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The teleconnection mechanisms associated with midlatitude climate dipoles are of high interest because of their potential broad impacts on ecological patterns and processes. A prominent example attracting increasing research interest is a summer (June–August) North American dipole (NAD), which drives continental-scale bird irruptions in the boreal forest (semiperiodic movements of large numbers of individual birds). Here, the NAD is objectively defined as a second principal component of 500-hPa geopotential height and is linked to two mechanisms: 1) Rossby waves associated with Madden–Julian oscillation (MJO) convection and 2) a pan-Pacific stationary Rossby wave triggered by East Asian monsoonal convection. The MJO mechanism relates to anomalously frequent occurrence of MJO phase 1 or 6, which are captured by the leading principal component of daily summer MJO phases (PCM1; accounting for 46% of the phase variance). In “nonuniform” MJO summers, defined as |PCM1| > 0.5, anomalously frequent phase 1 triggers positive NAD, and anomalously frequent phase 6 triggers negative NAD, yielding the correlation r(NAD, PCM1) = 0.55, p < 0.01. During “uniform” MJO summers, defined as |PCM1| ≤ 0.5, the effect of East Asian precipitation anomalies PEA becomes apparent, and r(NAD, PEA) = 0.49, p < 0.01. The impacts of PEA are largely masked during nonuniform MJO summers, meaning this subset of summers lacks a significant correlation between the NAD and PEA. Our interpretation is that uniformly distributed MJO allows monsoonal convection over the midlatitudes to modulate the NAD, whereas tropical convection anomalies associated with anomalously frequent MJO phases 1 and 6 overwhelm the extratropical teleconnection.

Color polymorphism is an adaptive strategy in which a species exhibits multiple color phenotypes in a population. Often times, phenotypes are variably suited to different environmental conditions which may buffer the population against variable conditions. Modern climate change is creating novel selective pressures for many species, especially in winter habitats. Few studies have quantified the benefits of polymorphism for allowing species to cope with climate-induced environmental change. We investigated how color polymorphism mediates selective pressures in ruffed grouse Bonasa umbellus, a widespread and winter-adapted bird species of North American forests. Ruffed grouse display phenotypic variation in plumage color, ranging from red to gray. Over five winter seasons (2015-2022), we monitored weather conditions, habitat use, and weekly survival for 94 ruffed grouse to test whether individuals had lower survival when grouse were phenotypically mismatched with snow cover (e.g., a gray bird on a snowless landscape or a red bird in snow). Grouse phenotypically mismatched with snow cover had lower survival, but only when winter survival rates were lowest. During winters of lower overall survival, red grouse exhibited higher survival during snow-free periods, whereas gray grouse had higher survival when snow was present. We also found that open habitat negatively impacted survival, regardless of color. While the effect of phenotypic mismatch was variable among years, it was a stronger predictor of winter survival than land cover features, suggesting that snow is an important habitat feature mediating overwinter survival. Our work offers an advancement in understanding how environmental variability affects geographic variation in and maintenance of multiple color phenotypes in seasonally-snow covered environments. Our finding that interactions between color morph and snow cover are important for conferring winter survival provides further evidence that color polymorphism may serve as a buffer against rapidly changing conditions and a pathway for persistence of polymorphic species.

Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity (non-stationarity) given adaptation to local and seasonal environments. Non-stationarity carries important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated spatial and seasonal variation in both thermal optimum and breadth, or the temperature and range of temperatures of peak occurrence. Some birds demonstrated constant thermal optima or breadths (stationarity) while others varied according to local and current environmental conditions (non-stationarity). Across species, birds typically invested in either geographic or seasonal adaptation to climate. Intraspecific variation in thermal sensitivity is likely an important but neglected aspect of organismal responses to climate change.

