Shorebird Migration in the Face of Climate Change

Changes in temperature and seasonality resulting from climate change are heterogeneous, potentially altering important sources of natural selection acting on species phenology. Some species have apparently adapted to climate change but the ability of most species to adapt remains unknown. The life history strategies of migratory animals are dictated by seasonal factors, which makes these species particularly vulnerable to heterogeneous changes in climate and phenology. Here, we examine the phenology of migratory shorebirds, their habitats, and primary food resources, and we hypothesize how climate change may affect migrants through predicted changes in phenology. Daily abundance of shorebirds at stopover sites was correlated with local phenology and peaked immediately prior to peaks in invertebrate food resources. A close relationship between migrant and invertebrate phenology indicates that shorebirds may be vulnerable to changes in seasonality driven by climate change. It is possible that shifts in migrant and invertebrate phenology will be congruent in magnitude and direction, but because migration phenology is dependent on a suite of ecological factors, any response is likely to occur at a larger temporal scale and may lag behind the response of invertebrate food resources. The resulting lack of sufficient access to food at stopover habitats may cause migrants to extend migration and have cascading effects throughout their life cycle. If the heterogeneous nature of climate change results in uneven changes in phenology between migrants and their prey, it may threaten the long-term viability of migratory populations

An Analysis of the Interactions Between Weather and Land Use on Midwestern Gamebird Populations Using Historical Data: A Preliminary Report

Concern surrounding species’ abilities to cope with a changing climate and variable land use presents opportunities to look forward toward solutions while investigating historical trends to assess the interaction of land use and weather. Uncertainty surrounding population responses to increased severity and frequency of severe weather associated with climate change presents challenges for making informed management decisions for a suite of already declining bird populations, including huntable populations of socially and economically important game birds, such as northern bobwhite (Colinus virginianus). Historical data are a rich resource for developing a priori hypotheses and models predicting species’ responses to climate change and continued variation in land use. We are utilizing 30 years of historical data to model the responses of northern, ring-necked pheasant (Phasianus colchicus), and wild turkey (Meleagris gallopavo) to land use change and weather within a gradient of land use and climate in Nebraska, Kansas, Iowa, and Missouri. Mixed models incorporating agricultural acreages, relative abundances of gallinaceous birds from the annual Breeding Bird Survey, and historical precipitation and temperature data built at the county-level will illuminate broad scale trends and enable us to draw conclusions about future population responses. We are finding expected differences in population trends between states within a climatic gradient, and varied responses to temperature and precipitation among gallinaceous species, where different annual periods are more or less crucial for different species despite similar life history characteristics. We expect that further modeling will continue to elucidate critical thresholds for birds in the Great Plains in terms of weather and habitat, allowing us to make strong recommendations to managers preparing to deal with the implications of climate change

Landscape Context Influences Nest Survival in a Midwest Grassland

Although the management and restoration of habitat is the key method to conserve species of interest, local habitat management often fails to elicit desired responses in populations. Landscape features beyond the local habitat scale affect the population dynamics of ring-necked pheasants (Phasianus colchicus), but the mechanism behind this response is unknown. One possibility is that nest survival, which is primarily reduced by nest predation, is regulating pheasant responses to the landscape. We investigated the extent to which land use affected nest survival by studying 202 artificial nests on 12 Conservation Reserve Program (CRP) fields in Nebraska, USA with varying surrounding land-use practices. After running a hierarchical analysis of competing models, we found that predicted nest survival increased as the amount of CRP, winter wheat, and pastureland surrounding a CRP field increased, whereas increasing fallow fields was correlated with decreased nest success. Our findings support theoretical and empirical evidence that nest predation rates are shaped by predator search efficacy. Changing the relative availability of nesting habitat that potentially holds alternative prey sources in our study affected nest survival rates, possibly by altering the search area of opportunistic nest predators. The similarities between the landscape relationships that predict nest survival and landscape predictors of pheasant abundance indicate that nest survival may potentially act as the mechanism shaping population dynamics within an ever changing farmland ecosystem. We recommend that managers consider the land use surrounding areas under consideration for habitat improvement to enhance conservation investments

Ecological neighborhoods as a framework for umbrella species selection

Umbrella species are typically chosen because they are expected to confer protection for other species assumed to have similar ecological requirements. Despite its popularity and substantial history, the value of the umbrella species concept has come into question because umbrella species chosen using heuristic methods, such as body or home range size, are not acting as adequate proxies for the metrics of interest: species richness or population abundance in a multi-species community for which protection is sought. How species associate with habitat across ecological scales has important implications for understanding population size and species richness, and therefore may be a better proxy for choosing an umbrella species. We determined the spatial scales of ecological neighborhoods important for predicting abundance of 8 potential umbrella species breeding in Nebraska using Bayesian latent indicator scale selection in N-mixture models accounting for imperfect detection. We compare the conservation value measured as collective avian abundance under different umbrella species selected following commonly used criteria and selected based on identifying spatial land cover characteristics within ecological neighborhoods that maximize collective abundance. Using traditional criteria to select an umbrella species resulted in sub-maximal expected collective abundance in 86% of cases compared to selecting an umbrella species based on land cover characteristics that maximized collective abundance directly. We conclude that directly assessing the expected quantitative outcomes, rather than ecological proxies, is likely the most efficient method to maximize the potential for conservation success under the umbrella species concept

