very frequent frugivore. Chevrotain visits to
fruiting P. emblica trees were only at night (though it
was photographed at other locations during the daytime
in our study site), and it was a cryptic animal that kept
to the under-growth and was never observed directly to
consume P. emblica fruit (Prasad, pers. obs.). Camera
trapping is a useful technique for studying such nocturnal or hard-to-observe frugivores. As shown by our
data, terrestrial frugivores visited fruiting P. emblica
trees once or twice per day. Using tree watches to study
frugivory for species that are primarily dispersed by
frugivores which visit fruiting trees infrequently yields
very little data (for e.g., Babweteera et al. 2007; Prasad
et al. 2004). Indeed, camera trapping is a more efficient
method for obtaining information on such infrequent
frugivory events. Further, large mammals like ruminants
are extremely wary of any signs of human presence and
our presence close to fruiting trees could deter them
from approaching trees. As pointed out by Obrien and
Kinnaird (2008) since camera traps sit unobtrusively in
the forest, they are well suited to study animals that
avoid humans or ones that might be influenced by the
presence of an observer.
We would also like to highlight that not all vertebrate
species that were photographed at fruiting P. emblica
trees consumed its fruit. It is very important to make this
distinction about confirming frugivory events, or else
our study too would have noted many more than six
terrestrial frugivores for P. emblica as reported by earlier
studies (for e.g., Babweteera et al. 2007; Beck and Terborgh 2002; Christianini and Galetti 2007; Cramer et al.
2007; Jayasekara et al. 2003; Kitamura et al. 2007; Miura et al. 1997). It is also possible to make this distinction about confirming actual frugivory events using
video camera traps. However, the available video camera traps are several times more expensive than photographic cameras, and they also have additional problems
with image resolution and power requirements (especially for nocturnal events requiring supplementary
lighting) that inhibit their implementation at larger
scales (A. Pittet, pers. obs.). Hopefully, these technical
problems with video camera traps will be resolved as
both video and battery technology continues to improve.
We would also like to add that while this study was
being implemented digital camera traps having infra-red
flashes have become more common and affordable, and
offer promising solutions to possible flash-avoidance
behavior of study animals (A. Pittet, pers. obs.).
Species like P. emblica that are mainly dependent on
large-bodied, terrestrial mammalian frugivores like
ruminants for dispersal are likely to be limited in their
ability to migrate to more suitable locations in response
to changing climates across fragmented landscapes
compared to bird-dispersed or wind-dispersed species
(Corlett 2009). In dry tropical forest sites like ours, up to
18% of the species are dispersed by ruminants (Prasad,
unpublished data). It is important to understand the
quantitative role of ruminants in the dispersal of others
fruit species that they consume in order to identify plant
species that might need our assistance to move across
fragmented landscapes in response to changing climates.
We hope that more quantitative information on frugivory by ruminants will become available with a wider
application of our simple modification of the cameratrap technique.
Acknowledgments We wish to thank the Tamil Nadu forest
department for providing permissions to carry out this work at
Mudumalai, the Ministry of Environments and Forests for funds,
and the camera-trap development team at the Centre for Electronic
Design and Technology, Indian Institute of Science, for providing
us the camera traps. The implementation of the camera trap
technique in the field rested on the experience and knowledge of
our field assistants, especially, Dhumba, Bomma, and Krishna.
Special thanks to Karpagam Chelliah, Smita Nair, R.P. Harisha,
Nisarg Prakash, and Raman Kumar for support at various stages
of this work and to Kartik Shanker and Meena Venkatraman who
helped identify the rodents.
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BIOTROPICA 38(5): 679–682 2006
10.1111/j.1744-7429.2006.00182.x
Ruminant-mediated Seed Dispersal of an Economically Valuable Tree in Indian Dry
Forests1
Soumya Prasad2,6 , Jagdish Krishnaswamy3 , Ravi Chellam4 , and Surendra Prakash Goyal5
2 Centre
for Ecological Sciences, Indian Institute of Science, Bangalore 560012, India
3 Ashoka
Trust for Research in Ecology and the Environment, 659, 5th A Main, Hebbal, Bangalore 560024, India and Centre for Wildlife Studies,
Wildlife Conservation Society-India Program, No. 823, 13th Cross, 7th Block West, Jayanagar-560082, Bangalore, India
4 United
Nations Development Program, 55, Lodi Estate, P.O. 3059, New Delhi 110003, India
5 Wildlife
Institute of India, P.O. 18, Chandrabani, Dehradun 248001, India
ABSTRACT
Ruminant-mediated seed dispersal, an understudied process in tropical forests, was examined via Phyllanthus emblica–Axis axis interaction. A captive Axis deer
regurgitated intact P. emblica seeds after retaining them in the rumen for 7–27 h. At Rajaji National Park, a considerable fraction (22%) of deer-regurgitated P. emblica
seeds germinated, although lower than unconsumed seeds (72%). The size and strength of seeds like P. emblica might ensure that ruminants regurgitate them intact
instead of defecating them.
Key words: chital; deer; large seeds; Phyllanthus emblica; Rajaji National Park; regurgitation.
FRUITS CONSTITUTE AN IMPORTANT DIET COMPONENT of many
tropical forest ruminants (Dubost 1984, Bodmer 1991). Unlike
arboreal frugivores such as primates, birds, and bats, few studies
have examined seed dispersal by terrestrial frugivores like ruminants. Ruminants swallow fruits whole (Dubost 1984). Small seeds
(<5 mm) have been found in a viable state in abomassum contents (Bodmer 1991) and dung of tropical ruminants (Middleton
& Mason 1992). Conversely, large (>5 mm) well-protected seeds
are reported to be regurgitated intact by ruminants (Mandujano et
al. 1994, Chen et al. 2001, Prasad et al. 2004).
Ruminants are among the few known frugivores known for
large-seeded tropical fruits (Gautier-Hion et al. 1985, Corlett 1998,
Kitamura et al. 2002). Positive relationships have been found between size of ingested fruits (<5–60 mm) and body size of ruminant
consumer (5–70 kg; Dubost 1984, Bodmer 1991). It is thus likely
that size of seeds dispersed increases with size of ruminant consumer
(Gautier-Hion et al. 1985). However, there is a paucity of studies
that have examined dispersal of large seeds by ruminants.
Phyllanthus emblica Linn. (Euphorbiaceae, syn. Emblica officinalis Gærtn) is a 10–15 m tall tropical Asian tree, whose seeds are
regurgitated by deer. From October through March, P. emblica trees
are laden with globose, greenish-yellow, drupaceous fruits. The fruit
encases a hard endocarp that dehisces to release six seeds (Table 1).
