Vegetation structure and climate shape mountain arthropod distributions across trophic levels.

Arthropods play a vital role in ecosystems; yet, their distributions remain poorly understood, particularly in mountainous regions. This study delves into the modelling of the distribution of 31 foliar arthropod genera in the French Alps, using a comprehensive approach encompassing multi-trophic sampling, community DNA metabarcoding and random forest models. The results underscore the significant importance of vegetation structure, such as herbaceous vegetation density, and forest density and heterogeneity, along with climate, in shaping the distributions of most arthropods.

Novel community data in ecology-properties and prospects.

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation.

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data.

Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The complexity of these data prevents current methods from extracting and analyzing all the relevant ecological information they contain, and new methods may provide better dimensionality reduction and clustering. Here we present two new deep learning-based methods that combine different types of neural networks (NNs) to ordinate eDNA samples and visualize ecosystem properties in a two-dimensional space: the first is based on variational autoencoders and the second on deep metric learning.

Analysis of complex trophic networks reveals the signature of land-use intensification on soil communities in agroecosystems.

Increasing evidence suggests that agricultural intensification is a threat to many groups of soil biota, but how the impacts of land-use intensity on soil organisms translate into changes in comprehensive soil interaction networks remains unclear. Here for the first time, we use environmental DNA to examine total soil multi-trophic diversity and food web structure for temperate agroecosystems along a gradient of land-use intensity. We tested for response patterns in key properties of the soil food webs in sixteen fields ranging from arable crops to grazed permanent grasslands as part of a long-term management experiment.

Cascading effects of moth outbreaks on subarctic soil food webs.

The increasing severity and frequency of natural disturbances requires a better understanding of their effects on all compartments of biodiversity. In Northern Fennoscandia, recent large-scale moth outbreaks have led to an abrupt change in plant communities from birch forests dominated by dwarf shrubs to grass-dominated systems. However, the indirect effects on the belowground compartment remained unclear.