Journal of Heredity, 2014, 537–545
doi:10.1093/jhered/esv023
Symposium Article
Symposium Article
Identifying Genetic Hotspots by Mapping
Molecular Diversity of Widespread Trees: When
Commonness Matters
Cintia P. Souto, Paula Mathiasen, María Cristina Acosta,
María Paula Quiroga, Romina Vidal-Russell, Cristian Echeverría, and
Andrea C. Premoli
From the Laboratorio Ecotono, Centro Regional Universitario Bariloche, Universidad Nacional del ComahueINIBIOMA CONICET, Quintral 1250, 8400 Bariloche, Argentina (Souto, Mathiasen, Acosta, Quiroga, Vidal-Russell, and
Premoli); Instituto Multidisciplinario de Biología Vegetal IMBIV, CONICET-Universidad Nacional de Córdoba, Córdoba,
Argentina (Acosta); and Laboratorio de Ecología del Paisaje, Universidad de Concepción, Chile (Echeverría).
Address correspondence to Andrea C. Premoli at the address above, or e-mail: [email protected]
Received August 29, 2014; First decision December 12, 2014; Accepted March 27, 2015
Corresponding Editor: Kathryn Rodriguez-Clark
Abstract
Conservation planning requires setting priorities at the same spatial scale at which decision-making
processes are undertaken considering all levels of biodiversity, but current methods for identifying
biodiversity hotspots ignore its genetic component. We developed a fine-scale approach based
on the definition of genetic hotspots, which have high genetic diversity and unique variants that
represent their evolutionary potential and evolutionary novelties. Our hypothesis is that wideranging taxa with similar ecological tolerances, yet of phylogenetically independent lineages, have
been and currently are shaped by ecological and evolutionary forces that result in geographically
concordant genetic patterns. We mapped previously published genetic diversity and unique
variants of biparentally inherited markers and chloroplast sequences for 9 species from 188 and
275 populations, respectively, of the 4 woody dominant families of the austral temperate forest,
an area considered a biodiversity hotspot. Spatial distribution patterns of genetic polymorphisms
differed among taxa according to their ecological tolerances. Eight genetic hotspots were detected
and we recommend conservation actions for some in the southern Coastal Range in Chile.
Existing spatially explicit genetic data from multiple populations and species can help to identify
biodiversity hotspots and guide conservation actions to establish science-based protected areas
that will preserve the evolutionary potential of key habitats and species.
Resumen
Al momento de elaborar planes de conservación se requiere establecer prioridades a la misma
escala espacial en la que ocurren los procesos de toma de decisiones, teniendo en cuenta todos
los niveles de la biodiversidad. Sin embargo los métodos actuales para identificar hotspots de
biodiversidad ignoran su componente genética. En este trabajo desarrollamos un enfoque a escala
espacial fina sobre la base de la definición de hotspots genéticos, que son áreas que contienen
una alta diversidad genética y variantes únicas, representando su potencial evolutivo y sus
© The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: [email protected]
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Journal of Heredity, 2015, Vol. 106, Special Issue
novedades evolutivas. Nuestra hipótesis es que poblaciones de especies de amplia distribución
con tolerancias ecológicas similares, aunque pertenecientes a linajes filogenéticamente
independientes, han sido y son moldeadas por fuerzas ecológicas y evolutivas que dan lugar a
patrones genéticos geográficamente concordantes. Mapeamos datos publicados anteriormente de
diversidad genética y variantes únicas en base a marcadores de herencia biparental y secuencias
del ADN del cloroplasto de 188 y 275 poblaciones respectivamente, de nueve especies de las
cuatro familias leñosas dominantes del bosque templado austral, un área considerada un hotspot
de biodiversidad. Los patrones de distribución espacial de los polimorfismos genéticos difieren
entre taxones de acuerdo con sus tolerancias ecológicas. Se detectaron ocho hotspots genéticos y
recomendamos acciones de conservación para algunos de ellos al sur de la Cordillera de la Costa
en Chile. Datos espacialmente explícitos de múltiples poblaciones y especies pueden ayudar a
identificar hotspots de biodiversidad y guiar acciones de conservación con una base científica
para establecer áreas protegidas que preserven el potencial evolutivo de hábitats y especies clave.
Subject areas: Conservation genetics and biodiversity
Key words: austral forests, genetic diversity, haplotype diversity, Patagonia, unique alleles, unique haplotypes
Plant species conservation genetics as a discipline was initially developed to analyze increasing anthropogenically driven impacts on small
populations. Early studies focused on species considered rare and/
or range restricted (Rabinowitz 1981), which tend to be genetically
depauperate due to genetic drift and inbreeding (Falk and Holsinger
1991). In addition to the genetic erosion suffered by species occurring in
small populations, environmental and demographic stochasticity may
threaten the local persistence of populations or extirpate entire species
in extreme cases of rarity (Lande 1988, Brooks et al. 2015). In contrast,
widespread species usually consist of large and relatively continuous
populations with high genetic diversity (Hamrick and Godt 1989). In
addition to a large amount of neutral genetic variation due to historical
isolation and barriers to gene flow, widespread species hold significant
adaptive variance related to the environmental gradients they inhabit.
Therefore, conservation of widespread species is mainly concerned with
the loss of locally adapted variants such as in management of economically important species like forest trees (Millar and Libby 1991, Pollock
et al. 2015). Such information may be valuable for the long-term persistence of variants along environmental gradients under the threat of
climate change. Also, wide-ranging species coexist with other rangerestricted (i.e., rare) species and maintain numerous key plant–plant
and plant–animal interactions in forest landscapes. Therefore, withinspecies polymorphisms in widespread taxa may be of great value in the
design of conservation actions for their populations and communities.
Intraspecific polymorphisms have been largely used to define
evolutionarily significant units (Moritz 1994) although later authors
provided additional suggestions for definition of such conservation units (e.g., Fraser and Bernatchez 2001; Palsbøll et al. 2007).
Monophyletic groups are regarded as minimum conservation units.
The degree of genetic and ecological interchangeability may also
provide measures of conservation distinctiveness at the intraspecific level (Crandall et al. 2000). However, some limitations may
exist with these definitions. Monophyletic groups may result from
molecular analysis of conserved regions of the mitochondria or the
chloroplast. For some lineages, such clades may be so geographically
extended that analysis yields coarse-grained information of limited
conservation value. Methods to define ecological exchangeability
mostly result from experimental studies such as common gardens
or reciprocal transplant experiments that are time consuming and
therefore may not be fully available for a great number of plant taxa.
Other population-level approaches such as Systematic Conservation
Planning may be used to determine the most cost-effective way to
invest in conservation actions (Margules and Pressey 2000) but
examples in the literature focus on single species rather than groups
of species (e.g., Diniz-Filho et al. 2012). Fine-scale methods are
needed that integrate genetic information on numerous taxa within
a given area, at a scale in which regional decisions are made about
conservation investment and efforts (e.g., Jenkins et al. 2013).
Spatially explicit molecular data have great potential but to date
have not been exploited for conservation planning. With the growing
availability of low-cost genetic markers, many tree species have been
the subject of global genetic surveys. Biparentally inherited polymorphic markers allow the analysis of the contemporary influence of drift
and gene flow, while conserved markers such as chloroplast sequences
allow the analysis of historical effects on populations. Biparentally
inherited markers genotyped in widespread trees were used early
on to guide conservation efforts (Millar and Libby 1991). Also, the
development of intraspecific phylogenies and the application of phylogeographic methods to study the spatial distribution of cpDNA lineages of woody species enabled the analysis of refugial areas and their
relevance in conservation (Newton et al. 1999). More recently, an
increasing integration of genetic data with geospatial information has
led to the development of landscape genetics. This emerging discipline
aims to understand the influence of landscape and environmental features on gene flow, population structure, and local adaptation, which
may be of evolutionary, ecological, and conservation value (Manel
et al. 2003). However, such analyses are mainly focused on single
species and their application to regional conservation strategies is
limited. Methods are needed that combine different types of markers
from a variety of species that will integrate genetic responses under
different timeframes and from samples of co-occurring ecologically
similar lineages within a region. Concordant patterns emerging from
such markers may indicate shared evolutionary histories and current
ecological processes, and thus future potential (Manel et al. 2012).
In the current biodiversity crisis, a common conservation priority is to protect the most species per dollar invested in conservation
actions (Naidoo et al. 2006). One of the approaches used to prioritize
areas for biological conservation is the identification of “biodiversity
hotspots,” which usually consist of large areas with exceptional concentrations of endemic species that are under threat due to habitat loss
(Myers et al. 2000). In addition to being coarse scale, biodiversity hotspots are significantly influenced by the criteria used to define them,
Journal of Heredity, 2015, Vol. 106, Special Issue
either based on richness, endemism, threat, or a combination of these.
However, it was suggested early on that a finer scale hotspot analysis
might be more useful, particularly if combined with other analytical methods (Reid 1998, Buerki et al. 2015). In this study we developed a Geographical Information System (GIS) method to integrate
intraspecific genetic polymorphism of species with similar ecological
tolerances in order to identify genetic hotspots and suggest priority
areas for conservation. The underlying argument for protecting these
areas relies on the phylogeographic principle that persistent barriers
to gene flow can result in major genetic discontinuities (Avise 2004).
Genetic imprints of former and current biogeographic processes could
be strong enough that correlated signals may be found in different
genomes (i.e., cytoplasmic and nuclear DNA) to the point that they
have influenced the genetic structures of independently evolving species in a concordant fashion (Avise et al. 1987). We tested the hypothesis that plants with similar ecological tolerances were similarly shaped
by evolutionary forces, such as the persistence in refugia during
Neogene glaciation events and areas of secondary contact, resulting in
genetic hotspots. Genetic hotspot areas are those where multiple species have high genetic diversity and/or contain unique genetic variants,
and may be used to set conservation priorities.
Materials and Methods
Sampling Design
We used our previously published data for 9 cold-tolerant widespread species that are endemic to austral temperate forests, considered a biodiversity hotspot covering southern Chile and adjacent
areas of Patagonia, Argentina (Myers et al. 2000). This region is
also of conservation concern as part of the World Wildlife Fund’s
designated Valdivian Ecoregion (www.worldwildlife.org/ecoregions/
nt0404). Data consisted of genetic variation parameters (see below)
and Global Positioning System locations for 360 populations (see
Supplementary Tables S1 and S2 online). We collected samples from
2 broadleaf families (Nothofagaceae Kuprian and Proteaceae Juss.)
and 2 conifer families (Cupressaceae Bartlett and Podocarpaceae
Endl.). Focal species coexist at several locations along their ranges,
which allowed us to sample following a spatially explicit design;
wherever they co-occur they were collected at the same location.
Within Proteaceae we sampled 34 different locations (i.e., populations) of Embothrium coccineum J.R.Forst. & G.Forst. hereafter
Embothrium (Souto and Premoli 2007; Vidal-Russell et al. 2011).
