2 tables with 5 tabs: Rewiring_AreaNat; ComparisonToExpectedAtRandom; IntTurnover&Components_Novotny; Rewiring_H2&Nestedness; Pollinators_Ab,Spec&Rewiring., Understanding the flexibility of interactions and network rewiring (i.e. reassembly of interactions due to partner-switching) is necessary to comprehend how future anthropogenic changes will affect interspecific interactions and the functioning of communities. A higher rewiring could be expected in more disturbed landscapes because these landscapes contain fewer and more generalist species with more homogeneous traits. We sampled pollination interactions in 20 wild Olea europaea communities along a disturbance gradient to evaluate the hypothesis that the loss of natural habitats increases seasonal (within-year) interaction rewiring in plant-pollinator communities, influencing their functional structure. For this, we particularly tested whether rewiring frequency was negatively related to the extent of natural habitats surrounding the communities, whether interaction rewiring influenced the static structure of networks (nestedness, network specialization –H2’–), and whether a high generalization (low specialization –d’–) and abundance of species in communities made them more prone to rewiring. We show that habitat loss increased seasonal interaction rewiring in networks. Changes in rewiring were related to changes in the cumulative static structure of pollination networks. Nestedness decreased and network specialization (H2’) also tended to decrease as interaction rewiring increased, suggesting an indirect effect of habitat loss on the robustness of networks through their dynamics. As expected, generalist insect and plant species were more prone to rewiring. However, flower abundance had different effects on the rewiring probability of plant species depending on the extent of habitat loss, with abundant species rewiring more in disturbed communities and rewiring less in more natural communities. Likely, this is related to the context-dependent foraging behaviour of pollinators, which may switch to more abundant species if the cost of searching for trait-matching resources is high in disturbed habitats. Our work shows the role of partner-switching in generalist species to adapt to new conditions. It also highlights the importance of going beyond general network metrics to understand the underlying processes of community-level interaction assembly, and predict and anticipate the effects of anthropogenic disturbances on pollination services., Ministerio de Ciencia e Innovación, Award: MCIN/AEI/10.13039/501100011033_ Project PRPPID2020-117863RB-I00; Ministerio de Ciencia e Innovación, Award: CGL2017-89254-R, Lazaro_Gomez-Martinez_DryadData.xlsx, README_Lazaro_Gomez-Martinez.xlsx, Peer reviewed

[Motivation] The accelerated and widespread conversion of once continuous ecosystems into fragmented landscapes has driven ecological research to understand the response of biodiversity to local (fragment size) and landscape (forest cover and fragmentation) changes. This information has important theoretical and applied implications, but is still far from complete. We compiled the most comprehensive and updated database to investigate how these local and landscape changes determine species composition, abundance and trait diversity of multiple taxonomic groups in forest fragments across the globe., [Main Types of Variables Contained] We gathered data for 1472 forest fragments, providing information on the abundance and composition of 9154 species belonging to vertebrates, invertebrates, and plants. For 2703 of these species, we obtained more than 20 functional traits. We provided the spatial location and size of each fragment and metrics of landscape composition and configuration., [Spatial Location and Grain] The dataset includes 1472 forest fragments sampled in 121 studies from all continents except Antarctica. Most datasets (77%) are from tropical regions, 17% are from temperate regions, and 6% are from subtropical regions. Species abundance and composition were collected at the plot or fragment scale, whereas the landscape metrics were extracted with buffer size ranging from a radius of 200–2000 m., [Time Period and Grain] Data on the abundance of species and community composition were collected between 1994 and 2022, and the landscape metrics were extracted from the same year that a given study collected the abundance and composition data., [Major Taxa and Level of Measurement] The studied organisms included invertebrates (Arachnida, Insecta and Gastropoda; 41% of the datasets), vertebrates (Amphibia, Squamata, Aves and Mammalia; 44%), and vascular plants (19%), and the lowest level of identification was species or morphospecies., [Software Format] The dataset and code can be downloaded on Zenodo or GitHub., This study was supported by the Institute for Global Change Biology in the School for Environment and Sustainability and the Department of Ecology and Evolutionary Biology at the University of Michigan. M.H.V. (#2022/01899-6, São Paulo Research Foundation—FAPESP), J.C.P. (#2018/00107-3), and F.R.d.S. (#2013/50714-0 and #2022/04012-2) were supported by grants from FAPESP. A.L. was supported by the project PRPPID2020-117863RB-I00 (MCIN/AEI/10.13039/501100011033). F.P.L.M. (470574/2013-5), M.B. (304189/2022-7), and L.F.S.M. (307984/2022-2) received support from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico). M.V.G. was funded by UNILA (PRPPG 205/2021 and 77/2022). N.S. received support from Fundação Araucária (PBA2022011000042)., Peer reviewed

Data associated with article DOI: 10.1002/njb.05010. Includes the species-level network metric calculated for each pollinator species in 2018 and 2022, as well as the differences in metrics between years. Separately are shown the dataset for the analyses at the pollinator-group level and the species that appeared in both study years., Spanish Ministry of Science, Innovation, and Universities, and the Spanish State Research Agency: CGL2017-89254-R, Spanish Ministry of Science, Innovation, and Universities, and the Spanish State Research Agency: PID2020-117863RB-I00, Spanish Ministry of Science, Innovation, and Universities, and the Spanish State Research Agency: PID2023-150295OBI00, Peer reviewed