The high climate vulnerability of western Mediterranean forests

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 895, P. 164983 - 164983

Published: June 21, 2023

Understanding the effects of climate change is one most challenging goals for biodiversity conservation. The forests Andalusia, in Southern Spain, are part an important Mediterranean Basin hotspot. However, great changes expected to occur this region, and there increasing need assess vulnerability its vegetation. We twelve forest types region that included European Directive 92/43/EEC as Habitats Community Interest (HCI). HCI natural habitat which danger, have a small range, or present outstanding example biogeographical regions Union. assessed by analyzing exposure level each type under two global models (MRI-CGCM3, predicts warmer wetter conditions, MIROC-ESM hotter drier conditions), emission scenarios (RCP4.5, representative concentration pathway stable emissions CO2, RCP8.5, highest CO2 emissions) mid- end-century time periods. analysis also includes sensitivity adaptive capacity dominant tree species compose type. An overall score was calculated type, model, scenario period. High-elevation those with high moisture requirements were more vulnerable change, while dominated thermophilic less resilient. worst impacts predicted model RCP8.5 end century (2070-2100), least climatic stress obtained MRI-CGCM3 RCP4.5 mid-century (2040-2070), still shows potential types. By century, entire domain will range between 32 % stressful situation (MRI-CGCM3 RCP4.5), 98 climatically (MIROC-ESM RCP8.5). be perceptible mid-century, suffering stress. "Andalusian oak forest" "Corylus wet "Mediterranean pine forest", "Olea Ceratonia forests" "oak vulnerable. This assessment identifies south Iberian Peninsula, provides context resource managers making decisions about how adapt change.

Language: Английский

Land Cover Changes of the Qilian Mountain National Park in Northwest China Based on Phenological Features and Sample Migration from 1990 to 2020

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(4), P. 1074 - 1074

Published: Feb. 16, 2023

The spatial and temporal variation analysis of land cover classification is important for studying the distribution transformation regional changes. Qilian Mountain National Park (QMNP), an ecological barrier in northwestern China, has lacked products long time series. Landsat images available on Google Earth Engine (GEE) make it possible to analyze changes over past three decades. purpose this study was generate a series datasets based method sample migration QMNP Northwest China. 5, 7, 8 field data were combined with multiple image features random forest algorithm complete from 1990 2020. results indicate that (1) Jeffries–Matusita (J-M) distance can reduce feature redundancy show elevation phenological have good differentiability among types easy mix classes; (2) every 10 years between 2020 consistent QMNP, there obvious differences east west part large area vegetation Sunan county central Tianzhu QMNP; (3) 30 years, forests grasslands decreased by 62.2 km2 794.7 km2, respectively, while shrubs increased 442.9 QMNP. conversion bare grassland interconversion different main patterns changes, mainly concentrated pastoral areas, meaning human activity factor changes; (4) when samples migrated 2010, 2000, 1990, overall accuracies 89.7%, 88.0%, 86.0%, 83.9%, respectively. conservation process closely related activities.

Language: Английский

GIS-Based Agricultural Land Use Favorability Assessment in the Context of Climate Change: A Case Study of the Apuseni Mountains

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(18), P. 8348 - 8348

Published: Sept. 17, 2024

With an emphasis on the effects of climate change, this study offers a thorough GIS-based assessment land use favorability in Apuseni Mountains. The Mountains, region characterized by its biodiversity and complex terrain, are increasingly vulnerable to impacts which threaten both natural ecosystems human activities. territory 11 territorial administrative units was selected for investigation because it shows more anthropogenic influence due migration people mountainous areas following COVID-19 pandemic, increased amount pressure area. Factors that describe area, soil characteristics, morphometric characteristics relief were used create classification present classes restrictiveness plots land, using quantitative GIS model determine main crops agricultural uses. current thus initially obtained, taking into account temperature precipitation values SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5 scenarios 2020–2099 time frame. results indicate variation statistical different classes, decrease 4.7% high class pastures, estimated 4.4% grassland, case orchards, situation reflects fluctuating variation. There is 6.4% very low according SSP2-4.5 (in reaching average 12.7 °C annual 895 mm), favorability, there increase falling better up 0.7%.

Language: Английский