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Landscape patterns have a great effect on river water quality. However, the strategies for enhancing water quality through landscape pattern management remain unclear. In this study, we aimed to provide effective guidance for water quality management by quantifying the key spatial scales and landscape metrics that influence the seasonal variations in water quality and establishing threshold relationships between these metrics and abrupt variations in water quality in the Chaohu Lake basin, China. Results discovered that water quality was poorer in summer and better in spring, with degraded water conditions primarily concentrated in the middle and lower reaches of the watershed. The 100 m riparian zone buffer scale landscape pattern was identified as the key scale affecting water quality in the summer, which accounted for 51.3% of the overall water quality variation. Furthermore, abrupt threshold analysis indicated that summer water quality could be effectively improved by maintaining the proportion and largest patch index of construction land within the 100 m riparian buffer below 22.0%. At the sub-basin scale, landscape pattern-based water quality management was most effective in spring, explaining 43.6% of the variation in water quality. Setting the largest patch index of construction land at the sub-basin scale below 43.0% and increasing the proportion of forest cover above 36.0% can also alleviate water pollution issues. These findings emphasize the importance of incorporating landscape patterns across scales into environment management decisions, providing a scientific basis for effective watershed water quality management. [Display omitted] • Identifying the spatial and temporal variation of river water quality by WQI. • Quantifying threshold relationships between landscape indicators and water quality. • 100 m riparian zone buffer scale was the key scale affecting water quality. • Integrating landscape patterns into management can improve water quality. [ABSTRACT FROM AUTHOR]

Coastal wetlands are critical ecosystems that are under intense pressure due to anthropogenic activities. In addition to urban growth and agriculture, shrimp farming has become one of the main drivers behind the loss of tropical and subtropical coastal wetlands. Despite its socio-economic importance, shrimp farming has high environmental costs worldwide. Consequently, monitoring shrimp farming at regional and local scales is essential to determine if the resulting pressure on coastal wetlands is increasing. We analyzed land use/land cover (LULC) in the Bahía Santa Maria-La Reforma (BSMR) lagoon system in northwestern Mexico using remote sensing data to determine landscape and surface cover changes. We also projected future scenarios based on stochastic models and evaluated landscape metrics considering the effects of shrimp farming. Four LULC thematic maps (1985, 1994, 2002, and 2017) with overall accuracy values > 80% and two projected maps (2027 and 2037) were produced. Agriculture was the dominant LULC class in the BSMR coastal lagoon system, although saltmarshes appear to be the most critical wetland type in the area. Shrimp farming, which was nonexistent in 1985, represented 4% of the total landscape in 2017. By 2037, this value is expected to increase to 5%. Saltmarshes showed negative trends due to the expansion of shrimp farming. Considering the importance of wetlands given their ecosystem services, this study highlights LULC changes due to economic activities and the need to improve management strategies to protect the wetlands of the BSMR coastal lagoon system. • LULCC was evaluated via post-classification comparison analysis. • The use of multidate images reduced biases derived from phrenological shifts. • Future scenarios were predicted with stochastic and artificial neural network models. • Saltmarshes are the most critically threatened wetland type in the study area. • Shrimp farming is the main driver of coastal wetland loss and fragmentation. [ABSTRACT FROM AUTHOR]

Topsoil erosion is a widespread and major threat to terrestrial ecosystems that leads to environmental deterioration. Monitoring soil erosion dynamics and understanding the driving mechanisms are of great significance for optimizing ecological restoration programs and combating land degradation. We apply a widely used soil erosion assessment model to quantify the changes in soil erosion on the Loess Plateau (LP) in response to afforestation-induced vegetation cover and land use/cover changes. Furthermore, we examine the relationship between landscape metrics and soil erosion using spatial econometric approach. The results indicate that soil erosion in the LP substantially decreased through afforestation efforts, while the observed sediment load declined significantly as a result of soil and water conservation programs. A number of largescale ecological programs altered the spatial configuration and structural composition of the landscape from different aspects, which disturbed the formation and transportation of soil erosion, eventually resulting in a reduction in soil loss. The spatial association between landscape metrics and soil erosion indicated that properly fragmented landscapes can effectively decrease soil erosion. Due to the spatial spillover, soil erosion in one county can be affected by soil erosion in adjacent counties. Therefore, the spillover effect between counties should not be ignored, and the responsibility for formulating and implementing solutions to combat land degradation should not fall solely on individual local governments. Preferably, the cooperation between different regions should be strengthened as a critical way to improve the efficiency of programs combating land degradation. • The landscape pattern metric changes were quantified. • The responses of soil loss to afforestation programs were revealed. • The associations between soil erosion and landscape metrics were investigated via spatial econometric approach. • The spatial spillover effects and their practical implications were discussed. [ABSTRACT FROM AUTHOR]