Abstract
Ecosystems transition quickly in the Anthropocene, whereas biodiversity adapts more slowly. Here we simulated a shifting woodland ecosystem on the Colorado Plateau of western North America by using as its proxy over space and time the fundamental niche of the Arizona black rattlesnake (Crotalus cerberus). We found an expansive (= end-of-Pleistocene) range that contracted sharply (= present), but is blocked topographically by Grand Canyon/Colorado River as it shifts predictably northwestward under moderate climate change (= 2080). Vulnerability to contemporary wildfire was quantified from available records, with forested area reduced more than 27% over 13 years. Both ‘ecosystem metrics' underscore how climate and wildfire are rapidly converting the Plateau ecosystem into novel habitat. To gauge potential effects on C. cerberus, we derived a series of relevant ‘conservation metrics' (i.e. genetic variability, dispersal capacity, effective population size) by sequencing 118 individuals across 846 bp of mitochondrial (mt)DNA-ATPase8/6. We identified five significantly different clades (net sequence divergence = 2.2%) isolated by drainage/topography, with low dispersal (FST = 0.82) and small sizes (2Nef = 5.2). Our compiled metrics (i.e. small-populations, topographic-isolation, low-dispersal versus conserved-niche, vulnerable-ecosystem, dispersal barriers) underscore the susceptibility of this woodland specialist to a climate and wildfire tandem. We offer adaptive management scenarios that may counterbalance these metrics and avoid the extirpation of this and other highly specialized, relictual woodland clades.
Keywords: climate change, Crotalus cerberus, drainage vicariance, environmental niche modelling, wildfire
1. Introduction
Geomorphic processes drive major ecosystem shifts, whereas more gradual changes in the natural environment promote their diversification. This synergistic ontogeny forms the baseline for a contemporary perspective on ecosystem evolution where environmental transformations are both shared and codependent with resident biodiversity [1]. It also yields a series of ‘ecosystem metrics’ that not only document the manner by which ecosystems transition over time, but also the concomitant constraints that can emerge with these shifts [2], particularly when transformations are inordinately forced.
Similarly, a series of ‘conservation metrics’ can be inferred for resident biodiversity to guide conservation efforts, such as building corridors to reconnect populations and ecosystems now fragmented by anthropogenic activities [3]. Alternatively, individuals can be translocated among isolated areas to re-establish extirpated biodiversity components or promote genetic rescue of dwindling populations [4], but such actions come with caveats [5]. Conservation metrics are most easily derived from molecular data that, in turn, can determine the origin of populations (via coalescence among clades), their levels of connectivity (by quantifying gene flow), as well as their persistence over time (by estimating genetic diversity, demographic trends and effective sizes) [5,6].
Conservation and ecosystem metrics are inherently relevant for biodiversity management, and a clear mapping of these ‘biodiversity-to-ecosystem’ linkages is especially germane for conservation in the Anthropocene [7]. Both provide a template for adaptive management, with options that can span from conserving or restoring damaged ecosystems [8], to coping with those deemed novel and thus seemingly intractable [9]. Many of these metrics are also employed to estimate climate change velocity, or the rapidity with which ecosystems are driven towards alternative equilibria. Such studies underscore the link between global refugia and areas of low velocity [10], and also predict the speed at which a particular species must migrate so as to maintain its niche [11]. This mapping also has relevance for those biodiversity elements considered short-range endemics (as herein) [12]. However, dispersal capacities and population sizes for such species are often misjudged or underestimated [5]. This, in turn, diminishes the predictive power of the mapping, particularly when vulnerabilities of ecosystem are increased and conserved niches additionally compressed. Many biodiversity elements that reside in such situations are now recognized as ‘conservation-reliant’ ([13], and references therein), necessitating the derivation of accurate conservation and ecosystem metrics so as to blunt impending impacts.
We employed several approaches to evaluate transitioning of the forested Colorado Plateau ecosystem of western North America, and to gauge the response by resident, range-restricted biodiversity to these shifts. Our intent was to evaluate conservation and niche metrics of a relatively sedentary but charismatic species as a potential bookmark for other niche-conserved species that may experience similar landscape-level interactions and disturbance histories. We first derived an ecological niche model (ENM) for a cryptic, but social study species (the Arizona black rattlesnake, Crotalus cerberus) [14,15] (figure 1), and used it as a proxy to evaluate the shifting forested habitat of the Plateau over time and in response to a fluctuating climate [12].
Figure 1.
Crotalus cerberus, Santa Catalina Mountains, Pinal County, Arizona. Picture taken by Roger A. Repp, 6 August 2008, and published with permission.
In this context, the geographical range of C. cerberus is considered a spatial representation of its fundamental niche [16], and the simulation of these data in both an historic and predictive framework is interpreted as a species-to-ecosystem map. ENMs are critical both for conservation planning and resource management, and are often used to determine those species likely to adapt in situ versus those that have the potential to disperse to a more suitable niche, or even face extirpation [17]. ENMs can also predict if refugia, as currently designated, will continue into the future or will instead become a sink for both ecosystem services and coevolved species [18]. We further extended our biodiversity-ecosystem map by estimating the contemporary vulnerability of the wooded Plateau to severity and extent of wildfire over the past 13 years.
Additionally, we quantified the conservation metrics of C. cerberus (i.e. the extent of its genetic variability, its capacity for dispersal, the size of its effective populations, its potential for bottlenecks) by sequencing two rapidly evolving mitochondrial (mt)DNA genes. Based on the insights gained from estimating these niche and conservation metrics, we offer potential policy enhancements that could facilitate the management of both the ecosystem and its biodiversity moving forward.
