Search Results (34)

The Okavango River is a transboundary waterway that flows through Angola, Namibia, and Botswana, forming a significant alluvial fan in northwestern Botswana. This fan creates a Delta that plays a vital role in the country’s GDP through tourism. While research has primarily focused on the Delta, the river’s catchment area in the Angolan highlands—its main water source and critical for downstream flow—has been largely overlooked. The basin is under pressure from development, water abstraction, and population growth in the surrounding areas, which negatively affect the environment. These challenges are intensified by climate change, leading to increased water scarcity that necessitates improved management strategies. Currently, there is a lack of published research on the basin’s hydrology, leaving many hydrological parameters related to streamflow in the catchments inadequately understood. Most existing studies have employed single-site calibration methods, which fail to capture the diverse characteristics of the basin’s catchments. To address this, a SWAT model has been developed to simulate the hydrologic behaviour of the basin using sequential multisite calibration with data from five gauging stations, including the main river systems: Cubango and Cuito. The SUFI2 program was used for sensitivity analysis, calibration, and validation. The initial sensitivity analysis identified several key parameters: the Soil Evaporation Compensation Factor (ESCO), the SCS curve number under moisture condition II (CN2), Saturated Hydraulic Conductivity (SOL_K), and Moist Bulk Density (SOL_BD) as the most influential. The calibration and validation results were generally satisfactory, with a coefficient of determination ranging from 0.47 to 0.72. Analysis of the water balance and parameter sensitivities revealed the varied hydrologic responses of different sub-watersheds with distinct soil profiles. Average annual precipitation varies from 1116 mm upstream to 369 mm downstream, with an evapotranspiration-to-precipitation ratio ranging from 0.47 to 0.95 and a water yield ratio between 0.51 and 0.03, thereby revealing their spatial gradients, notably increasing evapotranspiration and decreasing water yield downstream. The SWAT model’s water balance components provided promising results, with soil moisture data aligned with the TerraClimate dataset, achieving a coefficient of determination of 0.63. Additionally, the model captured the influence of the El Niño–Southern Oscillation (ENSO) on local hydrology. However, limitations were noted in simulating peak and low flows due to sparse gauge coverage, data gaps (e.g., groundwater abstraction, point sources), and the use of coarse-resolution climate inputs. Full article

In many southern African protected areas, religion and culture strongly influence how people initiate, adopt, or oppose conservation initiatives. If conservationists are unable to effectively engage with local communities, the result is often poor participation and failed conservation programs, particularly those operating under Western colonial paradigms. Contemplative inquiry has recently emerged as a promising relational, embodied, and dialogical approach to community engagement that also supports decolonial processes. This paper explores decolonial, relational and contemplative approaches to community-based fieldwork in the Okavango Delta, Botswana. Included are reflections on ethnographic interviews with Batswana conservation practitioners whose research lies at the intersection of Euro-Western environmentalism and an African relational ontology. This humanities-science transdisciplinary exploration challenges normative boundaries between intellectual territories and engages civil society beyond academia. It aims to “undiscipline” religion and conservation science, make a measurable contribution to conservation practice, and connect diverse knowledges in academia and civil society to address real-world ecological challenges. Full article

The effect of land use on sandy soils of southern Botswana was carried out by comparing the composition and properties of soil organic matter. Non-disturbed and disturbed soils were sampled from savanna ecosystems (Central District and Kweneng District). The biodegradability of organic matter was evaluated by incubation in the laboratory. Humic fractions were quantified and humic acids were analyzed by visible and infrared spectroscopy. The results indicate that continued disturbance, whether due to grazing or subsistence farming, has resulted in small yet significant changes in the concentration of available nutrients and organic matter in the soil. Nevertheless, substantial changes could be established in the soil C/N ratio, in the humic acid/fulvic acid ratio, and in the biodegradability of soil organic matter and the structural characteristics of humic acids. The increased aromaticity of humic acid (visible and IR spectroscopies) following disturbance suggests increased biogeochemical activity and/or the impact of abiotic processes (such as periodic fires) selectively removing aliphatic constituents. The overall results indicate low potential soil fertility, the sustainable preservation of which depends more on features related to quality than on the total amount of the soil organic matter, which shows aromatization parallel to its degree of association with the mineral fraction. Full article

