DOI: 10.6078/d1gb02
title: Data and Code for "Drought Influences Habitat Associations and Abundances of Birds in California's Central Valley"

description: As climate change increases the frequency and severity of droughts in many
 regions, conservation during drought is becoming a major challenge for
 ecologists. Droughts are multidimensional climate events whose impacts may
 be moderated by changes in temperature, water availability, or food
 availability, or some combination of these. Simultaneously, other
 stressors such as extensive anthropogenic landscape modification may
 synergize with drought. Useful observational models for guiding
 conservation decision-making during drought require multidimensional,
 dynamic representations to disentangle possible drought impacts, and
 consequently they will require large, highly resolved data sets. In this
 paper, we develop a multi-model predictive framework for assessing how
 drought impacts vary with species, habitats, and climate
 pathways. We found that while fewer than a quarter (16/66) of
 species experienced abundance declines during drought, nearly half of all
 species (27/66) changed their habitat associations during drought. Among
 species that shifted their habitat associations, use of natural habitats
 declined during drought while use of developed habitat and perennial
 agricultural habitat increased. Our findings suggest that birds
 take advantage of agricultural and developed land with artificial
 irrigation and heat-buffering microhabitat structure, such as in orchards
 or parks, to buffer drought impacts. A working lands approach that
 promotes biodiversity and mitigates stressors across a human-induced water
 gradient will be critical for conserving birds during drought.
description: We used a multi-model counterfactual analysis combining
 predictive linear mixed models and N-mixture models to characterize the
 multidimensional impacts of drought on 66 bird species. We analyzed counts
 from the eBird participatory science dataset between 2010 and 2019 and
 produced species, as well as habitat-specific estimates of the impact of
 drought on relative abundance.
description: As described in the README, all data are available from other
 publicly available datasets therein attributed. The analyses were run most
 recently in R version 4.3.1 for Windows. The following packages are
 required to reproduce results: rgdal, sp, SF, rgeos, raster, tidyverse,
 prism, lubridate, taxadb, taxalight, nimble, nimbleEcology, gridExtra,
 viridis, parallel, brms, MCMCvis. Refer to the associated GitHub
 repository, code and README files for detailed usage notes.
  
description: # Data and Code for "Drought influences habitat associations and
 abundances of birds in California's Central Valley" --- This
 project generated data files and conducted analyses reusing publicly
 available data sources, as attributed below. For the eBird dataset, we
 queried all complete checklist observations of birds in California, USA,
 from 2010 to 2019. * *eBird. 2021*. Citation: eBird: An online database of
 bird distribution and abundance [web application]. eBird, Cornell Lab of
 Ornithology, Ithaca, New York. Available:
 [http://www.ebird.org](http://www.ebird.org). (Accessed: August 1, 2020).
 Additionally, we used several other data inputs from publicly available
 repositories for the analysis: * *Functional Vegetation from LANDFIRE*.
 Citation: LANDFIRE. (2020). LANDFIRE Remap 2016 Existing Vegetation Type
 (EVT) CONUS. Earth Resources Observation and Science Center (EROS), U.S.
 Geological Survey.
 [http://datainventory.doi.gov/id/dataset/2d4c9eb438401e25f0de539924afcae2](http://datainventory.doi.gov/id/dataset/2d4c9eb438401e25f0de539924afcae2) * *SPEI from SPEIbase*. Citation: Beguería, S. (2022). sbegueria/SPEIbase: Version 2.7 (v2.7) [Computer software]. Zenodo. [https://doi.org/10.5281/zenodo.5864391](https://doi.org/10.5281/zenodo.5864391) * *EVI from MODIS*. Citation: Vermote, E., & Wolfe, R. (2023). MOD09GA MODIS/Terra Surface Reflectance Daily L2G Global 1kmand 500m SIN Grid V006 [Data set] 2015. [https://doi.org/10.5067/MODIS/MOD09GA.006](https://doi.org/10.5067/MODIS/MOD09GA.006) * *NDWI from Landsat*. Citation: USGS. (2022). *USGS Landsat 7 Collection 1 Tier 1 and Real-Time data Raw Scenes [Data set]*. [https://www.usgs.gov/landsat-missions/landsat-collection-1](https://www.usgs.gov/landsat-missions/landsat-collection-1) * Temperature and precipitation from PRISM. Citation: Hart, E. M., & Bell, K. (2015). *prism: Download data from the Oregon prism project*. [https://github.com/ropensci/prism](https://github.com/ropensci/prism) Refer to the README accompanying the code and the [GitHub repository](https://github.com/dochvam/drought_CV_eBird_reproducible) for more information about the requirements for reproducing the findings reported in the associated manuscript.