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Background. Woody aboveground biomass (AGB) stores and releases carbon in savannas, with fire as a key driver. Aims. Savanna fire management (SFM) programs reduce emissions from AGB burning but do not incorporate live tree carbon sequestration. Assessing the impact of SFM on woody AGB carbon sequestration requires precise measurement and modelling. Methods. We developed a multiscale remote sensing method for woody AGB estimation and applied it across ~105,000 ha of tropical savanna. A novel metric (shade volume) bridged the gap between terrestrial lidar-derived woody AGB and a convolutional neural network (CNN) model trained on airborne lidar and satellite imagery. Using the method we estimated savanna woody AGB and quantified AGB prediction error. Key results. CNN-predicted shade volume had 5.5% mean absolute error and -2.1% bias. Validation against independent 1 ha woody AGB measurements (n = 7) showed 7.9% mean error. In 40.1% of the study region, woody AGB predictions exceeded maximum potential biomass estimated by Australia’s national carbon accounting model. Conclusions. This methodology improves carbon estimation accuracy over large areas, enabling fine-scale monitoring of woody AGB under varied SFM strategies. Implications. Enhancing SFM carbon credit integrity requires direct measurement and transparency in woody AGB quantification, both achievable with this method.

Tree-grass coexistence is a defining feature of savanna ecosystems, which play an important role in supporting biodiversity and human populations worldwide. While recent advances have clarified many of the underlying processes, how these mechanisms interact to shape ecosystem dynamics under environmental stress is not yet understood. Here, we present and analyse a minimalistic spatially extended model of tree-grass dynamics in dry savannas. We incorporate tree facilitation of grasses through shading and grass competing with trees for water, both varying with tree life stage. Our model shows that these mechanisms lead to grass-tree coexistence and bistability between savanna and grassland states. Moreover, the model predicts vegetation patterns consisting of trees and grasses, particularly under harsh environmental conditions, which can persist in situations where a non-spatial version of the model predicts ecosystem collapse from savanna to grassland instead (a phenomenon called ‘Turing-evades-tipping’). Additionally, we identify a novel ‘Turing-triggers-tipping’ mechanism, where unstable pattern formation drives tipping events that are overlooked when spatial dynamics are not included. These transient patterns act as early warning signals for ecosystem transitions, offering a critical window for intervention. Further theoretical and empirical research is needed to determine when spatial patterns prevent tipping or drive collapse.

Aim: Theory suggests that as ecological systems approach regime shifts, they become increasingly slow in recovering from perturbations. This phenomenon, known as critical slowing down [CSD], leads to spatial and temporal signatures in ecological state variables, thus potentially offering early indicators of regime shifts. Indicators using temporal dynamics have been empirically validated in laboratory microcosms and other well-mixed systems, but tests of spatial indicators of regime shifts at large spatial scales in the field are rare due to the relative absence of high-resolution data and difficulties in experimental manipulations. Here, we test theoretical predictions of CSD-based spatial indicators using large-scale field data from the Serengeti-Mara grassland-woodland system. Location: Serengeti-Mara ecosystem, Tanzania and Kenya. Time period: Year 2000 Major taxa studied: Vegetation Method: We used a space-for-time substitution method to empirically test the validity of CSD-based spatial indicators, i.e., we computed indicators along a spatial [in lieu of temporal] gradient of ecological states. First we used a model of vegetation dynamics to determine if our space-for-time substitution method was appropriate. Then we tested for CSD-based spatial indicators using high-resolution spatial vegetation [30 m] and rainfall [2.5 km] data from the Serengeti-Mara ecosystem. Results: Our model predicts that CSD-based indicators increase along a spatial gradient of alternative vegetation states. Empirical analyses suggest that grasslands and woodlands occur as alternative stable states in the Serengeti-Mara ecosystem with rainfall as one of the potential drivers of transitions between these states. We found that four indices of CSD showed the theoretically expected increasing trends along spatial gradients of grasslands to woodlands: spatial variance, spatial skewness, spatial correlation at lag-1 and spatial spectra at low frequencies. Main conclusions: Our results suggest that CSD-based spatial indicators can offer early warning signals of critical transitions in large-scale ecosystems.

