Post on 12-May-2023
Book chapter for Molecular Approaches in Natural Resource Conservation (J.A 1
DeWoody, J.W. Bickham, C. Michler, K. Nichols, O.E. Rhodes, and K. Woeste, eds.). 2
Scheduled for release in 2009 from Cambridge University Press. 3
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A Community and Ecosystem Genetics Approach to Conservation 6
Biology and Management 7
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Thomas G. Whitham1,2
, Catherine A. Gehring1,2
, Luke M. Evans1,2
, Carri J. LeRoy3, 9
Randy K. Bangert1,4
, Jennifer A. Schweitzer5, Gerard J. Allan
1,2, Robert C. Barbour
6, 10
Dylan G. Fischer3, Bradley M. Potts
6 and Joseph K. Bailey
5 11
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1Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011 14
USA 15
2Merriam-Powell Center for Environmental Research, Northern Arizona University, 16
Flagstaff, Arizona 86011 USA 17
3Evergreen State College, Olympia, WA 98505 USA 18
4Biological Sciences, Stop 8007, Idaho State University, Pocatello, ID 63209 USA 19
5Department of Ecology and Evolution, University of Tennessee, Knoxville TN 37996 20
USA
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6School of Plant Science and Cooperative Research Centre for Forestry, University of 22
Tasmania, Private Bag 55, Hobart, Tasmania, 7001 Australia 23
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*Correspondence to: TGW 26
*e-mail: Thomas.Whitham@nau.edu 27
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Abstract 29
Community and ecosystem genetics is the study of the genetic interactions that occur 30
among species and their abiotic environment in complex communities. We argue that by 31
progressing from a population genetics approach focused on individual species to a 32
community genetics approach, conservation genetics and management will be less 33
susceptible to interpretation and management errors. These errors typically arise when 34
management decisions are based upon single species rather than whole communities. 35
Because species evolve in response to interactions among diverse species and their 36
environment, by studying evolution within a community context, conservation genetics 37
can move to a new level of understanding with associated changes in management. For 38
example, from a population genetics perspective, preserving genetic diversity in rare and 39
endangered species is important to prevent inbreeding depression and extinction. 40
However, from a community genetics perspective, preservation of genetic diversity in 41
abundant „foundation species‟ may be more important because as „community drivers‟, 42
the loss of genetic diversity in these foundation species impacts a much larger community 43
of organisms and ecosystem processes. Our studies show that different genotypes of 44
nararowleaf cottonwood (Populus angustifolia) support different communities of canopy 45
arthropods, soil microorganisms, trophic interactions with vertebrates, and ecosystem 46
processes such as leaf litter decomposition and nutrient cycling. Our studies also show 47
that these community and ecosystem phenotypes can be quantified as heritable plant 48
traits. Based on these and other studies from multiple systems, we develop five 49
conservation and management implications. 1. It is important to conserve genetic 50
diversity in foundation species to maintain biodiversity and ecosystem function. 2. 51
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Managing from a species-area curve perspective may be very different than managing 52
from a genetic diversity-area curve perspective. Do we conserve biodiversity based upon 53
area, genetic diversity of the foundation species or both? 3. We contrast the concept of a 54
minimum viable population (MVP) focused on an individual species with that of a 55
minimum viable interacting population (MVIP), which includes the interactions 56
necessary to support a dependent community or organisms. From a community genetics 57
perspective, the current concept of MVP under-represents the population size necessary 58
to conserve the dependent community, especially when applied to foundation species that 59
affect many other species. 4. Some genetically engineered organisms are likely to have 60
unintended community and ecosystem phenotypes. As part of the approval process, these 61
community and ecosystem phenotypes need to be evaluated. 5. Climate change creates a 62
conundrum with the management practice of restoring only with local genotypes. As 63
climate changes, locally adapted genotypes may no longer be locally adapted. Thus, 64
management based upon the use of genotypes from other regions that are a closer match 65
for what the local environment has become or is predicted to become may result in the 66
preservation of a foundation species and more of its dependent community than a strategy 67
of using only local stock in restoration. Here we discuss these and other implications of 68
incorporating a community genetics approach to conservation biology and management. 69
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Keywords: climate change, community and ecosystem genetics, conservation biology, 71
foundation species, genetic diversity-area curve, genetic similarity rule, genetically 72
engineered organisms, management, minimum viable interacting population, restoration 73
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Introduction 75
The emerging field of community and ecosystem genetics has so far focused on 76
how the genetic variation in one species can influence the composition of associated 77
communities and ecosystem processes such as decomposition (see definitions Table 1; 78
reviews by Whitham et al. 2003, 2006; Johnson & Stinchcombe 2007; Hughes et al. 79
2008). A key component of this approach has been an emphasis on understanding how 80
the genetics of foundation plant species influence a much larger community. It is 81
reasoned that because foundation species structure their ecosystems by creating locally 82
stable conditions and provide specific resources for diverse organisms (Dayton 1972; 83
Ellison et al. 2005), the genetics of these species as „community drivers‟ are most 84
important to understand and most likely to have cascading ecological and evolutionary 85
effects throughout an ecosystem (Whitham et al. 2006). For example, when a foundation 86
species‟ genotype influences the relative fitness of other species it constitutes an indirect 87
genetic interaction (Shuster et al. 2006), and when these interactions change species 88
composition and abundance among individual tree genotypes, they result in individual 89
genotypes having distinct community and ecosystem phenotypes. Thus, in addition to an 90
individual genotype having the „traditional‟ phenotype that population geneticists 91
typically consider as the expression of a trait in the individual and at the population level, 92
community geneticists must also consider higher-level phenotypes at the community and 93
ecosystem level. This distinctness at levels higher than the population can be quantified 94
as community heritability (i.e., the tendency for related individuals to support similar 95
communities of organisms and ecosystem processes; Whitham et al. 2003, 2006; Shuster 96
et al. 2006). 97
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Numerous studies in diverse systems demonstrate that community and ecosystem 98
phenotypes exist (e.g., cottonwoods – Dickson & Whitham 1996; Whitham et al. 2003; 99
Schweitzer et al. 2004, 2005a,b, 2008; Bailey et et al. al. 2004, 2006; Fischer 2004, 100
2006a,b, 2007; Wimp et al. 2005, 2007; Shuster et al. 2006; LeRoy et al. 2006, 2007; 101
aspen – Madritch et al. 2006, 2007; willows – Fritz & Price 1988; Hochwender & Fritz 102
2004; metrosideros – Treseder & Vitousek 2001; oaks – Madritch & Hunter 2002, 2004; 103
Tovar-Sanchez & Oyama 2006; aspen - Madritch et al. 2006, 2007; Donaldson & 104
Lindroth 2007; seagrass – Hughes & Stachowicz 2004; goldenrod – Maddox & Root 105
1987; Crutsinger et al. 2006; Crawford et al. 2008; eucalypts – Dungey et al. 2000; 106
Barbour et al. 2009; evening primrose – Johnson & Agrawal 2005; Johnson et al. 2005, 107
2006; Johnson 2008; common reed – Araki et al. 2005; birch – Silfver et al. 2007; alder – 108
Lecerf & Chauvet 2008; grape - English-Loeb & Norton 2006; Baccharis – Rudgers & 109
Whitney 2006). Although most of the species examined in these studies are considered 110
to be foundation species in their respective ecosystems, the evening primrose is a notable 111
exception. Thus, it would appear that a community genetics approach need not be limited 112
to just foundation species. 113
Having demonstrated that different plant genotypes support different 114
communities, new emphasis must be placed on understanding the implications of these 115
findings. For example, relatively few studies have quantified how the genetic variation in 116
foundation species might also affect the evolution of dependent community members 117
(e.g., review by Mopper 1996 and more recent studies on oaks - Mopper et al. 2000; 118
goldenrod - Craig et al. 2007; cottonwood - Evans et al. 2008), how the genetic variation 119
in a foundation species in one community might affect another community (e.g., 120
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terrestrial affects aquatic – Driebe & Whitham 2000; LeRoy et al. 2006, 2007; Lecerf & 121
