Biology subjects

Seidel, D.

Publications and source records attributed to Seidel, D..

4 recordsLinked to original sources

bioRxiv2026

Towards Scaling-Up Three-Dimensional Habitat Structural Measurements with Multi-Sensor Remote Sensing

Terrestrial Laser Scanning (TLS) captures fine-scaled three-dimensional measurements of ecosystem structure, supporting monitoring of the Essential Biodiversity Variables (EBVs). Yet employing TLS across landscapes remains challenging in remote and topographically complex areas. Remote sensing provides a potential pathway for upscaling TLS-derived structural metrics, but to what extent is unquantified particularly in heterogenous environments, like oceanic islands. Here, we investigated the ability of remote sensing to estimate TLS-derived habitat structure across three contrasting habitats (lowland rainforest, montane cloud forest, and subalpine summit scrub) on La Reunion island. Sentinel-1, Sentinel-2, and Aerial LiDAR (ALS) data were acquired over plots where TLS was completed. We derived defined indices of backscatter coefficients, vegetation indices, and LiDAR metrics and assessed their alignment with TLS measurements using a Procrustes analysis. Subsequently, we used General Additive Models to estimate TLS habitat structure from remote sensing variables. Sentinel-2 exhibited the highest multivariate alignment with TLS (r = 0.51). TLS measurements of horizontal and vertical structure were estimated with the highest cross-validated predictive accuracy (R2 0.39 - 0.73), whilst structural complexity metrics were estimated with greater difficulty (R2 0.02 - 0.20). Multi-sensor models outperformed all single-sensor models in prediction estimates. Model performance also varied across habitats, with the highest agreement between predicted and observed values in the lowland rainforest (r = 0.38), and the lowest agreement (r = 0.35) in the montane cloud forest. Yet the dominant structural feature of each habitat was most accurately captured with remote sensing. Our results demonstrate the potential of integrating multi-sensor remote sensing data to upscale key dimensions of TLS-derived ecosystem structure but remains challenging for fine-scale structural complexity. These findings highlight both the potential and constraints of remote sensing for developing scalable, long-term monitoring frameworks for EBVs, especially in structurally complex and underrepresented island ecosystems.

ecology↗

bioRxiv2025

Microclimatic heterogeneity is associated with forest structural complexity and biodiversity

Forest microclimates, their dependence on forest structure, and their impact on biodiversity are crucial for future forest management under climate change. However, standard approaches for measuring forest microclimates do not capture within-plot heterogeneity, which, according to the habitat heterogeneity hypothesis, is a key driver of local biodiversity. We quantified horizontal and vertical microclimatic heterogeneity within 30 broad-leaved forest plots in Central Europe using a three-dimensional design with high spatial resolution. Moreover, we examined whether microclimatic heterogeneity differs among silvicultural treatments and whether it can be predicted using forest structure indices derived from laser scanning. Additionally, we explored the relationship between microclimatic heterogeneity and biodiversity. In the understory of canopy gaps, warm and cold habitats co-existed in close proximity, leading to a high horizontal microclimatic heterogeneity. In closed stands with high structural complexity, we found steep gradients of increasing temperature and vapor pressure deficit from the ground to the canopy during mid-day. Canopy cover and forest structural complexity were strong indicators of microclimatic heterogeneity. We found positive relationships between herb layer temperature heterogeneity and the diversity of plants, Hymenoptera, and Diptera. Our results demonstrate that single-point measurements fail to capture the substantial microclimatic heterogeneity within plots, potentially misrepresenting the conditions experienced by forest species. However, laser scanning provides reliable indicators for within- plot microclimatic heterogeneity. With canopy gaps featuring high horizontal microclimatic heterogeneity and promoting the biodiversity of several taxonomic groups, we argue that managing forests for maximized temperature buffering should not be the only strategy to conserve forest biodiversity. HighlightsO_LIHigh small-scale horizontal microclimatic heterogeneity in canopy gaps C_LIO_LISteep vertical microclimatic gradients in closed-canopy forests C_LIO_LICanopy cover and structural complexity: indicators for microclimatic heterogeneity C_LIO_LIPositive relationship between herb layer temperature heterogeneity and biodiversity C_LI

ecology↗

bioRxiv2025

Forest vertical and horizontal temperature similarity drives arthropod communities in a managed temperate forest

Manipulating the canopy structure is the core tool of silviculture operation, and with that, changing the light availability alters temperature dynamics from the forest floor to the canopy. This should affect communities of ectothermic organisms such as insects, but we lack information on insect distributions in the complex 3D space of forests. Therefore, we set up temperature loggers and insect traps vertically (flight-interception traps) and horizontally (pitfall traps) in forests with experimental thinning and gap felling 8 years after the intervention. By metabarcoding, we identified [~]10,600 Operational Taxonomic Units (OTUs) from 44 orders including [~]2450 arthropods assigned to species in our 426 samples. Arthropod community similarity matrices were quantified along the Hill numbers accounting for rare to dominant species and under consideration of incomplete samples. Arthropod communities were shaped by stratification (height above ground 0 m, 2 m, 10 m, 15 m), and by temperature similarity. Average nighttime temperature was the most important temperature variable for overall arthropod community similarity metrics. Restricted to flight interception traps, flying insect communities responded to daily temperature maximum and nighttime average temperature. Restricted to pitfall traps, on the other hand, arthropod communities were shaped by the overall temperature metric only when focusing on rare species. Additionally, all communities were strongly affected by season. Our results implies that management interventions establish different temperature heterogeneity within forest patches, which ultimately could drive species community similarity when including all arthropods in the area between forest floor and canopy.

ecology↗

bioRxiv2024

TreeCompR: Tree competition indices for inventory data and 3D point clouds

O_LIIn times of more frequent global-change-type droughts and associated tree mortality events, competition release is one silvicultural measure discussed to have an impact on the resilience of managed forest stands. Understanding how trees compete with each other is therefore crucial, but different measurement options and competition indices leave users with the agony of choice, as no single competition index has proven universally superior. C_LIO_LITo help users with the choice and computation of appropriate indices, we present the open-source TreeCompR package, which can handle 3D point clouds in various formats as well as classical forest inventory data and serves as a centralized platform for exploring and comparing different competition indices (CIs). Within a common interface, users can efficiently select the most suitable CI for their specific research questions. The package facilitates the integration of both traditional distance-dependent and novel point cloud-based indices. C_LIO_LITo evaluate the package, we used TreeCompR to quantify the competition situation of 308 European beech trees from 13 sites in Central Europe. Based on this dataset, we discuss the interpretation, comparability and sensitivity of the different indices to their parameterization and identify possible sources of uncertainty and ways to minimize them. C_LIO_LIThe compatibility of TreeCompR with different data formats and different data collection methods makes it accessible and useful for a wide range of users, specifically ecologists and foresters. Due to the flexibility in the choice of input formats as well as the emphasis on tidy, well-structured output, our package can easily be integrated into existing data-analysis workflows both for 3D point cloud and classical forest inventory data. C_LI

ecology↗