These fruits, rich in vitamin C, are economically important nontimber forest products. Earlier research at Rajaji National Park (Prasad
et al. 2004) revealed that P. emblica fruits were consumed by two deer
(chital Axis axis Erxleben, barking deer Muntiacus muntjak Zimmermann), a colobine monkey (langur Semnopithecus entellus Dufresne),
and a rodent (Indian gerbil Tatera indica Hardwicke). Chital and
1 Received:
29 June 2005; revision accepted 16 November 2005.
author; e-mail: [email protected]
6 Corresponding
barking deer swallowed fallen fruits and later regurgitated seeds.
Langur dropped fruits under parent trees itself but this behavior
made fruit accessible to deer. At Rajaji, deer-regurgitated cocci (seeds
within endocarps) of P. emblica together with Terminalia belerica
Roxb. (Combretaceae), Zizyphus mauritiana Lam. (Rhamnaceae)
and Z. xylopyra Willd. occurred in clusters (4–193 cocci/group, median = 15, N = 23) at chital bedding sites (Prasad et al. 2004).
Such regurgitated cocci had little pulp and bore no signs of external
damage. For these species the cocci, which are units of primary
dispersal, function as seeds in ecological sense. These observations
prompted us to ask the following questions:
1. What proportion of ingested P. emblica seeds are regurgitated intact by deer? What is the germination success of deerregurgitated seeds?
2. Why do deer regurgitate seeds like P. emblica?
In this paper we present information from captive feeding trials and
germination experiments with P. emblica seeds. We also discuss fruit
traits of P. emblica and other ruminant-regurgitated seeds in order
to explain seed regurgitation by ruminants.
Feeding trials were conducted using captive deer at Mysore
and Yellapur to record retention time for P. emblica seeds (Oct–Dec
2002). The dimensions of P. emblica fruit used were not different
from Rajaji (ANOVA: length F = 0.40, P = 0.53, N = 25; diameter
F = 2.47, P = 0.12, N = 25). Isolated captive deer were initially fed
P. emblica pulp for 2 d to habituate them and later fed whole fruits
along with their regular diet. Isolation, feeding, and rumination
observations of deer in zoos were difficult. At the Mysore Zoo, we
could only examine the dung of one chital (female, 3–4 yr) for
fruit remains. A pet chital stag (2–3 yr) at Yellapur was hand-fed 92
P. emblica fruits in 45 min (to minimize time difference between
C 2006 The Author(s)
C 2006 by The Association for Tropical Biology and Conservation
Journal compilation 679
680
Prasad, Krishnaswamy, Chellam, and Goyal
TABLE 1.
Fruit
Cocci
Seed
Fruit traits of species whose cocci (seeds enclosed in endocarps) were regurgitated by deer at Rajaji National Park. Results are mean ± SD; figures in parentheses
are sample sizes.
Phyllanthus emblica
Terminalia belerica
Zizyphus mauritiana
Zizyphus xylopyra
Drupe, greenish yellow
6 ± 0 (14)
19.8 ± 2.3 (128)
Drupe, green
1 ± 0 (10)
29.6 ± 3.6 (50)
Drupe, reddish yellow
1.6 ± 0.5 (10)
15.0 ± 2.1 (50)
Drupe, green
3 ± 1 (16)
21.8 ± 1.4 (50)
Diameter (mm)
Mass (g)
23.0 ± 2.5 (128)
7.2 ± 2.2 (128)
24.0 ± 3.7 (50)
12.0 ± 5.2 (50)
16.3 ± 2.0 (50)
2.6 ± 0.9 (50)
22.3 ± 2.3 (50)
7.1 ± 2.1 (50)
Length (mm)
Diameter (mm)
Mass (g)
10.8 ± 0.7 (50)
9.1 ± 0.9 (50)
0.5 ± 0.1 (25)
23.5 ± 2.7 (50)
14.6 ± 2.5 (50)
2.8 ± 1.2 (50)
10.1 ± 1.1 (50)
8.1 ± 0.8(50)
0.5 ± 0.1 (50)
16.3 ± 1.5 (50)
13.8 ± 1.4 (50)
2.2 ± 0.7 (50)
Tensile strength (kg)
Length (mm)
Mass (g)
44 ± 12 (10)
5.1 ± 0.8 (45)
0.02 ± 0.01 (45)
69 ± 8 (10)
14.8 ± 1.1 (10)
0.7 ± 0.3 (10)
73 ± 22 (10)
6.1 ± 0.5 (10)
0.05 ± 0.01 (8)
54 ± 13 (10)
11.1 ± 0.7 (10)
0.12 ± 0.02 (10)
Type, color
Number of seeds per fruit
Length (mm)
feeding of individual fruits), monitored continuously for 36 h and
intermittently for the next 4 d. Dung and regurgitated matter were
collected immediately after discharge and examined separately. Since
ungulates are known to retain seeds for very long durations ( Janzen
1982), retrials with the same animals were not appropriate.
Germination experiments were carried out on P. emblica seeds
procured from a 2 km2 intensive study area at Rajaji. The experiment had three treatments—unconsumed fruits, freshly regurgitated cocci collected from chital bedding sites, and cocci whose
pulp was removed manually. Upon dehiscence of these fruits or
cocci, 95 seeds were randomly chosen for each treatment. Seeds
were planted individually in sand-filled trays (in December 2001)
and left outside. The seeds were watered every 2 d and the number
of germinated seeds (visible radicle protrusion) was counted every
3 d for 5 mo. Germination success is defined as the proportion
of seeds that germinated. Latency is taken as period between seed
planting and germination. Nonparametric Mann–Whitney test and
G test of independence were used to examine differences between
treatments (Zar 1984). Results are presented as mean (± SD).
Diameter, length, and mass of ripe fruits, cocci, and seeds were
measured for species whose seeds were regurgitated by deer at Rajaji
(i.e., P. emblica, T. belerica, Z. mauritiana, Z. xylopyra). Samples were
randomly chosen from fruits collected within the intensive study
area. Tensile strength of cocci was measured using a universal testing
machine (PSI Sales (P) Ltd, New Delhi, India). The cocci samples
were positioned individually on a fixed plate and an upper plate was
steadily pressed down till the cocci fractured. The load applied with
the upper plate at fracture was measured electronically.
