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Abstract Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries. It also aims to analyze the spatiotemporal distribution pattern of litter in the research area by estimating and analyzing the spatiotemporal pattern of litterfall along the desert riparian forests of the lower Qarqan and Tarim Rivers from 2001 to 2021. The results show that the initiation of the ecological water transfer project has facilitated the decomposition of litterfall, leading to an initial decline. Subsequently, the vegetation gradually recovered, leading to an increase in leaf litter input. Since 2001, litterfall initially decreased until reaching its lowest value of 4.39 × 109 kg in 2005, followed by a subsequent increase, reaching its highest value of 12.5 × 109 kg in 2021. The study concludes that ecological water conveyance promotes both the decomposition and increase of litterfall. Initially, it accelerates litterfall decomposition, while later stages foster an increase in Litterfall load. Meanwhile, due to the ecological water transfer project and the higher vegetation cover along the Tarim River compared to the Qarqan River, the Tarim River basin experiences higher average Litterfall load and variation.

Solanum rostratum Dunal, belongs to the Solanaceae family and has drawn attention for its intricate interplay of invasiveness, phytochemical composition, and potential bioactivities. Notably invasive, S. rostratum employs adaptive mechanisms during senescence, featuring thorn formation on leaves, fruits, and stems seed self-propulsion, and resistance to drought. This adaptability has led to its proliferation in countries such as China, Canada, and Australia, extending beyond its Mexican origin. Despite its invasive historical reputation, recent studies unveil a rich array of phytochemicals in S. rostratum, suggesting untapped economic potential due to under-exploration. This review delves into exploring the potential uses of S. rostratum while elucidating the bioactive compounds associated with diverse identified bioactivities. In terms of phytochemistry, S. rostratum reveals an abundance of various bioactive compounds, including alkaloids, flavonoids, phenols, saponins, and glycosides. These compounds confer a range of beneficial bioactivities, encompassing antioxidant, antifungal, anticarcinogenic, anti-inflammatory, phytotoxic, and pesticidal properties. This positions S. rostratum as a reservoir of valuable chemical constituents with potential applications, particularly in medicine and agriculture. The review provides comprehensive insights into the phytochemistry, bioactivities, and bioactivity-guided fractionation of S. rostratum. In this review, we focus on the potential utilization of S. rostratum by emphasizing its phytochemical profile, which holds promise for diverse applications. This review is the first that advocates for further exploration and research to unlock the plant’s full potential for both economic and environmental benefit.

In recent years, Rwanda, especially its Eastern Province, has been contending with water shortages, primarily due to prolonged dry spells and restricted water sources. This situation poses a substantial threat to the country’s agriculture-based economy and food security. The impact may escalate with climate change, exacerbating the frequency and severity of droughts. However, there is a lack of comprehensive spatiotemporal analysis of meteorological and agricultural droughts, which is an urgent need for a nationwide assessment of the drought’s impact on vegetation and agriculture. Therefore, the study aimed to identify meteorological and agricultural droughts by employing the Standardized Precipitation Evapotranspiration Index (SPEI) and the Vegetation Health Index (VHI). VHI comprises the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), both derived from the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). This study analyzed data from 31 meteorological stations spanning from 1983 to 2020, as well as remote sensing indices from 2001 to 2020, to assess the spatiotemporal patterns, characteristics, and adverse impact of droughts on vegetation and agriculture. The results showed that the years 2003, 2004, 2005, 2006, 2013, 2014, 2015, 2016, and 2017 were the most prolonged and severe for both meteorological and agricultural droughts, especially in the Southern Province and Eastern Province. These extremely dry conditions led to a decline in both vegetation and crop production in the country. It is recommended that policymakers engage in proactive drought mitigation activities, address climate change, and enforce water resource management policies in Rwanda. These actions are crucial to decreasing the risk of drought and its negative impact on both vegetation and crop production in Rwanda.