DOI: 10.5281/zenodo.15800524
title: Data from: Refining Refugia: How local climate and vegetation shape Boreal Songbird persistence

description: Abstract



As climate change accelerates shifts in species distributions, identifying areas of climatic stability—or refugia—has become a critical strategy for biodiversity conservation. In forested ecosystems, the interaction between local climate conditions and vegetation structure can mediate species responses to environmental change, yet many broad-scale models overlook this complexity. This study investigates how topographically downscaled climate—accounting for local variation in temperature and moisture—affects the predicted distribution and climate-change refugia of forest-associated songbirds in Alberta, Canada.  Specifically, we



Quantify how adjusted versus unadjusted climate shifts the relative importance of climate and vegetation predictors in boosted‐regression‐tree models for 48 forest songbird species;

Compare model explanatory power and distribution projections under climate‐only and climate + vegetation scenarios;

Map climate‐change refugia under SSP3-7.0 (2071–2100) for three nesting‐habitat groups (coniferous, deciduous, wetland) using a 13-GCM ensemble.


Model performance improved for 19 species in full models and 15 in climate-only models, with coniferous‐associated species showing the greatest sensitivity to microclimatic adjustment (48 % gain in pseudo-R²). Refugia area estimates diverged dramatically: coniferous species lost 58 % of habitat under unadjusted climate but only 21 % when adjusted; deciduous species consistently gained refugia; wetland species were largely unaffected by downscaling. Spatial refugia “hotspots” occurred in central river valleys for deciduous, foothills for coniferous, and northern lowlands for wetland birds.

Fine-scale climate adjustment refines our understanding of species‐specific vulnerability and persistence, improving refugia identification for targeted conservation. These data support reuse in ecological modeling, conservation planning, and meta-analyses of climate sensitivity.

 

 
description: Refining Refugia: How local climate and vegetation shape Boreal Songbird persistence

Description of the data and file structure

This dataset supports the manuscript “Refining Refugia: How local climate and vegetation shape Boreal Songbird persistence”. It includes spatial predictions of current and future habitat suitability for 48 boreal forest songbird species in Alberta, Canada. The models explore how macroclimate (unadjusted) and topographically downscaled (adjusted) climate variables, with and without vegetation covariates, influence species distributions and climate-change refugia under SSP3-7.0 for the 2071–2100 period.

Files and variables

The dataset is organized into four zip archives, each corresponding to a different species distribution model:





Model 1: Occupancy ~ Vegetation + Habitat + Climate (Corrected for local topography) (model1.zip)




Model 2: Occupancy ~ Vegetation + Habitat + Climate (Uncorrected) (model2.zip)




Model 3: Occupancy ~ Climate only (Corrected for local topography) (model3.zip)




Model 4: Occupancy ~ Climate only (Uncorrected) (model4.zip)



Each model was implemented using boosted regression trees and trained on autonomous recording unit (ARU) detections and fine-scale environmental covariates.

Folder Structure

Each zip archive contains two subfolders:





current/:





Binary predictions: Thresholded presence/absence rasters based on the mean prevalence threshold per species.




Continuous predictions: Raw model outputs representing relative habitat suitability (0–1) per species.






future/:







Binary overlap predictions: Areas of persistence where current and future binary predictions intersect per species.




Continuous predictions: Future suitability under a 13-GCM ensemble for SSP3-7.0 (2071–2100) per species.




Refugia predictions: Stacked refugia prediction for each habitat associated group. _nostd_ are the raw overlap of different species, while the other files have been standardized from 0-1.



File Naming Convention

Each raster file has a general structure:[model_type]_[climate_input]_[scenario]_[prediction``type]``[species_code].tif

Where:





model_type = M1, M2, M3, or M4. Also indicated by the file name: 





_vegt_habitat_climate_corrected_: Vegetation + Habitat + Climate (Corrected for local topography)




_vegt_habitat_climate_uncorrected_: Vegetation + Habitat + Climate (UNcorrected)




_no_vegt_habitat_climate_corrected_: Climate only (corrected for local topography)




_no_vegt_habitat_climate_uncorrected_Climate only (UNcorrected)






climate_input = adjusted or unadjusted




scenario = current or future




prediction_type = binary, continuous, or overlap




species_code = four-letter AOU code (e.g., BBWA for Bay-breasted Warbler)



Example: BBWA_M1_adjusted_future_continuous.tif

File Format and Projection





All rasters are in GeoTIFF format




Spatial resolution: 250 meters




Projection: is described at the file projection_info.prj



Access information

Other publicly accessible locations of the data:





Acoustic data collected with Autonomous Recording Units is available at Wildtrax




https://wildtrax.ca/ 




READ_ME_MODEL_DESCRIPTION.txt contains the general description of the models.