The effects of plant density upon several determinants of reproductive
success in Cistus landanifer (Cistaceae).
Daniel B. Metcalfe
M. Sc Biodiversity & Conservation 2003; Project Dissertation. School of Biology, University of Leeds.
Summary
1. C. landanifer is a self- incompatible shrub which forms a major component of many
Mediterranean habitats. It typically occurs in large, dense mono-species stands, though in
some areas individuals may be more sparsely distributed. The plant produces prominent
flowers which attract a wide diversity of pollinators. A proportion of these flowers
subsequently develop into fruits which are subject to parasitism and seed predation.
2. C. landanifer populations were surveyed at three sites. Information relating to plant
pollination success, reproductive effort and fruit parasitism was recorded. This data was
plotted against plant density in order to determine density-dependant patterns of
reproductive success.
3. Overall, pollination success declined significantly as the distance to the nearest cospecific increased. Reproductive effort and fruit parasitism showed the opposite pattern.
Pollination success and reproductive effort per fruit increased with fruit height, but only in
dispersed plants.
4. Measures of reproductive success were the product of a significant interaction between
pollination success and reproductive effort. This means that dispersed plants were able to
compensate for reduced pollination success by increasing reproductive effort.
5. These results indicate that overall reproductive success is the accumulated result of
several different processes which may each respond to plant density in different ways. In
order to effectively manage plant populations it is necessary to understand in greater detail
the dynamic interactions between these processes.
Introduction
A large number of studies have been
conducted examining the effects of population
density upon population size and growth. At
high densities increased competition for limited
resources may drive population size down to an
equilibrium level (e.g.: Nicholson 1933, 1957,
Smith 1935, Lack 1954). This inherent stability
could be disrupted, however, if population size
falls too low (Allee et al. 1949, Allee 1951). In
this scenario, low density or isolated
populations suffer from a decline in
reproductive success because of the difficulties
associated with finding suitable mates. Selfincompatible plants are ideal test subjects for
this area of research because, being sessile,
they are both particularly vulnerable to density
effects (since they are not directly able to find
mates themselves) and they are relatively easy
to locate and monitor.
Models of pollinator foraging indicate that
plant population density, by constraining
frequency and duration of pollinator visits, is
likely to have a crucial role to play in
1
individual plant pollination success (e.g.:
Zimmerman 1981). This theory is supported by
a substantial body of field research covering a
range of habitats, plants and pollinators
(Feinsinger et al. 1986, Kunin 1992, 1997,
Lamont 1993, Groom 1998).
However,
pollination success is not the only densitydependant component of overall reproductive
success. Also important is pre-pollination
reproductive effort, and post-pollination seed
predation. There has been relatively little
research into how population density affects
these two processes, and what the
repercussions are for plant reproductive
success. Where research has been conducted,
the results are often conflicting. For example,
despite early model predictions that
herbivores/predators should favor dense host
populations (Root 1973, Atsatt & O’Dowd
1976), subsequent studies have shown that
responses to host density are highly speciesspecific (Kunin 1999, and references therein).
Kunin (1999) even found disparate responses
between the early and late instar stages of the
same insect species (Tyria jacobaeae).
Plants actively respond to changes in their
environment by adjusting the quantity of
resources which they allocate to various organs
(Mooney & Winner 1991, Dale & Causton
1992, Reynolds & D’Antonio 1996). The type
of limiting resource can have a substantial
effect upon the pattern of resource partitioning
within plants. For example, plants in a nutrient
limited environment may allocate a greater
proportion of their resources to root production
(Chapin 1980, Smart & Barko 1980). This
change in the pattern of allocation may come at
the expense of other activities such as leaf,
flower, fruit and ovule production. One of the
most common reasons for changes in the
amount of resources available to each plant is
the local population density of co-specifics
(e.g.: Meekins & McCarthy 2000). Density
affects the level of competition and increases
the chance that resource limitation will occur.
Previous studies have found some evidence for
changes in the level of resource allocation to
reproduction with plant density (Snell & Burch
1975, Hickmann 1977, Mustajarvi et al. 2001)
but the results are conflicting, and it has proved
difficult to control for site variation in terms of
other physical resources (e.g.: light, water and
nutrients). It is possible that these responses are
at least partly due to density-dependant
changes in the visitation rate and behavior of
pollinators (Stanton et al. 1987, Saikkonen et
al. 1998), rather than just differences in the
level of intra-specific competition.
