Contrasting responses of above- and belowground diversity to multiple components of land-use intensity.

Land-use intensification is a major driver of biodiversity loss. However, understanding how different components of land use drive biodiversity loss requires the investigation of multiple trophic levels across spatial scales. Using data from 150 agricultural grasslands in central Europe, we assess the influence of multiple components of local- and landscape-level land use on more than 4,000 above- and belowground taxa, spanning 20 trophic groups. Plot-level land-use intensity is strongly and negatively associated with aboveground trophic groups, but positively or not associated with belowground trophic groups. Meanwhile, both above- and belowground trophic groups respond to landscape-level land use, but to different drivers: aboveground diversity of grasslands is promoted by diverse surrounding land-cover, while belowground diversity is positively related to a high permanent forest cover in the surrounding landscape. These results highlight a role of landscape-level land use in shaping belowground communities, and suggest that revised agroecosystem management strategies are needed to conserve whole-ecosystem biodiversity.

Estimation of vegetation water content at leaf and canopy level using dual-wavelength commercial terrestrial laser scanners.

Vegetation water content, quantified as the leaf equivalent water thickness (EWT), can serve as an indicator of vegetation stress. The intensity data recorded by terrestrial laser scanning (TLS) instruments, operating at shortwave infrared wavelengths, can be used to estimate the three-dimensional distribution of EWT, after a full and rigorous calibration for the range and incidence angle effects. However, TLS instruments do not record the incidence angles automatically, making calibration challenging. In this study, intensity data from two commercially available TLS instruments (Leica P40, 1550 nm shortwave infrared wavelength, and Leica P20, 808 nm near-infrared wavelength) were combined in a normalized difference index (NDI). The NDI was found to minimize the incidence angle effects with no need for further calibration. A dry-down experiment was conducted using deciduous and conifer canopies. The NDI was found to be highly correlated to EWT at leaf level (R2 of 0.91 and 0.74) and at canopy level (R2 of 0.89 and 0.74) for the deciduous and conifer canopies, respectively. Three-dimensional distributions of EWT at canopy level were generated, which revealed some vertical heterogeneity.

Non-intersecting leaf insertion algorithm for tree structure models.

We present an algorithm and an implementation to insert broadleaves or needleleaves into a quantitative structure model according to an arbitrary distribution, and a data structure to store the required information efficiently. A structure model contains the geometry and branching structure of a tree. The purpose of this work is to offer a tool for making more realistic simulations of tree models with leaves, particularly for tree models developed from terrestrial laser scanning (TLS) measurements. We demonstrate leaf insertion using cylinder-based structure models, but the associated software implementation is written in a way that enables the easy use of other types of structure models. Distributions controlling leaf location, size and angles as well as the shape of individual leaves are user definable, allowing any type of distribution. The leaf generation process consist of two stages, the first of which generates individual leaf geometry following the input distributions, while in the other stage intersections are prevented by carrying out transformations when required. Initial testing was carried out on English oak trees to demonstrate the approach and to assess the required computational resources. Depending on the size and complexity of the tree, leaf generation takes between 6 and 18 min. Various leaf area density distributions were defined, and the resulting leaf covers were compared with manual leaf harvesting measurements. The results are not conclusive, but they show great potential for the method. In the future, if our method is demonstrated to work well for TLS data from multiple tree types, the approach is likely to be very useful for three-dimensional structure and radiative transfer simulation applications, including remote sensing, ecology and forestry, among others.