Captive chital swallowed P. emblica fruits and did not spit
fruits, cocci, or seeds while feeding. The feeding trial at the zoo
indicated that chital regurgitated P. emblica fruits within the first
24 h. Precise estimates of rumen-retention time were obtained with
the pet chital at Yellapur. This animal regurgitated 78 percent of 92
fruits it was fed as intact cocci. This occurred between 7 and 27 h
after feeding (2.8 ± 4.0 cocci/h), with a peak between 10 and 18 h
(7.1 ± 4.1 cocci/h). The cocci remained in the rumen for an average
14.23 (± 4.15) h. Fruits were brought back into the mouth by
antiperistaltic movements, re-chewed and cocci regurgitated mostly
when the animal was resting (62%). The regurgitated cocci formed
a loose cluster around the animal, bore no signs of external damage
and released intact seeds. No seeds were regurgitated separate from
cocci. Dung of neither the pet chital nor the zoo animal, examined
for 2 and 5 d after feeding fruits, respectively, contained P. emblica
cocci or seed remains. The remaining cocci (22%) may have been
digested beyond recognition.
At Rajaji, germination success of unconsumed and pulpremoved seeds (72% and 58% of 95 seeds respectively) did not
differ significantly (G = 3.17, 0.10 > P > 0.05). Germination
success of deer-regurgitated seeds (22% of 95 seeds) was lower than
both unconsumed (G = 60.16, P < 0.0001) and pulp-removed
seeds (G = 36.30, P < 0.001). This result implies that rumen
retention, rather than pulp removal, negatively influences germination. Deer-regurgitated and pulp-removed cocci needed 1–2 d
to dehisce, while unconsumed fruits required 3 mo to dry and release seeds. The latency period of deer-regurgitated (105 ± 14 d)
and pulp-removed seeds (97 ± 10 d) did not differ significantly
(Mann–Whitney Z = 0.04, P > 0.05). Latency period of unconsumed seeds (131 ± 2) was greater than both deer-regurgitated
(Z = 5.33, P < 0.001) and pulp-removed (Z = 8.63, P < 0.001).
In this case, pulp-removal by frugivores, rather than rumen retention, seemed to affect germination time.
All species whose seeds were regurgitated by deer at Rajaji
were trees or large shrubs with drupaceous fruits having a fibrous
mesocarp. The thick, hard cocci that were regurgitated were all
over 10 mm in length, and 8–17 times the mass of seeds enclosed
(Table 1). Compared to these large cocci that are regurgitated intact,
small (<5 mm) seeded grass and herb species are reported to survive
in ruminant dung (Middleton & Mason 1992, Pakeman et al.
2002). It has often been suggested that large seeds consumed by
ruminants suffer extensive mechanical damage during mastication
Short Communications
(Bodmer 1991, Mouissie et al. 2005). With over 75 percent of
fruits fed to the captive chital being regurgitated as intact cocci, P.
emblica cocci appeared to be strong enough to prevent mechanical
damage during repeated mastication by deer. The cocci of other
deer-regurgitated species from Rajaji were stronger than P. emblica,
needing over 50 kg of force to fracture.
There were no P. emblica cocci or seeds in the dung of captive
deer, implying that deer disperse P. emblica solely through regurgitation. Rumen-retention lowered germination success of P. emblica
seeds, which is in agreement with results from feeding experiments
with other ruminants ( Janzen et al. 1985, Cosyns et al. 2005,
Mouissie et al. 2005). Yet, a considerable fraction of P. emblica seeds
survived rumen retention at Rajaji (22% of 95 seeds), implying
some probability of seeds surviving rumen passage. Retention-time
for P. emblica seeds in chital rumen (7–27 h) lies within the range of
recovery times from dung reported for various diets (12–79 h) for
white-tailed deer Odocoileus virginianus (Vellend et al. 2003) and
seeds fed (5–90 h) to dama deer Dama dama (Mouissie et al. 2005).
The daily home range of chital in dry tropical forests (14–20 ha,
Mishra 1982) is similar to that of white-tailed deer, which has been
shown to generate seed shadows with radii up to 3 km (Vellend
et al. 2003).
Movement of chital during the 1–2 d period when seeds remain in the rumen can aid long-distance dispersal of P. emblica
seeds, if seeds survive. Large-bodied frugivores like ruminants, with
their large home ranges and longer gut retention times are likely
candidates for long-distance dispersal of several plants (Vellend
et al. 2003, Cosyns et al. 2005, Mouissie et al. 2005). As with
other plants that produce economically important nontimber forest
products, recruitment of P. emblica is very low in intensively used
forests (Shahabuddin & Prasad 2004). Long-distance dispersal by
deer might have a key role to play in recolonization of degraded
habitats by species like P. emblica. Since ruminants are more susceptible to hunting, habitat degradation, and fragmentation than
smaller frugivores (Corlett 1998), the extent of dispersal limitation
for plants like P. emblica in degraded forests remains to be examined. Further research into this plant–animal interaction would aid
management and restoration of dry tropical forests.
The size and strength of seeds like P. emblica might ensure that
ruminants regurgitate them intact. Due to a constraint on size of
particles that can pass out of the ruminant fore-stomach, which
ranges from 1–7 mm depending on feeding niche and body size of
ruminant (Demment & Van Soest 1985, Clauss et al. 2002), large
seeds like P. emblica have to be either ground down to a passable
size or disgorged during rumination. Phyllanthus. emblica and other
seeds that are regurgitated intact are probably strong enough to prevent being broken down to smaller sizes upon repeated mastication
by ruminants. Fruit traits of species regurgitated by ruminants at
Rajaji (Table 1) and elsewhere (Gautier-Hion et al. 1985, Mandujano et al. 1994, Chen et al. 2001) appear to converge toward
being green or brown, drupaceous, with fibrous pulp and strong
seed protection. Seeds that survive the molar mills and digestive
track of ruminants need not be evolutionarily molded by endozoochory by ruminants. They could have also evolved in response
681
to rodent or primate seed predation, and serendipitously become
suited for ruminant-mediated dispersal. The underlying evolutionary processes need to be examined more closely using meta-analyses
and phylogenetic approaches.
ACKNOWLEDGMENTS
We thank the Director-Wildlife Institute of India (WII), K. Ullas Karanth and Wildlife Conservation Society-India Program for
funds; WII, Uttaranchal Forest Department, Nature Conservation Foundation (NCF) for logistic support. Colleagues at WII,
NCF, Ramsharan and Meghraj Saini at Rajaji, Kumar Pushkar,
C.S.Anandlakshmi, Jayashree Prasad, Drs. Ajith Kumar and Renee
Borges for discussions, information, and support. Raman Kumar
and three anonymous reviewers for comments on earlier versions of
this manuscript.
