Partners in Flight (PIF) has been publishing population estimates for landbirds in Canada and the United States since 2004. These estimates have been widely used in support of species status assessments, conservation planning, and communicating the status of bird populations. However, broad uncertainty around many estimates and potential biases due to gaps in geographic and temporal coverage have partly limited their applicability. Determining the absolute size of wild bird populations requires adequate survey data and appropriately complex modeling of detection probability to transform field observations into estimates of density. We have developed an updated approach that integrates data-derived estimates of detectability for hundreds of species, range-wide relative abundance surfaces, and spatial information from the North American Breeding Bird Survey (BBS) into a formal Bayesian model. This improved method combines important elements of the existing PIF population estimates framework with a large database of structured observations that allow formal detectability estimates (NA-POPS), the hierarchical Bayesian count-based trend models applied to the BBS data, and high-resolution spatially explicit estimates of relative abundance from eBird. It calibrates the relative abundance surface of a species to represent its density on the landscape and thereby can generate population estimates, with associated uncertainties, for any custom area. This model also generates population estimates for a single year, improving on the previous estimates that were averaged over 10 years. This new method works well for territorial songbirds and other species effectively monitored using point count field methods and observations during the early morning hours. Other species such as colonially nesting birds, crepuscular or nocturnal species, and species with highly specific habitat requirements, will require further model refinement. PIF will use this revised model to publish estimates of population sizes for North American birds and will continue to improve the model in an open and reproducible way.

Historically, research and monitoring of bird populations has been conducted with in-person point counts; however, passive acoustic monitoring (PAM) recordings transcribed by experts (“PAM point counts”) are rapidly replacing in-person surveys as an approach for counting birds. We reviewed the literature and used case-matched datasets from North America’s boreal forest to show that despite similarities in data structure, in-person and PAM point counts have fundamental differences in the detection process that lead to differences in detectability estimates from distance and removal sampling models. Observer effects on cue rate were more pronounced in PAM than in-person point counts. Cue rate estimates from PAM were significantly higher than from point counts due to earlier time of first detection in PAM point counts, the availability of data with higher-resolution time intervals in removal models, and the exclusion of visual detections. In contrast, exclusion of visual detections from point-count data estimates resulted in lower estimates of perceptibility. Cumulative lower values of detectability estimates from in-person point counts resulted in 15% higher density estimates on average when applied as statistical offsets. We suggest some of the differences in detectability estimates between survey methods are due to human error and/or failure of statistical assumptions and that availability estimates for species that are at least 90% aurally-detected should be preferentially derived from PAM data to reduce bias in density estimates for conservation applications and facilitate continued integration of historic and contemporary point-count datasets. Future research should focus on alternatives to removal modelling and understanding the detection process of automated classifiers to continue to improve detectability estimates and maximize the ability to integrate datasets across data types.

Quantifying links between breeding, stopover and non-breeding locations is critical to the management and conservation of migratory birds, particularly if they are hunted on migration and in winter. Endogenous markers such as stable isotopes provide a means of estimating natal or breeding origins and hence the degree of migratory connectivity between breeding and wintering areas. We used a stable hydrogen isotope (delta 2H) isoscape for Europe and 2H analysis of feathers from harvested birds to estimate the natal and moulting origins of Eurasian Woodcock Scolopax rusticola wintering in Britain and Ireland. Using feathers collected from known locations across the breeding range, we established the relationship between the hydrogen isotope composition of feathers (delta 2Hf) and mean annual detrended precipitation (delta 2Hp) for Woodcock in Europe. We used a spatially explicit Bayesian assignment to estimate probable origins for each delta 2Hf value. Our results indicated broad-front migration of Woodcock to Britain and Ireland, with most birds originating from Fennoscandia, the Baltic states, Belarus and western Russia. Migratory connectivity between breeding areas and wintering regions was low, but there was a difference in delta 2Hf values between six winter sampling regions, which was consistent with parallel migration routes from northern and eastern Europe. The estimated proportion of Woodcock shot that were residents averaged 10.3 +/- 3.3% across winter regions, and British birds were present in winter in regions where they do not currently breed.

