Response of vegetation variation to climate change and human activities in semi-arid swamps

Spatio-Temporal Heterogeneity of Ecological Quality in a Typical Dryland of Northern China Driven by Climate Change and Human Activities

With the intensification of climate change and anthropogenic impacts, the ecological environment in drylands faces serious challenges, underscoring the necessity for regionally adapted ecological quality evaluation. This study evaluates the suitability of the original Remote Sensing Ecological Index (oRSEI), modified RSEI (mRSEI), and adapted RSEI (aRSEI) in a typical dryland region of northern China. Spatio-temporal changes in ecological quality from 2000 to 2022 were analyzed using Theil-Sen median trend analysis, the Mann-Kendall test, and the Hurst exponent. Multiple regression residual analysis quantified the relative contributions of climate change and human activities to ecological quality changes. Results showed that (1) the aRSEI was the most suitable index for the study area; (2) observed changes exhibited significant spatial heterogeneity, with improvements generally in the inner areas of the Yellow River and declines in the outer areas; and (3) changes in ecological quality were primarily driven by climate change and human activities, with human activities dominating from 2000 to 2011 and the influence of climate change increasing from 2012 to 2022. This study compares the efficacy of RSEIs in evaluating dryland ecological quality, identifies spatio-temporal change patterns, and elucidates driving mechanisms, offering scientific evidence and policy recommendations for targeted conservation and restoration measures to address future changes in dryland regions.

Spatio-temporal variations and multi-scenario simulation of landscape ecological risk in the drylands of the Yellow River Basin

Over the past decades, the drylands of the Yellow River Basin (YRBD) have undergone profound changes in landscape patterns and ecological dynamics, significantly impacting regional sustainable development. To assess the spatio-temporal variations of ecological risk in the YRBD and provide guidance for sustainable regional development, we constructed a coupled Land Use-Landscape Ecological Risk Model-Geographical Detector-PLUS framework for the assessment, analysis, and simulation of dryland landscape ecological risk (LER). The main findings are as follows: (1) Between 2000 and 2020, the area of built-up land, forest, grassland, and water in the YRBD increased, while the area of unused land and cropland decreased. (2) LER exhibited significant spatial heterogeneity, dominated by Sub-low and Low risks. High risk areas were primarily located in the western Inner Mongolia Plateau, whereas Low risk areas were prevalent in the Loess Plateau, with an overall decline in risk levels over the 20 years. (3) Water resources, ecological status, and human activities are the main driving factors affecting LER, with the impact of human activities becoming increasingly significant over the past 20 years. (4) Under three development scenarios in 2030, the LER is projected to further decrease, although the impact of these scenarios varies across different research sub-regions. Notably, the Ecological Priority Scenario emerges as more effective in mitigating regional LER. (5) Developing precise land use policies tailored to regional characteristics, continuously implementing ecological restoration projects, strengthening water resource management, and enhancing monitoring capabilities are effective ways to reduce LER in the YRBD. This study systematically quantified the impact of different development scenarios on LER in the YRBD, revealing its spatio-temporal characteristics, and emphasized the importance of planning guidance, ecological restoration, and risk monitoring to align regional development with ecological protection. The findings provide scientific evidence for ecological protection and sustainable development in the YRBD and other drylands, offering valuable insights for global dryland ecological risk management.

Assessing the effects of climate and human activity on vegetation change in Northern China

Fractional vegetation cover (FVC) has changed significantly under various disturbances over northern China in recent decades. This research examines the dynamics of FVC and how it is affected by climate and human activity during the period of 1990-2018 in northern China. The effects of climate change (i.e., temperature, precipitation, solar radiation, and soil moisture) and human activity (socioeconomic data and land use) on vegetation coverage change in northern China from 1990 to 2018 were quantified using the Sen + Mann-Kendall test, partial correlation analysis, and structural equation modelling (SEM) methods. The findings of this research indicate the following: (1) From 1990 to 2018, the overall trend in FVC in northern China was increased. The areas with obvious increases were mainly situated on the northern slope of Tianshan Mountains, Xinjiang, the Loess Plateau, the Northeast China Plain, and the Sanjiang Plain, while the areas with distinct degradation were located in the Inner Mongolia Plateau, the Changbai Mountain and the eastern part of north China. (2) In the past 29 years, the FVC in northern China has been mainly affected by precipitation and soil moisture. (3) Based on structural equation modelling, we discovered that certain variables impacted the main factors influencing the amount of FVC in northern China. Human activity has had a larger impact on FVC than climate change. Our findings can accelerate the comprehension of vegetation dynamics and their underlying mechanisms and provide a theoretical basis for regional ecological environmental protection.