2. Material and methods
2.1. The fundamental niche of the Arizona black rattlesnake
We used ENMs to frame the study ecosystem and predict its potential range shift going forward. In this sense, ENMs represent the fundamental niche of a species, and are recognized as stable traits within and across lineages [19]. They essentially define that set of abiotic environmental conditions within which a species can survive and maintain viable populations. This approach is particularly well suited for C. cerberus, whose ectothermic physiology is tightly linked to environmental factors.
From 1998 to 2005, two teams collected genetic samples of 118 C. cerberus from across its range [20]. Capture coordinates for these samples were supplemented with locality coordinates from all available museum specimens, and the entire dataset (N = 302) was imported into MaxEnt [21] and parsed among training/testing sets (N = 227/75, respectively). Nineteen bioclimatic variables were obtained from the WorldClim database [22] and a correlation matrix derived to identify eight biologically meaningful but uncorrelated variables [23]. These are: annual mean temperature; mean diurnal range; maximum temperature in the warmest period; minimum temperature of the coldest period; annual temperature range; mean temperature of the warmest quarter; mean temperature of the coldest quarter and annual precipitation. Three of these were also employed in a previous climate model derived for Plateau grasslands [24], thus lending credence to the extrapolation of fundamental niche to ecosystem metrics.
Because C. cerberus was previously recognized as a member of a species-complex [25], and given the inherent complexity of modelling intra-specific entities [26–28], we excluded from calibration those areas where subspecies potentially co-occurred. In so doing, we adjusted for the fact that conspecifics (congenerics) with similar habitat requirements may also perhaps exist therein. ENMs consistently perform better, and most often predict larger areas of suitable conditions, when the potential for sub-taxonomic structure is accommodated.
The fundamental niche for C. cerberus was derived from 10 147 points and averaged across 15 replicates of 5000 iterations each. We then derived a predictive post-Pleistocene species envelope, as well as one for 2080, based on a conservative climate projection of the Coupled Global Climate Model 2 (CGCM2) [29], as averaged and iterated above. BioClim variables were assessed for their relative contributions while information content was evaluated using the jackknife procedure. We also tested a suite of standard regularization multipliers (i.e. values of 1–10, 15 and 20) to ensure veracity of the projected climate envelope model [30–32]. The improvement in the fit of the model was evaluated using ENMTools [33,34], and mean distributional estimates for both models were then imported into ARCGIS v. 10 for derivation of climate envelopes and core habitat areas (per [5]).
2.2. Ecosystem vulnerability as a metric
Wildfire was first documented in the Silurian (420 Ma [35]), and it subsequently dominated the highly flammable savannahs within which hominins coevolved over millennia. Reciprocity has occurred of late, particularly in western North America, where anthropogenic activities shape ecosystems by promoting the magnitude and intensity of wildfire [36,37]. This situation has been augmented by extreme drought, high wind and rugged topographies [38], and also compounded by controversial fire suppression programmes [39]. The consequence? A precipitous decline in biodiversity on the Plateau as burned acreage quadruples with every degree the temperature rises [40]. Those biodiversity elements less vagile are clearly most susceptible [41].
To evaluate the vulnerability of the forested ecosystem that contains C. cerberus, we obtained from the Web [42] locations burned by wildfire in the 13 most recent years. From this, we were able to dissect out and evaluate the number of hectares incinerated by wildfire.
2.3. Derivation of conservation metrics
For genetic analyses, whole blood was collected and preserved (approx. 0.1 ml) from 118 C. cerberus often sampled singly (or in pairs) across an elevated, forested and topographically rugged ecosystem [25]. These logistic difficulties, coupled with the natural history of the Crotalinae (per [43]), prevented an accumulation of samples sufficient for broad population genetic analysis and, in turn, restricted our choice of molecular markers to mtDNA. Previously derived protocols [44] guided the sequence analysis of the mtDNA ATPase8/6 genes, the construction of a minimum spanning network of haplotypes, and the derivation of net sequence divergences (sd) among clades. A Bayesian phylogenetic analysis (BA) [45] consisted of two runs of five chains sampled every 1000 generations, and terminated with average standard deviation among split frequencies less than 0.001. Parameters/trees were estimated from 10 million generations (less than 30% burn-in) and visualized as a majority-rule consensus tree, with prairie rattlesnake (C. viridis) as outgroup [25].
We applied five separate runs in a coalescent-based Markov Chain Monte Carlo (MCMC) approach [46] to estimate clade-specific values for Θ (= 2Ne × m) and M (= mutation-scaled immigration rate = m/μ) using 5 million generations/eight chains, four adaptively heated, with 10 000 burn-in samples discarded. Five Θ-values were averaged per clade, multiplied by each (of four) pairwise immigration values then derived as clade-specific mean effective population size (female 2Nef). Analysis of molecular variance (AMOVA) and FST values were computed among clades [47] or groups, as defined by landscape features (rivers and basins), with p-values derived from 1000 permutations.
3. Results
3.1. Ecosystem and conservation metrics
The modelled shifting of the C. cerberus distribution showed congruent trends over time and within the forested ecosystem of the Colorado Plateau, with an historic configuration (figure 2a) condensing sharply into the present (figure 2b). With less stringent climate predictors [21], the ENM further condensed to higher elevations at the northern periphery of the core area, but with a major extension to the extreme northwest (2080: figure 2c; contemporary range of C. cerberus framed in green). Of particular note is that the shifting core area for this species is truncated topographically by an impenetrable Grand Canyon and Colorado River, effectively eliminating any potential for range expansion concomitant with a shifting niche distribution.
Figure 2.
Three environmental niche models depicting core habitat for 302 Crotalus cerberus within the forested ecosystem of the Colorado Plateau, southwestern North America: (a) = 12 Kya (b) = present (orange = 13 most recent years of wildfire locations/ha = 27% of range) and (c) = 2080 (green polygon = current distribution).
Ecosystem vulnerability was estimated as the frequency and intensity of wildfire that has occurred on the Colorado Plateau of Arizona over the last 13 years (figure 3). These data were then topographically depicted in orange as burned hectares in figure 2b. The duration and extent of wildfire has reduced the forested niche of C. cerberus (and concurrently its ecosystem) by greater than 27%.
Figure 3.
(a) Frequency plot depicting millions of hectares burned in Arizona by year (13 most recent); (b) histogram presenting the number of fires (×1000) over the same temporal span. http://landfire.cr.usgs.gov/viewer/.
The conservation metrics of C. cerberus were estimated from the evaluation of mtDNA sequence data, and a Bayesian Analysis recovered five distinct clades at greater than 85% (figure 4a). A haplotype network projected onto a topographic map (figure 4b) revealed rivers as vicariant barriers. These were: Black River (Clade-1, NM); Salt and Gila rivers (Clade-5, southeastern AZ); Verde River (Clade-4, central AZ); East and West Clear creeks (Clade-2, northern AZ) and Big Chino Wash/Agua Fria (Clade-3, northwestern AZ). All clades diverged significantly with regard to pairwise sequence divergence and FST values (table 1).
Figure 4.
(a) Bayesian phylogenetic analysis of Crotalus cerberus (Colorado Plateau/southwestern North America) depicting 48 haplotypes/five clades derived from 846 bp of mtDNA-ATP8/6. Outgroup = Crotalus viridis; (b) haplotype network derived from the same data as above but projected onto Arizona topography, with rivers (open boxes) demarcating clades. AZ map produced by Map Resources (http://www.mapresources.com/).
Table 1.
Pairwise %-sequence divergences (top triangle) and FST-values (lower triangle) among five clades of Crotalus cerberus (Colorado Plateau, southwestern North America), as derived from 846 bp of mtDNA-ATP8/6 (N = 118 individuals). All values differ significantly (p < 0.005).
clade | 5-Blue | 4-Red | 3-Green | 2-Green | 1-NM |
---|---|---|---|---|---|
5-Blue | X | 1.0 | 2.4 | 2.7 | 2.2 |
4-Red | 0.65 | X | 2.0 | 2.3 | 2.1 |
3-Green | 0.83 | 0.83 | X | 1.5 | 2.7 |
2-Green | 0.84 | 0.83 | 0.81 | X | 2.9 |
1-NM | 0.80 | 0.80 | 0.90 | 0.88 | X |
Two AMOVAs significantly partitioned genetic diversity (p < 0.0001) by (i) clade (81.7%) and (ii) topography as demarcated by rivers (69.6%), but not according to drainage basins (40.9%), again underscoring the presence of rivers as physical barriers to gene flow. Conversely, average 2Nef values were depressed despite considerable historic migration, and ranged from 1.5 to 8.3, indicating that clade divergence was significantly driven by small size and increased isolation (table 2).
Table 2.
Average genetic diversity parameters for five clades of Crotalus cerberus (Colorado Plateau, southwestern North America) derived from 846 bp of mtDNA-ATP8/6 sequenced (N = 118 individuals). Values: theta = (av. Th); migration = (av. M); female effective population size = (av. 2Nef); net-sequence divergence = (av.%sd); FST = (av. FST).
clade | av. Th | av. M | av. 2Nef | av.%sd | av. FST |
---|---|---|---|---|---|
5-Blue | 0.0184 | 79.2 | 1.5 | 2.1 | 0.78 |
4-Red | 0.0289 | 287.3 | 8.3 | 1.8 | 0.78 |
3-Green | 0.0139 | 323.7 | 4.5 | 2.1 | 0.84 |
2-Green | 0.0153 | 367.4 | 5.6 | 2.3 | 0.85 |
1-NM | 0.0144 | 435.6 | 6.3 | 2.4 | 0.85 |
average | 0.0182 | 298.6 | 5.2 | 2.2 | 0.82 |
4. Discussion
Historic data are increasingly employed to comprehend long-term ecological change and to provide a context within which biodiversity conservation can be framed. As such, historic data are necessary to estimate how ecosystems transition over time, and to evaluate the corresponding response by resident biodiversity [48]. They also have a role in guiding ecosystem restoration, particularly for establishment of habitat corridors that promote connectivity and sustain long-term responses in an ever-shifting Anthropocene [1].
Our goal in this study was to understand the influence of climate and landscape on a niche-conserved, range-restricted species and apply it as a species-ecosystem proxy to gauge potential impacts on other species with similar ecologies. We first delineated the fundamental niche of C. cerberus as distributed at end-of-Pleistocene, then projected these data into the present, as well as predicting a conservative trajectory as configured over the next 50 years. The unique properties of molecular genetic data then allowed us to examine how tractable the dispersal of C. cerberus was within this ecosystem, and to reconstruct a geographical context for diversification. As a matrix within which to juxtapose the phylogeographic distribution across the Plateau, a snapshot of its deep history was first needed.
