Sea‐level rise,habitat loss,and potential extirpation of a salt marsh specialist bird in urbanized landscapes

Sea‐level rise (SLR) impacts on intertidal habitat depend on coastal topology, accretion, and constraints from surrounding development. Such habitat changes might affect species like Belding's savannah sparrows (Passerculus sandwichensis beldingi; BSSP), which live in high‐elevation salt marsh in the Southern California Bight. To predict how BSSP habitat might change under various SLR scenarios, we first constructed a suitability model by matching bird observations with elevation. We then mapped current BSSP breeding and foraging habitat at six estuarine sites by applying the elevation‐suitability model to digital elevation models. To estimate changes in digital elevation models under different SLR scenarios, we used a site‐specific, one‐dimensional elevation model (wetland accretion rate model of ecosystem resilience). We then applied our elevation‐suitability model to the projected digital elevation models. The resulting maps suggest that suitable breeding and foraging habitat could decline as increased inundation converts middle‐ and high‐elevation suitable habitat to mudflat and subtidal zones. As a result, the highest SLR scenario predicted that no suitable breeding or foraging habitat would remain at any site by 2100 and 2110. Removing development constraints to facilitate landward migration of high salt marsh, or redistributing dredge spoils to replace submerged habitat, might create future high salt marsh habitat, thereby reducing extirpation risk for BSSP in southern California.     

Evaluating regional resiliency of coastal wetlands to sea level rise through hypsometry‐based modeling

Sea level rise (SLR) threatens coastal wetlands worldwide, yet the fate of individual wetlands will vary based on local topography, wetland morphology, sediment dynamics, hydrologic processes, and plant‐mediated feedbacks. Local variability in these factors makes it difficult to predict SLR effects across wetlands or to develop a holistic regional perspective on SLR response for a diversity of wetland types. To improve regional predictions of SLR impacts to coastal wetlands, we developed a model that addresses the scale‐dependent factors controlling SLR response and accommodates different levels of data availability. The model quantifies SLR‐driven habitat conversion within wetlands across a region by predicting changes in individual wetland hypsometry. This standardized approach can be applied to all wetlands in a region regardless of data availability, making it ideal for modeling SLR response across a range of scales. Our model was applied to 105 wetlands in southern California that spanned a broad range of typology and data availability. Our findings suggest that if wetlands are confined to their current extents, the region will lose 12% of marsh habitats (vegetated marsh and unvegetated flats) with 0.6 m of SLR (projected for 2050) and 48% with 1.7 m of SLR (projected for 2100). Habitat conversion was more drastic in wetlands with larger proportions of marsh habitats relative to subtidal habitats and occurred more rapidly in small lagoons relative to larger sites. Our assessment can inform management of coastal wetland vulnerability, improve understanding of the SLR drivers relevant to individual wetlands, and highlight significant data gaps that impede SLR response modeling across spatial scales. This approach augments regional SLR assessments by considering spatial variability in SLR response drivers, addressing data gaps, and accommodating wetland diversity, which will provide greater insights into regional SLR response that are relevant to coastal management and restoration efforts.     

Managing for change: wetland transitions under sea‐level rise and outcomes for threatened species

Aim Global sea‐level rise (SLR) could be as much as 1.8 metres by 2100, which will impact coastal wetland communities and threatened species. We evaluated the likely outcomes of SLR for wetland communities using a process‐based simulation model and coupled this with a metapopulation model for a threatened native rodent (Xeromys myoides). Furthermore, we tested the amplified impacts of SLR, urban growth and introduced predators on X. myoides persistence. Location South‐east Queensland, Australia. Methods We adapted the Sea Level Affects Marshes Model to subtropical Australia. We used LiDAR elevation data, field data to parameterize surface accretion and shallow subsidence, and local knowledge to configure wetland transitions. SLR was simulated based on the IPCC B1 and A1FI scenarios, as well as the maximal limit of 1.8 m by 2100. Further, we coupled our demographic model to projected shifts in wetland habitat, and estimates of future wetland loss to urban expansion and feral cat (Felis catus) predation. Results Our models project a general decline in wetland communities under SLR, with a noted exception of mangroves. Under the A1FI scenario, SLR allows mangroves to migrate inland, with urban development acting as an obstruction in some areas. Mangrove expansion provides an unexpected benefit for dependent X. myoides populations, although the inclusion of predation and habitat loss due to urban development still suggests extirpation in c. 50 years. Main conclusions Through this case study, we illustrate the usefulness of process‐based SLR models in understanding outcomes for wetland communities and dependent species. Our models will underscore decision‐making in a dynamic system, with global applications for urban planning, conservation prioritization and wildlife management.     

