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Abstract Grassy ecosystems cover >25% of the world's land surface area. The abundance of herbaceous vegetation in these systems directly impacts a variety of ecological processes, including carbon sequestration, regulation of water and nutrient cycling, and support of grazing wildlife and livestock. Efforts to quantify herbaceous biomass, however, are often limited by a trade‐off between accuracy and spatial scale. Here, we describe a method for using Light Detection and Ranging (LiDAR) to estimate continuous aboveground biomass (AGB) at sub‐meter resolutions over large (10–10 000 ha) spatial scales. Across two African savanna ecosystems, we compared field‐ and LiDAR‐derived structural metrics—including measures of vegetation height and volume—with destructively harvested AGB by aligning our geospatial data with the location of harvested quadrats. Using this combination of approaches, we develop scaling equations to estimate spatially continuous herbaceous AGB over large areas. We demonstrate the utility of this method using a long‐term, large herbivore exclosure experiment as a case study and comprehensively compare common field‐ and LiDAR‐derived metrics for estimating herbaceous AGB. Our results indicate that UAV‐borne LiDAR provides comparable accuracy to standard field methods but over considerably larger areas. Nearly every measure of vegetation structure we quantified using LiDAR provided estimates of AGB that were comparable in accuracy (R² > 0.6) to the suite of common field methods we evaluated. However, marked differences between our two sites indicate that, for applications where accurate estimation of absolute biomass is a priority, site‐specific parameterization with destructive harvesting is necessary regardless of methodology. With the increasing availability of high‐resolution remote sensing data globally, our results indicate that many measures of herbaceous vegetation structure can be used to accurately compare AGB, even in the absence of complementary field data. 

Abstract Large mammalian herbivores exert strong top‐down control on plants, which in turn influence most ecological processes. Accordingly, the decline, displacement, or extinction of wild large herbivores in African savannas is expected to alter the physical structure of vegetation, the diversity of plant communities, and downstream ecosystem functions. However, herbivore impacts on vegetation comprise both direct and indirect effects and often depend on herbivore body size and plant type. Understanding how herbivores affect savanna vegetation requires disaggregating the effects of different herbivores and the responses of different plants, as well as accounting for both the structural complexity and composition of plant assemblages. We combined high‐resolution Light Detection and Ranging (LiDAR) with field measurements from size‐selective herbivore exclosures in Kenya to determine how herbivores affect the diversity and physical structure of vegetation, how these impacts vary with body size and plant type, and whether there are predictable associations between plant diversity and structural complexity. Herbivores generally reduced the diversity and abundance of both overstory and understory plants, though the magnitude of these impacts varied substantially as a function of body size and plant type: only megaherbivores (elephants and giraffes) affected tree cover, whereas medium‐ and small‐bodied herbivores had stronger effects on herbaceous diversity and abundance. We also found evidence that herbivores altered the strength and direction of interactions between trees and herbaceous plants, with signatures of facilitation in the presence of herbivores and of competition in their absence. While megaherbivores uniquely affected tree structure, medium‐ and small‐bodied species had stronger (and complementary) effects on metrics of herbaceous vegetation structure. Plant structural responses to herbivore exclusion were species‐specific: of five dominant tree species, just three exhibited significant individual morphological variation across exclosure treatments, and the size class of herbivores responsible for these effects varied across species. Irrespective of exclosure treatment, more species‐rich plant communities were more structurally complex. We conclude that the diversity and architecture of savanna vegetation depend on consumptive and nonconsumptive plant–herbivore interactions; the roles of herbivore diversity, body size, and plant traits in mediating those interactions; and a positive feedback between plant diversity and structural complexity. 

Abstract Background and Aims Terrestrial laser scanners (TLSs) have successfully captured various properties of individual trees and have potential to further increase the quality and efficiency of forest surveys. However, TLSs are limited to line of sight observations, and forests are complex structural environments that can occlude TLS beams and thereby cause incomplete TLS samples. We evaluate the prevalence and sources of occlusion that limit line of sight to forest stems for TLS scans, assess the impacts of TLS sample incompleteness, and evaluate sampling strategies and data analysis techniques aimed at improving sample quality and representativeness. Methods We use a large number of TLS scans (761), taken across a 255 650-m2 area of forest with detailed field survey data: the Harvard Forest Global Earth Observatory (ForestGEO) (MA, USA). Sets of TLS returns are matched to stem positions in the field surveys to derive TLS-observed stem sets, which are compared with two additional stem sets derived solely from the field survey data: a set of stems within a fixed range from the TLS and a set of stems based on 2-D modelling of line of sight. Stem counts and densities are compared between the stem sets, and four alternative derivations of area to correct stem densities for the effects of occlusion are evaluated. Representation of diameter at breast height and species, drawn from the field survey data, are also compared between the stem sets. Key Results Occlusion from non-stem sources was the major influence on TLS line of sight. Transect and point TLS samples demonstrated better representativeness of some stem properties than did plots. Deriving sampled area from TLS scans improved estimates of stem density. Conclusions TLS sampling efforts should consider alternative sampling strategies and move towards in-progress assessment of sample quality and dynamic adaptation of sampling.