In North America, winters are becoming more variable such that warm and cold extremes are increasingly common. Refugia (in time or space) can reduce the exposure animals experience to extreme temperatures. However, animals must be able to adjust their behavior to capitalize on refugia. Our goal was to identify the behavioral mechanisms that grant access to refugia in time and space, focusing on a northern ungulate (white-tailed deer, Odocoileus virginianus) as a model. We drew upon an extensive camera trap network in Wisconsin, USA, over two winters that experienced both warm and cold extremes. To understand the use of temporal refugia, we modeled deer activity (at daily resolution) during night, dawn, day, and dusk as a function of weather predictors. To understand the use of spatial refugia, we modeled deer activity at camera locations (at daily resolution) as a function of landscape characteristics, weather conditions, and landscape–weather interactions. During anomalously cold temperatures, deer became more diurnal; conversely, on anomalously warm days, deer were more nocturnal. Deer were more active in conifer-dominated landscapes on cold days. Conversely, during warm extremes, deer increased activity in deciduous-dominated landscapes. Finally, deer showed multiple modes of behavioral flexibility (activity in time as well as space) and demonstrated stronger responses to temperature anomalies later in the winter, suggesting that the effects of extreme events are dependent upon their seasonal timing. Behavioral shifts presumably reduce exposure to extremes and may render species more resilient to increasingly variable winter climates.

Animal behaviors are often modified in urban settings due to changes in species assemblages and interactions. The ability of prey to respond to a predator is a critical behavior, but urban populations may experience altered predation pressure, food supplementation, and other human-mediated disturbances that modify their responsiveness to predation risk and promote habituation.Citizen-science programs generally focus on the collection and analysis of observational data (e.g., bird checklists), but there has been increasing interest in the engagement of citizen scientists for ecological experimentation.Our goal was to implement a behavioral experiment in which citizen scientists recorded antipredator behaviors in wild birds occupying urban areas. In North America, increasing populations of

The subnivium is the seasonal microhabitat at the snow–ground interface and serves as a refuge for a diversity of species. Increasingly warmer winters are disrupting the continuity of snow cover, and likely the stability of the subnivium. To examine how the extent and duration of this sensitive and widespread below‐snow habitat will shift under warming winters, we deployed fully automated winter greenhouses across latitudinal and land‐cover gradients to monitor subnivium conditions under different climate‐change scenarios and predicted subnivium occurrence across the Great Lakes region. In a +3°C warming scenario, we found little change in subnivium extent or duration, whereas a +5°C scenario produced widespread and marked reductions in both extent (loss of 200,000 km², a 45% decline) and duration (>1 month decline). Although the subnivium appears resilient to moderate future warming, we predict abrupt and extensive changes in response to increased winter warming, which will have sweeping ecological and environmental consequences in high‐latitude ecosystems.

Animals are facing novel 'timescapes' in which the stimuli entraining their daily activity patterns no longer match historical conditions due to anthropogenic disturbance. However, the ecological effects (e.g., altered physiology, species interactions) of novel activity timing are virtually unknown. We reviewed 1328 studies and found relatively few focusing on anthropogenic effects on activity timing. We suggest three hypotheses to stimulate future research: (i) activity-timing mismatches determine ecological effects, (ii) duration and timing of timescape modification influence effects, and (iii) consequences of altered activity timing vary biogeographically due to broad-scale variation in factors compressing timescapes. The continued growth of sampling technologies promises to facilitate the study of the consequences of altered activity timing, with emerging applications for biodiversity conservation.

Global biodiversity is in unprecedented decline and on‐the‐ground solutions are imperative for conservation. Although there is a large volume of evidence related to climate change effects on wildlife, research on climate adaptation strategies is lagging. To assess the current state of knowledge in climate adaptation, we conducted a comprehensive literature review and evaluated 1,346 peer‐reviewed publications for management recommendations designed to address the consequences of climate change on wildlife populations. From 509 publications, we identified 2,306 recommendations and employed both qualitative and quantitative methods for data analysis. Although we found an increase in the volume and diversity of recommendations since 2007, a focus on protected areas (26%, 596 of 2,306 recommendations) and the non‐reserve matrix (12%, 276 of 2,306 recommendations) remained prominent in the climate adaptation literature. Common concepts include protected areas, invasive species, ecosystem services, adaptive management, stepping stones, assisted migration, and conservation easements. In contrast, only 1% of recommendations focused on reproduction (n = 26), survival (n = 14), disease (n = 26), or human‐wildlife conflict (n = 24). Few recommendations reflected the potential for local‐scale management interventions. We demonstrate limited advancement in preparing natural resource managers in climate adaptation at local, management‐relevant scales. Additional research is needed to identify and evaluate climate adaptation strategies aimed at reducing the vulnerability of wildlife to contemporary climate change.