4.1. The matrix of deep history
An historic perspective on landscape diversification has importance in that it can help gauge more contemporary impacts, as well as offer a prognosis for its trajectory in a changing climate [49]. The dynamic landscape of arid southwestern North America has been shaped by tectonism and climatic oscillations, but is now subjected to steadily increasing anthropogenic pressures [5,6,50]. Key geomorphic events that occurred on the Plateau during the Late Miocene–Early Pliocene were the collapse of the southwest Basin and Range physiographic province and the integration of the Colorado River. These synergistic occurrences were concomitant with the ongoing uplift of the Plateau, which in turn provoked deep incisions within its antecedent (i.e. previously formed) Plateau streams. For example, a well-defined structural trough guided the uppermost Gila River (figure 4) into a closed, ephemeral basin before the river integrated westward to the Colorado River [51]. Other Late Miocene drainages (i.e. Salt River, Verde River; figure 4) similarly flowed via deeply incised canyons into closed basins that soon spilled into headwater-eroding canyons during a more pluvial Late Pliocene [52]. These events were pivotal with regard to biodiversity evolution in that they promoted landscape diversification (figure 2a) and accentuated a vicariant separation of clades (figure 4a).
This pattern occurred repeatedly in southwestern North America [25,44,48], such that taxa with broader distributions were fragmented over time by the synergistic effects of climate and tectonism, whereas more geographically restricted taxa were relatively unaffected [48,53]. Thus, given the contemporary distribution reflected by our study species (green polygon, figure 2c), we expected and tested for a shallow genetic structure by quantifying molecular diversity within regions having a common phylogenetic or biogeographic history. Rather than a shallow diversification, we found instead a topographically embedded haplotype network of five significantly isolated clades, each with reduced gene flow, as underscored by migration rates, FST values, and female effective population sizes (tables 1 and 2). In addition, these diversification patterns aligned quite closely with drainage evolution (figure 4b).
Once we understood the strong influence of hydrographic and tectonic processes on the phylogeographic patterns of regional biotas [54], we could then evaluate the vulnerabilities of this ecosystem with regard to more contemporary impacts, and how the latter may, in turn, provoke a turnover of woodland habitat on the Plateau. We were also interested in gauging the magnitude and extent of these potential impacts with regard to C. cerberus.
4.2. Wildfire as an ecosystem regulator
Fire has become a global management tool, and it is often used in this context to regulate ecosystems [55]. Planned burns can provide benchmarks from which to infer impacts produced by spontaneous wildfire. The patterns that emerge, while intuitively appealing, are often ill defined [56–59], but with an occasional emergent property. Small mammals, for example, are a key component of forested food webs, and as such are prey items for C. cerberus. Their abundance within Sierra Nevada (CA) forests was greater within unburned plots [60], largely due to the presence of over-story and a shelter-providing ground layer, a phenomenon that translates broadly across vertebrate groups [61]. Furthermore, small mammals became extirpated when fire occurred more than once at a single location over a 5-year span [60]. Clearly, wildfire has serious and substantial effects on the persistence of favourable habitat, and on those biodiversity elements that form the prey of apex predators such as C. cerberus.
As a management tool, fire moderates the environment [55], but with the caveat that it must be controlled so as to avoid local extinctions. In this sense, high-intensity fires are quite lethal for small vertebrates, whether as management endeavours [62] or naturally occurring (per figure 3a). Wooded canyons and steep slopes burn more intensely due to an elevated fuel accumulation, and this reverberates post-fire in that surviving individuals subsequently remain in subterranean retreats for protracted periods [63]. The occurrence of wildfire and its intensity are covariates that not only impact the vegetation and prey base, but also the subsequent behaviours of prey and predators.
4.3. A juxtaposition of metrics
Conservation planning and fire management can be juxtaposed, in that both have readily achievable goals that are linked to decision-making tools and operational guidelines. However, each requires sustained data so as to identify critical questions, and to specify appropriate means of adjudication [64,65]. An optimal fire history is one such example that can be modelled for a given area by developing a biodiversity index so as to define species-specific responses [66]. Conservation objectives can emerge as a direct product, but with the caveat that life history, demography, and a fine-grained distribution are a priori requirements (per [5]). An unfortunate downside to this approach is that such data are often lacking for many relictual species, to include C. cerberus.
From an historic context, wildfire in southwestern North America was a ‘rejuvenator’ of mountainous ecosystems [66], but its effects post-settlement were deemed deleterious and it was vigorously suppressed as a consequence [39]. It has again rebounded as a significant disturbance [67] with an expansive future as an ecosystem ‘converter’ [68] in synergy with climate change [69]. Communities are now driven towards new equilibria that contain novel species-compositions that are resilient to a relapse [70].
5. Conclusion
In this study, we examined genetic structure of a niche-conserved species so as to understand the manner by which climate and landscape have influenced its past, contemporary and predicted distributions. In doing so, we found reduced gene flow, limited dispersal and significant vicariance as the ecosystem shifted in elevation rather than latitude. Furthermore, our data demonstrated discrete, significantly different clades whose genetic diversities cannot withstand the erosive effects of wildfire [71], particularly when the capacity to disperse is limited not only by life history but also by landscape barriers.
The goal of management should be to maintain levels of gene flow and efforts in this regard can be guided by conservation metrics, as inferred from molecular data. In this sense, the network of genetic connections as derived among clades is the web that sustains their continued evolution (figure 4). However, limitations are imposed by the ecosystem. For example, the strong synergy between severe drought and wildfire [72] is an unfortunate harbinger for eventual extinction of clades, or even species-extirpation on the southern Plateau, as ponderosa pine/pinyon-juniper woodlands are converted into novel habitat [70].
