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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 $(1/3)^2\approx 0.11$ , illustrating a simple probabilistic explanation for quasi-decadal finch irruption and potentially other episodic ecological events in regions affected by multiple climate modes.

Abstract Extensive restoration and translocation efforts beginning in the mid‐20th century helped to reestablish eastern wild turkeys (Meleagris gallopavo silvestris) throughout their ancestral range. The adaptability of wild turkeys resulted in further population expansion in regions that were considered unfavorable during initial reintroductions across the northern United States. Identification and understanding of species distributions and contemporary habitat associations are important for guiding effective conservation and management strategies across different ecological landscapes. To investigate differences in wild turkey distribution across two contrasting regions, heavily forested northern Wisconsin, USA, and predominately agricultural southeast Wisconsin, we conducted 3050 gobbling call‐count surveys from March to May of 2014–2018 and used multiseason correlated‐replicate occupancy models to evaluate occupancy–habitat associations and distributions of wild turkeys in each study region. Detection probabilities varied widely and were influenced by sampling period, time of day, and wind speed. Spatial autocorrelation between successive stations was prevalent along survey routes but was stronger in our northern study area. In heavily forested northern Wisconsin, turkeys were more likely to occupy areas characterized by moderate availability of open land cover. Conversely, large agricultural fields decreased the likelihood of turkey occupancy in southeast Wisconsin, but occupancy probability increased as upland hardwood forest cover became more aggregated on the landscape. Turkeys in northern Wisconsin were more likely to occupy landscapes with less snow cover and a higher percentage of row crops planted in corn. However, we were unable to find supporting evidence in either study area that the abandonment of turkeys from survey routes was associated with snow depth or with the percentage of agricultural cover. Spatially, model‐predicted estimates of patch‐specific occupancy indicated turkey distribution was nonuniform across northern and southeast Wisconsin. Our findings demonstrated that the environmental constraints of turkey occupancy varied across the latitudinal gradient of the state with open cover, snow, and row crops being influential in the north, and agricultural areas and hardwood forest cover important in the southeast. These forces contribute to nonstationarity in wild turkey–environment relationships. Key habitat–occupancy associations identified in our results can be used to prioritize and strategically target management efforts and resources in areas that are more likely to harbor sustainable turkey populations.

Abstract 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.

Recovering species are not returning to the same environments or communities from which they disappeared. Conservation researchers and practitioners are thus faced with additional challenges in ensuring species resilience in these rapidly changing ecosystems. Assessing the resilience of species in these novel systems can still be guided by species’ ecology, including knowledge of their population size, life history traits, and behavioral adaptations, as well as the type, strength, and number of ways that they interact with other species in the community. We summarized broad trends of Common Loons (Gavia immer) breeding at Voyageurs National Park from 1973 to 2009, and evaluated the effects of increased risk from recovering Bald Eagles (Haliaeetus leucocephalus) on chick survival from 2004 to 2006. Adult Common Loons appear to have increased over time. Using Bayesian survival models that accounted for imperfect detection of unmarked individuals, we determined that chick survival of Common Loons was high from year to year and was unrelated to predation risk from Bald Eagles because chicks in territories closer to active nests did not experience greater mortality than those farther away. We suggest that Common Loon chicks were unaffected by the recovery of this top predator during the three years of sampling. Previous research indicates that Bald Eagles and other predators are an important source of egg losses, but Common Loons can compensate by re-nesting. Despite current uncertainties from anthropogenic threats, knowledge of a species’ ecology remains instrumental in determining its resilience during recovery.

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.

Repeat digital photography at or near ground-level is a proven and efficient approach for tracking plant phenology. Here, we explored the potential to monitor phenology using the Snapshot Wisconsin (SW) trail camera network, a citizen science program. Using three curve-fitting methods for characterizing phenological transition dates, we assessed the phenological offset between understory vegetation and the overstory canopy in the trailcam observations and compared variations in derived phenology over the different spatial scales represented by trailcams (~20–50 m), Harmonized Landsat and Sentinel-2 (HLS, 30 m), and Moderate Resolution Imaging Spectroradiometer (MODIS, 500 m). Our results showed that the apparent phenological offset between understory and overstory vegetation differed among forest types: in broadleaf deciduous forests, understory vegetation had an earlier start-of-spring (SOS) and later end-of-autumn (EOA) than the overstory canopy; in mixed forests, the understory showed an earlier SOS than the overstory, but no significant difference in EOA; in evergreen conifer forests, neither SOS nor EOA differed significantly between the understory and overstory. We found moderate correlations (0.25 ≤ r ≤ 0.57) between trailcam- and satellite-derived phenological dates. Moreover, those derived dates varied significantly among the applied curve-fitting methods: total growing season length (from SOS to EOA) could be 19 days longer for a threshold-based method than for a logistic curve-fitting method (our reference model), but 17 days shorter than the logistic method when using a piecewise-continuous method based on fitted sine curves. Despite the spatial limitations of trailcams for characterizing phenology on landscape and regional scales, trailcam networks have considerable potential for informing local phenological studies and disentangling the many drivers of phenology that can remain undetected from the satellite perspective.

