Search

Grassland birds have exhibited dramatic and widespread declines since the mid‐20th century. Greater prairie chickens (Tympanuchus cupido pinnatus) are considered an umbrella species for grassland conservation and are frequent targets of management, but their responses to land use and management can be quite variable. We used data collected during 2007–2009 and 2014–2015 to investigate effects of land use and grassland management practices on habitat selection and survival rates of greater prairie chickens in central Wisconsin, USA. We examined habitat, nest‐site, and brood‐rearing site selection by hens and modeled effects of land cover and management on survival rates of hens, nests, and broods. Prairie chickens consistently selected grassland over other cover types, but selection or avoidance of management practices varied among life‐history stages. Hen, nest, and brood survival rates were influenced by different land cover types and management practices. At the landscape scale, hens selected areas where brush and trees had been removed during the previous year, which increased hen survival. Hens selected nest sites in hay fields and brood‐rearing sites in burned areas, but prescribed fire had a negative influence on hen survival. Brood survival rates were positively associated with grazing and were highest when home ranges contained ≈15%–20% shrub/tree cover. The effects of landscape composition on nest survival were ambiguous. Collectively, our results highlight the importance of evaluating responses to management efforts across a range of life‐history stages and suggest that a variety of management practices are likely necessary to provide structurally heterogeneous, high‐quality habitat for greater prairie chickens. Brush and tree removal, grazing, hay cultivation, and prescribed fire may be especially beneficial for prairie chickens in central Wisconsin, but trade‐offs among life‐history stages and the timing of management practices must be considered carefully., Greater prairie chickens (Tympanuchus cupido pinnatus) are considered an umbrella species for grassland conservation and are frequent targets of management, but their responses to land use and management can be quite variable. We examined habitat, nest‐site, and brood‐rearing site selection by hens and modeled effects of land cover and management on hen, nest, and brood survival. Collectively, our results highlight the importance of evaluating responses to management efforts across a range of life‐history stages and suggest that a variety of management practices are likely necessary to provide structurally heterogeneous, high‐quality habitat for greater prairie chickens.

Climate change and habitat loss pose the greatest contemporary threats to biodiversity, but their impacts on populations largely vary across species. These differential responses could be caused by complex interactions between landscape and climate change and species-specific sensitivities. Understanding the factors that determine which species are most vulnerable to the synergistic effects of climate change and habitat loss is a high conservation priority. Here, we ask (a) whether and to what extent land cover moderates the impacts of winter weather on population dynamics of wintering birds, and (b) what role species' physiology might play in modifying their responses to changing weather conditions. To address these questions, we used thousands of observations collected by citizen scientists participating in Project FeederWatch to build dynamic occupancy models for 14 species of wintering birds. Populations of wintering birds were more dynamic, having higher rates of local extinction and colonization, in more forested landscapes during extreme cold-presumably enabling them to better track resources. However, urban areas appeared to provide refuge for some species, as demonstrated by increased local colonization during the harshest winter weather. Lastly, we found that species-specific differences in thermal tolerances strongly influenced occupancy dynamics such that species that are less cold-tolerant were more likely to go locally extinct at colder sites and during colder periods throughout winter. Together, our results suggest that species that are less cold-tolerant and populations occupying less forested landscapes are most vulnerable to extreme winter weather.

Winter climate warming is rapidly leading to changes in snow depth and soil temperatures across mid- and high-latitude ecosystems, with important implications for survival and distribution of species that overwinter beneath the snow. Amphibians are a particularly vulnerable group to winter climate change because of the tight coupling between their body temperature and metabolic rate. Here, we used a mechanistic microclimate model coupled to an animal biophysics model to predict the spatially explicit effects of future climate change on the wintering energetics of a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus), across its distributional range in the eastern United States. Our below-the-snow microclimate simulations were driven by dynamically downscaled climate projections from a regional climate model coupled to a one-dimensional model of the Laurentian Great Lakes. We found that warming soil temperatures and decreasing winter length have opposing effects on Wood Frog winter energy requirements, leading to geographically heterogeneous implications for Wood Frogs. While energy expenditures and peak body ice content were predicted to decline in Wood Frogs across most of our study region, we identified an area of heightened energetic risk in the northwestern part of the Great Lakes region where energy requirements were predicted to increase. Because Wood Frogs rely on body stores acquired in fall to fuel winter survival and spring breeding, increased winter energy requirements have the potential to impact local survival and reproduction. Given the geographically variable and intertwined drivers of future under-snow conditions (e.g., declining snow depths, rising air temperatures, shortening winters), spatially explicit assessments of species energetics and risk will be important to understanding the vulnerability of subnivium-adapted species.

Ecological processes, such as migration and phenology, are strongly influenced by climate variability. Studying these processes often relies on associating observations of animals and plants with climate indices, such as the El Niño-Southern Oscillation (ENSO). A common characteristic of climate indices is the simultaneous emergence of opposite extremes of temperature and precipitation across continental scales, known as climate dipoles. The role of climate dipoles in shaping ecological and evolutionary processes has been largely overlooked. We review emerging evidence that climate dipoles can entrain species dynamics and offer a framework for identifying ecological dipoles using broad-scale biological data. Given future changes in climatic and atmospheric processes, climate and ecological dipoles are likely to shift in their intensity, distribution, and timing.

