Future Climate Change Shifts the Ranges of Major Encroaching Woody Plant Species in the Southern Great Plains, USA

Earth s Future, Journal Year: 2024, Volume and Issue: 12(7)

Published: July 1, 2024

Abstract Woody Plant Encroachment (WPE) is a key driver of grassland collapse in the Southern Great Plain (SGP), resulting series adverse ecological and socioeconomic consequences. Climate change will interact with ongoing WPE as it likely shift potential ranges species. In this study, we employed an ensemble approach integrating results from multiple Species Distribution Models to project future distribution four major species (Ashe juniper, honey mesquite, post oak, eastern redcedar) SGP across 21st century. The findings highlighted noteworthy trend: under climate conditions, for these were projected northward eastward. Of particular concern mesquite significant expansion range, potentially covering up two‐thirds SGP's non‐agricultural area by end Conversely, other three expected experience contraction their ranges. Ashe juniper may decline its current habitats central Texas but gain new northern Texas, Oklahoma, Kansas. suitable oak redcedar shrink eastward, primarily being restricted portions Oklahoma RCP4.5 smaller RCP8.5. provides scientific basis governments optimize allocation management resources implement timely practices control spread woody plants during early encroachment stage. Our study methodology applicable regions continents issues, including Africa, South America, Australia.

Language: Английский

Wildfire danger under changing climates in the southern Great Plains throughout the 21st century

Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 112994 - 112994

Published: Dec. 14, 2024

Language: Английский

Hydrological Response to Climate Change: McGAN for Multi-Site Scenario Weather Series Generation and LSTM for Streamflow Modeling

Atmosphere, Journal Year: 2024, Volume and Issue: 15(11), P. 1348 - 1348

Published: Nov. 9, 2024

This study focuses on the impacts of climate change hydrological processes in watersheds and proposes an integrated approach combining a weather generator with multi-site conditional generative adversarial network (McGAN) model. The incorporates ensemble GCM predictions to generate regional average synthetic series, while McGAN transforms these averages into spatially consistent data. By addressing spatial consistency problem generating this tackles key challenge site-scale impact assessment. Applied Jinghe River Basin west-central China, generated daily temperature precipitation data for four stations under different shared socioeconomic pathways (SSP1-26, SSP2-45, SSP3-70, SSP5-85) up 2100. These were then used long short-term memory (LSTM) network, trained historical data, simulate river flow from 2021 results show that (1) effectively addresses correlation generation; (2) future is likely increase flow, particularly high-emission scenarios; (3) frequency extreme events may increase, proactive policies can mitigate flood drought risks. offers new tool hydrologic–climatic assessment studies.

Language: Английский