Ecological niche modeling of coastal dune plants and future potential distribution in response to climate change and sea level rise

Climate change (CC) and sea level rise (SLR) are phenomena that could have severe impacts on the distribution of coastal dune vegetation. To explore this we modeled the climatic niches of six coastal dunes plant species that grow along the shoreline of the Gulf of Mexico and the Yucatan Peninsula, and projected climatic niches to future potential distributions based on two CC scenarios and SLR projections. Our analyses suggest that distribution of coastal plants will be severely limited, and more so in the case of local endemics (Chamaecrista chamaecristoides, Palafoxia lindenii, Cakile edentula). The possibilities of inland migration to the potential ‘new shoreline’ will be limited by human infrastructure and ecosystem alteration that will lead to a ‘coastal squeeze’ of the coastal habitats. Finally, we identified areas as future potential refuges for the six species in central Gulf of Mexico, and northern Yucatán Peninsula especially under CC and SLR scenarios.     

Impacts of a half century of sea‐level rise and development on an endangered mammal

The extraordinary growth of human populations and development in coastal areas over the last half century has eliminated and degraded coastal habitats and threatened the persistence of associated wildlife. Moreover, human‐induced sea‐level rise (SLR) is projected to further eliminate and alter the same coastal ecosystems, especially low‐lying regions. Whereas habitat loss and wildlife population declines from development are well documented, contemporary SLR has not yet been implicated in declines of coastal faunal populations. In addition, the projection of severe synergistic impacts from the combination of development and SLR is well described, yet the scientific literature offers little empirical evidence of the influence of these forces on coastal wildlife. Analysis of aerial photographs from 1959 to 2006 provided evidence of a 64% net loss of the endangered Lower Keys marsh rabbit's (Sylvilagus palustris hefneri; LKMR) habitat, the majority due to SLR (>48%). Furthermore, there was a strong negative relationship between the proportion of development per island and the amount of new habitat formed. Islands with modest development (less than 8% of land area) saw formation of new areas of marsh vegetation suitable for rabbits, whereas islands with 8% or more of their lands developed between 1959 and 2006 saw little to no addition of LKMR habitat. Only 8% of habitat loss was directly due to conversion to impervious surfaces, indicating that the greatest threats from development were indirect, including blocking of the inland migration of habitat triggered by SLR. Our results were consistent with an ongoing squeeze of coastal ecosystems between rising seas and development as a threat to LKMR habitat, which raises concern for a wide variety of coastal species. Our results provide evidence that SLR has become a contemporary conservation concern, one that is exacerbated by development, and expected to increase in magnitude as ocean waters continue to rise.     

Influence of climate change and postdelisting management on long‐term population viability of the conservation‐reliant Kirtland's Warbler

Rapid global climate change is resulting in novel abiotic and biotic conditions and interactions. Identifying management strategies that maximize probability of long‐term persistence requires an understanding of the vulnerability of species to environmental changes. We sought to quantify the vulnerability of Kirtland's Warbler (Setophaga kirtlandii), a rare Neotropical migratory songbird that breeds almost exclusively in the Lower Peninsula of Michigan and winters in the Bahamian Archipelago, to projected environmental changes on the breeding and wintering grounds. We developed a population‐level simulation model that incorporates the influence of annual environmental conditions on the breeding and wintering grounds, and parameterized the model using empirical relationships. We simulated independent and additive effects of reduced breeding grounds habitat quantity and quality, and wintering grounds habitat quality, on population viability. Our results indicated the Kirtland's Warbler population is stable under current environmental and management conditions. Reduced breeding grounds habitat quantity resulted in reductions of the stable population size, but did not cause extinction under the scenarios we examined. In contrast, projected large reductions in wintering grounds precipitation caused the population to decline, with risk of extinction magnified when breeding habitat quantity or quality also decreased. Our study indicates that probability of long‐term persistence for Kirtland's Warbler will depend on climate change impacts to wintering grounds habitat quality and contributes to the growing literature documenting the importance of considering the full annual cycle for understanding population dynamics of migratory species.     

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.     