The recovery of piscivorous birds around the world is touted as one of the great conservation successes of the 21st century, but for some species, this success was short-lived. Bald eagles, ospreys and great blue herons began repatriating Voyageurs National Park, USA, in the mid-20th century. However, after 1990, only eagles continued their recovery, while osprey and heron recovery failed for unknown reasons. We aimed to evaluate whether top-down effects of bald eagles and bottom-up effects of inclement weather, habitat quality and fish resources contributed to the failed recovery of ospreys and herons in a protected area. We quantified the relative influence of top-down and bottom-up factors on nest colonization, persistence (i.e., nest reuse) and success for ospreys, and occurrence and size of heronries using 26 years (1986-2012) of spatially explicit monitoring data coupled with multi-response hierarchical models and Bayesian variable selection approaches. Bald eagles were previously shown to recover faster due to intensive nest protection and management. Increased numbers of eagles were associated with a reduction in the numbers of osprey nests, their nesting success and heronry size, while higher local densities of nesting eagles deterred heronries nearby. We found little evidence of bottom-up limitations on the failed recovery of herons and ospreys. We present a conservation conundrum: bald eagles are top predators and a flagship species of conservation that have benefited from intensive protection, but this likely hindered the recovery of ospreys and herons. Returning top predators, or rewilding, is widely promoted as a conservation strategy for top-down ecosystem recovery, but managing top predators in isolation of jointly recovering species can halt or reverse ecosystem recovery. Previous studies warn of the potential consequences of ignoring biotic interactions amongst recovering species, but we go further by quantifying how these interactions contributed to failed recoveries via impacts on the nesting demography of jointly recovering species. Multi-species management is paramount to realizing the ecosystem benefits of top predator recovery.

Detection/non-detection data are widely collected by ecologists interested in estimating species distributions, abundances, and phenology, and are often subject to imperfect detection. Recent model development has focused on accounting for both false positive and false negative errors given evidence that misclassification is common across many sampling protocols. To date, however, model-based solutions to false positive error have largely addressed occupancy estimation. We describe a generalized model structure that allows investigators to account for false positive error in detection/non-detection data across a broad range of ecological parameters and model classes, and demonstrate that previously developed model-based solutions are special cases of the generalized model. Simulation results demonstrate that estimators for abundance and migratory arrival time ignoring false positive error exhibit severe (20-70%) relative bias even when only 5-10% of detections are false positives. Bias increased when false positive detections were more likely to occur at sites or within occasions in which true positive detections were unlikely to occur. Models accounting for false positive error following the site confirmation or observation confirmation designs generally reduced bias substantially, even when few detections were confirmed as true or false positives or when the process model for false positive error was misspecified. Results from an empirical example focusing on gray fox (Urocyon cinereoargenteus) in Wisconsin, USA reinforce concerns that biases induced by false positive error can also distort spatial predictions often used to guide decision-making. Model sensitivity to false positive error extends well beyond occupancy estimation, but encouragingly, model-based solutions developed for occupancy estimators are generalizable and effective across a range of models widely used in ecological research.

Recent advancements in information technology and data acquisition have created both new research opportunities and new challenges for using big data in ornithology. We provide an overview of the past, present, and future of big data in ornithology, and explore the rewards and risks associated with their application. Structured data resources (e.g., North American Breeding Bird Survey) continue to play an important role in advancing our understanding of bird population ecology, and the recent advent of semistructured (e.g., eBird) and unstructured (e.g., weather surveillance radar) big data resources has promoted the development of new empirical perspectives that are generating novel insights. For example, big data have been used to study and model bird diversity and distributions across space and time, explore the patterns and determinants of broad-scale migration strategies, and examine the dynamics and mechanisms associated with geographic and phenological responses to global change. The appli...

Grassland birds are declining faster than any other bird guild across North America. Shrinking ranges and population declines are attributed to widespread habitat loss and increasingly fragmented landscapes of agriculture and other land uses that are misaligned with grassland bird conservation. Concurrent with habitat loss and degradation, temperate grasslands have been disproportionally affected by climate change relative to most other terrestrial biomes. Distributions of grassland birds often correlate with gradients in climate, but few researchers have explored the consequences of weather on the demography of grassland birds inhabiting a range of grassland fragments. To do so, we modeled the effects of temperature and precipitation on nesting success rates of 12 grassland bird species inhabiting a range of grassland patches across North America (21,000 nests from 81 individual studies). Higher amounts of precipitation in the preceding year were associated with higher nesting success, but wetter conditions during the active breeding season reduced nesting success. Extremely cold or hot conditions during the early breeding season were associated with lower rates of nesting success. The direct and indirect influence of temperature and precipitation on nesting success was moderated by grassland patch size. The positive effects of precipitation in the preceding year on nesting success were strongest in relatively small grassland patches and had little effect in large patches. Conversely, warm temperatures reduced nesting success in small grassland patches but increased nesting success in large patches. Mechanisms underlying these differences may be patch-size-induced variation in microclimates and predator activity. Although the exact cause is unclear, large grassland patches, the most common metric of grassland conservation, appears to moderate the effects of weather on grassland-bird demography and could be an effective component of climate-change adaptation.

In regions where snowfall historically has been a defining seasonal characteristic of the landscape, warming winters have reduced the depth, duration, and extent of snowpack. However, most management and conservation has focused on how aboveground wildlife will be affected by altered snow conditions, even though the majority of species that persist through the winter do so under the snowpack in a thermally stable refugium: the subnivium. Shortened winters, forest management practices, and winter recreation can alter subnivium conditions by increasing snow compaction and compromising thermal stability at the soil-snow interface. To help slow the loss of the subnivium in the face of rapidly changing winter conditions, we suggest managers adopt regional conservation plans for identifying threatened snow-covered environments; measure and predict the effects land cover and habitat management has on local subnivium conditions; and control the timing and distribution of activities that disturb and compact snow cover (e.g., silvicultural practices, snow recreation, and road and trail maintenance). As a case study, we developed a spatially explicit model of subnivium presence in a working landscape of the Chequamegon National Forest, Wisconsin. We identified landscapes where winter recreation and management practices could threaten potentially important areas for subnivium persistence. Similar modeling approaches could inform management decisions related to subnivium conservation. Current climate projections predict that snow seasons will change rapidly in many regions, and as result, we advocate for the immediate recognition, conservation, and management of the subnivium and its dependent species.

