Savanna Vegetation Structure Research Articles

Influence of soil properties on woody vegetation structure, diversity and seasonality in Neotropical savannas

AbstractUnderstanding how savanna soil properties influence vegetation diversity and function is a major challenge in ecological studies. We investigated the effects of soil properties on woody species density, richness, composition, and vegetative phenology (inferred by the Normalized Difference Vegetation Index (NDVI)) in two alluvial and two interfluvial savanna sites (1 block of 10 plots of 20 × 50 m in each site), in the Brazilian Cerrado. We showed that plots in alluvial savannas present less fertile soils and have lower plant densities and species richness and higher seasonality of NDVI than plots in the interfluvial savannas. The species composition of the sites was associated with the P, Fe, K, and Mn content of the soil. Soil K, Fe, and Ca contents were the main variables associated with plant density in a linear mixed model (LMM) that explained 79% of data variability (r2c = 0.79%), and K, Fe, and Al were the main predictors to explain species richness (r2c = 0.81%). Soil K, pH, and Silt were the best predictors of the seasonality in NDVI (r2c = 0.14%). We highlight the all‐encompassing effect of K soil content on species density, richness, composition, and NDVI and argue that this macronutrient and a few other soil properties (e.g., P, Fe, Al, and Silt) are the main factors mediating plant responses to water and nutrient stress in woody savanna communities occurring in the Cerrado–Amazônia transition.

The role of ancient human settlements in creating nutrient hotspots in a savanna ecosystem, central Zimbabwe

Ancient human settlements play an important role in creating heterogeneous African savanna ecosystems through forming nutrient hotspots with increased biodiversity and improved forage quality. However, plant community development and herbivore utilization of these sites after abandonment remain poorly understood. We compared plant and soil parameters in ancient human settlements with off-sites locations. In addition, we set camera traps in ancient settlements and surrounding vegetation to determine their use by herbivores. Grass basal cover, height, biomass and species diversity in ancient settlements had recovered to similar levels with the surrounding landscape. Ancient settlements had small trees (in terms of height and canopy volume), lower tree density and lower species diversity than the surrounding landscape. Soil phosphorus and calcium were higher in ancient settlements than surrounding landscape, while pH, nitrogen, potassium, magnesium and sodium were similar between the two sites. Impala and greater kudu camera sightings were higher in ancient settlements than surrounding vegetation, while warthogs showed no preferential foraging between ancient settlements and surrounding vegetation. We conclude that ancient settlements created functional heterogeneity through altering the structure of savanna vegetation influencing foraging patterns of herbivores such as impala.

Plant richness and vegetation structure drive the topology of plant-herbivore networks in Neotropical savannas

Plants and phytophagous insects make up the highest terrestrial diversity on the planet, forming complex interspecific interaction networks. Interaction networks are an important tool to understand how ecological interactions shape plant-herbivore assemblages. In the present study, we tested the hypotheses that the plant species richness and vegetation structure (vegetation cover and vegetation height) (i) drive the richness and abundance of herbivorous insects and (ii) determines topological patterns (connectance, specialization and modularity) of plant-herbivore networks. We sampled ten different areas in the Neotropical savannas to assess those hypotheses and constructed plant-herbivore interaction matrices using species composition data. Plant-herbivore interaction networks comprised 298 plants of 60 species, 421 insects distributed in 96 morphospecies, and totalizing 218 interactions. We found that plant species richness positively influenced the species richness of herbivorous insects, whereas average vegetation height negatively affected the species richness of herbivorous insects. The abundance of herbivorous insects was negatively affected by plant species richness, and by vegetation height. Species richness and structure of plant communities also significantly affected network topological parameters. Network connectance was negatively influenced by plant richness and positively affected by vegetation cover. Besides, plant species richness positively influenced network modularity, whereas vegetation height negatively affected network modularity. However, the plant community diversity and vegetation structure did not affect network specialization. Our results show that both plant community diversity and vegetation structure in Neotropical savannas drive the structure of plant-herbivore interaction networks. Considering the current high rates of removal of native vegetation in Brazilian savannas, our findings indicate that the preserving this ecosystem is crucial for maintaining ecosystem services through plant-herbivore interaction networks.