An apt example of how climate change and wildfire can impact a cryptic, niche-conserved and short-range rattlesnake is provided by Crotalus willardi obscurus in the sky-islands of southwestern North America [5]. Long-term recapture data, combined with demographic and niche modelling, demonstrated a survival probability that is significantly impacted by wildfire, and furthermore, an extinction vortex driven by small population demographics. Both aspects translate well to C. cerberus and its larger geographical range. Both taxa are embedded within the rugged topography of a forested ecosystem that inhibits gene flow, constrains effective population sizes, and induced significant clade diversification. The two species are strikingly complementary with regard to ecosystems and life histories, and scant extrapolation is required to suggest that C. cerberus will have an extinction trajectory concomitant with that of C. w. obscurus in the near time.
In the context of adaptive management, how can the unique biodiversity of the Colorado Plateau ecosystem be appropriately conserved? Three opportunities present themselves: first, the conservation status of C. cerberus should be designated as ‘threatened’ under the Endangered Species Act (ESA), so as to more appropriately leverage ecosystem management for the Plateau. This would allow the U.S. Fish & Wildlife Service (FWS) to develop regulatory protections adjusted to the needs of the species, rather than as a protective blanket afforded to those designated as ‘endangered.’ In this sense, limited (but not complete) protection is provided under the ESA, and this in turn promotes additional (and entrepreneurial) conservation options. As part of this process, ‘critical habitat’ could be designated so as to effectively promote recovery goals [73].
These considerations promote a second opportunity. The Plateau should be promoted as a prime example of ecosystem vulnerability, as driven by climate change and its accompanying wildfire component [74]. The mapping of C. cerberus within its ecosystem underscores the fact that consequences are apparent for both when uncertain climatic shifts are manifest. Finally, other unique biodiversity elements on the Plateau should also be recognized so as to promote not only public awareness but also perceptions of stakeholders regarding ecosystem vulnerabilities. These actions may offer the Plateau and its biodiversity a brief respite, but hopefully enough time to allow substantive ecosystem-level initiatives in the context of region-specific mandates [44,49,50].
Acknowledgements
The following individuals provided collection and field assistance: Randy Babb, Bruce Christman, Marty Feldner, Larry Nienaber, Erika Nowak, Charlie Painter, Trevor Persons, Louis Porras, Roger Repp, Jeff Servoss, John Slone, and Bryan Starrett.
Ethics
Samples were collected under scientific collecting permits provided by the Arizona and New Mexico Game and Fish Departments and were conducted under a protocol approved by the Arizona State University Institutional Animal Care and Use Committee.
Data accessibility
GenBank accession number: KX095994-KX096036.
Authors' contributions
M.R.D./M.A./J.J.S./G.W.S./A.T.H./M.E.D. contributed to fieldwork; M.R.D./H.W.H./M.E.D. contributed to laboratory work; M.R.D./M.A.D./M.E.D. carried out statistical analyses; M.R.D./M.A.D./M.E.D. drafted the manuscript; all authors gave final approval for publication.
Competing interests
We declare we have no competing interests.
Funding
This research was enabled by generous endowments to the University of Arkansas for M.R.D. (Bruker Professorship in Life Sciences) and M.E.D. (21st Century Chair in Global Change Biology).
References
- 1.Rick TC, et al. 2014. Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene. BioScience 64, 680–692. (doi:10.1093/biosci/biu094) [Google Scholar]
- 2.Ellis EC, Goldewijk KK, Siebert S, Lightman D, Ramankutty N.. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Glob. Ecol. Biogeogr. 19, 589–606. (doi:10.1111/j.1466-8238.2010.00540.x) [Google Scholar]
- 3.Gilbert-Norton L, Wilson R, Stevens JR, Beard KH. 2010. A meta-analytic review of corridor effectiveness. Conserv. Biol. 24, 660–668. (doi:10.1111/j.1523-1739.2010.01450.x) [DOI] [PubMed] [Google Scholar]
- 4.Whiteley AR, Fitzpatrick SW, Funk CW, Tallmon DA. 2015. Genetic rescue to the rescue. Trends Ecol. Evol. 30, 42–49. (doi:10.1016/j.tree.2014.10.009) [DOI] [PubMed] [Google Scholar]
- 5.Davis MA, Douglas MR, Webb CT, Collyer ML, Holycross AT, Painter CW, Kamees LK, Douglas ME. 2015. Nowhere to go but up: impacts of climate change on demography of a short-range endemic (Crotalus willardi obscurus) in the sky-islands of southwestern North America. PLoS ONE 10, e0131067 (doi:10.1371/journal.pone.0131067) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Holycross AT, Douglas ME. 2007. Geographic isolation, genetic divergence, and ecological non-exchangeability define ESUs in a threatened sky-island rattlesnake. Biol. Consev. 134, 142–152. (doi:10.1016/j.biocon.2006.07.020) [Google Scholar]
- 7.Corlett RT. 2015. The Anthropocene concept in ecology and conservation. Trends Ecol. Evol. 30, 36–41. (doi:10.1016/j.tree.2014.10.007) [DOI] [PubMed] [Google Scholar]
- 8.Evans CE, Tulloch AIT, Law EA, Raiter KG, Possingham HP, Wilson KA. 2015. Clear consideration of costs, condition and conservation benefits yields better planning outcomes. Biol. Conserv. 191, 716–727. (doi:10.1016/j.biocon.2015.08.023) [Google Scholar]
- 9.Morse NB, Pellissier PA, Cianciola EN, Brereton RL, Sullivan MM, Shonka NK, Wheeler TB, McDowell WH. 2014. Novel ecosystems in the Anthropocene: a revision of the novel ecosystem concept for pragmatic applications. Ecol. Soc. 19, 12 (doi:10.5751/ES-06192-190212) [Google Scholar]
- 10.Serra-Diaz JM, Franklin J, Ninyerola M, Davis FW, Syphard AD, Regan HM, Ikegami M.. 2013. Bioclimatic velocity: the pace of species exposure to climate change. Divers. Distrib. 2013, 1–12. (doi:10.1111/ddi.12131) [Google Scholar]
- 11.Carroll C, Lawler JL, Roberts DR, Hamann A. 2015. Biotic and climatic velocity identify contrasting areas of vulnerability to climate change. PLoS ONE 10, e0140486 (doi:10.1371/journal.pone.0140486) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Sandel B, Arge L, Dalsgaard B, Davies RG, Gaston KJ, Sutherland WJ, Svenning J-C.. 2011. The influence of Late Quaternary climate-change velocity on species endemism. Science 334, 660–664. (doi:10.1126/science.1210173) [DOI] [PubMed] [Google Scholar]
- 13.Carroll C, Rohlf DJ, Li Y-W, Hartl B, Phillips MK, Noss RF. 2015. Connectivity conservation and endangered species recovery: A study in the challenges of defining conservation-reliant species. Conserv. Lett. 8, 132–138. (doi:10.1111/conl.12102) [Google Scholar]
- 14.Amarello M. 2012. Social snakes: non-random association patterns detected in a population of Arizona black rattlesnakes (Crotalus cerberus). MS thesis, Arizona State University, Tempe, AZ, USA. See http://repository.asu.edu/attachments/97634/content//tmp/package-3nztOF/Amarello_asu_0010N_12287.pdf.
