Una opinión sobre el estado actual y las perspectivas de la ganadería bovina en el sudoeste bonaerense

La presente exposición no tiene un carácter estrictamente técnico sino que trata de presentar las opiniones condensadas de varios actores que han tenido desempeño profesional en producción animal en distintas zonas que componen el sudoeste bonaerense (SOB). Con las entrevistas mantenidas con todos ellos se resumió una opinión sobre la evolución que tuvo la ganadería luego de los aportes en conocimientos en sanidad., genética y nutrición animal difundidos en los últimos de 30-40 años. Asimismo se evaluaron perspectivas hacia el futuro de la actividad en la región.Academia Nacional de Agronomía y Veterinari

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

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

Model collaboration for the improved assessment of biomass supply, demand, and impacts

Existing assessments of biomass supply and demand and their impacts face various types of limitations and uncertainties, partly due to the type of tools and methods applied (e.g., partial representation of sectors, lack of geographical details, and aggregated representation of technologies involved). Improved collaboration between existing modeling approaches may provide new, more comprehensive insights, especially into issues that involve multiple economic sectors, different temporal and spatial scales, or various impact categories. Model collaboration consists of aligning and harmonizing input data and scenarios, model comparison and/or model linkage. Improved collaboration between existing modeling approaches can help assess (i) the causes of differences and similarities in model output, which is important for interpreting the results for policy-making and (ii) the linkages, feedbacks, and trade-offs between different systems and impacts (e.g., economic and natural), which is key to a more comprehensive understanding of the impacts of biomass supply and demand. But, full consistency or integration in assumptions, structure, solution algorithms, dynamics and feedbacks can be difficult to achieve. And, if it is done, it frequently implies a trade-off in terms of resolution (spatial, temporal, and structural) and/or computation. Three key research areas are selected to illustrate how model collaboration can provide additional ways for tackling some of the shortcomings and uncertainties in the assessment of biomass supply and demand and their impacts. These research areas are livestock production, agricultural residues, and greenhouse gas emissions from land-use change. Describing how model collaboration might look like in these examples, we show how improved model collaboration can strengthen our ability to project biomass supply, demand, and impacts. This in turn can aid in improving the information for policy-makers and in taking better-informed decisions

Impact of genetic ancestry and sociodemographic status on the clinical expression of systemic lupus erythematosus in American Indian-European populations

Objective American Indian-Europeans, Asians, and African Americans have an excess morbidity from systemic lupus erythematosus (SLE) and a higher prevalence of lupus nephritis than do Caucasians. The aim of this study was to analyze the relationship between genetic ancestry and sociodemographic characteristics and clinical features in a large cohort of American Indian-European SLE patients. Methods A total of 2,116 SLE patients of American Indian-European origin and 4,001 SLE patients of European descent for whom we had clinical data were included in the study. Genotyping of 253 continental ancestry-informative markers was performed on the Illumina platform. Structure and Admixture software were used to determine genetic ancestry proportions of each individual. Logistic regression was used to test the association between genetic ancestry and sociodemographic and clinical characteristics. Odds ratios (ORs) were calculated with 95% confidence intervals (95% CIs). Results The average American Indian genetic ancestry of 2,116 SLE patients was 40.7%. American Indian genetic ancestry conferred increased risks of renal involvement (P less than 0.0001, OR 3.50 [95% CI 2.63- 4.63]) and early age at onset (P less than 0.0001). American Indian ancestry protected against photosensitivity (P less than 0.0001, OR 0.58 [95% CI 0.44-0.76]), oral ulcers (P less than 0.0001, OR 0.55 [95% CI 0.42-0.72]), and serositis (P less than 0.0001, OR 0.56 [95% CI 0.41-0.75]) after adjustment for age, sex, and age at onset. However, age and sex had stronger effects than genetic ancestry on malar rash, discoid rash, arthritis, and neurologic involvement. Conclusion In general, American Indian genetic ancestry correlates with lower sociodemographic status and increases the risk of developing renal involvement and SLE at an earlier age. Copyright © 2012 by the American College of Rheumatology

Impact of genetic ancestry and sociodemographic status on the clinical expression of systemic lupus erythematosus in American Indian-European populations

