Monitoring boreal avian populations: how can we estimate trends and trajectories from noisy data?

Roy, Christian; Michel, Nicole L.; Handel, Colleen M.; Wilgenburg, Steven L. Van; Burkhalter, J. Curtis; Gurney, Kirsty E. B.; Messmer, David J.; Princé, Karine; Rushing, Clark S.; Saracco, James F.; Schuster, Richard; Smith, Adam C.; Smith, Paul A.; Sólymos, Péter; Venier, Lisa A.; Zuckerberg, Ben

doi:10.5751/ace-01397-140208

Cited by 19 publications

(17 citation statements)

References 194 publications

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“…Other programs collect effort data that can be used to analytically control for variation, such as National Audubon Society’s Christmas Bird Count (Soykan et al 2016) and eBird (Hochachka et al 2012). However, few community science programs collect the ancillary data (e.g., distance, time of first detection) or utilize the structured protocols (e.g., repeat surveys, double observers) needed to produce accurate occupancy or abundance estimates corrected for imperfect detection (Roy et al 2019). Climate Watch was designed as a structured community science program, which uses spatially repeated surveys within predefined grid cells to enable estimates of detection probability and, consequently, occupancy probability.…”

Section: Introductionmentioning

confidence: 99%

Community science validates climate suitability projections from ecological niche modeling

Saunders

Michel

Bateman

et al. 2020

Ecological Applications

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Climate change poses an intensifying threat to many bird species and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated in situ and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision‐making. Using data from a novel, large‐scale community science program, we developed dynamic occupancy models to validate near‐term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species’ ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species–climate relationships. We also included a Bird Conservation Region strata‐level random effect to examine among‐strata variation in occupancy that may be attributable to land‐use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species’ ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. Our findings lend much‐needed support to the use of ENM projections for addressing questions about potential climate‐induced changes in species’ occupancy dynamics. More broadly, our work highlights the value of community scientist observations for ground‐truthing projections from statistical models and for refining our understanding of the processes shaping species’ distributions under a changing climate.

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Section: Introductionmentioning

confidence: 99%

Community science validates climate suitability projections from ecological niche modeling

Saunders

Michel

Bateman

et al. 2020

Ecological Applications

Self Cite

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“…When that assumption is violated, however, inference is compromised. Without identifying the relative contributions of each process affecting the index value, the potential effectiveness of management actions can be limited (Roy et al 2019). For example, declines in abundance caused by human factors (e.g., overharvest, disturbance) may be masked in an index if temporary immigration increases in the area covered by the index (i.e., possible source-sink dynamics).…”

Section: Discussionmentioning

confidence: 99%

Integrating distance sampling survey data with population indices to separate trends in abundance and temporary immigration

et al. 2022

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Managers rely on accurate estimators of wildlife abundance and trends for management decisions. Despite the focus of contemporary wildlife science on developing methods to improve inference from wildlife surveys, legacy datasets often rely on index counts that lack information about the detection process. Data integration can be a useful tool for combining index counts with data collected under more rigorous designs (i.e., designs that account for the detection process), but care is required when datasets represent different population processes or are mismatched in space and time. This can be particularly problematic in cases where animals aggregate in response to a spatially or temporally limited resource because individuals may temporarily immigrate from outside the study area and be included in the abundance index. Abundance indices based on brown bear (Ursus arctos) feeding aggregations within coastal meadows in early summer in Lake Clark National Park and Preserve, Alaska, USA, are one such example. These indices reflect the target population (brown bears residing within the park) and temporary immigrants (i.e., bears drawn from outside the park boundary). To properly account for the effects of temporary immigration, we integrated the index data with abundance data collected via park-wide distance sampling surveys, the latter of which properly addressed the detection process. By assuming that the distance data provide inference

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“…Our results expand on previous analysis of black and surf scoters by Reed et al (2017), which also identified the Barrenlands as an area of high multi-species importance. The areas identified by our models as being of highest multi-species importance, including the Barrenlands and parts of northern Quebec, fall outside the boundaries of most North American breeding bird surveys including the Waterfowl Breeding and Population Habitat Survey (Roy et al 2019); however, the Barrenlands are currently being targeted for additional pilot surveys to quantify the extent of use by nesting sea ducks (Reed et al 2017). In our analysis, no sites were in the top 10% of suitable breeding habitats for all species.…”

Section: Discussionmentioning

confidence: 99%

Assessing year‐round habitat use by migratory sea ducks in a multi‐species context reveals seasonal variation in habitat selection and partitioning

et al. 2020

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Long‐distance migration presents complex conservation challenges, and migratory species often experience shortfalls in conservation due to the difficulty of identifying important locations and resources throughout the annual cycle. In order to prioritize habitats for conservation of migratory wildlife, it is necessary to understand how habitat needs change throughout the annual cycle, as well as to identify key habitat sites and features that concentrate large numbers of individuals and species. Among long‐distance migrants, sea ducks have particularly complex migratory patterns, which often include distinct post‐breeding molt sites as well as breeding, staging and wintering locations. Using a large set of individual tracking data (n = 476 individuals) from five species of sea ducks in eastern North America, we evaluated multi‐species habitat suitability and partitioning across the breeding, post‐breeding migration and molt, wintering and pre‐breeding migration seasons. During breeding, species generally occupied distinct habitat areas, with the highest levels of multi‐species overlap occurring in the Barrenlands west of Hudson Bay. Species generally preferred flatter areas closer to lakes with lower maximum temperatures relative to average conditions, but varied in distance to shore, elevation and precipitation. During non‐breeding, species overlapped extensively during winter but diverged during migration. All species preferred shallow‐water, nearshore habitats with high productivity, but varied in their relationships to salinity, temperature and bottom slope. Sea ducks selected most strongly for preferred habitats during post‐breeding migration, with high partitioning among species; however, both selection and partitioning were weaker during pre‐breeding migration. The addition of tidal current velocity, aquatic vegetation presence and bottom substrate improved non‐breeding habitat models where available. Our results highlight the utility of multi‐species, annual‐cycle habitat assessments in identifying key habitat features and periods of vulnerability in order to optimize conservation strategies for migratory wildlife.

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Monitoring boreal avian populations: how can we estimate trends and trajectories from noisy data?

Cited by 19 publications

References 194 publications

Community science validates climate suitability projections from ecological niche modeling

Community science validates climate suitability projections from ecological niche modeling

Integrating distance sampling survey data with population indices to separate trends in abundance and temporary immigration

Assessing year‐round habitat use by migratory sea ducks in a multi‐species context reveals seasonal variation in habitat selection and partitioning

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