📚 Volume 29, Issue 3
📋 ID: 3mrr0u0
Authors
Dr. Mei Ling Zhang, Prof. Carlos Rivera, Dr. Amara Singh
, Yang Wagner
Institute of Environmental Sciences, University of Cape Town, South Africa; Department of Ecology, University of São Paulo, Brazil; School of Earth and Environmental Sciences, University of Delhi, India
Keywords
Ecological Modeling
Climate Change
Plant Distribution
Biodiversity
Conservation
Remote Sensing
Abstract
This study presents an integrated ecological modeling approach to predict the distribution of plant species under various climate change scenarios. The research utilizes a combination of remote sensing data, climate models, and species occurrence records to develop predictive models for plant distribution shifts. The focus is on assessing the impact of temperature, precipitation changes, and extreme weather events on biodiversity hotspots. The methodology employs machine learning techniques to analyze complex interactions between biotic and abiotic factors influencing plant habitats. The findings aim to guide conservation strategies by identifying vulnerable species and regions requiring immediate attention.
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📝 How to Cite
Dr. Mei Ling Zhang, Prof. Carlos Rivera, Dr. Amara Singh , Yang Wagner (2022).
"INTEGRATED ECOLOGICAL MODELING FOR PREDICTING PLANT SPECIES DISTRIBUTION IN CHANGING CLIMATES".
Wulfenia, 29(3).
