Leakiness: A new index for monitoring the health of arid and semiarid landscapes using remotely sensed vegetation cover and elevation data

The health of arid and semiarid lands needs to be monitored, particularly if they are used to produce food and fiber, and are prone to loss of vegetation cover and soil. Indicators of landscape health based on remotely sensed data could cost-effectively integrate structural and functional attributes of land surfaces across a range of scales. In this paper, we describe a new index for remotely monitoring changes in the health of land. The new index takes important aspects of landscape structure and function into account by focusing on the potential for landscapes to lose or ‘leak’ (not retain) soil sediments. We combined remotely sensed vegetation patchiness data with digital elevation model (DEM) data to derive a quantitative metric, the landscape leakiness index, LI. This index is strongly linked to landscape function by algorithms that reflect the way in which spatial configuration of vegetation cover and terrain affect soil loss. Linking LI to landscape function is an improvement on existing indicators that are based on qualitatively assessing remotely sensed changes in vegetation cover. Using archived Landsat imagery and Shuttle Radar Topography Mission DEMs, we found for example that LI indicated improvements in the condition or health of a rangeland paddock that was monitored from 1980 to 2002. This paddock is located in central Australia and its improved health is documented by photographs and field data. Although the full applicability of LI remains to be explored, we have demonstrated that it has the potential to serve as a useful ecological indicator for monitoring the health of arid and semiarid landscapes.     

Use of indigenous ecological knowledge of the Maasai pastoralists for assessing rangeland biodiversity in Tanzania

This paper incorporates the indigenous ecological knowledge (IEK) of the Maasai pastoralists and ecological methods to assess effects of grazing and cropping on rangeland biodiversity at macro‐ and micro‐landscape scales in northern Tanzania. The joint surveys with pastoralists identified indicator plant species and their associations with micro‐landscapes and livestock grazing suitability (i.e. for cattle and small ruminant grazing), while traditional calf‐pasture reserves (alalili pl. alalilia) were evaluated for preservation of rangeland biodiversity. The macro‐landscapes comprising the cool high plateau (osupuko pl. isipuki) and montane forest highland (endim) were included in the survey. At micro‐landscape scales, the osupuko was classified into uplands (orkung'u), slopes (andamata) and dry valley bottomlands (ayarata). The micro‐landscapes were assessed in terms of herbaceous plant species and woody species richness and risks of soil erosion. Biodiversity varied at both the macro‐ and micro‐landscape scales and in accordance with the land‐use types. Greater plant species diversity and less erosion risks were found in the pastoral landscapes than in the agro‐pastoral landscapes. The calf‐grazing pastures had greater herbaceous species richness than the non‐calf pastures, which in turn had more woody species. The study concludes that the indigenous systems of landscape classification provides a valuable basis for assessing rangeland biodiversity, which ecologists should incorporate into ecological surveys of the rangelands in East Africa in the future.     

Use of terrestrial invertebrates for biodiversity monitoring in Australian rangelands,with particular reference to ants

Abstract Taken literally, the aim of biodiversity monitoring is to track changes in the biological integrity of ecosystems. Given the overwhelmingly dominant contribution of invertebrates to biodiversity, no biodiversity monitoring programme can be considered credible if invertebrates are not addressed effectively. Here we review the use of terrestrial invertebrates, with a particular focus on ants, as bioindicators in Australia in the context of monitoring biodiversity in Australia's rangelands. Ant monitoring systems in Australia were initially developed for assessing restoration success following mining, and have since been applied to a wide range of other land‐use situations, including grazing impacts in rangelands. The use of ants as bioindicators in Australia is supported by an extensive portfolio of studies of the responses of ant communities to disturbance, as well as by a global model of ant community dynamics based on functional groups in relation to environmental stress and disturbance. Available data from mining studies suggest that ants reflect changes in other invertebrate groups, but this remains largely undocumented in rangelands. The feasibility of using ants as indicators in land management remains a key issue, given the large numbers of taxonomically challenging specimens in samples, and a lack of invertebrate expertise within most land‐management agencies. However, recent work has shown that major efficiencies can be achieved by simplifying the ant sorting process, and such efficiencies can actually enhance rather than compromise indicator performance.     

