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Citizen science, the involvement of volunteers in research, has increased the scale of ecological field studies with continent-wide, centralized monitoring efforts and, more rarely, tapping of volunteers to conduct large, coordinated, field experiments. The unique benefit for the field of ecology lies in understanding processes occurring at broad geographic scales and on private lands, which are impossible to sample extensively with traditional field research models. Citizen science produces large, longitudinal data sets, whose potential for error and bias is poorly understood. Because it does not usually aim to uncover mechanisms underlying ecological patterns, citizen science is best viewed as complementary to more localized, hypothesis-driven research. In the process of addressing the impacts of current, global \"experiments\" altering habitat and climate, large-scale citizen science has led to new, quantitative approaches to emerging questions about the distribution and abundance of organisms across space and time.

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.

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.

Citizen science is a research practice that relies on public contributions of data. The strong recognition of its educational value combined with the need for novel methods to handle subsequent large and complex data sets raises the question: Is citizen science effective at science? A quantitative assessment of the contributions of citizen science for its core purpose--scientific research--is lacking. We examined the contribution of citizen science to a review paper by ornithologists in which they formulated ten central claims about the impact of climate change on avian migration. Citizen science was never explicitly mentioned in the review article. For each of the claims, these ornithologists scored their opinions about the amount of research effort invested in each claim and how strongly the claim was supported by evidence. This allowed us to also determine whether their trust in claims was, unwittingly or not, related to the degree to which the claims relied primarily on data generated by citizen scientists. We found that papers based on citizen science constituted between 24 and 77% of the references backing each claim, with no evidence of a mistrust of claims that relied heavily on citizen-science data. We reveal that many of these papers may not easily be recognized as drawing upon volunteer contributions, as the search terms \"citizen science\" and \"volunteer\" would have overlooked the majority of the studies that back the ten claims about birds and climate change. Our results suggest that the significance of citizen science to global research, an endeavor that is reliant on long-term information at large spatial scales, might be far greater than is readily perceived. To better understand and track the contributions of citizen science in the future, we urge researchers to use the keyword \"citizen science\" in papers that draw on efforts of non-professionals.

Extreme weather events are increasing in frequency and intensity as a result of modern climate change. During winter, species may be especially vulnerable to extreme weather as they are surviving on scarce resources and living at the edge of their thermal limits. We compiled data from eBird, a global citizen science initiative, to examine how 41 eastern North American birds shifted their occurrence and abundance patterns immediately following two recent extreme weather events each affecting > 2 million km2, the intrusion of a polar vortex and a winter heat wave. eBird data is continuously collected at high spatiotemporal resolution across large spatial extents, allowing us to compare species' responses immediately before and after these extreme events with trends in other winters across geographic scales. Overall, we found that birds responded differently to each extreme weather event. Bird occurrence rates did not change following the polar vortex, but where species occurred, population density was temporarily reduced, suggesting reductions in number of individuals driven by decreases in behavioral activity or temporary movement out of the area. However, birds demonstrated widespread increases in occurrence and increases in density and number of individuals where they occurred for at least 20 days after the heat wave, hinting at longer‐term range changes. Smaller‐bodied, warm‐adapted passerines tended to be most sensitive to extreme weather and responded most negatively to the polar vortex and most positively to the heat wave, while larger‐bodied, cold‐adapted waterbirds expressed only mild responses to either event. Thus, certain species may be exceptionally sensitive to extreme weather events while others are less sensitive. As climate change progresses and climatic variability increases, researchers and managers must better quantify the broad‐scale sensitivity of different species to multiple types of extreme weather events.