Objective American Indian-Europeans, Asians, and African Americans have an excess morbidity from systemic lupus erythematosus (SLE) and a higher prevalence of lupus nephritis than do Caucasians. The aim of this study was to analyze the relationship between genetic ancestry and sociodemographic characteristics and clinical features in a large cohort of American Indian-European SLE patients. Methods A total of 2,116 SLE patients of American Indian-European origin and 4,001 SLE patients of European descent for whom we had clinical data were included in the study. Genotyping of 253 continental ancestry-informative markers was performed on the Illumina platform. Structure and Admixture software were used to determine genetic ancestry proportions of each individual. Logistic regression was used to test the association between genetic ancestry and sociodemographic and clinical characteristics. Odds ratios (ORs) were calculated with 95% confidence intervals (95% CIs). Results The average American Indian genetic ancestry of 2,116 SLE patients was 40.7%. American Indian genetic ancestry conferred increased risks of renal involvement (P less than 0.0001, OR 3.50 [95% CI 2.63- 4.63]) and early age at onset (P less than 0.0001). American Indian ancestry protected against photosensitivity (P less than 0.0001, OR 0.58 [95% CI 0.44-0.76]), oral ulcers (P less than 0.0001, OR 0.55 [95% CI 0.42-0.72]), and serositis (P less than 0.0001, OR 0.56 [95% CI 0.41-0.75]) after adjustment for age, sex, and age at onset. However, age and sex had stronger effects than genetic ancestry on malar rash, discoid rash, arthritis, and neurologic involvement. Conclusion In general, American Indian genetic ancestry correlates with lower sociodemographic status and increases the risk of developing renal involvement and SLE at an earlier age. Copyright © 2012 by the American College of Rheumatology

Impact of genetic ancestry and sociodemographic status on the clinical expression of systemic lupus erythematosus in American Indian-European populations

Artículo de publicación ISIObjective American Indian-Europeans, Asians, and African Americans have an excess morbidity from systemic lupus erythematosus (SLE) and a higher prevalence of lupus nephritis than do Caucasians. The aim of this study was to analyze the relationship between genetic ancestry and sociodemographic characteristics and clinical features in a large cohort of American Indian-European SLE patients. Methods A total of 2,116 SLE patients of American Indian-European origin and 4,001 SLE patients of European descent for whom we had clinical data were included in the study. Genotyping of 253 continental ancestry-informative markers was performed on the Illumina platform. Structure and Admixture software were used to determine genetic ancestry proportions of each individual. Logistic regression was used to test the association between genetic ancestry and sociodemographic and clinical characteristics. Odds ratios (ORs) were calculated with 95% confidence intervals (95% CIs). Results The average American Indian genetic ancestry of 2,116 SLE patients was 40.7%. American Indian genetic ancestry conferred increased risks of renal involvement (P < 0.0001, OR 3.50 [95% CI 2.63- 4.63]) and early age at onset (P < 0.0001). American Indian ancestry protected against photosensitivity (P < 0.0001, OR 0.58 [95% CI 0.44-0.76]), oral ulcers (P < 0.0001, OR 0.55 [95% CI 0.42-0.72]), and serositis (P < 0.0001, OR 0.56 [95% CI 0.41-0.75]) after adjustment for age, sex, and age at onset. However, age and sex had stronger effects than genetic ancestry on malar rash, discoid rash, arthritis, and neurologic involvement. Conclusion In general, American Indian genetic ancestry correlates with lower sociodemographic status and increases the risk of developing renal involvement and SLE at an earlier age.NIH P01-AR-49084 P60-AR-053308 R01-AR-052300 R21-AI-070304 K24-AR-002138 P60 2-AR-30692 UL1-RR-025741 P30-AR-053483 P30-RR-031152 P01-AI-083194 AR-43727 American Recovery and Reinvestment Act grant AR-058621 Centers of Biomedical Research Excellence (COBRE) grant 8 P20-GM-103456-09 National Center for Research Resources UL1-RR-025005 Alliance for Lupus Research Kirkland Scholar Award Federico Wilhelm Agricola Foundatio