Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

Julkaisu on kaksikielinen: suomi ja ruotsi

Quantas espécies de plantas vasculares existem em um hotspot local de biodiversidade no sudeste do Brasil?

Scientific information about the distribution of species richness and diversity is necessary for full comprehension of our evolutionary heritage forming a powerful tool for the development of nature conservation strategies. The aim of this article was to estimate the vascular plant species richness of the campos rupestres from the Itacolomi State Park (ISP) in order to verify the park´s classification as a local hotspot of biodiversity and to outline the status quo of knowledge about biodiversity in the region. For that, the species richness of two phytosociological surveys of 0.15 ha each were extrapolated using (a) the species-area relationship fitted by the power and the logarithmic model as well as (b) the taxon ratio model. The taxon ratio model estimates total vascular plant species richness to 1109 species using seven different taxa. Extrapolations of different fittings of the species-area relationships calculate the complete park’s richness to values between 241 and 386 (logarithmic model), and 3346 to 10421 (power model). These extrapolations are far beyond realistic: the logarithmic model underestimates the park´s species richness, because more than 520 vascular plant species have already been registered in the park. On the other hand, it is not plausible that one-fourth or more of all species registered so far in the Atlantic Tropical Forest Biome occur in the ISP as indicated by the extrapolation with the power model. The most realistic estimation was achieved by the taxon ratio model. Although confidence intervals are large, the species richness estimated by this method legitimates the classification of the ISP as a local hotspot of biodiversity, but this value also outlines the lack of knowledge about biodiversity in this region and the urgent need for more taxonomical and ecological research.Key words: campos rupestres, species-area relationship, taxon ratios, Espinhaço Mountain Range.Informação científica sobre a distribuição de riqueza e diversidade de espécies é necessária para a compreensão plena da nossa herança evolutiva formando uma ferramenta poderosa para o desenvolvimento de estratégias de conservação de natureza. O objetivo deste trabalho constituiu-se em estimar a riqueza de plantas vasculares nos campos rupestres do Parque Estadual do Itacolomi (PEI) para justificar a sua classificação como um hotspot local de biodiversidade e para delinear o status quo do conhecimento sobre a biodiversidade na região. Para isso, o número de espécies encontradas em dois levantamentos fitossociológicos de 0,15 ha cada foi extrapolado usando (a) a relação espécie-área ajustada pelo modelo de potência e pelo modelo logarítmico bem como (b) o modelo de relação de táxons. O modelo de relação de táxons estimou a riqueza total para 1.109 espécies usando sete diferentes táxons. Extrapolações de diferentes modelos da relação espécie-área estimaram a riqueza total dos campos rupestres do parque para valores entre 241 e 386 (modelo logarítmico) e 3346 e 10421 (modelo de potência). As extrapolações da relação espécie-área foram muito além do real: o modelo logarítmico subestimou a riqueza de espécies do parque, porque há mais de 520 espécies de plantas vasculares registradas para o parque. Por outro lado, não é plausível que um quarto ou mais das espécies registradas no Bioma Mata Atlântica ocorra no PEI como a extrapolação do modelo de potência indicou. A estimativa mais realista foi alcançada pelo modelo de relação dos táxons. Embora os intervalos de confiança sejam grandes, a riqueza de espécies estimada por esse método justificou a classificação do PEI como um hotspot local de biodiversidade. A riqueza estimada de espécies também destacou a falta de conhecimento sobre a biodiversidade da região e a necessidade urgente de mais pesquisas taxonômicas e ecológicas.Palavras-chave: campos rupestres, relação espécie-área, relações táxon, Serra do Espinhaço

DNA-Based Arthropod Diversity Assessment in Amazonian Iron Mine Lands Show Ecological Succession Towards Undisturbed Reference Sites

Human activities change natural landscapes, and in doing so endanger biodiversity and associated ecosystem services. To reduce the net impacts of these activities, such as mining, disturbed areas are rehabilitated and restored. During this process, monitoring is important to ensure that desired trajectories are maintained. In the Carajás region of the Brazilian Amazon, exploration for iron ores has transformed the original ecosystem; natural forest and a savanna formation with lateritic iron duricrust outcrops named canga. Here, native vegetation is logged and topsoil removed and deposited in waste piles along with mine waste. During rehabilitation, these waste piles are hydroseeded with non-native plant species to achieve rapid revegetation. Further, seeds of native canga and forest plant species are planted to point ecological succession towards natural ecosystems. In this study, we investigate diversity and composition of the arthropod community along a post-mining rehabilitation and restoration gradient, taking seasonality and primer bias into account. We use DNA metabarcoding of bulk arthropod samples collected in both the dry and rainy seasons from waste-pile benches at various stages of revegetation: non-revegetated exposed soils, initial stage with one-to-three-year-old stands, intermediate stage with four-to-five-year-old stands, and advanced stage with six-to-seven-year-old stands. We use samples from undisturbed cangas and forests as reference sites. In addition, we vegetation diversity and structure were measured to investigate relations between arthropod community and vegetation structure. Our results show that, over time, the arthropod community composition of the waste piles becomes more similar to the reference forests, but not to the reference cangas. Nevertheless, even the communities in the advanced-stage waste piles are different from the reference forests, and full restoration in these highly diverse ecosystems is not achieved, even after 6 to 7 years. Finally, our results show seasonal variation in arthropod communities and primer bias

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio