Biodiversity conservation adaptation to climate change: Protecting the actors or the stage.

To be able to protect biodiversity in coming decades, conservation strategies need to consider what sites will be important for species not just today but also in the future. Different methods have been proposed to identify places that will be important for species in the future. Two of the most frequently used methods, ecological niche modeling and climate resilience, have distinct aims. The former focuses on identifying the suitable environmental conditions for species, thus protecting the "actor," namely, the species, whereas the latter seeks to safeguard the "stage," or the landscape in which species occur. We used the two methods to identify climate refugia for 258 forest vertebrates under short- and long-term climatic changes in a biodiversity hotspot, the Appalachian ecoregion of the United States. We also evaluated the spatial congruence of the two approaches for a possible conservation application, that of protecting 30% of the Appalachian region, in line with recent national and international policy recommendations. We detected weak positive correlations between resilience scores and baseline vertebrate richness, estimated with ecological niche models for historical (baseline) climatic conditions. The correlations were stronger for amphibians and mammals than for birds and reptiles. Under climate change scenarios, the correlations between estimated vertebrate richness and resilience were also weakly positive; a positive correlation was detected only for amphibians. Locations with estimated future gain of suitable climatic conditions for vertebrates showed low correlation with resilience. Overall, our results indicate that climate resilience and ecological niche modeling approaches capture different characteristics of projected distributional changes of Appalachian vertebrates. A climate resilience (the stage) approach could be more effective in safeguarding species with low dispersal abilities, whereas an ecological niche modeling (the actor) approach could be more suitable for species with long-distance dispersal capacity because they may be more broadly impacted by climate and less sensitive to geophysical features captured by a climate resilience approach.

The relative influence of history, climate, topography and vegetation structure on local animal richness varies among taxa and spatial grains.

Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade-off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated. Here, we related variation in local species richness of ground beetles, landbirds and small mammals to variation in vegetation structure and topography, regional climate, biome diversity and glaciation history for 27 sites across the USA at two different spatial grains. We studied the relative influence of broad-scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity and glacial era ice cover) and fine-scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot-level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales. For all three animal groups, our models explained much of the variation in local species richness (85%-89%), but site-level variables explained a greater proportion of richness variance than plot-level variables. Temperature was the most important site-level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot-level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site-level predictor. Relationships between plot-level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to the continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multiscale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment-richness studies.

Global progress in incorporating climate adaptation into land protection for biodiversity since Aichi targets.

Climate adaptation strategies are being developed and implemented to protect biodiversity from the impacts of climate change. A well-established strategy involves the identification and addition of new areas for conservation, and most countries agreed in 2010 to expand the global protected area (PA) network to 17% by 2020 (Aichi Biodiversity Target 11). Although great efforts to expand the global PA network have been made, the potential of newly established PAs to conserve biodiversity under future climate change remains unclear at the global scale. Here, we conducted the first global-extent, country-level assessment of the contribution of PA network expansion toward three key land prioritization approaches for biodiversity persistence under climate change: protecting climate refugia, protecting abiotic diversity, and increasing connectivity. These approaches avoid uncertainties of biodiversity predictions under climate change as well as the issue of undescribed species. We found that 51% of the countries created new PAs in locations with lower mean climate velocity (representing better climate refugia) and 58% added PAs in areas with higher mean abiotic diversity compared to the available, non-human-dominated lands not chosen for protection. However, connectivity among PAs declined in 53% of the countries, indicating that many new PAs were located far from existing PAs. Lastly, we identified potential improvements for climate adaptation, showing that 94% of the countries have the opportunity to improve in executing one or more approaches to conserve biodiversity. Most countries (60%) were associated with multiple opportunities, highlighting the need for integrative strategies that target multiple land protection approaches. Our results demonstrate that a global improvement in the protection of climate refugia, abiotic diversity, and connectivity of reserves is needed to complement land protection informed by existing and projected species distributions. Our study also provides a framework for countries to prioritize land protection for climate adaptation using publicly available data.

Potential regional declines in species richness of tomato pollinators in North America under climate change.

