@misc{NeyretLeProvostBoesingetal., author = {Neyret, Margot and Le Provost, Ga{\"e}tane and Boesing, Andrea Larissa and Schneider, Florian D. and Baulechner, Dennis and Bergmann, Joana and Vries, Franciska T. de and Fiore-Donno, Anna Maria and Geisen, Stefan and Goldmann, Kezia and Merges, Anna and Saifutdinov, Ruslan A. and Simons, Nadja K. and Tobias, Joseph A. and Zaitsev, Andrey S. and Gossner, Martin M. and Jung, Kirsten and Kandeler, Ellen and Krauss, Jochen and Penone, Caterina and Schloter, Michael and Schulz, Stefanie and Staab, Michael and Wolters, Volkmar and Apostolakis, Antonios and Birkhofer, Klaus and Boch, Steffen and Boeddinghaus, Runa S. and Bolliger, Ralph and Bonkowski, Michael and Buscot, Fran{\c{c}}ois and Dumack, Kenneth and Fischer, Markus and Gan, Huei Ying and Heinze, Johannes and H{\"o}lzel, Norbert and John, Katharina and Klaus, Valentin H. and Kleinebecker, Till and Marhan, Sven and M{\"u}ller, J{\"o}rg and Renner, Swen C. and Rillig, Matthias C. and Schenk, No{\"e}lle V. and Sch{\"o}ning, Ingo and Schrumpf, Marion and Seibold, Sebastian and Socher, Stephanie A. and Solly, Emily F. and Teuscher, Miriam and Kleunen, Mark van and Wubet, Tesfaye and Manning, Peter}, title = {A slow-fast trait continuum at the whole community level in relation to land-use intensification}, series = {Nature Communications}, volume = {15}, journal = {Nature Communications}, number = {1}, issn = {2041-1723}, doi = {10.1038/s41467-024-45113-5}, abstract = {AbstractOrganismal functional strategies form a continuum from slow- to fast-growing organisms, in response to common drivers such as resource availability and disturbance. However, whether there is synchronisation of these strategies at the entire community level is unclear. Here, we combine trait data for 2800 above- and belowground taxa from 14 trophic guilds spanning a disturbance and resource availability gradient in German grasslands. The results indicate that most guilds consistently respond to these drivers through both direct and trophically mediated effects, resulting in a 'slow-fast' axis at the level of the entire community. Using 15 indicators of carbon and nutrient fluxes, biomass production and decomposition, we also show that fast trait communities are associated with faster rates of ecosystem functioning. These findings demonstrate that 'slow' and 'fast' strategies can be manifested at the level of whole communities, opening new avenues of ecosystem-level functional classification.}, language = {en} } @misc{MenaresSaizSchenketal., author = {Menares, Esteban and Sa{\´i}z, Hugo and Schenk, No{\"e}lle V. and Garcia de la Riva, Enrique and Krauss, Jochen and Birkhofer, Klaus}, title = {Co-occurrence patterns do not predict mutualistic interactions between plant and butterfly species}, series = {Ecology and Evolution}, volume = {14}, journal = {Ecology and Evolution}, number = {11}, issn = {2045-7758}, doi = {10.1002/ece3.70498}, pages = {13}, abstract = {Biotic interactions are crucial for determining the structure and dynamics of communities; however, direct measurement of these interactions can be challenging in terms of time and resources, especially when numerous species are involved. Inferring species interactions from species co-occurrence patterns is increasingly being used; however, recent studies have highlighted some limitations. To our knowledge, no attempt has been made to test the accuracy of the existing methods for detecting mutualistic interactions in terrestrial ecosystems. In this study, we compiled two literature-based, long-term datasets of interactions between butterflies and herbaceous plant species in two regions of Germany and compared them with observational abundance and presence/absence data collected within a year in the same regions. We tested how well the species associations generated by three different co-occurrence analysis methods matched those of empirically measured mutualistic associations using sensitivity and specificity analyses and compared the strength of associations. We also checked whether flower abundance data (instead of plant abundance data) increased the accuracy of the co-occurrence models and validated our results using empirical flower visitation data. The results revealed that, although all methods exhibited low sensitivity, our implementation of the Relative Interaction Intensity index with pairwise null models performed the best, followed by the probabilistic method and Spearman's rank correlation method. However, empirical data showed a significant number of interactions that were not detected using co-occurrence methods. Incorporating flower abundance data did not improve sensitivity but enhanced specificity in one region. Further analysis demonstrated incongruence between the predicted co-occurrence associations and actual interaction strengths, with many pairs exhibiting high interaction strength but low co-occurrence or vice versa. These findings underscore the complexity of ecological dynamics and highlight the limitations of current co-occurrence methods for accurately capturing species interactions.}, language = {en} }