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Assessing ecological sustainability of non-timber forest produce extraction / 235
Assessing Ecological Sustainability of Non-Timber
Forest Produce Extraction: The Indian Scenario
Ghazala Shahabuddin and Soumya Prasad
Non-timber forest products (NTFP) are extensively extracted from Indian forests,
and their role in rural and forest economies is immense. However, the long-term
ecological sustainability of NTFP extraction with respect to resource populations,
dependent animal species and ecosystem functioning has remained largely
unexamined. In this article NTFP research undertaken in India is reviewed in an
attempt to understand issues related to ecological sustainability. There is a glaring
scarcity of systematic research on ecological aspects of NTFP extraction in India.
From the few available studies, it appears that species differ in their responses to
harvest depending on the plant part extracted, natural history attributes and
harvesting techniques. However, regeneration and population densities of some
NTFP species are reported to be adversely affected by extraction. Such adverse
effects, though, cannot be attributed to NTFP harvests alone, but rather to a combination of harvests, damaging harvesting practices and accompanying anthropogenic disturbances such as fire, grazing and fuel wood collection. There is little
information on the long-term indirect effects of NTFP extraction on dependent
animal species. The available literature also indicates a disturbing trend of ecosystem simplification due to intensive forest use, including extraction of NTFP,
which may gradually lead to the weeding out of vulnerable plant species from
Indian forests. Much more research is required before it can be clearly understood
to what extent and in what ways livelihoods based on NTFP can be compatible
with biodiversity conservation.
Acknowledgements: We thank M.D. Madhusudan, Nitin Rai, Renee Borges and Sharad Lelé for
discussions and information that led to this article; Nitin Rai and Divya Mudappa for providing
valuable information from their ongoing research for this review; Ashish David, Bharath
Sundaram, Joseph Vattakavan, Raman Kumar and Roopali Raghavan for help with the preparation of this manuscript. SP wishes to thank the Wildlife Institute of India for providing
facilities that supported this work. GS is grateful to Winrock International-India for their financial
support for a research project that inspired this review.
Ghazala Shahabuddin is at Environmental Studies Group, Council for Social Development, 53,
Lodi Estate, New Delhi 110 003. E-mail: [email protected].
Soumya Prasad is at the Centre for Ecological Sciences, Indian Institute of Science, Bangalore
560 012. E-mail: [email protected].
Conservation & Society, 2, 2 (2004)
SAGE Publications New Delhi/Thousand Oaks/London
236 / GHAZALA SHAHABUDDIN
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SOUMYA PRASAD
INTRODUCTION
IN THE PAST, policy makers, forest economists and foresters have viewed forests
primarily as a source of national revenue with timber as the dominant product
(Tewari 1994). However, in an era of fast-declining old-growth forests, great significance is attached nowadays to forest products besides timber, that is, nontimber forest products (NTFP). Such forest products range from exudates (gums,
resins and latex) to canes, fruits, flowers, seeds, seed derivatives, entire plants,
leaves, root or stem bark, fungi, meat and by-products from game animals, animals
for the pet trade, micro-organisms, and insects (Panayotou and Ashton 1992; Tewari
1994). Non-timber forest products differ from timber in terms of the greater variety
of products and of species, the shorter frequency of harvest cycles and the typically
smaller yields per unit area. However, as opposed to timber, rarely are entire plants
harvested during NTFP extraction. Additionally, unlike timber that brings profits
to state treasuries, economic benefits provided by NTFP accrue largely at the
local level (Lelé 1994; Panayotou and Ashton 1992).
It has been proposed that long-term economic benefits from sustainable NTFP
extraction might be significant enough to prevent forests from being put to more
destructive land uses such as logging, mining or ranching, and help lower rates of
tropical deforestation (Panayotou and Ashton 1992). This concept had its birth in
the struggle of the Brazilian rubber-tappers to save their forests from encroaching
ranchers and loggers during the late 1980s, which led to over 3 million ha of
forests being set aside as extractive reserves (Fearnside 1989; Nepstad and
Schwartzman 1992; Schwartzman 1992). The potential role of NTFP in forest
conservation was further supported by several studies that demonstrated that the
long-term financial return from sustainable NTFP harvest could far outweigh the
net economic benefits of timber production or conversion of the same area of land
to agricultural fields (Chopra 1997; Malhotra et al. 1992; Nepstad et al. 1992;
Peters et al. 1989; Pinedo-Vasquez et al. 1992). These developments fuelled much
excitement in the conservation community about the prospects of establishing
extractive reserves that could help maintain biodiversity while simultaneously
providing sustainable economic returns to local people and governments. Several
authors have tried to temper this enthusiasm for extractive use by pointing out
that there are many limitations to hypothetical calculations of the income derived
from an average hectare of tropical forest (Fearnside 1989; Pinedo-Vasquez et al.
1990; Sheil and Wunder 2002; Vasquez and Gentry 1989) and have questioned
the wisdom of using such valuation studies as a basis for conservation policy
(Sheil and Wunder 2002).
In India, too, the role of NTFP in rural and forest economies is immense. Economically significant NTFP have been recorded from over 3,000 plant species
extracted from forests and associated ecosystems in India (Tewari 1994). In certain
areas, NTFP have been reported to contribute up to 40 per cent of the household
income (Chopra 1997). NTFP extraction is very widespread, both within and
outside protected areas. Kothari et al. (1995), for example, reported that NTFP
Assessing ecological sustainability of non-timber forest produce extraction / 237
are known to be extracted from fourteen (36 per cent) of the thirty-nine national
parks and 104 (56 per cent) of the 185 wildlife sanctuaries in India (although
NTFP extraction is not permitted in national parks and is allowed only with special
sanction inside sanctuaries; extraction is permitted in reserved and other categories
of forests, however [Anon 1972, 1980]). In India the role of NTFP in forest conservation has gained additional impetus lately with increasing emphasis on
participatory models of forest conservation, such as joint forest management and
community-based conservation, in which NTFP extraction constitutes an attractive
economic incentive for local people (for recent reviews, see Kothari et al. 1997;
Ravindranath et al. 2000).