Chauvet 2008), and how a community might feed back to affect the survival and 122
performance of the genotype expressing the trait (Fischer et al. 2006; Schweitzer et al. 123
2008). These remain important frontiers of research for a community genetics approach 124
to reach its full conceptual potential. However, based upon our current knowledge, it 125
seems clear that this approach can offer productive insights into conservation biology and 126
management. The remainder of this chapter considers the conservation implications of 127
the existence of heritable community and ecosystem phenotypes. 128
129
Conservation in a community context 130
Two main reasons support a community genetics approach for conservation and 131
management. First, because all species have evolved in a community context of many 132
interacting species and their abiotic environments, it is unrealistic to study any one 133
species in isolation as if it had evolved in a vacuum (e.g., Thompson 2005; Wade 2007). 134
Thus, the community context of species evolution is far more realistic as it considers 135
more of the variables that are likely to have influenced the evolution of any one species. 136
Second, and perhaps most importantly from a manager‟s perspective, a 137
community approach is less likely to result in management errors. For example, as a 138
two-way interaction, mistletoes are clearly parasites of flowering plants. However, few 139
interactions are just two-way interactions. In their studies of one-seed juniper (Juniperus 140
monosperma) and its associated mistletoe (Phoradendron juniperinum), van Ommeren 141
and Whitham (2002) found that the berries produced by both the juniper and mistletoe 142
were primarily dispersed by birds such as Townsend‟s solitaires (Myadestes townsendi). 143
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If the seeds of mistletoe attract more birds that end up dispersing more juniper berries, 144
then as a three-way interaction, mistletoe might be considered as a mutualist rather than a 145
parasite. In support of this hypothesis, they found that juniper stands with mistletoe 146
attracted up to 3 times more birds than stands with little or no mistletoe. Most 147
importantly, the number of juniper seedlings was more than 2-fold greater in stands with 148
high mistletoe density compared with stands that had little or no mistletoe. Based upon a 149
two-way interaction, a manager would be justified in removing mistletoe to promote tree 150
performance. However, based upon a three-way interaction, the opposite strategy might 151
be warranted in which mistletoe could benefit juniper recruitment by promoting avian 152
seed dispersal. Thus, just by adding one additional species to the analysis, the 153
fundamental relationships of juniper and mistletoe can „switch or reverse‟ from negative 154
to positive, and management decisions would also shift accordingly. Because the species 155
composing a community interact, the sign of the ecological interaction and the 156
appropriate management decision is dependent upon the number of interacting players 157
and their combined interactions. 158
Although the above study demonstrates how a community versus a population 159
analysis can result in a qualitative change in interpretation that affects management 160
decisions, it is important to know whether such reversals in interpretation are common 161
enough to warrant concern. Bailey and Whitham (2007) reviewed 85 studies and 417 162
tests that varied in the number of factors examined in scientific studies, which included 163
numbers of species, local to geographic scale, and number of years of the study (Figure 164
1). When the study included only one factor, there was no chance of detecting either a 165
significant interaction or a reversal in outcome as it is beyond the ability of the statistical 166
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approach. However, when 2 factors were include in the study, there was a 55% 167
probability of detecting a significant interaction term (solid bars) and this probability 168
increased to nearly 95% when 4 factors were included in the analysis. Note that such an 169
interaction term could be just a „quantitative‟ change in which the sign of an interaction 170
would still remain the same (i.e., negative remains negative, and positive remains 171
positive). More importantly, they found that as the number of factors increased, the 172
number of reversals also increased such that when the analysis included 4 factors, there 173
was a nearly 80% probability that the sign of the interaction of one or more factors 174
reversed from negative to positive or positive to negative. These „qualitative‟ changes in 175
interpretation are the most vexing, as they have a high probability of resulting in 176
fundamental management errors. This study concluded that to avoid such errors, 177
conservation biologists and managers need to adopt a long-term, community approach 178
that covers a large geographic area. 179
Because species interact with one another (i.e., it is a multivariate world), only by 180
including the major interacting species can one really understand the sign of the 181
interactions. This is why a community approach is desirable and is less likely to result in 182
management errors that are both costly and produce unintended effects. 183
184
Heritable community and ecosystem phenotypes 185
To justify a community genetics approach it is essential to demonstrate that 186
community and ecosystem phenotypes exist and that they are heritable. Although 187
numerous studies in diverse systems have shown that different genotypes support 188
different community members and ecosystem processes (see references in introduction), 189
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only a few studies have quantified the heritability of community and ecosystem 190
phenotypes (e.g., arthropod diversity on evening primrose – Johnson & Agrawal 2005; 191
Johnson et al. 2006; arthropod community composition, soil microbial community 192
composition, and trophic interactions on narrowleaf cottonwood – Shuster et al. 2006; 193
Schweitzer et al. 2008; Bailey et al. 2006, respectively). For example, Figure 2 shows 194
that the canopy arthropod community on narrowleaf cottonwood (Populus angustifolia) 195
was under strong genetic control such that regardless of where replicate clones of the 196
same tree genotype were planted within a common garden, they tended to accumulate and 197
support the same community of arthropods (Shuster et al. 2006). Because this study 198
utilized replicate clones of individual tree genotypes, we calculated broad-sense 199
community heritability (H2
c), which estimates that genetic factors account for about 60% 200
of the variation in the canopy arthropod community (H2
c = 0.60). 201
In another common garden study of the soil microbial community, Schweitzer et 202
al. (2008) assessed the microbial community composition in bulk soil beneath tree 203
canopies using phospholipid fatty acid (PLFA) biomarkers (Figure 2). PLFAs are unique 204
to major taxonomic groups (e.g., gram positive and gram negative bacteria, and fungi) 205
and 30 different groups were identified. Their analysis found a strong tree genetic 206
component to microbial community composition (H2
c = 0.70). Schweitzer et al. (2008) 207
also found soil microbial biomass nitrogen (N) exhibited high broad-sense heritability 208
(H2 = 0.61), indicating a genetic basis for soil N pools stored in microorganims. This 209
latter finding is important because soil microorganisms mediate many ecosystem 210
processes, including litter decomposition, rates of nutrient mineralization, and nutrient 211
pools. Since these nutrient pools are genotype dependent, the formation of different 212
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microbial communities beneath different tree genotypes may feed back to affect plant 213
fitness. If so, this would establish a crucial link between the microbial community and 214
plant fitness that could pave the way for ecosystem science to be placed within an 215
evolutionary framework (Bever et al. 1997; Hooper et al. 2000; Whitham et al. 2003; 216
Bartelt-Ryser et al. 2005). 217
The potential for similar feedbacks on plant performance also exist aboveground 218
in the interactions of insect herbivores and their avian predators (Figure 2). For example, 219
the presence or absence of the leaf-galling aphid, Pemphigus betae, is determined by 220
susceptible or resistant tree genotypes. This interaction predictably affects other trophic 221
levels and alters the composition of a diverse community of fungi, insects, spiders, and 222
avian predators (Dickson & Whitham 1996; Bailey et al. 2006). In combination, these 223
and other studies described above suggest that indirect genetic interactions among 224
relatively few foundation species (e.g., tree, herbivore, predator, mutualist, and/or 225
pathogen) and their environment may structure the composition and abundance of a much 226
larger community of organisms, which could then feed back to affect the performance of 227
individual tree genotypes. 228
An important goal for understanding the ecology, evolution, conservation and 229
management of any ecosystem is to define how many foundation species (plants, animals, 230
microbes) define a given ecosystem and their extended effects on associated species. 231
