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

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

Mutually beneficial pollinator diversity and crop yield outcomes in small and large farms

Ecological intensification, or the improvement of crop yield through enhancement of biodiversity, may be a sustainable pathway toward greater food supplies. Such sustainable increases may be especially important for the 2 billion people reliant on small farms, many of which are undernourished, yet we know little about the efficacy of this approach. Using a coordinated protocol across regions and crops, we quantify to what degree enhancing pollinator density and richness can improve yields on 344 fields from 33 pollinator-dependent crop systems in small and large farms from Africa, Asia, and Latin America. For fields less than 2 hectares, we found that yield gaps could be closed by a median of 24% through higher flower-visitor density. For larger fields, such benefits only occurred at high flower-visitor richness.Worldwide, our study demonstrates that ecological intensification can create synchronous biodiversity and yield outcomes.Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Negro. Centro de Investigaciones y Transferencia de Rio Negro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Rio Negro; ArgentinaFil: Carvalheiro, Luísa G.. Universidade do Brasília; BrasilFil: Vaissière, Bernard E.. Centre de Recherche de Nantes. Institut National de la Recherche Agronomique; FranciaFil: Gemmill Herren, Barbara. Food and Agriculture Organization of the United Nations; ItaliaFil: Hipólito, Juliana. Universidade Federal da Bahia; BrasilFil: Freitas, Breno M.. Universidade Federal do Ceará; BrasilFil: Ngo, Hien T.. Intergovernmental Platform on Biodiversity and Ecosystem Services; AlemaniaFil: Azzu, Nadine. Food and Agriculture Organization of the United Nations; ItaliaFil: Sáez, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Åström, Jens. Norwegian Institute for Nature Research; NoruegaFil: An, Jiandong. Chinese Academy of Agricultural Sciences; ChinaFil: Blochtein, Betina. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Buchori, Damayanti. Bogor Agricultural University; IndonesiaFil: Chamorro García, Fermín J.. Universidad Nacional de Colombia; ColombiaFil: Da Silva, Fabiana Oliveira. Universidade Federal de Sergipe; BrasilFil: Devkota, Kedar. Institute of Agriculture and Animal Science; NepalFil: De Fátima Ribeiro, Márcia. Embrapa Semiárido; BrasilFil: Freitas, Leandro. Jardim Botânico do Rio de Janeiro; BrasilFil: Gaglianone, Maria C.. Universidade Estadual Do Norte Fluminense Darcy Ribeiro; BrasilFil: Goss, Maria. University of Zimbabwe; ZimbabueFil: Irshad, Mohammad. Honey Bee Research Institute; PakistánFil: Kasina, Muo. Kenya Agricultural and Livestock Research Organisation-Sericulture; KeniaFil: Pacheco Filho, Alípio J.S.. Universidade Federal do Ceará; BrasilFil: Piedade Kiill, Lucia H.. Embrapa Semiárido; BrasilFil: Kwapong, Peter. University of Cape Coast; GhanaFil: Parra, Guiomar Nates. Universidad Nacional de Colombia; ColombiaFil: Pires, Carmen. Parque Estação Biológica; BrasilFil: Pires, Viviane. Instituto do Meio Ambiente e Recursos Hídrico; BrasilFil: Rawal, Ranbeer S.. G.B. Pant Institute of Himalayan Environment and Development; IndiaFil: Rizali, Akhmad. University of Brawijaya; IndonesiaFil: Saraiva, Antonio M.. Universidade de Sao Paulo; BrasilFil: Veldtman, Ruan. South African National Biodiversity Institute; Sudáfrica. Stellenbosch University; SudáfricaFil: Viana, Blandina F.. Universidade Federal da Bahia; BrasilFil: Witter, Sidia. Fundação Estadual de Pesquisa Agropecuária; BrasilFil: Zhang, Hong. Chinese Academy of Agricultural Sciences; Chin

Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications