The savanna habitats often harbour abundant and species-rich bat communities. Whether they represent mere ad hoc assemblages of incidentally co-occurring forms or distinct entities integrated by locally specific adaptations and balanced resource partitionings is largely unknown, as are the natural drivers shaping community variation at different spatial scales. An extensive dataset (130,888 acoustic bat records from 31 acoustic parataxa) was collected in 60 plots across Kruger National Park (KNP), South Africa; the plots were located (i) at perennial rivers, (ii) at seasonal rivers, and (iii) on dry crests away from any water source. Besides the effect of water availability, distance to campsites, and microgeographic variation on bat community richness and structure, we found (i) extensive homogeneity in community structure at local, subregional, and regional scales contrasting to a mosaic from between-plot variation, (ii) absence of robust effects of environmental biotic and abiotic predictors on the distribution of individual acoustic parataxa and community variation, (iii) nearly identical pattern of habitat preferences in all community members approaching the centroid of KNP habitat variation, and (iv) an exceptionally high degree of community nestedness. These results suggest that the bat community of the KNP savanna biome represents a single entity consistently integrated with a network of coexistence relations that probably arose locally during a long savanna history.

Savanna ecosystems, characterised by pronounced seasonality and heterogeneous vegetation, are increasingly threatened by woody encroachment and climate change. Spaceborne lidar from the Global Ecosystem Dynamics Investigation (GEDI) provides critical data for monitoring these changes, yet its application in savannas is challenged by phenological variability. Focusing on Kruger National Park, South Africa, we evaluate how phenology-aligned training sample selection and feature engineering affect the performance and temporal transferability of random forest models estimating canopy height, canopy cover, plant area index, and foliage height diversity. We compare three strategies to identify leaf-on GEDI observations (internal flag, static window, and a novel dynamic approach) and test alternative beam-sensitivity thresholds. We also assess the predictive value of synthetic aperture radar (SAR) and multispectral features derived from Sentinel-1 and Sentinel-2 time series. Results show that models trained on static and dynamic sample subsets consistently outperform those trained on the flag subset. Unlike the static approach, the novel dynamic method captures phenological variation without requiring prior regional knowledge, thereby offering a more transferable solution. Optimising beam sensitivity reduces estimation errors, particularly for canopy top height. Furthermore, we find that models using SAR features achieve higher accuracy and temporal stability then multispectral-based models, reflecting SAR backscatter robustness during the dry season. By enabling reliable mapping of vegetation structure, this framework supports operational monitoring of woody encroachment, habitat structure, and herbivore-fire-vegetation interactions. Overall, integrating phenology-aligned training sample selection with SAR features provides a robust framework for generating consistent records of savanna vegetation structure.

The negative impact of alien species is recognised as a major threat to biodiversity. An impact indicator, a measurable proxy of the status of alien species impacts over space and time, is essential for informing biological invasion policies and management strategies. We introduce an open-source workflow for computing impact indicators of alien species, combining occurrence data from the Global Biodiversity Information Facility (GBIF) with assessments of Environmental Impact Classification for Alien Taxa (EICAT). To implement the workflow, we developed an R package, impIndicator, which allows users to compute and visualise impact indicators for individual species and sites, as well as regional impact indicators. This tool can support ecological research and management by providing standardised insights into where alien species pose the greatest threats and whether current interventions are effectively reducing them. Such information is directly relevant to policy frameworks, including Target 6 of the Convention on Biological Diversity’s Kunming–Montreal Global Biodiversity Framework and the Sustainable Development Goals. We demonstrate the workflow using Acacia species in the Iberian Peninsula, South Africa and California, showcasing the spatiotemporal dynamics of their impacts and highlighting sites with higher impact risk. The resulting impact indicators were sensitive to variation in sampling effort and the completeness of the underlying occurrence data, highlighting the importance of well-sampled and systematically curated biodiversity datasets for robust impact assessment.

Climate change is driving unprecedented declines in dominant, habitat-forming foundation species across marine and terrestrial ecosystems globally. As climatic novelty becomes the norm, ecosystem reassembly will become increasingly common. Predicting and understanding these transitions, and their implications for future ecosystem functioning, is essential for designing effective forward-looking management strategies. We explored 3 scenarios that describe a range of ecosystem reassembly trajectories following declines in previously dominant habitat-forming taxa: compensation, in which functionally similar subdominant or immigrating taxa maintain ecosystem structure and function; decline, in which no compensation occurs leading to loss of ecosystem structure and function; and transformation, in which the ecosystem present historically can no longer persist and shifts into a fundamentally different ecosystem type with distinct structure and function. This range of potential outcomes highlights the urgent need to assess the ecological feasibility and functional implications of potential management actions. Scientists and managers can work together to quantify local-scale climatic novelty and ecosystem resilience to better predict the most likely reassembly trajectories and identify management interventions that will optimize ecosystem function. This approach would allow for more proactive planning to support persistence of ecosystem structure and function, helping to future-proof ecosystem management in a rapidly changing world.

Tropical savannahs experience pronounced seasonality, especially in rainfall and temperature, shaping plant productivity and resource availability. Yet, temporal patterns in insect diversity remain poorly understood. We investigated seasonal variation in species richness and community composition of moths (herbivores) and mantises (predators) across four main landsystems in Kruger National Park, South Africa. Using light traps during early and late wet seasons, we captured 65 593 moths (817 morphospecies) and 3511 mantises (38 morphospecies). Species richness of both groups significantly increased from the early to the late wet season, particularly in the wetter southern landsystems, likely driven by rainfall-enhanced resource availability and habitat complexity. Community composition varied seasonally and among landsystems, with moths primarily influenced by seasonal changes, whereas mantises responded more strongly to landsystem differences. Our results indicate that rainfall-driven seasonal resource variability is a key determinant of insect phenological patterns in tropical savannahs. Predicted shifts in rainfall patterns due to climate change may alter insect emergence timing and trophic interactions, highlighting the importance of incorporating seasonal dynamics into biodiversity conservation and management strategies.

Afrotropical savannas are biodiversity-rich ecosystems increasingly threatened by woody plant encroachment. In southern Africa, the leguminous tree Colophospermum mopane dominates over one-third of the savanna region and is projected to expand substantially under climate change. Yet, the consequences of its local dominance for biodiversity remain poorly understood. We conducted the first landscape-scale, multi-taxon assessment of mopane’s bottom-up effects, analysing species richness and community composition of vascular plants, insects, birds, bats, and non-flying mammals across a gradient of mopane cover in Kruger National Park, South Africa. Our replicated plot-based study found that species richness of birds, mammals, bats, and insects declined significantly with increasing mopane dominance, with the steepest reductions in birds. Plant overall species richness was unaffected, although grasses showed a weak positive trend. We also revealed significant community compositional shifts in birds, bats, and mammals, while insect communities lost species without systematic composition change. Functional-group analyses confirmed species richness declines for herbivores across taxa, and for bird carnivores and omnivores, pointing to mopane’s role as a strong ecological filter that reduces host plant and other resources availability, with consequences to the higher trophic levels. These results highlight mopane dominance as a potential driver of biodiversity simplification in African savannas, with cascading implications for ecosystem functioning. Given projections of mopane expansion and its socioeconomic value to local communities, management and policy must avoid promoting mopane dominance in land-use or restoration schemes. Safeguarding heterogeneous savanna mosaics will be essential for conserving biodiversity and ecosystem resilience under climate change. ### Competing Interest Statement The authors have declared no competing interest. Czech Science Foundation, https://ror.org/01pv73b02, 18-18495S, 21-24186M

