Summary1. Large herbivores play a key role in creating spatial heterogeneity through the formation of grazing lawns. Recent research suggests that the currently accepted nutrient-based theory on the formation of these grazing lawns cannot universally explain their formation in all ecosystems where they are found. 2. We developed and investigated an alternative hypothesis on grazing lawn formation and maintenance based on herbivore effects on the plant-soil water balance. We propose that large herbivores change the soil water balance in grazing lawns through defoliation and soil compaction, causing a shift in vegetation composition towards a drought-tolerant plant community. 3. Investigating this idea in a tropical savanna, we indeed found profound differences in grazing lawn soil properties and water balance. In particular, defoliation increased soil temperatures and potential evaporation rates while soil compaction increased bulk density and decreased water infiltration rates, especially on fine-textured soils. Soil moisture was therefore generally much lower in grazing lawns than in adjacent bunch grass areas. 4. Furthermore, we found that grazing lawn species show drought-tolerant traits, with higher leaf sodium levels, suggesting evolutionary adaptation to these herbivore-induced dry conditions. However, leaf water potentials did not differ between grazing lawn and bunch grass species. 5. Synthesis. This study shows that large herbivores might form grazing lawns through previously underestimated effects on water balance. Thus, future studies on large herbivore effects on vegetation should increasingly focus on additional pathways of soil compaction and defoliation. While nutrient-based processes driving grazing lawn formation may operate during the wet season in savannas, we suggest that water balance-based processes are additionally important during the dry season.

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Lidar‐derived forest structural diversity (FSD) metrics—including measures of forest canopy height, vegetation arrangement, canopy cover (CC), structural complexity and leaf area and density—are increasingly used to describe forest structural characteristics and can be used to infer many ecosystem functions. Despite broad adoption, the importance of spatial resolution (grain and extent) over which these structural metrics are calculated remains largely unconsidered. Often researchers will quantify FSD at the spatial grain size of the process of interest without considering the scale dependency or statistical behaviour of the FSD metric employed. We investigated the appropriate scale of inference for eight lidar‐derived spatial metrics—CC, canopy relief ratio, foliar height diversity, leaf area index, mean and median canopy height, mean outer canopy height, and rugosity (RT)‐‐representing five FSD categories—canopy arrangement, CC, canopy height, leaf area and density, and canopy complexity. Optimal scale was determined using the representative elementary area (REA) concept whereby the REA is the smallest grain size representative of the extent. Structural metrics were calculated at increasing canopy spatial grain (from 5 to 1000 m) from aerial lidar data collected at nine different forested ecosystems including sub‐boreal, broadleaf temperate, needleleaf temperate, dry tropical, woodland and savanna systems, all sites are part of the National Ecological Observatory Network within the conterminous United States. To identify the REA of each FSD metric, we used changepoint analysis via segmented or piecewise regression which identifies significant changepoints for both the magnitude and variance of each metric. We find that using a spatial grain size between 25 and 75 m sufficiently captures the REA of CC, canopy arrangement, canopy leaf area and canopy complexity metrics across multiple forest types and a grain size of 30–150 m captures the REA of canopy height metrics. However, differences were evident among forest types with higher REA necessary to characterize CC in evergreen needleleaf forests, and canopy height in deciduous broadleaved forests. These findings indicate the appropriate range of spatial grain sizes from which inferences can be drawn from this set of FSD metrics, informing the use of lidar‐derived structural metrics for research and management applications.

Anthropogenic environmental change affects organisms by exposing them to enhanced sensory stimuli that can elicit novel behavioural responses. A pervasive feature of the built environment is artificial nocturnal lighting, and brightly lit urban areas can influence organism abundance, distribution and community structure within proximate landscapes. In some cases, the attractive or disorienting effect of artificial light at night can draw animals into highly unfavourable habitats, acting as a macroscale attractive ecological sink. Despite their significance for animal ecology, identifying cases of these phenomena and determining their effective scales and the number of organisms impacted remains challenging. Using an integrated set of remote-sensing observations, we quantify the effect of a large-scale attractive sink on nocturnal flights of an outbreak insect population in Las Vegas, USA. At the peak of the outbreak, over 45 million grasshoppers took flight across the region, with the greatest numbers concentrating over high-intensity city lighting. Patterns of dusk ascent from vegetated habitat toward urban areas suggest a daily pull toward a time-varying nocturnal attractive sink. The strength of this attractor varies with grasshopper density. These observations provide the first macroscale characterization of the effects of nocturnal urban lighting on the behaviour of regional insect populations and demonstrate the link between insect perception of the built environment and resulting changes in spatial and movement ecology. As human-induced environmental change continues to affect insect populations, understanding the impacts of nocturnal light on insect behaviour and fitness will be vital to developing robust large-scale management and conservation strategies.