Within Nothofagaceae, samples consisted of 92 populations of
Nothofagus antarctica (G.Forst.) Oerst., 83 of N. pumilio, 17 of
N. betuloides (Mirb.) Oerst., 56 of N. dombeyi (Mirb.) Oesrt., and
11 of the relatively range-restricted N. nitida (Phil.) Krasser (Premoli
1997; Premoli and Kitzberger 2005; Mathiasen and Premoli 2010;
Acosta et al. 2012; Acosta et al. 2014). Within Cupressaceae we sampled 30 populations of Fitzroya cupressoides (Molina) I.M.Johnst.
hereafter Fitzroya (Premoli et al. 2000a, 2000b) and 23 populations
of Pilgerodendron uviferum (D.Don) Florin hereafter Pilgerodendron
(Premoli et al. 2002, 2003). Within Podocarpaceae we sampled 14
populations of Podocarpus nubigenus Lindl. (Quiroga and Premoli
2010). Some of the study species are of great conservation value, such
as the endemic Embothrium, Fitzroya, and Pilgerodendron, which
are monotypic genera. In addition, Fitzroya and Pilgerodendron are
listed in the Appendix I of the Convention on International Trade in
Endangered Species of Wild Flora and Fauna (CITES). In particular,
Fitzroya is the second longest living tree species in the world, and
counts of its rings have extended climate reconstructions to more
than 3000 years pb (Lara and Villalba 1993).
539
Genetic Variation Parameters
We used previously published genetic data for isozyme and chloroplast DNA (cpDNA) markers in nine cold-tolerant species to estimate genetic diversity parameters (Table 1). Nuclear isozyme data
were collected from fresh leaf samples from approximately 30 randomly selected individuals from each population of Embothrium,
Nothofagus antarctica, N. betuloides, N. dombeyi, N. nitida,
N. pumilio, Fitzroya, Pilgerodendron, and Podocarpus nubigenus.
For further information on sampled populations and locations,
regions, and protected areas mentioned below, see the reference
map (Figure 1). Chloroplast DNA parameters were estimated
using samples from 1 to 5 individuals from each population of
Embothrium, N. antarctica, N. betuloides, N. dombeyi, N. nitida,
and N. pumilio.
For each marker class, we selected two population parameters
to assess total genetic variation: the expected heterozygosity (He)
and the number of unique alleles (Au) for nuclear isozymes (see
Supplementary Table S1 online), and the haplotype diversity (H,
estimated as the total number of haplotypes found in each population divided by the total number of haplotypes for each species) and
the number of unique haplotypes (Hu) for cpDNA markers (see
Supplementary Table S2 online). These parameters of genetic richness and genetic uniqueness were selected to portray the evolutionary potential and novelties present in each population. In order to
avoid underestimation of the less genetically variable species, population diversity parameters (He and H) were ranked in 5 classes
within each species (Figure 2). Unique alleles and haplotypes (Au
and Hu) were recorded as presence/absence within each population
(see Supplementary Tables S1 and S2 online). Diversity ranks (Her
and Hr) and presence/absence of variants (Aup and Hup) for each
population were used as raw data and were mapped individually.
These maps were created in DIVA-GIS v. 7.5 using the Shannon
diversity index routine, using a 0.1667 minute cell size and a circular neighborhood size of 0.5 degrees (see Supplementary Figures S1
and S2 online).
Genetic hotspots were defined as those locales with the highest values of Shannon diversity mapped in DIVA-GIS, based on a
genetic diversity and unique variant index (GDUVI). This index
combines all the available genetic parameters for each species at
each population. It was calculated as the sum of the rank scores
(Her and Hr) and the unique variant values (Aup and Hup) divided
by the number of available parameters. In cases which information
was available for all parameters (i.e., Her + Aup + Hr + Hup) the
sum was divided by 4 or alternatively by 2, if for a given species
only data for isozymes or cpDNA were available). Then we used
the same software and settings to produce a genetic hotspot map
(Figure 3).
To test the robustness of the observed spatial pattern to the number and identity of species and markers incorporated in the analysis,
we conducted a bootstrap analysis in R (R Core Team 2014). We
resampled the GDUVI parameter 1000 times over species and populations with replacement. We calculated the median GDUVI value of
1000 replicates (i.e., the most frequently visited value when bootstrapping for a given population of each species). Finally, we mapped
genetic hotspots using the Shannon diversity index routine in DIVAGIS using the same settings used for the observed data to compare
the observed spatial pattern with the bootstrap results.
Data Archiving In fulfillment of data archiving guidelines (Baker
2013), we have deposited the primary data underlying these analyses as online Supporting Information including: Sampling locations,
genetic diversity, and unique genetic variants.
