TY - GEN A1 - Neyret, Margot A1 - Le Provost, Gaëtane A1 - Boesing, Andrea Larissa A1 - Schneider, Florian D. A1 - Baulechner, Dennis A1 - Bergmann, Joana A1 - Vries, Franciska T. de A1 - Fiore-Donno, Anna Maria A1 - Geisen, Stefan A1 - Goldmann, Kezia A1 - Merges, Anna A1 - Saifutdinov, Ruslan A. A1 - Simons, Nadja K. A1 - Tobias, Joseph A. A1 - Zaitsev, Andrey S. A1 - Gossner, Martin M. A1 - Jung, Kirsten A1 - Kandeler, Ellen A1 - Krauss, Jochen A1 - Penone, Caterina A1 - Schloter, Michael A1 - Schulz, Stefanie A1 - Staab, Michael A1 - Wolters, Volkmar A1 - Apostolakis, Antonios A1 - Birkhofer, Klaus A1 - Boch, Steffen A1 - Boeddinghaus, Runa S. A1 - Bolliger, Ralph A1 - Bonkowski, Michael A1 - Buscot, François A1 - Dumack, Kenneth A1 - Fischer, Markus A1 - Gan, Huei Ying A1 - Heinze, Johannes A1 - Hölzel, Norbert A1 - John, Katharina A1 - Klaus, Valentin H. A1 - Kleinebecker, Till A1 - Marhan, Sven A1 - Müller, Jörg A1 - Renner, Swen C. A1 - Rillig, Matthias C. A1 - Schenk, Noëlle V. A1 - Schöning, Ingo A1 - Schrumpf, Marion A1 - Seibold, Sebastian A1 - Socher, Stephanie A. A1 - Solly, Emily F. A1 - Teuscher, Miriam A1 - Kleunen, Mark van A1 - Wubet, Tesfaye A1 - Manning, Peter T1 - A slow-fast trait continuum at the whole community level in relation to land-use intensification T2 - Nature Communications N2 - 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. KW - General Physics and Astronomy KW - General Biochemistry KW - General Chemistry KW - Multidisciplinary KW - Genetics and Molecular Biology Y1 - 2024 U6 - https://doi.org/10.1038/s41467-024-45113-5 SN - 2041-1723 VL - 15 IS - 1 ER - TY - GEN A1 - Menares, Esteban A1 - Saíz, Hugo A1 - Schenk, Noëlle V. A1 - Garcia de la Riva, Enrique A1 - Krauss, Jochen A1 - Birkhofer, Klaus T1 - Co-occurrence patterns do not predict mutualistic interactions between plant and butterfly species T2 - Ecology and Evolution N2 - 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. KW - Biodiversity Exploratories KW - co- occurrence analysis | KW - flower visitations KW - mutualistic interactions KW - resence/absence data KW - species associations Y1 - 2024 U6 - https://doi.org/10.1002/ece3.70498 SN - 2045-7758 VL - 14 IS - 11 ER -