Integrating remote sensing and local ecological knowledge to monitor rangeland dynamics

Rangelands are among the most extensive anthropogenic landscapes on earth, supporting nearly 500 million people. Disagreements over the extent and severity of rangeland degradation affect pastoralist livelihoods, especially when impacts of drought and over-grazing are confounded. While vegetation indices (such as NDVI, or Normalized Difference Vegetation Index) derived from remotely sensed imagery are often used to monitor rangelands, their strategic integration with local ecological knowledge (LEK) is under-appreciated. Here, we explore these complementary approaches in Kyrgyzstan’s pasture-rich province of Naryn, where disagreements regarding pasture degradation could greatly benefit from additional information. We examine a time series of MODIS satellite imagery (2000–2015) to characterize browning trends in vegetation as well as to distinguish between climate- and grazing-induced trends. We also compare and contrast measured trends with LEK perceptions of pasture degradation. To do so, we first examine statistical trends in NDVI as well as in NDVI residuals after de-trending with meteorological data. Second, we use participatory mapping to identify areas local pasture managers believe are overgrazed, a particularly useful approach in lieu of reliable historical stocking rates for livestock in this region. Lastly, we compare the strengths and weaknesses of LEK and remote sensing for landscape monitoring.Browning trends were widespread as declining trends in NDVI (and NDVI residuals) covered 24% (and 9%) of the landscape, respectively. Local managers’ perceptions of pasture degradation better reflected trends seen in NDVI than in climate-controlled NDVI residuals, suggesting patterns in the latter are less apparent to managers. Our approach demonstrated great potential for the integration of two inexpensive and effective methods of rangeland monitoring well-suited to the country’s needs. Despite limitations due to terrain, our approach was most successful within the semi-arid steppe where pasture degradation is believed to be most severe. In many parts of the world, sources of long-term spatially extensive data are rare or even non-existent. Thus, paired LEK and remote sensing can contribute to comprehensive and informative assessments of land degradation, especially where contentious management issues intersect with sparse data availability. LEK is a valuable source of complementary information to remote sensing and should be integrated more routinely and formally into landscape monitoring. To aid this endeavor, we synthesize advice for linking LEK and remote sensing across diverse landscape situations.     

Monitoring rangeland biodiversity: Plants as indicators

Abstract As well as being important components of biodiversity in their own right, plants reflect the physical environment, are the primary target of many of the pressures acting on rangelands, and are relatively amenable to measurement. Hence, measurements based on plants have considerable potential to be efficient indicators of the response of rangeland biodiversity to land use. A recent report commissioned by the National Land and Water Resources Audit recommended a core set of 11 indicators, six of which relied on measurements of plants. These were trends in (i) the extent of clearing; (ii) the cover of native perennial ground‐layer vegetation; (iii) the distribution and abundance of exotic plant species; (iv) the distribution and abundance of fire‐sensitive species; (v) the distribution and abundance of grazing‐sensitive species; and (vi) the distribution and abundance of listed threatened entities. Most indicated responses of plants to pressures acting on them. Only two (clearing and exotic plants) related to pressures. We recommend that the set be expanded to include two additional pressure indicators, one for grazing and another for fire, in recognition of their extent and potential influence on rangeland biodiversity. We also recommend that benchmark sites be included in all ground‐based monitoring programmes to provide reference standards for those biotic indicators about which little is known. Assessments of the current state of knowledge about these indicators for two case‐study regions, the Gascoyne–Murchison strategy area and Cape York Peninsula, have shown that it would be possible to monitor most of them directly at regional scales, but that current monitoring programmes fall short of achieving this.     