For many terrestrial organisms in the Northern Hemisphere, winter is a period of resource scarcity and energy deficits, survivable only because a seasonal refugium - the \"subnivium\" - exists beneath the snow. The warmer and more stable conditions within the subnivium are principally driven by snow duration, density, and depth. In temperate regions, the subnivium is important for the overwintering success of plants and animals, yet winter conditions are changing rapidly worldwide. Throughout the Northern Hemisphere, the impacts of climate change are predicted to be most prominent during the winter months, resulting in a shorter snow season and decreased snow depth. These climatic changes will likely modify the defining qualities of the subnivium, resulting in broad-scale shifts in distributions of species that are dependent on these refugia. Resultant changes to the subnivium, however, will be spatially and temporally variable. We believe that ecologists and managers are overlooking this widespread, crucial, and vulnerable seasonal refugium, which is rapidly deteriorating due to global climate change.

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.

Pine Siskins exemplify normally boreal seed-eating birds that can be sparse or absent across entire regions of North America in one year and then appear in large numbers the next. These dramatic avian “irruptions” are thought to stem from intermittent but broadly synchronous seed production (masting) in one year and meager seed crops in the next. A prevalent hypothesis is that widespread masting in the boreal forest at high latitudes is driven primarily by favorable climate during the two to three consecutive years required to initiate and mature seed crops in most conifers. Seed production is expensive for trees and is much reduced in the years following masting, driving boreal birds to search elsewhere for food and overwintering habitat. Despite this plausible logic, prior efforts to discover climate-irruption relationships have been inconclusive. Here, analysis of more than 2 million Pine Siskin observations from Project FeederWatch, a citizen science program, reveals two principal irruption modes (North-South and West-East), both of which are correlated with climate variability. The North-South irruption mode is, in part, influenced by winter harshness, but the predominant climate drivers of both modes manifest in the warm season as continental-scale pairs of oppositely signed precipitation and temperature anomalies (i.e., dipoles). The climate dipoles juxtapose favorable and unfavorable conditions for seed production and wintering habitat, motivating a push-pull paradigm to explain irruptions of Pine Siskins and possibly other boreal bird populations in North America. Significance This study is the first, to our knowledge, to reveal how climate variability drives irruptions of North American boreal seed-eating birds. Patterns of Pine Siskin irruption and associated climate drivers manifest as two modes (North-South and West-East) in which dipoles of temperature and precipitation anomalies push and pull irruptive movements across the continent at biennial to decadal periodicities. Our study accentuates the value of sustained and synoptic biological observations, contributed by citizen scientists in this case, that match the spatial and temporal scales at which climatic phenomena are observed and understood. Such observations can help probe new questions, such as the role of climatic dipoles in other large-scale ecological processes.

Climate associated ecological phenomena that occur approximately once per decade suggest the influence of decadal climate oscillations. However, the consistency and origins of such climate patterns in the Atlantic and Pacific regions is currently under debate. Here, we propose a probabilistic explanation for episodic ecological events based on the likelihood of multiple climate patterns converging in a particular phase combination. To illustrate, we apply this model to continental scale facultative migration of seed-eating finches out of the boreal forest. This irruption phenomenon is triggered by seed crop failures stemming from two weakly correlated climate patterns occurring simultaneously in their positive phases—the North Atlantic Oscillation (NAO) and the North Pacific Oscillation (NPO). The joint probability of NAO and NPO both being positive (above upper tercile) is about (1/3)2≈0.11, illustrating a simple probabilistic explanation for quasi-decadal finch irruption and potentially other episodic ecological events in regions affected by multiple climate modes.

As climate change advances, there is a need to examine climate conditions at scales that are ecologically relevant to species. While microclimates in forested systems have been extensively studied, microclimates in grasslands have received little attention despite the climate vulnerability of this endangered biome. We employed a novel combination of iButton temperature and humidity measurements, fine-scale spatial observations of vegetation and topography collected by unpiloted aircraft system, and gridded mesoclimate products to model microclimate anomalies in temperate grasslands. We found that grasslands harbored diverse microclimates and that primary productivity (as represented by normalized difference vegetation index), canopy height, and topography were strong spatial drivers of these anomalies. Microclimate heterogeneity is likely of ecological importance to grassland organisms seeking out climate change refugia, and thus there is a need to consider microclimate complexity in the management and conservation of grassland biodiversity.