MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info: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 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

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

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

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

Alterations in evoked otoacoustic emissions by the use of meglumine antimoniate in American tegumentary leishmaniasis patients

Submitted by Janaína Nascimento ([email protected]) on 2019-07-19T13:50:23Z No. of bitstreams: 1 ve_Bezerra_Débora_etal_INI_2017.pdf: 1274540 bytes, checksum: ea37b81d1d5c8c29cc86661f270e23ef (MD5)Approved for entry into archive by Janaína Nascimento ([email protected]) on 2019-07-19T14:16:29Z (GMT) No. of bitstreams: 1 ve_Bezerra_Débora_etal_INI_2017.pdf: 1274540 bytes, checksum: ea37b81d1d5c8c29cc86661f270e23ef (MD5)Made available in DSpace on 2019-07-19T14:16:29Z (GMT). No. of bitstreams: 1 ve_Bezerra_Débora_etal_INI_2017.pdf: 1274540 bytes, checksum: ea37b81d1d5c8c29cc86661f270e23ef (MD5) Previous issue date: 2017Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Federal University of Rio de Janeiro. Faculty of Medicine. Department of Otorhinolaryngology and Ophthalmology. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Federal University of Rio de Janeiro. Faculty of Medicine. Department of Otorhinolaryngology and Ophthalmology. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Federal University of Rio de Janeiro. Faculty of Medicine. Department of Otorhinolaryngology and Ophthalmology. Rio de Janeiro, RJ, Brazil.Federal University of the State of the Rio de Janeiro. Faculty of Medicine. Department of Otorhinolaryngology. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil / Brazilian National Council for Scientific and Technological Development. Brasilia, DF, Brazil / Carlos Chagas Filho Foundation for Research Support of the state of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil / Federal University of Rio de Janeiro. Faculty of Medicine. Department of Otorhinolaryngology and Ophthalmology. Rio de Janeiro, RJ, Brazil / Carlos Chagas Filho Foundation for Research Support of the state of Rio de Janeiro. Rio de Janeiro, RJ, Brazil / New University of Lisbon. Hygiene and Tropical Medicine Institute. Lisbon, Portugal.Tegumentary Leishmaniasis (TL) is a neglected, non-contagious, infectious disease, caused by different protozoa species of the Leishmania genus that affects skin and mucous membranes. Meglumine Antimoniate (MA), the first drug of choice for TL treatment in Brazil, has already been associated with cochlear toxicity, which is defined as damages of the cochlea caused by exposure to chemical substances, resulting in reversible or irreversible hearing loss. Auditory monitoring for cochlear toxicity aims at the early detection of auditory disorders, enabling, when possible, hearing to be preserved or an early auditory rehabilitation. Although otoacoustic emissions (OAEs) are used in this monitoring, there is no consensus on the criteria that define cochlear toxicity by this examination. The objective of this study was to describe the characteristics of the OAEs in cochlear toxicity monitoring in TL patients using MA

Auditory monitoring with distortion product evoked otoacoustic emissions before treatment, at the end of treatment and 1 and 2 months after the end of treatment of meglumine antimoniate in american tegumentary leishmaniasis patients.

<p>* Higher number of alterations in distortion product evoked otoacoustic emissions at the end of treatment than before treatment (p = 0.039).</p

Auditory monitoring with transient evoked otoacoustic emissions before treatment, at the end of treatment and 1 and 2 months after the end of treatment of meglumine antimoniate in american tegumentary leishmaniasis patients.

<p>Auditory monitoring with transient evoked otoacoustic emissions before treatment, at the end of treatment and 1 and 2 months after the end of treatment of meglumine antimoniate in american tegumentary leishmaniasis patients.</p

Comparison between presence and absence of alterations in distortion product evoked otoacoustic emissions (DPEOAE) before beginning treatment with Meglumine Antimoniate (MA) of 64 ears of 32 patients with tegumentary leishmaniasis.

<p>Evandro Chagas National Institute of Infectious Diseases–Oswaldo Cruz Foundation, 2016.</p