Understanding range-wide demographic, spatial, and temporal variation in annual survival is essential for managing species of conservation concern. Multi-population models are useful tools for integrating diverse datasets, reducing biases, and deriving survival estimates across differing spatial scales. We conducted a range-wide, multi-population apparent annual survival analysis for a declining songbird, Vermivora chrysoptera (Golden-winged Warbler), using data from 18 sites across its breeding and nonbreeding grounds. This Nearctic-Neotropical migrant breeds in 2 disjunct regional populations, the Great Lakes and Appalachian Mountains, which are experiencing different rates of decline. We aimed to quantify regional-, site-, and sex-specific apparent annual survival estimates to identify geographic patterns or demographic factors influencing population declines. We used simulations to assess the precision of our estimates. Our models did not reveal a substantial difference in apparent annual survival between the Great Lakes (0.41, 95% credible interval (CrI):0.31-0.50) and the Appalachian regions (0.49, 95% CrI: 0.36-0.60), as CrIs overlapped. Site-specific estimates also showed no clear differences in apparent annual survival among sites representing both regional populations. Male apparent annual survival tended to be greater than female apparent annual survival in both regions, though CrI's overlapped. Our study suggests demographic factors other than adult annual survival likely play a larger role in recent regional and range-wide population declines, such as productivity, juvenile/immature survival, or recruitment. Simulations indicate that improving recapture probability and study duration of datasets could lead to more precise apparent annual survival estimates. However, our model produced CrI ranges comparable to the most ideal data collection scenario, suggesting the lack of trends we found was not due to variability in our estimates. We stress the importance of addressing inherent biases in survival datasets and the need for standardized collaborative efforts to inform species conservation on a range-wide scale. Vermivora chrysoptera (Golden-winged Warbler) is a declining songbird breeding within 2 disjunct regional populations. The Appalachian Mountains population has undergone significantly higher population declines relative to the Great Lakes population; however, the drivers behind these declines are not well understood. We conducted a range-wide apparent annual survival analysis to obtain spatial and demographic survival estimates for adult V. chrysoptera and paired this analysis with a simulation exercise to gauge the precision of our estimates. Apparent annual survival rates of the Great Lakes and the Appalachian populations were statistically similar. While males tended to have greater apparent annual survival rates than females, overlapping credible intervals made it difficult to infer sex-specific differences. Our study suggests that factors such as productivity, juvenile/immature survival, or recruitment may play a more significant role in regional population declines over the past 2 decades than adult annual survival. An integrated population model would help to elucidate specific limiting factors. We emphasize the importance of standardizing data collection methods across studies for focal species to improve the precision of multi-population models and to better inform conservation efforts. Comprender la variaci & oacute;n demogr & aacute;fica, espacial y temporal de la supervivencia anual a lo largo de toda la distribuci & oacute;n es esencial para manejar especies de inter & eacute;s para la conservaci & oacute;n. Los modelos multi-poblacionales son herramientas & uacute;tiles para integrar diversos conjuntos de datos, reducir sesgos y obtener estimaciones de supervivencia a diferentes escalas espaciales. Realizamos un an & aacute;lisis multi-poblacional de la supervivencia anual aparente en toda la distribuci & oacute;n de una especie de ave canora en declive, Vermivora chrysoptera, utilizando datos de 18 sitios a lo largo de sus & aacute;reas reproductivas y no reproductivas. Este migrante ne & aacute;rtico-neotropical se reproduce en dos poblaciones regionales disyuntas, los Grandes Lagos y las Monta & ntilde;as Apalaches, que est & aacute;n experimentando diferentes tasas de declive. Nuestro objetivo fue cuantificar estimaciones de supervivencia anual aparente espec & iacute;ficas por regi & oacute;n, sitio y sexo para identificar patrones geogr & aacute;ficos o factores demogr & aacute;ficos que influyen en los declives poblacionales. Utilizamos simulaciones para evaluar la precisi & oacute;n de nuestras estimaciones. Nuestros modelos no revelaron una diferencia sustancial en la supervivencia anual aparente entre las regiones de los Grandes Lagos (0,41, intervalo cre & iacute;ble [ICr] del 95%: 0,31-0,50) y los Apalaches (0,49, ICr 95%: 0,36-0,60), ya que los intervalos cre & iacute;bles se superponen. Las estimaciones espec & iacute;ficas por sitio tampoco mostraron diferencias claras en la supervivencia anual aparente entre los sitios que representan ambas poblaciones regionales. La supervivencia anual aparente de los machos tendi & oacute; a ser mayor que la de las hembras en ambas regiones, aunque los intervalos cre & iacute;bles se superponen. Nuestro estudio sugiere que otros factores demogr & aacute;ficos distintos a la supervivencia anual de adultos probablemente desempe & ntilde;an un papel mayor en los recientes declives poblacionales regionales y a escala de distribuci & oacute;n, tales como la productividad, la supervivencia de juveniles/inmaduros o el reclutamiento. Las simulaciones indican que mejorar la probabilidad de recaptura y la duraci & oacute;n de los estudios de las bases de datos podr & iacute;a conducir a estimaciones m & aacute;s precisas de la supervivencia anual aparente. Sin embargo, nuestro modelo produjo rangos de intervalos cre & iacute;bles comparables al escenario m & aacute;s ideal de recolecci & oacute;n de datos, lo que sugiere que la ausencia de tendencias que encontramos no se debi & oacute; a la variabilidad en nuestras estimaciones. Destacamos la importancia de abordar los sesgos inherentes en las bases de datos de supervivencia y la necesidad de esfuerzos colaborativos estandarizados para contribuir a la conservaci & oacute;n de la especie a escala de toda su distribuci & oacute;n.

