A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest

Authors

Andrea Paz, CUNY Graduate CenterFollow
Thiago S. Silva, Universidade Estadual Paulista
Ana C. Carnaval, CUNY City CollegeFollow

Document Type

Article

Publication Date

2022

Abstract

Monitoring biodiversity change is key to effective conservation policy. While it is difficult to establish in situ biodiversity monitoring programs at broad geographical scales, remote sensing advances allow for near-real time Earth observations that may help with this goal. We combine periodical and freely available remote sensing information describing temperature and precipitation with curated biological information from several groups of animals and plants in the Brazilian Atlantic rainforest to design an indirect remote sensing framework that monitors potential loss and gain of biodiversity in near-real time. Using data from biological collections and information from repeated field inventories, we demonstrate that this framework has the potential to accurately predict trends of biodiversity change for both taxonomic and phylogenetic diversity. The framework identifies areas of potential diversity loss more accurately than areas of species gain, and performs best when applied to broadly distributed groups of animals and plants.

Comments

This article was originally published in PeerJ, available at http://doi.org/10.7717/peerj.13534

This work is distributed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).