AimDespite the evidenced importance of insects in savannah ecosystems, the drivers of their diversity patterns remain poorly understood, particularly in the Afrotropical region. This study addresses part of this gap by investigating the effects of climate, habitat, disturbance and vegetation variables on species richness and community composition of phytophagous and predatory insects in South African savannahs.LocationKruger National Park (KNP), South Africa.TaxonPhytophagous insects (moths) and carnivorous insects (mantises).MethodsMoths and mantises were light-trapped in 60 plots distributed across KNP during two seasons. Direct and indirect effects of environmental variables on insect species richness were analysed using structural equation models, and on community composition through distance-based redundancy analyses (db-RDA).ResultsBased on an extensive dataset of 65,593 moth individuals representing 817 species and 3511 mantis individuals representing 38 species, we identified plant communities as the primary driver of species richness and community structure for both insect groups. The effects of vegetation on insect communities were indirectly shaped by climate, particularly mean temperature (negatively correlated with precipitation), through its effects on plant species richness. Additionally, a complex interplay among bedrock type, water availability and disturbance from large herbivores further shaped insect diversity.Main ConclusionsOur findings highlight the critical role of plant species richness in determining insect diversity patterns in savannah ecosystems. We also confirmed the region's vulnerability to climate change, as decreasing precipitation and increasing temperatures alter vegetation composition and biomass, consequently affecting insect communities. Effective conservation strategies should focus on managing large herbivores to maintain diverse vegetation, which is crucial for supporting insect diversity. Priority should be given to balancing water availability and disturbance intensity, particularly in preserving the health of rivers and their surroundings, to mitigate the adverse effects of climate change on these ecosystems.

Across savanna ecosystems worldwide, the decline of large trees and the rapid expansion of shrubs present major conservation challenges. These trends are especially pronounced in South Africa's Kruger National Park (KNP), the country's largest protected area. To quantify their extent and identify their drivers, we conducted a spatial assessment of tree cover and density across KNP from 2011 until 2022. We then evaluated how these response variables are influenced by abiotic factors, including fire, climate, soil, and geology, and by biotic factors, such as the densities of African elephant adult male bulls and herds, including females and calves. We defined trees as land-cover elements that cast a distinct shadow and stand taller than 5 m. Using Collect Earth, an open-source software for augmented visual interpretation of high-resolution satellite imagery, we assessed tree cover and density on 4258 plots of 0.5 ha each. We recorded 27,918 trees, equivalent to an average density of 13 trees/ha. Counts in each plot were truncated to a maximum of 30 individuals. We validated our estimates of tree cover and height against independent, high-resolution airborne LiDAR measurements, which yielded an RMSE of 8.89% for trees taller than 3 m. The relative influence of selected predictors on tree cover and density was analyzed through logistic and survival regressions. Geology had the greatest influence on tree distribution, where both tree cover and density were higher on nutrient-poor granitic substrates than on nutrient-rich basalts. Tree cover and density were higher in areas with low fire frequency, close to main rivers, and with higher sand content in the soil. The mean annual rainfall showed a positive correlation with tree cover, while it had a negative correlation with the number of trees. Elephant bulls were found to be negatively correlated with both tree cover and density. In contrast, elephant herds exhibited a positive correlation with tree cover and density. This study highlights the importance of understanding the effects of multiple factors on tree distribution and aims to provide a baseline for assessing tree cover and density across KNP to support ongoing tree management strategies and contribute to future conservation priorities.

We aim to explore what processes dominate community assembly of dragonflies (Odonata: Anisoptera) and damselflies (Odonata: Zygoptera) by differentiating the environmental and geographical drivers behind compositional turnover of narrow-ranged versus widespread species. In this way, we further aim to describe patterns of species incidence and compositional turnover to expand upon the body of knowledge related to understanding biodiversity patterns and processes. We explored species turnover of dragonflies and damselflies separately, using zeta diversity to measure compositional turnover among multiple assemblages. Narrow-ranged and widespread species within each suborder showed similar drivers. Specifically, both narrow-ranged and widespread dragonflies show rapid turnover with small shifts in annual mean temperature, temperature seasonality and annual precipitation, whereas for damselflies, the major driver for turnover is distance between sites followed by climatic variables. Our results therefore show that odonate turnover is largely driven by climate, although the limited dispersal capabilities of damselflies also influences community assembly. Climate change could cause major changes in composition of odonates, presenting a challenge for conservation planning in Africa as species assemblages that were previously conserved may no longer be protected if their ranges shift outside protected areas. For damselflies, adaptation is a major concern, and with their limited dispersal capabilities and climate sensitivity, they may not be able to migrate effectively in response to changing climate conditions. The underlying assembly processes do not differ considerably for narrow-ranged and widespread species within each suborder, suggesting that conservation planning tailored to each suborder may be sufficient in Africa.