During the southern summer season of 2015 and 2016, South Africa experienced one of the most severe meteorological droughts since the start of climate recording, due to an exceptionally strong El Niño event. To investigate spatiotemporal dynamics of surface moisture and vegetation structure, data from ESA’s Copernicus Sentinel-1/-2 and NASA’s Landsat-8 for the period between March 2015 and November 2017 were utilized. In combination, these radar and optical satellite systems provide promising data with high spatial and temporal resolution. Sentinel-1 C-band data was exploited to derive surface moisture based on a hyper-temporal co-polarized (vertical-vertical—VV) radar backscatter change detection approach, describing dynamics between dry and wet seasons. Vegetation information from a TLS (Terrestrial Laser Scanner)-derived canopy height model (CHM), as well as the normalized difference vegetation index (NDVI) from Sentinel-2 and Landsat-8, were utilized to analyze vegetation structure types and dynamics with respect to the surface moisture index (SurfMI). Our results indicate that our combined radar–optical approach allows for a separation and retrieval of surface moisture conditions suitable for drought monitoring. Moreover, we conclude that it is crucial for the development of a drought monitoring system for savanna ecosystems to integrate land cover and vegetation information for analyzing surface moisture dynamics derived from Earth observation time series.

1. Prescribed burning is used in tropical savannas to improve habitat conditions for domestic and wild herbivores, but its effects on the ecological interactions between these herbivore guilds have never been assessed experimentally. Understanding such effects will contribute towards more informed management of both guilds in landscapes where they share habitats. 2. We investigated the effects of burning on the nutritional outcomes for cattle sharing habitat with wildlife in a Kenyan savanna ecosystem. We compared forage availability and cattle forage and nutrient intake rates across burned and unburned areas cattle accessed exclusively, and those they shared with medium-sized wild ungulates, both with and without megaherbivores (elephants and giraffes). We performed these measurements in May 2013 (wet period, 2 months post-burning) and February 2014 (dry period, 11 months post-burning). Additionally, we monitored wildlife use of these areas. 3. Prescribed burning enhanced cattle nutrition, but only in areas cattle did not share with wildlife. Shared foraging with wildlife reduced cattle forage and nutrient intake rates by 37-97% in burned areas (burns), but not in unburned areas; these reductions corresponded with reduced herbage availability in the shared burns. 4. In May (the wet period), cattle met their nutrient intake requirements in burns, regardless of whether they were sharing these areas with wildlife. However, in February (the dry period), nutrient requirements were unmet or tended to be unmet in burns shared with wildlife; requirements were met or significantly exceeded in the unshared burns. 5. Experimental exclusion of megaherbivores did not moderate these effects, suggesting that they were primarily caused by medium-sized wild ungulates which were highly attracted to burns. 6. Synthesis and applications. Prescribed burning produces negative nutritional outcomes for cattle when sharing habitat with wild ungulates. Because these effects could negatively influence livestock-wildlife coexistence, burning should be applied prudently in such human-occupied savanna landscapes. Specifically, because unburned areas serve as refuge foraging areas during the dry season, interspersing burns with unburned areas could minimize fire-driven negative interactions between cattle and wild ungulates. Conversely, burning could be used to draw wildlife away from valuable cattle foraging areas, such as those near available water.

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas.