Desertification in the Sahel: a reinterpretation

The impact of human management, in particular livestock grazing, on the vegetation cover of the Sahel is still debated. In a range of studies, satellite images have been used to analyze the development of the Sahelian vegetation cover over time. These studies did not reveal any significant degradation of the Sahel in the last two decades. In this paper, we examine the ecological assumptions underlying the use of satellite imagery to analyze degradation of the Sahel. Specifically, we analyze the variability of the rain‐use efficiency (RUE), which is often used as an indicator for the state of the vegetation cover. We detect a fundamental flaw in the way RUE has been handled in most remote sensing studies; they ignored the relation between annual rainfall variation and RUE. Because of the upward trend in annual rainfall that occurred during the 1980s and 1990s, this leads to a bias in the interpretation of the satellite images. In this paper, we show the importance of the variability in RUE for the analysis of remote sensing imagery of semiarid rangelands. Our analysis also shows that it is likely that there has been anthropogenic degradation of the Sahelian vegetation cover in the last two decades. This has important consequences for the debate on the impacts of grazing on semiarid rangelands. Furthermore, the occurrence of anthropogenic degradation is relevant to explain the magnitude of 20th century Sahelian droughts. The analyses also indicate that the population of the Sahel may be more vulnerable for droughts than currently assumed.     

The value of paddock trees for regional conservation in an agricultural landscape

Summary Isolated trees and small patches of trees – paddock trees – are a prominent feature of agricultural landscapes in Australia, but are declining in many areas due to natural senescence, clearing, dieback and the general absence of recruitment. We assessed the importance of paddock trees for woodland conservation in a 30 000 ha sample of the New South Wales (NSW) South‐west Slopes using Satellite Pour l’Observation de la Terre (SPOT) panchromatic satellite imagery combined with models predicting the original distribution of vegetation communities. Tree‐cover occurred over 12% of the study area. The patch‐size distribution of vegetation in the study area varied between woodland types. For woodland communities that were confined to hills and ridges, most tree‐cover occurred as few, large remnants. For woodland communities of the foothills and plains (Blakely's Red Gum, Eucalyptus blakelyi and Yellow Box, Eucalyptus melliodora, or White Box, Eucalyptus albens and Red Stringybark), 54% of remnant tree‐cover occurred as patches < 1 ha. The loss of paddock trees will cause substantial reductions to some woodland communities. For example, the loss of patches < 1 ha in woodlands dominated by Blakely's Red Gum and Yellow Box would reduce this association from 7.4% to 3.4% of its predicted pre‐1750 distribution. Mean distance to tree‐cover across the study area increased almost fourfold if patches < 1 ha were removed from the landscape, which may have consequences for movements of some flora and fauna. Failure to protect and perpetuate paddock trees will diminish the likelihood of achieving the conservation objectives of comprehensiveness, adequacy and representativeness in agricultural landscapes.     

Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation

A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672km² area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio-temporal variables such as rainfall, soil type, and vegetation community distributions, due to the nature of the cross-fence experimental design, and the spatially comprehensive data available in satellite imagery. This method provides a potential tool to aid land managers in decision making processes, particularly with regard to stocking rates.     

Vegetation mapping of the Great Fish River basin,South Africa: Integrating spatial and multi‐spectral remote sensing techniques

Abstract. We present a remote sensing based vegetation mapping technique well suited to a heterogeneous, semi‐arid environment. 10 structural vegetation classes were identified and described on the ground. Using Landsat‐TM from two different seasons and a combination of three conventional classification techniques (including a multi‐temporal classification) we were unsuccessful in delineating all of the desired vegetation classes. We then employed a simple tex‐tural classification index, known as the Moving Standard Deviation Index (MSDI), that has been used to map degradation status. MSDI measures spatial variations in the landscape and is calculated by passing a 3 × 3 standard deviation filter across the Landsat‐TM red band. High MSDI values are associated with degraded or disturbed rangelands whilst low MSDI values are associated with undisturbed rangeland. A combination of two conventional multi‐spectral techniques and MSDI were used to produce a final vegetation classification at an accuracy of 84 %. MSDI successfully discriminated between two contrasting vegetation types of identical spectral properties and significantly strengthened the accuracy of the classification. We recommend the use of a tex‐tural index such as MSDI to supplement conventional vegetation classification techniques in heterogeneous, semi‐arid or arid environments.     