Effects of long‐term fixed fire regimes on African savanna vegetation biomass, vertical structure and tree stem density

Abstract Fire plays an integral role in shaping the vegetation structure of savanna ecosystems. However, the effects of fire regime characteristics, such as frequency and season of burn, on savanna vegetation structure, biomass and tree abundance across landscape types are largely unknown. We used high‐resolution airborne light detection and ranging (LiDAR) to investigate the long‐term effects of fire manipulation on savanna vegetation in Kruger National Park, South Africa. We analysed the effects of fire exclusion and experimental burns every 1, 2, 3, 4 and 6 years and during different seasons on aboveground biomass (AGB), tree stem densities and vegetation vertical height profiles across a rainfall gradient and on contrasting geologies. Across savanna types, and especially in drier savannas, fire season was more influential for constraining AGB than fire frequency. Plots experiencing fires during the late‐ and mid‐dry season had 44.50% and 43.60%, respectively, lower AGB relative to unburnt plots than wet‐season fires. However, in mesic savannas, fire frequency interacted with fire season to influence AGB: plots subjected to high frequency, dry‐season fires had 55.35% lower AGB than unburnt plots, whereas plots burnt in the wet season at lower frequencies had lower AGB (24.40% lower than unburnt plots) than plots subjected to high frequency, wet‐season fires (13.74% lower AGB than unburnt plots). Fire regimes had variable effects on tree densities, and effects varied with the savanna type. Woody vertical vegetation profiles showed the largest differences in response to dry‐season fires, with the greatest divergence in vegetation height classes <5 m. Synthesis and applications. Understanding the influence of fire regimes on vegetation structure has important implications for the management of savanna heterogeneity and for predicting trajectories of change in savanna vegetation as fire regimes vary with climate change. We show that the magnitude of the effect of fire on woody vegetation structure varies with savanna context. Our results suggest that heterogeneous vegetation structure can be achieved by applying fires in the dry season in mesic savannas, whereas in dry savannas, variation in fire regimes is less consequential for constraining biomass accumulation and altering vegetation structure.

Flying high: Sampling savanna vegetation with UAV‐lidar

Abstract The flexibility of UAV‐lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest. To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX − 1LR over a 300 × 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover. Comparing vegetation metrics from acquisitions with different flight patterns and sensor parameters, we found that both flight altitude and pattern had significant impacts on derived structure metrics, with variation in altitude causing the largest impacts. Flying higher resulted in lower point cloud heights, leading to a consistent downward trend in percentile height metrics and fractional cover. The magnitude and direction of these trends also varied depending on the vegetation type sampled (trees, shrubs or grasses), showing that the structure and composition of savanna vegetation can interact with the lidar signal and alter derived metrics. While there were statistically significant differences in metrics among acquisitions, the average differences were often on the order of a few centimetres or less, which shows great promise for future comparison studies. We discuss how these results apply in practice, explaining the potential trade‐offs of flying at higher altitudes and with alternate patterns. We highlight how flight and sensor parameters can be geared toward specific ecological applications and vegetation types, and we explore future opportunities for optimizing UAV‐lidar sampling designs in savannas.

Quantifying the sensitivity of L-Band SAR to a decade of vegetation structure changes in savannas

Global savannas are the third largest carbon sink with large human populations being highly dependent on their ecosystem services. However, savannas are changing rapidly due to climate change, fire, animal management, and intense fuelwood harvesting. In southern Africa, large trees (>5 m in height) are under threat while shrub cover (<3 m) is increasing. The collection of multi-date airborne LiDAR (ALS) data, initiated over a decade ago in the Lowveld of South Africa, provided a rare opportunity to quantify the ability of L-band SAR to track changes in savanna vegetation structure and this study is the first to do so, to our knowledge. The objective was to test the ability of ALOS PALSAR 1&2, dual-pol (HH, HV) data to quantify woody cover and volume change in savannas over 2-, 8- and 10-year periods through comparison to ALS. For each epoch (2008, 2010, 2018), multiple PALSAR images were processed to Gamma0 (γ0) at 15 m resolution with multi-temporal speckle filtering. ALS data were processed to fractional canopy cover and volume, and then compared to 5 × 5 aggregated (75 m) SAR mean γ0. The ALS cover change (∆CALS) and volume change between pairs of years were highly correlated, with (R2 > 0.8), thus results for cover change applied equally to volume change. Cover change was predicted using (i) direct backscatter change or (ii) the difference between annual cover map product derived using the Bayesian Water Cloud Model (BWCM) and logarithmic models. The linear relationship between ∆γ0 and ∆CALS varied between year pairs but reached a maximum R2 of 0.7 for 2018–2010 and a moderate R2 of 0.4 for 2018–2008. Overall, 1 dB ∆γ0 corresponded to approximately 0.1 cover change. The three cover change models had very similar uncertainties with mean RMSE = 0.15, which is 13% of the observed cover change range (−0.6 to +0.6). The direct backscatter change approach had less underestimation of positive and negative cover change. The L-band backscatter had a higher sensitivity than suggested by previous studies, as it was able to reliably distinguish cover change at 0.25 increments. The SAR-derived cover change maps detected the loss of stands of big trees, and widespread increases in cover of 0.35–0.65 in communal rangelands due to shrub encroachment. In contrast, the maps suggest that cover generally decreased in conservation areas, forming distinct fence-line effects, potentially caused by significant increases in elephant numbers and frequent, intense wildfires in reserves.

Drought limits large trees in African savannas with or without elephants

AbstractConsumers, including megaherbivores and fire, are considered important limiting forces for woody plants and canopy closure in African savannas. However, climatic events like drought can also play a significant role in limiting trees and maintaining tree‐grass coexistence in savannas. The extent to which top‐down control (e.g. megaherbivores) and bottom‐up resource limitation through drought and competition interact to influence savanna tree mortality and woody structure is unclear. Here, we compared the change in the number of large trees before and after a severe drought in a savanna with elephants (Loxodonta africana) and one without elephants. Elephants and drought both limited the number of large trees at our sites, but contrary to our predictions, there was no interactive effect of these drivers on overall changes in tree densities. However, there was a synergistic effect on the dominant tree species, Senegalia nigrescens, such that tree loss post‐drought was greater where elephants were present compared to where they were absent. Hence, our results suggest that species‐specific differences in drought resistance, as well as density‐dependent factors, likely impact the severity of drought effects on savanna tree communities. In savannas, drought has the potential to exert strong control on tree survival and prevent canopy closure, thus partially filling the role of megaherbivores in limiting large trees when these consumers are absent. As drought severity and frequency are predicted to increase in the future, the influence of drought on savanna vegetation structure becomes increasingly important to consider.

Fire effects on riparian vegetation recovery and nutrient fluxes in Brazilian Cerrado

AbstractFire can change gallery forest vegetation structure, thereby altering nutrient fluxes between terrestrial and aquatic ecosystems. In Brazilian savannas, which are fire‐prone ecosystems, the fire regime is changing due to human activities such as converting native vegetation to farmland and urban areas. Uncontrolled wildfires in these savannas can reach gallery forests, which are more sensitive to fire impacts, leading to concerns about the effects of fire on gallery forest vegetation structure and freshwater ecosystems. We analysed the relationships between fire severity (the degree to which the fire has changed an area), percentage of burned area, variation in precipitation with gallery forest and savanna vegetation structure recovery and input of nutrients (NH4, , and ) to streams for 16 months after a fire event in five watersheds associated with small streams. One year after the fire, vegetation recovery (NDVI) was lower in gallery forest areas than in savanna woodlands, despite the more severe fires in savannas. The short‐term effects of fire on gallery forest vegetation included increased nitrate concentrations in streams, which were also influenced by increased precipitation and the extent of the burned area. The nutrient inputs into the stream stabilized within 1 year. However, gallery forest vegetation did not fully recover at that time and may continue to alter the functioning of the aquatic ecosystem. Together, these results demonstrate the need for an integrated fire management plan that considers both gallery forests and the surrounding savannas in the landscape to address consequences to aquatic ecosystems.

Context‐dependent effects of shifting large herbivore assemblages on plant structure and diversity

Abstract Despite wide recognition of the importance of anthropogenically driven changes in large herbivore communities—including both declines in wildlife and increases in livestock—there remain large gaps in our knowledge about the impacts of these changes on plant communities, particularly when combined with concurrent changes in climate. Considering these prominent forms of global change in tandem enables us to better understand controls on savanna vegetation structure and diversity under real‐world conditions. We conducted a field experiment using complete and semi‐permeable herbivore exclosures to explore the difference in plant communities among sites with wild herbivores only, with cattle in addition to wild herbivores, and with no large herbivores. To understand variation in effects across climatic contexts, the experiment was replicated at three locations along a topoclimatic gradient in California. Critically, this is the first such experiment to compare cattle and wildlife impacts along an environmental gradient within a single controlled experiment. Vegetation structure responded strongly to herbivore treatment regardless of climate. Relative to the isolated effects of wildlife, exclusion of all large herbivores generally increased structural components related to cover and above‐ground biomass while the addition of cattle led to reductions in vegetation cover, litter, shading and standing biomass. Furthermore, wildlife had a consistent neutral or positive effect on plant diversity, while the effect of livestock addition was context dependent. Cattle had a neutral to strongly negative effect at low aridity, but a positive effect at high aridity. These results suggest that (a) herbivore effects can override climate effects on vegetation structure, (b) cattle addition can drive different effects on diversity and (c) herbivore effects on diversity are modulated by climate. Synthesis. Our results illustrate very distinctive shifts in plant communities between two realistic forms of change in ungulate herbivore assemblages—livestock addition and large herbivore losses—particularly for plant diversity responses, and that these responses vary across climatic contexts. This finding has important implications for the management and protection of plant biodiversity given that over a quarter of the Earth's land area is managed for livestock and climate regimes are changing globally.

Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems &gt; 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.

Moving from plot-based to hillslope-scale assessments of savanna vegetation structure with long-range terrestrial laser scanning (LR-TLS)

Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide.

Savanna vegetation structure in the Brazilian Cerrado allows for the accurate estimation of aboveground biomass using terrestrial laser scanning

Understanding structural variations in natural systems can help us understand their responses to disturbance and environmental changes and plan for the mitigation of human-induced impacts. Terrestrial laser scanning (TLS) is a technological solution to quickly and accurately capture and model vegetation structure. In the Brazilian Cerrado biome, characterized by highly heterogeneous plant formations and marked seasonality, TLS may help improve aboveground biomass (AGB) estimates. This study aimed to use single-scan TLS-derived metrics to predict plot-scale aboveground biomass for three vegetation types with high structural diversity and biomass content (woodland savanna, forested savanna, and gallery forest). Ten plots were scanned in each vegetation type, and variables related to point density at different strata and height distribution were extracted from the point cloud to predict AGB measured in local field inventories. The woodland savanna provided good fit models with only two metrics (rainy season: proportion of points below 1.37 m and height of the 99th percentile; adj-R2 = 0.92, RMSE (root mean square error) = 2.67 Mg/ha or 12%; and dry season: height of the 20th and the 99th percentiles; adj-R2 = 0.88, RMSE = 3.32 Mg/ha or 15%). The model for the forested savanna had relatively less explanatory power with one influential predictor (forested savanna: height of the 20th percentile; adj-R2 = 0.58, RMSE = 6.85 Mg/ha or 21%). For the gallery forest, however, the canopy structure could not be adequately characterized due to occlusion of laser returns by dense sub-canopy strata. Our study shows the strong potential of the terrestrial LiDAR technology for estimation of plot-based biomass across diverse savanna vegetation types, where the sparse tree structure allows for better laser penetration the accurate generation of height profiles.

Sampling methods affect observed response of bird species richness to vegetation structure in Brazilian savannas

ABSTRACT Vegetation structure is a potentially important ecological factor structuring bird communities, but can also affect bird detectability, which can complicate the resolution of ecological patterns. We addressed how vegetation structure may bias the efficiency of the 3 methods most commonly used to sample bird species richness in the Brazilian savanna (Cerrado), which features a gradient of vegetation structure from grasslands to woodlands. We compiled secondary data on Cerrado bird species richness from the scientific literature, master's theses, doctoral dissertations, and regionally important biological publications. We used generalized linear mixed models (GLMM) to analyze the effects of habitat type and sampling method on Cerrado bird species richness estimates, controlling for variation among publications, researchers, and study sites. The data provided strong support for interactive effects between habitat type and sampling method on observed bird species richness. Point count surveys had a g...

On the relationship between fire regime and vegetation structure in the tropics.

We assessed data from 11 experiments examining the effects of the timing and/or frequency of fire on tropical forest and/or savanna vegetation structure over one decade or more. The initial 'control treatment' in many such cases consisted of previously cleared land. This is as opposed to natural vegetation subject to some sort of endogenous fire regime before the imposition of fire treatments. Effects of fire on fractional foliar cover are up to 10-fold greater when clearing pre-treatments are imposed. Moreover, because many of the 'classic' fire trials were initialised with applied management questions in mind, most have also used burning regimes much more frequent and/or severe than those occurring in the absence of human activity. Once these factors are taken into account, our modelling analysis shows that nonanthropogenic fire regimes serve to reduce canopy vegetative cover to a much lower extent than has previously been argued to be the case. These results call into question the notion that fire effects on tropical vegetation can be of a sufficient magnitude to maintain open-type savanna ecosystems under climatic/soil regimes otherwise sufficient to give rise to a more luxurious forest-type vegetation cover.

Prediction and scale in savanna ecosystems.

Contents Summary 52 I. Introduction 52 II. Determinants of savanna vegetation structure 53 III. Are trees in savannas really more heterogeneous? 53 IV. Are trees in savannas a 'slow' variable? 54 V. Are trees in savannas spatially patterned? 55 VI. Conclusions 55 Acknowledgements 55 References 56 SUMMARY: Savannas are highly variable systems, and predicting variation, especially in the tree layer, represents a major unresolved challenge for forecasting biosphere responses to global change. Prediction to date has focused on disentangling interactions between resource limitation and chronic disturbances to identify what determines local savanna vegetation heterogeneity. By focusing at too fine a scale, this approach overlooks: sample size limitation arising from sparse tree distributions; stochasticity in demographic and environmental processes that is preserved as heterogeneity among tree populations with slow dynamics; and spatial self-organization. Renewed focus on large (1-50ha) permanent plots and on spatial patterns of tree-layer variability at even larger landscape spatial scales (≥1000s of ha) promises to resolve these limitations, consistent with the goal of predicting large-scale biosphere responses to global change.

Can cattle grazing substitute fire for maintaining appreciated pine savannas at the frontier of a montane forest biosphere-reserve?

