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The Mekong River is one of the most biodiverse, productive rivers in the world, supporting more than 1000 fish species and the livelihoods of tens of millions of people. The spatial dynamics and population status of many Mekong fish species, especially megafishes, are poorly understood. Therefore, this information is rarely incorporated into environmental risk assessments for large infrastructure projects, such as mainstream hydropower developments, which have been accelerating rapidly in the Mekong Basin. In this study, we present initial findings from the ongoing, collaborative, transnational acoustic telemetry monitoring of nearly 300 tagged fishes representing 27 species, which yield important insights into the potential impacts that proposed hydropower dams would have on populations of ecologically and economically important fish species. Included in these data are more than ten months of hydrophone records tracking the location of a 300 kg giant freshwater stingray, Urogymnus polylepis (Bleeker, 1852), currently the world’s largest known freshwater fish, used to detect its migration behavior and distribution patterns. The telemetry data, combined with fisher surveys used to gather local ecological knowledge, provide evidence that the proposed dams would fragment the existing populations of this iconic species as well as those of other fish species that support river food web balance and local food systems. Furthermore, the existence of giant freshwater stringray populations and other unique megafauna reinforces the universal natural heritage value of the stretch of the Mekong River between the Lao People’s Democratic Republic/Cambodia border and the city of Kratie. This stretch of river is located between two proposed megadams, the 900 MW Stung Treng Dam and the 2300 MW Sambor Dam. However, the Cambodian Ministry of Environment has also proposed this area for designation as a UNESCO World Heritage Site (Biosphere Reserve). The documentation of the movement of migratory fishes through this reach of the river using acoustic telemetry, the surprising discovery of the world’s largest freshwater fish, the potential threat posed by dam construction, and the management ramifications of UNESCO World Heritage Site designation underscore the importance of scientific research and community involvement in landscape-scale development decisions. The decisions made today will affect the fate of this global biodiversity hotspot, the world’s most productive inland fisheries, and the livelihoods of millions of people throughout the Lower Mekong Basin.

Tropical lakes and their associated floodplain habitats are dynamic habitat mosaics strongly influenced by seasonal variations in hydrologic conditions. In flood-pulse systems, water level oscillations directly influence the connectivity to floodplain habitats for fish. Here, we aimed to investigate whether seasonal changes in the water level of a flood-pulse system (the Tonle Sap Lake, Cambodia) differentially affect diet breadth and dietary overlap of three common and commercially important fish species (Anabas testudineus, Boesemania microplepis and Notopterus notopterus) presenting important differences in their life-cycle (e.g. seasonal migration). For this purpose, the three fish species were sampled at four locations spread over the lake and their stomach contents extracted for analyses. Dietary differences were investigated across seasons regarding the diet composition and diet breadth of each species as well as the amount of dietary overlap between species. We found that the proportion of empty stomachs changed similarly across seasons for the three species, thus suggesting that ecological differences between species are not sufficient to outweigh the effect of seasonal variations in resource abundance. In contrast, changes in diet composition were species-specific and can be explained by ecological and behavioral differences between species. Diet breadth differed between species in all seasons, except during the wet season, and tended to be higher during the dry season when dietary overlap was the lowest. These variations likely result from changes in the diversity and amount of resources and may lead to habitat use shifts with potential implications for competitive interactions. In particular, increasing connectivity to floodplain habitats may reduce the competitive pressure during the wet season, while resource scarcity during the dry season may constrain individuals to diversify their diet to avoid competition. Overall, our results suggest a considerable plasticity in the feeding behavior of the three species as demonstrated by seasonal variation in both diet breadth and dietary overlap. Such variations can be explained by a number of factors and processes, including changes in resource availability or competitive interactions between individuals for resources, whose relative influence might vary depending on the magnitude and the timing of the flood-pulse driving the connectivity to floodplain habitats. Gaining knowledge on the seasonal evolution of fish's diet is relevant for fisheries management and conservation and our result could be used to guide aquaculture development in Cambodia.

Support vector machine (SVM) is a binary classifier widely used in machine learning. However, neglecting the latent data structure in previous SVM can limit the performance of SVM and its extensions. To address this issue, the authors propose a novel SVM with discriminative low‐rank embedding (LRSVM) that finds a discriminative latent low‐rank subspace more suitable for SVM classification. The extension models of LRSVM are introduced by imposing different orthogonality constraints to prevent computational inaccuracies. A detailed derivation of the authors' iterative algorithms are given that is essentially for solving the SVM on the low‐rank subspace. Additionally, some theorems and properties of the proposed models are presented by the authors. It is worth mentioning that the subproblems of the proposed algorithms are equivalent to the standard or the weighted linear discriminant analysis (LDA) problems. This indicates that the projection subspaces obtained by the authors' algorithms are more suitable for SVM classification compared to those from the LDA method. The convergence analysis for the authors proposed algorithms are also provided. Furthermore, the authors conduct experiments on various machine learning data sets to evaluate the algorithms. The experiment results show that the authors' algorithms perform significantly better than other algorithms, which indicates their superior abilities on classification tasks. [ABSTRACT FROM AUTHOR]

Despite the government's active promotion of rice production, a significant portion of the population still faces food insecurity. While existing literature often highlights the success of achieving rice surplus, few studies delve into the connections between rice surplus and food security, and critically analyze why food security is persistent. In addressing this issue, the study investigates the underlying causes of food insecurity amidst the government's efforts to increase rice production. The study entails a comprehensive review of existing literature and an examination of food security in three provinces in the Cambodian Mekong Delta. It concludes that while rice intensification has led to increased rice production available for consumption, challenges persist in terms of access to and utilization of rice for food consumption. These challenges are attributed to increased production costs with minimal profit margins, indebtedness, migration, land grabs, water conflicts, and lack of institutional integration in food systems, compounded by the effects of climate change and environmental degradation. As a result, a farming household with one hectare of farmland cannot produce enough rice for food consumption. Consequently, young people opt to sell off their land to settle debts and seek employment opportunities in urban and overseas areas. [ABSTRACT FROM AUTHOR]

The giant freshwater whipray is a large-bodied stingray species that is listed as endangered across its known range from India through Southeast Asia. However, little is known about the species' ecology, biology, and conservation status. We reviewed all available literature, articles, and reports on the species found through database and internet searches in order to consolidate and update information on the giant freshwater whipray. We found that remarkably little research has been done, and most existing information on the species is derived from fisher catch reports. Whiprays of 300 kg or more have been reported in most countries where it occurs. The available evidence suggests that this species is endangered across its range by numerous threats, including fishing, bycatch, bottom trawls, pollution, and habitat destruction and fragmentation. Various reports indicate declines in population size, genetic diversity, and body size. Relatively stable populations may persist in the Maeklong River, Thailand, the Mekong River in Cambodia, and insular Southeast Asia. More work is needed to understand the species' spatio-temporal distribution, reproductive behavior, migration patterns, and general ecological and biological characteristics in order to inform effective management and conservation plans. Due to difficulties in sampling this rare species and monitoring fisher catches, partnership and collaboration with all stakeholders, including local fishers, government officials, and researchers, is essential to produce conservation gains for the giant freshwater whipray. [ABSTRACT FROM AUTHOR]