Diversity of desert rangelands of Tunisia

Plants are important components of any rangeland. However, the importance of desert rangeland plant diversity has often been underestimated. It has been argued that desert rangelands of Tunisia in good ecological condition provide more services than those in poor ecological condition. This is because rangelands in good condition support a more diverse mixture of vegetation with many benefits, such as forage for livestock and medicinal plants. Nearly one-quarter of Tunisia, covering about 5.5 million hectares, are rangelands, of which 87% are located in the arid and desert areas (45% and 42%, respectively). Here, we provide a brief review of the floristic richness of desert rangelands of Tunisia. Approximately 135 species are specific to desert rangelands. The predominant families are Asteraceae, Poaceae, Brassicaceae, Chenopodiaceae, and Fabaceae. These represent approximately 50% of Tunisian desert flora.     

Remote sensing imagery in vegetation mapping: a review

Aims Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping. Generally, it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level. Then, correlations of the vegetation types (communities or species) within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified. These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process, which is also called image processing. This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.Methods Specifically, this paper focuses on the comparisons of popular remote sensing sensors, commonly adopted image processing methods and prevailing classification accuracy assessments.Important findings The basic concepts, available imagery sources and classification techniques of remote sensing imagery related to vegetation mapping were introduced, analyzed and compared. The advantages and limitations of using remote sensing imagery for vegetation cover mapping were provided to iterate the importance of thorough understanding of the related concepts and careful design of the technical procedures, which can be utilized to study vegetation cover from remote sensed images.     

航空航天遥感在物种多样性研究与保护中的应用

人类活动导致全球范围内生物多样性丧失日趋严重。物种多样性是研究最为深入以及最贴近生物多样性管理的层次。物种多样性的研究往往受到多时空尺度生态过程的影响, 传统物种多样性调查方法受到人力物力影响, 局限性大, 物种多样性的研究与管理亟需整合不同来源的数据。遥感技术从传统的光学遥感阶段发展到不同平台、不同维度相结合的多源遥感阶段, 并逐渐进入以高空间分辨率和高光谱为特征、以激光雷达为前沿发展方向的综合遥感阶段。遥感技术因为其监测范围广、能监测人迹罕至地区以及长期可重复等特性, 为研究不同时空尺度的生态学科学问题提供了更新更优的研究手段。本文围绕种群动态、种间关系与群落多样性、功能属性及功能多样性以及生物多样性保护管理等生物多样性研究热点问题, 系统地论述了航空航天遥感技术在物种多样性研究与保护领域的应用, 总结了航空航天遥感技术在研究与物种多样性有关的主要生态学问题中的机遇与挑战。我们认为航空航天遥感技术利用多光谱甚至高光谱与激光技术从空中监测物种多样性, 从不同视角、基于不同光源提供了物种多样性不同侧面的信息, 能够减小地面调查强度, 在大范围和边远地区的物种多样性调查研究中有着至关重要的作用。依据光谱特性的物种判别以及依据激光雷达的三维结构量测将促进生物多样性的研究与管理, 加强遥感学家和生物多样性研究者的沟通交流将有助于促进不同时空尺度的生物多样性与遥感技术的结合。     

Comparison of biodiversity and ground cover between a commercial rotationally grazed property and an adjacent nature reserve in semi‐arid rangeland

Continuous livestock grazing can have negative effects on biodiversity and landscape function in arid and semi‐arid rangelands. Alternative grazing management practices, such as rotational grazing, may be a viable option for broad‐scale biodiversity conservation and sustainable pastoral management. This study compared ground cover, plant species composition and floristic and functional diversity along gradients of grazing intensity between a pastoral property rotationally grazed by goats and an adjacent nature reserve (ungrazed by commercial livestock) in semi‐arid south‐eastern Australia. Understorey plant species composition differed significantly between the rotationally grazed property and the nature reserve, with a greater proportion and frequency of palatable species recorded in the nature reserve. Understorey plant species richness, diversity, functional biodiversity measures and ground cover declined with increasing grazing pressure close to water points under commercial rotational grazing management. However, at a whole‐paddock scale, there were few differences in plant biodiversity and ground cover between the rotationally grazed property and the nature reserve, despite differences in overall plant species composition. Flexible, adaptive, rotational grazing should be investigated further for its potential to achieve both socio‐economic and biodiversity conservation outcomes in semi‐arid rangelands to complement existing conservation reserves.     