Journal of Heredity, 2015, Vol. 106, Special Issue
540
Table 1. Studied species, number of sampled populations (n), individuals in brackets, and population genetic variation parameters estimated from nuclear isozymes and chloroplast DNA markers for each focal species
Isozymes
Cloroplast DNA
Species
n
N loci N isozymes He
Broadleaf
Embothrium
coccineum
34 (935)
16
9
0.179 (0.055)
8
30 (90)
Nothofagus
antarctica
28 (995)
8
5
0.169 (0.050)
1
92 (133) psbB-psbH trnL- 0.052 (0.015)
trnF trnH-psbA
8
21
Nothofagus
betuloides
4 (111)
15
10
0.116 (0.014)
2
13 (22)
psbB-psbH trnL- 0.231 (0.075)
trnF trnH-psbA
2
5
Nothofagus
dombeyi
8 (533)
15
10
0.145 (0.079)
8
48 (92)
psbB-psbH trnL- 0.058 (0.024) 10
trnF trnH-psbA
20
Nothofagus
nitida
4 (167)
15
10
0.045 (0.016)
4
7 (24)
42 (1101)
8
5
0.068 (0.057)
3
30 (864)
21
11
24 (689)
14
14 (354)
12
Nothofagus
pumilio
Conifers
Fitzroya cu
pressoides
Pilgerodendron
uviferum
Podocarpus
nubigenus
Au n
Region
H
Hu HT References
trnL-trnF ndhCtrnV
0.082 (0.037) 13
22
psbB-psbH trnL- 0.286 (0.094)
trnF trnH-psbA
3
4
85 (195) psbB-psbH trnL- 0.075 (0.016)
trnF trnH-psbA
3
14
0.077 (0.026) 11
—
—
—
—
—
9
0.042 (0.038)
8
—
—
—
—
—
6
0.218 (0.059)
4
—
a
—
—
—
Souto and Premoli
(2007); Vidal-Russell et al. (2011)
Premoli and Steinke
(2008); Steinke et al.
(2008); Acosta et al.
(2012, 2014)
Premoli (1996,
1997); Acosta et al.
(2014)
Premoli (1996,
1997); Premoli and
Kitzberger (2005);
Acosta et al. (2014)
Premoli (1996,
1997); Acosta et al.
(2014)
Mathiasen and
Premoli (2010)
Premoli et al. (2000
a and b, 2003)
Premoli et al. (2001,
2002)
Quiroga and Premoli (2010)
Monomorphic regions: trnL - trnF; trnLe1 - trne2; trnD - trnT; trnS - trnTm
He, average (SD) expected heterozygosity; Au, total unique alleles; H, average (SD) haplotype diversity; Hu, total unique haplotypes; and HT, total number of
haplotypes. Along with previously published references.
a
Results
Combined Markers Map
Along the austral temperate forest region, expected heterozygosity (He) in nuclear isozymes had the highest rank scores in 6 areas
(shown in red in Supplementary Figure S1a online). Three of these
areas were located in the Coastal Range in Chile, between lat 40ºS
and 42ºS. The other 3 areas with high ranks for diversity were along
the Andean Cordillera in Argentina. Nuclear isozyme data on presence of unique alleles (Au) revealed up 14 additional areas with
the highest Shannon diversity scores (see Supplementary Figure S1b
online). In the map of chloroplast DNA haplotype diversity (H), on
the other hand, there were seven areas with the highest scores (see
Supplementary Figure S2a online). Four of these were located in
Chile (1 in the Nahuelbuta region, 2 on Chiloe Island, and 1 in the
Andean Range of the Region de los Lagos). In Argentina, H had the
higher rank score in 3 areas located north of lat 42ºS. As for unique
alleles in chloroplast DNA (Hu), the number of high score areas
increased to 18 (see Supplementary Figure S2b online). Chilean
areas with high scores for this parameter included Nahuelbuta,
Chiloe Island, and 5 areas along the Andean Cordillera in the
Region de los Rios and Region de los Lagos (between lat 37ºS and
42ºS). In Argentina, the unique chloroplast DNA haplotype map
highlighted 5 areas along the Andean Cordillera north of lat 42ºS,
while 5 high-scoring areas were located further south, between lat
43ºS and 51ºS. As expected, the 2 marker classes had different spatial patterns, reflecting more ancient events for cpDNA, more recent
events for nuclear isozymes.
When nuclear and chloroplast marker parameters were mapped
together (Figure 4a), we identified eight genetic hotspots.
Particularly in Chile, a small protected area in Alerce Costero was
included in a larger genetic hotspot, near Valdivia city at lat 40ºS.
A second small area was at similar latitude but near the Andean
range, outside of any reserve system. Toward the south, Astilleros
and Chiloe Island (lat 42ºS–43ºS) had genetic hotspots that were
mainly outside any protected area. In Argentina, all genetic hotspots were protected within national parks: a high-scoring area
within Lanin National Park at lat 39ºS, a larger area within the
Nahuel Huapi National Park at lat 41ºS, and 3 high-scoring areas
in Los Alerces and Los Glaciares National Parks between lat 43ºS
and 50ºS. Along the Andean range, several protected areas had only
moderate genetic hotspot scores. Although the exact location of
the highest-ranking areas shifts to some extent, the bootstrap resampling demonstrated that hotspot patterns were generally robust
(Figure 4b). Nonetheless, a new hotspot emerges in the extreme
south in the bootstrapped data.
Discussion
Biodiversity hotspots are defined at a coarse scale and are often
based on richness, endemism, threat, or a combination of these—but
to date have not incorporated genetic data. We developed a finescale GIS-based method to integrate intraspecific genetic data from
Journal of Heredity, 2015, Vol. 106, Special Issue
541
Figure 1. Reference map showing sampled localities, regions, and protected areas names mentioned in the text.
species with similar ecological tolerances in order to identify genetic
hotspots to aid the selection of priority areas for conservation.