- 15.Clark RW. 2004. Kin recognition in rattlesnakes. Proc. R. Soc. Lond. B 271(Suppl 4), S243–S245. (doi:10.1098/rsbl.2004.0162) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Lomolino MV, Riddle BR, Brown JH. 2009. Biogeography, 3rd edn Sunderland, MA: Sinauer Associates. [Google Scholar]
- 17.Elith J, Leathwick JR. 2009. Species distribution models: ecological explanation and prediction across space and time. Ann. Rev. Ecol. Evol. Syst. 40, 677–697. (doi:10.1146/annurev.ecolsys.110308.120159) [Google Scholar]
- 18.Araujo MB, Alagador D, Cabeza M, Nogues-Bravo D, Thuiller W.. 2011. Climate change threatens European conservation areas. Ecol. Lett. 14, 484–492. (doi:10.1111/j.1461-0248.2011.01610.x) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Saupe EE, Qiao H, Hendricks JR, Portell RW, Hunter SJ, Soberón J, Lieberman BS. 2015. Niche breadth and geographic range size as determinants of species survival on geological time scales. Glob. Ecol. Biogeogr. 24, 1159–1169. (doi:10.1111/geb.12333) [Google Scholar]
- 20.Davis MA. 2012. Morphometrics, molecular ecology, and multivariate environmental niche define the evolutionary history of the Western rattlesnake (Crotalus viridis) complex. PhD dissertation, University of Illinois, Urbana-Champaign, Champaign, IL, USA.
- 21.Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259. (doi:10.1016/j.ecolmodel.2005.03.026) [Google Scholar]
- 22.Hijmans RJ, Cameron SE, Parra LJ, Jones PG, Jarvis A.. 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Clim. 25, 1965–1978. (doi:10.1002/joc.1276) [Google Scholar]
- 23.Dormann CF, et al. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46. (doi:10.1111/j.1600-0587.2012.07348.x) [Google Scholar]
- 24.Gremer JR, Bradford JB, Munson SM, Duniway MC. 2015. Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States. Glob. Change Biol. 21, 4049–4062. (doi:10.1111/gcb.13043) [DOI] [PubMed] [Google Scholar]
- 25.Douglas ME, Douglas MR, Schuett GW, Porras LW, Holycross AT. 2002. Phylogeography of the western rattlesnake (Crotalus viridis) complex, with emphasis on the Colorado Plateau. In Biology of the vipers (eds Schuett GW, Höggren M, Douglas ME, Greene HW), pp. 11–50. Eagle Mountain, UT: Eagle Mountain Publishing LC. [Google Scholar]
- 26.Pearman PB, D'Amen M, Graham CH, Thullier W, Zimmermann NE. 2010. Within-taxon niche structure: niche conservatism, divergence and predicted effects of climate change. Ecography 33, 990–1003. (doi:10.1111/j.1600-0587.2010.06443.x) [Google Scholar]
- 27.Broennimann O, et al. 2012. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–497. (doi:10.1111/j.1466-8238.2011.00698.x) [Google Scholar]
- 28.D'Amen M, Zimmermann NE, Pearman PB. 2013. Conservation of phylogeographic lineages under climate change. Glob. Ecol. Biogeogr. 22, 93–104. (doi:10.1111/j.1466-8238.2012.00774.x) [Google Scholar]
- 29.IPCC. 2013. Climate Change 2013—the physical science basis. Working group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press. [Google Scholar]
- 30.Elith J, Kearney M, Phillips S.. 2010. The art of modeling range-shifting species. Methods Ecol. Evol. 1, 330–342. (doi:10.1111/j.2041-210X.2010.00036.x) [Google Scholar]
- 31.Warren DL, Seifert SN. 2011. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol. Appl. 21, 335–342. (doi:10.1890/10-1171.1) [DOI] [PubMed] [Google Scholar]
- 32.Ficetola G, Bonardia A, Mücherb CA, Gilissenc NLM, Padoa-Schioppaa E.. 2014. How many predictors in species distribution models at the landscape scale? Land use versus LiDAR-derived canopy height. Int. J. Geogr. Inf. Sci. 28, 1723–1739. (doi:10.1080/13658816.2014.891222) [Google Scholar]
- 33.Warren DL, Glor RE, Turelli M.. 2008. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868–2883. (doi:10.1111/j.1558-5646.2008.00482.x) [DOI] [PubMed] [Google Scholar]
- 34.Warren DL, Glor RE, Turelli M.. 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33, 607–611. (doi:10.1111/j.1600-0587.2009.06142.x) [Google Scholar]
- 35.Scott AC, Glasspool IJ. 2006. The diversification of Paleozoic fire systems and fluctuations in atmospheric oxygen concentration. Proc. Natl Acad. Sci. USA 103, 10 861–10 865. (doi:10.1073/pnas.0604090103) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Bowman DMJS, et al. 2009. Fire in the Earth system. Science 324, 481–484. (doi:10.1126/science.1163886) [DOI] [PubMed] [Google Scholar]
