Climate change effects on animal presence in the Massaciuccoli Lake basin

Ecological Informatics, Journal Year: 2024, Volume and Issue: 81, P. 102644 - 102644

Published: May 16, 2024

Big-data mining approaches based on Artificial Intelligence models can help forecast biodiversity changes before they happen. These predict macroscopic species distribution patterns and trends that inform preventive measures to avoid the loss of ecosystem functions services. They can, therefore, study mitigate climate change implications conservation in fragile ecosystems. Wetlands are particularly ecosystems where poses severe risks has dramatically reduced their size over past century, with profound consequences Through big-data approaches, we future wetland context change. This paper proposes such predictive analysis for a specific wetland: The Massaciuccoli Lake basin Tuscany, Italy. is critical tourist attraction due its rich biodiversity, making it an area interest citizens, tourists, scientists. However, region's suitability native non-native at risk land-use Using machine-learning models, potential effects animal spatial under different greenhouse gas emission scenarios. results suggest habitat generally improved from 1950 today, presumably owing targeted strategies adopted area, but will severely reduce bird by 2050 while favouring several insect species' proliferation other change, even medium-emission scenario. lead significant basin's biodiversity. Our methodology adaptable basins, being fully open data models. spatially explicit modelling used this research provides valuable information policymakers planners, complementing traditional trend analyses.

Language: Английский

Distinct assembly mechanisms of the abundant and rare bacterial taxa in plateau habitats

Applied Soil Ecology, Journal Year: 2025, Volume and Issue: 209, P. 106053 - 106053

Published: March 29, 2025

Language: Английский