The African savannah elephant (Loxodonta africana) migrate in landscapes with patchily distributed food resources in semi-arid environments. GPS collar data in combination with the Minimum Convex Polygon approach (100% MCP) can be utilised to investigate elephant home ranges and spatial ecology. Mapping of suitable habitats in landscapes with isolated and patchy resources housing threatened and endangered species like the African savannah elephant is critical for conservation of their natural habitat. This study aimed to: (i) investigate the seasonal ranging patterns of the African savannah elephants and (ii) model the preferred habitat of the African savannah elephants in Mana Pools National Park (MNP) in Zimbabwe. Minimum Convex Polygon method was employed to delineate elephant home ranges and the MaxEnt algorithm was used to model their habitat preferences. There were significant differences (p < 0.05) in the size of the home ranges across all the three demarcated seasons (wet, transitional and dry). Elephant habitat preference is mainly driven by the presence, quantity and quality of palatable vegetation close to the Zambezi River in the Mana Pools National Park. GPS telemetry provides smart data for understanding elephant behaviour and movement patterns in semi-arid environments across seasons.

Desert shrubs are the dominant vegetation type in arid deserts and serve as crucial elements in sand retention, biodiversity maintenance, and carbon sequestration. However, due to their patchy and scattered distributions and spectral resemblance to herbaceous plants, desert shrub mapping relies on high-resolution imagery, which is less accessible for large-scale mapping. Here, a set of desert shrub mapping indices for Sentinel-2 (DSMIS) and for universal medium-resolution imagery (DSMIL) is developed to distinguish desert shrubs with dense vimen canopies. The index exploits the canopy structure and spectral characteristics, which have a sparse and multilayered canopy and a high proportion of desiccated branches, resulting in a consistently low reflectance in the red-edge to near-infrared range. The effectiveness of DSMI indices was examined in Ordos, China. In the experiment, an optimal threshold of 10.3 was obtained via DSMIs with Sentinel-2, which achieved an overall accuracy of 91.6% and identified a minimum desert shrub coverage of 0.23. In comparison, a threshold of 9.7 was obtained by DSMIL with Landsat-8, achieving an accuracy of 90.1% and identifying a minimum coverage of 0.17. The performance of DSMI was superior to that of the commonly used random forest, and this index could further improve classification as a complement to machine learning methods. The late stage of the nongrowing season was identified as the optimal period for desert shrub mapping with the index. DSMI also performed well at two test sites with diverse desert shrub dominant species and growing conditions. This study provides a novel index for desert shrub mapping and a practical tool for monitoring desertification in arid desert regions. It also offers a new perspective for historical dynamic studies of desert shrubs and other land cover types where only optical data are available.

BackgroundClimate change is increasing temperatures, frequency of heatwaves, and erratic rainfall, which threatens human biology and health, particularly in already extreme environments. Therefore, it is important to understand how environmental heat stress measures are tied to human water needs and thermoregulation under increasingly hot conditions.AimTo test how ambient temperature, heat index, and wet bulb globe temperature (WBGT) relate to hydration status and thermal heat perception in a hot, semi-arid environment.Subjects and methodsUrine samples, perceived heat stress, and anthropometrics were collected among Daasanach semi-nomadic pastoralists (n = 187 children, n = 231 adults) in northern Kenya. Environmental heat stress measures were recorded at sample collection; samples' urine specific gravity (USG) was measured.ResultsMultiple linear and logistic regressions indicate that all environmental heat stress measures were associated with USG, odds of dehydration, and heat perception. Ambient temperature performed marginally better than WBGT, and both performed better than heat index. These associations were stronger among children than adults.ConclusionIn a hot, semi-arid climate, ambient temperature and WBGT accurately predict human water needs and heat stress, with children more vulnerable to dehydration. To mitigate consequences of extreme heat, local bioculturally-appropriate hydration (e.g. tea) and cooling (e.g. shade) strategies should be encouraged.