People’s perception of the conflict they are experiencing with wildlife is a major factor in determining the extent of human-elephant conflict (HEC) occurring and needs to be considered when devising HEC management strategies. To understand perceptions and attitudes, however, it is necessary to identify factors that influence them. This study used a combination of multivariate ordered probit and generalized linear models to probe the complexities of farmer perception and attitudes and reveal underlying influential factors that shape perceived conflict levels. The study shows that the perception of HEC is complicated, influenced by an array of factors, both directly and indirectly, many of which are socio-demographic characteristics of the farmer, rather than quantifiable indicators of actual conflict. It was found that perceived human-elephant conflict (HEC) in the Okavango is affected by the ethnicity of the farmer, the raiding history of a field, the distance of fields to elephant pathways, and a farmer’s feeling towards elephants. Yet, feelings towards elephants are affected by attitudes towards wildlife, which are influenced by the benefits communities receive from living near wildlife. The perceived conflict levels of respondents were higher than the predicted actual conflict levels. Such discrepancies could be interpreted as “people over-reporting the scale of the problem”, yet results indicate that the crop-raiding history of a farmer alone is not adequate to assess the overall level of conflict being experienced because other social and environmental factors are involved in determining farmer perception of conflict. A holistic approach is needed to address the complexities of perceived and actual conflicts to ultimately reduce HEC. This involves targeting mitigation strategies for specific groups of people, considering elephant pathways and field locations in land use planning, and finding ways to improve benefits accrued to the community through wildlife-related enterprises that bring benefits back from living with elephants. Full article

This study addresses the gap in understanding the diversity, species, and functional trait distribution of different algal groups that occur in the Okavango Delta (a near-pristine subtropical wetland in northwestern Botswana) across hydrological and habitat gradients. We systematically characterize the delta’s algal flora, addressing the gap left by previous research that was limited to single algal groups (e.g., diatoms) and/or only looking at upstream areas in the Okavango River basin. We analyzed 130 algal samples from 49 upstream and downstream sites with higher and lower flooding frequency, respectively, across a river-to-floodplain habitat gradient. Chlorophyta and Bacillariophyta dominated both abundance and taxon richness (>80%) of the total 494 taxa found from 49,158 algal units counted (cells, colonies, coenobia, and filaments). Smaller algae were more abundant in downstream floodplains than in upstream channels and lagoons. Motile and siliceous algae were much more abundant than non-motile, nitrogen fixing, and phagotrophic algae. The frequency of these traits was associated more with flooding frequency than habitat type. The highest algal richness and diversity were found downstream, where shallow floodplain ecosystems with seasonally fluctuating water depths offer greater habitat heterogeneity, and macronutrients are resuspended. The increasing threats from upstream water abstraction plans, fracking, and climate change require enhanced protection and monitoring of the Okavango Delta’s natural annual flood-pulse to maintain the high species and functional diversity of this unique wetland’s microalgae. Full article