The role of demography,intra‐species variation,and species distribution models in species' projections under climate change

Organisms are projected to shift their distribution ranges under climate change. The typical way to assess range shifts is by species distribution models (SDMs), which predict species’ responses to climate based solely on projected climatic suitability. However, life history traits can impact species’ responses to shifting habitat suitability. Additionally, it remains unclear if differences in vital rates across populations within a species can offset or exacerbate the effects of predicted changes in climatic suitability on population viability. In order to obtain a fuller understanding of the response of one species to projected climatic changes, we coupled demographic processes with predicted changes in suitable habitat for the monocarpic thistle Carlina vulgaris across northern Europe. We first developed a life history model with species‐specific average fecundity and survival rates and linked it to a SDM that predicted changes in habitat suitability through time with changes in climatic variables. We then varied the demographic parameters based upon observed vital rates of local populations from a translocation experiment. Despite the fact that the SDM alone predicted C. vulgaris to be a climate ‘winner’ overall, coupling the model with changes in demography and small‐scale habitat suitability resulted in a matrix of stable, declining, and increasing patches. For populations predicted to experience declines or increases in abundance due to changes in habitat suitability, altered fecundity and survival rates can reverse projected population trends.     

Ecophysiological variation across a forest‐ecotone gradient produces divergent climate change vulnerability within species

Climate change related risks and impacts on ectotherms will be mediated by habitats and their influence on local thermal environments. While many studies have documented morphological and genetic aspects of niche divergence across habitats, few have examined thermal performance across such gradients and directly linked this variation to contemporary climate change impacts. In this study, we quantified variation in thermal performance across a gradient from forest to gallery forest‐savanna mosaic in Cameroon for a skink species (Trachylepis affinis) known to be diverging genetically and morphologically across that habitat gradient. Based on these results, we then applied a mechanistic modelling approach (NicheMapR) to project changes in potential activity, as constrained by thermal performance, in response to climate change. As a complimentary approach, we also compared mechanistic projections with climate‐driven changes in habitat suitability based on species distribution models of forest and ecotone skinks. We found that ecotone skinks may benefit from warming and experience increased activity while forest skinks will likely face a drastic decrease in thermal suitability across the forest zone. Species distribution models projected that thermal suitability for forest skinks in coastal forests would decline but in other parts of the forest zone skinks are projected to experience increased thermal suitability. The results here highlight the utility of mechanistic approaches in revealing and understanding patterns of climate change vulnerability which may not be detected with species distribution models alone. This study also emphasizes the importance of intra‐specific physiological variation, and habitat‐specific thermal performance relationships in particular, in determining warming responses.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

Future climate change driven sea‐level rise: secondary consequences from human displacement for island biodiversity

Sea‐level rise (SLR) due to global warming will result in the loss of many coastal areas. The direct or primary effects due to inundation and erosion from SLR are currently being assessed; however, the indirect or secondary ecological effects, such as changes caused by the displacement of human populations, have not been previously evaluated. We examined the potential ecological consequences of future SLR on >1,200 islands in the Southeast Asian and the Pacific region. Using three SLR scenarios (1, 3, and 6 m elevation, where 1 m approximates most predictions by the end of this century), we assessed the consequences of primary and secondary SLR effects from human displacement on habitat availability and distributions of selected mammal species. We estimate that between 3–32% of the coastal zone of these islands could be lost from primary effects, and consequently 8–52 million people would become SLR refugees. Assuming that inundated urban and intensive agricultural areas will be relocated with an equal area of habitat loss in the hinterland, we project that secondary SLR effects can lead to an equal or even higher percent range loss than primary effects for at least 10–18% of the sample mammals in a moderate range loss scenario and for 22–46% in a maximum range loss scenario. In addition, we found some species to be more vulnerable to secondary than primary effects. Finally, we found high spatial variation in vulnerability: species on islands in Oceania are more vulnerable to primary SLR effects, whereas species on islands in Indo‐Malaysia, with potentially 7–48 million SLR refugees, are more vulnerable to secondary effects. Our findings show that primary and secondary SLR effects can have enormous consequences for human inhabitants and island biodiversity, and that both need to be incorporated into ecological risk assessment, conservation, and regional planning.     

Time to extinction in deteriorating environments

Habitat degradation and destruction are the predominant drivers of population extinction, but there is little theory to guide the analysis of population viability in deteriorating environments. To address this gap, we investigated extinction times in time-varying, demographically stochastic versions of the logistic model for population dynamics. A property of these models is the “extinction delay,” a quantitative measure of the time lag in extinction created by species-specific extinction debt. For completeness, three models were constructed to represent the different demographic routes by which deterioration may affect population dynamics. Numerical analysis for two notional life histories indicated that the demographic response to environmental deterioration had a large effect on extinction delay, but a third analysis showed that the trajectory of the decline in carrying capacity ultimately characterized its magnitude. A concave decline in carrying capacity produced a large extinction delay while a small delay occurred with a convex decline. Furthermore, our results explore the non-monotonicity of extinction debt with respect to the speed of deterioration. A peak is present at low levels of deterioration, and the height of the peak and the asymptote of delay are affected by both life history parameterizations and the rate of change of the carrying capacity. The results suggest that population viability analyses must consider not only environmental deterioration, but also the effects of deterioration on the trajectory of the decline in carrying capacity.     