In the current climate of increasing support for extractivism as a tool for biodiversity conservation, the long-term ecological sustainability of such extractivism
has unfortunately remained obscure and unstudied. However, recently there has
been increasing concern globally about the impacts of NTFP extraction on populations subject to extraction, on resource users other than humans, as well as on
ecosystem functioning (Bawa 1992; Bhatnagar 2002; Lambert 1998; Shankar
et al. 1996, 1998; Ticktin 2004; Vasquez and Gentry 1989). In India, too, populations of commercially extracted species are reported to be declining in many
parts of the country, and reports of adverse ecological impacts of NTFP harvest
are becoming increasingly common (Mohan Ram, personal communication;
Murali et al. 1996; Negi 2003; Shankar et al. 1998). Clearly, a rethinking of the
linkages between forest produce extraction and ecological sustainability in India’s
forests is long overdue.
Sustainable resource use can be defined as the maintenance of an undiminished
flow of benefits from the resource to its users over time (Lelé 1994). However,
this deceptively simple definition is complicated by the fact that the various different benefits provided by any forest resource to its different users are generally not
simultaneously maximised (ibid.). Homma (1992) proposed that if sustainability
of NTFP extraction is to be achieved from the point of view of all resource users,
then social, economic and political structures at local, regional and national levels
need to be managed in such a way that NTFP extraction is lucrative over time,
yields social improvement for its participants, and does not compromise ecological
and agronomic equilibrium. In purely ecological terms, extraction can be considered sustainable if the harvest has no long-term deleterious effect on the
reproduction and regeneration of populations being harvested in comparison to
equivalent non-harvested natural populations, and if the harvest has no discernable
adverse effect on other species in the community, or on ecosystem structure or
functioning (Hall and Bawa 1993). We confine ourselves to discussing the
ecological aspects of sustainability only, while recognising that forest management
policy has to equally critically take into account political, economic and cultural
contexts of forest use. In this article we review NTFP research done in India in an
attempt to answer the following specific question: What are the possible impacts
of NTFP extraction on target populations, on dependent animal species, and on
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ecosystem structure and function? Since the literature on hunting in India is still
very limited, we confine ourselves to NTFP of plant origin.
IMPACTS
OF
NTFP EXTRACTION
ON
RESOURCE POPULATIONS
NTFP harvests may affect plant populations at two different levels: first, at the level
of the individual, on vital rates such as growth and reproductive capacity; and,
second, at the level of the population, which manifests in its demographic structure
and long-term dynamics. The direct effects of intensive forest produce collection
may include decline in productivity, density and/or regeneration of the targeted
plant species, depending on the part of the plant that is utilised (Cunningham
2001; Peters 1994; see Figure 1 for a synopsis of the possible biological effects of
NTFP harvest).
Figure 1
Possible Ecological Impacts of NTFP Extraction
An important approach to studying impacts of NTFP harvest on natural populations has been to examine whether there is sufficient regeneration of the resource
population, particularly for tree species (Hall and Bawa 1993). The underlying
rationale is that a continuously regenerating population will ensure that the resource
is not depleted and there will be a continuous flow of benefits to people dependent
on these resources over time. However, assigning cause and effect between resource use and observed regeneration is not straightforward for several reasons.
First, it is difficult to locate control (unharvested) populations that differ from
treatment (harvested) populations in every respect except for intensity of harvest.
This is because anthropogenic factors such as grazing, fuel wood use, fire management, hunting, timber cutting and NTFP extraction are often correlated.
Assessing ecological sustainability of non-timber forest produce extraction / 239
For example, in tropical dry forests in India, low-intensity fires that are lit for the
purpose of making NTFP collection easier cause damage to seedlings and saplings
of several tree species (Saha 2002). Lack of regeneration could also be due to
other environmental stresses, such as herbivore damage, presence of invasive
plant species, pathogens and resource deficiencies, whose effects may be enhanced
under certain anthropogenic disturbances. Therefore, an observed lack of adequate
regeneration of a target population could be due to one or a combination of these
factors. Second, defining how much regeneration constitutes ‘adequate’ regeneration is not straightforward due to differences in vital rates and population parameters across species and across ecosystems.
The most commonly adopted approaches to overcome these practical difficulties
in designing studies to assess impacts of NTFP harvest on target populations
have been, first, to compare regeneration and girth-class distributions (proportion
of individuals belonging to different size or age classes) of NTFP species at sites
subject to different harvesting intensities. Typically, an inverse J-shaped curve
that shows very high proportion of seedlings and saplings in relation to adult
trees is considered to represent a healthy regenerating population. Sharply declining
densities of individuals in successively larger size (or age) classes produces the
inverse J-shaped girth-class distribution for a species. A second step in this approach is to compare girth-class distributions of harvested NTFP and non-NTFP
species within a given forest area. However, in this case there may be the danger
of glossing over important differences in natural history attributes of different
species. Another approach is to use population modelling to assess impacts of
various extraction pressures on population structure using empirically determined
estimates of growth and reproductive rates. There have also been attempts to
quantify genetic variability and reproductive fitness of populations subject to
different intensities of harvest. Use of such measures offers insights into impacts
of harvests on processes such as pollination, dispersal and gene flow within populations, and thus relate to long-term evolutionary consequences of harvest.
A large number of studies on the linkages between NTFP harvest and resource
regeneration have emerged from long-term research being carried out at a single
site in south India—the Biligiri Rangaswamy Temple (BRT) wildlife sanctuary
(Murali et al. 1996; Shankar et al. 1998; Sinha 2000). Shorter-term studies have
also been carried out at sites in central (Koliyal 1997; Pant 2003) and north-west
(Prasad 2001) India. All these studies have focused partly or exclusively on Phyllanthus emblica. Some studies at BRT have also examined Phyllanthus indofischeri, Strychnos potatorum, Terminalia bellerica and T. chebula (Shaankar et
al. 2001; Shankar et al. 1998; Sinha 2000), and Koliyal (1997) has studied Madhuca
latifolia and Buchanania lanzan in central India. A recently concluded study,
possibly the most comprehensive so far, has investigated the population status of
Garcinia gummi-gutta in differently managed sites in wet evergreen forests of
the Western Ghats (Rai 2003; see also Rai and Uhl in this issue). For all other
NTFP such as Shorea robusta, Diospyros melanoxylon, Boswellia serrata, Sterculia
urens and Cordyceps sinensis, literature that exists on demographic aspects
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of harvested populations is largely anecdotal in nature (see Table 1 for details of
uses and parts extracted of these and other plant species mentioned in this article).