Widespread species endemic to the austral temperate South
American forests differed in their levels of genetic diversity. While
some species were genetically diverse for biparentally inherited
markers, such as Embothrium, Fitzroya, and Nothofagus antarctica;
others were more genetically depauperate, such as Pilgerodendron
and Nothofagus pumilio. The more genetically diverse species occur
in more heterogeneous environments. For example, the range of
Embothrium spans 20º of latitude and is both morphologically and
genetically highly variable in correspondence to Patagonian geographic and climatic gradients (Souto and Smouse 2014). Nothofagus
antarctica occurs in a variety of habitat types where distinct morphotypes have been identified (Steinke et al. 2008). Similarly, Fitzroya,
although restricted to temperate rainforest, occurs in a wide variety
of soils and elevations (Donoso 2006). In contrast, Pilgerodendron
and N. pumilio can be considered relatively habitat specific with
ecological optima at high latitudes and also at high elevations in
the case of N. pumilio. Species with high genetic diversity for biparentally inherited markers were also more variable for chloroplast
DNA sequences. Interspecific comparisons may be biased because
most species included in this study are phylogenetically independent, but for those species pairs where comparisons were feasible,
greater neutral diversity was observed in more polymorphic species. For example, N. pumilio and N. antarctica have similarly wide
latitudinal ranges, but the latter is more diverse in morphology and
habitat (Steinke et al. 2008) and is also more polymorphic for different molecular markers (Acosta et al. 2012, 2014). Generalizations
concerning predicted patterns and levels of genetic diversity in widespread plants must be made with caution. Nevertheless, although
levels of genetic polymorphism in widespread phylogenetically independent taxa varied along their ranges, they yielded concordant spatial patterns that revealed genetic hotspots (Figure 4a).
Preserving the evolutionary potential of species is a major concern in conservation, as it may allow them to respond to a changing climate and ensure long-term population persistence. Climate
responses may be accomplished through rapid adaptive adjustment
or migration that tracks an ecological optimum (Chevin et al. 2010).
Mapping genetic hotspots can contribute to the design of effective
conservation actions by detecting local areas with high genetic diversity, and the presence of unique gene variants—and thus presumably
high evolutionary potential. Population genetic theory predicts that
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Journal of Heredity, 2015, Vol. 106, Special Issue
Figure 2. Expected heterozygosity histograms estimated from nuclear isozyme markers for the studied species where the available number of data points came
from more than 8 populations.
Figure 3. Schematic diagram describing the procedure involved in estimating and mapping genetic hotspots. ISO, nuclear isozyme data; DNA, chloroplast DNA
markers; He, expected heterozygosity; Au, unique alleles; H; haplotype diversity; Hu, unique haplotypes; Her and Hr, ranked He and H respectively; Aup and Hup,
presence/absence of unique variants; and GEDUVI, genetic diversity and unique variant index.
the evolutionary potential of populations depends on the adaptive
genetic variance (Fisher 1930). Although we mapped neutral genetic
variation, hotspots were located along environmental gradients
under contrasting precipitation (along a W–E direction), and temperature (along N–S gradient). In particular, adaptive and neutral
traits analyzed throughout these gradients of a widespread species
as Embothrium showed geographically concordant patterns (Souto
and Smouse 2014). Therefore, in heterogeneous environments, as
Patagonia, neutral genetic variation might be to some extent a proxy
for adaptive variation. If the long-term objective is to protect the
Journal of Heredity, 2015, Vol. 106, Special Issue
543
Figure 4. (a). Genetic hotspots map estimated with the average rank score of genetic diversity of nuclear isozyme and chloroplast DNA markers for 360 studied
populations of nine focal species from austral temperate forests. (b). Genetic hotspots map estimated with the Bootstrap median value of the average rank score
of genetic diversity of nuclear isozyme and chloroplast DNA markers for 360 studied populations of 9 focal species from austral temperate forests.
evolutionary potential of forests, then managers and conservation
practitioners should aim to preserve as much adaptive variation as
possible. Although perhaps valid when applied to flagship species,
such an approach loses practicality when considering multiple species. Genome-wide scans are targeting non-neutral DNA regions that
are expected to significantly contribute to bridging the gap between
neutral and adaptive variation (Kirk and Freeland 2011).
Mapping genetic hotspots is particularly relevant if they are
located in areas under threat, such as the central and southern Coastal
Range of Chile. Relatively stable tectonic and topographic characteristics of the Coastal Range and the oceanic influence that moderates
low temperatures during cooling episodes have favored the longterm in situ preservation of lineages of Gondwanic origin, such as
the members of the different families analyzed here (Premoli et al.
2012; Acosta et al. 2014). Other genetic studies support the Coastal
Range as a refugial area for other tree species (Marchelli and Gallo
2006; Azpilicueta et al. 2009). The area has high species richness and
unique taxa (Smith-Ramírez et al. 2005). Nonetheless, the Coastal
Range primarily consists of small native forest fragments in an intensively used matrix—particularly at the northernmost range, where
industrial Pinus and Eucalyptus plantations are the dominant land
cover (Echeverría et al. 2006). Therefore, urgent actions are needed
to protect relict coastal native forests in central Chile near the city of
Valdivia and the southern range in northern Chiloe Island where significant genetic resources are still present in the dominant tree species.
Genetic hotspots on the Andean range, particularly at lat 40°S and
43°S, mostly represent areas of secondary contact. These suture zones
were areas of highly divergent lineages that came into contact as a
result of significant paleolandscape changes that occurred during the
Paleogene and early Neogene as a result of marine transgressions that
dominated the Patagonian landscape (Acosta et al. 2014). Numerous
protected areas include or exist near Andean hotspots that ensure
the long-term persistence of those populations, but hotspots can also
guide protection actions. For example, in Argentina, National Park
authorities banned cattle grazing in a genetically diverse area of a
Nothofagus species (Gallo et al. 2009). Towards the far south in the
Chilean Patagonia, hotspot areas are threatened by the construction
of river dams, hydroelectrical projects, and road construction, and
may be lost if prompt conservation actions are not taken. In extreme
southern areas, bootstrapped scores yielded genetic hotspots, particularly for N. pumilio and Embothrium where glacial refugia were suggested (Souto and Premoli 2007; Premoli et al. 2010). This result is
relevant in areas where intensive forestry practices take place as in the
austral-most island of Tierra del Fuego.