Human induced savannas in subtropical regions are often favored by small-holder farmers for livestock production and extraction of wood or non-wood products. Frequent burning and grazing are required to maintain the savanna vegetation structure. However, in conservation areas, fire suppression is promoted to avoid wildfires; whereas domestic livestock grazing is considered a strong interfering factor for tree establishment, due to trampling and browsing. In tropical forests which were converted to savannas, competitive exotic grasses have often replaced the native grasses. Where exotic grasses are present, aboveground biomass accumulation and thus man-induced fire risk are high and potentially undermine tree recruitment. On the long-term, the savanna state may shift into a grass-dominated state with little tree cover, generating unfavorable conditions from a livelihood perspective. We examined this problem in a human-induced pine savanna in the La Sepultura Biosphere Reserve in Chiapas, Mexico. Smallholder farmers highly valued this savanna for both livestock production and resin extraction from the fire resistant pine Pinus oocarpa. However, fire suppression and the presence of exotic grasses are reducing the tree recruitment. The main research question was to what degree can cattle grazing replace fire in its role of biomass removal and thereby stimulate pine recruitment and maintain the desired savanna state. We determined current savanna extension in the region and interviewed farmers to reconstruct past savannazation processes and expansion of exotic grasses. We related adult species-specific tree density to the herbaceous-grass cover, and pine and oak seedling and sapling densities to understory vegetation cover, canopy closure, and cattle grazing history. Finally, a field experiment was conducted to examine the effects of livestock grazing on survival and growth of planted pine saplings. The savanna currently covers 20% of the study site; it is the result of past slash-and-burn agriculture and selective logging, which have favored the expansion of several exotic grass species. In savannas where exotic grasses are abundant, sapling density was lower compared to sites with a native grass cover. While livestock grazing seemed to increase pine seedling density likely as a consequence of reduced grass cover, pine sapling survival however, was significantly reduced by livestock trampling. By seeking a balance between the livestock’s benefits and adverse effects on pine recruitment, farmers may develop an integrated management system adapted to their specific biotic rangeland conditions. It should allow forage production, while controlling the negative effects of exotic grasses on pine recruitment, thus maintaining a productive pine savanna system.

Soils and fire jointly determine vegetation structure in an African savanna.

Savanna vegetation is variable, and predicting how water, nutrients, and chronic disturbances interact to determine vegetation structure in savannas represents a challenge. Here, we examined insitu interactions among rainfall, soils, grasses, fire, and elephants that determine tree layer responses to resource gradients in Kruger National Park in South Africa, using 363 long-term monitoring sites throughout the park. Grass biomass increased with rainfall and on nutrient-rich clay soils. Fire frequency, too, increased with rainfall. Conversely, tree density was greater on sandier soils, where water infiltrates more readily, and in areas where the maximum interval between fires was longer, irrespective of average fire frequency. Elephant density responded positively to tree density, but did not contribute significantly to decreasing tree density. Savanna vegetation structure was reasonably predictable, via a combination of rainfall (favoring grasses), soil (sandy soils favoring trees), and fire (limiting trees until a longer interval between fires allows them to establish). Explicit consideration of bottom-up and top-down interactions may thus contribute to a predictive understanding of savanna vegetation heterogeneity.

The effect of urban growth on landscape-scale restoration for a fire-dependent songbird

A landscape-scale perspective on restoration ecology has been advocated, but few studies have informed restoration with landscape metrics or addressed broad-scale threats. Threats such as urban growth may affect restoration effectiveness in a landscape context. Here, we studied longleaf pine savanna in the rapidly urbanizing southeastern United States where a habitat-specialist bird, Bachman's sparrow (Peucaea aestivalis), is closely associated with savanna vegetation structure and frequent fire. Our objectives were to construct a species distribution model for Bachman's sparrow, determine the relationship between fire and urbanization, quantify the urban growth effect (2010–2090), identify potential restoration areas, and determine the interaction between restoration potential and urban growth by 2050. Number of patches, patch size, and isolation metrics were used to evaluate scenarios. The species distribution model was 88% accurate and emphasized multiscale canopy cover characteristics, fire, and percent habitat. Fires were less common <600 m from urban areas, and this fire suppression effect exacerbated urban growth effects. For restoration scenarios, canopy cover reduction by 30% resulted in nearly double the amount of habitat compared to the prescribed fire scenario; canopy cover reduction resulted in larger patch sizes and less patch isolation compared to current conditions. The effect of urban growth on restoration scenarios was unequal. Seventy-four percent of restoration areas from the prescribed fire scenario overlapped with projected urban growth, whereas the canopy cover reduction scenario only overlapped by 9%. We emphasize the benefits of simultaneously considering the effects of urban growth and landscape-scale restoration potential to promote a landscape with greater patch sizes and less isolation.