In addition, the within-plant distribution of
reproductive effort may be set to maximize
overall reproductive success. For example, if
pollinators preferentially select flowers which
are higher up on the plant due to their increased
visibility, plants may respond to this behavior
by allocating more reproductive resources
(e.g.: flowers, ovules per ovary) into their
upper portion. Furthermore, this pattern of
allocation may change with plant density, since
density can alter the visibility of flowers at
different heights, with consequences for
pollinator behavior. This process could
potentially operate for many other factors (e.g.:
fruit parasitism, seed predation) but few studies
have documented density-dependant effects
upon plant reproductive success in such detail.
Naturally rare, sparsely populated plant
species may have evolved mechanisms to
overcome difficulties associated with isolation;
such as long-distance seed dispersal mechanisms, a persistent seed bank, specialized
plant-pollinator mutualisms, and self-compatibility (Barrett & Kohn 1991, Ayres & Ryan
1997, but see Wolf & Harrison 2001). The
most immediate risk of pollination failure and
species extinction is faced by plant species
which lack those characteristics described
above (Wilcock & Neiland 2002, and
references therein). For these species the main
problem arises when human activity artificially
imposes low population density, through
habitat fragmentation and/or degradation.
Research in this area, therefore, has important
2
implications not just for theories relating to
population dynamics but also for the design of
effective
population
management
and
conservation strategies.
This report presents the results of a study
examining the effect of plant density upon the
various determinants of reproductive success in
a self-incompatible Mediterranean shrub.
Specifically, I have addressed the following
questions:
1) Does plant density affect pollination
success?
2) Does plant density affect reproductive
effort?
3) Does plant density affect rate of fruit
predation? And finally:
4) Does plant density affect the with-in plant
distribution of the above variables?
This information cannot be considered
complete without further research into the
underlying mechanisms responsible for any
patterns observed (e.g.: pollinator behavior,
resource availability). As a field study, it also
lacks the strictly controlled conditions of the
experimental approach. Nevertheless, it
provides potentially valuable insights into the
spatial dynamics of plant reproduction, which
warrant further research.
Material & Methods
Study species
Cistus landanifer L. is a member of the
family Cistaceae, comprising five genera
(Cistus, Fumana, Halimium, Helianthemum
and Tuberaria), which forms a major
component of western Mediterranean matorral
scrub. C. landanifer tends to occur on nutrientpoor, dry soils from the south of France, and
throughout the Iberian Peninsula with its
southern-most limit in North Africa (Morocco,
Algeria). The species is easily distinguishable
because of its growth form, large flowers and
resinous exudates produced by the leaves and
stems in summer which release a characteristic
odor. The breeding system is self-incompatible,
and the generalist floral architecture and
pollen/nectar rewards attract a wide diversity of
insect pollinators (Talavera et al. 1993). The
fruiting capsules are resistant to fire, but
susceptible to fruit parasitism and seed
predation by a number of insect species
(Bastida & Talavera 2002).
Study site
The study was carried out in an area of
matorral near the town of Luz, in the Alentejo
region of Portugal. The climate is typically
Mediterranean with a hot, dry summer
(temperatures often reaching 40 C), and a
relatively wet and cold winter (90 % of the
rainfall occurring between October and April).
Three sites were chosen to represent the full
range of environmental variation within which
C. landanifer exists. Sites 1 and 2 both
consisted of an area of relatively low species
diversity open grassland and scattered C.
landanifer individuals, with occasional patches
of dense C. landanifer stands. The geology of
the area was predominantly igneous with thin
soils. Both sites were part of traditional grazing
lands where the C. landanifer stands had been
cleared in places to make way for pasture. In
contrast, the local habitat of site 3 consisted of
dispersed Cork Oak, Holm Oak and Olive trees
with a diverse shrub layer dominated by
Cistaceae, Leguminoseae and Ericaceae. Site 3
was an abandoned agricultural area with deep
soils on fine-grained sedimentary parent rock.
The area was in the process of being colonized
by a nearby dense stand of mature C.
landanifer individuals.
Intra-site
variation,
in
terms
of
environmental variables (altitude, slope, aspect,
geology, soil depth, habitat structure and
species composition), was minimized so any
patterns should be mainly attributable to plant
density differences. If any patterns persist from
site to site despite the high level of inter-site
variation this will provide robust support for
3
hypotheses
regarding
density-dependant
changes in reproductive success.
Sampling techniques
A single 2 hundred metre transect, orientated north-south, was established at each site.
