Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.     

American pika in a low‐elevation lava landscape: expanding the known distribution of a temperature‐sensitive species

In 2010, the American pika (Ochotona princeps fenisex) was denied federal protection based on limited evidence of persistence in low‐elevation environments. Studies in nonalpine areas have been limited to relatively few environments, and it is unclear whether patterns observed elsewhere (e.g., Bodie, CA) represent other nonalpine habitats. This study was designed to establish pika presence in a new location, determine distribution within the surveyed area, and evaluate influences of elevation, vegetation, lava complexity, and distance to habitat edge on pika site occupancy. In 2011 and 2012, we conducted surveys for American pika on four distinct subalpine lava flows of Newberry National Volcanic Monument, Oregon, USA. Field surveys were conducted at predetermined locations within lava flows via silent observation and active searching for pika sign. Site habitat characteristics were included as predictors of occupancy in multinomial regression models. Above and belowground temperatures were recorded at a subsample of pika detection sites. Pika were detected in 26% (2011) and 19% (2012) of survey plots. Seventy‐four pika were detected outside survey plot boundaries. Lava complexity was the strongest predictor of pika occurrence, where pika were up to seven times more likely to occur in the most complicated lava formations. Pika were two times more likely to occur with increasing elevation, although they were found at all elevations in the study area. This study expands the known distribution of the species and provides additional evidence for persistence in nonalpine habitats. Results partially support the predictive occupancy model developed for pika at Craters of the Moon National Monument, another lava environment. Characteristics of the lava environment clearly influence pika site occupancy, but habitat variables reported as important in other studies were inconclusive here. Further work is needed to gain a better understanding of the species’ current distribution and ability to persist under future climate conditions.     

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current,past, and future climates

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat‐balance model, to convert macroclimate data to pika‐specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate‐imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.     

Variation in subsurface thermal characteristics of microrefuges used by range core and peripheral populations of the American pika (Ochotona princeps)

Microrefuges provide microclimates decoupled from inhospitable regional climate regimes that enable range‐peripheral populations to persist and are important to cold‐adapted species in an era of accelerated climate change. However, identifying and describing the thermal characteristics of microrefuge habitats is challenging, particularly for mobile organisms in cryptic, patchy habitats. We examined variation in subsurface thermal conditions of microrefuge habitats among different rock substrate types used by the American pika (Ochotona princeps ), a climate‐sensitive, rock‐dwelling Lagomorph. We compared subsurface temperatures in talus and lava substrates in pika survey sites in two US national park units; one park study area on the range periphery and the other in the range core. We deployed paired sensors to examine within‐site temperature variation. We hypothesized that subsurface temperatures within occupied sites and structurally complex substrates would be cooler in summer and warmer in winter than unoccupied and less complex sites. Although within‐site variability was high, with correlations between paired sensors as low as 47%, we found compelling evidence that pikas occupy microrefuge habitats where subsurface conditions provide more thermal stability than in unoccupied microhabitats. The percentage of days in which microhabitat temperatures were between ?2.5 and 25.5°C was significantly higher in occupied sites. Interestingly, thermal conditions were substantially more stable (p  < .05) in the lava substrate type identified to be preferentially used by pikas (pahoehoe vs. a'a) in a previous study. Our study and others suggest that thermal stability appears to be the defining characteristic of subsurface microrefuges used by American pikas and is a likely explanation for enigmatic population persistence at the range periphery. Our study exemplifies an integrated approach for studying complex microhabitat conditions, paired with site use surveys and contextualized with information about gene flow provided by complementary studies.     

Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology

Understanding the drivers of phenological events is vital for forecasting species’ responses to climate change. We developed flexible Bayesian survival regression models to assess a 29‐year, individual‐level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time‐varying (chill and heat units) and time‐invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2–6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time‐to‐event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.     

Adaptive divergence along environmental gradients in a climate‐change‐sensitive mammal

In the face of predicted climate change, a broader understanding of biotic responses to varying environments has become increasingly important within the context of biodiversity conservation. Local adaptation is one potential option, yet remarkably few studies have harnessed genomic tools to evaluate the efficacy of this response within natural populations. Here, we show evidence of selection driving divergence of a climate‐change‐sensitive mammal, the American pika (Ochotona princeps), distributed along elevation gradients at its northern range margin in the Coast Mountains of British Columbia (BC), Canada. We employed amplified‐fragment‐length‐polymorphism‐based genomic scans to conduct genomewide searches for candidate loci among populations inhabiting varying environments from sea level to 1500 m. Using several independent approaches to outlier locus detection, we identified 68 candidate loci putatively under selection (out of a total 1509 screened), 15 of which displayed significant associations with environmental variables including annual precipitation and maximum summer temperature. These candidate loci may represent important targets for predicting pika responses to climate change and informing novel approaches to wildlife conservation in a changing world.     

