title: The reduced effectiveness of protected areas under climate change threatens Atlantic forest tiger moths.
abstract: Climate change leads to species' range shifts, which may end up reducing the effectiveness of protected areas. These deleterious changes in biodiversity may become amplified if they include functionally important species, such as herbivores or pollinators. We evaluated how effective protected areas in the Brazilian Atlantic Forest are in maintaining the diversity of tiger moths (Arctiinae) under climate change. Specifically, we assessed whether protected areas will gain or lose species under climate change and mapped their locations in the Atlantic Forest, in order to assess potential spatial patterns of protected areas that will gain or lose species richness. Comparisons were completed using modeled species occurrence data based on the current and projected climate in 2080. We also built a null model for random allocation of protected areas to identify where reductions in species richness will be more severe than expected. We employed several modern techniques for modeling species' distributions and summarized results using ensembles of models. Our models indicate areas of high species richness in the central and southern regions of the Atlantic Forest both for now and the future. However, we estimate that in 2080 these regions should become climatically unsuitable, decreasing the species' distribution area. Around 4% of species were predicted to become extinct, some of them being endemic to the biome. Estimates of species turnover from current to future climate tended to be high, but these findings are dependent on modeling methods. Our most important results show that only a few protected areas in the southern region of the biome would gain species. Protected areas in semideciduous forests in the western region of the biome would lose more species than expected by the null model employed. Hence, current protected areas are worse off, than just randomly selected areas, at protecting species in the future.
authors.affiliation: Departamento de Ecologia, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Viviane G
authors.initials: VG
authors.lastname: Ferro
authors.affiliation: Programa de Pós-Graduação em Ecologia e Evolução, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Priscila
authors.initials: P
authors.lastname: Lemes
authors.affiliation: Departamento de Ecologia, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Adriano S
authors.initials: AS
authors.lastname: Melo
authors.affiliation: Departamento de Ecologia, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Rafael
authors.initials: R
authors.lastname: Loyola
mesh_terms: D000818:Animals; D044822:Biodiversity; D057231:Climate Change; D003247:Conservation of Natural Resources; D000069550:Machine Learning; D009036:Moths; D009626:Terminology as Topic