Abstract Many animals depend on stable below‐the‐snow (subnivium) conditions to survive winter in seasonally cold regions. Freeze‐tolerant ectotherms may experience increased ice content and/or energy expenditure in suboptimal subnivium conditions, with implications for overwinter survival and body reserves available for spring reproduction. We used a novel mechanistic modeling approach to explore effects of winter climate on the microclimate conditions, energy expenditure, and ice dynamics of the freeze‐tolerant, subnivium‐dwelling wood frog (Lithobates sylvaticus) in the Upper Midwest and Great Lakes Basin region of the United States. We hypothesized that (1) frogs would experience the greatest energy cost to survive winter in southern regions of our study area, where air temperatures are warmer and shallower snow could allow for increased numbers of freeze–thaw cycles, and (2) frogs would be most vulnerable to lethal freezing in the cold, dry northwest portion of our study region. We found that total winter energy expenditure changed little with latitude because the effect of warmer soil temperatures (higher metabolic rates) to the south was offset by a shorter winter duration. Energy expenditures were greatest in the snowbelts of the Great Lakes, characterized by more persistent snow cover and relatively warm soil temperatures. In contrast, highest ice contents occurred in the northwest of the study region where air temperatures were coldest and snow was shallow. Thus, it appears that wood frogs experience a trade‐off between risk of lethal ice content and extensive use of body reserves across geographic space. Simulations showed that interpopulation differences in burrow depth and cryoprotectant concentration can influence risk of lethal ice content and overuse of body reserves prior to spring breeding, and those risks vary in relation to winter climate. Our mechanistic modeling approach is a novel tool for predicting risk and shifting niche space for cold‐adapted and subnivium‐dependent species.

Habitat thresholds are often interpreted as the minimum required area of habitat, and subsequently promoted as conservation targets in natural resource policies and planning. Unfortunately, several recent reviews and messages of caution on the application of habitat thresholds in conservation have largely fallen on deaf ears, leading to a dangerous oversimplification and generalization of the concept. We highlight the prevalence of oversimplification/over-generalization of results from habitat threshold studies in policy documentation, the consequences of such over-generalization, and directions for habitat threshold studies that have conservation applications without risking overgeneralization. We argue that in order to steer away from misapplication of habitat thresholds in conservation, we should not focus on generalized nominal habitat values (i.e., amounts or percentages of habitat), but on the use of habitat threshold modeling for comparative exercises of area-sensitivity or the identification of environmental dangers. In addition, we should remain focused on understanding the processes and mechanisms underlying species responses to habitat change. Finally, studies could that focus on deriving nominal value threshold amounts should do so only if the thresholds are detailed, species-specific, and translated to conservation targets particular to the study area only.

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.

In seasonally snow-covered environments, many organisms endure winter by using the subnivium, a below-snow thermally stable seasonal refugium. Because the insulation of snow is dependent on snow depth and density, the stability of temperatures within the subnivium varies across land cover types. Additionally, across much of the Northern Hemisphere snow extent, depth and duration are generally decreasing while snow density is increasing due to climate change. These changes are likely to destabilize the thermal profile of the subnivium, although they have not yet been quantified. To explore the effects of land cover and climate change on the subnivium, we measured snow pack characteristics (depth and density), and ambient and subnivium temperatures from three different land cover types (prairie, deciduous forest, and coniferous forest) and within a micro-greenhouse (2.5 x 2.5 x 2 m) that maintained a temperature of 5 °C warmer than outdoor ambient temperatures, and automatically opened during snow events throughout the winter of 2013/14. We found that the mean daily subnivium temperature was significantly colder in the deciduous cover type than the prairie cover type, and that prairie had higher maximum subnivium temperatures than both of the other cover types. Our climate change simulation revealed that, although ambient temperatures within the micro-greenhouse were 5 °C warmer than outside the greenhouse, the daily minimum subnivium temperature was significantly lower inside the greenhouse. Our findings suggest that climate change could have considerable effects on the refuge quality of the subnivium, and that some cover types appear to be more susceptible to these effects than others.

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.