Table 1
Details of Parts Extracted and Uses of NTFP Plant Species
Species
Part extracted
Uses
Phyllanthus emblica (Euphorbiaceae)
Fruit, seed
Phyllanthus indofischeri
(Euphorbiaceae)
Madhuca latifolia (Sapotaceae)
Fruit, seed
Flower, fruit
Buchanania lanzan (Anacardiaceae)
Sida rhombifolia (Malvaceae)
Sida cordifolia (Malvaceae)
Asparagus racemosus (Liliaceae)
Dioscorea bulbifera (Dioscoreaceae)
Hemidesmus indicus (Asclepiadaceae)
Decalepis hamiltonii (Asclepiadaceae)
Strychnos potatorum (Loganiaceae)
Garcinia gummi-gutta (Guttiferae)
Fruit
Whole plant
Whole plant
Bulbs (root)
Tubers (root)
Rhizome (root)
Rhizome (root)
Fruit
Fruit
Shorea robusta (Dipterocarpaceae)
Leaves, seed
Diospyros melanoxylon (Ebenaceae)
Leaves, fruit
Boswellia serrata (Burseraceae)
Resin
Sterculia urens (Sterculiaceae)
Gum
Cordyceps sinensis
Chlorophytum tuberosum baker
(Liliaceae)
Rauvolfia serpentina (Apocynaceae)
Syzygium cumini (Myrtaceae)
Artocarpus spp. (Moraceae)
Whole plant
Tuber (root)
Fruits in pickles; seed extracts in
hair oil and medicines
Fruits in pickles; seed extracts in
hair oil and medicines
Flowers used for liquor; oil extracted
from seeds; seed powder used as flour
Fruits edible
Medicine
Medicine
Medicine
Medicine
Medicine
Medicine
Ripe fruit edible; used in medicine
Rind used as souring agent, and in
medicine
Used for plates; seeds used for oil
extraction
Leaves used in cigarette making;
fruits edible
For religious end products:
frankincense and myrrh
For emulsifiers, adhesives, fixatives
and laxatives
Medicine
Medicine, edible
Tuber (root)
Fruit
Fruit
Medicine
Edible
Edible
Many studies have found lowered regeneration of NTFP species at heavily
harvested sites when compared to areas subject to lower harvesting pressures
(Koliyal 1997; Murali et al. 1996; Pant 2003; Shaankar et al. 2001; Shankar et al.
1998; see Figure 2 for a hypothetical example). Some of these studies also report
that regeneration of NTFP species was lower than that of non-NTFP species at
heavily harvested sites (Murali et al. 1996; Shankar et al. 1998). The latter two
studies also report overall low numbers of saplings in the smallest size class all
over the BRT sanctuary, whether in high-intensity or low-intensity harvest sites,
indicating extremely low rates of regeneration of not just NTFP, but several other
tree species. For Phyllanthus emblica, the most widely studied species across the
country, a number of studies have reported low seedling and sapling densities in
Assessing ecological sustainability of non-timber forest produce extraction / 241
intensively harvested areas compared to areas subject to lower extraction pressures
(Koliyal 1997; Murali et al. 1996; Padmini et al. 2001; Prasad 2001; Shankar et
al. 1998). In sharp contrast to these studies, Rai (2003) did not find any statistical
difference in ratios of G. gummi-gutta seedling densities (<0.5 m in height, the
smallest size class) to large trees (having greater than 20 cm girth at breast height
[gbh]) between low-intensity and high-intensity harvest. There may, however, in
fact be some differences in densities of saplings (>0.5 m height, but <40 cm gbh)
between low-intensity and high-intensity harvesting sites when standardised with
respect to tree density (see Figure 6 in Rai and Uhl in this issue).
Figure 2
Comparison of Hypothetical Girth Class Distributions of a Tree Species
between Unharvested and High-intensity Harvested Sites
Note: The girth class distribution in the unharvested site shows a typical inverse J-shaped curve
with high densities of individuals in the smallest seedling and sapling classes. Harvest of
seeds often leads to low or absent new regeneration, but similar densities of adult trees. Such
patterns have been observed for commercially important tree species in several sites in India.
Results from all of the above studies should be thought of as indicating broad
trends rather than yielding conclusive results, given typically low sample sizes.
The lack of control sites (where there has been no harvest), especially in comparable physiographic conditions, necessitates comparisons between many sites across
a gradient of harvest histories and intensities. Use of distal and proximal sites as
surrogates for low-intensity and high-intensity harvesting situations respectively
(as in Murali et al. 1996; Shaankar et al. 2001; Shankar et al. 1998) is also problematic, given that foraging radii and routes may change from year to year. Additionally, some studies mentioned (for example, Rai 2003) intensive harvesting had
begun only a few years before the data was collected. Impacts of harvesting on
242 / GHAZALA SHAHABUDDIN
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regeneration of the resource species may not be detected in such a short period.
As indicated by results from a recent study across twenty-three sites in the Amazon
(Peres et al. 2003), both history and intensity of harvests are major determinants
of population structure of harvested species. Peres et al. (ibid.) found that juvenile
recruitment was severely affected in populations subject to persistent harvests.
Another approach to assess impacts of harvests and other anthropogenic factors
on resource populations is the use of matrix models used to model population
dynamics (Boot and Gullison 1995). The validity of such models is critically
dependent on accurate field estimation of plant growth rates and reproductive
rates, which are likely to be very variable both spatially and temporally, necessitating extensive sampling in space and time (Freese 1997; Peters 1994). In India
there have been few attempts to establish limits on harvests using such population
modelling approaches. Shankar et al. (1996) have tried to define sustainable yield
for P. emblica extraction at the BRT sanctuary, but their attempt was inadequate
due to lack of sufficient data. And Murali and Srinivasulu (2000) modelled effects
of different rates of extraction on plant densities of some medicinally important
herb species at the BRT sanctuary: Sida cordifolia, Sida rhombifolia, Dioscorea
bulbifera, Asparagus racemosus, Decalepis hamiltonii and Hemidesmus indicus,
using an empirical approach (see Table 1 for uses of these plant species). In most
cases, more than 25 per cent extraction was found to be detrimental to local plant
populations. The most comprehensive work on these lines was carried out by Rai
(2003) who quantified growth rates and reproductive capacity of G. gummi-gutta
trees. For this population, even very high levels of harvest of seed (up to 90 per
cent) were demonstrated not to affect the future structure of the resource population
(ibid.). However, a sharp decline in tree populations was projected beyond 90 per
cent seed harvest. As model parameters can vary substantially between years
depending on climatic conditions and other ecological factors, model projections
as in Rai (ibid.), and Murali and Srinivasulu (2000) should be treated as tentative.
Further work, taking into account temporal and spatial variability, is required to
substantiate findings such as these.