Population modelling and genetics of a critically endangered Madagascan palm Tahina spectabilis

Madagascar is home to 208 indigenous palm species, almost all of them endemic and >80% of which are endangered. We undertook complete population census and sampling for genetic analysis of a relatively recently discovered giant fan palm, the Critically Endangered Tahina spectablis in 2008 and 2016. Our 2016 study included newly discovered populations and added to our genetic study. We incorporated these new populations into species distribution niche model (SDM) and projected these onto maps of the region. We developed population matrix models based on observed demographic data to model population change and predict the species vulnerability to extinction by undertaking population viability analysis (PVA). We investigated the potential conservation value of reintroduced planted populations within the species potential suitable habitat. We found that the population studied in 2008 had grown in size due to seedling regeneration but had declined in the number of reproductively mature plants, and we were able to estimate that the species reproduces and dies after approximately 70 years. Our models suggest that if the habitat where it resides continues to be protected the species is unlikely to go extinct due to inherent population decline and that it will likely experience significant population growth after approximately 80 years due to the reproductive and life cycle attributes of the species. The newly discovered populations contain more genetic diversity than the first discovered southern population which is genetically depauperate. The species appears to demonstrate a pattern of dispersal leading to isolated founder plants which may eventually lead to population development depending on local establishment opportunities. The conservation efforts currently put in place including the reintroduction of plants within the species potential suitable habitat if maintained are thought likely to enable the species to sustain itself but it remains vulnerable to anthropogenic impacts.     

Relative influence of habitat structure,species interactions and rainfall on the post‐fire population dynamics of ground‐dwelling vertebrates

The long‐term impacts of wildfires on animal populations are largely unknown. We used time‐series data based on a tracking index, from coastal NSW spanning 28 years after a wildfire, to investigate the relative influence of habitat structure, species interactions and climate on post‐fire animal population dynamics. The fire had an immediate impact on habitat structure, reducing and simplifying vegetation cover, which then underwent post‐fire successional change including an increase and plateau in tree canopy cover; an increase, stabilization and then decline in shrub cover; and an increase in ground litter cover. Population changes of different animal species were influenced by different components of successional change, but there was also evidence that species interactions were important. For example, bandicoots (Isoodon obesulus and Perameles nasuta combined) increased concurrent with an increase in shrub cover then declined at a faster rate than a direct association with senescing shrub cover would suggest, while the feral cat (Felis catus) population changed with the bandicoot population, suggesting a link between these species. Potoroos (Potorous tridactylus) increased 10 years after the fire concurrent with the closing tree canopy, but there was also evidence of a negative association with feral foxes (Vulpes vulpes). Variation in rainfall did not have significant effects on the population dynamics of any species. Our results suggest that changes in habitat structure play a key role in the post‐fire dynamics of many ground‐dwelling animals and hence different fire regimes are likely to influence animal dynamics through their effects on habitat structure. However, the role of predator–prey interactions, particularly with feral predators, is less clear and further study will require manipulative experiments of predators in conjunction with fire treatments to determine whether feral predator control should be integrated with fire management to improve outcomes for some native species.     

Frog population viability under present and future climate conditions: a Bayesian state-space approach

1.?World-wide extinctions of amphibians are at the forefront of the biodiversity crisis, with climate change figuring prominently as a potential driver of continued amphibian decline. As in other taxa, changes in both the mean and variability of climate conditions may affect amphibian populations in complex, unpredictable ways. In western North America, climate models predict a reduced duration and extent of mountain snowpack and increased variability in precipitation, which may have consequences for amphibians inhabiting montane ecosystems. 2.?We used Bayesian capture-recapture methods to estimate survival and transition probabilities in a high-elevation population of the Columbia spotted frog (Rana luteiventris) over 10?years and related these rates to interannual variation in peak snowpack. Then, we forecasted frog population growth and viability under a range of scenarios with varying levels of change in mean and variance in snowpack. 3.?Over a range of future scenarios, changes in mean snowpack had a greater effect on viability than changes in the variance of snowpack, with forecasts largely predicting an increase in population viability. Population models based on snowpack during our study period predicted a declining population. 4.?Although mean conditions were more important for viability than variance, for a given mean snowpack depth, increases in variability could change a population from increasing to decreasing. Therefore, the influence of changing climate variability on populations should be accounted for in predictive models. The Bayesian modelling framework allows for the explicit characterization of uncertainty in parameter estimates and ecological forecasts, and thus provides a natural approach for examining relative contributions of mean and variability in climatic variables to population dynamics. 5.?Longevity and heterogeneous habitat may contribute to the potential for this amphibian species to be resilient to increased climatic variation, and shorter-lived species inhabiting homogeneous ecosystems may be more susceptible to increased variability in climate conditions.     

