Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

The shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiver sity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxo nomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world’s known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world’s most biodiverse countries. We further identify collection gaps and summarize future goals that extend be yond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still un equally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the coun try. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora.Fil: Gomes da Silva, Janaina. Jardim Botânico do Rio de Janeiro: Rio de Janeiro, BrasilFil: Filardi, Fabiana L.R. Jardim Botânico do Rio de Janeiro; BrasilFil: Barbosa, María Regina de V. Universidade Federal da Paraíba: Joao Pessoa; BrasilFil: Baumgratz, José Fernando Andrade. Jardim Botânico do Rio de Janeiro; BrasilFil: de Mattos Bicudo, Carlos Eduardo. Instituto de Botânica. Núcleo de Pesquisa em Ecologia; BrasilFil: Cavalcanti, Taciana. Empresa Brasileira de Pesquisa Agropecuária Recursos Genéticos e Biotecnologia; BrasilFil: Coelho, Marcus. Prefeitura Municipal de Campinas; BrasilFil: Ferreira da Costa, Andrea. Federal University of Rio de Janeiro. Museu Nacional. Department of Botany; BrasilFil: Costa, Denise. Instituto de Pesquisas Jardim Botanico do Rio de Janeiro; BrasilFil: Dalcin, Eduardo C. Rio de Janeiro Botanical Garden Research Institute; BrasilFil: Labiak, Paulo. Universidade Federal do Parana; BrasilFil: Cavalcante de Lima, Haroldo. Jardim Botânico do Rio de Janeiro; BrasilFil: Lohmann, Lucia. Universidade de São Paulo; BrasilFil: Maia, Leonor. Universidade Federal de Pernambuco; BrasilFil: Mansano, Vidal de Freitas. Instituto de Pesquisas Jardim Botânico do Rio de Janeiro; Brasil. Jardim Botânico do Rio de Janeiro; BrasilFil: Menezes, Mariângela. Federal University of Rio de Janeiro. Museu Nacional. Department of Botany; BrasilFil: Morim, Marli. Instituto de Pesquisas Jardim Botânico do Rio de Janeiro; BrasilFil: Moura, Carlos Wallace do Nascimento. Universidade Estadual de Feira de Santana. Department of Biological Science; BrasilFil: Lughadha, Eimear NIck. Royal Botanic Gardens; Reino UnidoFil: Peralta, Denilson. Instituto de Pesquisas Ambientais; BrazilFil: Prado, Jefferson. Instituto de Pesquisas Ambientais; BrasilFil: Roque, Nádia. Universidade Federal da Bahia; BrasilFil: Stehmann, Joao. Universidade Federal de Minas Gerais; BrasilFil: da Silva Sylvestre, Lana. Universidade Federal do Rio de Janeiro; BrasilFil: Trierveiler-Pereira, Larissa. Universidade Estadual de Maringá. Departamento de Análises Clínicas e Biomedicina; BrasilFil: Walter, Bruno Machado Teles. EMBRAPA Cenargen Brasília; BrasilFil: Zimbrão, Geraldo. Universidade Federal do Rio de Janeiro; BrasilFil: Forzza, Rafaela C. Jardim Botânico do Rio de Janeiro; BrasilFil: Morales, Matías. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Morón. Facultad de Agronomía y Ciencias Agroalimentarias; Argentin

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

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

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost

Brazilian Flora 2020: leveraging the power of a collaborative scientific network.

The shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiver sity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxo nomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world’s known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world’s most biodiverse countries. We further identify collection gaps and summarize future goals that extend be yond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still un equally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the coun try. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora.Fil: Gomes da Silva, Janaina. Jardim Botânico do Rio de Janeiro: Rio de Janeiro, BrasilFil: Filardi, Fabiana L.R. Jardim Botânico do Rio de Janeiro; BrasilFil: Barbosa, María Regina de V. Universidade Federal da Paraíba: Joao Pessoa; BrasilFil: Baumgratz, José Fernando Andrade. Jardim Botânico do Rio de Janeiro; BrasilFil: de Mattos Bicudo, Carlos Eduardo. Instituto de Botânica. Núcleo de Pesquisa em Ecologia; BrasilFil: Cavalcanti, Taciana. Empresa Brasileira de Pesquisa Agropecuária Recursos Genéticos e Biotecnologia; BrasilFil: Coelho, Marcus. Prefeitura Municipal de Campinas; BrasilFil: Ferreira da Costa, Andrea. Federal University of Rio de Janeiro. Museu Nacional. Department of Botany; BrasilFil: Costa, Denise. Instituto de Pesquisas Jardim Botanico do Rio de Janeiro; BrasilFil: Dalcin, Eduardo C. Rio de Janeiro Botanical Garden Research Institute; BrasilFil: Labiak, Paulo. Universidade Federal do Parana; BrasilFil: Cavalcante de Lima, Haroldo. Jardim Botânico do Rio de Janeiro; BrasilFil: Lohmann, Lucia. Universidade de São Paulo; BrasilFil: Maia, Leonor. Universidade Federal de Pernambuco; BrasilFil: Mansano, Vidal de Freitas. Instituto de Pesquisas Jardim Botânico do Rio de Janeiro; Brasil. Jardim Botânico do Rio de Janeiro; BrasilFil: Menezes, Mariângela. Federal University of Rio de Janeiro. Museu Nacional. Department of Botany; BrasilFil: Morim, Marli. Instituto de Pesquisas Jardim Botânico do Rio de Janeiro; BrasilFil: Moura, Carlos Wallace do Nascimento. Universidade Estadual de Feira de Santana. Department of Biological Science; BrasilFil: Lughadha, Eimear NIck. Royal Botanic Gardens; Reino UnidoFil: Peralta, Denilson. Instituto de Pesquisas Ambientais; BrazilFil: Prado, Jefferson. Instituto de Pesquisas Ambientais; BrasilFil: Roque, Nádia. Universidade Federal da Bahia; BrasilFil: Stehmann, Joao. Universidade Federal de Minas Gerais; BrasilFil: da Silva Sylvestre, Lana. Universidade Federal do Rio de Janeiro; BrasilFil: Trierveiler-Pereira, Larissa. Universidade Estadual de Maringá. Departamento de Análises Clínicas e Biomedicina; BrasilFil: Walter, Bruno Machado Teles. EMBRAPA Cenargen Brasília; BrasilFil: Zimbrão, Geraldo. Universidade Federal do Rio de Janeiro; BrasilFil: Forzza, Rafaela C. Jardim Botânico do Rio de Janeiro; BrasilFil: Morales, Matías. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Morón. Facultad de Agronomía y Ciencias Agroalimentarias; Argentin

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.A study mapping the tree species richness in Amazonian forests shows that soil type exerts a strong effect on species richness, probably caused by the areas of these forest types. Cumulative water deficit, tree density and temperature seasonality affect species richness at a regional scale

Mapping density, diversity and species-richness of the Amazon tree flora

AbstractUsing 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.</jats:p