Sampling was carried out by choosing numbers
from a random number table to decide the
following: distance moved along the transect,
east or west, and distance moved in the
selected direction up to a maximum of 50
metres. The plant closest to the point chosen
was sampled. Each plant sampled was marked
so that it would not be sampled again. Only
plants with three or more fruits and between
0.9-1.60 metres in height were included in the
survey. For each plant I measured distance to
the nearest co-specific (nearest neighbor
distance or ‘NND’), height, and the number of
flowers and fruits produced. Flower production
was assessed by counting the number of
persistent woody peduncles per plant.
Sampling was timed to take place after the
main period of flowering, but before seed
dispersal (June-July 2003).
Three fruits were selected from each plant
(one each from the top, middle and bottom
portion of the plant). In those plants with just
three fruits, all were included in the sample.
For each capsule, I noted its height on the plant
and any evidence of parasitism.
I also
estimated the number of seeds and
undeveloped ovules per fruit by manually
counting seeds and ovules in two locules per
fruit with a low power microscope (×20), then
taking the average and multiplying it by the
number of locules in the fruit. Fruit which was
collected but then found to be completely
parasitized was discarded and not included in
the analysis. Seed and ovule estimates were
derived from partially parasitized fruits (i.e.:
some locules remained intact) in the same way
as non-parasitized fruit.
Data analysis
Inter-plant comparisons (data plotted
against NND) utilized mean values from the
three fruits collected per plant. Within-plant
analysis (data plotted against fruit height)
considered each fruit separately. With-in plant
data was displayed in two groups: dense (NND
< 1metre and dispersed (NND > 1 metre).
Correlations between variables were carried
out using the non-parametric Spearmans Rank
method. Interactions between variables were
assessed using a univariate GLM model. Data
that did not conform to the assumptions of
parametric analysis was transformed as
necessary.
Results
A total of 60 plants, and 180 fruits were
sampled. NND, plant height and fruit height
varied between 0.15- 30.5 metres, 0.9- 1.63
metres and 0.14- 1.30 metres respectively.
Plant height is a complicating factor since it
correlates significantly with the following
variables: flower number (Fig. 1; Spearmans
Rank correlation coefficient = 0.280, p = 0.03),
seeds per fruit (Spearmans Rank correlation
coefficient = 0.254, p = 0.05) and seeds per
plant (Spearmans rank correlation coefficient =
0.273, p = 0.035). However, there is no
significant correlation between NND and plant
height (Fig. 2; Spearmans Rank correlation
coefficient = - 0.108, p = 0.413).
There were important differences between
sites for a wide variety of variables. Firstly, the
NND between plants sampled at each site
differed substantially (Site 1: mean = 7.09
metres, min. = 0.3, max. = 30.5 metres; Site 2
mean = 5.01 metres, min. = 0.3 metres, max. =
20.55 metres; Site 3 mean = 2.51 metres, min.
= 0.15 metres, max. = 10.52 metres). There
was a significant difference between the
average proportion of ovules fertilized (seed :
ovule ratio) in Site 1 and 3 (Fig. 3; ANOVA, F
= 4.981, p = 0.008). Similarly, the proportion
of flowers which developed fruit (fruit : flower
ratio) was also different between both site 1
4
Fl ower number
300
90
80
70
Percentage success
and 2 (Fig. 3; ANOVA, F = 9.676, p = 0.016),
and site 1 and 3 (Fig. 3; ANOVA F = 9.696, p
< 0.001). Inter-site differences in terms of
seeds and reproductive cells produced per plant
were not so apparent. Further analysis of site
effects will be continued below.
60
50
40
30
20
200
10
1.00
2.00
3.00
Site
100
Figure 3. Pollination success at different sites.
The red and green bars refer to the average seed :
ovule and fruit : flower ratio respectively.
0
80
100
120
140
160
180
Plant height
Figure 1. Flower number per plant as a function of
plant height. In this and all subsequent figures; red,
green and blue triangles and trend lines refer to sites 1,
2 and 3 respectively.
180
Plant height
160
140
120
100
80
1.0
1.5
2.0
2.5
3.0
3.5
NND
Figure 2. Plant size, as estimated by height, as a
function of NND. No significant effect of interplant distance is apparent.
4.0
Pollination success
For the entire sample, the fruit : flower ratio
is inversely correlated with NND (Fig. 4;
Spearman’s rank correlation coefficient = 0.555, p <0.001). This clear relationship with
NND is also apparent for other measures of
pollination success such as seed : ovule ratio
(Fig. 5; Spearmans Rank correlation coefficient
= - 0.749, p < 0.001), seeds per fruit (Fig. 6;
Spearmans Rank correlation coefficient = 0.462, p < 0.001), and total seeds per plant
(Fig. 7; Spearmans Rank correlation coefficient
= - 0.321, p = 0.012). The number of fruit per
plant was not related to NND (Fig. 8).