Vegetation changes in savanna ecosystems are playing an increasingly important role in shaping tick populations and the spread of tick-borne diseases, with consequences for both wildlife and livestock health. This study examines how factors such as climate variability, land use, vegetation structures, and host availability influence tick survival, distribution, and behavior. As grasslands degrade and woody plants become more dominant, ticks are finding more suitable habitats, often supported by microclimatic conditions that favor their development. At the same time, increased contact between domestic and wild animals is facilitating the transmission of pathogens. This review highlights how seasonal patterns, fire regimes, grazing pressure, and climate change are driving shifts in tick activity and expanding their geographical range. These changes increase the risk of disease for animals and humans alike. Addressing these challenges calls for integrated management strategies that include vegetation control, host population monitoring, and sustainable vector control methods. A holistic approach that connects ecological, animal, and human health perspectives is essential for effective disease prevention and long-term ecosystem management.

Recent studies have argued that changes in fire regimes in the 21st century are posing a major threat to global biodiversity. In this scenario, incorporating species’ physiological, ecological, and evolutionary traits with their local fire exposure might facilitate accurate identification of species most at risk from fire. Here, we developed a framework for identifying the animal species most vulnerable to extinction from fire-induced stress in the Brazilian savanna. The proposed framework addresses vulnerability from two components: (1) exposure, which refers to the frequency, extent, and magnitude to which a system or species experiences fire, and (2) sensitivity, which reflects how much species are affected by fire. Sensitivity is based on biological, physiological, and behavioral traits that can influence animals’ mortality “during” and “after” fire. We generated a Fire Vulnerability Index (FVI) that can be used to group species into four categories, ranging from extremely vulnerable (highly sensible species in highly exposed areas), to least vulnerable (low-sensitivity species in less exposed areas). We highlight the urgent need to broaden fire vulnerability assessment methods and introduce a new approach considering biological traits that contribute significantly to a species’ sensitivity alongside regional/local fire exposure.

Despite calls by various international agencies, considerable work is still required to understand and incorporate the importance of earth’s ecosystems for informing public policies. Savannas comprise nearly one third of global terrestrial ecosystems and support many local and Indigenous communities, but the value of their ecosystem services (ES) is insufficiently understood. This study proposes an integrated ES valuation framework and applies it to assess ES for an Indigenous savanna estate in northern Australia, describing how capabilities along with biophysical and socio-cultural ES benefits play a vital role for peoples’ wellbeing. We estimated the monetary value of ES by applying a conventional Basic Value Transfer (BVT) method for biophysical benefits (USD 84 M y−1), and a wellbeing approach for valuing socio-cultural benefits and capabilities (USD 4 M y−1). The latter offers a relatively nominal estimate but underscores the importance of including peoples’ capabilities in order to demonstrate wellbeing benefits for Indigenous people who regularly visit and utilize their lands. We explore two scenarios, Business as Usual (pastoral land use) and ES-based economies (implying customary land use, particularly through fire management) to project plausible broader benefits for the community over a longer term. This research describes how inclusion of Indigenous peoples’ capabilities and socio-cultural values are critical for ES assessments, and indicates that an integrated approach is essential for appropriately informing local, regional and global development policies.

Savanna ecosystems contribute ~30% of global net primary production (NPP), but they vary substantially in composition and function, specifically in the understory, which can result in complex responses to environmental fluctuations. We tested how understory phenology and its contribution to ecosystem productivity within a longleaf pine ecosystem varied at two ends of a soil moisture gradient (mesic and xeric). We used the Normalized Difference Vegetation Index (NDVI) of the understory and ecosystem productivity estimates from eddy covariance systems to understand how variation in the understory affected overall ecosystem recovery from disturbances (drought and fire). We found that the mesic site recovered more rapidly from the disturbance of fire, compared to the xeric site, indicated by a faster increase in NDVI. During drought, understory NDVI at the xeric site decreased less compared to the mesic site, suggesting adaptation to lower soil moisture conditions. Our results also show large variation within savanna ecosystems in the contribution of the understory to ecosystem productivity and recovery, highlighting the critical need to further subcategorize global savanna ecosystems by their structural features, to accurately predict their contribution to global estimates of NPP.