About 70% of the world's main crops depend on insect pollination. Climate change is already affecting the abundance and distribution of insects, which could cause geographical mismatches between crops and their pollinators. Crops that rely primarily on wild pollinators (e.g., crops that cannot be effectively pollinated by commercial colonies of honey bees) could be particularly in jeopardy. However, limited information on plant-pollinator associations and pollinator distributions complicate the assessment of climate change impacts on specific crops. To study the potential impacts of climate change on pollination of a specific crop in North America, we use the case of open-field tomato crops, which rely on buzz pollinators (species that use vibration to release pollen, such as bumble bees) to increase their production. We aimed to (1) assess potential changes in buzz pollinator distribution and richness, and (2) evaluate the overlap between areas with high densities of tomato crops and high potential decrease in richness. We used baseline (1961-1990) climate and future (2050s and 2080s) climatic projections in ecological niche models fitted with occurrences of wild bees, documented in the literature as pollinators of tomatoes, to estimate the baseline and future potential distribution of suitable climatic conditions of targeted species and to create maps of richness change across North America. We obtained reliable models for 15 species and found important potential decreases in the distribution of some pollinators (e.g., Lasioglossum pectorale and Augochlorella aurata). We observed geographical discrepancies in the projected change in species richness across North America, detecting important declines in the eastern United States (up to 11 species decrease for 2050s). After overlapping the maps of species richness change with a tomato crop map for the United States, we found spatial correspondence between richness declines and areas with high concentration of tomato crops. Disparities in the effects of climate change on the potential future distribution of different wild pollinators and geographical variation in richness highlight the importance of crop-specific studies. Our study also emphasizes the challenges of compiling and modeling crop-specific pollinator data and the need to improve our understanding of current distribution of pollinators and their community dynamics under climate change.

Incorporating fragmentation and non-native species into distribution models to inform fluvial fish conservation.

Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the range of the fluvial-specialist shoal bass (Micropterus cataractae) continues to decrease, yet how perceived threats have contributed to range loss is largely unknown. We used species distribution models to determine which factors contributed most to shoal bass range loss. We estimated a potential distribution based on natural abiotic factors and a series of currently occupied distributions that incorporated variables characterizing land cover, non-native species, and river fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). We allowed interspecific relationships between non-native congeners and shoal bass to vary across fragmentation intensities. Results from the potential distribution model estimated shoal bass presence throughout much of their native basin, whereas models of currently occupied distribution showed that range loss increased as fragmentation intensified. Response curves from models of currently occupied distribution indicated a potential interaction between fragmentation intensity and the relationship between shoal bass and non-native congeners, wherein non-natives may be favored at the highest fragmentation intensity. Response curves also suggested that >100 km of interconnected, free-flowing stream fragments were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested that models had favorable predictive and discriminative abilities. Similar approaches that use readily available, diverse, geospatial data sets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats.

Effects of life-history requirements on the distribution of a threatened reptile.

Survival and reproduction are the two primary life-history traits essential for species' persistence; however, the environmental conditions that support each of these traits may not be the same. Despite this, reproductive requirements are seldom considered when estimating species' potential distributions. We sought to examine potentially limiting environmental factors influencing the distribution of an oviparous reptile of conservation concern with respect to the species' survival and reproduction and to assess the implications of the species' predicted climatic constraints on current conservation practices. We used ecological niche modeling to predict the probability of environmental suitability for the alligator snapping turtle (Macrochelys temminckii). We built an annual climate model to examine survival and a nesting climate model to examine reproduction. We combined incubation temperature requirements, products of modeled soil temperature data, and our estimated distributions to determine whether embryonic development constrained the northern distribution of the species. Low annual precipitation constrained the western distribution of alligator snapping turtles, whereas the northern distribution was constrained by thermal requirements during embryonic development. Only a portion of the geographic range predicted to have a high probability of suitability for alligator snapping turtle survival was estimated to be capable of supporting successful embryonic development. Historic occurrence records suggest adult alligator snapping turtles can survive in regions with colder climes than those associated with consistent and successful production of offspring. Estimated egg-incubation requirements indicated that current reintroductions at the northern edge of the species' range are within reproductively viable environmental conditions. Our results highlight the importance of considering survival and reproduction when estimating species' ecological niches, implicating conservation plans, and benefits of incorporating physiological data when evaluating species' distributions.

Ecological approaches in veterinary epidemiology: mapping the risk of bat-borne rabies using vegetation indices and night-time light satellite imagery.

Rabies remains a disease of significant public health concern. In the Americas, bats are an important source of rabies for pets, livestock, and humans. For effective rabies control and prevention, identifying potential areas for disease occurrence is critical to guide future research, inform public health policies, and design interventions. To anticipate zoonotic infectious diseases distribution at coarse scale, veterinary epidemiology needs to advance via exploring current geographic ecology tools and data using a biological approach. We analyzed bat-borne rabies reports in Chile from 2002 to 2012 to establish associations between rabies occurrence and environmental factors to generate an ecological niche model (ENM). The main rabies reservoir in Chile is the bat species Tadarida brasiliensis; we mapped 726 occurrences of rabies virus variant AgV4 in this bat species and integrated them with contemporary Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The correct prediction of areas with rabies in bats and the reliable anticipation of human rabies in our study illustrate the usefulness of ENM for mapping rabies and other zoonotic pathogens. Additionally, we highlight critical issues with selection of environmental variables, methods for model validation, and consideration of sampling bias. Indeed, models with weak or incorrect validation approaches should be interpreted with caution. In conclusion, ecological niche modeling applications for mapping disease risk at coarse geographic scales have a promising future, especially with refinement and enrichment of models with additional information, such as night-time light data, which increased substantially the model's ability to anticipate human rabies.

Mixed-species flock sizes and compositions influence flock members' success in three field experiments with novel feeders.

Mixed-species groups and aggregations are quite common and may provide substantial fitness-related benefits to group members. Individuals may benefit from the overall size of the mixed-species group or from the diversity of species present, or both. Here we exposed mixed-species flocks of songbirds (Carolina chickadees, Poecile carolinensis, tufted titmice, Baeolophus bicolor, and the satellite species attracted to these two species) to three different novel feeder experiments to assess the influence of mixed-species flock size and composition on ability to solve the feeder tasks. We also assessed the potential role of habitat density and traffic noise on birds' ability to solve these tasks. We found that likelihood of solving a novel feeder task was associated with mixed-species flock size and composition, though the specific social factor involved depended on the particular species and on the novel feeder. We did not find an influence of habitat density or background traffic noise on likelihood of solving novel feeder tasks. Overall, our results reveal the importance of variation in mixed-species group size and diversity on foraging success in these songbirds.

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene.

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

How does spatial extent and environmental limits affect the accuracy of species richness estimates from ecological niche models? A case study with North American Pinaceae and Cactaceae.

Measuring species richness at varying spatial extents can be challenging, especially at large extents where exhaustive species surveys are difficult or impossible. Our work aimed at determining the reliability of species richness estimates from stacked ecological niche models at different spatial extents for taxonomic groups with vastly different environmental dependencies and interactions. To accomplish this, we generated ecological niche models for the species of Cactaceae and Pinaceae that occur within 180 published floras from North America north of Mexico. We overlaid or stacked the resulting species' potential distribution estimates over the bounding boxes representing each of the 180 floras to generate predictions of species richness. In general, our stacked models of Cactaceae and Pinaceae were poor predictors of species richness. The relationships between observed and predicted values improved noticeably with the size of spatial extents. However, the stacked models tended to overpredict the richness of Cactaceae and over- and underpredict the richness of Pinaceae. Cactaceae stacked models showed higher sensitivity and lower specificity than those for Pinaceae. We conclude that stacked ecological niche models may be somewhat poor predictors of species richness at smaller spatial extents and should be used with caution for this purpose. Perhaps more importantly, abilities to compensate for their limitations or apply corrections to their reliability may vary with taxonomic groups.

Influence of social and physical environmental variation on antipredator behavior in mixed-species parid flocks.