- 37.Nijhuis M. 2012. Forest fires: burn out. Nature 489, 352–354. (doi:10.1038/489352a) [DOI] [PubMed] [Google Scholar]
- 38.Dillon GK, Holden DA, Morgan P, Crimmins MA, Heyerdahl EK, Luce CH. 2011. Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006. Ecosphere 2, 130 (doi:10.1890/ES11-00271.1) [Google Scholar]
- 39.Hurteau MD, Bradford JB, Fulé PZ, Taylor AH, Martin KL. 2014. Climate change, fire management, and ecological services in the southwestern US. For. Ecol. Manag. 327, 280–289. (doi:10.1016/j.foreco.2013.08.007) [Google Scholar]
- 40.National Research Council. 2011. Climate stabilization targets: emissions, concentrations, and impacts over decades to millennia. Washington, DC: National Academies Press. [Google Scholar]
- 41.D'Eon RG, Glenn SM, Parfitt I, Fortin M-J. 2002. Landscape connectivity as a function of scale and organism vagility in a real forested landscape. Conserv. Ecol. 6, 10 See http://www.consecol.org/vol6/iss2/art10. [Google Scholar]
- 42.U.S. Dept. Interior Geological Survey Landfire Disturbance 1999–2012 layer. See http://landfire.cr.usgs.gov/viewer/ (accessed 17 March 2016).
- 43.Levine BA, Smith CF, Douglas MR, Davis MA, Schuett GW, Beaupre SM, Douglas ME. 2016. Population genetics of a North American pitviper, the copperhead (Viperidae: Agkistrodon contortrix). Copeia 104 (doi:10.1643/CG-13-150) [Google Scholar]
- 44.Sullivan BK, Douglas MR, Walker JM, Cordes JE, Davis MA, Anthonysamy WJB, Sullivan KO, Douglas ME. 2014. Conservation and management of polytypic species: the little striped whiptail complex (Aspidoscelis inornata) as a case study. Copeia 2014, 519–529. (doi:10.1643/CG-13-140) [Google Scholar]
- 45.Ronquist F, et al. 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542. (doi:10.1093/sysbio/sys029) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Beerli P, Palczewski M.. 2010. Unified framework to evaluate panmixia and migration direction among multiple sampling locations. Genetics 185, 313–326. (doi:10.1534/genetics.109.112532) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Excoffier L, Lischer HEL. 2010. Arlequin suite v3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Res. 10, 564–567. (doi:10.1111/j.1755-0998.2010.02847.x) [DOI] [PubMed] [Google Scholar]
- 48.Douglas ME, Douglas MR, Schuett GW, Porras LW. 2006. Evolution of rattlesnakes (Viperidae; Crotalus) in the warm deserts of western North America shaped by Neogene vicariance and Quaternary climate change. Mol. Ecol. 15, 3353–3374. (doi:10.1111/j.1365-294X.2006.03007.x) [DOI] [PubMed] [Google Scholar]
- 49.Douglas ME, Douglas MR, Schuett GW, Beck DD, Sullivan BK. 2010. Conservation phylogenetics of Helodermatid lizards using multiple molecular markers and a supertree approach. Mol. Phylogenet. Evol. 55, 153–167. (doi:10.1016/j.ympev.2009.12.009) [DOI] [PubMed] [Google Scholar]
- 50.Hopken MA, Douglas MR, Douglas ME. 2013. Stream hierarchy defines riverscape genetics of a North American desert fish. Mol. Ecol. 15, 956–971. (doi:10.1111/mec.12156) [DOI] [PubMed] [Google Scholar]
- 51.Minckley WL, Henderson DA, Bond CE. 1987. Geography of western North American freshwater fishes: description and relationship to intracontinental tectonism. In The zoogeography of North American freshwater fishes (eds Hocutt CH, Wiley EO), pp. 519–613. New York, NY: John Wiley & Sons. [Google Scholar]
- 52.Blakely R, Ranney W. 2008. Ancient Landscapes of the Colorado Plateau. Grand Canyon, AZ: Grand Canyon Association. [Google Scholar]
- 53.Riddle BR, Jezkova T, Hornsby A, Matocq M.. 2014. Assembly of the modern Great Basin mammal biota: emerging insights from the integration of molecular biogeography with the fossil record. J. Mammal. 95, 1107–1127. (doi:10.1644/14-MAMM-S-064) [Google Scholar]
- 54.Riddle BR, Dawson MN, Hadly EA, Hafner DJ, Hickerson MJ, Mantooth SJ, Yoder AD. 2008. The role of molecular genetics in sculpting the future of integrative biogeography. Prog. Phys. Geogr. 32, 173–202. (doi:10.1177/0309133308093822) [Google Scholar]
- 55.Ryan KC, Knapp EE, Varner JM. 2013. Prescribed fire in North American forests and woodlands: history, current practice, and challenges. Front. Ecol. Environ. 11, e153–ee24. (doi:10.1890/120329) [Google Scholar]