Allen's rule predicts that homeotherms inhabiting cooler climates will have smaller appendages, while those inhabiting warmer climates will have larger appendages relative to body size. Birds’ bills tend to be larger at lower latitudes, but few studies have tested whether modern climate change and urbanization affect bill size. Our study explored whether bill size in a wide‐ranging bird would be larger in warmer, drier regions and increase with rising temperatures. Furthermore, we predicted that bill size would be larger in densely populated areas, due to urban heat island effects and the higher concentration of supplementary foods. Using measurements from 605 museum specimens, we explored the effects of climate and housing density on northern cardinal bill size over an 85‐year period across the Linnaean subspecies’ range. We quantified the geographic relationships between bill surface area, housing density, and minimum temperature using linear mixed effect models and geographically weighted regression. We then tested whether bill surface area changed due to housing density and temperature in three subregions (Chicago, IL., Washington, D.C., and Ithaca, NY). Across North America, cardinals occupying drier regions had larger bills, a pattern strongest in males. This relationship was mediated by temperature such that birds in warm, dry areas had larger bills than those in cool, dry areas. Over time, female cardinals’ bill size increased with warming temperatures in Washington, D.C., and Ithaca. Bill size was smaller in developed areas of Chicago, but larger in Washington, D.C., while there was no pattern in Ithaca, NY. We found that climate and urbanization were strongly associated with bill size for a wide‐ranging bird. These biogeographic relationships were characterized by sex‐specific differences, varying relationships with housing density, and geographic variability. It is likely that anthropogenic pressures will continue to influence species, potentially promoting microevolutionary changes over space and time.

Temperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts. The goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability. We conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model. We uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction. Future distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.

Extreme weather, including heat waves, droughts, and high rainfall, is becoming more common and affecting a diversity of species and taxa. However, researchers lack a framework that can anticipate how diverse species will respond to weather extremes spanning weeks to months. Here we used high-resolution occurrence data from eBird, a global citizen science initiative, and dynamic species distribution models to examine how 109 North American bird species ranging in migration distance, diet, body size, habitat preference, and prevalence (commonness) respond to extreme heat, drought, and rainfall across a wide range of temporal scales. Across species, temperature influenced species' distributions more than precipitation at weekly and monthly scales, while precipitation was more important at seasonal scales. Phylogenetically controlled multivariate models revealed that migration distance was the most important factor mediating responses to extremely hot or dry weeks; residents and short-distance migrants occurred less often following extreme heat. At monthly or seasonal scales, less common birds experienced decreases in occurrence following drought-like conditions, while widespread species were unaffected. Spatial predictions demonstrated variation in responses to extreme weather across species' ranges, with predicted decreases in occurrence up to 40% in parts of ranges. Our results highlight that extreme weather has variable and potentially strong implications for birds at different time scales, but these responses are mediated by life-history characteristics. As weather once considered extreme occurs more frequently, researchers and managers require a better understanding of how diverse species respond to extreme conditions.

The rapid improvement of camera traps in recent decades has revolutionized biodiversity monitoring. Despite clear applications in conservation science, camera traps have seldom been used to model the abundance of unmarked animal populations. We sought to summarize the challenges facing abundance estimation of unmarked animals, compile an overview of existing analytical frameworks, and provide guidance for practitioners seeking a suitable method. When a camera records multiple detections of an unmarked animal, one cannot determine whether the images represent multiple mobile individuals or a single individual repeatedly entering the camera viewshed. Furthermore, animal movement obfuscates a clear definition of the sampling area and, as a result, the area to which an abundance estimate corresponds. Recognizing these challenges, we identified 6 analytical approaches and reviewed 927 camera-trap studies published from 2014 to 2019 to assess the use and prevalence of each method. Only about 5% of the studies used any of the abundance-estimation methods we identified. Most of these studies estimated local abundance or covariate relationships rather than predicting abundance or density over broader areas. Next, for each analytical approach, we compiled the data requirements, assumptions, advantages, and disadvantages to help practitioners navigate the landscape of abundance estimation methods. When seeking an appropriate method, practitioners should evaluate the life history of the focal taxa, carefully define the area of the sampling frame, and consider what types of data collection are possible. The challenge of estimating abundance of unmarked animal populations persists; although multiple methods exist, no one method is optimal for camera-trap data under all circumstances. As analytical frameworks continue to evolve and abundance estimation of unmarked animals becomes increasingly common, camera traps will become even more important for informing conservation decision-making.Estimación de la Abundancia de Animales No Marcados con Base en Datos de Cámaras Trampa Resumen La rápida mejoría de las cámaras trampa en las décadas recientes ha revolucionado el monitoreo de la biodiversidad. A pesar de su clara aplicación en las ciencias de la conservación, las cámaras trampa han sido utilizadas pocas veces para modelar la abundancia de las poblaciones de animales no marcados. Buscamos resumir los retos que enfrenta la estimación de la abundancia de animales no marcados, compilar una perspectiva general de los marcos analíticos de trabajo existentes y proporcionar una guía para aquellos practicantes que buscan un método adecuado. Cuando una cámara registra múltiples detecciones de animales no marcados, no se puede determinar si las imágenes representan a diferentes individuos en movimiento o a un solo individuo que entra repetidamente a la zona de visión de la cámara. Sumado a esto, el movimiento animal ofusca una definición clara del área de muestreo y, como resultado, del área a la cual corresponde un estimado de abundancia. Después de reconocer estos retos, identificamos seis estrategias analíticas y revisamos 927 estudios con cámaras trampa publicados entre 2014 y 2019 para evaluar el uso y la prevalencia de cada método. Solamente en el 5% de los estudios se usó cualquiera de los métodos de estimación de abundancia que identificamos. La mayoría de estos estudios estimaron la abundancia local o las relaciones de covarianza en lugar de predecir la abundancia o la densidad a lo largo de áreas más amplias. Después, para cada estrategia analítica, recopilamos los requerimientos de datos, suposiciones, ventajas y desventajas para ayudar a los practicantes a navegar el paisaje de los métodos de estimación de abundancia. Cuando los practicantes busquen un método apropiado deberán evaluar la historia de vida del taxón focal, definir cuidadosamente el área del marco de muestreo y considerar cuáles tipos de recolección de datos son posibles. El reto de estimar la abundancia de poblaciones de animales no marcados persiste; aunque existan muchos métodos, no hay método único óptimo para los datos de las cámaras trampa que cumpla con todas las circunstancias. Mientras los marcos analíticos de trabajo sigan evolucionando y la estimación de la abundancia de animales no marcados sea cada vez más común, las cámaras trampa serán todavía más importantes para informar la toma de decisiones de conservación.近几十年来红外相机陷阱技术的快速发展已经彻底改变了生物多样性监测的现状。尽管红外相机陷阱法在动物保护科学中有明确的应用, 但它很少被用来模拟无标记动物的种群数量。本研究旨在总结无标记动物的丰度估计所面临的挑战, 总结现有的分析框架并为寻求合适方法的实践者提供指导意见。当红外相机多次记录到无标记的动物时, 人们无法确定这些图像代表的是多个个体还是一个重复进入相机拍摄范围的个体。此外, 动物的运动导致不能清晰地划定采样区域, 因此也模糊了所对应区域的丰度估计。面对这些挑战, 我们确定了六种分析方法, 并综述了 2014 年至 2019 年发表的 927 项红外相机陷阱研究, 以评估每种方法的使用情况和流行程度。结果发现, 只有约 5% 的研究使用了至少一种我们确定的丰度估计方法。这些研究大多是估计局部丰度或协变量关系, 而不是预测更大范围内的动物丰度或密度。接下来, 我们总结了每种分析方法的数据需求、假设、优点和缺点, 以帮助实践者了解丰度估计方法的总体情况。实践者在寻找合适的方法时, 应评估研究所关注类群的生活史, 谨慎地确定采样范围, 并考虑可能收集到的数据类型。无标记动物的种群数量估计仍面临挑战, 虽然已存在多种方法, 但没有一种方法对于所有红外相机陷阱数据都是最优的。随着分析框架的不断发展和对无标记动物数量估计变得越来越普遍, 红外相机陷阱法在为指导保护决策中也将更加重要。【翻译: 胡怡思; 审校: 聂永刚】.