Carolina chickadees (Poecile carolinensis) and tufted titmice (Baeolophus bicolor) regularly form flocks with multiple species through the winter months, including white-breasted nuthatches (Sitta carolinensis). Earlier studies found that behavior of both chickadees and titmice was sensitive to mixed-species flock composition. Little is known about the influence of background noise level and vegetation density on the antipredator behaviors of individuals within these flocks, however. We tested for the effects of vegetation density, traffic noise, and flock composition (conspecific number, flock diversity, and flock size) on antipredator behavioral responses following an alarm call playback (Study 1) and an owl model presentation (Study 2) at feeders. We recorded background traffic noise and performed lidar scans to quantify vegetation density at each site. After a feeder had been stocked with seed and a flock was present, we recorded calls produced, and we identified flock composition metrics. We coded seed-taking latency, call latency, mob latency, and mob duration following the respective stimulus presentation and tested for effects of flock composition metrics, vegetation density, and background noise on these responses. For the alarm call playback study, flock composition drove behaviors in chickadees and titmice, and vegetation density drove behaviors in chickadees and nuthatches. For the owl model study, conspecific number predicted behavior in chickadees, and mob duration was predicted by nuthatch number. The results reveal individual sensitivity to group composition in anti-predatory and foraging behavior in simulated risky contexts. Additionally, our data suggest that the modality of perceived simulated risk (acoustic vs. visual) and the density of vegetation influence behavior in these groups.

Aggregate population-level models informed by genetics predict more suitable habitat than traditional species-level model across the range of a widespread riparian tree.

Identifying and predicting how species ranges will shift in response to climate change is paramount for conservation and restoration. Ecological niche models are the most common method used to estimate potential distributions of species; however, they traditionally omit knowledge of intraspecific variation that can allow populations to respond uniquely to change. Here, we aim to test how population X environment relationships influence predicted suitable geographic distributions by comparing aggregated population-level models with species-level model predictions of suitable habitat within population ranges and across the species' range. We also test the effect of two variable selection methods on these predictions-both addressing the possibility of local adaptation: Models were built with (a) a common set, and number, of predictors and, (b) a unique combination and number of predictors specific to each group's training extent. Our study addresses the overarching hypothesis that populations have unique environmental niches, and specifically that (1) species-level models predict more suitable habitat within the ranges of genetic populations than individual models built from those groups, particularly when compared models are built with the same set of environmental predictors; and (2) aggregated genetic population models predict more suitable habitat across the species' range than the species-level model, an = d this difference will increase when models are trained with individualized predictors. We found the species models predicted more habitat within population ranges for two of three genetic groups regardless of variable selection, and that aggregated population models predicted more habitat than species' models, but that individualized predictors increased this difference. Our study emphasizes the extent to which changes to model predictions depend on the inclusion of genetic information and on the type and selection of predictors. Results from these modeling decisions can have broad implications for predicting population-level ecological and evolutionary responses to climate change.

Variable precipitation leads to dynamic range limits of forest songbirds at a forest-grassland ecotone.

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest-grassland ecotone in the southcentral United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad-scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest-breeding passerines from 30-year average climate conditions from 1980 to 2010. During this time, the southern Great Plains experienced an unprecedented wet period without periodic multi-year droughts that characterized the region's long-term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952-1958 and 1966-1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest-grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980-2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966-1972 range limit projections. Periods of lower precipitation in the forest-grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.

A checklist for maximizing reproducibility of ecological niche models.

Reporting specific modelling methods and metadata is essential to the reproducibility of ecological studies, yet guidelines rarely exist regarding what information should be noted. Here, we address this issue for ecological niche modelling or species distribution modelling, a rapidly developing toolset in ecology used across many aspects of biodiversity science. Our quantitative review of the recent literature reveals a general lack of sufficient information to fully reproduce the work. Over two-thirds of the examined studies neglected to report the version or access date of the underlying data, and only half reported model parameters. To address this problem, we propose adopting a checklist to guide studies in reporting at least the minimum information necessary for ecological niche modelling reproducibility, offering a straightforward way to balance efficiency and accuracy. We encourage the ecological niche modelling community, as well as journal reviewers and editors, to utilize and further develop this framework to facilitate and improve the reproducibility of future work. The proposed checklist framework is generalizable to other areas of ecology, especially those utilizing biodiversity data, environmental data and statistical modelling, and could also be adopted by a broader array of disciplines.

