C. F. Dormann

Process-guidance improves predictive performance of neural networks for carbon turnover in ecosystems

The paper improves neural network predictions for carbon turnover in ecosystems by integrating process-based models, showing better performance than data-only or mechanism-only models.

Linking null models to hypotheses to improve nestedness analysis

The paper introduces a framework linking null models to hypotheses to improve nestedness analysis in ecological networks.

European agroforestry is no universal remedy for biodiversity: a time-cumulative meta-analysis

This study finds agroforestry does not universally boost biodiversity, with benefits only in silvoarable systems over conventional agriculture, but results are inconsistent and influenced by unmeasured factors.

Neither global nor consistent: a technical comment on the tree diversity-productivity analysis of Liang et al. (2016)

The paper re-analyzes Liang et al. (2016) data, finding no local-scale effect of tree species richness on productivity and highlighting regional variability.

A new model explaining the origin of different topologies in interaction networks

The paper presents a mechanistic model explaining the origin of different topologies in interaction networks through specialization and trade-offs, showing nested and compound topologies based on diversity and resource dissimilarity.