Unmanned aerial vehicles (UAVs) can be used to monitor soil moisture (SM) in semiarid regions. We collected high resolution RGB imagery concurrently with hundreds of SM samples across nine sites over a latitudinal gradient in the western USA. We used RGB bands, texture metrics, and vegetation indices to predict SM using machine learning. The model showed a moderately acceptable accuracy (R-2 = 0.63 with cross validation, R-2 = 0.53 using an independent validation). Texture metrics ('mean' and 'entropy'), and the Excess Green (ExG) index had high predictive power while RGB bands performed poorly. Unlike Idaho and Montana, the spatial predictions for Utah and California showed high reliability (alpha < 0.01). Novel linear equations for the conversion of raw digital number (DN) values to reflectance are provided and facilitate remote sensing applications that build upon UAV-RGB imagery as a robust and cost-effective pathway to model SM for monitoring semiarid ecosystems.

Climate change, population growth, and economic development exacerbate water scarcity. This study investigates the impact of drought on water availability in the Belt and Road region using high-resolution remote sensing data from 2001 to 2020. The results revealed an average water availability (precipitation minus evapotranspiration) of 249 mm/year and a declining trend in the Belt and Road region. Approximately 13% of the Belt and Road region faces water deficits (evapotranspiration exceeds precipitation), primarily in arid and semi-arid regions with high drought frequency. The area in the water deficit is expanding, and the intensity of the water deficit is increasing. The annual trend of water availability is strongly related to the frequency of droughts, i.e. water availability decreases with increased drought frequency. Drought exacerbates seasonal water stress in approximately one-third of the Belt and Road region, mainly in Europe and northern Asia, where drought frequently occurs during seasons with low water availability. The more severe the drought, the larger the negative anomaly in water availability. The critical role of evapotranspiration in seasonal water availability variability is also highlighted. This research underscores the importance of understanding drought-induced changes in water availability, which is crucial for sustainable water resource management.

This paper investigates the impacts and dynamics of land use/land cover (LULC) change dynamics in mountainous catchments in semi-arid regions, focusing on drivers, methods, and hydrological impacts. This study reviews studies using the application of remotely sensed data and spatially modified data, highlighting advancements in LULC assessments through GIS integration and predictive modelling. Key drivers include agricultural expansion, population growth, urbanisation, and infrastructure development, which transform forests and grasslands into built environments, affecting ecosystem services and biodiversity. LULC changes significantly impact hydrology, leading to increased surface runoff, poor water quality, and disruptions in the hydrological cycle. Agricultural expansion also contributes to habitat fragmentation ad biodiversity loss. This study underscores the importance of sustainable land management and informed policy decisions to mitigate negative impacts and enhance ecological resilience in semi-arid regions.

This study investigates the distribution and impact of photovoltaic (PV) stations in the arid Northwest China, a crucial area for regional economic cooperation. A hierarchical extraction method combining RegNet and SAM models achieved 91.89% accuracy in PV station identification, while also showing a broader extraction coverage compared to existing datasets. In 2023, we identified 688 centralized PV stations, covering a total area of 719.28 km(2). Using the Continuous Change Detection and Classification (CCDC) algorithm along with Global Moran's I, we observed significant development in PV installations between 2013 and 2021, with smaller stations being more spatially dispersed. Ecological analysis revealed that PV stations were predominantly situated within the Gobi area/desert, with a minor proportion located in low-coverage grasslands. The impacts of PV stations on local temperature exhibited both locational and seasonal variations. Temperature variations between PV stations and their 1 km buffer zones were significant, with over half of the PV stations contributing a cooling effect on their surroundings (50.78% in summers and 58.79% in winters). Additionally, vegetation coverage increased with distance from the PV stations, which indicated a substantial ecological interaction, underscoring the potential advantages and complexities associated with PV deployment in arid ecosystems.