AbstractThe savanna ecosystem is dominated by grasses, which are a key food source for many species of grazing animals. This relationship creates a diverse mosaic of habitats and contributes to the high grass species richness of savannas. However, how grazing interacts with environmental conditions in determining grass species richness and abundance in savannas is still insufficiently understood. In the Kruger National Park, South Africa, we recorded grass species and estimated their covers in 60 plots 50 × 50 m in size, accounting for varying proximity to water and different bedrocks. To achieve this, we located plots (i) near perennial rivers, near seasonal rivers, and on crests that are distant from all water sources and (ii) on nutrient‐rich basaltic and nutrient‐poor granitic bedrock. The presence and abundance of large herbivores were recorded by 60 camera traps located in the same plots. Grass cover was higher at crests and seasonal rivers than at perennial rivers and on basalts than on granites. The relationship between grass species richness and herbivore abundance or species richness was positive at crests, while that between grass species richness and herbivore species richness was negative at seasonal rivers. We found no support for controlling the dominance of grasses by herbivores in crests, but herbivore‐induced microsite heterogeneity may account for high grass species richness there. In contrast, the decrease in grass species richness with herbivore species richness at seasonal rivers indicates that the strong grazing pressure over‐rides the resistance of some species to grazing and trampling. We suggest that the relationships between grasses and herbivores may work in both directions, but the relationship is habitat‐dependent, so that in less productive environments, the effect of herbivores on vegetation prevails, while in more productive environments along rivers the effect of vegetation and water supply on herbivores is more important.

Long-term spatial studies are crucial for understanding how the Earth's surface has changed. Before satellite imagery, landscapes were monitored using black and white (B&W) aerial photographs. However, surveys were infrequent and image analysis was a manual process that was both time-consuming and costly. In this study, we created a composite of high spatial resolution (0.5-0.75 m) B&W aerial images from 1939-1944, covering about 91% of Kruger National Park (KNP)'s nearly 2 million ha. We used this to produce the first historical woody cover (tall trees and shrubs) map of KNP, which until now was only partially understood through fragmented descriptions in period literature and small-area case studies. We established a supervised learning workflow using Google Earth Engine (GEE) which included performing an Object-based Image Analysis (OBIA) with a Random Forest classifier. This approach, enhanced by integrating texture, shape, neighboring features, and spectral variables into the training/validation dataset, enabled the identification of woody vegetation from B&W landscape objects. To enhance accuracy, we guided our sampling method using vegetation types with comparable woody cover and species composition. Initially, we tested our method on a smaller set of images (25 km2), and after confirming its effectiveness, we then expanded the approach to cover all available historical aerial imagery. Our results show that in 1939-1944, 26% of KNP was covered in woody vegetation (overall accuracy of 89%, producer's accuracy (non-woody = 88%, woody = 90%), and user's accuracy (non-woody = 90%, woody = 87%)). The importance of geological substrate in driving vegetation pattern is reflected in a higher woody cover percentage on granite (28%) than on basalt (21%) soils, with the lowest woody cover on northern basalts (11%) and the highest on north-central granites (32%). This study highlights the potential of GEE and OBIA for analyzing large-area, high spatial resolution B&W aerial photographs in a systematic and efficient manner and the importance of creating large-scale historical land cover baselines to support environmental planning and landscape management.

EDITORIAL article Front. Ecol. Evol., 28 February 2024Sec. Environmental Informatics and Remote Sensing Volume 12 - 2024 | https://doi.org/10.3389/fevo.2024.1386917

Thanks to the high diversity of ecosystems and habitats, South Africa harbours tremendous diversity of insects. The Kruger National Park, due to its position close to the border between two biogeographic regions and high heterogeneity of environmental conditions, represents an insufficiently studied hotspot of lepidopteran diversity. During our ecological research in the Kruger National Park, we collected abundant moth material, including several interesting faunistic records reported in this study.We reported 13 species of moths which had not yet been recorded in South Africa. In many cases, our records represented an important extension of the species’ known distribution, including two species (Ozarba gaedei and O. persinua) whose distribution ranges extended into the Zambezian biogeographic region. Such findings confirmed the poor regional knowledge of lepidopteran diversity.