Wildlife managers need reliable information on species distributions (i.e. patterns of occurrence and abundance) to make effective decisions. Historically, managers have relied on harvest records (collected at broad spatial extents but coarse resolution) to monitor wildlife populations. However, emerging citizen-science datastreams can potentially supplement harvest-based monitoring by providing fine-resolution data that permit identification of species-environment relationships needed to predict occurrence and abundance. We combined harvest records and citizen-science camera-trap data in integrated species distribution models (iSDMs) to estimate species-environment relationships and distribution patterns of six wildlife species in Wisconsin, USA. We expected that iSDMs would more precisely estimate species-environment relationships and predict spatial abundance patterns intermediate between camera- and harvest-only SDMs. We also conducted simulations to explore the consequences of incomplete knowledge of harvest effort for estimates of abundance and species-environment relationships. Integrated models produced more precise species-environment relationships than camera-only models in 53% of the relationships we tested; all harvest-only models failed to converge. Moreover, integrated and camera-only models showed low agreement (mean: 19.67%) in identifying abundance “hotspots” but considerably higher agreement (mean: 45.17%) in identifying abundance “cold spots”. Our simulations showed that abundance patterns estimated by iSDMs may suffer from imprecision if harvest effort is poorly measured. We recommend that harvest records be collected at finer spatial resolutions and be paired with in-depth effort reporting. Our work demonstrates the potential for integrating an existing datastream (harvest records) with an emerging one (citizen-science camera-trap monitoring) for modeling species distributions and providing support for wildlife management decisions.

With over half of earth's terrestrial biota living beneath forest canopies, our ability to accurately capture organism–climate relationships in forested ecosystems is imperative for predicting species' vulnerability to future climate change. Assessing the vulnerability of forest dependent species, however, hinges on quantifying microclimates that exist below the forest canopy and might be influenced by varying levels of disturbance in human-modified landscapes. The goal of our study was to examine the multi-scaled predictors of subcanopy microclimate variability across a heterogeneous landscape in Midwestern USA during winter, and to further evaluate whether a widely available interpolated climate model accurately captures this variability. By deploying a network of temperature sensors along a fragmentation gradient, we found that forests in more fragmented landscapes with greater amounts of forest edge and increasing distances between forest patches, experienced colder minimum and average daily temperatures throughout the winter than forests in less fragmented landscapes. We found that greater tree densities and higher elevations led to warmer microclimates while increasing distances from urban centers led to colder microclimates. The negative effect of forest edge on minimum temperatures was lessened by the effect of increasing basal area, highlighting the importance of local- and landscape-scale features on microclimate heterogeneity. Temperature discrepancies between subcanopy microclimates and climate interpolations were influenced by many of the same features, and could be of a similar magnitude as those predicted by future climate change scenarios. Using a biological threshold based on metabolic and demographic constraints for winter birds, we found that the variability in microclimates along our forest fragmentation gradient (50 km) was comparable to the magnitude captured by weather stations across a latitudinal gradient spanning more than 650 km. Our results suggest that biophysical properties of landscapes can alter spatial gradients of microclimates and should be considered when assessing species' vulnerabilities to future climate change.