Understanding the spatial linkages between breeding and non-breeding grounds of migratory species is important for assessing factors influencing population-specific trends and to guide regional conservation actions. In Canada, the Least Bittern (Botaurus exilis) is considered threatened under the Species at Risk Act. Due to the secretive behaviour of this small heron, information regarding migratory pathways and wintering locations is limited. To estimate the geographic locations of potential wintering grounds, we collected body contour feathers from museum specimens of Least Bittern sampled from across their breeding range in Canada. We measured the hydrogen, carbon, and nitrogen isotopic compositions of feathers to estimate the locations of Least Bittern wintering grounds using assignment-to-origin algorithms. The regions of the highest likelihood of origin of sampled Least Bittern were wintering sites in Mexico, central America along the Gulf Coast, and possibly coastal and Amazonian South America. Habitat loss is acknowledged as the main contributor to the population decline of Least Bittern, and these results may help understand potential factors driving their populations and support conservation and management efforts across their wintering range.

Aim To evaluate (1) whether three migratory nightjar species (Family Caprimulgidae) adhere to Bergmann's rule, (2) whether environmental factors on the breeding or wintering grounds determine body size, and (3) which mechanistic hypotheses best explain Bergmannian patterns in body size. Location North and South America; Europe and Africa. Taxon Eastern whip-poor-will (Antrostomus vociferus), Common nighthawk (Chordeiles minor) and European nightjar (Caprimulgus europaeus). Methods We used GPS tracking and morphometric data to assess competing hypotheses explaining variation in body size for each species, based on their breeding (n = 3388) and wintering (n = 189) locations. Results All three species exhibited Bergmannian patterns in body size, providing the first evidence that nightjars conform to Bergmann's rule despite adaptations to severe environmental conditions. Environmental and geographic variables at breeding sites were stronger predictors of body size than wintering-site variables. Although we found partial support for Bergmann's temperature regulation hypothesis, geographic variables, rather than specific environmental factors, emerged as the strongest predictors of body size variation. Main Conclusions Latitude and longitude correlated strongly with environmental variables and migratory distance; thus, these geographical variables likely encompass many factors that influence body size in nightjars. The present study is among the first to use tracking data from individual birds to understand how environmental pressures across the annual cycle are related to body size. Our findings highlight the critical role of geographic breeding-ground factors in shaping Bergmannian patterns, offering robust evidence to support nearly two centuries of research since Bergmann's rule was first described in 1847.

