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Miombo and mopane woodlands are the dominant land cover in southern Africa. Ecosystem services from these woodlands support the livelihoods of 100 M rural people and 50 M urban dwellers, and others beyond the region. Provisioning services contribute $9 ± 2 billion yr−1 to rural livelihoods; 76% of energy used in the region is derived from woodlands; and traded woodfuels have an annual value of $780 M. Woodlands support much of the region's agriculture through transfers of nutrients to fields and shifting cultivation. Woodlands store 18–24 PgC carbon, and harbour a unique and diverse flora and fauna that provides spiritual succour and attracts tourists. Longstanding processes that will impact service provision are the expansion of croplands (0.1 M km2; 2000–2014), harvesting of woodfuels (93 M tonnes yr−1) and changing access arrangements. Novel, exogenous changes include large-scale land acquisitions (0.07 M km2; 2000–2015), climate change and rising CO2. The net ecological response to these changes is poorly constrained, as they act in different directions, and differentially on trees and grasses, leading to uncertainty in future service provision. Land-use change and socio-political dynamics are likely to be dominant forces of change in the short term, but important land-use dynamics remain unquantified. This article is part of the themed issue ‘Tropical grassy biomes: linking ecology, human use and conservation’.

In-vitro culture of mycorrhizal mushroom (MM) species in southern Africa remains largely unexplored, par ticularly using tree-derived media. In this study, a Julbernardia globiflora [(Benth.) Troupin] leaf infusion was tested for its ability to promote MM mycelial growth. Amanita loosii, Cantharellus miomboensis and Cantharellus heinemannianus isolates were incubated at a pH of 2, 3, 4, 5, 6 or 7 and at 25 °C in six leaf extract agar (LEA) infusion concentrations of 150, 175, 200, 225 or 250 grams of leaves/L distilled water, with potato dextrose agar (PDA) as a standard. We determined mycelium growth rates for all treatment combinations. Mycelium growth rate was found to be optimal at a pH between 4 and 6 in all leaf infusion concentrations tested. Significant (p<0.001) linear regressions of A. loosii and C. miomboensis were found for pH only (R2=0.837 and 0.8582, respectively) and a significant (p<0.001) regression was found for C. heinemannianus (R2=0.293). Amanita loosii and C. heinemannianus had faster (p<0.001) growth in PDA than in LEA, while C. miomboensis had similar growth rates in the two media. Growth characteristics observed were attributed to acid phosphatase mediated physiological processes in mycelium for the different MM species with an optimum pH of 4-6. MM mycelia were white, mycelia for A. loosii and C. miomboensis were loose and for C. heinemannianus were thin filaments. LEA proved to be a potential alternative medium for culturing MM species.

Dimensions of tree root systems in savannas are poorly understood, despite being essential in resource acquisition and post-disturbance recovery. We studied tree rooting patterns in Southern African savannas to ask: how tree rooting strategies affected species responses to severe drought; and how potential rooting depths varied across gradients in soil texture and rainfall. First, detailed excavations of eight species in Kruger National Park suggest that the ratio of deep to shallow taproot diameters provides a reasonable proxy for potential rooting depth, facilitating extensive interspecific comparison. Detailed excavations also suggest that allocation to deep roots traded off with shallow lateral root investment, and that drought-sensitive species rooted more shallowly than drought-resistant ones. More broadly across 57 species in Southern Africa, potential rooting depths were phylogenetically constrained, with investment to deep roots evident among miombo Detarioids, consistent with results suggesting they green up before onset of seasonal rains. Soil substrate explained variation, with deeper roots on sandy, nutrient-poor soils relative to clayey, nutrient-rich ones. Although potential rooting depth decreased with increasing wet season length, mean annual rainfall had no systematic effect on rooting depth. Overall, our results suggest that rooting depth systematically structures the ecology of savanna trees. Further work examining other anatomical and physiological root traits should be a priority for understanding savanna responses to changing climate and disturbances.

Understanding the distribution and diversity of arbuscular mycorrhizal fungi (AMF) and the rules that govern AMF assemblages has been hampered by a lack of data from natural ecosystems. In addition, the current knowledge on AMF diversity is biased towards temperate ecosystems, whereas little is known about other habitats such as dry tropical ecosystems. We explored the diversity and structure of AMF communities in grasslands, savannas, dry forests and miombo in a protected area under dry tropical climate (Gorongosa National Park, Mozambique) using 454 pyrosequencing. In total, 147 AMF virtual taxa (VT) were detected, including 22 VT new to science. We found a high turnover of AMF with ˂ 12% of VT present in all vegetation types. Forested areas supported more diverse AMF communities than savannas and grassland. Miombo woodlands had the highest AMF richness, number of novel VT, and number of exclusive and indicator taxa. Our data reveal a sharp differentiation of AMF communities between forested areas and periodically flooded savannas and grasslands. This marked ecological structure of AMF communities provides the first comprehensive landscape-scale evidence that, at the background of globally low endemism of AMF, local communities are shaped by regional processes including environmental filtering by edaphic properties and natural disturbance.

