This research investigated the performance of four different machine learning supervised image classifiers: artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machine (SVM) using SPOT-7 and Sentinel-1 images to classify mangrove age and species in 2019 in a Red River estuary, typical of others found in northern Viet Nam. The four classifiers were chosen because they are considered to have high accuracy, however, their use in mangrove age and species classifications has thus far been limited. A time-series of Landsat images from 1975 to 2019 was used to map mangrove extent changes using the unsupervised classification method of iterative self-organizing data analysis technique (ISODATA) and a comparison with accuracy of K-means classification, which found that mangrove extent has increased, despite a fall in the 1980s, indicating the success of mangrove plantation and forest protection efforts by local people in the study area. To evaluate the supervised image classifiers, 183 in situ training plots were assessed, 70% of them were used to train the supervised algorithms, with 30% of them employed to validate the results. In order to improve mangrove species separations, Gram–Schmidt and principal component analysis image fusion techniques were applied to generate better quality images. All supervised and unsupervised (2019) results of mangrove age, species, and extent were mapped and accuracy was evaluated. Confusion matrices were calculated showing that the classified layers agreed with the ground-truth data where most producer and user accuracies were greater than 80%. The overall accuracy and Kappa coefficients (around 0.9) indicated that the image classifications were very good. The test showed that SVM was the most accurate, followed by DT, ANN, and RF in this case study. The changes in mangrove extent identified in this study and the methods tested for using remotely sensed data will be valuable to monitoring and evaluation assessments of mangrove plantation projects.

Wetland socio-ecological systems provide livelihood benefits for many poor people throughout the developing world, yet their sustainable development requires local utilisation strategies that balance both environmental and development outcomes. Community-based local institutional arrangements that mediate peoples’ relationships with their environment and facilitate adaptive co-management offer one means of achieving this, and increasingly many NGOs and development practitioners have sought to integrate local institutional capacity building into development projects. In the context of wider academic debates surrounding the long-term sustainability of externally facilitated local institutions, this article draws on the experiences of the three-year Striking a Balance (SAB) project in Malawi which sought to embed sustainable wetland management practices within community-based local institutional arrangements. Drawing on field data collected through participatory methods at three project sites some 5 years after the cessation of project activities, we examine the extent to which SAB’s local institutional capacity building has been successful, and from this draw some lessons for externally driven project interventions which seek win-win outcomes for people and the environment. With reference to Elinor Ostrom’s design principles for long-enduring common property resource institutions, we suggest that the observed declining effectiveness of SAB’s local institutions can be attributed to issues of stakeholder inclusiveness and representations; their sustainability was arguably compromised from their inception on account of them being nested within pre-existing, externally driven village ‘clubs’ whose membership and decision-making was not congruent with all the wetland stakeholders within the community.

Considerable attention has been paid to the potentially confounding effects of geological and seasonal variation on outputs from bioassessments in temperate streams, but our understanding about these influences is limited for many tropical systems. We explored variation in macroinvertebrate assemblage composition and the environmental characteristics of 3(rd)- to 5(th)-order streams in a geologically heterogeneous tropical landscape in the wet and dry seasons. Study streams drained catchments with land cover ranging from predominantly forested to agricultural land, but data indicated that distinct water-chemistry and substratum conditions associated with predominantly calcareous and silicate geologies were key determinants of macroinvertebrate assemblage composition. Most notably, calcareous streams were characterized by a relatively abundant noninsect fauna, particularly a pachychilid gastropod snail. The association between geological variation and assemblage composition was apparent during both seasons, but significant temporal variation in compositional characteristics was detected only in calcareous streams, possibly because of limited statistical power to detect change at silicate sites, or the limited extent of our temporal data. We discuss the implications of our findings for tropical bioassessment programs. Our key findings suggest that geology can be an important determinant of macroinvertebrate assemblages in tropical streams and that geological heterogeneity may influence the scale of temporal response in characteristic macroinvertebrate assemblages

Change in mangrove extent and condition has potential consequences for social disparity in terms of who can adapt to change in ecosystem services and places perceived important for providing them. Participatory GIS can elicit spatial variation in the importance attached to ecosystem service places, but disaggregated research that can reveal difference over the small spatial extents often covered by mangroves is underdeveloped. Using mixed-methods (quantitative, qualitative and spatial) in a rehabilitated mangrove system in Vietnam, this study assesses if and why perspectives about ecosystem services and their providing places vary among households with different capacities to adapt to mangrove change.Three household groups with different adaptive capacities were characterised using quantitative adaptive capacity indicators, demographic and economic data, and trajectory interviews spanning three decades: accumulating, coping and flexible households Coastal protection was identified as beneficial by all, and sediment, habitat provisioning and food services were also frequently associated with mangroves. Only food was identified significantly more or less by different groups. Spatial hotspots generated for each group by quantifying overlap in places perceived important for providing these four services, revealed greatest difference in locations important for food. Interviews indicated change in the characteristics of mangrove localities and different abilities to adapt to them enabled some households to prosper while others struggled. We consider adaptive capacities that helped temper mangrove change, and who might be most impacted by continuing change. We conclude by identifying ways forward for rehabilitation strategies centred on local people’s differential adaptive capacity and multiple ecosystem service needs.