Collinearity in ecological niche modeling: Confusions and challenges.

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Beyond the numbers: Human attitudes and conflict with lions (Panthera leo) in and around Gambella National Park, Ethiopia.

Human-lion conflict is one of the leading threats to lion populations and while livestock loss is a source of conflict, the degree to which livestock depredation is tolerated by people varies between regions and across cultures. Knowledge of local attitudes towards lions and identification of drivers of human-lion conflict can help formulate mitigation measures aimed at promoting coexistence of humans with lions. We assessed locals' attitudes towards lions in and around Gambella National Park and compared the findings with published data from Kafa Biosphere Reserve, both in western Ethiopia. We used household interviews to quantify livestock loss. We found that depredation was relatively low and that disease and theft were the top factors of livestock loss. Remarkably, however, tolerance of lions was lower around Gambella National Park than in Kafa Biosphere Reserve. Multivariate analysis revealed that education level, number of livestock per household, livestock loss due to depredation, and livestock loss due to theft were strong predictors of locals' attitude towards lion population growth and conservation. We show that the amount of livestock depredation alone is not sufficient to understand human-lion conflicts and we highlight the importance of accounting for cultural differences in lion conservation. The low cultural value of lions in the Gambella region corroborate the findings of our study. In combination with growing human population and land-use change pressures, low cultural value poses serious challenges to long-term lion conservation in the Gambella region. We recommend using Arnstein's ladder of participation in conservation education programs to move towards proactive involvement of locals in conservation.

Canine and human infection with Borrelia burgdorferi in the New York City metropolitan area.

BACKGROUND: Autochthonous transmission of Borrelia burgdorferi, the primary agent of Lyme disease in dogs and people in North America, commonly occurs in the northeastern United States, including the New York City metropolitan area, a region with a large human and pet population and broadly diverse demographics and habitats. METHODS: We evaluated results from a specific, C6-based serologic assay performed on 234,633 canine samples to compare evidence of past or current infection with B. burgdorferi (sensu stricto) in dogs to county-wide social and environmental factors, as well as to reported cases of Lyme disease in people. RESULTS: The data revealed a wide range of county level percent positive canine test results (1.2-27.3%) and human case reports (0.5-438.7 case reports/100,000 people). Dogs from highly (> 50%) forested areas and counties with lower population density had the highest percent positive test results, at 21.1% and 17.9%, respectively. Canine percent positive tests correlated with population-adjusted human case reports (R2 = 0.48, P < 0.0001), as well as population density, development intensity, temperature, normalized difference vegetation index, and habitat type. Subsequent multiple regression allowed an accurate prediction of infection risk in dogs (R2 = 0.90) but was less accurate at predicting human case reports (R2 = 0.74). CONCLUSION: In areas where Lyme disease is endemic, canine serology continues to provide insight into risk factors for transmission to both dogs and people although some differences in geographic patterns of canine infection and human disease reports are evident.

Towards an eco-phylogenetic framework for infectious disease ecology.

Identifying patterns and drivers of infectious disease dynamics across multiple scales is a fundamental challenge for modern science. There is growing awareness that it is necessary to incorporate multi-host and/or multi-parasite interactions to understand and predict current and future disease threats better, and new tools are needed to help address this task. Eco-phylogenetics (phylogenetic community ecology) provides one avenue for exploring multi-host multi-parasite systems, yet the incorporation of eco-phylogenetic concepts and methods into studies of host pathogen dynamics has lagged behind. Eco-phylogenetics is a transformative approach that uses evolutionary history to infer present-day dynamics. Here, we present an eco-phylogenetic framework to reveal insights into parasite communities and infectious disease dynamics across spatial and temporal scales. We illustrate how eco-phylogenetic methods can help untangle the mechanisms of host-parasite dynamics from individual (e.g. co-infection) to landscape scales (e.g. parasite/host community structure). An improved ecological understanding of multi-host and multi-pathogen dynamics across scales will increase our ability to predict disease threats.

Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts.

Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species' distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species' distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel's quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence species' distributions. Special attention should be given to selecting variables for ENMs, and tests of model performance should be used to validate the choice of variables.