Only seed : ovule ratio remained
significantly negatively correlated with NND at
all of the sites when they were considered
separately. Other measures of pollination
success were correlated with NND at some
sites but not others. For example, the number
of seeds per fruit declined with NND at site 1
(Spearmans Rank correlation coefficient = 0.552, p = 0.012), but no significant pattern
was apparent at sites 2 or 3. When interaction
between factors was analyzed it was found that
seeds per fruit was the product of a significant
5
1.0
1600
1400
1200
Seeds per fruit
interaction between seed : ovule ratio and
reproductive cells per fruit (UNANOVA, F =
44.674, p < 0.001). Similarly, fruit : flower
ratio and flower number interacted to derive
fruits per plant (UNANOVA, F = 33.512, p <
0.001).
1000
800
600
Fracti on of flowers setting fruit
400
.8
200
0
.6
1.0
1.5
2.0
2.5
3.0
3.5
4.0
NND
.4
Figure 6. Average number of seeds per fruit as a
function of NND.
.2
5.0
0.0
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Figure 4. The fraction of flowers setting fruit in the
sampled population of C. landanifer as a function of
NND. NND in this and all subsequent figures is plotted
on a log scale.
1.4
Seeds per plant
NND
4.0
3.5
3.0
1.2
Fracti on of ovules fertilised
2.5
1.0
1.0
2.0
2.5
3.0
3.5
4.0
NND
.8
Figure 7. Estimated number of seeds per plant as a
function of NND. Seeds per plant has been log
transformed. This plot is the product of figures 6 and 8.
.6
.4
.2
0.0
1.0
1.5
1.5
2.0
2.5
3.0
3.5
4.0
NND
Figure 5. Average Seed : Ovule ratio as a function of
NND. Seed : Ovule ratio in this and all subsequent
figures has been Arcsin transformed
There is some evidence for within-plant
variation in pollination success: seed number
per fruit increased with fruit height in the
dispersed plant group (Fig. 10; Spearmans
Rank correlation coefficient = 0.353, p =
0.009). No such pattern was evident for the
concentrated
group
(Spearmans
Rank
correlation coefficient = 0.123, p = 0.319). No
relationship was found between seed : ovule
ratio and height for either groups (Fig. 9).
6
Indeed, irrespective of height, seed : ovule ratio
was over 95% for the majority of seeds
sampled within the concentrated group.
1800
1600
1400
2.0
Seeds per fruit
1200
1.8
Number of fruit
1.6
1.4
1000
800
600
1.2
400
1.0
200
0
.8
0
20
40
.6
60
80
100
120
140
Fruit height
.4
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Figure 10. Estimated seeds per fruit as a function of
fruit height.
NND
Reproductive effort
Figure 8. Total number of fruit per plant as a
function of NND. There is no clear densitydependant pattern
1.6
Fracti on of ovules fertilised
1.4
1.2
1.0
.8
.6
.4
.2
0.0
0
20
40
60
80
100
120
140
Fruit height
Figure 9. Seed : Ovule ratio per fruit as a function of
fruit height. In this and all subsequent figures with
fruit height on the x-axis; hollow triangles and solid
triangles indicate individuals from the concentrated
and dispersed group respectively, the dashed trendline represents the concentrated group and the solid
trend-line corresponds to the dispersed group.
For the dataset as a whole, reproductive
effort increases with NND: both total flowers
per plant (Fig. 11; Spearmans Rank correlation
coefficient = 0.434, p = 0.001) and
reproductive cells per fruit (Fig. 12; Spearmans
Rank correlation coefficient = 0.447, p <
0.001) are significantly correlated with NND.
The product of these two factors means that
there is a strong positive correlation between
the total number of reproductive cells per plant
and NND (Fig. 13; Spearmans Rank
correlation coefficient = 0.567, p < 0.001).
When the effect of site is considered
reproductive effort does not consistently
change with NND. Specifically, the plants
sampled at sites 1 and 2 tended to respond to
NND in a similar manner, compared to site 3
where there was a relatively weaker response
to NND.
Reproductive cells per fruit increased with fruit
height, in the dispersed group (Fig. 14;
Spearmans Rank correlation coefficient =
0.270, p = 0.048). There is no significant
pattern of within-plant reproductive resource
allocation in the concentrated group (Fig. 14;
7
Spearmans rank correlation coefficient = 0.177,
p = 0.150).