Two experiments were conducted over two growing seasons (2021/2022 and 2022/2023) in the South of Alamein Region (Moghra), Matrouh Governorate, Egypt, to evaluate the effects of soil covering, planting methods and sugar beet varieties on growth, yield, quality traits and water use efficiency (WUE). Treatments included two soil coverings (black polyethylene mulch vs. no mulch), two planting methods (manual vs. small planter) and four sugar beet varieties (two monogerm: Slama and Gustav, and two multigerm: Faten and Halawa). Principal component analysis (PCA) was used to identify key traits contributing to performance differences. Black polyethylene mulch significantly improved germination, growth, sucrose content, extractable sugar percentage, root yield, sugar yield and WUE compared to no mulch. Similarly, planting with small machinery outperformed manual planting. Among the varieties, Gustav and Halawa showed superior performance across seasons. PCA revealed that the first three components explained 92.15% of the total variation. PCA1 (55.3% variation) identified root yield and WUE for sugar yield as critical traits, while PCA2 (88.56% variation) highlighted leaf area index and sugar yield. These findings suggest that black polyethylene mulch, mechanized planting and high-performing varieties like Gustav and Halawa enhance sugar beet productivity and resource efficiency. Future research should explore eco-friendly alternatives to plastic mulch and evaluate the long-term impacts of mechanized planting and mulching in semi-arid agriculture.

The Loess Plateau is one of the most severely eroded regions in China. Assessing the spatiotemporal changes in wind erosion control services is of significant importance for the ecological protection of the Loess Plateau. The dynamic changes in these services are primarily influenced by human activities and natural climate changes. However, existing studies lack a quantitative evaluation of the contributions of climate change and human activities to the spatiotemporal changes in wind erosion control services on the Loess Plateau. This study utilized a modified soil wind erosion equation and partial derivative method to investigate the response characteristics of wind erosion control service changes on the Loess Plateau to climatic factors and human activities and quantified the relative contributions of these two driving factors. Additionally, the key threshold points of precipitation and grazing affecting soil wind erosion were found by constraint-line method. The results indicated that the amount of the sand fixation per unit area on the Loess Plateau increased slowly at a rate of 0.05 thm-2a-1 from 2000 to 2013 and then increased at a rate of 0.97 thm-2a-1 from 2013 to 2020. Spatially, 47.55% of the area showed an increasing trend, while 41.32% of the area showed a decreasing trend. Overall, the contribution of climate change to the variation in sand fixation services on the Loess Plateau is greater than that of human activities, but their contributions exhibit spatial heterogeneity. In the A2, B1, and B2 subregions, the decrease in sand fixation services and the increase in the A2 subregion are primarily influenced by human activities. Between 2000 and 2020, the average contributions of wind speed and precipitation to SR (sand fixation per unit area) on the Loess Plateau were 0.243 thm-2a-1 and 0.09 thm-2a-1, respectively, making them the most significant climatic drivers of SR changes. In coal mining areas on the Loess Plateau, the amount of the sand fixation per unit area mainly showed a decreasing trend (52.30%), while the conversion of cropland and unused land to grassland significantly promoted an increase in the amount of sand fixation, accounting for 50.30% of the total increase. After grazing intensity reaches a threshold (around 13.51%-35.84%), SR declines rapidly with further increases in grazing intensity. Various major ecological projects have also significantly promoted the increase in wind erosion control. The study results can provide empirical support and a basis for formulating ecological restoration plans for different ecological zones on the Loess Plateau, as well as for soil wind erosion control in coal mining and grazing areas.

An assessment of regional vulnerability to geological disasters can directly indicate the extent and intensity of risks within the study area. The loess tableland area in northern Shaanxi is located at the junction of the southern part of the loess plateau and the northern part of the Guanzhong Plain, where geological disasters occur frequently. In this paper, the information quantity model method is proposed, seven factors including slope angle, slope height, slope shape, slope direction, slope structure, geomorphic unit type and engineering geological rock group are selected as the susceptibility evaluation index, and the geological hazard susceptibility of Xunyi County, a typical loess tableland, is comprehensively evaluated by GIS platform. The results showed that high, medium, low and very low prone areas accounted for 11.5%, 21.73%, 31.14% and 35.63% of the total area, respectively. Geological disasters are mainly distributed between the loess tableland and loess gully in the transition area. The area under the ROC curve (AUC) was used to evaluate the accuracy, and the AUC was 82.06 %, indicating that the results were accurate. The research results can provide reliable guidance for disaster prevention and control in northern Shaanxi and the entire Loess Plateau.