Climate change is not occurring over a homogeneous landscape and the quantity and quality of available land cover will likely affect the way species respond to climate change. The influence of land cover on species’ responses to climate change, however, is likely to differ depending on habitat type and composition. Our goal was to investigate responses of forest and grassland breeding birds to over 20 years of climate change across varying gradients of forest and grassland habitat. Specifically, we investigated whether (i) increasing amounts of available land cover modify responses of forest and grassland-dependent birds to changing climate and (ii) the effect of increasing land cover amount differs for forest and grassland birds. We used Bayesian spatially-varying intercept models to evaluate species- and community-level responses of 30 forest and 10 grassland birds to climate change across varying amounts of their associated land cover types. Responses of forest birds to climate change were weak and constant across a gradient of forest cover. Conversely, grassland birds responded strongly to changing climatic conditions. Specifically, increasing temperatures led to higher probabilities of localized extinctions for grassland birds, and this effect was intensified in regions with low amounts of grassland cover. Within the context of northeastern forests and grasslands, we conclude that forests serve as a possible buffer to the impacts of climate change on birds. Conversely, species occupying open, fragmented grassland areas might be particularly at risk of a changing climate due to the diminished buffering capacity of these ecosystems.

Range boundaries are a manifestation of species' tolerances to environmental factors, including climate and human disturbance. As such, studying populations persisting along range boundaries can provide important insights into species' sensitivity to environmental change. Because multiple environmental influences may contribute to a range limit, studies focusing on range boundaries can guide management and conservation of these critical populations. To this end, we quantified the environmental factors associated with snowshoe hare (Lepus americanus) occurrence at their southern range limit in Wisconsin. We surveyed 199 locations across a regional southern range boundary of snowshoe hares and analyzed the data within an occupancy modeling framework to test the hypothesis that this range boundary results from an interaction between winter climate and land cover. We found that dense vegetation structure and increasing forest and snow cover duration had positive effects on snowshoe hare occupancy along their southern range boundary, supporting our prediction that a suite of abiotic factors is associated with the southerly distribution of this winter-adapted mammal. These effects were additive and we found limited support for climate–land cover interactions, forest composition, winter snow depth, or predator occurrence. Spatial predictions of occupancy using only forest and snow cover variables denote a sharp range boundary, further illustrating the importance of these variables in shaping this species distribution. Our results highlight an important vulnerability of snowshoe hares to future climate change, and options for mediating this vulnerability through the maintenance of early successional habitat and forested landscapes along their southern range boundary. © 2016 The Wildlife Society.

Changes in land use and climate are among the main drivers of range shifts for multiple species and taxa. While such distributional changes are often observed at broad scales, the processes driving them – colonization and extinction along range boundaries – occur at local scales. There is a need then, to identify whether these local drivers are consistent with patterns at broader scales. Snowshoe hares (Lepus americanus), an important prey species in northern forest ecosystems, have experienced range contraction along much of their southern boundary. Population declines are linked to climate change via camouflage mismatch, an inability to match seasonal coat color molts with declining snow cover duration. We used data from camera traps to monitor the spatial extent and habitat associations of hares before, during and after an experimental translocation, and multi-season occupancy models to model the effects of habitat and climate on colonization and extinction patterns. We compared our contemporary occupancy models to historical patterns of extirpation and simulated future effects of timber harvest on occupancy. Colonization by hares was strongly associated with distance from source population and patch size of aspen-alder. Historical patterns of extirpation were consistent with contemporary patterns, and simulations revealed that increased frequency and magnitude of aspen harvest increased hare occupancy by creating large patches of early-successional habitat. As global change alters ecological communities, identifying mechanisms that drive range-shifts and targeting landscape features that can be manipulated to buffer those effects can be used to promote the persistence of individual species and ecological communities.

Conservation for species impacted by climate change often occurs at scales impractical for local land managers. Snowshoe hares (Lepus americanus) are one of the most well‐documented species declining from climate change–specifically a reduction in snowcover–yet clear management strategies have yet to emerge. To test whether camouflage mismatch is reducing hare survival we translocated 96 hares to a site recently extirpated of snowshoe hares, and monitored coat color change, mismatch with snow, habitat use, and weekly survival in winter‐spring of 2017. Hare survival was low during periods of camouflage mismatch, and mismatched hares were 3.2 × less likely to survive, but this pattern varied by habitat. We found that aspen‐alder stands >5 hectares negated the mortality costs of mismatch. We provide experimental evidence that mismatch is driving the range contraction of snowshoe hares, and identify specific habitats to buffer the consequences of climate change on this declining winter specialist.

Urbanization causes the simplification of natural habitats, resulting in animal communities dominated by exotic species with few top predators. In recent years, however, many predators such as hawks, and in the US coyotes and cougars, have become increasingly common in urban environments. Hawks in the Accipiter genus, especially, are recovering from widespread population declines and are increasingly common in urbanizing landscapes. Our goal was to identify factors that determine the occupancy, colonization and persistence of Accipiter hawks in a major metropolitan area. Through a novel combination of citizen science and advanced remote sensing, we quantified how urban features facilitate the dynamics and long-term establishment of Accipiter hawks. Based on data from Project FeederWatch, we quantified 21 years (1996–2016) of changes in the spatio-temporal dynamics of Accipiter hawks in Chicago, IL, USA. Using a multi-season occupancy model, we estimated Cooper's ( Accipiter cooperii ) and sharp-shinned ( A. striatus ) hawk occupancy dynamics as a function of tree canopy cover, impervious surface cover and prey availability. In the late 1990s, hawks occupied 26% of sites around Chicago, but after two decades, their occupancy fluctuated close to 67% of sites and they colonized increasingly urbanized areas. Once established, hawks persisted in areas with high levels of impervious surfaces as long as those areas supported high abundances of prey birds. Urban areas represent increasingly habitable environments for recovering predators, and understanding the precise urban features that drive colonization and persistence is important for wildlife conservation in an urbanizing world.

Animals in temperate northern regions employ a variety of strategies to cope with the energetic demands of winter. Behavioral plasticity may be important, as winter weather conditions are increasingly variable as a result of modern climate change. If behavioral strategies for thermoregulation are no longer effective in a changing environment, animals may experience physiological stress, which can have fitness consequences. We monitored winter roosting behavior of radio–tagged ruffed grouse (Bonasa umbellus), recorded snow depth and temperature, and assayed droppings for fecal corticosterone metabolites (FCM). Grouse FCM levels increased with declining temperatures. FCM levels were high when snow was shallow, but decreased rapidly as snow depth increased beyond 20 cm. When grouse used snow burrows, there was no effect of temperature on FCM levels. Snow burrowing is an important strategy that appears to allow grouse to mediate the possibly stressful effects of cold temperatures. This is one of the first studies to explore how variable winter weather conditions influence stress in a free–living cold–adapted vertebrate and its ability to mediate this relationship behaviorally. Animals that depend on the snowpack as a winter refuge will likely experience increased stress and possible fitness costs resulting from the loss of snow cover due to climate change.

Measurement or observation error is common in ecological data: as citizen scientists and automated algorithms play larger roles processing growing volumes of data to address problems at large scales, concerns about data quality and strategies for improving it have received greater focus. However, practical guidance pertaining to fundamental data quality questions for data users or managers-how accurate do data need to be and what is the best or most efficient way to improve it?-remains limited. We present a generalizable framework for evaluating data quality and identifying remediation practices, and demonstrate the framework using trail camera images classified using crowdsourcing to determine acceptable rates of misclassification and identify optimal remediation strategies for analysis using occupancy models. We used expert validation to estimate baseline classification accuracy and simulation to determine the sensitivity of two occupancy estimators (standard and false-positive extensions) to different empirical misclassification rates. We used regression techniques to identify important predictors of misclassification and prioritize remediation strategies. More than 93% of images were accurately classified, but simulation results suggested that most species were not identified accurately enough to permit distribution estimation at our predefined threshold for accuracy (5% absolute bias). A model developed to screen incorrect classifications predicted misclassified images with97% accuracy: enough to meet our accuracy threshold. Occupancy models that accounted for false-positive error provided even more accurate inference even at high rates of misclassification (30%). As simulation suggested occupancy models were less sensitive to additional false-negative error, screening models or fitting occupancy models accounting for false-positive error emerged as efficient data remediation solutions. Combining simulation-based sensitivity analysis with empirical estimation of baseline error and its variability allows users and managers of potentially error-prone data to identify and fix problematic data more efficiently. It may be particularly helpful for "big data" efforts dependent upon citizen scientists or automated classification algorithms with many downstream users, but given the ubiquity of observation or measurement error, even conventional studies may benefit from focusing more attention upon data quality.

Establishing protected areas, where human activities and land cover changes are restricted, is among the most widely used strategies for biodiversity conservation. This practice is based on the assumption that protected areas buffer species from processes that drive extinction. However, protected areas can maintain biodiversity in the face of climate change and subsequent shifts in distributions have been questioned. We evaluated the degree to which protected areas influenced colonization and extinction patterns of 97 avian species over 20 years in the northeastern United States. We fitted single-visit dynamic occupancy models to data from Breeding Bird Atlases to quantify the magnitude of the effect of drivers of local colonization and extinction (e.g., climate, land cover, and amount of protected area) in heterogeneous landscapes that varied in the amount of area under protection. Colonization and extinction probabilities improved as the amount of protected area increased, but these effects were conditional on landscape context and species characteristics. In this forest-dominated region, benefits of additional land protection were greatest when both forest cover in a grid square and amount of protected area in neighboring grid squares were low. Effects did not vary with species' migratory habit or conservation status. Increasing the amounts of land protection benefitted the range margins species but not the core range species. The greatest improvements in colonization and extinction rates accrued for forest birds relative to open-habitat or generalist species. Overall, protected areas stemmed extinction more than they promoted colonization. Our results indicate that land protection remains a viable conservation strategy despite changing habitat and climate, as protected areas both reduce the risk of local extinction and facilitate movement into new areas. Our findings suggest conservation in the face of climate change favors creation of new protected areas over enlarging existing ones as the optimal strategy to reduce extinction and provide stepping stones for the greatest number of species.Valor de las Áreas Protegidas para la Persistencia de Aves a lo largo de 20 Años de Cambio Climático y Cambios en el Uso de Suelo Resumen El establecimiento de áreas protegidas, donde las actividades humanas y los cambios en la cobertura de suelo están restringidos, es una de las estrategias más utilizadas para la conservación de la biodiversidad. Esta práctica está basada en la suposición de que las áreas protegidas guarecen a las especies de los procesos que ocasionan la extinción. Sin embargo, se ha cuestionado si las áreas protegidas pueden mantener la biodiversidad de cara al cambio climático y los cambios subsecuentes en su distribución. Evaluamos el grado al cual las áreas protegidas influyeron sobre los patrones de colonización y extinción de 97 especies de aves durante 20 años en el noreste de los Estados Unidos. Ajustamos los modelos de ocupación dinámica de visita única a los datos de los Atlas de Aves Reproductoras para cuantificar la magnitud del efecto de los causantes de colonización y extinción local (p. ej.: clima, cobertura de suelo, tamaño del área protegida) en paisajes heterogéneos que variaron en cantidad de área bajo protección. Las probabilidades de colonización y extinción mejoraron conforme aumentó el tamaño del área protegida, pero estos efectos fueron condicionales con respecto al contexto del paisaje y a las características de la especie. En esta región dominada por bosques, los beneficios de una protección adicional del suelo fueron mayores cuando la cobertura de bosque en una cuadrícula y el tamaño del área protegida en una cuadrícula adyacente fueron bajos. Los efectos no variaron acorde a los hábitos migratorios o al estado de conservación de la especie. El aumento en la cantidad de suelo protegido benefició a las especies en los márgenes de su extensión pero no en la extensión nuclear de la especie. La mayores mejorías en la colonización y en las tasas de extinción se acumularon para las aves de bosque en relación con especies generalistas o de hábitat abierto. En general, las áreas protegidas frenaron la extinción más veces de las que promovieron la colonización. Nuestros resultados indican que la protección de suelo permanece como una estrategia viable de conservación a pesar del cambio que existe en los hábitats y en el clima ya que las áreas protegidas reducen el riesgo de extinción local y facilitan el movimiento hacia zonas nuevas. Nuestros hallazgos sugieren que la conservación de cara al cambio climático favorece la creación de nuevas áreas protegidas por encima del aumento de las ya existentes como la estrategia óptima para reducir la extinción y proporcionar escalones para el mayor número de especies.建立限制人类活动和土地覆盖变化的保护地是生物多样性保护最常用的策略之一。这一策略基于一种假设, 即保护地缓冲了导致物种灭绝的过程。然而, 在气候变化及其引起的物种分布变化的情况下, 保护地是否能维持生物多样性仍存在争议。我们评估了二十年来美国东北部的保护地对 97 种鸟类定殖和灭绝格局的影响情况。我们将单次调查的动态占有模型与繁殖鸟类图谱的数据进行拟合, 来定量受保护面积不同的异质性景观中, 导致局部定殖和灭绝的因素 (如气候、土地覆盖、保护地面积) 的影响程度。随着保护地面积增加, 定殖和灭绝的可能性也有所提高, 但这些影响可能取决于景观环境和物种特性。在以森林为主的研究区域内, 当一个网格的森林覆盖和周围网格的保护地面积都很小时, 增加土地保护带来的效益最高。另外, 物种受到的影响与其迁徙习性或保护现状无关。扩大土地保护面积有利于保护该区域边缘分布的物种, 而不是核心范围的物种。森林鸟种相比于开放生境或广生性的物种, 定殖率和灭绝率得到最大改善。总的来说, 保护地阻止灭绝的作用大于促进定殖。我们的研究结果显示, 尽管生境和气候在发生变化, 土地保护仍然是一个可行的保护策略, 因为保护地既能降低局部灭绝的风险, 又能促进物种迁入新区域。我们的发现还表明, 在气候变化面前, 设立新的保护地比扩大已有保护地更有利于保护, 是减少物种灭绝、为更多物种提供踏脚石的最佳策略。 【翻译: 胡怡思; 审校: 聂永刚】.