Point-count surveys are commonplace in avian monitoring and research but were initially designed to collect data on avian relative abundance rather than densities. However, the increasing realization that detection biases influence conclusions from point-count surveys has given rise to several statistical approaches to correcting such biases. Distance sampling allows for correction of biases in perceptibility and estimation of avian densities. A key assumption is that distance estimation is accurate, but experimental evidence suggests observation error is large, particularly for estimates based on acoustic detections. We had observers estimate distances to 128 singing birds and one mammal while other staff systematically tracked calling individuals and measured the distance from the observer. Log-log regression showed distance estimation errors and uncertainty increased with increasing distance from the observer. We modeled the relationship between true effective detection radius (EDR) and estimated EDR (including distance estimation error). Simulations showed that species with small EDRs (30 m) had densities underestimated by 23% on average (SD = 11), while densities for species with large (130 m) EDRs were biased upward by 59% on average (SD = 25), but these biases could be corrected post-hoc. Applying the same post-hoc corrections in species-habitat regression models for 4 species of boreal forest birds found that our post-hoc corrections increased EDRs by up to 26% and decreased estimated bird densities by up to 38% for highly detectable species, while effects on less detectable species were more subtle. We suggest collection of more known-distance data that may allow post-hoc corrections to reduce bias in avian density estimates from point-count surveys.

Large portions of the boreal forest are inaccessible to breeding season surveys, leading to highly uncertain assessments of boreal bird populations. However, systematic monitoring of boreal-breeding bird populations during migration has the potential to inform trend estimates for these species. A network of bird observatories across North America have collected decades of standardized daily counts during fall and spring migration seasons with a goal of monitoring avian population dynamics, but statistical approaches to appropriately weight station-level trends in regional-scale analyses have been lacking. Here, we describe a statistical model that estimates population trends across a species' breeding range by integrating migration count data with estimates of the proportions of migrants coming from separate breeding-ground strata based on stable hydrogen isotopes (delta 2Hf) in feather samples of migrants. We applied this model to Blackpoll Warbler (Setophaga striata), a species of conservation concern, and compared migration-based population trend estimates to those from the North American Breeding Bird Survey (BBS). Migration-based and BBS-derived trend estimates were strongly negative for the portion of the species' boreal breeding range east of the Great Lakes, where our analysis indicated populations have potentially declined by > 40% from 1998 to 2018. In contrast, migration analyses suggested that populations were stable or increasing in western Canada, though BBS suggested those populations likely declined, possibly owing to spatial biases in breeding season surveys in that region. Continental trend estimates depended strongly on the source of relative abundance estimates that were used to re-weight stratum trends at larger scales, emphasizing the critical need for improved breeding abundance estimates throughout the core of the boreal forest. Our approach yields trend estimates that are independent from other breeding season survey programs and can be integrated with breeding survey estimates to provide a weight-of-evidence approach when spatial biases in data collection are a major concern. Application of our method to other species inadequately monitored throughout their life cycle will be an important advance for North American landbird monitoring.

Spatially explicit estimates of species abundance and distribution are increasingly needed to support conservation planning and management across multiple spatial scales. We present a generalized modeling framework that bridges the gap between local studies and regional to national planning by compiling and harmonizing diverse datasets to predict avian abundance at fine resolution and broad extent. We applied detectability offsets to integrate point-count data from over 250,000 locations across subarctic Canada. Data were subsampled by two time periods and 16 geographic regions, and we used boosted regression trees to model the density of 143 boreal landbird species as a function of climate, vegetation composition (local [250 m] and landscape [similar to 1.5 km]), land cover, and topography. Bootstrapped regional predictions were combined to generate density maps, region- and habitat-specific estimates, and Canada-wide population totals. We estimated similar to 3.56 billion breeding males (7.13 billion individuals), with most occurring in boreal and hemi-boreal regions. Forest generalists accounted for nearly half the total (1.57 billion males), followed by boreal specialists (1.05 billion), habitat generalists (350 million), and species associated with eastern forests (274 million), grasslands (124 million), western forests (74.7 million), wetlands (63.5 million), and Arctic tundra (17.7 million). Introduced species totaled 48.9 million breeding males. Across species, landscape-level vegetation composition explained most variation in abundance, indicating that climate effects are primarily indirect, operating through vegetation. Landscape-scale variables were critical to capturing this variation. Model classification accuracy was highest for forest- and grassland-associated species (lowest for mountain and urban species), and for the families Regulidae and Phasianidae (lowest for Bombycillidae and Paridae). This work provides a standardized, updatable, and reproducible workflow for generating spatially explicit bird abundance estimates. These products can be revised as new data become available and used to support ongoing conservation and land-use decisions.