6.0
Reproductive cells per plant
2.6
2.4
Fl ower number
2.2
2.0
1.8
1.6
5.5
5.0
4.5
4.0
1.4
3.5
1.2
1.0
1.5
2.0
1.0
3.0
3.5
4.0
NND
.8
1.0
1.5
2.0
2.5
3.0
3.5
Figure 13. Estimated total reproductive cells per
plant as a function of NND. Total reproductive cells
has been log transformed. This plot is the product of
Figures 11 and 12.
4.0
NND
Figure 11. Total number of flowers per plant as a
function of NND. Flower number has been log
transformed
2000
2000
1800
1800
1600
Reproductive cells per fruit
Number of reproductive cells
2.5
1600
1400
1200
1000
1400
1200
1000
800
800
600
600
400
0
20
40
60
80
100
120
140
400
1.0
1.5
2.0
2.5
3.0
3.5
NND
Figure 12. Average number of reproductive cells
(seeds + ovules) per fruit as a function of NND.
4.0
Fruit height
Figure 14. Average number of reproductive cells per
fruit as a function of fruit height.
Fruit parasitism
The rate of fruit parasitism in the fruits
sampled increases significantly with NND (Fig.
15; Spearmans Rank correlation coefficient =
0.567, p < 0.001). When the dataset is divided
into two groups (NND<1 metre, and NND>1
8
metre) the mean rate of parasitism is
approximately three times higher in the
dispersed group compared to the densely
populated group. There is no significant pattern
of fruit parasitism with fruit height (Spearmans
Rank correlation coefficient = 0.062, p =
0.638).
1.2
Proportion of pa rasitized fruit
1.0
.8
.6
.4
.2
0.0
-.2
-1000
0
1000
2000
3000
4000
NND
Figure 15. Proportion of parasitized fruit per plant
sampled as a function of distance.
Discussion
Pollination success
The pattern of pollination success observed
in this study firmly supports the growing body
of evidence which suggests that, contrary to
traditional opinion (Bawa & Beach 1981),
pollination can and does limit reproductive
success in a large number of plant species
(Burd 1994, Larson & Barrett 2000). In some
respects, the results mirror those of a similar
study examining the reproductive biology of C.
landanifer (Talavera et al. 1993). Both studies
find an inverse correlation between measures
of pollination success per unit effort (fruit :
flower and seed : ovule ratio) and NND. The
main difference is that in this study the
relationship between absolute measures of
pollination success (number of seeds per fruit
and plant, and number of fruits per plant) and
NND is not so significant. This may be because
sparsely distributed plants are able to partially
offset the negative consequences of low density
(reduced pollinator visits causing reduced seed
set, increased fruit abortion) by attracting
pollinators with larger floral displays. It is
possible that this effect is not so apparent in the
study carried out by Talavera et al. (1993)
because their dataset includes many plants with
a much higher NND (maximum = 80m,
compared to 30m in this study). Perhaps with
these greater distances there is little advantage
to be gained by increasing reproductive effort.
Any effects of reduced pollinator visitation
for dispersed plants may have been exacerbated
by increased rates of ‘improper pollen transfer’
(Rathcke 1983). This reduction in pollination
‘quality’, as well as ‘quantity’, occurs if
dispersed plants are visited by generalist
pollinators which subsequently deposit
predominantly foreign pollen. Any pollen
which is picked up has very little chance of
reaching a co-specific. Even worse, when
resources are sparsely distributed pollinators
tend to spend longer at each resource patch;
switching between plants less often (Beattie
1976) and visiting more flowers per plant
(Heinrich 1979, Klinkhamer & de Jong 1990,
Cresswell 1997). This means that dispersed
self-incompatible plants could be at a further
disadvantage because more of their own pollen
is wasted on their own flowers (Ramsey &
Vaughton 2000). Pollinators in concentrated
resources behave in a way which maximizes
useful transmission of pollen- by probing a few
flowers per plant and moving often from plant
to plant.
Kunin (1993) conducted an experiment in
order to evaluate the relative importance of
quality and quantity effects under different
conditions. He concluded that ‘selfincompatible plants served by generalist
pollinators may be particularly susceptible to
difficulties’. The unsophisticated floral
architecture of C. landanifer together with
9
provision of abundant nectar and pollen
ensures that individuals are visited by a diverse
range of insect pollinators (Talavera et al.
1993, but see Herrera 1985, Brandt &
Gottsberger 1988). Many of these pollinators
are generalists which visited other plant species
present at all of the field sites surveyed
(Personal observation). Therefore it is likely
that C. landanifer will be particularly
vulnerable to changes in the density of cospecifics.
