The habitat-heterogeneity hypothesis predicts that biodiversity increases with increasing habitat heterogeneity due to greater niche dimensionality. However, recent studies have reported that richness can decrease with high heterogeneity due to stochastic extinctions, creating trade-offs between area and heterogeneity. This suggests that greater complexity in heterogeneity-diversity relationships (HDRs) may exist, with potential for group-specific responses to different facets of heterogeneity that may only be partitioned out by a simultaneous test of HDRs of several species groups and several facets of heterogeneity. Here, we systematically decompose habitat heterogeneity into six major facets on ~500 temperate forest plots across Germany and quantify biodiversity of 12 different species groups, including bats, birds, arthropods, fungi, lichens and plants, representing 2600 species. Heterogeneity in horizontal and vertical forest structure underpinned most HDRs, followed by plant diversity, deadwood and topographic heterogeneity, but the relative importance varied even within the same trophic level. Among significant HDRs, 53% increased monotonically, consistent with the classical habitat-heterogeneity hypothesis, but 21% were humped-shaped, 25% had a monotonically decreasing slope and 1% showed no clear pattern. Overall, we found no evidence of a single generalizable mechanism determining HDR patterns.

Recent progress in remote sensing provides much-needed, large-scale spatio-temporal information on habitat structures important for biodiversity conservation. Here we examine the potential of a newly launched satellite-borne radar system (Sentinel-1) to map the biodiversity of twelve taxa across five temperate forest regions in central Europe. We show that the sensitivity of radar to habitat structure is similar to that of airborne laser scanning (ALS), the current gold standard in the measurement of forest structure. Our models of different facets of biodiversity reveal that radar performs as well as ALS; median R² over twelve taxa by ALS and radar are 0.51 and 0.57 respectively for the first non-metric multidimensional scaling axes representing assemblage composition. We further demonstrate the promising predictive ability of radar-derived data with external validation based on the species composition of birds and saproxylic beetles. Establishing new area-wide biodiversity monitoring by remote sensing will require the coupling of radar data to stratified and standardized collected local species data.

Knowledge of forest structures—and of dead wood in particular—is fundamental to understanding, managing, and preserving the biodiversity of our forests. Lidar is a valuable technology for the area-wide mapping of trees in 3D because of its capability to penetrate vegetation. In essence, this technique enables the detection of single trees and their properties in all forest layers. This paper highlights a successful mapping of tree species—subdivided into conifers and broadleaf trees—and standing dead wood in a large forest 924 km2 in size. As a novelty, we calibrate the critical stopping criterion of the tree segmentation based on a normalized cut with regard to coniferous and broadleaf trees. The experiments were conducted in Šumava National Park and Bavarian Forest National Park. For both parks, lidar data were acquired at a point density of 55 points/m2. Aerial multispectral imagery was captured for Šumava National Park at a ground sample distance (GSD) of 17 cm and for Bavarian Forest National Park at 9.5 cm GSD. Classification of the two tree groups and standing dead wood—located in areas of pest infestation—is based on a diverse set of features (geometric, intensity-based, 3D shape contexts, multispectral-based) and well-known classifiers (Random forest and logistic regression). We show that the effect of under- and oversegmentation can be reduced by the modified normalized cut segmentation, thereby improving the precision by 13%. Conifers, broadleaf trees, and standing dead trees are classified with overall accuracies better than 90%. All in all, this experiment demonstrates the feasibility of large-scale and high-accuracy mapping of single conifers, broadleaf trees, and standing dead trees using lidar and aerial imagery.

Aim Despite increasing interest in β‐diversity, that is the spatial and temporal turnover of species, the mechanisms underlying species turnover at different spatial scales are not fully understood, although they likely differ among different functional groups. We investigated the relative importance of dispersal limitations and the environmental filtering caused by vegetation for local, multi‐taxa forest communities differing in their dispersal ability, trophic position and body size. Location Temperate forests in five regions across Germany. Methods In the inter‐region analysis, the independent and shared effects of the regional spatial structure (regional species pool), landscape spatial structure (dispersal limitation) and environmental factors on species turnover were quantified with a 1‐ha grain across 11 functional groups in up to 495 plots by variation partitioning. In the intra‐region analysis, the relative importance of three environmental factors related to vegetation (herb and tree layer composition and forest physiognomy) and spatial structure for species turnover was determined. Results In the inter‐region analysis, over half of the explained variation in community composition (23% of the total explained 35%) was explained by the shared effects of several factors, indicative of spatially structured environmental filtering. Among the independent effects, environmental factors were the strongest on average over 11 groups, but the importance of landscape spatial structure increased for less dispersive functional groups. In the intra‐region analysis, the independent effect of plant species composition had a stronger influence on species turnover than forest physiognomy, but the relative importance of the latter increased with increasing trophic position and body size. Main conclusions Our study revealed that the mechanisms structuring assemblage composition are associated with the traits of functional groups. Hence, conservation frameworks targeting biodiversity of multiple groups should cover both environmental and biogeographical gradients. Within regions, forest management can enhance β‐diversity particularly by diversifying tree species composition and forest physiognomy.

In the version of this Article originally published, incorrect data curves were displayed in Fig. 2c. The data curves should have appeared as shown below. This has now been corrected.