Land-use changes and precipitation cycles to understand hydrodynamic responses in semiarid Mediterranean karstic watersheds

Characterization of the impacts of hydro-dams on wetland inundations in Southeast Asia

Inundations of wetlands play a significant role in wetland ecosystems, but they are vulnerable to hydrological alterations. In Southeast Asia, many hydro-dams, which significantly alter the hydrology, have been built, but little is known about the influences of dams on wetland inundations. In this study, we quantified the characteristics of inundations and related the alterations to the dams by distinguishing them from influences of climate variabilities and local human activities. A multi-sensor approach using Landsat 8, Sentinel-1, and MODIS was devised to delineate the weekly inundations of 362 Southeast Asian wetlands from 2014 to 2021. The four hydrological characteristics (cyclical patterns, trends, intra-annual variability, and amplitude of inundations) were quantified, and the alteration of the characteristics caused by dams was separated from climate variabilities and local human activities using correlation analysis and logistic regression models. The results found that cyclical patterns, trends, intra-annual variability, and amplitude of wetland inundations changed significantly over the period, but the magnitudes vary significantly depending on their geographic locations with respect to the dams. Findings showed that dams critically affect the wetlands even though dams are located distantly from the dams. This indicates that wetlands should be monitored and conserved for reducing the influences of dams. This study advances our understanding of the effects of dams on wetlands by using the multi-sensor approach and distinguishing them from climate variabilities and local human activities.

Multicriteria spatial model to prioritize degraded areas for landscape restoration through agroforestry

Reconciling the restoration of ecosystem services within agricultural landscapes is an effort that has been advancing within degraded areas restoration through agroforestry systems. However, to contribute to the effectiveness of these initiatives, it is essential to integrate landscape vulnerability and local demands to better highlight in which areas the implementation of agroforestry systems should be prioritized. Thus, we developed a spatial hierarchization methodology as a decision support tool as an active strategy for agroecosystem restoration. The proposed method constitutes a spatial indicator of priority areas to guide agroforestry interventions, including resource allocation and public policies for payment for environmental services. The methodology consists of Multicriteria Decision Analysis implemented in GIS software by combining input datasets based on biophysical conditions, environmental and socioeconomic aspects, that integrated promotes an assessment of the environment fragility, the pressures and responses to land use dynamic; a strategy for landscape restoration and conservation of the natural habitats, and multiple specific scenarios for decision making regarding the agricultural and the local actors demands. The output of the model provides the spatial distribution of areas suitable for the implementation of agroforestry systems, sorted into four priority levels (Low, Medium, High, and Extreme priority). The method is a promising tool proposal for territorial management and governance and subsidizes future research on the flows of ecosystem services.•Assessment of the environment fragility and the pressures and responses to land use dynamic.•Strategy for landscape restoration and conservation of remaining natural habitats.•Multiple specific scenarios for decision making regarding the agricultural and the local actors demands.