1 2 Bounechada mustapha,  1 * Allag Fateh and 1Fenni Mohamed

Faculty of Natural Sciences and Life, UFAS Setif 1 University, Algeria

2. Laboratory research LADPVA

* author presented

Abstract

Objective: The objective of this research is to assess the impact of climate change on wildlife populations and ecosystems, focusing on how changing environmental conditions affect species distribution, behavior, and survival.

Methodology: This study employs artificial neural networks (ANNs) to analyze extensive datasets that include climate variables, species distribution records, and ecological indicators. By integrating data from satellite imagery, climate models, and field studies, the ANN will be trained to identify patterns and predict wildlife responses to various climate scenarios.

Results: The analysis reveals significant correlations between climate change factors—such as temperature increases, altered precipitation patterns, and habitat loss—and shifts in wildlife populations. Specific findings indicate that certain species are at a heightened risk of extinction, while others may adapt or migrate to new habitats. The model provides valuable predictions on future wildlife distributions under different climate scenarios.

Conclusion: The findings underscore the urgent need for conservation strategies that consider the impacts of climate change on wildlife. By utilizing artificial neural networks, this research offers a robust framework for predicting wildlife responses, informing policymakers and conservationists in their efforts to mitigate the effects of climate change and protect vulnerable species and ecosystems.

Key words: Climate models, Wildlife, Intelligent modeling, ANN.