Influência de diferentes dietas com alto teor de concentrados sobre parâmetros ruminais, bioquímicos e urinários de ovinos

Oito ovinos adultos da raça Santa Inês receberam dieta controle (C) (80 % de feno de coast-cross e 20 % de ração comercial) e em seguida foram submetidos a quadrado latino com dietas contendo 30% desse feno e 70% dos concentrados: polpa cítrica peletizada (PCP); polpa cítrica farelada (PCF); fubá de milho (FM) e farelo de trigo (FT). Após 21 d de adaptação às dietas foi realizada monitoração visual por 24 h. No dia subseqüente à observação, na 3ª hora após a alimentação foram coletadas amostras de conteúdo ruminal, urina e sangue. No conteúdo ruminal foram determinados o pH, nas amostras de urina foram feitas análises de pH, uréia, fósforo, creatinina e exame de sedimento, enquanto que no sangue foram feitas análises hemogasométricas, e determinações séricas de uréia, fósforo e creatinina e calculado o índice de excreção urinária [IEUP] e a taxa de excreção fracional [TEFP] do fósforo. Os dados foram avaliados por análise de variância e Teste Tukey ou Mann-Whitney. Tanto a PCP como a PCF estimularam significativamente a ruminação, semelhante ao grupo controle, e com maior tempo que o FM. Maiores concentrações de P sérico, IEUP e TEFP foram encontrados na dieta FT. Quanto maiores os teores de P sérico maior a excreção de P na urina (R2 = 0,61). Quanto maior o tempo devotado à ruminação menor foi o fósforo sanguíneo (R2 = 0,39; P < 0,001). A maior ruminação diminuiu os teores de P sérico e sua excreção urinária, diminuindo a predisposição à urolitíase em ovinos

Influência de diferentes dietas com alto teor de concentrados sobre parâmetros ruminais, bioquímicos e urinários de ovinos

Oito ovinos adultos da raça Santa Inês receberam dieta controle (C) (80 % de feno de coast-cross e 20 % de ração comercial) e em seguida foram submetidos a quadrado latino com dietas contendo 30% desse feno e 70% dos concentrados: polpa cítrica peletizada (PCP); polpa cítrica farelada (PCF); fubá de milho (FM) e farelo de trigo (FT). Após 21 d de adaptação às dietas foi realizada monitoração visual por 24 h. No dia subseqüente à observação, na 3ª hora após a alimentação foram coletadas amostras de conteúdo ruminal, urina e sangue. No conteúdo ruminal foram determinados o pH, nas amostras de urina foram feitas análises de pH, uréia, fósforo, creatinina e exame de sedimento, enquanto que no sangue foram feitas análises hemogasométricas, e determinações séricas de uréia, fósforo e creatinina e calculado o índice de excreção urinária [IEUP] e a taxa de excreção fracional [TEFP] do fósforo. Os dados foram avaliados por análise de variância e Teste Tukey ou Mann-Whitney. Tanto a PCP como a PCF estimularam significativamente a ruminação, semelhante ao grupo controle, e com maior tempo que o FM. Maiores concentrações de P sérico, IEUP e TEFP foram encontrados na dieta FT. Quanto maiores os teores de P sérico maior a excreção de P na urina (R2 = 0,61). Quanto maior o tempo devotado à ruminação menor foi o fósforo sanguíneo (R2 = 0,39; P &lt; 0,001). A maior ruminação diminuiu os teores de P sérico e sua excreção urinária, diminuindo a predisposição à urolitíase em ovinos

Prevention of acute ruminal lactic acidosis in sheep by probiotic or monensin supplementation: clinical aspects

The aim of this study was to evaluate the effects of two additives (probiotic and monensin) over clinical parameters of sheep submitted to acute ruminal lactic acidosis (ARLA). Eighteen sheeps were divided into three groups of six animals each as follows: probiotic group, supplemented with 4×109 CFU/animal/day of Saccharomyces cerevisiae; monensin group, supplemented with 33 mg of monensin sodium per kg of diet; and control group, without any supplementation. After 30 days of diet (75% of Coast-cross hay and 25% concentrate with 14% of crude protein) and additive intake, ARLA was induced in the all animals by intraruminal administration of 15g of sucrose per kilogram (kg) of body weight. Complete physical examinations to assess the vital signs of the animals were conducted at the following times: baseline (T0), six (T6h), 12 (T12h), 18 (T18h), 24 (T24h), 36 (T36h), and 48 (T48h) hours after ARLA induction. At those times, blood samples were obtained to determine the plasma volume deficit (PVD) and ruminal content for pH measurement. All animals experienced clinical signs of ARLA with ruminal pH lower than 4.9 at T24h. The heart rate and PVD were lower (P < 0.05) in the probiotic group at T36h. Compared to the control and monensin groups, the probiotic group experienced milder ARLA characterized by lower degrees of dehydration and fewer clinical symptoms

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