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site‐specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.     

Predicting shifts in parasite distribution with climate change: a multitrophic level approach

Climate change likely will lead to increasingly favourable environmental conditions for many parasites. However, predictions regarding parasitism's impacts often fail to account for the likely variability in host distribution and how this may alter parasite occurrence. Here, we investigate potential distributional shifts in the meningeal worm, Parelaphostrongylosis tenuis, a protostrongylid nematode commonly found in white‐tailed deer in North America, whose life cycle also involves a free‐living stage and a gastropod intermediate host. We modelled the distribution of the hosts and free‐living larva as a complete assemblage to assess whether a complex trophic system will lead to an overall increase in parasite distribution with climate change, or whether divergent environmental niches may promote an ecological mismatch. Using an ensemble approach to climate modelling under two different carbon emission scenarios, we show that whereas the overall trend is for an increase in niche breadth for each species, mismatches arise in habitat suitability of the free‐living larva vs. the definitive and intermediate hosts. By incorporating these projected mismatches into a combined model, we project a shift in parasite distribution accounting for all steps in the transmission cycle, and identify that overall habitat suitability of the parasite will decline in the Great Plains and southeastern USA, but will increase in the Boreal Forest ecoregion, particularly in Alberta. These results have important implications for wildlife conservation and management due to the known pathogenicity of parelaphostrongylosis to alternate hosts including moose, caribou and elk. Our results suggest that disease risk forecasts which fail to consider biotic interactions may be overly simplistic, and that accounting for each of the parasite's life stages is key to refining predicted responses to climate change.     

The implication of irrigation in climate change impact assessment: a European‐wide study

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO₂ effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982–2006) and three SRES scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process‐based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr^?1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO₂ effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO₂ effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

An approach to consider behavioral plasticity as a source of uncertainty when forecasting species' response to climate change

The rapid ecological shifts that are occurring due to climate change present major challenges for managers and policymakers and, therefore, are one of the main concerns for environmental modelers and evolutionary biologists. Species distribution models (SDM) are appropriate tools for assessing the relationship between species distribution and environmental conditions, so being customarily used to forecast the biogeographical response of species to climate change. A serious limitation of species distribution models when forecasting the effects of climate change is that they normally assume that species behavior and climatic tolerances will remain constant through time. In this study, we propose a new methodology, based on fuzzy logic, useful for incorporating the potential capacity of species to adapt to new conditions into species distribution models. Our results demonstrate that it is possible to include different behavioral responses of species when predicting the effects of climate change on species distribution. Favorability models offered in this study show two extremes: one considering that the species will not modify its present behavior, and another assuming that the species will take full advantage of the possibilities offered by an increase in environmental favorability. This methodology may mean a more realistic approach to the assessment of the consequences of global change on species' distribution and conservation. Overlooking the potential of species' phenotypical plasticity may under‐ or overestimate the predicted response of species to changes in environmental drivers and its effects on species distribution. Using this approach, we could reinforce the science behind conservation planning in the current situation of rapid climate change.     

Projected shifts in fish species dominance in Wisconsin lakes under climate change

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake‐specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake‐specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid‐century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.     

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.     

Hierarchical foraging by giraffe in a heterogeneous savannah,Tanzania

Understanding foraging decisions made by wildlife at different spatio‐temporal scales is important for wildlife management and conservation. We tested whether foraging decisions by Masai giraffe (Giraffa camelopardalis tippelskirchi Matschie) differed with scales; habitat, patch and tree in a heterogeneous savannah. We collected data from Arusha National Park, Tanzania, in March–May and August–October 2013. Visual observations were used to collect data on foraging behaviour. Measurements of tree height and stem height and scoring of accumulated browsing were made in 133 patches around trees where the giraffes had been seen browsing, and in a corresponding number of available patches. Giraffes selected Acacia shrub and Dodonea shrub habitats but not for water availability or predator avoidance. For patch use, giraffe selected high quantity of Acacia xanthophloea and Dodonea viscosa. Between plant species, A. xanthophloea was the most preferred and within plant species, tree quality was enhanced by tree height and high score of accumulated browsing. Generally, giraffes selected for A. xanthophloea at all scales.     