Understanding the genetics (genotypic or genetic variation therein) of foundation species 232
in a community context is likely to be more informative than the genetics of most other 233
species (e.g., rare species) and should result in fewer management errors than single 234
factor or population approaches. So far, our findings suggest that the study of relatively 235
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few foundation species in a community context can tell us much about a larger system 236
involving many species. If correct, then the conservation and management of whole 237
ecosystems may be more tractable than previously thought as all species are not equally 238
important in „driving‟ the system. This does not imply that these species are not 239
important or deserving of preservation. It simply argues that the interactions of relatively 240
few species structure an ecosystem and that many species respond to rather than create 241
the conditions required by other species for their survival. If concentrating on the 242
community genetics of foundation species proves generally correct, it would greatly 243
simplify the dilemma of having to understand the complex interactions of all species to 244
make appropriate management decisions, which is a daunting if not impossible task. 245
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Conservation consequences of heritable phenotypes 247
If different genotypes of a foundation tree species support different community 248
members and ecosystem processes as the above heritability studies demonstrate, several 249
key predictions can be made, which are of conservation and management value. First, if 250
different tree genotypes support different communities, we would expect that the 251
genotypes that are genetically most similar will support the most similar communities. 252
At both local and regional levels, Bangert et al. (2006a, b) found that genetically similar 253
cottonwoods supported similar arthropod communities, whereas genetically dissimilar 254
plants supported more different communities (i.e., a genetic similarity rule hypothesis). 255
For example, using a Mantel test to compare the molecular marker and arthropod 256
community matrices of individual trees, trees that were the most genetically similar, were 257
also the most similar in their arthropod communities (Figure 3). This pattern holds for 258
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trees growing in a common garden, for trees growing in the wild in a single river (Figure 259
3; Bangert et al. 2006a), and for trees growing throughout the American West in multiple 260
river systems covering 720,000 km2 (Bangert et al. 2006b). Studies with blue gum 261
(Eucalyptus globulus) in Australia showed a similar pattern in which the most genetically 262
similar trees and geographic races also supported more similar canopy communities 263
(Barbour et al. 2009). In both studies the correlation in divergence in molecular and 264
community variation was mediated through correlated divergence in quantitative traits 265
such as leaf morphology and chemistry. Although it is well known that many specialist 266
insects may show corresponding divergence that is correlated with the divergence of their 267
host plant species (e.g., Abbot & Withgott 2004), it appears that the same pattern holds 268
for less specialized community members. From a conservation perspective, the findings 269
of Figures 2 and 3 argue that genetic diversity in a foundation tree species matters for the 270
dependent community of microbes, arthropods, and vertebrates. 271
Second, if different tree genotypes support different communities, then greater 272
genetic diversity in a foundation species should be directly correlated with greater 273
community diversity. Based on this prediction, Wimp et al. (2004) used AFLP molecular 274
markers to quantify genetic variation in 11 different stands of cottonwoods growing along 275
the Weber River in Utah, U.S.A. The arthropod community was then censused for the 276
same trees and they found that stand genetic diversity accounted for about 60% of the 277
variation in the diversity of an arthropod community composed of 207 species (Figure 278
4). Similar findings were obtained with oaks (Quercus spp.; Tovar-Sanchez & Oyama 279
2006). Experimental studies that manipulated genetic diversity with evening primrose 280
(Oenothera biennis) and goldenrod (Solidago altisima) also showed that genetically 281
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diverse patches supported significantly greater species richness than monocultures 282
(Johnson et al. 2006; Crutsinger et al. 2006, respectively). 283
Third, if individual plant genotypes support different communities, they also may 284
drive genetic differentiation and speciation in dependent community members. Several 285
studies have found that populations of herbivores are adapted to individual host 286
genotypes (Karban 1989; Mopper 1996; Mopper et al. 1995, 2000; Evans et al. 2008). 287
Because speciation may follow from locally adapted, differentiated populations of 288
arthropods (Via 2001; Dres & Mallet 2002), conserving genotypic diversity in foundation 289
species can conserve locally adapted populations of arthropods. This may extend to 290
multiple trophic levels. For example, multiple herbivores (Stireman et al. 2005) and their 291
parasitoids (Stireman et al. 2006) are genetically differentiated on two closely related 292
sympatric species of Solidago indicating that host plants can affect species‟ evolution at 293
multiple tropic levels. A major conclusion from such studies is that genetic diversity is 294
far more than just an endangered species issue, it is also very important for common 295
foundation species in which different plant genotypes support different community 296
members. 297
Fourth, when different genotypes of a foundation species support different 298
communities, management practices based on species-area relationships may need to 299
shift to genetic diversity-area relationships. In other words, is the species-area curve 300
really driven by area, or is it driven by the genetic diversity of the foundation species, or 301
some combination of both? To answer this question, Bangert et al. (2008) quantified the 302
arthropod species accumulation curve for broadleaf cottonwoods (Figure 5a). This curve 303
shows that as the arthropod communities of more trees are sampled (i.e., area), arthropod 304
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species richness rises predictably and begins to plateau. This is a common pattern and is 305
a primary justification for the conservation practice of preserving large areas to capture 306
the species pool. However, when molecular marker diversity for the same trees was 307
analyzed to produce a molecular marker richness accumulation curve, the same pattern 308
emerged. This curve shows that as the molecular markers of more trees are sampled (i.e., 309
area), marker richness also rises predictably and begins to plateau. These two curves are 310
remarkably similar. Furthermore, arthropod species richness is highly correlated with 311
molecular marker richness (r2 = 0.92; Figure 5b). This strong correlation raises the 312
issue, is the species-area curve driving biodiversity or is it the genetic diversity of the 313
foundation species that drives biodiversity, or some combination of the two? Although 314
area and genetic diversity of foundation species are undoubtedly autocorrelated, from a 315
manager‟s perspective it is important to know whether a landscape should be managed 316
from an area perspective or from the genetic diversity of a foundation species‟ 317
perspective. Furthermore, if future conservation efforts try to establish living repositories 318
for individual species, it is important to define the genetic diversity of these repositories 319
that will be required to support their dependent communities. 320
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A community genetics perspective on minimum viable populations 322
Historically, an important concept in conservation biology is the minimum viable 323
population (MVP), which is the size of a population that, with a given probability, will 324
ensure the existence of the population for a stated period of time (Shaffer 1981; Gilpin 325
1987). This concept is especially important for rare and endangered species whose 326
populations are often small, highly inbred and lacking in genetic diversity. While this 327
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concept attempts to understand what population sizes are required to save a single 328
species, it falls short of understanding the population size that is necessary to save 329
dependent community members. This concern is especially relevant for species that 330
require a single host species or a subset of the host‟s genotypes for their survival. 331
An example of how the distribution, population growth rate and evolution of one 332
species can be dependent upon genotypic differences of another species is that of the gall-333
forming mite, Aceria parapopuli, on cottonwoods. McIntyre and Whitham (2003) found 334
that 99% of the mite‟s population was concentrated on naturally occurring F1 hybrids 335
between narrowleaf and Fremont cottonwood (P. angustifolia, P. fremontii, respectively). 336