Aim: The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location: Worldwide, 12,343 sites, all ecosystem types. Time Period: 1991 to present. Major Taxa Studied: All soniferous taxa. Methods: We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results: Terrestrial sampling is spatially denser (46 sites per million square kilometre-Mkm(2)) than aquatic sampling (0.3 and 1.8 sites/Mkm(2) in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions: PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio-temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross-realm biodiversity research and monitoring efforts.

The urgent need for remote, reliable, and scalable biodiversity monitoring amidst mounting human pressures on ecosystems and changing climate has sparked interest in Passive Acoustic Monitoring (PAM) worldwide. PAM holds potential for supporting global sustainability goals by aiding conservation efforts, but so far, there is no comprehensive overview of its coverage. Here we present metadata from 293 PAM datasets recorded since 1991 in the first global synthesis of ecoacoustic sampling coverage across spatial, temporal, and ecological scales. We report data on sampling sites, deployment schedules, focal taxa, and recording parameters, and quantify biological, anthropogenic, and geophysical soundscape components across nine terrestrial and aquatic ecosystems. We found that terrestrial sampling is spatially denser (33 sites/Mkm2) compared to aquatic realms, with significant data gaps in subterranean realms. While diel and lunar cycles are well-sampled, seasonal coverage is lacking in freshwater and terrestrial ecosystems, while 57% of marine datasets cover all seasons. Opportunities for improvement include broader taxonomic sampling on land, expanding coverage in the high seas, and increasing spatial replication in freshwater environments. Additionally, we highlight nine case studies showcasing how PAM-based soundscape ecology can contribute to macroecology, conservation, and phenology studies, illustrating its potential to support global sustainability efforts both on land and underwater.### Competing Interest StatementThe authors have declared no competing interest.

To recover species at risk, it is necessary to identify habitat critical to their recovery. Challenges for species with large ranges (thousands of square kilometres) include delineating management unit boundaries within which habitat use differs from other units, along with assessing any differences among units in amounts of and threats to habitat over time. We developed a reproducible framework to support identification of critical habitat for wide-ranging species at risk. The framework (i) reviews species distribution and life history; (ii) delineates management units across the range; (iii) evaluates and compares current and (iv) potential future habitat and population size and (v) prioritizes areas within management units based on current and future conditions under various scenarios of climate change and land-use. We used Canada Warbler ( Cardellina canadensis ) and Wood Thrush ( Hylocichla mustelina ) in Canada as case studies. Using geographically weighted regression models and cluster analysis to measure spatial variation in model coefficients, we found geographic differences in habitat association only for Canada Warbler. Using other models to predict current habitat amount for each species in different management units, then future habitat amount under land use and climate change, we projected that: (1) Canada Warbler populations would decrease in Alberta but increase in Nova Scotia and (2) Wood Thrush populations would increase under most scenarios run in Quebec, New Brunswick and Nova Scotia, but not in Ontario. By comparing results from future scenarios and spatial prioritization exercises, our framework supports identification of critical habitat in ways that incorporate climate and land-use projections.

Autonomous Recording Units (ARUs) are widely used to survey for a variety of taxa. This survey method allows for high spatial and temporal coverage but will typically include identification errors that can bias estimates of occupancy. In some instances, verifying all individual detections is prohibitive. To direct verification effort, we developed a model to estimate the probability that transcribers would agree on an identification. Agreement probability was positively influenced by transcriber skill, identification confidence, species commonness and some song types. In contrast, agreement probability was lower when an acoustic signal was classified as a trill. We evaluated our model on independent data where all species detections were verified, and verification effort (time) was quantified. Our model performed well at predicting transcriber agreement on independent data (AUC = 0.71). We applied the model to randomised subsets of the independent data to compare the cost benefit of three approaches to verification under varying effort. We show how modelling probability of transcriber agreement can be used to more efficiently direct verification of species acoustic tags. Our approach could be adapted elsewhere to quantify and reduce species misidentifications in unverified passive acoustic monitoring data for either manual processing or detections from automated classifiers.

