Feedback and Trigger of Household Decision-Making to Ecological Protection Policies in Sanjiangyuan National Park

Ignoring the responses of local households to ecological protection policies can not only seriously limit sustainable development of the alpine grassland ecosystem, but also not improve livelihood on the Qinghai-Tibetan Plateau (QTP). It is of vital importance to clearly understand coupling feedback and trigger between household decision-making of local herdsmen with the implementation of ecological protection policies. We selected Sanjiangyuan National Park (SNP) as the study area which was in the hinterland of the QTP and the first national park in China. We used the global rangeland (G-Range) model to simulate alpine grassland changes and DEcisions under Conditions of Uncertainty by Modeled Agents (DECUMA) model to identify household decision-making of local herdsmen. Results showed that: (1) distribution of livestock density was basically consistent with the distribution of habitat suitability of local households in the SNP; (2) more than half of the uneducated households (52 and 70%) opposed the eco-compensation and eco-migration policies; (3) most of the households (53.7%) never traded livestock for maintaining their livelihood; and (4) When local households owed 65,000 yuan (≈10,000 dollars) in debts, as the critical value (trigger), they traded livestock to support their livelihood. We suggest that feedback and trigger of household decision-making should be fully considered by managers of national park and policymakers of local governments in planning ecological protection policies to maintain sustainable development of alpine grassland, which is of practical significance to long-term conservation and sustainable utilization of natural resources in the SNP.

The effect of livestock density on Trypanosoma brucei gambiense and T. b. rhodesiense : a causal inference-based approach

Domestic and wild animals are important reservoirs of the rhodesiense form of human African trypanosomiasis (rHAT), however quantification of this effect offers utility for deploying non-medical control activities, and anticipating their success when wildlife are excluded. Further, the uncertain role of animal reservoirs—particularly pigs—threatens elimination of transmission (EOT) targets set for the gambiense form (gHAT). Using a new time series of high-resolution cattle and pig density maps, HAT surveillance data collated by the WHO Atlas of HAT, and methods drawn from causal inference and spatial epidemiology, we conducted a retrospective ecological cohort study in Uganda, Malawi, Democratic Republic of Congo (DRC) and South Sudan to estimate the effect of cattle and pig density on HAT risk.

Estimating The Distribution of Livestock In Space And Time: A Time-Series Contribution To Livestock Density Mapping

More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock thus have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo (DRC), and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.

High-Resolution Gridded Livestock Projection for Western China Based on Machine Learning

Accurate high-resolution gridded livestock distribution data are of great significance for the rational utilization of grassland resources, environmental impact assessment, and the sustainable development of animal husbandry. Traditional livestock distribution data are collected at the administrative unit level, which does not provide a sufficiently detailed geographical description of livestock distribution. In this study, we proposed a scheme by integrating high-resolution gridded geographic data and livestock statistics through machine learning regression models to spatially disaggregate the livestock statistics data into 1 km × 1 km spatial resolution. Three machine learning models, including support vector machine (SVM), random forest (RF), and deep neural network (DNN), were constructed to represent the complex nonlinear relationship between various environmental factors (e.g., land use practice, topography, climate, and socioeconomic factors) and livestock density. By applying the proposed method, we generated a set of 1 km × 1 km spatial distribution maps of cattle and sheep for western China from 2000 to 2015 at five-year intervals. Our projected cattle and sheep distribution maps reveal the spatial heterogeneity structures and change trend of livestock distribution at the grid level from 2000 to 2015. Compared with the traditional census livestock density, the gridded livestock distribution based on DNN has the highest accuracy, with the determinant coefficient (R2) of 0.75, root mean square error (RMSE) of 9.82 heads/km2 for cattle, and the R2 of 0.73, RMSE of 31.38 heads/km2 for sheep. The accuracy of the RF is slightly lower than the DNN but higher than the SVM. The projection accuracy of the three machine learning models is superior to those of the published Gridded Livestock of the World (GLW) datasets. Consequently, deep learning has the potential to be an effective tool for high-resolution gridded livestock projection by combining geographic and census data.

Snow Leopard Dietary Preferences and Livestock Predation Revealed by Fecal DNA Metabarcoding: No Evidence for Apparent Competition Between Wild and Domestic Prey

