Reconstruction and variability of tropical pollination networks in the Brazilian Atlantic Forest

• Autor(a) principal: Pereira, Juliana
• Data de Publicação: 2022
• Outros Autores: Ribeiro, Milton Cezar [UNESP], Battiston, Federico, Jordán, Ferenc
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s42974-022-00106-6; http://hdl.handle.net/11449/242175
• topic: Blockmodels; Ecological networks; Species co-occurrence; Species interactions

Loss of biodiversity comprehends not only the extinction of individual species, but also the loss of the ecological interactions among them. Survival of species, continuation of ecosystem functioning in nature, and ecosystem services to humans depend on the maintenance of well-functioning networks of species interactions (e.g. plant–pollinator networks and food webs). Analyses of ecological networks often rely on biased and incomplete survey data, especially in species-rich areas, such as the tropics. We used a network inference method to reconstruct pollination data compiled from a large tropical rainforest habitat extent. To gain insight into the characteristics of plant–pollinator interactions across the region, we combined the reconstructed pollination network with species distribution modelling to obtain local pollination networks throughout the area. We explored how global network properties relate to natural forest cover and land cover heterogeneity. We found that some network properties (the sum and evenness of link weights, connectance and nestedness) are positively correlated with forest cover, indicating that networks in sites with more natural habitat have greater diversity of interactions. Modularity was not related to forest cover, but seemed to reflect habitat heterogeneity, due to the broad spatial scale of the study. We believe that the methodology suggested here can facilitate the use of incomplete network data in a reliable way and allow us to better understand and protect networks of species interactions in high biodiversity regions of the world.