- 56.Lindenmayer DB, et al. 2008. How predictable are reptile responses to wildfire? Oikos 117, 1086–1097. (doi:10.1111/j.0030-1299.2008.16683.x) [Google Scholar]
- 57.Nimmo DG, Kelly LT, Farnsworth LM, Watson SJ, Bennett AF. 2014. Why do some species have geographically varying responses to fire history? Ecography 37, 805–813. (doi:10.1111/ecog.00684) [Google Scholar]
- 58.Pastro LA, Dickman CR, Letnic M.. 2014. Fire type and hemisphere determine the effects of fire on the alpha and beta diversity of vertebrates: a global meta-analysis. Glob. Ecol. Biogeogr. 23, 1146–1156. (doi:10.1111/geb.12195) [Google Scholar]
- 59.Plavsic MJ. 2014. Proximate and ultimate drivers of small-mammal recolonization after fire: microhabitat conditions, rainfall and species traits. Anim. Conserv. 17, 573–582. (doi:10.1111/acv.12124) [Google Scholar]
- 60.Roberts SL, Kelt DA, van Wagtendonk JW, Miles AK, Meyer MD. 2015. Effects of fire on small mammal communities in frequent-fire forests in California. J. Mammal. 96, 107–119. (doi:10.1093/jmammal/gyu011) [Google Scholar]
- 61.Hu Y, Urlus J, Gillespie G, Letnic M, Jessop TS. 2013. Evaluating the role of fire disturbance in structuring small reptile communities in temperate forests. Biodivers. Conserv. 22, 1949–1963. (doi:10.1007/s10531-013-0519-z) [Google Scholar]
- 62.Griffiths AD, Garnett ST, Brook BW. 2015. Fire frequency matters more than fire size: testing the pyrodiversity–biodiversity paradigm for at-risk small mammals in an Australian tropical savanna. Biol. Conserv. 186, 337–346. (doi:10.1016/j.biocon.2015.03.021) [Google Scholar]
- 63.Smith LJ, Holycross AT, Painter CW, Douglas ME. 2002. Montane rattlesnakes and prescribed fire. Southwest. Nat. 46, 54–61. (doi:10.2307/3672373) [Google Scholar]
- 64.Driscoll DA, et al. 2010. Fire management for biodiversity conservation: key research questions and our capacity to answer them. Biol. Conserv. 143, 1928–1939. (doi:10.1016/j.biocon.2010.05.026) [Google Scholar]
- 65.Kelly LT, Bennett AF, Clarke MF, McCarthy Michael A.. 2015. Optimal fire histories for biodiversity conservation. Conserv. Biol. 29, 473–481. (doi:10.1111/cobi.12384) [DOI] [PubMed] [Google Scholar]
- 66.Allen CD, Betancourt JL, Swetnam TW. 1998. Landscape changes in the southwestern United States: techniques, long-term data sets and trends. In Perspectives on the land use history of North America: a context for understanding our changing environment (ed. Sisk TD.), pp. 71–84. Reston, VA: U.S. Geological Survey, Biological Resources Division; USGS/BRD/BSR-1998-0003. See http://landcover.usgs.gov/luhna/chap9.php. [Google Scholar]
- 67.Dennison PE, Brewer SC, Arnold JD, Moritz MA. 2014. Large wildfire trends in the western United States, 1984–2011. Geophys. Res. Lett. 41, 2928–2933. (doi:10.1002/2014GL059576) [Google Scholar]
- 68.Moritz MA, Parisien M-A, Batllori E, Krawchuk MA, Van Dorn J, Ganz DJ, Hayhoe K. 2012. Climate change and disruptions to global fire activity. Ecosphere 3, 49 (doi:10.1890/ES11-00345.1) [Google Scholar]
- 69.Flannigan MD, Stocks BJ, Wotton BM. 2000. Climate change and forest fires. Sci. Total Environ. 262, 221–229. (doi:10.1016/S0048-9697(00)00524-6) [DOI] [PubMed] [Google Scholar]
- 70.Williams JW, Jackson ST, Kutzbach JE. 2007. Projected distributions of novel and disappearing climates by 2100 AD. Proc. Natl Acad. Sci. USA 104, 5738–5742. (doi:10.1073/pnas.0606292104) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Dubey S, Pike DA, Shine R. 2013. Predicting the impacts of climate change on genetic diversity in an endangered lizard species. Clim. Change 117, 319–327. (doi:10.1007/s10584-012-0540-3) [Google Scholar]
- 72.Margolis EQ, Swetnam TW, Allen CD. 2007. A stand-replacing fire history in upper montane forests of the southern Rocky Mountains. Can. J. For. Res. 37, 2227–2241. (doi:10.1139/X07-079) [Google Scholar]
- 73.Clark JR. 2013. The Endangered Species Act at 40: opportunities for improvements. Bioscience 63, 924–925. (doi:10.1525/bio.2013.63.12.4) [Google Scholar]
- 74.Waples RS. 2013. Special Section: Incorporating climate change into risk analyses under the U.S. Endangered Species Act. Conserv. Biol. 27, 1137–1137. (doi:10.1111/cobi.12180) [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
GenBank accession number: KX095994-KX096036.