A comparison of cover calculation techniques for relating point-intercept vegetation sampling to remote sensing imagery

Accurate and timely spatial predictions of vegetation cover from remote imagery are an important data source for natural resource management. High-quality in situ data are needed to develop and validate these products. Point-intercept sampling techniques are a common method for obtaining quantitative information on vegetation cover that have been widely implemented in a number of local and national monitoring programs. The use of point-intercept data in remote sensing projects, however, is complicated due to differences in how vegetation cover indicators can be calculated. Decisions on whether to use plant intercepts from any canopy layer (i.e., any-hit cover) or only the first plant intercept at each point (i.e., top-hit cover) can result in discrepancies in cover estimates which are used to train remotely-sensed imagery. Our objective in this paper was to explore the theory of point-intercept sampling relative to training and testing remotely-sensed imagery, and to test the strength of relationships between top-hit and any-hit methods of calculating vegetation cover and high-resolution satellite imagery in two study areas managed by the Bureau of Land Management in northwestern Colorado and northeastern California. We modeled top-hit and any-hit percent cover for six vegetation indicators from 5m-resolution RapidEye imagery using beta regression. Model performance was judged using normalized root mean-squared error (RMSE) from a 5-fold cross validation. Any-hit cover estimates were significantly higher (α < 0.05) than top-hit cover estimates for forbs and grasses in the White River study area, but only marginally higher in Northern California. Pseudo-R² values for beta regression models of vegetation cover from RapidEye image information varied from 0.1525 to 0.7732 in White River and 0.2455 to 0.6085 in Northern California, with little pattern to whether any-hit or top-hit indicators produced better model fit. However, normalized RMSE was lower for any-hit cover (indicating better model performance) or minimally higher than top-hit cover for all indicators in each study area. Our results do not support the idea that top-hit cover estimates from point-intercept sampling are the most appropriate for remote sensing applications in arid and semi-arid shrub-steppe environments. In fact, having two sets of different indicators calculated from the same data may cause additional confusion in a situation where there is already considerable debate on how vegetation cover should be measured and used. Ultimately, selection of indicators to use for developing remote sensing classification or predictive models should be based first on the meaning or interpretation of the indicator in the ecosystem of interest, and second on how well the indicator performs in modeling applications.     

Characteristics of Australia's rangelands and key design issues for monitoring biodiversity

Abstract We explored the key issues that are most likely to influence any set of guiding principles for developing biodiversity monitoring programmes in Australia's rangelands. We defined the Australian rangelands and came up with an overview of their climate extremes, land‐use pressures and biodiversity loss, and then focussed on issues underpinning the design phase of any monitoring programme. Using Noss's 1990 framework of compositional, structural and functional attributes of biodiversity and its new revisions by others, we showed how the elusive, abstract concept of biodiversity can be used to identify many measurable attributes that can form a minimum and necessary set of indicators for any biodiversity monitoring task. We then described the steps in the monitoring process, with a particular focus on the reasons for monitoring biodiversity as they strongly influence the selection of indicators. We concluded by compiling a table of key issues as background information for developing guiding principles (Table 4). The list is by no means an exhaustive list for the design phase but it does indicate that considerable attention needs to be given to this phase when developing monitoring programmes. We have intentionally not addressed the equally important issues associated with the planning and delivery phases of developing a monitoring programme, as Wallace et al. and Watson and Novelly cover these in their papers in the present issue of Austral Ecology.     