Morphological variation in salamanders and their potential response to climate change

Despite the recognition that some species might quickly adapt to new conditions under climate change, demonstrating and predicting such a fundamental response is challenging. Morphological variations in response to climate may be caused by evolutionary changes or phenotypic plasticity, or both, but teasing apart these processes is difficult. Here, we built on the number of thoracic vertebrae (NTV) in ectothermic vertebrates, a known genetically based feature, to establish a link with body size and evaluate how climate change might affect the future morphological response of this group of species. First, we show that in old‐world salamanders, NTV variation is strongly related to changes in body size. Secondly, using 22 salamander species as a case study, we found support for relationships between the spatial variation in selected bioclimatic variables and NTV for most of species. For 44% of species, precipitation and aridity were the predominant drivers of geographical variation of the NTV. Temperature features were dominant for 31% of species, while for 19% temperature and precipitation played a comparable role. This two‐step analysis demonstrates that ectothermic vertebrates may evolve in response to climate change by modifying the number of thoracic vertebrae. These findings allow to develop scenarios for potential morphological evolution under future climate change and to identify areas and species in which the most marked evolutionary responses are expected. Resistance to climate change estimated from species distribution models was positively related to present‐day species morphological response, suggesting that the ability of morphological evolution may play a role for species’ persistence under climate change. The possibility that present‐day capacity for local adaptation might help the resistance response to climate change can be integrated into analyses of the impact of global changes and should also be considered when planning management actions favouring species persistence.     

Projected impacts of 21st century climate change on diapause in Calanus finmarchicus

Diapause plays a key role in the life cycle of high latitude zooplankton. During diapause, animals avoid starving in winter by living in deep waters where metabolism is lower and met by lipid reserves. Global warming is therefore expected to shorten the maximum potential diapause duration by increasing metabolic rates and by reducing body size and lipid reserves. This will alter the phenology of zooplankton, impact higher trophic levels and disrupt biological carbon pumps. Here, we project the impacts of climate change on the key North Atlantic copepod Calanus finmarchicus under IPCC RCP 8.5. Potential diapause duration is modelled in relation to body size and overwintering temperature. The projections show pronounced geographic variations. Potential diapause duration reduces by more than 30% in the Western Atlantic, whereas in the key overwintering centre of the Norwegian Sea it changes only marginally. Surface temperature rises, which reduce body size and lipid reserves, will have a similar impact to deep‐water changes on diapause in many regions. Because deep‐water warming lags that at the surface, animals in the Labrador Sea could offset warming impacts by diapausing in deeper waters. However, the ability to control diapause depth may be limited.     

Plasticity in functional traits in the context of climate change: a case study of the subalpine forb Boechera stricta (Brassicaceae)

Environmental variation often induces shifts in functional traits, yet we know little about whether plasticity will reduce extinction risks under climate change. As climate change proceeds, phenotypic plasticity could enable species with limited dispersal capacity to persist in situ, and migrating populations of other species to establish in new sites at higher elevations or latitudes. Alternatively, climate change could induce maladaptive plasticity, reducing fitness, and potentially stalling adaptation and migration. Here, we quantified plasticity in life history, foliar morphology, and ecophysiology in Boechera stricta (Brassicaceae), a perennial forb native to the Rocky Mountains. In this region, warming winters are reducing snowpack and warming springs are advancing the timing of snow melt. We hypothesized that traits that were historically advantageous in hot and dry, low‐elevation locations will be favored at higher elevation sites due to climate change. To test this hypothesis, we quantified trait variation in natural populations across an elevational gradient. We then estimated plasticity and genetic variation in common gardens at two elevations. Finally, we tested whether climatic manipulations induce plasticity, with the prediction that plants exposed to early snow removal would resemble individuals from lower elevation populations. In natural populations, foliar morphology and ecophysiology varied with elevation in the predicted directions. In the common gardens, trait plasticity was generally concordant with phenotypic clines from the natural populations. Experimental snow removal advanced flowering phenology by 7 days, which is similar in magnitude to flowering time shifts over 2–3 decades of climate change. Therefore, snow manipulations in this system can be used to predict eco‐evolutionary responses to global change. Snow removal also altered foliar morphology, but in unexpected ways. Extensive plasticity could buffer against immediate fitness declines due to changing climates.     

Simulating effects of climate change under direct and diapause development in a butterfly

Temperature is one of the most important ecological factors affecting species survival and distributions. Therefore, global climate change, involving increases in mean surface temperature and the occurrence of extreme weather events, may pose a substantial challenge to biodiversity. Whereas tropical ectotherms are believed to be very sensitive to climate change, temperate‐zone species may actually benefit from higher temperatures. However, as in temperate zones large parts of the year are unsuitable for growth and reproduction, seasonal time constraints may complicate matters. Against this background we here investigate the impact of simulated climate change, involving increased mean temperatures and heat waves, across developmental pathways of the butterfly Lycaena tityrus (Poda) (Lepidoptera: Lycaenidae). Increased temperatures speeded up development but decreased pupal mass as expected. However, we found no evidence for detrimental effects of increased temperatures or even simulated heat waves. Furthermore, patterns did not differ between indirectly and directly developing individuals, which are assumed to be more time constrained. Our findings support the notion that not all species will be detrimentally affected by climate change, and suggest that species attributes may be more important than potential time constraints imposed by different developmental pathways.