Geese Winter Predicted Presence - Sacramento-San Joaquin Delta - Point Blue [ds3059]

This is one of 11 raster geotiff layers in the larger dataset "Predicted probability of waterbird group distributions in the Sacramento-San Joaquin Delta". This dataset was developed by Point Blue Conservation Science for a project funded through the Proposition 1 Delta Water Quality and Ecosystem Restoration Program administered by the California Department of Fish and Wildlife titled "Trade-offs and Co-benefits of Landscape Change Scenarios on Bird Communities and Ecosystem Services in the Sacramento-San Joaquin River Delta (Grant Agreement Number Q1996022). These data were used in spatial prioritization analyses for identifying Priority Bird Conservation Areas for riparian landbirds and waterbirds in the Delta (see related datasets: "Spatial prioritization for bird conservation in the Sacramento-San Joaquin Delta" and "Priority Bird Conservation Areas in the Sacramento-San Joaquin Delta"). Each layer in this dataset consists of the predicted probability of presence for an individual waterbird group resulting from fitting species distribution models to a recent representation of the land cover and land use in the Delta in 2018 (see related dataset: "Baseline and projected future land use and land cover in the Sacramento-San Joaquin Delta"). Species distribution models were developed from thousands of bird surveys for each of 6 waterbird groups during the non-breeding season, with separate models for the fall (Jul 15-Nov 15) and winter (Nov 17-Mar 5) seasons, including: herons/egrets (cicon), cranes (crane), dabbling ducks (dblr), diving ducks (divduck), geese (geese), and shorebirds (shore). However, no model (and thus no predicted distribution) was produced for diving ducks during the fall season due to insufficient data. See Dybala et al. (In review) for additional details on the development, assumptions, and limitations of the underlying species distribution models and the baseline landscape. In particular, waterbird surveys were limited to alfalfa, rice, irrigated pasture, and managed wetlands during both seasons, plus corn and winter wheat during the winter season. Consequently, predictions of species presence are limited to pixels with these land covers, resulting in some areas with no prediction. However, we assumed (and assigned) zero probability of presence for land cover classes we had defined as unsuitable a priori, including perennial crops, urban, and barren land cover classes.

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