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.

Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.

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.

Grassland birds are among the most globally threatened bird groups due to substantial degradation of native grassland habitats. However, the current network of grassland conservation areas may not be adequate for halting population declines and biodiversity loss. Here, we evaluate a network of grassland conservation areas within Wisconsin, U.S.A., that includes both large Focal Landscapes and smaller targeted conservation areas (e.g., Grassland Bird Conservation Areas, GBCAs) established within them. To date, this conservation network has lacked baseline information to assess whether the current placement of these conservation areas aligns with population hot spots of grassland‐dependent taxa. To do so, we fitted data from thousands of avian point‐count surveys collected by citizen scientists as part of Wisconsin's Breeding Bird Atlas II with multinomial N‐mixture models to estimate habitat–abundance relationships, develop spatially explicit predictions of abundance, and establish ecological baselines within priority conservation areas for a suite of obligate grassland songbirds. Next, we developed spatial randomization tests to evaluate the placement of this conservation network relative to randomly placed conservation networks. Overall, less than 20% of species statewide populations were found within the current grassland conservation network. Spatial tests demonstrated a high representation of this bird assemblage within the entire conservation network, but with a bias toward birds associated with moderately tallgrasses relative to those associated with shortgrasses or tallgrasses. We also found that GBCAs had higher representation at Focal Landscape rather than statewide scales. Here, we demonstrated how combining citizen science data with hierarchical modeling is a powerful tool for estimating ecological baselines and conducting large‐scale evaluations of an existing conservation network for multiple grassland birds. Our flexible spatial randomization approach offers the potential to be applied to other protected area networks and serves as a complementary tool for conservation planning efforts globally., Grassland birds are rapidly declining globally and therefore are of conservation concern. Here, we integrated citizen science data, hierarchical occupancy models, and novel spatial simulations to evaluate the spatial configuration of an existing conservation network for the conservation of 9 obligate grassland birds. We found representation of grassland birds within the conservation network to be high for species that specialize in moderately tall grassland habitats but not shortgrass or tallgrass specialists.

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.

The emergence of citizen science, passive sensors (e.g., trail cameras and acoustic monitoring), and satellite remote sensing have enabled biological data to be collected at unprecedented spatial and temporal scales. There is growing interest in networking these datastreams to expedite the collection and synthesis of environmental and biological data to improve broad-scale ecological monitoring, but there are no examples of such networks being developed to directly inform decision-making by managing agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin (SW), that links satellite remote sensing (RS) with a volunteer-based trail camera network to generate new insights into wildlife distributions and improve their management by the state agency. SW relies on citizen scientists to deploy trail cameras across the state and classify images of wildlife. As of early 2020 SW comprises nearly 1800 volunteers hosting >2100 active cameras recording >37 million images across a sampling effort of >2000 combined trap-years at >3300 distinct camera locations. We use a set of case studies to demonstrate the potential power of a JON to monitor wildlife with unprecedented combinations of spatial, temporal, and biological resolution and extent. Specifically, we demonstrate that SW markedly improves the spatial and temporal resolution with which black bear distributions can be monitored or forecast, in turn improving the resolution of decision-making. Enhancing the biological resolution of monitoring (e.g., monitoring the distribution of species traits or behaviors) may provide new insights into population drivers, such as the connection between vegetation productivity and white-tailed deer foraging behaviors. Enhanced taxonomic extent provided by trail cameras and other passive sensor networks provide managers new information for a wide range of species and communities that are not otherwise monitored. Our cases further show that JONs synergize existing monitoring practices by serving as a complementary and independent line of evidence or as a tool to enhance the extent and precision of existing models through integrated modeling approaches. SW and other JONS are a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.