98%
921
2 minutes
20
Integrated management of ecosystem services through ecosystem service bundles (ESBs) is increasingly recognized as one of the most promising approaches for optimizing ecosystem services. Understanding the spatiotemporal dynamics of ESBs is critical for developing precise and adaptive regional ecosystem management strategies. However, most existing studies focus on the static identification of ESBs, with limited attention to the long-term stability and underlying drivers. With Hunan Province as an example and based on the spatiotemporal evolution of six key ecosystem services from 1995 to 2020, we introduced the "dominant service cluster change frequency" indicator to quantify the spatiotemporal stability of ESBs, and established an explanatory framework for the stability dri-ving mechanism. The results showed that food production, carbon sequestration, and soil retention significantly increased, habitat quality remained relatively stable, while flood regulation and water yield declined. The spatial patterns of multiple service types also underwent significant change during 1995-2020. ESBs showed high spatial heterogeneity and temporal dynamics, with 58.2% of the area showing high transition frequency and only 41.8% remaining relatively stable. High stability regions were mainly located in plains and mountainous forest areas with high levels of agricultural intensification. Geographic detector analysis revealed that land-use factors (e.g., cropland and forest ratios) and climate variables (e.g., precipitation and temperature) were the primary drivers of ESB stability. The interaction effects between land use and climate were stronger than single-factor effects. Based on the stability classifications, we further proposed adaptive and region-specific ecosystem management strategies to provide a new path for improving the ability to sustain service supply and the timeliness of policy implementation. This study would expand the perspective of dynamic regulation in the study of ESBs, providing theoretical support and practical basis for the refined management of ecosystem multifunctionality in changing environments.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.13287/j.1001-9332.202508.026 | DOI Listing |
Glob Chang Biol
September 2025
Chair of Silviculture, Faculty of Environment and Natural Resources, Institute of Forest Sciences, University of Freiburg, Freiburg, Germany.
Mixed-species forests are proposed to enhance tree resistance and resilience to drought. However, growing evidence shows that tree species richness does not consistently improve tree growth responses to drought. The underlying mechanisms remain uncertain, especially under unprecedented multiyear droughts.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
School of Civil Engineering, Putian University, Putian City, 351100, China.
Land degradation (LD) is a critical environmental challenge caused by human activities and climate change. Reversing degraded land requires effective LD monitoring. The UN Sustainable Development Goal (SDG) indicator 15.
View Article and Find Full Text PDFNat Microbiol
September 2025
Division of Computational Pathology, Brigham and Women's Hospital, Boston, MA, USA.
Although dynamical systems models are a powerful tool for analysing microbial ecosystems, challenges in learning these models from complex microbiome datasets and interpreting their outputs limit use. We introduce the Microbial Dynamical Systems Inference Engine 2 (MDSINE2), a Bayesian method that learns compact and interpretable ecosystems-scale dynamical systems models from microbiome timeseries data. Microbial dynamics are modelled as stochastic processes driven by interaction modules, or groups of microbes with similar interaction structure and responses to perturbations, and additionally, noise characteristics of data are modelled.
View Article and Find Full Text PDFJ Acoust Soc Am
September 2025
Applied Physics Laboratory, University of Washington, Seattle, Washington 98105, USA.
Echolocating bats provide vital ecosystem services and can be monitored effectively using passive acoustic monitoring (PAM) techniques. Duty-cycle subsampling is widely used to collect PAM data at regular ON/OFF cycles to circumvent battery and storage capacity constraints for long-term monitoring. However, the impact of duty-cycle subsampling and potential detector errors on estimating bat activity has not been systematically investigated for bats.
View Article and Find Full Text PDFNurs Health Sci
September 2025
School of Nursing and Midwifery, Centre for Quality and Patient Safety, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
Caesarean section (CS) rates are increasing globally. We aimed to understand stakeholders' perspectives on factors driving CS in pregnancy care to inform areas for intervention. Stakeholders from five health services participated in three Group Model Building workshops to identify the drivers of CS and intervention opportunities.
View Article and Find Full Text PDF