Community science validates climate suitability projections from ecological niche modeling

Abstract

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.

Half‐Century Winter Duck Abundance and Temperature Trends in the Mississippi and Atlantic Flyways

“…These predictions will be interesting to monitor and test, either through continued CBC surveys or independent ground or aerial surveys and analyses (Masto et al 2020). Empirical evidence from other targeted community science surveys suggest that birds are colonizing new areas as predicted by climate-based range models (Saunders et al 2020), and local range contractions have also been observed (Wiens 2016).…”

The value of local community knowledge in species distribution modelling for a threatened Neotropical parrot

“…Recent studies have shown that web-based citizen science projects and online biodiversity databases can be used to build reliable species distribution models (e.g. Saunders et al 2020;Langham et al 2015;Fournier et al 2017). This study presents evidence that in areas where there are substantial barriers to web-based citizen science projects, for example in socio-economically deprived areas (e.g.…”

“…Often this information is used to supplement 'expert' data by guiding further field surveys (Hart & Upoki 1997;O'Brien et al 1998;Chaiyes et al 2017) but in some cases it is shown to be just as accurate as the equivalent 'expert' data, providing that some form of filter for reliability is incorporated (Polfus et al 2014). Recently, a number of studies have even shown that georeferenced occurrence data collected through citizen science platforms and online biodiversity databases such as eBird, can be used to build accurate SDMs (Bradsworth et al 2017;Coxen et al 2017;Fournier et al 2017;Saunders et al 2020). However, it is important to note that all opportunistically collected citizen science data present additional challenges such as spatial biases and variation in observer skill (Isaac and Pocock 2015;Johnston et al 2020) and online recording schemes such as eBird create barriers by requiring observations to be collected and submitted in a particular way.…”

The unrealized potential of community science to support research on the resilience of protected areas

“…In fact, many community science‐based phenology networks have already been set up with the goal of tracking climate shifts and long‐term community science data sets have already been used to link change in phenological events in both birds and plants with climate change (Donnelly et al, 2014; Gonsamo, Chen, & Wu, 2013). Community science programs have also been established to conduct surveillance monitoring, to analyze imagery data (Kosmala et al, 2016), and even validate climate models (Saunders et al, 2020). In addition, community science has been used to track evolutionary change of species with shorter generations (Silvertown et al, 2011; Worthington et al, 2012).…”