Genetic studies offer opportunities to examine long-term evolutionary implications of chronic harvesting on resource populations. The few genetic studies of
NTFP species from India are largely suggestive and are constrained by being
limited to a few loci. Shaanker et al. (2001) found no significant differences between populations of Terminalia bellerica and T. chebula for genetic diversity
parameters across a disturbance gradient (control, moderate and high) at the BRT,
but there were some appreciable differences between the disturbance levels as
seen with principal component analyses (PCA) for both species. This suggests
that extraction may have altered the genetic structure of these two plant populations.
For P. emblica, Padmini et al. (2001) found that extraction of fruits may lead to
loss of reproductive fitness and genetic differentiation of populations across disturbance gradients at two sites (BRT and Mudumalai wildlife sanctuary). While
several seed and seedling features were significantly affected by disturbance at
both sites, genetic diversity decreased with increasing disturbance only at one of
Assessing ecological sustainability of non-timber forest produce extraction / 243
the sites (Mudumalai). Populations close to human settlements tended to cluster
together and were separated from those farther away within each site and on
pooling samples (ibid.). This suggests that P. emblica populations are affected
nearly similarly by anthropogenic pressures at these two sites.
Many studies have indicated that damaging harvesting methods affect resource
populations equally or more than the actual removal of plant parts. Sinha (2000)
found that fire had a larger effect on population growth rates than actual harvests
for Phyllanthus emblica and P. indofischeri at the BRT. Traditional non-destructive
methods are increasingly being replaced by less time-consuming and less labourintensive methods in India, both due to increase in demand for NTFP and the
open-access nature of forest land (see Rai 2003). Removal or damage of reproductive individuals may have the greatest impact on population growth in slowgrowing tree species. Sinha and Bawa (2002) found that populations of P. emblica
and P. indofischeri were more sensitive to destructive harvesting (for example,
lopping of branches) than to fruit harvest per se. They found that such harvesting
techniques reduced fruit production the following year for these species. Rai (2003)
similarly found that population growth was more sensitive to adult tree mortality
caused by lopping than to harvest of G. gummi-gutta fruit in wet evergreen forests
of the Western Ghats. Koliyal (1997) and Pant (2003) have also reported destructive
harvesting practices in deciduous forests of central India with branches, and
sometimes whole trees, being cut down to obtain fruits.
Effects of extraction on local population densities of extracted plant species,
particularly tree species, may be expected to manifest only in the long term. However, in several cases, adverse effects have already been observed on adult populations of plants. Shankar et al. (1998) found that NTFP species exhibited greater
densities and basal areas in sites subjected to relatively lower extraction pressures
compared to heavily extracted sites. Anecdotal information exists from other areas,
though this needs to be substantiated by systematically collected long-term data.
Several commercially important species are likely to become extinct in Sheopur
forest division in Madhya Pradesh, including Boswellia serrata, Sterculia urens
and Phyllanthus emblica (Bhattacharya and Hayat 2003). Several species of
rhododendrons in Sikkim are thought to be under threat of extinction from overexploitation for fuel wood and incense manufacture (Singh et al. 2003). Similarly,
surveys of Cordyceps sinensis in Uttaranchal, a composite fungus larva organism
formed by the parasitisation of a moth caterpillar by fungus, indicate that the
population of this species in Uttaranchal is visibly declining even on an annual
basis due to the pressure from human extraction (Negi 2003). Interviews with village groups managing central Indian forests in Gadchiroli, Maharashtra, indicate
that there is a general perception of population decline in Sterculia urens due to
over-exploitation of gum (Shahabuddin, personal observation). Rapidly declining
densities of Acacia catechu, a species whose bark has been harvested intensively
for katha manufacture during the last few decades, has been reported from the
Aravalli hills of north-western India (Mohan Ram, personal communication).
Availability of medicinal plants such as Chlorophytum tuberosum and Rauwolfia
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SOUMYA PRASAD
serpentina is also under serious threat in central Indian forests due to overexploitation (Boaz, undated).
IMPACTS
ON
OTHER SPECIES
The removal of a given plant product from a forest may also adversely affect
dependent animal populations, the effects of which could then reverberate through
forest ecosystems as many of the affected species could be significant pollinators
or fruit dispersers (see Terborgh 1998). With ever-increasing habitat loss and fragmentation, NTFP resources could currently be of critical importance to the survival
of threatened populations of animals, particularly those sourced from keystone
species (ibid.). The degree of specialisation of animal species with respect to
specific plant products would determine, to a large extent, the degree of impact.
In the long term, it is possible that large-scale export of nutrients from these forests
in the form of various plant parts may be unsustainable, though these effects are
rarely studied (Salafsky et al. 1992). Though it is well-recognised that humans
share forest resources with a large number of other species, there have been few
studies to date looking at sustainability of NTFP extraction from the point of
view of other resource users (but see Bakuneeta et al. 1995; Chapman and
Onderdonk 1998; Lambert 1998; Prasad 2001). Could extractive activities become
unsustainable to these other resource users?
Extraction of forest produce might degrade the quality of the habitat of dependent
species due to reduction in quantity of available food. Prasad (2001) investigated
impacts of fruit harvest on the frugivore community of P. emblica at Rajaji National
Park in north-west India. At Rajaji, P. emblica fruits were con-sumed by four
mammals—langur (Semnopithecus entellus), chital (Axis axis), barking deer
(Muntiacus muntjac) and Indian gerbil (Tatera indica). For these frugivores,
extraction of fruits by people represented loss of a food resource (ibid.). Current
knowledge of the ecology of certain frugivorous species suggests that loss of
food resources due to NTFP extraction might limit wildlife populations. For example, Green and Minkowski (1977) observed that in the shola forests of the
Western Ghats, harvesting of the scarce Artocarpus spp. fruits deprived the liontailed macaque (Macaca silenus) of one of its most important year-round foods.
Kumar (1985), from a year-long study of the lion-tailed macaque, found that
removal of selected products like fruits of Artocarpus hirsuta, Syzygium cumini
and cane could drastically alter food resources of this species, even if done rarely.
In particular, extractive uses have the potential to limit food resources of animals
like the brown palm civet (Paradoxurus jerdoni), which are heavily dependent on
seasonal and spatially patchy resources such as fruits (Herrera 1982; van Schaik
et al. 1993). Fruit resources constitute a large fraction of the diet of the brown palm
civet (a mammal endemic to the Western Ghats) in all seasons (Mudappa 2001).