Understanding the spatial spread pathways and connectivity of Land Use/Cover (LULC) change within basins is critical to natural resources management. However, existing studies approach LULC change as distinct patches but ignore the connectivity between them. It is crucial to investigate approaches that can detect the spread pathways of LULC change to aid natural resource management and decision-making. This study aims to evaluate the utility of the Circuit Theory to detect the spread and connectivity of LULC change within the Okavango basin. Patches of LULC change sites that were derived from change detection of LULC based on the Deep Neural Network (DNN) for the period between 2004 and 2020 were used. The changed sites were categorized based on the nature of the change of the classes, namely Category A (natural classes to artificial classes), Category B (artificial classes to natural classes), and Category C (natural classes to natural classes). In order to generate the resistance layer; an ensemble of machine learning algorithms was first calibrated with social-ecological drivers of LULC change and centroids of LULC change patches to determine the susceptibility of the landscape to LULC change. An inverse function was then applied to the susceptibility layer to derive the resistance layer. In order to analyze the connectivity and potential spread pathways of LULC change, the Circuit Theory (CT) model was built for each LULC change category. The CT model was calibrated using the resistance layer and patches of LULC change in Circuitscape 4.0. The corridor validation index was used to evaluate the performance of CT modeling. The use of the CT model calibrated with a resistance layer (derived from susceptibility modeling) successfully established the spread pathways and connectivity of LULC change for all the categories (validation index > 0.60). Novel maps of LULC change spread pathways in the Okavango basin were generated. The spread pathways were found to be concentrated in the northwestern, central, and southern parts of the basin for Category A transitions. As for category B transitions, the spread pathways were mainly concentrated in the northeastern and southern parts of the basin and along the major rivers. While for Category C transitions were found to be spreading from the central towards the southern parts, mainly in areas associated with semi-arid climatic conditions. A total of 186 pinch points (Category A: 57, Category B: 71, Category C: 58) were detected. The pinch points can guide targeted management LULC change through the setting up of conservation areas, forest restoration projects, drought monitoring, and invasive species control programs. This study provides a new decision-making method for targeted LULC change management in transboundary basins. The findings of this study provide insights into underlying processes driving the spread of LULC change and enhanced indicators for the evaluation of LULC spread in complex environments. Such information is crucial to inform land use planning, monitoring, and sustainable natural resource management, particularly water resources. Full article

This articles presents a new series of maps showing the climate and environmental variability of Botswana. Situated in southern Africa, Botswana has an arid to semi-arid climate, which significantly varies in its different regions: Kalahari Desert, Makgadikgadi Pan and Okavango Delta. While desert regions are prone to droughts and periods of extreme heat during the summer months, other regions experience heavy downpours, as well as episodic and unpredictable rains that affect agricultural activities. Such climatic variations affect social and economic aspects of life in Botswana. This study aimed to visualise the non-linear correlations between the topography and climate setting at the country’s scale. Variables included T °C min, T °C max, precipitation, soil moisture, evapotranspiration (PET and AET), downward surface shortwave radiation, vapour pressure and vapour pressure deficit (VPD), wind speed and Palmer Drought Severity Index (PDSI). The dataset was taken from the TerraClimate source and GEBCO for topographic mapping. The mapping approach included the use of Generic Mapping Tools (GMT), a console-based scripting toolset, which enables the use of a scripting method of automated mapping. Several GMT modules were used to derive a set of climate parameters for Botswana. The data were supplemented with the adjusted cartographic elements and inspected by the Geospatial Data Abstraction Library (GDAL). The PDSI in Botswana in 2018 shows stepwise variation with seven areas of drought: (1) −3.7 to −2.2. (extreme); (2) −2.2 to −0.8 (strong, southern Kalahari); (3) −0.8 to 0.7 (significant, central Kalahari; (4) 0.7 to 2.1 (moderate); (5) 2.1 to 3.5 (lesser); (6) 3.5 to 4.9 (low); (7) 4.9 to 6.4 (least). The VPD has a general trend towards the south-western region (Kalahari Desert, up to 3.3), while it is lower in the north-eastern region of Botswana (up to 1.4). Other values vary respectively, as demonstrated in the presented 12 maps of climate and environmental inventory in Botswana. Full article

Botswana constitutes a major gap in our knowledge of the distribution of Ostracoda in the region of Southern Africa, restraining thorough biogeographic interpretations. We combine records from previously published surveys along with our own field collections to provide a collation of living and fossil (Late Pleistocene to Holocene) Ostracoda recorded in Botswana. Our survey yielded 17 species, of which nine species have not been recorded before in the country. Including the present update, 54 species (45 living and nine fossil or subfossil) belonging to 22 genera of five families (with 76% species belonging to the family Cyprididae) are currently reported from Botswana. Yet, 23 taxa are left in open nomenclature, indicating the urgent need for sound systematic studies on harmonizing taxonomy of Southern African ostracods, especially of those inhabiting small temporary waterbodies, considered as threatened with extinction before being properly described or discovered. This updated checklist provides detailed information about the distribution and habitat of each recorded species. Species richness, distribution patterns, and diversity of ostracod species regionally and in different freshwater ecoregions are also discussed. We found low alpha (site) diversity (mean 3.3 species per site) and a significant difference in species composition and beta diversity of the Okavango ecoregion versus the Kalahari and Zambezian Lowveld ecoregions. Full article

Inland fisheries play a critical role in the ecology of the Okavango Delta, but their conservation is particularly complex. For nearly a decade, communities, conservancies, policy makers, and partner organisations have worked to establish fish reserves across the Kavango and Zambezi. Guidelines on the establishment of fish reserves have been developed to delineate the process through which these protected areas are established, and a structured learning process has unpacked knowledge held by different stakeholders to better understand the opportunities and limitations of fish reserves and to subsequently revise these guidelines. This article aims to share these lessons and to contribute to the debate on the most effective institutional arrangements for this unique space of conservation. Full article

Characterizing compositional and structural aspects of vegetation is critical to effectively assessing land function. When priorities are placed on ecological integrity, remotely sensed estimates of fractional vegetation components (FVCs) are useful for measuring landscape-level habitat structure and function. In this study, we address whether FVC estimates, stratified by dominant vegetation type, vary with different classification approaches applied to very-high-resolution small unoccupied aerial system (UAS)-derived imagery. Using Parrot Sequoia imagery, flown on a DJI Mavic Pro micro-quadcopter, we compare pixel- and segment-based random forest classifiers alongside a vegetation height-threshold model for characterizing the FVC in a southern African dryland savanna. Results show differences in agreement between each classification method, with the most disagreement in shrub-dominated sites. When compared to vegetation classes chosen by visual identification, the pixel-based random forest classifier had the highest overall agreement and was the only classifier not to differ significantly from the hand-delineated FVC estimation. However, when separating out woody biomass components of tree and shrub, the vegetation height-threshold performed better than both random-forest approaches. These findings underscore the utility and challenges represented by very-high-resolution multispectral UAS-derived data (~10 cm ground resolution) and their uses to estimate FVC. Semi-automated approaches statistically differ from by-hand estimation in most cases; however, we present insights for approaches that are applicable across varying vegetation types and structural conditions. Importantly, characterization of savanna land function cannot rely only on a “greenness” measure but also requires a structural vegetation component. Underscoring these insights is that the spatial heterogeneity of vegetation structure on the landscape broadly informs land management, from land allocation, wildlife habitat use, natural resource collection, and as an indicator of overall ecosystem function. Full article

Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural resources within the Okavango Basin is undoubtedly a complex issue. It is often difficult to accurately map land use and cover using remote sensing in heterogeneous landscapes. This study investigates the combined value of climate-based regionalization and integration of spectral bands with spectral indices to enhance the accuracy of multi-temporal land use/cover classification using deep learning and machine learning approaches. Two experiments were set up, the first entailing the integration of spectral bands with spectral indices and the second involving the combined integration of spectral indices and climate-based regionalization based on Koppen–Geiger climate zones. Landsat 5 TM and Landsat 8 OLI images, machine learning classifiers (random forest and extreme gradient boosting), and deep learning (neural network and deep neural network) classifiers were used in this study. Supervised classification using a total of 5140 samples was conducted for the years 1996, 2004, 2013, and 2020. Average overall accuracy and Kappa coefficients were used to validate the results. The study found that the integration of spectral bands with indices improves the accuracy of land use/cover classification using machine learning and deep learning. Post-feature selection combinations yield higher accuracies in comparison to combinations of bands and indices. A combined integration of spectral indices with bands and climate-based regionalization did not significantly improve the accuracy of land use/cover classification consistently for all the classifiers (p < 0.05). However, post-feature selection combinations and climate-based regionalization significantly improved the accuracy for all classifiers investigated in this study. Findings of this study will improve the reliability of land use/cover monitoring in complex heterogeneous TDBs. Full article

