Rapid urbanization intensifies the fragmentation of landscape patches and affects the stability of ecosystems. The construction of an ecological network can effectively promote the connection of important ecological spaces and improve the landscape integrity. However, the landscape connectivity, directly affecting the stability of ecological network, was less considered in the ecological network construction of recent researches, which easily caused the instability of constructed ecological network. Therefore, this study introduced landscape connectivity index to establish a modified ecological network optimization method based on the minimum cumulative resistance (MCR) model. The results showed that, compared with the traditional model, the modified model focused on the spatially detailed measurement of regional connectivity, and emphasized the impact of human disturbance on ecosystem stability at the landscape scale. The constructed corridors in the optimized ecological network of the modified model not only effectively improved the connection degree between important ecological sources but also avoided the areas with low landscape connectivity and high obstacles to ecological flow, especially in the counties of Zizhong, Dongxing, and Longchang within the focal study area. The ecological network established by the traditional model and modified model generated 19 and 20 ecological corridors with lengths of 334.49 km and 364.35 km, respectively, and the number of ecological nodes was 18 and 22. Evaluated by the Gravity method, the modified model identified the important ecological corridors in the ecological network, and the energy transfer efficiency of the network was improved. This study provided an effective way to improve the structural stability of ecological network construction and can provide scientific support for regional landscape pattern optimization and ecological security construction.
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http://dx.doi.org/10.1007/s11356-023-26197-w | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated the stochasticity of soil microbes and multitrophic networks through amplicon sequencing, assessed soil community functions related to carbon (C), N, phosphorus (P), and sulfur (S) cycling, and characterized the dominant bacterial life history strategies via metagenomics along a gradient of increasing pesticide diversity under two N addition levels.
View Article and Find Full Text PDFPsychol Assess
January 2025
Maastricht University, Faculty of Psychology and Neuroscience, Department of Clinical Psychological Science.
Ecological momentary assessment (EMA) collects real-time data in daily life, enhancing ecological validity and reducing recall bias. An EMA questionnaire that measures symptoms and transdiagnostic factors was recently developed with network modeling purposes. This study examines this EMA protocol's (a) subjective experience (e.
View Article and Find Full Text PDFJ Behav Med
January 2025
Department of Counseling Psychology and Human Services, Prevention Science Institute, University of Oregon, Eugene, OR, USA.
Executive functioning (EF) has been linked to chronic disease risk in children. Health behaviors are thought to partially explain this association. The current cross-sectional study evaluated specific domains of EF and varied health behaviors in three pediatric life stages.
View Article and Find Full Text PDFEnviron Geochem Health
January 2025
School of Environmental Science and Engineering, Shandong University, Qingdao, 266237, China.
Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.
View Article and Find Full Text PDFConserv Biol
January 2025
Marine Science Institute, University of California, Santa Barbara, Santa Barbara, California, USA.
Marine protected areas (MPAs) are widely implemented tools for long-term ocean conservation and resource management. Assessments of MPA performance have largely focused on specific ecosystems individually and have rarely evaluated performance across multiple ecosystems either in an individual MPA or across an MPA network. We evaluated the conservation performance of 59 MPAs in California's large MPA network, which encompasses 4 primary ecosystems (surf zone, kelp forest, shallow reef, deep reef) and 4 bioregions, and identified MPA attributes that best explain performance.
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