Unmanned aerial systems accurately map rangeland condition indicators in a dryland savannah

Dry savannahs are highly sensitive to climate change and under intense anthropogenic pressure. Therefore, the methods for assessing their status should be easy and repeatable. Monitoring through satellite data and field measurements are limited in accurately assessing the spatiotemporal dynamics of ecosystems. Fortunately, emerging technologies like Unmanned Aerial Systems (UAS) allow to transcend these limitations. But their calibration with field data for application in rangelands is still relatively new and less common than for example in precision agriculture. In this study we developed a drone-based workflow for mapping the condition of rangelands in dryland savannah. We evaluated how accurately and efficiently the two common indicators (i.e., potential forage biomass and rangeland cover type) of rangeland condition can be estimated from drone imagery across a range of conditions (i.e., highly degraded to healthy rangelands). To develop the drone-based potential forage biomass model we tested the accuracy of four vegetation indices to predict field biomass, with the optimized soil adjusted vegetation index (OSAVI) showing the highest prediction accuracy (R² = 0.89 and RMSE = 194.05). The OSAVI-based model yielded a significant strong relationship (R² = 0.80, p < 0.001) between predicted and field observed potential forage biomass across the rangeland system. For land cover, we applied a decision tree classification based on thresholds determined using data mining, with a mean overall accuracy of 95.8%. The drone-based estimates of bare cover, herbaceous cover and woody cover showed strong agreements (R² ranging between 0.86 and 0.97) with the two image-truthing methods (line-point intercept and visual estimations) tested. We show that the drone-based approach is more efficient, unbiased, and repeatable than the field methods. Based on these results, the drone-based workflow presented here offers a reproducible, accurate and efficient approach for near-real time monitoring of rangeland condition at a landscape level. This may assist with climate-adapted management to prevent further land degradation and associated threats to biodiversity and human livelihoods.     

Rehabilitation of Semiarid Landscapes in Australia. II. Restoring Vegetation Patches

This paper describes a practical technique, tested experimentally, for rehabilitating degraded semiarid landscapes in Australia. This rehabilitation technique is based on the ecological principle that semiarid landscapes are spatially organized as patchy, source-sink systems; this patchy organization functions to conserve limited water and nutrients within the system. The aim was to rebuild vegetation patchiness, lost through decades of utilization of these landscapes as rangelands. Patches were reconstructed from large tree branches and shrubs obtained locally and placed in elongated piles along contours. These piles of branches were very effective in recreating productive soil patches within the landscape, as described in part I of this study. These new patchy habitats promoted the establishment and growth of perennial grasses. Although the foliage cover of these grasses declined into a drought, which started before the end of the experiment, plant survivorship remained high. This suggests that patches also function as refugia for organisms during droughts. The patches of branches remained robust and functional, even under grazing impacts, although plant growth and survival were significantly higher within an ungrazed paddock than in a grazed paddock.     

Changes in landuse alter ant diversity,assemblage composition and dominant functional groups in African savannas

Africa’s savannas are undergoing rapid conversion from rangelands into villages and croplands. Despite limited research, and evidence of deleterious effects to biodiversity, international organisations have earmarked this system for cropland. Invertebrates, and ants in particular, are sensitive indicators of habitat fragmentation, and contribute to ecosystem services at a range of scales. We investigated how rangelands, villages and croplands differ in ant species and functional diversity, and assemblage composition. We sampled ants using pitfall traps at 42 sites (14 replicates each in rangeland, cropland, and village) in northern South African savannas. We investigated the impact of landuse, season, and multiple soil and vegetation habitat variables on ant species diversity, assemblages and functional diversity. Rangelands had the greatest ant species richness, particularly in the wet season. Richness declined with increasing soil clay content. Ant assemblages were distinctly different between landuse types. Rangeland harboured the widest diversity of indicator species, and contained greatest functional diversity. Rangelands accommodated more scavengers, granivores, and plant-matter feeders than cropland, and representation of these groups varied with season. Ants play essential roles in soil nutrient cycling, plant and seedling recruitment, and impact other arthropods through predation and aphidoculous behaviour that in turn influences entire food webs. Thus, the reduced species richness, changes in assemblage composition and the loss of functional groups in ant assemblages found in cropland and villages is potentially problematic. Left unchallenged, these new forms of landuse threaten to characterise the entire African savanna system, impacting not only future ecological, but possibly also human wellbeing.