Because suitable F1 hybrid hosts are rare in the wild, the „„actual‟‟ host population for 337
these mites is a small subset of the larger cottonwood population. Furthermore, Evans et 338
al. (2008) showed that the mites are even further differentiated such that the mites on the 339
hybrids and parental hosts are different cryptic species. Transfer experiments showed 340
that even among F1 hybrids the mites can be adapted to individual tree genotypes. Thus, 341
even though cottonwoods are very common trees in riparian forests, a dependent species 342
can still be limited by the number of suitable host genotypes. 343
Even generalist species can be genetically differentiated and highly specialized at 344
the local level (Thompson 1994). The eastern tiger swallowtail, Papilio glaucus, has a 345
large list of host species, but at a local scale, it can be very host specific (Scriber 1986). 346
Other examples are provided by Feder et al. (1988), Wood & Keese (1990), Roinen et al. 347
(1993), and Thompson (1994). Microorganims can exhibit even greater specificity. 348
Gene-specific interactions between Rhizobium leguminosarum bv. viciae and native 349
Afghani pea plants (Pisum sativum) regulate symbiosis. The loss of a single gene will 350
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disrupt the symbiotic interaction and prevent nitrogen fixation (Vijn et al. 1993). 351
Specificity in gene-for-gene interactions in molecular control points between plants and 352
microorganisms in the rhizosphere is thought to be widespread in many foundation 353
species (Hirsch et al. 2003; Phillips et al. 2003). 354
Such specificity suggests that minimum viable population (MVP) sizes (Shaffer 355
1981) in one species may be too small to support important interactions with other 356
species (see Thompson 1994). Other researchers have recognized the weaknesses 357
associated with the conservation of individual species rather than communities or 358
ecosystems (e.g., Rohlf 1991; Simberloff 1998; Lindenmayer et al. 2007). A community 359
genetics approach enhances our toolbox for understanding why the genetics of foundation 360
species are so important, provides genetic-based mechanisms to support these criticisms, 361
and has the potential to merge different points of view as it spans genes-to-ecosystems. 362
Because of these issues, Whitham et al. (2003) proposed the minimum viable 363
interacting population size (MVIP) that represents the size of a population needed to 364
maintain the genetic diversity at levels required by other dependent and interacting 365
species in a community context. For example, minimum viable population (MVP) sizes 366
for conserving a foundation tree species are probably much smaller than the population 367
size required to conserve other dependent community members that require a subset of 368
the tree‟s genotypes for their survival (MVIP). Thus, MVP represents the lower end of 369
the population size that is required to conserve the foundation species, and MVIP 370
represents the upper end of the population size of the foundation species that is required 371
to conserve the dependent community and their interactions. Figure 6 provides an initial 372
guide as to where the differences between MVP for a foundation species and MVIP for a 373
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foundation species and its dependent community would be expected to be highest and 374
lowest. High community and ecosystem heritability (H2
c) suggests that many community 375
members and the ecosystem processes they drive are dependent on the individual 376
genotypes of a foundation species, whereas low or non-significant H2
c suggests that the 377
distributions of most community members are not genotype dependent. Thus, as 378
community heritability increases for any given foundation species, we would expect that 379
the difference between MVP and MVIP would also increase. 380
MVP and MVIP represent end points on the population to community continuum. 381
They provide a conceptual mechanism for why conservation efforts may flounder if they 382
do not consider the consequences of genetic variation in foundation species on the 383
dependent community. Numerous studies show that temperate and boreal trees exhibit 384
moderate to strong clines in ecologically important traits suggesting that populations are 385
genetically differentiated and locally adapted (Aitken et al. 2008). Associated with this 386
genetic structuring, common garden studies of Barbour et al. (2009) showed that different 387
geographic races of the same eucalypt species supported different communities. 388
Although current conservation strategies target rare species, it may be even more 389
important to conserve the genetic variation in foundation species with broad distributions, 390
because individual genotypes and races have different community and ecosystem 391
phenotypes. 392
393
Community phenotypes of genetically engineered organisms 394
Although the incorporation of novel genes into an organism through recombinant 395
DNA technology has enormous potential benefits, including increasing crop yields and 396
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reducing reliance on chemical pesticides (Avise 2003), the genes introduced into GEOs 397
(genetically engineered organisms) may have unintended community and ecosystem 398
phenotypes that are important to evaluate. Several issues need to be considered. First, 399
GEOs now have been introduced over large areas in both industrialized and developing 400
economies. For example, the global area planted with transgenic crops exceeded 110 401
million hectares in 2007, a 12% increase over the previous year (Lawrence 2008). 402
Because many of these crops are grown as monocultures with little genetic variation, they 403
are, in effect, both a foundation species and a foundation genotype. 404
Second, there is increasing evidence that transgenic organisms can move beyond 405
their intended destinations where they have the potential to persist and to hybridize with 406
native species. Maximal gene flow distances of 21 km were observed in herbicide 407
(glyphosate) resistant creeping bent grass (Agrostis stolonifera L.), a wind-pollinated out-408
crossing perennial turf grass planted in test fields in Oregon (Watrud et al. 2004). Three 409
years after the test fields were taken out of production, 62% of plants tested were 410
glyphosate-resistant (Zapiola et al. 2008). There is evidence that transgenic canola 411
(Brassica napus) and sunflower (Helianthus annuus) hybridize with wild relatives, 412
though the fitness of these hybrids is highly variable and frequently not greater than wild 413
genotypes (reviewed in Chapman & Burke 2006). Recent research also suggests that the 414
risk of environmental impact from horizontal gene transfer of bacterial genes from crops 415
to surrounding soil microorganisms is much higher than initially supposed (Heinemann & 416
Traavik 2004). In their review, Marvier and Van Acker (2005) concluded that movement 417
of transgenes beyond their intended destinations is a “virtual certainty”. 418
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A third reason that transgenics may have unintended ecological consequences for 419
communities and ecosystems is that transgenes are designed to have significant fitness 420
consequences (e.g., reducing herbivory, disease or competition) thereby increasing the 421
likelihood that transgenics will interact significantly with members of the communities in 422
which they are introduced. Furthermore, crops with stacked traits (two or more 423
transgenes) are now more widely planted than those containing only insect resistance 424
traits (Lawrence 2008). 425
Transgenics have been shown to have non-target community and ecosystem 426
phenotypes. For example, Bt corn byproducts can enter headwater streams where they 427
are stored, consumed and transported downstream to other bodies of water. Feeding 428
trials in the laboratory indicate that Bt corn residues negatively affect non-target stream 429
insects (Rosi-Marshall et al. 2007). However, recent meta-analyses highlight the need 430
for comparison of the effects of transgenes to those of traditional agricultural practices. 431
An analysis of 42 experiments showed that Bt cotton and corn altered the abundance of 432
some taxa of non-target arthropods, but the effects of the transgenes were much smaller 433
than those of traditional pesticides (Marvier et al. 2007). Likewise, consistent effects of 434
Bt corn, cotton and potatoes on particular functional guilds of non-target arthropods were 435
not observed (Wolfenbarger et al. 2008). A recent review of Bt plant effects on the soil 436
biota also found few significant impacts (Icoz & Stotzky 2008). Note that most studies of 437
non-target effects of transgenic organisms are relatively short-term and thus may ignore 438
effects that accumulate slowly or are triggered by a change in environmental conditions. 439
A community genetics analysis provides a method for quantifying the community 440
and ecosystem phenotypes of transgenes and their heritability. Importantly, in many 441
20
ecological studies, the direct effects of a trait on an organism‟s phenotype (e.g., increased 442
resistance to pest attack) may be less important than the indirect effects on the 443
community phenotype (e.g., increased resistance to pest attack alters competitive 444