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

The use of optical remote sensing data for savanna vegetation structure mapping is hindered by sparse and heterogeneous distribution of vegetation canopy, leading to near-similar spectral signatures among lifeforms. An additional challenge to optical sensors is the high cloud cover and unpredictable weather conditions. Longwave microwave data, with its low sensitivity to clouds addresses some of these problems, but many space borne studies are still limited by low quality structural reference data. Terrestrial laser scanning (TLS) derived canopy cover and height metrics can improve aboveground biomass (AGB) prediction at both plot and landscape level. To date, few studies have explored the strength of TLS for vegetation structural mapping, and particularly few focusing on savannas. In this study, we evaluate the potential of high resolution TLS-derived canopy cover and height metrics to estimate plot-level aboveground biomass, and to extrapolate to a landscape-wide biomass estimation using multi-temporal L-band Synthetic Aperture Radar (SAR) within a 9 km2 area savanna in Kruger National Park (KNP). We inventoried 42 field plots in the wet season and computed AGB for each plot using site-specific allometry. Canopy cover, canopy height, and their product were regressed with plot-level AGB over the TLS-footprint, while SAR backscatter was used to model dry season biomass for the years 2007, 2008, 2009, and 2010 for the study area. The results from model validation showed a significant linear relationship between TLS-derived predictors with field biomass, p &lt; 0.05 and adjusted R2 ranging between 0.56 for SAR to 0.93 for the TLS-derived canopy cover and height. Log-transformed AGB yielded lower errors with TLS metrics compared with non-transformed AGB. An assessment of the backscatter based on root mean square error (RMSE) showed better AGB prediction with cross-polarized (RMSE = 6.6 t/ha) as opposed to co-polarized data (RMSE = 6.7 t/ha), attributed to volume scattering of woody vegetation along river valleys and streams. The AGB change analysis showed 32 ha (3.5%) of the 900 ha experienced AGB loses above an average of 5 t/ha per annum, which can mainly be attributed to the falling of trees by mega herbivores such as elephants. The study concludes that SAR data, especially L-band SAR, can be used in the detection of small changes in savanna vegetation over time.

Prospects of the ICESat-2 laser altimetry mission for savanna ecosystem structural studies based on airborne simulation data

The next planned spaceborne lidar mission is the Ice, Cloud and land Elevation Satellite 2 (ICESat-2), which will use the Advanced Topographic Laser Altimeter System (ATLAS) sensor, a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in an oak savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA’s Goddard Space Flight Center. ATLAS-like data was generated using the MATLAS simulator, which adjusts MABEL data’s detected number of signal and noise photons to that expected from the ATLAS instrument. Transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we chose to use data from the near infrared channel that had the highest number of photons. We segmented each transect into 50m, 25m and 14m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an automated algorithm to identify cut off points where the cumulative density of photons from the highest elevation indicates the presence of the canopy top and likewise where such cumulative density from the lowest elevation indicates the mean terrain elevation. MABEL derived height metrics were moderately correlated to discrete return lidar (DRL) derived height metrics (r2 and RMSE values ranging from 0.60 to 0.73 and 2.9m to 4.4m respectively) but MATLAS simulation resulted in more modest correlations with DRL indices (r2 ranging from 0.5 to 0.64 and RMSE from 3.6m to 4.6m). Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover. On the basis of the simulated data, there is reason to believe that the ability of ICESat-2 to estimate height in savannas will be comparable to the original ICESat mission although the respective sensors have different measurement principles.