Abstract

AbstractAimThe world's forested area has been declining, especially in developing countries. In contrast, forest plantations are increasing, particularly exotic Eucalyptus plantations, which cover nowadays over 20 million ha worldwide. This global landscape change affects native communities, especially those at higher trophic levels that are affected by bottom–up cascading effects, such as carnivores. We seek to identify the general life‐history traits of mammalian carnivore species that use exotic Eucalyptus plantations.LocationWe reviewed 55 studies reporting carnivore presence in Eucalyptus plantations worldwide.MethodsWe consider seven species life‐history traits (generation length, social behaviour, body mass, energetic trophic level, diet diversity, habitat generalist/specialist and locomotion mode) as candidate drivers. We used generalized linear mixed models, with life‐history traits as fixed factors, and study as well as carnivore species as random factors. We obtained the carnivore occurrence data from the literature (detection of 42 different species, from seven families). We considered non‐detected species those with an IUCN Red List of Threatened Species estimated distribution range overlapping with the study areas, but not recorded by the studies.ResultsWhile we found no evidence of an effect of any of the other life‐history traits tested, our modelling procedure indicated that habitat generalist species are more likely to use Eucalyptus forests than specialist species.Main conclusionsOur results, therefore, confirm an impoverishment of predator communities in disturbed environments, with the exclusion of the most specialist predators, leading to fragmentation of their populations and, ultimately contributing to their local extinction. The local extinction of specialist carnivores may lead to “functional homogenization” of communities within plantations, modifying ecosystem functioning with a negative impact on plantations’ productivity, profitability and services.

Highlights

  • No variables displayed high collinearity in our set of explanatory variables (i.e. Variance Inflation Factors (VIF) ≥ 5), and we did not remove any of the initial variables from the analysis, leaving all seven variables to be used for model building

  • habitat generalist/ specialist character (Habitat) generalist character was key for carnivore occurrence in Eucalyptus plantations, partially supporting our second hypothesis, that is, habitat generalist species are more prone to use exotic plantations, as they are able to use a wider range of environments/resources (e.g. Timo et al, 2014)

  • Other alternative hypotheses based on carnivore's body mass, generation length, generalist feeding behaviour, locomotion mode and social behaviour had no support from our data

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Summary

| Literature review

We conducted a systematic review of published literature to identify studies detecting the presence of mammalian carnivore species within exotic Eucalyptus plantations all over the world. No variables displayed high collinearity in our set of explanatory variables (i.e. VIF ≥ 5), and we did not remove any of the initial variables from the analysis, leaving all seven variables to be used for model building (generation length, social behaviour, body mass, energetic trophic level, Shannon–Wiener Index, locomotion mode and habitat generalist/specialist character) (see Appendix S2 for variables variation). The estimated best overall average model included three variables: habitat generalist/specialist character; energetic trophic level; and Shannon–Wiener Index From those only one (“Habitat generalist/specialist character”) had a 90% confidence interval that did not overlap with zero, evidencing their influence on carnivore presence in Eucalyptus plantations (Table 3). We could not assess how they influence carnivore occurrence as the 90% confidence interval included positive and negative values According to these results, habitat generalists have a higher probability of occurring in Eucalyptus plantations (Table 3). The best models presented good predicting capacity, with an AUC value of 0.883 (Manel et al, 2001)

Findings
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| CONCLUSION
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