• Positive biodiversity–ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance-driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. • We used > 1000 vegetation plots distributed across 10 southern African countries and structural equation modelling to determine the relationship between tree species diversity and above-ground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. • We found positive effects of tree species diversity on above-ground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha−1. We found that water availability mainly affects biomass indirectly, via increasing species diversity. • The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under-appreciated determinant of wooded ecosystem structure and function.

Angola’s forests are abundant and highly productive with enormous potential to support local needs and exportation. The forests are well distributed across the country, but the existing road network is generally poor and, in some cases, inappropriate. Based on our previous work examining deforestation patterns and the modeling of primary tree attributes of vegetation types, we proposed forest management zones (MZ) for future planning in Huambo province in Angola. Herein, that same framework is applied for the detection of the existing road network in Huambo and the proposal of alternative routes inside the MZ. We used analytic hierarchy process (AHP) and geographic information systems (GIS) to optimize connectivity among the existing forest plantations and their distance to the closest major cities within the province. We developed road suitability maps based on AHP and GIS to ensure safer driving conditions and contribute to the forest planner’s access to the current plantations. According to the suitability map created, 59.51% of the total area is suitable for road development and is counted in classes 4 and 5 in automatic classification. Parameters such as geology, slope, distance from roads to the railway, soil types, elevation, flow accumulation, and aspect were used. We provide a completed assessment of the state of existing roads and evaluate the safety of the observed road sections based on the AHP method. The calculated weights of the factors were all consistent with the model used (consistency ratio was 0.09 < 0.1). Finally, we proposed the best alternative routes to the existing cities, MZ in miombo woodlands, and forest plantations inside the province. Our findings indicated that flow accumulation, soil type, and geology were the most significant factors impacting road construction. Overall, our framework is an important starting point for further research activities towards developing a spatial decision support system (SDSS) for planning road networks in Angola.

Southern Africa experiences a great number of wildfires, but the dependence on low-resolution products to detect and quantify fires means both that there is a time lag and that many small fire events are never identified. This is particularly relevant in miombo woodlands, where fires are frequent and predominantly small. We developed a cutting-edge deep-learning-based approach that uses freely available Sentinel-2 data for near-real-time, high-resolution fire detection in Mozambique. The importance of Sentinel-2 main bands and their derivatives was evaluated using TreeNet, and the top five variables were selected to create three training datasets. We designed a UNet architecture, including contraction and expansion paths and a bridge between them with several layers and functions. We then added attention gate units (AUNet) and residual blocks and attention gate units (RAUNet) to the UNet architecture. We trained the three models with the three datasets. The efficiency of all three models was high (intersection over union (IoU) > 0.85) and increased with more variables. This is the first time an RAUNet architecture has been used to detect fire events, and it performed better than the UNet and AUNet models—especially for detecting small fires. The RAUNet model with five variables had IoU = 0.9238 and overall accuracy = 0.985. We suggest that others test the RAUNet model with large datasets from different regions and other satellites so that it may be applied more broadly to improve the detection of wildfires.

Although charcoal production is a source of income, it is often associated with deforestation due to the felling of trees in rural areas. In this study, we quantified the yield of carbonization in the rural area of Lubumbashi, Democratic Republic of the Congo (DR Congo), and identified its determinants. By analyzing 20 kilns of professional producers in different villages, we found that these charcoal producers build large kilns, which contained an average of 46.9 ± 21.5 m3 of wood from 19 species of Miombo woodland trees, with a predominance of Julbernardia paniculata (Benth.) Troupin, alongside Brachystegia microphylla Harms and B. spiciformis Benth. The average carbonization yield was 10.2%, varying from village to village due to parameters such as kiln size, quantity of wood used, kiln coverage time, wind exposure, substrate type, and tree species. It was noted that the moisture content and dimensions of the wood did not significantly correlate with the quantity of charcoal harvested per kiln. Yield improvement should, therefore, take these parameters into account to enable charcoal producers to increase their income while adopting sustainable production practices.

Application of 3D data derived from images captured using unmanned aerial vehicles (UAVs) in forest biomass estimation has shown great potential in reducing costs and improving the estimates. However, such data have never been tested in miombo woodlands. UAV-based biomass estimation relies on the availability of reliable digital terrain models (DTMs). The main objective of this study was to evaluate application of 3D data derived from UAV imagery in biomass estimation and to compare impacts of DTMs generated based on different methods and parameter settings. Biomass was modeled using data acquired from 107 sample plots in a forest reserve in miombo woodlands of Malawi. The results indicated that there are no significant differences (p = 0.985) between tested DTMs except for that based on shuttle radar topography mission (SRTM). A model developed using unsupervised ground filtering based on a grid search approach, had the smallest root mean square error (RMSE) of 46.7% of a mean biomass value of 38.99 Mg·ha−1. Amongst the independent variables, maximum canopy height (Hmax) was the most frequently selected. In addition, all models included spectral variables incorporating the three color bands red, green and blue. The study has demonstrated that UAV acquired image data can be used in biomass estimation in miombo woodlands using automatically generated DTMs.