Okavango delta is a typical distributive fluvial system, which is composed of a series of sand island-river-swamp networks. River migration in the Okavango delta is analyzed by using satellite images from Google Earth and Alaska Satellite Facility (ASF). Four configuration characterization parameters are selected to depict and measure the meandering river. These four parameters are sinuosity index (S), curvature (C), the difference of along-current deflection angle (Δθ) and expansion coefficient (Km). In the fan, the channel migration is mainly asymmetric. According to geomorphic elements and associated features, Okavango Delta can be subdivided into three zones: axial zone, median zone and distal zone. Under the influence of slope, climate and vegetation, different migration modes are developed in different zones. As the river moves downstream, the sinuosity index of the river on the Okavango Delta decreases downstream. Based on the characteristics of different zones, the sedimentary facies model of a single source distributive fluvial system of a meandering river is proposed. The models of channel migration and sedimentary facies have wide application. This research will not only provide a basis for the prediction of future river channels but will also provide important theoretical guidance for the study of the sedimentary morphology of underground reservoirs. Full article

Vector mosquitoes contribute significantly to the global burden of diseases in humans, livestock and wildlife. As such, the spatial distribution and abundance of mosquito species and their surveillance cannot be ignored. Here, we surveyed mosquito species across major tourism hotspots in semi-arid Botswana, including, for the first time, the Central Kalahari Game Reserve. Our results reported several mosquito species across seven genera, belonging to Aedes, Anopheles, Culex, Mansonia, Mimomyia, Coquillettidia and Uranotaenia. These results document a significant species inventory that may inform early warning vector-borne disease control systems and likely help manage the risk of emerging and re-emerging mosquito-borne infections. Full article

In large freshwater river basins across the globe, the composite influences of large-scale climatic processes and human activities (e.g., deforestation) on hydrological processes have been studied. However, the knowledge of these processes in this era of the Anthropocene in the understudied hydrologically pristine South Central African (SCA) region is limited. This study employs satellite observations of evapotranspiration (ET), precipitation and freshwater between 2002 and 2017 to explore the hydrological patterns of this region, which play a crucial role in global climatology. Multivariate methods, including the rotated principal component analysis (rPCA) were used to assess the relationship of terrestrial water storage (TWS) in response to climatic units (precipitation and ET). The use of the rPCA technique in assessing changes in TWS is warranted to provide more information on hydrological changes that are usually obscured by other dominant naturally-driven fluxes. Results show a low trend in vegetation transpiration due to deforestation around the Congo basin. Overall, the Congo (r2 = 76%) and Orange (r2 = 72%) River basins maintained an above-average consistency between precipitation and TWS throughout the study region and period. Consistent loss in freshwater is observed in the Zambezi (−9.9 ± 2.6 mm/year) and Okavango (−9.1 ± 2.5 mm/year) basins from 2002 to 2008. The Limpopo River basin is observed to have a 6% below average reduction in rainfall rates which contributed to its consistent loss in freshwater (−4.6 ± 3.2 mm/year) from 2006 to 2012.Using multi-linear regression and correlation analysis we show that ET contributes to the variability and distribution of TWS in the region. The relationship of ET with TWS (r = 0.5) and rainfall (r = 0.8) over SCA provides insight into the role of ET in regulating fluxes and the mechanisms that drive precipitation in the region. The moderate ET–TWS relationship also shows the effect of climate and anthropogenic influence in their interactions. Full article

Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas. Full article