Hotspots have been useful in setting conservation priorities at
large spatial scales, but their potential has to date been limited at
regional scales where most decision-making processes are undertaken
(Reid 1998). We suggest that concordant genetic patterns of widespread ecologically similar taxa may greatly help guide conservation
efforts at regional scales. Widespread species occur in a great diversity
of habitats, reflecting a substantial amount of the diversity in other
taxa as well as including threatened and endangered species. It is well
known that biodiversity hotspots are highly dependent on the species group examined as well as on spatial scale, producing concordant
patterns at some scales and discordant ones at others (Myers et al.
2000). In this regard, looking for genetic hotspots could be a useful
tool as more genetic data becomes available. The scale for the current
study was chosen because it is part of a biodiversity hotspot. To detect
genetic hotspots, it seems important to include widespread and dominant species of the area sharing similar ecological tolerances. We recommend combining different sets of markers, which has much more
potential to identify genetic hotspots than looking at just one marker
type. Available resampling techniques allow testing for the robustness
of the observed geographic patterns. The combination of geographic
techniques along with the available genetic data may greatly contribute to the design of fine-scale conservation actions.
The evidence presented here shows that phylogenetically independent species sharing similar ecological characteristics can yield
544
geographically concordant molecular patterns, which reveal genetic
hotspots and suggest where they may be found in other taxa and
regions of the world. For example, while cold-tolerant taxa probably
survived in multiple ice-free areas throughout their geographic distribution during glaciation events, cold-sensitive species did so in warm
(i.e., northern areas in the Southern Hemisphere) locations (NúñezÁvila and Armesto 2006; Souto et al. 2012). Therefore, genetic hotspots may be hypothesized towards the warm end of the distribution
range of warm-loving taxa inhabiting temperate regions. At subtropical
latitudes, species that withstand chilling probably subsisted during cool
trends through local altitudinal migrations (Hewitt 2001; Quiroga and
Premoli 2010). Thus, mountain regions as well as southern (relatively
cold) latitudes for such taxa may also hold genetic hotspots.
In addition to evolutionary (i.e., glacial) history, ecological processes shape genetic patterns observed in nature. Most communities are frequently affected by natural disturbances that imprint
significant genetic consequences on their populations. These will
be dependent on the spatial scale of disturbance and the autoecological traits of species involved. For example, mature forests
of predominantly seed-producing species undergoing gap-phase
regeneration due to tree falls hold higher genetic diversity and heterogeneity of genetic structures than post-fire stands (Premoli and
Kitzberger 2005). This is mainly because large-scale disturbances
such as fire result in the survival of a few remnant trees that will
regenerate the site. Genetic bottlenecks occurring during post-fire
regeneration yield genetically poor and homogeneous populations
(Premoli and Kitzberger 2005). Nonetheless, species that have the
ability to resprout after fire may be resilient to large-scale fires,
preserving the genetic structure that existed prior to the perturbation (Premoli and Steinke 2008). Hence, both old-growth forests of
predominantly seeders and woody shrub lands with the ability to
resprout may hold genetic hotspots.
Anthropogenic disturbances also impact the genetic structure of
tree populations, which in turn may depend on their autoecological
traits. For example, self-incompatible plants that are dependent on
pollinating agents can maintain high genetic diversity in small fragments (Mathiasen et al. 2007). Therefore they can be less sensitive to
forest fragmentation than plants that can tolerate selfing; as a result,
fragmented landscapes of the former may be genetic hotspots.
In recent years, landscape genetics has made efforts to integrate
population genetics, landscape ecology, and a variety of spatial
statistics (Manel et al. 2003; Gaggiotti and Foll 2010; Sork et al.
2010). Here, we developed a simple but novel fine-scale GIS-based
approach to define genetic hotspots that can also be applied in the
design of science-based protected areas that may better preserve the
evolutionary potential of habitats and species.
Supplementary Material
Supplementary material can be found at http://www.jhered.oxfordjournals.org/.
Funding
Universidad Nacional del Comahue Project B172.
References
Acosta MC, Mathiasen P, Premoli AC. 2012. Predominant regeneration strategy results in species-specific genetic patterns in sympatric Nothofagus s.s.
congeners (Nothofagaceae). Austr J Bot. 60:319–327.
Journal of Heredity, 2015, Vol. 106, Special Issue
Acosta MC, Mathiasen P, Premoli AC. 2014. Retracing the evolutionary history of Nothofagus in its geo-climatic context: new developments in the
emerging field of phylogeology. Geobiology. 12:497–510.
Avise JC, Arnold J, Ball RM Jr, Bermingham E, Lamb T, Neigel JE, Reeb CA,
Saunders NC. 1987. Intraspecific phylogeography: the mitochondrial
DNA bridge between population genetics and systematics. Annu Rev Ecol
Evol Syst. 18:489–522.
Avise JC. 2004. Molecular markers, natural history, and evolution. Sunderland
(MA): Sinauer Associates Inc.
Azpilicueta MM, Marchelli P, Gallo LA. 2009. The effects of Quaternary
glaciations in Patagonia as evidenced by chloroplast DNA phylogeography of Southern beech Nothofagus obliqua. Tree Genet Genomes.
5:561–571.