The results of Kunins’ (1993) study also
suggest that the particular mix of flowering
species in a habitat can have a major influence
over pollinator behavior. Pollinators may
change from specialists to generalists
depending upon floral composition. This could
be a complicating factor in this study, since the
abundance and species composition of
flowering plants differs between all of the sites.
Yet the fact that the plants sampled at all of the
sites showed the same general responses to
density, in terms of pollination success,
indicates that any differences are outweighed
by the similarities.
It is more difficult to know how to interpret
the within-plant distribution of pollination
success found in this study. Why only plants
within the dispersed group should experience
variation in pollination success with fruit
height is unclear. Given that reproductive effort
(reproductive cells per fruit) also increased
with height it is possible that another,
unrecorded, indicator of reproductive effort–
perhaps flower size or duration of flower
opening– increases with height. Talavera et al.
(1992) documented substantial variation in the
flower size of C. landanifer (55- 70 mm). They
also record a much longer duration of flower
opening (up to 3 days) compared with previous
studies. Therefore, the necessary variation of
reproductive effort exists for this hypothesis to
be plausible. Indeed, simply the pattern of
growth of C. landanifer could promote a
vertical stratification of reproductive effort
since the first buds usually form higher up on
the plant. If the size of flowers or duration of
opening is highest at the top of the plant,
pollinators may be attracted in greater numbers
to this larger display (Klinkhamer et al. 1989,
Ohashi & Yahara 1998) thereby increasing
pollination success.
This within-plant pattern of pollination
success was not uniform; the majority of the
plants in the concentrated group experienced
very high rates of pollination success,
regardless of fruit height. Perhaps in dense
clumps of C. landanifer the quantity and/or
quality of pollinator visitation is so high that
there is no relative advantage for flowers in any
position (i.e.: flowers in all positions, and
opening even for the minimum amount of time
achieve maximal pollination success). These
hypotheses require further research at the study
site to observe flower characteristics and
pollinator behavior in order to be validated.
Reproductive effort
Several other studies have also found that
various measures of plant reproductive effort
are positively correlated with population
density (Snell & Burch 1975, Hickmann 1977).
Mustajarvi et al. (2001) found that sparse
populations of the self-compatible plant
Lychnis viscaria had more flowers per influorescence and larger flowers compared to dense
populations. They conclude that reproductive
success may be more constrained by resource
availability in self-compatible plants, in comparison with self-incompatible plants where the
effects of pollinators may be more important.
Yet in this study it appears that both of these
factors have important effects upon the selfincompatible C. landanifer. Not only does
reproductive effort change with NND, but
these changes are able to partially compensate
for differences in relative pollination success.
For example, though there is a clear inverse
correlation between fruit number per unit effort
(fruit : flower ratio) with NND, when the effect
of reproductive effort is removed (i.e.: flower
10
number per plant) and absolute counts of fruits
per plant are plotted against NND there is no
significant trend. However, the lack of a trend
is at least partly due the underestimation of the
extent of fruit abortion in isolated plants (see
critical analysis of results, below). The
potential compensatory mechanism is clear in
the case of flower number. By increasing
flower number dispersed plants can attract
more pollinators and increase the absolute
number of flowers pollinated to such a level
that the ovaries subsequently develop into
fruits. The existence of such strategies has been
confirmed elsewhere (Klinkhamer et al. 1989,
Klinkhamer & de Jong 1990 and references
therein).
It is not clear how this process may work for
the other measure of pollination success per
unit effort: seed : ovule ratio. In this study it
appears that by increasing the number of
ovules per fruit plants can then increase the
number of ovules subsequently fertilized. This
conclusion is probably false since the only
credible factor that can affect fertilization rate
is the number of compatible pollen grains
successfully entering the ovary. More likely is
that both of these variables are affected by
another factor. One possibility, mentioned
above, is that flowers with more reproductive
cells per ovary may also tend to be larger or
open for a longer time. Larger flowers, with a
longer flowering period, can attract more
pollinators, which deposit more pollen which
in turn increases the number of ovules
fertilized. It makes sense that flowers which are
visited more often by pollinators should have
more ovules in their ovary, since it reduces the
chance that the number of pollen grains
entering the ovary exceeds the number of
available ovules. Again, these hypotheses
require additional fieldwork in order to be
tested.
Another important question is whether the
changes in effort are based upon densitydependant changes in resource availability and
competition, or if they are caused by plants at
various densities actively allocating a different
proportion of their resources to reproduction.
