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

Image-guided percutaneous intralesional administration of mesenchymal stromal cells in subjects with chronic complete spinal cord injury: a pilot study

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2017-08-16T13:31:50Z No. of bitstreams: 1 Larocca TF Image-guided....pdf: 387218 bytes, checksum: 3e5d59f868cf7e153f1aa904be8b2251 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2017-08-16T13:45:57Z (GMT) No. of bitstreams: 1 Larocca TF Image-guided....pdf: 387218 bytes, checksum: 3e5d59f868cf7e153f1aa904be8b2251 (MD5)Made available in DSpace on 2017-08-16T13:45:57Z (GMT). No. of bitstreams: 1 Larocca TF Image-guided....pdf: 387218 bytes, checksum: 3e5d59f868cf7e153f1aa904be8b2251 (MD5) Previous issue date: 2017Brazilian Development Bank (BNDES).Hospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Hospital São Rafael. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Hospital São Rafael. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / National Institute of Science andTechnology for Regenerative Medicine. Rio de Janeiro, RJ, BrazilHospital São Rafael. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / University of Bahia. Faculty of Pharmacy. Salvador, BA, BrazilHospital São Rafael. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Hospital São Rafael. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, BrazilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, BrazilHospital São Rafael. Salvador, BA, BrasilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / National Institute of Science andTechnology for Regenerative Medicine. Rio de Janeiro, RJ, BrazilHospital São Rafael. Center for Biotechnology and Cell Therapy. Salvador, BA, Brazil / National Institute of Science andTechnology for Regenerative Medicine. Rio de Janeiro, RJ, BrazilThe potential of cell therapies to improve neurological function in subjects with spinal cord injury (SCI) is currently under investigation. In this context, the choice of cell type, dose, route and administration regimen are key factors. Mesenchymal stromal cells (MSCs) can be easily obtained, expanded and are suitable for autologous transplantation. Here we conducted a pilot study that evaluated safety, feasibility and potential efficacy of intralesional MSCs transplantation performed through image-guided percutaneous injection, in subjects with chronic complete SCI. Methods. Five subjects with chronic traumatic SCI (>6 months), at thoracic level, classified as American Spinal Cord Injury Association impairment scale (AIS) grade A, complete injury, were included. Somatosensory evoked potentials (SSEP), spinal magnetic resonance imaging (MRI) and urodynamics were assessed before and after treatment. Autologous MSCs were injected directly into the lesion site through percutaneous injection guided by computerized tomography (CT). Results. Tomography-guided percutaneous cell transplantation was a safe procedure without adverse effects. All subjects displayed improvements in spinal cord independence measure (SCIM) scores and functional independence measure (FIM), mainly due to improvements in bowel movements and regularity. Three subjects showed improved sensitivity to tactile stimulation.Two subjects improved AIS grade to B, incomplete injury, although this was sustained in only one of them during the study follow-up. Conclusion. Autologous bone marrow MSC transplantation, performed through CT-guided percutaneous injection, was shown to be safe and feasible. Further studies are required to demonstrate efficacy of this therapeutic scheme

Neotropical xenarthrans: a dataset of occurrence of xenarthran species in the Neotropics.

International audienceXenarthrans—anteaters, sloths, and armadillos—have essential functions forecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosys-tem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts withdomestic dogs, these species have been threatened locally, regionally, or even across their fulldistribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths.Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae(3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data onDasypus pilo-sus(Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized,but new genetic studies have revealed that the group is represented by seven species. In thisdata paper, we compiled a total of 42,528 records of 31 species, represented by occurrence andquantitative data, totaling 24,847 unique georeferenced records. The geographic range is fromthe southern United States, Mexico, and Caribbean countries at the northern portion of theNeotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regardinganteaters,Myrmecophaga tridactylahas the most records (n=5,941), andCyclopessp. havethe fewest (n=240). The armadillo species with the most data isDasypus novemcinctus(n=11,588), and the fewest data are recorded forCalyptophractus retusus(n=33). Withregard to sloth species,Bradypus variegatushas the most records (n=962), andBradypus pyg-maeushas the fewest (n=12). Our main objective with Neotropical Xenarthrans is to makeoccurrence and quantitative data available to facilitate more ecological research, particularly ifwe integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, andNeotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure,habitat loss, fragmentation effects, species invasion, and climate change effects will be possiblewith the Neotropical Xenarthrans data set. Please cite this data paper when using its data inpublications. We also request that researchers and teachers inform us of how they are usingthese data

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data