Baker CS. 2013. Journal of heredity adopts joint data archiving policy. J
Hered. 104:1. doi:10.1093/jhered/ess137
Brooks TM, Cuttelod A, Faith DP, Garcia-Moreno J, Langhammer P, PerezEspona S. 2015. Why and how might genetic and phylogenetic diversity
be reflected in the identification of key biodiversity areas? Phil Trans
R Soc Lond B Biol Sci. 370:20140019. Available from: http://dx.doi.
org/10.1098/rstb.2014.0019
Buerki S, Callmander MW, Bachman S, Moat J, Labat J-N, Forest F. 2015.
Incorporating evolutionary history into conservation planning in biodiversity hotspots. Phil Trans R Soc Lond B Biol Sci. 370:20140014. Available
from: http://dx.doi.org/10.1098/rstb.2014.0014
Chevin LM, Lande R, Mace GM. 2010. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol.
8:e1000357.
Crandall KA, Bininda-Emonds OR, Mace GM, Wayne RK. 2000. Considering evolutionary processes in conservation biology. Trends Ecol Evol.
15:290–295.
Diniz-Filho JAF, Melo BD, de Oliveira G, Collevatti GR, Soares TN, Nabout
JC, Lima JS, Dobrovolski R, Chaves LJ, Naves VR, et al. 2012. Planning
for optimal conservation of geographical genetic variability within species.
Conserv Genet. 13:1085–1093.
Donoso C. 2006. Las especies arbóreas de los bosques templados de Chile y
Argentina. Autoecología. Valdivia (Chile): Marisa Cuneo Ediciones.
Echeverría C, Coomes D, Salas J, Rey-Benayas JM, Lara A, Newton A. 2006.
Rapid deforestation and fragmentation of Chilean temperate forests. Biol
Conser. 130:481–494.
Falk DA, Holsinger KE. 1991. Genetics and conservation of rare plants. New
York: Oxford University Press.
Fisher RA. 1930. The Genetical theory of natural selection. Oxford: Clarendon Press. [Variorum edition, Bennett JH, editor). 1999. Oxford: Oxford
University Press].
Fraser DJ, Bernatchez L. 2001. Adaptive evolutionary conservation: towards a
unified concept for defining conservation units. Mol Ecol. 10:2741–2752.
Gaggiotti OE, Foll M. 2010. Quantifying population structure with the
F-model. Mol Ecol Res. 10:821–830.
Gallo LA, Marchelli P, Chauchard L, Peñalba MG. 2009. Knowing and doing:
research leading to action in the conservation of forest genetic diversity of
Patagonian temperate forests. Conserv Biol. 23:895–898.
Hamrick JL, Godt MJW. 1989. Allozyme diversity in plant species. In: Brown
AHD, Clegg MT, Kahler AL, Weir BS, editors. Plant population genetics,
breeding and germplasm resources. Sunderland (MA): Sinauer Associates
Inc. p. 44–64.
Hewitt GM. 2001. Speciation, hybrid zones and phylogeography - or seeing
genes in space and time. Mol Ecol. 10:537–549.
Jenkins CN, Pimm SL, Joppa LN. 2013. Global patterns of terrestrial vertebrate diversity and conservation. Proc Natl Acad Sci USA. 110:E2602–
E2610.
Kirk H, Freeland JR. 2011. Applications and implications of neutral versus
non-neutral markers in molecular ecology. Int J Mol Sci. 12:3966–3988.
Lande R. 1988. Genetics and demography in biological conservation. Science.
241:1455–1460.
Lara A, Villalba R. 1993. A 3620-year temperature record from Fitzroya
cupressoides tree rings in southern South America. Science. 260:1104–
1106.
Journal of Heredity, 2015, Vol. 106, Special Issue
Manel S, Schwartz MK, Luikart G, Taberlet P. 2003. Landscape genetics:
combining landscape ecology and population genetics. Trends Ecol Evol.
18:189–197.
Manel S, Gugerli F, Thuiller W, Alvarez N, Legendre P, Holderegger R, Gielly
L, Taberlet P; IntraBioDiv Consortium. 2012. Broad-scale adaptive genetic
variation in alpine plants is driven by temperature and precipitation. Mol
Ecol. 21:3729–3738.
Marchelli P, Gallo L. 2006. Multiple ice-age refugia in a southern beech of
South America as evidenced by chloroplast DNA markers. Conserv Genet.
7:591–603.
Margules CR, Pressey RL. 2000. Systematic conservation planning. Nature.
405:243–253.
Mathiasen P, Rovere AE, Premoli AC. 2007. Genetic structure and early effects
of inbreeding in fragmented temperate forests of a self-incompatible tree,
Embothrium coccineum. Conserv Biol. 21:232–240.
Mathiasen P, Premoli AC. 2010. Out in the cold: genetic variation of Nothofagus pumilio (Nothofagaceae) provides evidence for latitudinally distinct
evolutionary histories in austral South America. Mol Ecol. 19:371–385.
Millar CI, Libby WJ. 1991. Strategies for conserving clinal, ecotypic, and disjunct population diversity in widespread species. Genetics and conservation of rare plants. New York: Oxford University Press.
Moritz C. 1994. Applications of mitochondrial DNA analysis in conservation:
a critical review. Mol Ecol. 3:401–411.
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GA, Kent J. 2000.
Biodiversity hotspots for conservation priorities. Nature. 403:853–
858.
Naidoo R, Balmford A, Ferraro PJ, Polasky S, Ricketts TH, Rouget M. 2006.
Integrating economic costs into conservation planning. Trends Ecol Evol.
21:681–687.
Newton AC, Allnutt TR, Gillies AC, Lowe AJ, Ennos RA. 1999. Molecular
phylogeography, intraspecific variation and the conservation of tree species. Trends Ecol Evol. 14:140–145.
