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Disentangling effects of local and landscape variables on attractiveness of restored gravel‐sand pits for bat foraging activities
Author(s) -
Kerbiriou Christian,
ParisotLaprun Marion
Publication year - 2020
Publication title -
land degradation and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 81
eISSN - 1099-145X
pISSN - 1085-3278
DOI - 10.1002/ldr.3604
Subject(s) - foraging , attractiveness , biodiversity , ecology , habitat , geography , restoration ecology , environmental science , environmental resource management , biology , psychology , psychoanalysis
Despite the impacts of extraction activities, quarries have great potential for conservation of biodiversity, and their restoration can be considered a major task in restoration ecology. A particularly important issue is to quantify the roles of the following various factors that may influence biodiversity and restoration success: (a) local variables, (b) landscape variables and (c) ecological management. Following a multi‐model inference, we identify which variables were the most useful predictors of bat activity in gravel‐sand pits. We used data from 21 French gravel‐sand pits provided by the biodiversity‐monitoring scheme, ROSELIERE. Our results suggest that within these restored gravel‐sand pits, landscape variables appear to be better predictors of the attractiveness of restored gravel‐sand pits for the foraging activity of bats than local variables. Species or community indexes appeared to be more sensitive to landscape variables measured at a large scale (i.e., 1,000 m). Among local variables, the time elapsed after operation was a better predictor of bat foraging activity than the description of the habitat itself. The effect was more obvious within a site with an elapsed time since operation greater than 10 years. Our findings suggest that to increase the attractiveness of gravel‐sand pits for bat foraging activities, planning policies should consider not only the intrinsic characteristics of a project (i.e., local variables) but also the surrounding environment (i.e., landscape variables).