The former process should dominate over
relatively short distances, whilst the latter
could theoretically operate at any density. If
competition was the dominant process
operating in this study system you would
expect to find that reproductive effort initially
increases but soon levels off as NND increases
beyond a few metres. However, this is not the
pattern observed; instead effort continues to
increase at a fairly constant rate over the full
range of NND sampled. A strategy of increased
allocation by dispersed plants to reproduction
would make sense given that competition for
pollinators, in contrast to competition for light,
water and nutrients, can take place over a
relatively large spatial scale.
Nevertheless the availability of physical
resources may also have a role to play in
resource allocation to reproductive structures.
This conclusion is supported by the betweensite differences in reproductive effort with
NND. Site 3 in particular shows no significant
change in resource allocation with NND. This
effect is at least partly due to the higher density
of C. landanifer at site 3 which meant that
average inter-plant distance was lower than at
the other sites. Correlation works best when the
data points are scattered across the full range of
the x-axis, which is not the case with site 3
variables.
Fruit parasitism
As outlined in the introduction, an
increasing number of studies have found that
‘resource users’ (i.e.: herbivores, predators,
parasites) do not inevitably concentrate around
dense resources (as suggested by the ‘Resource
Concentration Hypothesis’, Root 1973). This
study adds to this body of evidence by showing
a much higher rate of fruit parasitism amongst
dispersed C. landanifer individuals, compared
to those plants in dense populations. Responses
to changes in resource density seem to depend
11
upon a variety of species-specific characters.
Kunin (1999) reviews six possible predictors of
how a resource user will respond to an
available resource: sensory biases, dispersal
biases, food requirements, diet breadth,
competitive exclusion and predation risk. He
suggests that small organisms with limited
dispersal capability, a specialized diet, which
suffers from high levels of competition from
other resource users and predation risk and
uses senses other than vision to locate the
resource, are more likely to target sparsely
populated plants.
However, in order to test these hypotheses it
is necessary to have detailed information about
the number and type of resource users found. It
was not possible to collect this data in the
current study, though Bastida & Talavera
(2002) have recorded some limited information
about seed predators in C. landanifer. Further
research at the study site would allow a more
comprehensive examination of the effects of
plant density upon fruit parasitism and other
activities (e.g.: herbivory, post-dispersal seed
predation). What is clear is that the spatial
pattern of parasitism observed further reduces
the overall reproductive success of isolated
plants.
Critical assessment of results
The key objectives of this study were to
examine whether plant density affected the
scale and distribution of various determinants
of reproductive success. In this respect, it has
fallen short of its targets for the following
reasons. Firstly, correlation does not test for a
causal relationship between factors; instead it
can only demonstrate that some form of
association exists between them. Furthermore,
it was not possible to record detailed
information about pollinators, fruit parasites
and resource availability which could have
provided a concrete causal link between NND
and the other variables recorded.
Kunin (1993) was able to demonstrate that
density, by altering pollinator visitation rates
and behavior, caused changes in seed set. Other
studies, reviewed in the introduction, have
shown a similarly direct relationship between
density and reproductive effort, and pattern of
resource use. Therefore, it is plausible that the
same causal mechanisms operate in this study
system. Nevertheless, without further research
in this area it is unwise to disregard the
possibility that the patterns observed are caused
by some other unknown factor or interaction. It
is, for example, possible that the variations in
plant density observed are the result of local
differences in resource availability. Changes in
reproductive success may reflect variation in
site quality rather than changes in competition,
pollinator visitation or seed predation. In this
study this is unlikely for a number of reasons.
Firstly, variation in C. landanifer density at
all of the sites was caused by shrub clearance.
Areas with low plant density had some years
previously supported high densities. In addition, if low plant density is caused by poor site
quality and resultant resource limitation you
would expect to find reduced reproductive
effort with NND. This is not the case in this
study where, irrespective of size, dispersed
plants tend to produce more flowers, and more
ovules per flower compared to concentrated
plants. Resource availability could only limit
overall reproductive success if the number of
seeds produced were constrained by the
number of ovules available to be fertilized.
This is not the case in the dispersed plants
sampled in this study. Site clearly does have an
effect upon the overall level of reproductive
success, but the general pattern of response of
variables at each site to NND is strikingly
similar to each other (see, for example, figure
7). The correlations derived are, therefore,
unlikely to be an artefact of site differences.
The lack of statistically significant patterns for
many variables when the sites were analyzed
separately is certainly partly due to the smaller
sample sizes. There do exist methods which
12
could separate out the influence of site
(univariate GLM models) without splitting up
the data, but it was not possible to explore them
given the time restrictions involved in data
analysis. Separate correlations for each site do
at least give a qualitative picture of the effects
of site.
I could find no evidence that C. landanifer,
at any density, was targeted by herbivores.