Núñez-Ávila MC, Armesto JJ. 2006. Relict islands of the temperate rainforest tree Aextoxicon punctatum (Aextoxicaceae) in semi-arid Chile: genetic
diversity and biogeographic history. Aust J Bot. 54: 733–743.
Palsbøll PJ, Bérubé M, Allendorf FW. 2007. Identification of management
units using population genetic data. Trends Ecol Evol. 22:11–16.
Pollock LJ, Rosauer DF, Thornhill AH, Kujala H, Crisp MD, Miller JT, McCarthy MA. 2015. Phylogenetic diversity meets conservation policy: small
areas are key to preserving eucalypt lineages. Phil Trans R Soc Lond B
Biol Sci. 370:20140007. Available from: http://dx.doi.org/10.1098/
rstb.2014.0007
Premoli, A.C. 1996. Leaf shape in South American Nothofagus. A combination of traditional and new methods in morphometrics. Bot. J. Linn. Soc.
121: 25–40.
Premoli AC. 1997. Genetic variation in a geographically restricted and two
widespread species of South American Nothofagus. J Biogeogr. 24:883–
892.
Premoli AC, Kitzberger T, Veblen TT. 2000a. Isozyme variation and recent
biogeographical history of the long-lived conifer Fitzroya cupressoides. J
Biogeogr. 27:251–260.
Premoli AC, Kitzberger T, Veblen TT. 2000b. Conservation genetics of the
endangered conifer Fitzroya cupressoides in Chile and Argentina. Conserv
Genet. 1:57–66.
545
Premoli, A.C., C.P. Souto, T.R. Allnutt & A.C. Newton. 2001. Effects of population disjunction on isozyme variation in the widespread Pilgerodendron
uviferum. Heredity. 87:337–343.
Premoli AC, Souto CP, Rovere AE, Allnut TR, Newton AC. 2002. Patterns of
isozyme variation as indicators of biogeographic history in Pilgerodendron uviferum (D. Don) Florín. Divers Distrib. 8:57–66.
Premoli AC, Vergara R, Souto CP, Lara A, Newton AC. 2003. Lowland valleys
shelter ancient Fitzroya cupressoides in the Central Depression of southern
Chile. J Roy Soc New Zeal. 33:623–631.
Premoli AC, Kitzberger T. 2005. Regeneration mode affects spatial genetic
structure of Nothofagus dombeyi forests. Mol Ecol. 14:2319–2329.
Premoli AC, Steinke L. 2008. Genetics of sprouting: effects of long-term persistence in fire-prone ecosystems. Mol Ecol. 17:3827–3835.
Premoli AC, Mathiasen P, Kitzberger T. 2010. Southernmost Nothofagus trees
enduring ice ages: genetic evidence and ecological niche retrodiction reveal
high latitude (54°S) glacial refugia. Palaeogeogr Palaeoclimatol Palaeoecol.
298:247–256.
Premoli AC, Mathiasen P, Acosta MC, Ramos VA. 2012. Phylogeographically
concordant chloroplast DNA divergence in sympatric Nothofagus s.s.
How deep can it be? New Phytol. 193:261–275.
Quiroga MP, Premoli AC. 2010. Genetic structure of Podocarpus nubigena
(Podocarpaceae) provides evidence of Quaternary and ancient historical
events. Palaeogeogr Palaeoclimatol Palaeoecol. 285:186–193.
R Core Team. 2014. R: A language and environment for statistical computing.
Vienna (Austria): R Foundation for Statistical Computing. Available from:
http://www.R-project.org/.
Rabinowitz D. 1981. Seven forms of rarity. In: Synge H, editor. The biological
aspects of rare plant conservation. New York: Wiley. p. 205–217.
Reid WV. 1998. Biodiversity hotspots. Trends Ecol Evol. 13:275–280.
Smith-Ramírez C, Armesto JJ, Saavedra B. 2005. Estado del conocimiento y
conservación de los ecosistemas de la cordillera de la costa: síntesis y perspectivas. In: Smith-Ramírez C, Armesto JJ, Valdovinos C, editors. Historia, Biodiversidad y Ecología de los Bosques Costeros de Chile. Santiago
(Chile): Editorial Universitaria. p. 645–650.
Sork VL, Davis FW, Westfall R, Flint A, Ikegami M, Wang H, Grivet D. 2010.
Gene movement and genetic association with regional climate gradients in
California valley oak (Quercus lobata Née) in the face of climate change.
Mol Ecol. 19:3806–3823.
Souto C, Premoli A. 2007. Genetic variation in the widespread Embothrium
coccineum (Proteaceae) endemic to Patagonia: effects of phylogeny and
historical events. Aust J Bot. 55:809–817.
Souto CP, Heinemann K, Kitzberger T, Newton AC. 2012. Genetic diversity
and structure in Austrocedrus chilensis populations: implications for dryland forest restoration. Rest Ecol. 20:568–575.
Souto CP, Smouse PE. 2014. Correlated morphological and genetic patterns
in Embothrium coccineum (Proteaceae) across climate and geography: can Embothrium survive patagonian climate change?. Aust J Bot.
61:516–527.
Steinke L, Premoli AC, Souto CP, Hedrén M. 2008. Adaptive and neutral variation of the resprouter Nothofagus antarctica growing in distinct habitats
in north-western Patagonia. Silva Fenn. 42:177–188.
Vidal-Russell R, Souto CP, Premoli AC. 2011. Multiple Pleistocene refugia
in the widespread Patagonian tree Embothrium coccineum (Proteaceae).
Aust J Bot. 59:299–314.