For the thirty-four plant food items identified to species level in the diet of the
brown palm civet by Mudappa (ibid.), we found that fourteen (29 per cent) had
Assessing ecological sustainability of non-timber forest produce extraction / 245
uses listed for fruit or seeds, twenty-three (68 per cent) had parts other than fruit
or seed used by people and only eight (23 per cent) had no uses listed in the volumes
of Wealth of India (Anon 1976). It remains to be examined whether such human
uses have actually limited population sizes and distribution of the brown palm
civet or other dependent animal species.
Rai (2003), however, has noted that there may not necessarily be competition
between frugivores of G. gummi-gutta and fruit harvesters if fruits are picked off
the ground after natural fall rather than directly harvested from trees. Most recorded
frugivores are arboreal and likely to consume pulp from fruits on the tree itself
while only the hard, uneaten rind, which is left on the ground, has market value.
Nonetheless, while traditionally G. gummi-gutta was harvested by picking the
rind off the ground, large-scale commercial extraction mostly involves collection
of fruits from trees (Balachandra Hegde, personal communication).
Of special concern within protected areas in India is the association of illegal
hunting with legitimate forest-based activities such as NTFP extraction (A.J.T.
Johnsingh, personal communication; Madhusudan and Karanth 2000; Prasad
2001). It has often been argued that permitting NTFP extraction in protected areas
might lead to such collateral damage, which could take a heavy toll on wildlife
within these areas. Thus, in areas designated for wildlife protection, permitting
NTFP harvests might have other far-reaching consequences, even for species that
are not dependent on the resource directly, in ways that have yet to be understood.
Effects on Community Composition and Ecosystem Functioning
Declining densities and regeneration of extracted species can lead to substantial
changes in structure of forest communities. Such changes might be reflected in a
shift in the composition of plant communities as well as a lowering of diversity,
biomass and net primary productivity of these ecosystems. A growing body of
literature based on studies conducted in various parts of India indicates that intensive human use of forests is leading to a gradual change in forest ecosystems
characterised by species impoverishment and, consequently, ecosystem simplification. Species exploited intensively for their parts, those vulnerable to fire, invasive
species, grazing and repeated lopping, those dispersed exclusively by animals, or
those germinating in specific micro-climatic and soil conditions, appear to be at
risk and may be getting ‘weeded’ out from intensively exploited forests (Daniels
et al. 1995; Ganeshaiah et al. 1998).
Though there are no studies that have focused exclusively on impacts of NTFP
harvest on community composition or ecosystem function, extractive uses have
been listed as one of the anthropogenic pressures that has brought about these
changes (ibid.). As an example, it has been observed that deciduous forests are
slowly being taken over by increasing density of scrub forest species at the BRT
sanctuary (ibid.). Similarly, it has been documented that evergreen and deciduous
species in wet evergreen forests of the Western Ghats are giving way to species
246 / GHAZALA SHAHABUDDIN
AND
SOUMYA PRASAD
that have features adapted to arid climates (Daniels et al. 1995). Ganeshaiah et
al. (1998) and Pant (2003) found that long-term anthropogenic pressures had led
to animal-dispersed species becoming less common, and wind-dispersed plant
species increasing in density, resulting in a shift in phyto-sociological attributes
of plant communities. In the Shorea robusta-dominated forests of south-western
West Bengal, it is feared by many that intensive extraction of biomass over the
last two centuries may have converted originally multi-species Shorea-dominated
forests to almost mono-cultural stands (T.K. Mishra, personal communication;
Palit 1999; Shahabuddin 2002). Throughout this region, regeneration of Shorea
robusta is very low and is regarded as a serious problem today. Quantitative studies
have shown that areas subject to lower levels of extractive pressures were more
diverse in terms of tree species and had lower densities of S. robusta in proportion
to other species (Das et al. 2000; Lal et al. 1993; Mishra and Banerjee 1997;
Ramnarayan et al., undated). As mentioned earlier in this article, where overall
poor rates of regeneration of several tree species have been recorded through
extensive sampling at the landscape level at BRT (Murali et al. 1996; Shankar et
al. 1998; see Figure 2). These observations portend a highly species-poor scenario
in the future for regions subject to intensive harvests. Only long-term vegetation
studies in intensively used forests can help quantify some of these changes thought
to be underway in forest ecosystems on a large scale.
CONCLUSION
The current review indicates that there is scant, mostly anecdotal, information on
the ecological sustainability of extraction of the hundreds of NTFP in India, obtained from various plants. Only a few species of trees have been studied quantitatively and over adequate spatial and temporal scales for discerning possible
harvesting impacts; there are next to no studies on herbs and shrubs.
The available literature indicates that species and populations differ in their
responses to harvesting, as would be expected. The degree to which plant populations are adversely affected by harvesting depends on natural history attributes
of plant species, harvesting techniques adopted, the extent of extraction and the
plant part used (see also Rai 2003; Ticktin 2004). However, it is also clear that
several NTFP plant species in India may be subject to unsustainable use as indicated
by lowering of adult population densities and reduced regeneration ability, even
inside protected areas. In many cases, it is likely that forest use practices that
typically accompany harvesting activities, such as grazing, fires and tree cutting,
and accompanying micro-climatic and soil changes, may have as much or greater
impact on regeneration of resource populations as does actual removal of plant
parts. Certainly, taken together, harvesting of plant parts and accompanying forest
use practices are having an overall detrimental effect on plant regeneration and
densities of studied NTFP species in many sites. There is also evidence from the
published literature that NTFP extraction and accompanying forest use practices
Assessing ecological sustainability of non-timber forest produce extraction / 247
may be leading to overall forest ecosystem simplification due to selective extinctions of plant species in the long term.
Recent ecological studies on frugivorous and other animal species indicate
that NTFP extraction may represent a significant loss of food resource and changes
in habitat structure for dependent animal species. A near absence of long-term
quantitative studies makes it difficult to link population declines of dependent
animal species, if any, with NTFP harvests. Nonetheless, from current knowledge
of plant–animal linkages in tropical forest ecosystems, we infer that collection of
plant parts is particularly likely to have an impact on specialist animal species.
The current review thus indicates that in the process of planning for forest use,
we need to not only recognise potential impacts of NTFP extraction on target
species, but also on other resource users of the same resource, as well as on ecosystem processes. A more rigorous information base on important NTFP species
throughout the country needs to be built up before extractive uses or interventions
can be planned in Indian forests, especially in areas designated for wildlife
protection. Much more research is required before it can be clearly understood to
what extent and in what ways livelihoods based on NTFP can be compatible with
biodiversity conservation.
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