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Strong context-dependence in the relative importance of climate and habitat on macro-moth community changes in Finland
  • Emy Guilbault
Emy Guilbault
University of Helsinki

Corresponding Author:[email protected]

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Evaluating the relative impacts of land use and climate change on community change is challenging – and their impact may be contextdependent. Here, we use long-term nocturnal macro-moth community data to evaluate the relative impacts of changing habitats vs. changing climates on community composition and diversity of moths in different landscape settings and for moth species associated with different traits. We used Hierarchical Modelling of Species Communities to pinpoint moth species’ responses to climate and habitat composition in 109 sites across Finland. To characterise context-dependence, we extended this framework with conditional variance partitioning analysis. We used the model predictions to evaluate the relative effect of drivers on community diversity across Finland. The landscape context (i.e. the habitat composition around the site and its changes) emerged as the dominant driver of macro-moth communities. At the site level, where forests or shrub-like vegetation dominates, variation in species occurrence was mostly explained by local habitat conditions. In heterogeneous and water-dominated habitats, both habitat and climate variability contributed equally to patterns in species occurrence. At the species level, macro-moth responses to drivers of change varied according to their host plant affinity but independently of their wingspan. Climate and habitat changes can thus contribute congruently or unequally to community change, depending on the habitat. At the community level, traits also give insights into trends in and temporal variability of biogeographic patterns. Our results underpin the importance of land-use change as a key driver of community change – even among heatsensitive ectotherms. We also demonstrate that the sensitivity of local communities to climate and land use change varies among habitat profiles. Overall, our results highlight the importance of accounting for local conditions to understand and predict community patterns under global change.
10 Nov 2023Submitted to Ecography
12 Nov 2023Assigned to Editor
12 Nov 2023Submission Checks Completed
12 Nov 2023Review(s) Completed, Editorial Evaluation Pending
14 Nov 2023Reviewer(s) Assigned