interactions with other species to alter community structure). The movement of 445
transgenes into wild populations, via hybridization and introgression, could alter 446
interspecific interactions potentially resulting in changes in the distribution of the wild 447
population and its dependent community. Few studies of GEOs examine the 448
consequences of transgenes on interactions among organisms, particularly indirect 449
interactions. In addition, subtle, initial changes in interactions between transgenic and 450
wild populations may not be detected in short-term studies that are frequently limited in 451
spatial scale as well. The community and ecosystem consequences of transgenes are also 452
important to define because of the growing view that transgenes will escape from their 453
intended destination and that they cannot be retracted once they have escaped (Marvier & 454
Van Acker 2005). Once released, some transgenes may have irreversible conservation 455
implications for communities and ecosystems. These possible negative consequences of 456
GEOs should be considered along with their potential benefits such as promoting 457
agricultural efficiency and reducing pesticide use. 458
459
Community genetics and climate change 460
Climate change is a „wild card‟ in conservation and restoration. Because of 461
concerns about restoring only with locally adapted genotypes, the policies of most 462
agencies require the use of local stock in restoration. While this is a valid view in an 463
unchanging world, in a dynamic world facing major vegetation shifts in response to 464
21
climate change, the „local‟ environment may well shift so fast or so much that local 465
genotypes will no longer be locally adapted (see also Aitken et al. 2008). In the 466
American Southwest, the effects of climate change are pronounced and affecting the 467
distributions of pinyon pine (Pinus edulis), cottonwood (Populus fremontii), ponderosa 468
pine (Pinus ponderosa), aspen (Populus tremuloides), and manzanita (Arctostaphylos 469
pungens), which are foundation species of their respective communities from low 470
elevation deserts to mountain forests (Breshears et al. 2005; Mueller et al. 2005; Gitlin et 471
al. 2006). For example, climate change models of Rehfeldt et al. (2006) predict that the 472
climate envelopes for both pinyon pine (Pinus edulis) and saguaro cactus (Carnegiea 473
gigantea) will shift out of Arizona by 2090 where they are currently foundation species 474
that define their respective communities (Figure 7). Such dramatic shifts in the 475
distributions of these species are likely to represent both ecological and evolutionary 476
events, and major conservation challenges. If these shifts come about, Saguaro National 477
Monument will no longer contain saguaros, and for saguaros to physically reach their 478
new climate envelope in eastern Nevada, human assisted migration will likely be required 479
(McLachlan et al. 2007; Aitken et al. 2008). 480
One factor that can potentially alleviate such dramatic shifts in distribution is the 481
potential for selection to favor more drought adapted genotypes that allow species to 482
persist in areas where they might otherwise go locally extinct. For example, Franks et al. 483
(2007) found rapid evolution in flowering time of field mustard (Brassica rapa) in 484
response to altered growing seasons over just seven years. Post-drought descendants of 485
this annual bloomed earlier than pre-drought ancestors, advancing first flowering by as 486
much as 9 days. The intermediate flowering time of ancestor x descendant hybrids 487
22
supports an additive genetic basis for this divergence. Even vertebrate species appear 488
capable of rapid evolutionary responses to climate change. Over a 30 year period, Grant 489
and Grant (2002) observed rapid evolution in the shape and size of beaks of finches in 490
association with climate change driven changes in seed availability. 491
So, what is the community genetics connection to climate change? If climate 492
change acts as an agent of selection to alter the frequency distribution of genotypes of 493
foundation species, then their dependent communities will also be affected. For example, 494
Whitham et al. (2003) showed that approximately 1000 species of organisms from 495
microbes to vertebrates were differentially associated with insect resistant and susceptible 496
pinyon pine (P. edulis). Recent studies by Sthultz et al. (2009) showed that insect 497
resistant trees were three times more likely to die than susceptible trees during a record 498
drought and that the change in the distribution of resistant and susceptible phenotypes on 499
the landscape had changed from resistant-dominated stands to near parity. Thus, even if 500
a foundation species survived in a given habitat, the change in its genetic structure is 501
likely to affect dependent community members whose distributions are also dependent 502
upon the genotypes of the foundation plant species (see earlier sections). 503
Rehfeldt et al. (2006) used climate envelopes to predict the future distributions of 504
many tree species of the western USA, including P. edulis. They concluded that P. edulis 505
would be extirpated from Arizona within 80 years. This prediction, however, did not 506
include potentially drought adapted genotypes of P. edulis or reflect the genetic variation 507
among populations that might exist over its large geographic distribution. In contrast, a 508
few other models have incorporated intraspecific genetic variation and demonstrated its 509
potential influence on climate change projections. For example, based on provenance 510
23
trials involving 140 populations tested at 62 sites throughout most of the range of 511
lodgepole pine, P. contorta, O‟Neill et al. (2008) included genetic differences in the 512
performance of these populations into their models. Because populations tend to be 513
locally adapted, these models predicted that different populations would vary greatly in 514
their responses to climate change and that many populations would be maladapted to 515
their new local environment. This provenance trial approach also provides an 516
experimental method for identifying which populations and genotypes might best survive 517
predicted climate changes. Thus, for species where such provenance trials already exist, 518
the use of this powerful experimental approach could greatly enhance the precision of 519
climate change models. 520
From these examples, it would appear that climate change creates a conundrum 521
for conservation biologists and managers. If our management policies require restoration 522
with local genotypes, in a climate change scenario are we then planting the very 523
genotypes that are doomed to fail? Few studies with foundation species are in place to 524
provide clear information for managers to make appropriate decisions (but see O‟Neill et 525
al. 2008). We need a national network of common gardens for foundation species in 526
which genotypes from the whole range of a species‟ distribution are planted reciprocally 527
within their current range and their predicted new ranges. Only with such empirical 528
information can we identify the specific genotypes and source populations that are best 529
suited to current and predicted future local conditions. 530
531
Management conclusions 532
24
A community and ecosystem genetics approach is based upon the fundamental finding 533
that individual genotypes or populations of foundation species have heritable community 534
and ecosystem phenotypes (Figure 2). Because this finding has emerged from diverse 535
systems on different continents, our review explores five management implications. 1. 536
Management practices should be based upon conserving genetic diversity in foundation 537
species. Because different genotypes support different communities (Figures 2 & 3), 538
greater biodiversity will be achieved by preserving the greatest genetic diversity in the 539
foundation species (e.g., Figure 4). 2. It is important for managers to determine if they 540
should be managing for area, the genetic diversity of the foundation species or some 541
combination of both. This is due to the fact that the species-area curve (i.e., the current 542
basis of the management practice of setting aside large geographical areas to capture the 543
maximum number of species in preserves) is also highly correlated with the genetic 544
diversity of foundation species-area curve (Figure 5). 3. Managers should incorporate 545
the concept of the minimum viable interacting population (MVIP) to conserve 546
biodiversity. Because the distribution of many species is dependent upon a subset of the 547
genotypes of a foundation species, the population size of the foundation species required 548
to support all of its dependent community members is much larger than that needed to 549
save the foundation species itself (Figure 6). 4. We need management protocols that 550
specifically quantify the unintended ecosystem effects of genetically engineered 551
organisms (i.e., their community and ecosystem phenotypes) as part of the evaluation 552
process for commercial release. 5. Managing for climate change by establishing 553
provenance trials of foundation species throughout their current and predicted range is 554
needed to identify the genotypes and source populations that are most likely to survive, 555
25
reproduce and support their dependent communities in a new climate. These are a few of 556
the management issues that arise when we apply a community and ecosystem genetics 557
approach rather than just a population genetics approach. 558
As an initial step to achieve these goals, it would be especially helpful and cost 559
effective if managers took the additional step of tagging and recording the donors used 560
for propagation (both for seeds and cuttings) and then tagged the individuals used in 561
restoration plantings. It is especially important to do this for each of the known or 562
suspected foundation species as these are the primary „drivers‟ that define and structure 563
the rest of the community. Although such „book keeping‟ would represent a small 564
fraction of the overall cost of a restoration project, the value added could be great and 565
result in cost savings in future restoration projects. If multiple source populations and 566
genotypes were used, managers could identify which genotypes and source populations 567
were best adapted to a specific planting site. Even poorer performers may have high 568
future value because those that perform best under current climatic conditions may not be 569
the best with future climatic conditions (e.g., Sthultz et al. 2009). Performance data 570
combined with climate change models could be used to identify which source populations 571
and genotypes might best suit a predicted future climate. Because many plants used in 572
restoration are long-lived, once restoration sites are established, they can also be used for 573
the life of the site to quantify the diverse communities of organisms they support as a 574
function of the individual genotypes and source populations used in the restoration 575
project. Since species evolve in a community context, then we must ultimately conserve 576
and manage species in a community context. 577
578
26
Acknowledgements 579
We thank an NSF Frontiers of Integrative Biological Research grant for bringing together 580
diverse scientists to help integrate and develop the emerging field of community and 581
ecosystem genetics. NSF IGERT and Science Foundation Arizona grants supported 582
student research; The Australian Research Council (grants DP0451533 and DP0773686) 583
supported parallel studies in Australia, and NSF grant DEB-0816675 supported climate 584
change research in the U.S.A. The Ogden Nature Center, the Utah Department of Natural 585
Resources and Reclamation provided lands for common gardens, restoration and public 586
outreach. 587
588
References Cited 589
Abbot P, Withgott JH (2004) Phylogenetic and molecular evidence for allochronic 590
speciation in gall-forming aphids (Pemphigus). Evolution, 58, 539-553. 591
Aitken SN, Yeaman S, Holliday JA et al. (2008) Adaptation, migration or extirpation: 592
climate change outcomes for tree populations. Evolutionary Applications, 1, 95-593
111. 594
Araki R, Mori M, Mori M et al. (2005) Genetic differences in nitrate uptake in two 595
clones of the common reed, Phragmites australis. Breeding Science, 55, 297-302. 596
Avise JC (2003) The best and the worst of times for evolutionary biology. BioScience, 597
53, 247-255. 598
Bailey JK, Schweitzer JA, Rehill BJ et al. (2004) Beavers as molecular geneticists: A 599
genetic basis to the foraging of an ecosystem engineer. Ecology, 85, 603-608. 600
27
Bailey JK, Whitham TG (2007) Biodiversity is related to indirect interactions among 601
species of large effect. In: Ecological Communities: Plant Mediation in Indirect 602
Interaction Webs (eds Ohgushi T, Craig TP, Price PW), pp. 306-328. Cambridge 603
University Press, UK. 604
Bailey JK, Schweitzer JA, Úbeda F et al. (2009) From genes to ecosystems: A synthesis 605
of the effects of plant genetic factors across levels of organization. Philosophical 606
Transactions of the Royal Society B, (in press). 607
Bailey JK, Wooley SC, Lindroth RL et al. (2006) Importance of species interactions to 608
community heritability: A genetic basis to trophic-level interactions. Ecology 609
Letters, 9, 78-85. 610
Bangert RK, Lonsdorf EV, Wimp GM et al. (2008) Genetic structure of a foundation 611
species: scaling community phenotypes from the individual to the region. 612
Heredity, 100, 121-131. 613
Bangert RK, Turek RJ, Martinsen GD et al. (2005) Benefits of conservation of plant 614
genetic diversity on arthropod diversity. Conservation Biology, 19, 379–390. 615
Bangert RK, Turek RJ, Rehill B et al. (2006) A genetic similarity rule determines 616
arthropod community structure. Molecular Ecology, 15, 1379–1392. 617
Barbour RC, O'Reilly-Wapstra JM, De Little DW et al. (2009) A geographic mosaic of 618
genetic variation within a foundation tree species and its community-level 619
consequences. Ecology (in press). 620
Bartelt-Ryser J, Joshi J, Schmid B et al. (2005) Soil feedbacks of plant diversity on soil 621
microbial communities and subsequent plant growth. Perspectives in Plant 622
Ecology, Evolution and Systematics, 7, 27–49. 623
28
Bever JD, Westover KM, Antonovics J (1997) Incorporating the soil community into 624
plant population dynamics: the utility of the feedback approach. Journal of 625
Ecology, 85, 561–573. 626
Breshears DB, Cobb NS, Rich PM et al. (2005) Regional vegetation die-off in response 627
to global-change-type drought. Proc. Natl. Acad. Sci. USA, 102, 15144–15148. 628
Chapman MA, Burke JM (2006) Letting the gene out of the bottle: the population 629
genetics of genetically modified crops. New Phytologist, 170, 429-443. 630
Craig TP, Itami JK, Craig JV (2007) Host plant genotype influences survival of hybrids 631
between Eurosta solidaginis host races. Evolution, 61, 2607-2613. 632
Crawford KM, Crutsinger GM, Sanders NJ (2007) Host-plant genotypic diversity 633
mediates the distribution of an ecosystem engineer. Ecology, 88, 2114-2120. 634
Crutsinger GM, Collins MD, Fordyce JA et al. (2006) Plant genotypic diversity predicts 635
community structure and governs an ecosystem process. Science, 313, 966–968. 636
Dayton PK (1972) Toward an understanding of community resilience and the potential 637
effects of enrichments to the benthos at McMurdo Sound, Antarctica. In: 638
Proceedings of the Colloquium on Conservation Problems (ed Parker BC), pp. 639
81-96. Allen Press, Lawrence, Kansas. 640
Dickson LL, Whitham TG (1996) Genetically-based plant resistance traits affect 641
arthropods, fungi, and birds. Oecologia, 106, 400–406. 642
Donaldson JR, Lindroth RL (2007) Genetics, environment, and their interaction 643
determine efficacy of chemical defense in trembling aspen. Ecology, 88, 729-739. 644
Dres M, Mallet J (2002) Host races in plant-feeding insects and their importance in 645
sympatric speciation. Phil. Trans. R. Soc. Lon. B. Biol. Sci., 357, 471-492. 646
29
Driebe EM, Whitham TG (2000) Cottonwood hybridization affects tannin and nitrogen 647
content of leaf litter and alters decomposition. Oecologia, 123, 99-107. 648
Dungey HS, Potts BM, Whitham TG et al. (2000) Plant genetics affects arthropod 649
community richness and composition: evidence from a synthetic eucalypt hybrid 650
population. Evolution, 54, 1938–1946. 651
Ellison AM, Bank MS, Clinton BD et al. (2005) Loss of a foundation species: 652
consequences for the structure and dynamics of forested ecosystems. Frontiers in 653
Ecology and the Environment, 3, 479–486. 654
English-Loeb G, Norton A (2006) Lack of trade-off between direct and indirect defence 655
against grape powdery mildew in riverbank grape. Ecological Entomology, 31, 656
415-422. 657
Evans LM, Allan GJ, Shuster SM et al. (2008) Tree hybridization and genotypic variation 658
drive cryptic speciation of a specialist mite herbivore. Evolution, 62, 3027-3040. 659
Feder JL, Chilcote CA, Bush GL (1988) Genetic differentiation between sympatric host 660
races of the apple maggot fly Rhagoletis pomonella. Natur, 336, 61-64. 661
Fischer DG, Hart SC, LeRoy CJ et al. (2007) Decoupled fine root production and total 662
belowground carbon allocation in Populus forests. New Phytologist, 176, 415-663
425. 664
Fischer DG, Hart SC, Rehill BJ et al. (2006) Do high-tannin leaves require more roots? 665
Oecologia, 149, 668-675. 666
Fischer DG, Hart SC, Whitham TG et al. (2004) Ecosystem implications of genetic 667
variation in water-use of a dominant riparian tree. Oecologia, 139, 188-197. 668
30
Fischer DG, Hart SC, Whitham TG et al. (2006) Hidden belowground responses to 669
defense: Do highly defended leaves require more roots? Oecologia, 149, 668-675. 670
Fritz RS, Price PW (1988) Genetic variation among plants and insect community 671
structure: Willows and sawflies. Ecology, 69, 845-856. 672
Gilpin ME (1987) Minimum viable populations: A restoration ecology perspective. In: 673
Restoration Ecology a Synthetic Approach to Ecological Research (eds Pages 674
301-305 in Jorden iii WR, Gilpin ME, Aber JD), pp. 301-305. Cambridge 675
University Press, Cambridge, England. 676
Gitlin AR, Sthultz CM, Bowker MA et al. (2006) Mortality gradients within and among 677
dominant plant populations as barometers of ecosystem change during extreme 678
drought. Conservation Biology, 20, 1477-1486. 679
Grant PR, Grant BR (2002) Unpredictable evolution in a 30-year study of Darwin‟s 680
finches. Science, 296, 707–711. 681
Heinemann JA, Traavik T (2004) Problems in monitoring horizontal gene transfer in field 682
trials of transgenic plants. Nature Biotechnology, 23, 488. 683