Effects of climate warming and human activities on the distribution patterns of Fritillaria unibracteata in eastern Qinghai-Tibetan Plateau

Fritillaria unibracteata is an endangered medicinal material species endemic to the Qinghai Tibet Plateau, and belongs to the national Class III endangered plant. In addition to expelling wind and removing damne, it also warms menstruation and relieves pain in clinic use of tranditional Chinese medicine. In recent years, affected by the destruction of shrubs and climate change, the habitat of F. unibracteata wild resources has been seriously damaged, indicating of great significance to predict its potential suitable habitat using MaxEnt model. The AUC values without human activities were 0.983 ± 0.013-0.988 ± 0.001, while it is 0.982 ± 0.015-0.989 ± 0.000 with human activities, justifying their applications for predicting the potential areas of F. unibracteata. Without human activities, there were 8.47 × 104 km2 of highly suitable habitats in northern Sichuan, southern Gansu and southeastern Qinghai. But the poorly, moderately and highly suitable areas of F. unibracteata have decreased to 33.8 × 104 km2, 9.66 × 104 km2 and 6.64 × 104 km2 due to human activities. Environmental variables affecting F. unibracteata distribution included the minimum temperature in the coldest month (-16.89--4.96 °C), annual precipitation (416.64-866.96 mm), temperature annual range (24.83-31.97 °C), elevation (2879.69-3981.82 m), human footprint (2.58-23.66) and mean UV-B of highest month (7381.92-8574.27 kJ/m2). In the 2050s and 2090s, human activities would significantly reduce the highly suitable habitats of F. unibracteata. Under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, the centroid would move to the low latitude area from the current position first, and then to a high latitude area. Wild resources of F. unibracteata in China can be effectively conserved based on our results.

Effects of hydrothermal factors and human activities on the vegetation coverage of the Qinghai-Tibet Plateau

A systematic understanding of the spatio-temporal changes and driving factors in the Qinghai-Tibet Plateau holds significant scientific reference value for the future of ecological sustainable development. This paper utilizes MODIS normalized difference vegetation index (NDVI) and meteorological data to investigate the spatio-temporal changes and driving factors of vegetation coverage in the Qinghai-Tibet Plateau from 2001 to 2020. Methods employed include the dimidiate pixel model, trend analysis, partial correlation analysis, and residual analysis. The results demonstrate a generally fluctuating upward trend in vegetation coverage across the Tibetan Plateau over the past two decades, with spatial expansion occurring from northwest to southeast. Vegetation coverage exhibits a positive correlation with climate factors. Approximately 60.7% of the area showed a positive correlation between vegetation fractional cover (FVC) and precipitation, with 8.66% of the area demonstrating extremely significant (p < 0.05) and significant (p < 0.01) positive correlation. Human activities, on the whole, have contributed to the enhancement of vegetation cover in the Qinghai-Tibet Plateau. The areas where human activities have positively impacted vegetation cover are primarily situated in north-central Qinghai and north of Ngari, while areas experiencing degradation include certain grassland regions in central-eastern Yushu, Nagqu, and Lhasa.

Impacts of extreme weather events on terrestrial carbon and nitrogen cycling: A global meta-analysis

Some weather events like drought, increased precipitation, and warming exert substantial impact on the terrestrial C and N cycling. However, it remains largely unclear about the effect of extreme weather events (extreme drought, heavy rainfall, extreme heat, and extreme cold) on terrestrial C and N cycling. This study aims to analyze the responses of pools and fluxes of C and N in plants, soil, and microbes to extreme weather events by conducting a global meta-analysis of 656 pairwise observations. Results showed that extreme weather events (extreme drought, heavy rainfall, and extreme heat) decreased plant biomass and C flux, and extreme drought and heavy rainfall decreased the plant N pool and soil N flux. These results suggest that extreme weather events weaken the C and N cycling process in terrestrial ecosystems. However, this study did not determine the impact of extreme cold on ecosystem C and N cycling. Additional field experiments are needed to reveal the effects of extreme cold on global C and N cycling patterns.