Data from: Forest cover drives bird occupancy across guilds and habitats in a Colombian coffee farming landscape

Description for "Data file - Botero-Delgadillo et al.xlsx" file. Data from: Forest cover drives bird occupancy across guilds and habitats in a Colombian coffee farming landscapeMS Reference Number: JAPPL-2025-01356Article DOI: Pending Please address questions to: Esteban Botero D.Director of Conservation ScienceSELVA: Research for Conservation in the Neotropics (https://www.selva.org.co)Research AssociateBird Friendly Program, Smithsonaina MIgratory Bird Center (https://nationalzoo.si.edu/migratory-birds/bird-friendly)e-mail: [e-mail]; [e-mail] ========================================================================================================================================================================== General information: This repository contains bird community, landcover, and vegetation data collected in coffee agroforestry systems and forest habitats in the Eastern Andes of Colombia (Cundinamarca Department). Data were collected during two seasons (July–August 2021 and December 2021–January 2022) to evaluate how landscape composition and local vegetation structure influence bird occupancy across ecological guilds. Bird data were obtained from repeated 10-minute point-count surveys conducted at 119 sampling stations distributed across sun coffee, shade coffee, and forest habitats. Each point was surveyed eight times (four per season), resulting in 952 surveys. The dataset includes bird detections, survey metadata, habitat classification, local vegetation measurements, and landscape metrics. Additionally, we provide an annotated R script required to reproduce all analyses and figures using the R statistical environment (version 4.0.2; R Development Core Team, 2020). This script is provided as “R code – Data formatting and Bayesian MSOMs.R”. The raw dataset is provided as a single Excel file containing seven spreadsheets, which are briefly described below. The file itself includes a “README” sheet with detailed information on data structure, variable definitions, and metadata (first sheet). ************************************************************************************* ********** Spreadsheet 1: "README" **********This spreadsheet contains instrctions to dataset conventions and variable codes and units. ********** Spreadsheet 2 "eBird raw data" **********This spreadsheet contains bird point-count data downloaded from the eBird open-access platform (Sullivan et al., 2009; https://ebird.org), including all detections used in the analyses. ********** Spreadsheet 3 "Local vegetation & landscape" **********This spreadsheet contains local vegetation structure data collected at the 119 bird point-count stations established in coffee and forest habitats to characterize bird communities. ********** Spreadsheet 4 "Data for MSOM - NM" ********** This spreadsheet contains formatted data for the non-migratory season (NM; July–August 2021), ready to be used with the annotated script (“R code – Data formatting and Bayesian MSOMs.R”) to fit Bayesian community occupancy models in the spOccupancy package (Doser et al., 2022) in R. ********** Spreadsheet 5 "Data for MSOM - M" ********** This spreadsheet contains formatted data for the migratory season (M; December 2021–January 2022), prepared for use with the same annotated script to fit Bayesian community occupancy models. ********** Spreadsheet 6 "Species coeffs NM model" ********** This spreadsheet contains species-specific coefficients for all model parameters derived from the community occupancy model for the non-migratory season. ********** Spreadsheet 7 "Species coeffs M model" **********This spreadsheet contains species-specific coefficients for all model parameters derived from the community occupancy model for the migratory season. ************************************************************************************* ===================================================================================== Methodological information (for more details, please see the related manuscript): Survey sites were selected using a stratified random design based on a custom landcover classification that distinguished forest, sun coffee, shade coffee, open areas, and human-dominated land. Point-count stations were distributed across a gradient of forest cover (4–62% within a 2 km radius) and ranged in elevation from 1,105 to 1,855 m. Bird surveys followed standardized 10-minute point counts within a 30 m radius, recording visual and auditory detections. Surveys were conducted by two trained observers using a fully crossed design across seasons. Flyovers were excluded to ensure habitat-specific detections. Local vegetation structure was quantified within a 30 m radius using metrics of canopy cover, canopy height, basal area, and tree species richness. These variables were summarized using principal components analysis to derive indices of vegetation complexity and heterogeneity. Landscape metrics included percent open area within 500 m and percent forest cover within a 2 km radius. Bird occurrence data were analyzed using Bayesian hierarchical multi-species occupancy models implemented in the spOccupancy R package. Models incorporated detection and occupancy processes with predictors at multiple spatial scales, including habitat type, vegetation structure, landscape composition, and elevation. Random effects accounted for spatial clustering among municipalities. Model outputs were used to estimate occupancy responses for the full bird community, ecological guilds (defined by habitat association and diet), and species of conservation concern. Additional analyses included post hoc guild-level inference, range-size relationships, and identification of threshold values in forest cover and vegetation complexity to inform sustainability recommendations. An annotated script required for data processing, modeling, prediction, and figure generation is included in the repository. ************************************************************************************* References: Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2022). spOccupancy: An R package for single-species, multi-species, and integrated spatial occupancy models. Methods in Ecology and Evolution, 13, 1670–1678. https://doi.org/10.1111/2041-210X.13897 R Development Core Team (2020). R: a language and environment for statistical computing (version 4.0.2). R Foundation for Statistical Computing, Vienna, Austria. http://www.R.project.org Sullivan, B. L., Wood, C. L., Iliff, M. J., Bonney, R. E., Fink, D., & Kelling, S. (2009). eBird: a citizen-based bird observation network in the biological sciences. Biological Conservation, 142, 2282–2292. https://doi.org/10.1016/j.biocon.2009.05.006 ==========================================================================================================================================================================