Global biodiversity is threatened by unprecedented and increasing anthropogenic pressures, including habitat loss and fragmentation. LiDAR can become a decisive technology by providing accurate information about the linkages between biodiversity and ecosystem structure. Here, we review the current use of LiDAR metrics in ecological studies regarding birds, mammals, reptiles, amphibians, invertebrates, bryophytes, lichens, and fungi (BLF). We quantify the types of research (ecosystem and LiDAR sources) and describe the LiDAR platforms and data that are currently available. We also categorize and harmonize LiDAR metrics into five LiDAR morphological traits (canopy cover, height and vertical distribution, understory and shrubland, and topographic traits) and quantify their current use and effectiveness across taxonomic groups and ecosystems. The literature review returned 173 papers that met our criteria. Europe and North America held most of the studies, and birds were the most studied group, whereas temperate forest was by far the most represented ecosystem. Globally, canopy height was the most used LiDAR trait, especially in forest ecosystems, whereas canopy cover and terrain topography traits performed better in those ecosystems where they were mapped. Understory structure and shrubland traits together with terrain topography showed high effectiveness for less studied groups such as BLF and invertebrates and in open landscapes. Our results show how LiDAR technology has greatly contributed to habitat mapping, including organisms poorly studied until recently, such as BLF. Finally, we discuss the forthcoming opportunities for biodiversity mapping with different LiDAR platforms in combination with spectral information. We advocate (i) for the integration of spaceborne LiDAR data with the already available airborne (airplane, drones) and terrestrial technology, and (ii) the coupling of it with multispectral/hyperspectral information, which will allow for the exploration and analyses of new species and ecosystems.

The first density estimates of a peripheral guanaco population and its habitat use at different spatial scales are presented for a protected area of Monte desert, Argentina. Transects were surveyed in the wet and dry seasons of 2005. All guanaco herds observed during systematic surveys using roads and tracks were GPS located and their habitat use was identified. Herd size differed significantly between the dry and wet seasons. Population densities differed between wet (0.10–0.12 individuals/km²) and dry seasons (0.60–0.75 individuals/km²). The population estimates ranged from 75 individuals (dry season) to 388 individuals (wet season). Guanacos showed differential habitat use, the first determinant being abiotic factors, such as topography, soil characteristics or microclimate conditions, animals being detected in rougher rocky substrata in the dry season and in open flat terrain in the wet season, followed by a mesoscale selection defined by plant communities. At the latter scale, guanaco preferentially used mixed creosote bushland and saltbush more intensively during the wet season, and open scrub and columnar-cactus slopes in the dry season. The estimated population of this protected area was small but its population density was within the range of other populations and was relatively high for this dry and unproductive area.

LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse’s habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse’s preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest patch, such as the presence and cover of shrubs, as well as other characteristics likely including time since perturbation, food availability and predation risk. Our results suggest that LiDAR is a promising technology for further exploring habitat preferences by small mammal communities.

Defining plant communities in desert zones is difficult due to large scale homogeneity and small scale heterogeneity, thus making provision of systematic information for conservation decisions problematic. We analysed plant communities of the most arid sector of Monte Desert for structure, plant composition and environmental variables. Small-scale variables such as slope, rock cover, bare ground and litter, as well as large-scale ones such as species diversity, composition and similarity within and between sites were included. Analyses of floristic composition showed the difficulty of segregating distinct communities due to high internal heterogeneity and overlap between the different sites. Only mesquite woodlands, a community situated at the extreme of the soil moisture-gradient was segregated. Ordination on structural variables was somewhat more successful in segregating communities on the basis of substrate type and of tree and shrub cover. Our results showed the difficulty distinguishing plant communities in temperate deserts, suggesting the existence of relatively stable assemblages of species at the extremes of the gradients and of great heterogeneity within and between sites. They cannot be defined by floristic variables solely, but require environmental information also.

European traditional cultural landscapes are increasingly modified by rural abandonment and urban growth processes. Acknowledged as of High Nature Value for providing multiple ecosystem services while contributing to human well-being, the future of these social-ecological systems is uncertain. Here we aim to (1) explore dominant land use and cover (LULC) changes linked to extensive livestock farming across an urban-rural gradient defined by a large city (Madrid) over the last three decades; (2) identify and classify the main driving forces shaping these landscape trajectories and; (3) acknowledge the main landscape values for promoting landscape stewardship under participatory governance frameworks. For doing so, we combine mapping analyses (CORINE Land cover) with stakeholder perceptions and positions. Our results show a dual process of progressive abandonment of agroecosystems linked to traditional livestock farming and an ever-increasing urban growth over the last three decades as the most important driving forces. The growing urban sprawl in areas close to Madrid begins to be perceived as problematic for interviewees. The decline of extensive livestock farming in detriment of tourism, particularly evident in rural areas far from Madrid, is perceived as a threat to the cultural heritage and traditions of rural people. This decline is also perceived as a worrying increase of wildfire risk. Stakeholders stressed the need of valuing extensive livestock farming to prevent rural-urban migration, dynamizing rural economies, conserving landscapes and traditions while producing food-quality products. Interviewees advocated for science-based, stakeholder-inclusive and participatory landscape planning and co-management, leading to more context-specific, regionalized policymaking.