Though site 1 and 2 were part of grazing lands
for cattle, sheep and goats I never observed any
livestock in the vicinity of either site.
Mycorrhizal interactions may be responsible
for density-related patterns in other systems
(but see Hirrel et al. 1978), but C. landanifer is
not mycorrhizal. For these reasons densitydependant changes in pollinator visitation rates
and behavior is the most plausible explanation
for the pattern of pollination success observed
in this study.
It is more difficult to explain the pattern of
reproductive effort and fruit parasitism
observed within the study. Any changes in
reproductive effort with NND are subject to a
number of different interpretations. Despite
every effort to minimize intra-site variation it is
possible that changes in reproductive effort
simply reflect differences in physical variables.
The disadvantage of the use of transects is that
they may unwittingly be aligned along some
kind of environmental gradient. However, it is
unlikely that this would account for many of
the patterns observed in this study, which occur
in all sites. Even if the physical environment
could be made completely homogenous there
are still several plausible determinants of
reproductive effort. Teasing apart the
interactions between these factors and various
correlates of reproductive effort requires
further field research.
There is a clear spatial pattern of fruit
parasitism recorded in this study, but the
reasons for this pattern are uncertain (see
Kunin 1999, for a review of the possibilities).
Collection of additional fruit from more plants,
and modifying seed-set estimates for partially
parasitized fruit would provide a more detailed
picture of any patterns, and reveal the
consequences for reproductive success. These
measures were beyond the remit of the current
study, and in some cases would have conflicted
with other objectives. For example, many more
fruits per plant would have been sampled but I
wanted to include as many dispersed plants as
possible. The most isolated C. landanifer
individuals seldom had more than a few fruits.
A more serious problem, which this study
shares with many others, is the potential effect
of spatial autocorrelation at the field site and
within the data. All efforts were made in this
study to select sites which were internally
homogenous. Since the existence of site variation could change the pattern of autocorrelation
such that the frequency of type I errors (i.e.: the
failure to reject the null hypothesis when in fact
there is no effect of plant density on the
response variables) were increased. The
relatively small spatial scale of the study area,
with the greatest NND being just 30.5 metres,
should increase the level of population
homogeneity through autocorrelation. Though
it was not possible in the current analysis,
techniques do exist to generate modified
correlations or regressions which specifically
take into account spatial auto-correlation
(Dutilleul’s t-test; Dutilleul 1993, Legendre
2002). Given that many of the patterns
observed in this study were very highly
significant, it is likely that even after correction
they would remain significant.
Despite the weaknesses outlined above, this
study does have several advantages over
previous, more controlled experiments. Most
importantly, this study details the pattern and
extent of variation, in terms of reproductive
success, which may exist in the field. The
experimental approach has already demonstrated that many of these processes can, in
principle, operate. Whether or not they are
important in nature is another issue. In
addition, the spatial dynamics of reproductive
success were examined in greater detail than in
13
many previous research efforts. This added
detail adds an extra level of complexity which
can cloud analysis and interpretation, but is
nevertheless a truer representation of what
occurs in nature.
Many of the patterns observed are
underestimated because the non-parametric
methods used have relatively low statistical
power. Furthermore, because it was only
possible to survey non-aborted fruits, the full
extent of reproductive failure in dispersed
plants (i.e.: including relative reproductive
success of aborted fruits) was certainly
underestimated. The abortion rate was also a
conservative estimate since no plants were
included if they had fewer than three fruits. In
practice this meant that many of the most
isolated, and potentially most interesting,
plants could not be sampled.
Conclusion
Reproductive success in C. landanifer is the
product of several different density-dependant
processes. The cumulative effect of these
processes is such that sparsely populated plants
are likely to produce fewer viable seedlings.
Effective management of plant populations will
depend upon a greater understanding of the
factors that determine reproductive success and
how they respond to plant density. In this study
system there is likely to be a strong selective
advantage for those dispersed plants which are
able to increase their reproductive effort. This
study has generated a number of hypotheses
which remain to be tested. Further research
with C. landanifer, and in other study systems
should allow us to generate general principles
which will shed light both on aspects of
population dynamics, and of conservation
biology.
Acknowledgements
This project was, to a large extent, supported
financially by an M.Sc project grant from the
School of Biology, University of Leeds.
Thanks go to the following people whose input
significantly improved the manuscript; Bill
Kunin, Chris Thomas and Steve Sait. I am
deeply indebted to Manuela Pires da Fonseca
and Joao Tiago Sabino Marques for providing
extensive logistical support and advice in the
field. Finally, thanks also to Laura Smith and
Leili Shamimi for putting up with me for six
weeks.
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