Hirsch AM, Bauer WD, Bird DM et al. (2003) Molecular signals and receptors: 684
controlling rhizosphere interactions between plants and other organisms Ecology, 685
84, 858–868 686
Hochwender CG, Fritz RS (2004) Plant genetic differences influence herbivore 687
community structure: evidence from a hybrid willow system. Oecologia, 138, 688
547–557. 689
31
Hooper DU, Bignell DE, Brown VK et al. (2000) Interaction between aboveground and 690
belowground biodiversity in terrestrial ecosystems: patterns, mechanisms and 691
feedbacks. BioScience 50, 1049–1061. 692
Hughes AR, Inouye BD, Johnson MTJ et al. (2008) Ecological consequences of genetic 693
diversity. Ecology Letters, 11, 609-623. 694
Hughes AR., Stachowicz JJ (2004) Genetic diversity enhances the resistance of a 695
seagrass ecosystem to disturbance. Proc. Natl. Acad. Sci. USA, 101, 8998-9002. 696
Icoz I, Stotzky G (2008) Fate and effects of insect-resistant Bt crops in soil ecosystems. 697
Soil Biology and Biochemistry, 40, 559–586 698
Johnson MTJ (2008) Bottom-up effects of plant genotype on aphids, ants and predators. 699
Ecology, 89, 145-154. 700
Johnson MTJ, Agrawal AA (2005) Plant genotype and the environment interact to shape 701
a diverse arthropod community on evening primrose (Oenothera biennsis). 702
Ecology, 18, 549–551. 703
Johnson MTJ, Lajeunesse MJ, Agrawal AA (2006) Additive and interactive effects of 704
plant genotypic diversity on arthropod communities and plant fitness. Ecology 705
Letters, 9, 24–34. 706
Johnson MTJ, Stinchcombe JR (2007) An emerging synthesis between community 707
ecology and evolutionary biology. Trends in Ecology and Evolution, 22, 250-257. 708
Johnson MTJ, Stinchcombe JR (2007) An emerging synthesis between community 709
ecology and evolutionary biology. Trends. Ecol. Evol., 22, 250-257. 710
Karban R (1989) Fine-scale adaptation of herbivorous thrips to individual host plants. 711
Nature, 340, 60-61. 712
32
Keim P, Paige KN, Whitham TG et al. (1989) Genetic analysis of an interspecific hybrid 713
swarm of Populus: occurrence of unidirectional introgression. Genetics, 123, 714
557–565. 715
Lawrence S (2008) Brazil surpasses US in new transgenic crop plantings. Nature 716
Biotechnology, 26, 260. 717
Lecerf A, Chauvet E (2008) Intraspecific variability in leaf traits strongly affects alder 718
leaf decomposition in a stream. Basic and Applied Ecology, 9, 598-605. 719
LeRoy CJ, Whitham TG, Keim P et al. (2006) Plant genes link forests and streams. 720
Ecology, 87, 255-261. 721
LeRoy CJ, Whitham TG, Wooley SC et al. (2007) Within-species variation in foliar 722
chemistry influences leaf-litter decomposition in a Utah river. Journal of the 723
North American Benthological Society, 26, 426-438. 724
Lindenmayer DB, Fischer J, Felton A et al. (2007) The complementarity of single-725
species and ecosystem-oriented research in conservation research. Oikos, 116, 726
1220-1226. 727
Maddox GD, Root RB (1987) Resistance to 16 diverse species of herbivorous insects 728
within a population of goldenrod, Solidago altissima: genetic variation and 729
heritability. Oecologia, 72, 8–14. 730
Madritch MD, Donaldson JR, Lindroth RL (2006) Genetic identity of Populus 731
tremuloides litter influences decomposition and nutrient release in a mixed forest 732
stand. Ecosystems, 9, 528-537. 733
33
Madritch MD, Donaldson JR, Lindroth RL (2007) Canopy herbivory can mediate the 734
influence of plant genotype on soil processes through frass deposition. Soil 735
Biology and Biochemistry, 39, 1192-1201. 736
Madritch MD, Hunter MD (2002) Phenotypic diversity influences ecosystem functioning 737
in an oak sandhills community. Ecology, 83, 2084-2090. 738
Madritch MD, Hunter MD (2004) Phenotypic diversity and litter chemistry affect nutrient 739
dynamics during litter decomposition in a two species mix. Oikos, 105, 125-131. 740
Marvier M, McCreedy C, Regetz J et al. (2007) A meta-anaylsis of effects of Bt cotton 741
and maize on non-target invertebrates. Science, 316,1475-1477. 742
Marvier M, VanAcker R (2005) Can crop transgenes be kept on a leash? Frontiers in 743
Ecology and the Environment, 3, 99-106. 744
McIntyre PJ, Whitham TG (2003) Plant genotype affects long-term herbivore population 745
dynamics and extinction: Conservation implications. Ecology, 84, 311-322. 746
McLachlan JS, Hellman JJ, Schwartz MW (2007) A framework for debate of assisted 747
migration in an era of climate change. Conservation Biology, 21, 297-302. 748
Mopper S (1996) Adaptive genetic structure in phytophagous insect populations. Trends 749
Ecol. Evol., 11, 235-238. 750
Mopper S, Beck M, Simberloff D et al. (1995) Local adaptation and agents of selection in 751
a mobile insect. Evolution, 49, 810-815. 752
Mopper S, Stiling P, Landau K et al. (2000) Spatiotemporal variation in leafminer 753
population structure and adaptation to individual oak trees. Ecology, 81, 1577-754
1587. 755
34
Mueller RC, Scudder CM, Porter ME et al. (2005a) Differential mortality in response to 756
severe drought: implications for long-term vegetation shifts. Journal of Ecology, 757
93, 1085-1093. 758
O‟Neill GA, Hamann A, Wang T (2008) Accounting for population variation improves 759
estimates of the impact of climate change on species‟ growth and distribution. 760
Journal of Applied Ecology, 45, 1040–1049. 761
Parmesan C (2006) Ecological and evolutionary responses to recent climate change. 762
Annual Review of Ecology, Evolution, and Systematics, 37, 637-669. 763
Phillips DA, Ferris H, Cook DR et al. (2003) Molecular control points in rhizosphere 764
food webs. Ecology, 84, 816–826. 765
Rehfeldt GE, Crookston NL, Warwell MV et al. (2006) Empirical analyses of plant-766
climate relationships for the western United States. International Journal of Plant 767
Sciences, 167, 1123-1150. 768
Reusch TBH, Ehlers A, Hammerlie A, et al. (2005) Ecosystem recovery after climatic 769
extremes enhanced by genotypic diversity. Proc. Natl. Acad. Sci. USA, 102, 770
2826-2831. 771
Rohlf, D. J. 1991. Six biological reasons why the Endangered Species Act doesn't work 772
-- and what to do about it. Conservation Biology 5:273-282. 773
Roinen H, Vuorinen J, Tahvanainen J et al. (1993) Host preference and allozyme 774
differentiation in shoot galling sawfly, Euura atra. Evolution, 47, 300-308. 775
Rosi-Marshall EJ, Tank JL, Royer TV et al. (2007) Toxins in transgenic crop byproducts 776
may affect headwater stream ecosystems. Proceedings of the National Academy 777
of Science, 104, 16204-16208. 778
35
Rudgers JA, Whitney KD (2006) Interactions between insect herbivores and a plant 779
architectural dimorphism. Journal of Ecology, 94, 1249-1260. 780
Schweitzer JA, Bailey JK, Fischer DG et al. (2008) Plant-soil microorganism 781
interactions: A heritable relationship between plant genotype and associated soil 782
microorganisms. Ecology, 89, 773-781. 783
Schweitzer JA, Bailey JK, Hart SC et al. (2005a) Nonadditive effects of mixing 784
cottonwood genotypes on litter decomposition and nutrient dynamics. Ecology, 785
86, 2834-2840. 786
Schweitzer JA, Bailey JK, Hart SC et al. (2005b) The interaction of plant genotype and 787
herbivory decelerate leaf litter decomposition and alter nutrient dynamics. Oikos, 788
110, 133–145. 789
Schweitzer JA, Bailey JK, Rehill BJ et al. (2004) Genetically based trait in a dominant 790
tree affects ecosystem processes. Ecology Letters, 7, 127-134. 791
Scriber JM (1986) Origins of the regional feeding abilities in the tiger swallowtail 792
butterfly: ecological monophagy and the Papilio glaucus australis subspecies in 793
Florida. Oecologia, 71, 94-103. 794
Seager R, Ting M, Held I et al. (2007) Model projections of an imminent transition to a 795
more arid climate in southwestern North America. Science, 316, 1181-1184. 796
Shaffer ML (1981) Minimum population sizes for species conservation. BioScience, 31, 797
131–134. 798
Shuster SM, Lonsdorf EV, Wimp GM et al. (2006) Community heritability measures the 799
evolutionary consequences of indirect genetic effects on community structure. 800
Evolution, 60, 991-1003. 801
36
Silfver T, Mikola J, Rousi M et al. (2007) Leaf litter decomposition differs among 802
genotypes in a local Betula pendula population. Oecologia, 152, 707-714. 803
Simberloff D (1998) Flagships, umbrellas, and keystones: is single-species management 804
passe in the landscape era? Biological Conservation, 83, 247-257. 805
Sthultz CM, Gehring CA, Whitham TG (2009) Deadly combination of genes and 806
drought: Increased mortality of herbivore-resistant trees in a foundation species. 807
Global Change Biology (in press). 808
Stireman JO III, Nason JD, Heard S (2005) Host-associated genetic differentiation in 809
phytophagous insects: General phenomenon or isolated exceptions? Evidence 810
from a goldenrod-insect community. Evolution, 59, 2573-2587. 811
Stireman JO III, Nason JD, Heard S et al. (2006) Cascading host-associated genetic 812
differentiation in parasitoids of phytophagous insects. Proceedings of the Royal 813
Society of London, Series B, 273, 523-530. 814
Thompson JN (1994) The Coevolutionary Process. University of Chicago Press, 815
Chicago. 816
Thompson JN (2005) The Geographic Mosaic of Coevolution. University of Chicago 817
Press, ChPicago. 818
Tovar-Sanchez E, Oyama K (2006) Effect of hybridization of the Quercus crassifolia x 819
Quercus crassipes complex on the community structure of endophagous insects. 820