Landscape Context Influences Nest Survival in a Midwest Grassland

Although the management and restoration of habitat is the key method to conserve species of interest, local habitat management often fails to elicit desired responses in populations. Landscape features beyond the local habitat scale affect the population dynamics of ring-necked pheasants (Phasianus colchicus), but the mechanism behind this response is unknown. One possibility is that nest survival, which is primarily reduced by nest predation, is regulating pheasant responses to the landscape. We investigated the extent to which land use affected nest survival by studying 202 artificial nests on 12 Conservation Reserve Program (CRP) fields in Nebraska, USA with varying surrounding land-use practices. After running a hierarchical analysis of competing models, we found that predicted nest survival increased as the amount of CRP, winter wheat, and pastureland surrounding a CRP field increased, whereas increasing fallow fields was correlated with decreased nest success. Our findings support theoretical and empirical evidence that nest predation rates are shaped by predator search efficacy. Changing the relative availability of nesting habitat that potentially holds alternative prey sources in our study affected nest survival rates, possibly by altering the search area of opportunistic nest predators. The similarities between the landscape relationships that predict nest survival and landscape predictors of pheasant abundance indicate that nest survival may potentially act as the mechanism shaping population dynamics within an ever changing farmland ecosystem. We recommend that managers consider the land use surrounding areas under consideration for habitat improvement to enhance conservation investments

Patch Size and Nest Density Influence Nest Survival

Nest predation is the primary cause of avian nest failure and therefore an important driver of avian population growth. Studies indicate that landscape context plays an important role in nest success, and although this is widely attributed to changes in nest predator communities, landscape context also influences nest density which affects predator search area and effort. Much debate remains as to whether specifically the size of a habitat patch or the density of nests has the greatest effect on nest predation rates. We explored the interactions between landscape context, predator efficiency, and nest survival. Northern bobwhite quail (Colinus virginianus) possess specific habitat requirements within a small home range and are a short-lived species that relies upon high reproductive performance, which make them the ideal system to test the extent to which landscape context affects nest predation rates. We investigated the extent to which the size of a grassland patch versus nest density affects nest survival by studying the predation rates of 617 artificial nests during two 23 day trials on 12 study sites in south central Nebraska. To examine the effects of patch size, we selected 6 study sites that were small patches of grassland (including pastures and Conservation Reserve Program fields) ranging in size from 40-60 ha and 6 study sites that were approximately 50 ha sections of larger contiguous grasslands. A high density of artificial nests were placed on half of the small and large patch study sites with the remaining sites having a low density of nests, for the second trial the nest density treatments were switched for each site

Leaps, Chains, and Climate Change for Western Migratory Songbirds*

Climate change has increased worldwide temperatures, affected seasonal patterns, and altered important sources of natural selection. To manage wildlife populations successfully, we must understand how patterns and processes of climate change alter trade-offs between sources of selection to predict how individuals may respond, populations may evolve, and management actions may ameliorate the costs of changing climates. Here we discuss how the migratory patterns of leapfrog and chain migration facilitate or constrain responses by migratory songbirds to spatial and temporal variation in climate change across western North America. Based on 52 years of climate data, we show that changes in average minimum monthly temperature differ significantly between the spring migration zone in the desert Southwest and breeding locations throughout western North America, and that these differences are most extreme for populations breeding at low latitudes (37°–49°) and exacerbated for species exhibiting leapfrog migration. Given the importance of climate in the evolution of migratory behaviors, such extreme alterations in the geographical patterns of climate may ultimately threaten the long-term population viability of species dependent on low latitudes for breeding or exhibiting leapfrog migration

A Bayesian method for assessing multi-scale species-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multiscale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships

Biodiversity Scale-Dependence and Opposing Multi-level Correlations Underlie Differences among Taxonomic, Phylogenetic and Functional Diversity

Aim: Biodiversity is a multidimensional property of biological communities that represents different information depending on how it is measured, but how dimensions relate to one another and under what conditions is not well understood. We explore how taxonomic, phylogenetic, and functional diversity can differ in scale-of-effect dependence and habitat-biodiversity relationships, and subsequently how spatial differences among biodiversity dimensions may arise. Location: Nebraska, United States. Taxon: Birds. Methods: Across 2016 and 2017, we conducted 2,641 point counts at 781 sites. We modeled the occupancy of 141 species using Bayesian Bernoulli-Bernoulli hierarchical logistic regressions. We calculated species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) for each site and year based on predicted occupancy, accounting for imperfect detection. Using Bayesian latent indicator scale selection and multivariate modeling, we quantified the spatial scales-of-effect that best explained the relationships between environmental characteristics and SR, PD, and FD. Additionally, we decomposed the residual between-site and within-site biodiversity correlations using our repeated measures design. Results: Although relationships between specific land cover types and SR, PD, and FD were qualitatively similar, the spatial scales at which these variables were important in explaining biodiversity differed among dimensions. Between-site residual biodiversity correlations were negative, yet within-site biodiversity residual correlations were positive. Main conclusions: Our results demonstrate how spatial differences among biodiversity dimensions may arise from biodiversity-specific scale-dependent habitat relationships, low shared environmental correlations, and opposing residual correlations between dimensions, suggesting that single-scale and single-dimension analyses are not entirely appropriate for quantifying habitat-biodiversity relationships. After accounting for shared habitat relationships, we found positive within-site residual correlations between SR, PD, and FD, suggesting that habitat change over time influenced all biodiversity dimensions similarly. However, negative between-site residual correlation among biodiversity dimensions may indicate trade-offs in achieving maximum biodiversity across multiple biodiversity dimensions at any given location