Species distribution modeling is important for predicting species responses to environmental change, but model accuracy can be limited by a lack of data in remote areas. Hierarchically stratified surveys (cluster sampling) offer an efficient approach to sampling in remote areas, but an appropriate balance is needed between cost efficiency and statistical independence. The cost-effectiveness of cluster sampling likely varies with temporal sampling intensity (e.g., single vs. multiple repeat samples) due to differences in spatial autocorrelation. Our aim was to assess the trade-offs between spatial and temporal replication and optimize sampling in which temporal replication occurs. We used bootstrap resampling to create alternative designs from multi-species avian point-count and autonomous recording unit data. We varied the number of primary sample units (PSUs), secondary sampling units per PSU (SSUs), and temporal repeat samples (i.e., visits) at each SSU. We fit species accumulation curves to examine how spatial and temporal replication influenced species accumulation. We split data into spatially independent model training and validation datasets and fit species distribution models (SDM) for 47 species using generalized linear models and examined how prediction accuracy changed with sampling intensity to examine the cost-benefit trade-offs between spatial versus temporal replication within PSUs. We found that spatial and temporal replication were partially redundant and adding more visits had less influence on predictive accuracy when there were more SSUs and vice versa. The cost-benefit of increasing spatial replication within PSUs varied with the costs of accessing SSUs. The optimal number of SSUs per PSU varied with both temporal replication and the number of unique PSUs sampled. In general, using ≤ 3 SSUs per PSU produced the most accurate SDM predictions when the number of PSUs was high. When the number of PSUs was low and/or SSU costs were low, increasing clustering within PSUs can optimize sampling.

Climate change presents a major threat to biodiversity globally. Northern ecosystems, such as Canada's boreal forest, are predicted to experience particularly severe climate-induced changes. These changes may reduce the carrying capacity and habitat suitability of the boreal forest for many wildlife species. Boreal birds are susceptible to both direct and indirect effects of climate change, and several studies have predicted northward shifts in species distributions as temperatures become warmer. We forecasted spatially-explicit changes in the densities of 72 boreal landbird species using integrated climate change projections and a forest dynamics model in the Taiga Plains ecozone of the Northwest Territories (NT), Canada, over the 2011–2091 horizon. We 1) identified ''winner,'' ''loser,'' and ''bellringer'' species over short (2031) and long-term (2091) forecasts, 2) mapped landbird range and density changes under three contrasting Global Circulation Models (GCMs), and 3) quantify differences in landbird density predictions across a latitudinal gradient. Species that showed a moderate increase or decrease in their predicted abundance were considered ''winners'' and ''losers,'' respectively. Species that showed a marked increase or decrease – a doubling or halving – of their predicted abundance in all three GCMs, were termed ''bellringers''. From 2011–2031, only 2/72 (2.8%) were considered winners, and 3/72 (4.2%) were losers. From 2011–2091, the abundance of more species was predicted to change: 26/72 (36.1%) were winners, and 10/72 species (13.9%) were losers. Four species were considered bellringers: Gray-cheeked Thrush, White-crowned Sparrow, Fox Sparrow, and American Tree Sparrow. Overall, projected range shifts were strongly oriented along a southeast-to-northwest axis. Shifts to the north and south were evenly distributed among all three GCMs. Our results suggest that future climate-mitigated distribution shifts and population declines of boreal landbirds will require targeted conservation actions. They also highlight the importance of the NT as a potential refugium for many boreal-breeding landbird species in Canada.

