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Small-scale Acacia decurrens plantation forests, established by farmers on degraded lands, have become increasingly prevalent in the Northwestern Highlands of Ethiopia. This trend has been particularly notable in Fagita Lekoma District over the past few decades. Such plantations play a significant role in addressing concerns related to sustainable agricultural land use, mitigating the adverse effects of deforestation, and meeting the livelihood and energy requirements of a growing population. However, the spatial distribution of Acacia decurrens and the essential remote sensing and environmental variables that determine its distribution are not well understood. This study aimed to model the spatial distribution of Acacia decurrens plantation forests using PlanetScope data and environmental variables combined with a species distribution model (SDM). Employing 557 presence/absence points, noncollinear variables were identified and utilized as input for six SDM algorithms, with a 70:30 split between training and test data, and 10-fold bootstrap replication. The model performance was evaluated using the receiver operation characteristic curve (AUC) and true skill statics (TSS). The ensemble model, which combined results from six individual algorithms, was implemented to predict the spatial distribution of Acacia decurrens. The highest accuracy with the values of 0.93 (AUC) and 0.82 (TSS) was observed using random forest (RF), followed by SVM with values of 0.89 (AUC) and 0.71 (TSS), and BRT with values of 0.89 (AUC) and 0.7 (TSS). According to the ensemble model result, Acacia decurrens plantation forests cover 22.44% of the district, with the spatial distribution decreasing towards lower elevation areas in the northeastern and western parts of the district. The major determinant variables for identifying the species were vegetation indices, specifically CVI, ARVI, and GI, with AUC metric values of 39.3%, 16%, and 7.1%, respectively. The findings of this study indicate that the combination of high-resolution remote sensing-derived vegetation indices and environmental variables using SDM could play a vital role in identifying Acacia decurrens plantations, offering valuable insights for land use planning and management strategies. Moreover, comprehending the spatial distribution’s extent is crucial baseline information for assessing its environmental implications at a local scale. Full article

Vegetation is an essential component of the terrestrial ecosystem and has changed significantly over the last two decades in the Northwestern Highlands of Ethiopia. However, previous studies have focused on the detection of bitemporal change and lacked the incorporation of entire vegetation time series changes, which are considered significant indicators of ecosystem conditions. The Normalized Difference Vegetation Index (NDVI) time series dataset from the Moderate-Resolution Imaging Spectroradiometer (MODIS) is an efficient method for analyzing the dynamics of vegetation change over a lengthy period using remote sensing techniques. This study aimed to utilize time series satellite data to detect vegetation changes from 2000 to 2020 and investigate their links with ecosystem conditions. The time-series satellite processing package (TIMESAT) was used to estimate the seasonal parameter values of NDVI and their correlation across the seasons during the study period. Break Detection for Additive Season and Trend (BFAST) was applied to identify the year of breakpoints, the direction of magnitude, and the number of breakpoints. The results were reported, analyzed, and linked to ecosystem conditions. The overall trend in the study area increased from 0.58 (2000–2004) to 0.65 (2015–2020). As a result, ecosystem condition indicators such as peak value (PV), base value (BV), amplitude (Amp), and large integral (LI) exhibited significant positive trends, particularly for Acacia decurrens plantations, Eucalyptus plantations, and grasslands, but phenology indicator parameters such as start of season (SOS), end of season (EOS), and length of season (LOS) did not show significant trends for almost any vegetation type. The most abrupt changes were recorded in 2015 (24.7%), 2012 (18.6%), and 2014 (9.8%). Approximately 30% of the vegetation changes were positive in magnitude. The results of this study imply that there was an improvement in the ecosystem’s condition following the establishment of the Acacia decurrens plantation. The findings are considered relevant inputs for policymakers and serve as an initial stage for the assessment of the other environmental and climatic implications of Acacia decurrens plantations at the local scale. Full article