By Janaína Simões | Agência FAPESP – By mapping the distribution of butterfly species in the Atlantic Rainforest biome along the coast of Brazil, researchers have found species diversity to be greatest in Serra do Mar (literally “Sea Ridge” in Portuguese), Serra da Mantiqueira and Araucaria Pine Forest sub-regions, and in specific areas of Espírito Santo, Minas Gerais, Bahia and Pernambuco states. According to the study, these areas should therefore be prioritized by conservation policymakers.
The researchers also mapped areas with fewer species, such as the São Francisco River Basin. For these cases, they propose measures to restore ecosystem services, including the retrieval of at least part of the benefits provided by ecosystem services, such as nutrient cycling, climate and air quality regulation, control of soil erosion and pollination, among others.
The study was conducted by researchers at the University of Campinas (UNICAMP), São Paulo State University (UNESP) and the Federal University of Mato Grosso (UFMT) in Brazil.
The mapping survey shows that landscape variables such as percentage forest cover and terrain slope are as important as climate to explain current species distribution. The influence of landscape-related factors is well understood from microscale studies and for small groups of animals and plants, but it is a novelty in studies covering large geographic areas and many species.
In showing the areas of the biome for which landscape is more relevant than climate, the study also highlights the impact of human activity and the importance of forest remnants to the maintenance of species richness.
“Many Atlantic Rainforest landscapes have been altered, and the regions with the most species richness are close to big cities, so the influence of human activity on natural landscapes is currently the greatest threat to butterfly diversity in the biome,” Jessie Pereira dos Santos, joint first author of the article, told Agência FAPESP. Santos is a professor at UNICAMP’s Institute of Biology in the Department of Animal Biology.
Butterflies are key biological indicators in diagnosing the health of the environment and monitoring biodiversity. “Knowing what’s happening to these insects helps us understand what’s happening to the biome as a whole and helps formulate conservation policy,” Santos said.
The study shows that butterfly distribution patterns are similar to patterns for other groups of organisms, reinforcing the theory that the biome has centers of endemism – areas with high diversity and large numbers of species that do not occur elsewhere. The existence of these hotspots is one of the hypotheses scientists have raised to explain the biome’s exceptional diversity.
Through the mapping survey, the researchers quantified the contributions of the landscape and climate to butterfly species distribution, confirming that loss of natural habitats is the foremost threat to species diversity. The main map shows the locations in which landscape-related factors predominate over climate in influencing species loss.
“We were able to produce an overview of species richness and distribution for a large group of butterflies throughout the Atlantic Rainforest. This information had previously been confined to smaller groups,” Santos said.
According to André Victor Lucci Freitas, also a professor at UNICAMP’s Institute of Biology and last author of the article, one of the study’s most important contributions is the deployment of landscape metrics, such as land use, forest fragmentation, and other processes driven by human action, from a macroecological perspective, in which the focus is on relationships between organisms and their environment on a broad spatial scale. These metrics are typically used in studies of small areas, and very few studies have focused on the effects of landscape changes in this macro context. “Our research shows that the influence of landscape variables is as important as the influence of climate-related factors in determining large-scale species distribution,” he said.
The most common butterfly species in the biome include those of the genus Hermeuptychia, small brown butterflies frequently seen urban areas, on vacant lots and in parks; cracker butterflies of the genus Hamadryas, also seen in urban parks and recognizable by the clicking or cracking sound made by males as part of their territorial display; “blue morphos” (genus Morpho); and “owl butterflies” (genus Caligo), which have eyespots resembling owls’ eyes on their wings. The coconut caterpillar and others of the genus Brassolis are well-known for feeding on palm and banana trees. There are also rare or curious species, such as those of the genus Pampasatyrus.
The list of species used in the study resulted from the efforts of several researchers, especially Keith S. Brown Jr., principal investigator for a Thematic Project supported by the FAPESP Research Program on Biodiversity Characterization, Conservation, Restoration and Sustainable Use (BIOTA-FAPESP).
The computational models used to produce the butterfly distribution maps were based on 146 of the 279 species identified by the researchers in published and unpublished occurrence records because they were present in at least ten forest remnants according to the records. They considered the other 133 species endemic or rare, including them only in occurrence grid cells and final richness maps.
For methodological reasons, they chose to study butterflies that feed on rotting fruit and can be trapped using fermented fruit as bait in a passive collection method that does not depend on the collector’s experience and facilitates sample standardization.
The biome was divided into five endemism centers using a classification established in previous research – Bahia, Brejos Nordestinos (humid forest enclaves in the Northeast Caatinga region), Pernambuco, Diamantina, and the Serra do Mar – and three transition areas, namely São Francisco, Interior Forests, and Araucaria Pine Forests.
Models based on landscape and climate
The dataset from occurrence records was merged with data collected in the field. Landscape- and climate-related contributions to species richness were picked out using EcoLand, a novel methodology developed by the researchers. The resulting maps display predicted species richness based on landscape and climate variables separately and combined. “By combining the projections in different ways, it’s possible to see whether landscape or climate best predicts a given species richness value in different locations,” Santos said.
For example, the EcoLand analysis showed that both landscape- and climate-related species richness was high in most conserved Atlantic Rainforest remnants. However, in the large urban centers located near these areas, landscape variables predicted lower species richness even if climate variables predicted the opposite.
“The conclusion was that landscape variables were insufficient to support high species richness in these areas,” Santos said. The South region was another case in point. “Landscape variables predicted high species richness in this region, while climate factors were no longer adequate to assure high values,” he noted.
Separate analysis of the climate-based model showed that the areas with the highest species richness were Serra do Mar and Serra da Mantiqueira, with up to 162 species. The areas with the lowest species richness (fewer than 50 species) were São Francisco, the transition to the Cerrado (Brazilian savanna), and areas near the border with Paraguay and Argentina.
According to the landscape-based model, the areas with the highest species richness were Atlantic Rainforest remnants in the interior of Santa Catarina and Paraná states, including the Araucaria sub-region, and isolated points in Serra do Mar and Bahia. Up to 190 species were present in these areas. São Francisco and Pernambuco had the lowest species richness values in this model.
When the models were superimposed on a single map using EcoLand, it showed that most Atlantic Rainforest remnants had medium species richness values. Serra do Mar and Serra da Mantiqueira had high values, as did parts of Bahia and Pernambuco, as well as the Interior sub-region. The lowest values were in the northwestern portion of the region studied, particularly the São Francisco sub-region.
Areas with high species richness according to climate-related variables but low species richness according to landscape-related variables were mostly adjacent to the areas with high species richness areas predicted by both models. “These are probably the areas where butterfly richness was most affected by landscape modification and forest fragmentation. These areas are spread through practically all biogeographical sub-regions […], except the São Francisco sub-region”, the authors write.
This finding reinforces the importance of protecting forest remnants to assure the survival of all these species. Some 70% of Brazilians live in areas where the land was once covered by Atlantic Rainforest, now reduced to 11% of its original size.
In their conclusions, the authors note that areas of high species richness predicted by both climate and landscape models, such as Serra do Mar, should be core conservation priorities. They also argue that restoration of native cover should be prioritized in areas with low landscape-related species richness values and high climate-related values according to the model, and recommend implementing ecological corridors to improve connectivity in areas like Bahia where forests have been devastated and persist as a plethora of small fragments.
Given the ongoing climate changes, the authors also underscore the importance of areas with high species richness predicted by landscape but not climate, such as the Araucaria sub-region. For areas with high and medium richness values, conservation of species diversity should be prioritized, Santos said, “but we recommend a different approach for areas with lower values. Instead of vigorous action to conserve species [as richness is too low to justify investment in conservation in these areas], the priority should be to promote societal wellbeing by restoring basic ecosystem services.”
Ecosystem services contribute to the quality of life for the inhabitants of these areas and include pollination, soil fertilization, decomposition, control of soil erosion and climate, water flow regulation, water supply, and mitigation of greenhouse gas emissions, among others. “Habitat restoration can rehabilitate ecosystem services, but this isn’t always possible for lack of investment – hence our suggestion,” Santos said.
The EcoLand mapping exercise supported the main endemism locations described in previous studies for plants and other animals that inhabit Atlantic Rainforest areas. “We obtained diversity distribution patterns similar to those observed for other groups of organisms, supporting the theories that seek to explain the origins of diversity in this biome,” Santos said.
The trends detected should be seen as a warning. “Loss of diversity due to climate change is a major issue, but natural habitat losses are the main threat to diversity,” Santos stressed. “The cumulative effects of climate change could yield even more alarming scenarios.”
The article “Effects of landscape modification on species richness patterns of fruit-feeding butterflies in Brazilian Atlantic Forest” is at: onlinelibrary.wiley.com/doi/epdf/10.1111/ddi.13007.
Original article by Agência Fapesp: https://agencia.fapesp.br/mapping-of-butterfly-species-distribution-in-atlantic-rainforest-areas-identifies-conservation-priorities/35727/