Predictive multi‐scale occupancy models at range‐wide extents: Effects of habitat and human disturbance on distributions of wetland birds

Abstract

Aim: Predicting distributions is fundamental to ecology, yet hindered by spatially restricted sampling, scale-dependent relationships and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern. Location: USA. Methods:We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales.We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-scale analyses and scale optimization, and species-specific detectability for a suite of wide-ranging species.Results: Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban and hydrologic disturbances operating from local scales (100-500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at >1 scale. Five species showed evidence for continental-scale range contraction during the study. Main conclusions:We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data-driven, empirical SDMs built at the range-wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine-scale wetland vegetation missed important broadscale drivers of occupancy for marsh birds.

Species‐Habitat Relationships and Priority Areas for Marsh‐Breeding Birds in Ontario

“…Based on previous research, we predicted that occupancy of marsh‐breeding bird species would be positively associated with marsh cover and negatively associated with urban, agricultural, and forest cover (Tozer et al 2010, Quesnelle et al 2013, Tozer 2016, Panci et al 2017, Saunders et al 2019). We also predicted that species would be associated with landscape features at a variety of different scales (Stevens and Conway 2020), and that the majority of the new additional priority areas based on marsh‐breeding birds would fall outside existing priority areas based on waterfowl (Prairie Habitat Joint Venture 2014).…”

Mapping habitat suitability at range‐wide scales: Spatially‐explicit distribution models to inform conservation and research for marsh birds

“…We used raster regression to build spatially‐explicit models that predict breeding habitat quality. Predictions were generated from multiscale hierarchical occupancy models built using field data collected over a 14‐year period across the U.S. (Stevens & Conway, , ). We used the optimally predictive model for each species to predict occupancy probability as a function of rasters that measured habitat and disturbance covariates over a variety of spatial extents via moving‐window analyses (see Appendix A for details).…”

“…We also considered anthropogenic disturbances (agriculture, development, and modification of hydrology) at broader extents within a watershed, which were important for some species (Tables A1 and A2). Both the specific covariates and the spatial extents at which each covariate was measured were species‐specific and optimized for out‐of‐sample spatial prediction (i.e., to predict at new locations in space; Stevens & Conway, , ). These analyses allowed for fine‐resolution (30 m) prediction of habitat quality for each species based on ecological effects of habitat and disturbance variables that could operate over a range of spatial extents that are relevant to these birds (Glisson, Conway, Nadeau, & Borgmann, ; Stevens & Conway, ).…”

“…We demonstrate the utility of generating data‐driven, spatially‐explicit habitat models at range‐wide extents for species of conservation concern. We illustrate this for secretive marsh birds, a group of emergent‐wetland specialists whose populations have been negatively impacted by continental‐scale destruction and modification of wetlands (Eddleman, Knopf, Meanley, Reid, & Zembal, ; Stevens & Conway, ). Emergent wetlands have dramatically declined over the past century in North America, largely due to conversion of wetlands for human uses (Brinson & Malvárez, ; Dahl, ).…”

“…Emergent wetlands have dramatically declined over the past century in North America, largely due to conversion of wetlands for human uses (Brinson & Malvárez, ; Dahl, ). Marsh bird populations have declined, and the breeding ranges of several species are contracting (Conway, Eddleman, & Anderson, ; Conway & Sulzman, ; Eddleman et al, ; Stevens & Conway, ). Consequently, multiple species are federally protected by endangered species legislation in the United States, Canada, and Mexico (COSEWIC, , Diario Oficial de la Federacion, ).…”