In November 2025, Northern Sumatra experienced one of the most extreme flood disasters in recent history, triggered by a rare combination of sustained high-intensity rainfall and long-term land-cover disturbance. Using satellite-based rainfall estimates, historical rainfall records, and land-cover change analysis, this study examines the spatial and temporal dynamics of the event. The rainfall produced over 950 mm within four days, with daily accumulation exceeding 390 mm and hourly peaks surpassing 40 mm/hr. Statistical analysis using the Generalized Extreme Value (GEV) distribution estimated a return period of approximately 192 years for the daily maximum. Land-cover analysis revealed extensive deforestation between 1990 and 2024, including in designated protection and conservation forest zones. Flood impacts were concentrated in watersheds with high forest loss and recent land disturbance, particularly in Aceh and North Sumatra. This study highlights how compounding hydroclimatic extremes and upstream land degradation can significantly amplify flood risk. The findings underscore the importance of integrating forest conservation and multi-day rainfall indicators into regional flood risk assessments and early warning systems.
Estimating the rate of soil erosion generally takes time, money, and energy. There are many parameters that must be accommodated, such as the physical properties of the soil, land cover, rainfall, topography, and so on. One alternative method for estimating erosion rates is to use a remote sensing approach. The aim of this research is to estimate the rate of soil erosion in the Special Purpose Forest Area of the University of Lambung Mangkurat (KHDTK ULM) Mandiangin, using the E30 model and Sentinel-2 imagery. The erosion rate are measured directly in the field with a number of sample points. According to the E30 model concept, field erosion samples are only measured on land that has a slope of 300. The topographic data itself is extracted from DEMNAS data. Meanwhile, soil bulk density data was obtained from https://soilgrids.org/, and solum data was taken from https://daac.ornl.gov/. From the Sentinel-2 imagery, Normalized Difference Vegetation Index (NDVI) data was extracted, which is one of the parameters in the E30 model. The estimated results of the erosion rate at KHDTK ULM Mandiangin show that, in general, the highest erosion rate at KHDTK ULM Mandiangin is around 480 tons/ha/year. Additionally, almost 80% of the KHDTK ULM Mandiangin area has a very serious erosion hazard level. Of course, the fastest rate of erosion is located on hill slopes with steep topography. Apart from having steep topography, one of the factors causing the high rate of erosion at KHDTK ULM is the thin soil layer and the lack of dense forest cover. This finding indicates the need to conserve vegetation cover on steep lands.
Climatic elements are limiting factors for plants; therefore, climate change can impact the phenology of plants. This study aims to determine the impact of climate change on the reproductive phenology of four local mango cultivars on Sulawesi Island, Indonesia. Data were collected during 2013 and 2014 by observing and recording the production of vegetative shoots, generative shoots, and fruits from the trees of each mango cultivar weekly. To assess the impact of seasonal change on fruit quality, the weight and sugar level of the ripe fruits in each cultivar were measured. Climate data were obtained from the National Centers for Environmental Prediction and the Indonesian Agency for Meteorology, Climatology, and Geophysics Region IV, Makassar. Results show that from 1979 until 2014, the climate in the study site changed from type D to type C according to the Schmidt-Ferguson Climate Classification method, indicating that the wet season became longer. Following climate change, the reproductive phenology of the four mango cultivars also changed from once to twice annually, whereby the flush of vegetative and reproductive shoots that appeared during the first period in March did not successfully develop into mature fruit but developed following the second period in July. The change of season also impacted the quality of the mangoes, as fruit produced during the longer dry season had higher sugar levels than those produced during the shorter dry season.
Bakut Island is one of the conservation forest areas in South Kalimantan. This island is the habitat of proboscis monkeys, and the proboscis monkey population is increasing from year to year. Therefore, it is estimated that one day the proboscis monkey habitat on Bakut Island will be over capacity. This study aims to estimate how long the population of proboscis monkeys on Bakut Island Nature Tourism Park can survive there by examining the amount of food the island's vegetation can produce. Proboscis monkey feed itself is estimated using the Leaf Area Index (LAI). LAI was extracted using UAV imaging and NICFI multitemporal imagery. Meanwhile, the carrying capacity of the proboscis monkey habitat is assessed using the quantity of consumption of the proboscis monkey population relative to food availability. Simulations of the carrying capacity of proboscis monkey habitat into the future were carried out using projections of the future proboscis monkey population and LAI growth. The entire computational process of simulating habitat carrying capacity is carried out using the Python language. The results of the analysis show that Bakut Island is only able to support proboscis monkey habitat until 2038. In that year, the proboscis monkey population on Bakut Island is projected to number 1,290 individuals. After 2038, the predicted amount of feed needed by the proboscis monkey population will exceed the feed available on Bakut Island. The limitation of this research is that it only uses one parameter to assess the carrying capacity of proboscis monkey habitat, namely food availability. There are still other parameters that have not been accommodated, including the home range and trees for nests.
Rhizophora mucronata is a black mangrove with the most productive ecosystem that has benefits many people. But in reality, because of their business, some people often neglect preserving mangrove ecosystems and habitats. This study was conducted to analyze the level of genetic diversity and the relationship between R. mucronata in West Sulawesi based on morphological markers that will be used in future restoration efforts of black mangroves around the coast. This study used ten trees from three origins: Polewali Regency Mandar, Majene, and Mamuju. Then, several parts of the tree are used for this study, namely leaves, trunks, bark, roots, flowers, and propagules. However, the observed characteristics are leaf shape, stem shape, and color samples such as bark color, stem color, root color, color propagule (fruit and hypocotyl), and leaf color with a qualitative and quantitative approach. The results of this study show that black mangroves in Polewali Mandar, Majene, and Mamuju show high-value genetic diversity. The genetic distance between Polewali Mandar and Mamuju shows a high value of 0.13, meaning they have a distant kinship. Meanwhile, the genetic distance between Polewali Mandar and Majene shows a low value of 0.09, meaning they are close relatives. The findings of this study directly address the research urgency by highlighting the high genetic diversity of R. mucronata populations in West Sulawesi, despite increasing threats from anthropogenic activities. The observed genetic distances indicate significant variation among populations, particularly between Polewali Mandar and Mamuju, which suggests the need for targeted conservation strategies. The close genetic relationship between Polewali Mandar and Majene further emphasizes the importance of localized preservation efforts. These insights provide a scientific basis for future restoration initiatives, ensuring conservation programs maintain genetic resilience and adaptability within the mangrove ecosystem.