International audience; Global changes are modifying the structure of species assemblages, but the generality of resulting diversity patterns and of their drivers is poorly understood. Any such changes can be detected and explained by comparing temporal trends in taxonomic and functional diversity over broad spatial extents. In this study, we addressed three complementary questions: How did bird taxonomic and functional diversity change over the past 40 years in the conterminous United States? Are these trends non-linear? Can temporal variations in functional diversity be explained by broad-scale changes in climate and vegetation productivity? We quantified changes in taxonomic and functional diversity for 807 bird assemblages over the past four decades (1970-2011) considering a suite of 16 ecological traits for 435 species. We found increases in local bird species richness and taxonomic equitability that plateaued in the early 2000's while total abundance declined over the whole period. Functional richness, the total range of traits in an assemblage, increased due to the rising prevalence of species with atypical life-history strategies and under-represented habitat or trophic preferences. However, these species did not trigger major changes in the functional composition of bird assemblages. Inter-annual variations in climate and primary productivity explained the richness of bird life-history traits in local assemblages, suggesting that these traits are influenced by broad-scale environmental factors, while others respond more to more local drivers. Our results highlight that a comparative analysis of the multiple facets of functional diversity can raise novel insights on processes underlying temporal trends in biodiversity.

Emerging technologies make it increasingly straightforward for scientists to collect data that are fine in scale, broad in scope, and transparent with open access. However, the resulting datasets may contain sensitive information such as location information about endangered resources or private landowners. These tensions are particularly relevant for citizen science programs which engage the public in answering scientific questions. Citizen science programs are often promoted as being able to achieve multiple scientific (e.g. quality data and open sharing of data) and social goals (e.g. increased transparency and public trust), but likely tensions between these desired outcomes are less frequently discussed. We develop a conceptual framework for tensions in citizen science information and review the internal policies and practices currently used to navigate between data sharing and privacy protection. We also examine the case of Snapshot Wisconsin's wildlife camera traps on private land to understand how program managers balanced data production and sharing with protection of sensitive information and how citizen scientists perceived the project. We found that programs may be forced to make tradeoffs between data quality, privacy protection, resource security, transparency, and trust. In order to maximize conservation outcomes, we recommend that managers anticipate potential tradeoffs in advance of data collection, develop policies and practices to address these, and practice iterative evaluation that solicits feedback from participants.

