Faster, better, smarter ecological niche modeling and species distribution modeling
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Updated
Jan 3, 2023 - R
Faster, better, smarter ecological niche modeling and species distribution modeling
Simple layers for species distribution modeling and bioclimatic data
Work with species distributions in Julia
📦 🌎 ⛰️ ☀️ ☁️ 🌱 Get climatic and other environmental variables
🌳 🌍 📓 Code and data for Tagliari et al. 2021, Not all species will migrate poleward as the climate warms: the case of the seven baobab species in Madagascar. Global Change Biology.
Generates null models for species occurrence data
ABMI mammal species density estimation and habitat modeling
All-in-one model based custom predictions
Rossman R., Yackulic C., Saunders S.P., Reid J., Davis R., and Zipkin E.F. 2016. Dynamic N-occupancy models: estimating demographic rates and local abundances from detection-nondetection data. Ecology. 97: 3300-3307.
Science Centre Development Website
Sipe H, IN Keren, and SJ Converse. 2023. Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales. Ecology and Evolution.
Alberta bird models using ABMI+BAM+BBS data
Application of Taylor Diagrams to Ecological Niche Models/Species Distribution Models
A SDM pipeline implemented in R with {targets}
The script provides a guideline to prepare data for the estimation of distribution range, create and download NDVI data, generate environmental variables from Digital Elevation Models, NDVI datasets and Climate-EU model, calculate landscape metrics for a species’ habitat using binary habitat maps, conduct LASSO and Elastic Net and run GLMs.
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