Oecologia, 147, 702–713. 821
Treseder KK, Vitousek PM (2001) Potential ecosystem-level effects of genetic variation 822
among populations of Metrosideros polymorpha from a soil fertility gradient in 823
Hawaii. Oecologia, 126, 266-275. 824
37
van Ommeren RJ, Whitham TG (2002) Changes in interactions between juniper and 825
mistletoe mediated by shared avian frugivores: Parasitism to potential mutualism. 826
Oecologia, 130, 281-288. 827
Via S (2001) Sympatric speciation in animals: the ugly duckling grows up. Trends Ecol. 828
Evol., 16, 381-390. 829
Vijn I, das Neves L, van Kammen A et al. (1993) Nod factors and nodulation in plants. 830
Science, 260, 1764-65. 831
Wade, MJ (2007) The co-evolutionary genetics of ecological communities. Nature 832
Reviews Genetics, 8, 185-195. 833
Wartrud LS, Henry Lee E, Fairbrother A et al. (2004) Evidence for landscape-level, 834
pollen-mediated gene flow from genetically modified creeping bentgrass with 835
CP4 EPSPS as a marker. Proceedings of the National Academy of Science, 101, 836
14533-14538. 837
Whitham TG, Bailey JK, Schweitzer JA et al. (2006) A framework for community and 838
ecosystem genetics: From genes to ecosystems. Nature Reviews Genetics, 7, 510-839
523. 840
Whitham TG, DiFazio SP, Schweitzer JA et al. (2008) Extending genomics to natural 841
communities and ecosystems. Science, 320, 492-495. 842
Whitham TG, Young WP, Martinsen GD et al. (2003) Community and ecosystem 843
genetics: A consequence of the extended phenotype. Ecology, 84, 559-573. 844
Wimp GM, Martinsen GD, Floate KD et al. (2005) Plant genetic determinants of 845
arthropod community structure and diversity. Evolution, 59, 61-69. 846
38
Wimp GM, Wooley S, Bangert RK et al. (2007) Plant genetics predicts intra-annual 847
variation in phytochemistry and arthropod community structure. Molecular 848
Ecology, 16, 5057-5069. 849
Wimp GM, Young WP, Woolbright SA et al. (2004) Conserving plant genetic diversity 850
for dependent animal communities. Ecology Letters, 7, 776-780. 851
Wolfenbarger LL, Naranjo SE, Lundgren JG et al. (2008) Bt crop effects on functional 852
guilds of non-target arthropods: A meta-analysis. PLoS ONE, 3, e2118 853
doi:10.1371/journal.pone.0002118. 854
Wood TK, Keese MC (1990) Host plant-induced assortative mating in Enchenopa tree 855
hoppers. Evolution, 44, 619-28. 856
Zapiola M, Campbell C, Butler M et al. (2008) Escape and establishment of transgenic 857
glyphosate-resistant creeping bentgrass (Agrostis stolonifera) in Oregon, USA: A 858
4-year study. Journal of Applied Ecology, 45, 486-494. 859
860
861
39
Table 1. Definitions of community genetics terms 862
863
Community and ecosystem genetics - The study of the genetic interactions that occur 864
among species and their abiotic environment in complex communities 865
Community and ecosystem phenotypes - The effects of genes at levels higher than the 866
population. These phenotypes result from interspecific indirect genetic effects, 867
which can be summarized as a univariate trait. 868
Community heritability - The tendency for related individuals to support similar 869
communities of organisms and ecosystem processes. 870
Foundation species – Species that structure a community by creating locally stable 871
conditions for other species, and by modulating and stabilizing fundamental 872
ecosystem processes. 873
Minimum viable population (MVP) – The size of a population that, with a given 874
probability, will ensure the existence of the population for a stated period of time. 875
Minimum viable interacting population (MVIP) - The size of a population that is 876
required to maintain genetic diversity at levels required by other dependent and 877
interacting species in a community context. 878
879
880
881
40
Figure Legends 882
883
Figure 1. A survey of the literature shows interaction effects and pattern reversals are 884
common, which argues for a community approach to avoid potentially costly errors in 885
conservation and management decisions. Solid bars show that as the number of factors in 886
a study increases, the observed percentage of significant interaction effects also increases 887
(i.e., both quantitative and qualitative interactions). Open bars show that as the number 888
of factors in a study increases, the observed percentage of reversals also increases (i.e., a 889
qualitative change in the sign of an interaction). Figure from Bailey and Whitham 890
(2007). 891
892
Figure 2. Community and ecosystem phenotypes of individual tree genotypes of 893
Populus angustifolia show broad-sense heritability (H2). Significant heritability of the 894
canopy arthropod community, soil microbial community, trophic interactions between 895
birds and insects, and soil nutrient pools demonstrate how trait variation in a foundation 896
tree can structure communities and ecosystem processes (H2
C for community traits; H2 897
for single ecosystem trait). Because soil microorganisms mediate many ecosystem 898
processes, including litter decomposition and rates of nutrient mineralization, the 899
formation of these communities may feed back to affect plant fitness. Solid lines indicate 900
known interactions; dashed lines indicate possible interactions. Quantitative genetic 901
patterns such as these argue that genomic approaches will enhance our understanding of 902
how interacting community members influence ecosystem processes. Figure from 903
Whitham et al. (2008). 904
41
905
Figure 3. Because genetically similar trees support similar communities of organisms, 906
(i.e., the Genetic Similarity Rule), genetic diversity in a foundation plant species is likely 907
to support greater biodiversity in the associated community. On average, Mantel tests 908
show that arthropod communities become less similar as plant genetic distance increases 909
(i.e., small genetic distance indicates more closely related trees). Genetic distances of the 910
common garden trees (solid circles) were based on RFLP markers. The genetic distances 911
of the naturally growing trees in the wild (open triangles) were based on AFLP marker 912
data and only include the F1 and backcross hybrids, thus removing the leverage of the two 913
pure parental species from the analysis. Figure from Bangert et al. (2006a). 914
915
Figure 4. At the stand level, genetic diversity in a foundation tree species is highly 916
correlated with the diversity of an arthropod community of 207 species. Cottonwood 917
genetic diversity predicted arthropod diversity at a stand level. Each point in the 918
scatterplot represents the Shannon–Weaver index of arthropod diversity (H¢ ) as a 919
function of cottonwood gene diversity (He) in the same stand; a total of 11 stands were 920
analyzed. The diagonal line represents the line of best fit that describes the relationship 921
between increasing arthropod diversity as a result of increasing cottonwood genetic 922
diversity. Figure from Wimp et al. 2004) 923
924
Figure 5. The species-area curve is also a species-genetic diversity curve, which may 925
affect management decisions to preserve communities based on area, genetic diversity of 926
foundation species or both. (a) Scaling in which both arthropods and molecular makers 927
42
scale similarly as a function of the number of broadleaf cottonwoods sampled (sample 928
size or number is also a proxy for area). At their asymptotes, adequate sampling captures 929
most of the arthropod community and genetic diversity, respectively. (b) Consistent with 930
the above similarity in scaling, there is a strong positive relationship between arthropod 931
species richness and marker richness. Because trees were selected at random, no 932
geographic structure is reflected in these patterns. Figure from Bangert et al. (2008). 933
934
Figure 6. This graphical model illustrates the hypothesized relationship between high 935
community heritability (i.e., different genotypes of a foundation species support different 936
communities of organisms and ecosystem processes) and the population size needed to 937
preserve the dependent community. As community heritability increases, the population 938
size of the foundation species must rise to support its dependent community and the 939
ecosystem processes they promote. This community perspective on the minimum viable 940
population (MVP) is termed the minimum viable interacting population (MVIP), which 941
takes into account the genetic-based interactions among species in a community context. 942
943
Figure 7. Climate change is predicted to have rapid and major affects on the distribution 944
of foundation plant species across the American West. Modeled climate profiles for 945
saguaro and pinyon pine are shown for the contemporary climate and for the decades 946
beginning in 2030, 2060, and 2090 (left to right). Figure from Rehfeldt et al. (2006). 947
948
949
43
950 Figure 1 951 952
# of Statistical Factors
1 2 3 4
% o
f S
ign
ific
an
t In
tera
cti
on
Te
rms
0
20
40
60
80
100All Observed Significant Interaction Terms
Observed Interactions Resulting in ReversalsFig. 2
953 954
46
968 Figure 4 969 970
Average cottonwood gene diversity (He)
0.14 0.16 0.18 0.20 0.22 0.24 0.26 0.28 0.30 0.32 0.34
Shannon-w
eave
r in
dex o
f
arthropod d
ive
rsity (H
')
2.2
2.4
2.6
2.8
3.0
3.2
3.4
3.6
971 972
R2
= 0.591
P = 0.006
48
979 Figure 6 980 981
Community Heritability H2C
Low High
Population
size needed
to conserve
dependent
community
MVIP – Minimum Viable Interacting Population
982