Sediment-benthos relationships as a tool to assist in conservation practices in a coastal lagoon subjected to sediment change

This study explores the relation between sediment composition and intertidal macrobenthos populations in the Zwin nature reserve (Belgium and The Netherlands), a tidal lagoon that is included in the Ramsar list of wetlands of international importance and has been designated as Natura 2000 area, among others due to its function as wintering habitat for shorebirds that feed upon macrobenthic invertebrates. Species response models show highest biomass of these prey species in organically enriched cohesive sediments and a distinct decline in probability of occurrence for most species in coarse sediments. Further, the biomass of macrobenthos declined between 2003 and 2010 in the extensive low intertidal inlet channel concurrent with the coarsening of the sediment over time in this hydrodynamically stressed habitat. In contrast, macrobenthos biomass increased in a sheltered shallow intertidal habitat that acted as a catchment area for finer sediments, therefore facilitating the succession towards a higher elevated habitat with salt marsh vegetation establishment. Hence, spatio-temporal sediment dynamics decreased site quality for intertidal predators due to a reduction in feeding areas over time, and a change in physical sediment properties that alter the macrobenthos species occurrence and population biomass. This study thus illustrates that sediment transport dynamics may affect the functioning of coastal shallow soft-sediment habitats, like coastal lagoons. The presented macrobenthos species response models provide a tool to assist in management actions that enable the conservation of cohesive low intertidal habitats that provide a high food supply to shorebirds, fish and macrocrustaceans.     

Projecting the future of an alpine ungulate under climate change scenarios

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key “early warning signs” about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37‐year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate‐driven effects influence mountain goat populations, we developed an age‐structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70‐year time window (2015–2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., “thermoneutral”) summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%–86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate‐linked bottom‐up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence.     

Impacts of Land Cover Data Selection and Trait Parameterisation on Dynamic Modelling of Species’ Range Expansion

Dynamic models for range expansion provide a promising tool for assessing species’ capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.     

Predicting the effects of climate change on population connectivity and genetic diversity of an imperiled freshwater mussel,Cumberlandia monodonta (Bivalvia: Margaritiferidae), in riverine systems

In the face of global climate change, organisms may respond to temperature increases by shifting their ranges poleward or to higher altitudes. However, the direction of range shifts in riverine systems is less clear. Because rivers are dendritic networks, there is only one dispersal route from any given location to another. Thus, range shifts are only possible if branches are connected by suitable habitat, and stream‐dwelling organisms can disperse through these branches. We used Cumberlandia monodonta (Bivalvia: Unionoida: Margaritiferidae) as a model species to investigate the effects of climate change on population connectivity because a majority of contemporary populations are panmictic. We combined ecological niche models (ENMs) with population genetic simulations to investigate the effects of climate change on population connectivity and genetic diversity of C. monodonta. The ENMs were constructed using bioclimatic and landscape data to project shifts in suitable habitat under future climate scenarios. We then used forward‐time simulations to project potential changes in genetic diversity and population connectivity based on these range shifts. ENM results under current conditions indicated long stretches of highly suitable habitat in rivers where C. monodonta persists; populations in the upper Mississippi River remain connected by suitable habitat that does not impede gene flow. Future climate scenarios projected northward and headwater‐ward range contraction and drastic declines in habitat suitability for most extant populations throughout the Mississippi River Basin. Simulations indicated that climate change would greatly reduce genetic diversity and connectivity across populations. Results suggest that a single, large population of C. monodonta will become further fragmented into smaller populations, each of which will be isolated and begin to differentiate genetically. Because C. monodonta is a widely distributed species and purely aquatic, our results suggest that persistence and connectivity of stream‐dwelling organisms will be significantly altered in response to future climate change.