Understanding and accurately modeling species distributions lies at the heart of many problems in ecology, evolution, and conservation. Multiple sources of data are increasingly available for modeling species distributions, such as data from citizen science programs, atlases, museums, and planned surveys. Yet reliably combining data sources can be challenging because data sources can vary considerably in their design, gradients covered, and potential sampling biases. We review, synthesize, and illustrate recent developments in combining multiple sources of data for species distribution modeling. We identify five ways in which multiple sources of data are typically combined for modeling species distributions. These approaches vary in their ability to accommodate sampling design, bias, and uncertainty when quantifying environmental relationships in species distribution models. Many of the challenges for combining data are solved through the prudent use of integrated species distribution models: models that simultaneously combine different data sources on species locations to quantify environmental relationships for explaining species distribution. We illustrate these approaches using planned survey data on 24 species of birds coupled with opportunistically collected eBird data in the southeastern United States. This example illustrates some of the benefits of data integration, such as increased precision in environmental relationships, greater predictive accuracy, and accounting for sample bias. Yet it also illustrates challenges of combining data sources with vastly different sampling methodologies and amounts of data. We provide one solution to this challenge through the use of weighted joint likelihoods. Weighted joint likelihoods provide a means to emphasize data sources based on different criteria (e.g., sample size), and we find that weighting improves predictions for all species considered. We conclude by providing practical guidance on combining multiple sources of data for modeling species distributions.

The effects of climate change on biodiversity have emerged as a dominant theme in conservation biology, possibly eclipsing concern over habitat loss in recent years. The extent to which this shifting focus has tracked the most eminent threats to biodiversity is not well documented. We investigated the mechanisms driving shifts in the southern range boundary of a forest and snow cover specialist, the snowshoe hare, to explore how its range boundary has responded to shifting rates of climate and land cover change over time. We found that although both forest and snow cover contributed to the historical range boundary, the current duration of snow cover best explains the most recent northward shift, while forest cover has declined in relative importance. In this respect, the southern range boundary of snowshoe hares has mirrored the focus of conservation research; first habitat loss and fragmentation was the stronger environmental constraint, but climate change has now become the main threat. Projections of future range shifts show that climate change, and associated snow cover loss, will continue to be the major driver of this species' range loss into the future.

The distributions of animal populations are not static. During regular migratory movements species exploit different habitats. This spatiotemporal variation needs to be accounted for when modeling a species’ distribution and is essential for developing conservation strategies for widespread species, and especially for migratory species. Attempts to design conservation landscapes across large regions based on models of distributions in a single season or a small region may not fully reflect the limiting factors that are driving population declines. Our goal is to predict and explore patterns of species’ occurrence and local habitat usage across broad landscapes. We use data from eBird (http://www.ebird.org), an online citizen science bird-monitoring project and environmental descriptions from continent-wide covariates linked through observation location and time. These covariates include remotely sensed habitat information from the National Land Cover Database and vegetation phenology from MODIS. We model species occurrence with the SpatioTemporal Exploratory Model (STEM), an ensemble model designed to adapt to non-stationary spatiotemporal processes. This is accomplished by creating a large ensemble of local models, each restricted to a local spatial and temporal region. Within each region a user specified predictive model associates the predictors with the response. Patterns modeled locally “scale up” via ensemble averaging to larger scales. Here we analyze eBird data to study broad-scale movements of bird populations throughout the year. We use STEM built with decision trees to adapt to a wide variety avian migration patterns without requiring a detailed understanding of the underlying dynamic local processes. We demonstrate how eBird data are capable of resolving the changing distributions of birds through their migrations. Then we illustrate how seasonal variation in habitat association can be identified and explored. These tools provide valuable information for generating hypotheses and making inference about the processes driving dynamic species distributional patterns.

The subnivium is a seasonal refuge that exists at the interface between the snowpack and the ground, and provides a haven for a diversity of species to survive extreme winter temperatures. Due to the fitness of many plants and animals being strongly influenced by winter conditions, much attention has been given to changes in the timing of snow cover extent and duration in seasonally snow-covered environments; however, these broad-scale characteristics do not capture the finer-scale dynamics of the subnivium. To study the factors associated with subnivium development, we quantified three critical phenophases of the subnivium: establishment, maintenance, and disintegration along a latitudinal and land cover gradient in the Great Lakes Region of North America. We hypothesized that subnivium phenophases would depend primarily on snow depth and air temperature, but that these would be mediated by latitude and land cover. We found that patterns in both establishment and disintegration were affected by latitude more than land cover, but that variability in the timing of early season snowfall events overrode the effects of both factors in subnivium establishment. In contrast, disintegration was predictably later in more northerly sites, regardless of interannual variation in weather patterns. We found that the subnivium was the result of a balance between ambient temperature, snow depth, and snow density, but that ambient temperatures constrained the system by contributing to the frequency of snowfall and inducing changes in snow depth and density. Areas in lake effect zones, characterized by high snow depths and persistent snow cover, may be the last refugia for subnivia-dependent species given the predicted shifting climate regimes of the 21st century.

Global climate warming is predicted to lead to global and regional changes in the distribution of organisms. One influential approach to test this prediction using temporally repeated mapping surveys of organisms was suggested in a seminal paper by Thomas & Lennon (1999, Nature). The Thomas & Lennon approach corrects observed changes in the range margin for changes in the range size, and thus potentially controls for other broad-scale environmental changes between surveys, however the approach does not necessarily account for potential biases in sampling effort. To verify whether the issue of variation in sampling effort affects empirical estimates of shifts in range margin, we reanalyzed all three published studies exploring range margin changes of breeding birds in Great Britain (GB), Finland, and New York State (NY). Accounting for changes in survey effort on range margins lowered the estimated shift for breeding birds in New York, but the shift remained statistically significant. For Great Britain and Finland, for which no direct estimate of survey effort is available, we used species richness (a strong correlate of survey effort in New York) as a proxy and found that in both cases the estimated shift in range margin was significantly reduced and became nonsignificant. To understand how robust the approach is to sampling biases, we use a simulation model to show that the Thomas & Lennon approach is, under certain conditions, sensitive to changes in detection probability (probability to detect true occupancy) which in turn may be affected by changes in surveying effort between surveys. We thus found evidence that temporal changes in the distribution of breeding birds based on repeated mapping surveys may be inflated by changes in survey effort along range boundaries. We discuss possible approaches to deal with this issue in the analysis and design of national or regional surveys.