Chickaloon Flats, Kenai National Wildlife Refuge, is an 11,000-ha tidal mudflat complex in upper Cook Inlet, Alaska. One-third (23 of 70) of Alaskan shorebird species use this protected coastal estuary stopover during migration. We conducted an isotopic approach to estimate probable breeding, staging and/or non-breeding origins of six shorebird species, some of high conservation concern, using Chickaloon during spring and fall migration of 2009 and 2010. We analyzed stable-hydrogen (delta H-2), carbon (delta C-13), and nitrogen (delta N-15) isotope ratios from feathers and performed a likelihood-based assignment to infer North and South American origins. Estimated molting distributions for Greater Yellowlegs (Tringa melanoleuca) occurred in southwest Alaska, and south-central Alaska for Short-billed Dowitcher (Limnodromus griseus caurinus). Lesser Yellowlegs (Tringa flavipes) likely molted in western Alaska and a latitudinal band across Canada and wintered throughout the contiguous United States. Least Sandpipers (Calidris minutilla) wintered from Oregon and south in North America but showed an isotopically similar possibility in Ecuador, Colombia, and Venezuela. Long-billed Dowitchers (Limnodromus scolopaceus) molted primaries across western United States and Canada. Pectoral Sandpipers (Calidris melanotos) likely molted near Rio de La Plata in southeastern South America. These results highlight the overall value of Chickaloon Flats as a stopover for long-distance shorebird migrants.

Conservation approaches that efficiently protect multiple values, such as the umbrella species concept, have been widely promoted with expected dramatic ecosystem changes. Due to its social and cultural importance, and recent declining trends, boreal populations of woodland caribou have been suggested as potential umbrella species for other declining taxa, such as boreal landbirds. We propose a generic pixel-based umbrella index that focuses on fine-grained habitat overlaps. In light of ongoing conservation efforts worldwide implementing area-based targets (e.g., 30% by 2030), we used a random neutral model as baseline, as opposed to a no-conservation scenario, which has been used elsewhere. We found that the conservation efficiency of caribou as an umbrella for 71 co-occurring landbirds-three of which are priority species-in the Northwest Territories, Canada, is generally lower than our random model, as 53% of the species presented negative umbrella index medians with the interquartile range not overlapping zero. We conclude that in cases where area-based targets drive decision-making and the issue at stake involves identifying which areas to conserve-not whether to conserve-woodland caribou may be a leaky umbrella for most co-occurring landbird species and these might need complementary conservation actions to be brought in from the rain.

Distributions of landbirds in Canadian northern forests are expected to be affected by climate change, but it remains unclear which pathways are responsible for projected climate effects. Determining whether climate change acts indirectly through changing fire regimes and/or vegetation dynamics, or directly through changes in climatic suitability may allow land managers to address negative trajectories via forest management. We used SpaDES, a novel toolkit built in R that facilitates the implementation of simulation models from different areas of knowledge to develop a simulation experiment for a study area comprising 50 million ha in the Northwest Territories, Canada. Our factorial experiment was designed to contrast climate effects pathways on 64 landbird species using climate-sensitive and non-climate sensitive models for tree growth and mortality, wildfire, and landbirds. Climate-change effects were predicted to increase suitable habitat for 73% of species, resulting in average net gain of 7.49 million ha across species. We observed higher species turnover in the northeastern, south-central (species loss), and western regions (species gain). Importantly, we found that most of the predicted differences in net area of occupancy across models were attributed to direct climate effects rather than simulated vegetation change, despite a similar relative importance of vegetation and climate variables in landbird models. Even with close to a doubling of annual area burned by 2100, and a 600 kg/ha increase in aboveground tree biomass predicted in this region, differences in landbird net occupancy across models attributed to climate-driven forest growth were very small, likely resulting from differences in the pace of vegetation and climate changes, or vegetation lags. The effect of vegetation lags (i.e., differences from climatic equilibrium) varied across species, resulting in a wide range of changes in landbird distribution, and consequently predicted occupancy, due to climate effects. These findings suggest that hybrid approaches using statistical models and landscape simulation tools could improve wildlife forecasts when future uncoupling of vegetation and climate is anticipated. This study lays some of the methodological groundwork for ecological adaptive management using the new platform SpaDES, which allows for iterative forecasting, mixing of modeling paradigms, and tightening connections between data, parameterization, and simulation.