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1.
Naturwissenschaften ; 110(4): 28, 2023 Jun 08.
Artigo em Inglês | MEDLINE | ID: mdl-37289369

RESUMO

Habitat fragmentation and ecosystem changes have the potential to affect animal populations in different ways. To effectively monitor these changes, biomonitoring tools have been developed and applied to detect changes in population structure and/or individual traits that reflect such changes. Fluctuating asymmetry (FA) represents random deviations from perfect symmetry in bilateral traits from perfect symmetry in response to genetic and/or environmental stresses. In this study, we evaluated the use of FA as a tool to monitor stress caused by forest fragmentation and edge formation, using the tropical butterfly M. helenor (Nymphalidae) as a model species. We collected adult butterflies from three fragments of Atlantic Forest in Brazil encompassing both edge and interior habitats. Four wing traits (wing length, wing width, ocelli area, and ocelli diameter) were evaluated. Butterflies captured at edge sites exhibited higher FA values for wing length and wing width compared to those captured at interior sites, whereas traits related to ocelli did not show differences between the two habitat types. Our results suggest that the differences in abiotic and biotic conditions between forest interior and edges can act as a source of stress, impacting the symmetry of flight-related traits. On the other hand, as ocelli are crucial for butterfly camouflage and counter-predator strategies, our results indicate that this trait may be more conserved. By employing FA, we identified trait-specific responses to habitat fragmentation, thus suggesting its potential as a biomarker for environmental stress that can be used in butterflies to monitor habitat quality and change.


Assuntos
Borboletas , Ecossistema , Animais , Borboletas/genética , Florestas , Asas de Animais , Fenótipo
2.
Ecology ; 99(12): 2875, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30380155

RESUMO

Butterflies are one of the best-known insect groups, and they have been the subject of numerous studies in ecology and evolution, especially in the tropics. Much attention has been given to the fruit-feeding butterfly guild in biodiversity conservation studies, due to the relative ease with which taxa may be identified and specimens sampled using bait traps. However, there remain many uncertainties about the macroecological and biogeographical patterns of butterflies in tropical ecosystems. In the present study, we gathered information about fruit-feeding butterfly species in local communities from the Atlantic Forests of South America. The ATLANTIC BUTTERFLIES data set, which is part of ATLANTIC SERIES data papers, results from a compilation of 145 unpublished inventories and 64 other references, including articles, theses, and book chapters published from 1949 to 2018. In total, the data set contains 7,062 records (presence) of 279 species of fruit-feeding butterflies identified with taxonomic certainty, from 122 study locations. The Satyrini is the tribe with highest number of species (45%) and records (30%), followed by Brassolini, with 13% of species and 12.5% of records. The 10 most common species correspond to 14.2% of all records. This data set represents a major effort to compile inventories of fruit-feeding butterfly communities, filling a knowledge gap about the diversity and distribution of these butterflies in the Atlantic Forest. We hope that the present data set can provide guidelines for future studies and planning of new inventories of fruit-feeding butterflies in this biome. The information presented here also has potential use in studies across a great variety of spatial scales, from local and landscape levels to macroecological research and biogeographical research. We expect that such studies be very important for the better implementation of conservation initiatives, and for understanding the multiple ecological processes that involve fruit-feeding butterflies as biological indicators. No copyright restrictions apply to the use of this data set. Please cite this Data paper when using the current data in publications or teaching events.

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