Accurate assessments of the patterns and drivers of livestock depredation by wild carnivores are vital for designing effective mitigation strategies to reduce human-wildlife conflict. Snow leopard’s (Panthera uncia) range extensively overlaps pastoralist land-use and livestock predation there is widely reported, but the ecological determinants of livestock consumption by snow leopards remain obscure. We investigated snow leopard dietary habits at seven sites across the Sanjiangyuan region of the Qinghai–Tibetan Plateau (QTP), an area central to the species’ global range. Snow leopard abundance, wild prey composition, and livestock density varied among those sites, thus allowing us to test the effects of various factors on snow leopard diet and livestock predation. Using DNA metabarcoding, we obtained highly resolved dietary data from 351 genetically verified snow leopard fecal samples. We then analyzed the prey preferences of snow leopards and examined ecological factors related to their livestock consumption. Across the sites, snow leopard prey was composed mainly of wild ungulates (mean = 81.5% of dietary sequences), particularly bharal (Pseudois nayaur), and supplemented with livestock (7.62%) and smaller mammals (marmots, pikas, mice; 10.7%). Snow leopards showed a strong preference for bharal, relative to livestock, based on their densities. Interestingly, both proportional and total livestock consumption by snow leopards increased linearly with local livestock biomass, but not with livestock density. That, together with a slight negative relationship with bharal density, supports apparent facilitation between wild and domestic prey. We also found a significant positive correlation between population densities of snow leopard and bharal, yet those densities showed slight negative relationships with livestock density. Our results highlight the importance of sufficient wild ungulate abundance to the conservation of viable snow leopard populations. Additionally, livestock protection is critically needed to reduce losses to snow leopard depredation, especially where local livestock abundances are high.

SIFAT KUALITATIF DAN KUANTITATIF SAPI BALI BETINA

The purpose of this study was to determine the qualitative and quantitative characteristics of female Bali cattle in Atinggola District, North Gorontalo Regency, Gorontalo Province. This study used a field experiment method in the form of direct observation and measurement of female Bali cattle based on the total population and livestock density in each village in Atinggola District. A total of 122 female Bali cattle aged 2-4 years were used as samples for observation and measurement. Bali cattle aged 2 3 years have a white pattern on the butt (butt mirror) with clear boundaries of 74.64% and 25.33% without clear boundaries. The white pattern on the feet (socks) is clearly visible with the skin color on the legs 73.33% and 26.67% there is no dividing line between the body color and the white pattern on the legs (socks). Bali cattle aged 3 4 years have a white pattern on the butt (butt mirror) which is clearly demarcated by 63.83% and 36.17% without clear boundaries. The white pattern on the feet (socks) is well defined with body hair color 68.09% and 31.91% there is no clear boundary between body color and pattern color. Female Bali cattle aged 2 3 aged 5.81-25.15, the average body length, chest circumference, and height were 93.91±9.29, 148.78±20.40 and 106, respectively, 10±6.16. Bali cattle aged 34 have a diversity of body size of 5.29-35.17%. The average values of chest circumference, body length, and height were 98.73±10.31, 144.22±14.62, 144.22±14.62, respectively. Female Bali cattle from Atinggola District, North Gorontalo Regency, Gorontalo have qualitative characteristics that do not deviate from native Indonesian Bali cattle. Body size diversity of female Bali cattle aged 2 3 was 5.81-25.15, while Bali cattle aged 3 4 had body size diversity of 5.29-35.17%

Reconciling biome-wide conservation of an apex carnivore with land-use economics in the increasingly threatened Pantanal wetlands

Conservation of carnivores involves finding solutions to minimize habitat loss and human-wildlife conflict. Understanding the nature of land-use economics can allow us to mitigate both threats. In the Pantanal, the two main economic activities are cattle ranching and ecotourism, each of which directly and indirectly affect the persistence of jaguars (Panthera onca). To understand how the geography of these economic activities is related to jaguar populations, we developed a jaguar distribution model (JDM), livestock density model, and ecotourism lodge density model for the Pantanal. Due to the recent wildfires within the Pantanal, we also assess the impact of burnt areas that are suitable for jaguars, cattle ranching, and tourism. Our JDM indicate that 64% of the Pantanal holds suitable habitat for jaguars. However, jaguar habitat suitability was positively correlated with ecotourism, but negatively correlated with areas most suitable for intensive cattle-ranching. This demonstrates a biome-wide scenario compatible with jaguar conservation. Of particular concern, recent wildfires overlap most suitable areas for jaguars. If wildfires become increasingly frequent, this would represent a serious threat to jaguars and many other wildlife populations. We emphasize the global importance of the Pantanal wetland ecoregion as a key stronghold for long-term jaguar conservation.

Analisis Potensi Wilayah untuk Pengembangan Ternak Ruminansia di Kabupaten Lampung Tengah Area potential analysis is required as the right direction for development. Aim This study is to identify areas of the development of ruminant livestock in the Centr

Area potential analysis is required as the right direction for development. Aim This study is to identify areas of the development of ruminant livestock in the Central Lampung Regency. The method used is the analysis of livestock density and Location quotient. Data that used is secondary data from Central Lampung In Lift Year 2020/2021. The method used is descriptive-analytical. The result showed that Selagai Lingga sub-district is the most priority location for the development of ruminants. Following Sendang Agung and Trimurjo sub-districts. Anak Tuha and Bumi Ratu Nuhan are the third priority. Based on the Location Quotient (LQ) analysis, Selagai Lingga Sub-District is categorized as a basic sector for goats and sheep, Sendang Agung for Buffalo and sheep, Anak Tuha and Bumi Ratu Nuban are the basic sector for buffalo, goat, and sheep. Seputih Agung is the basic sector for Cattle.

Modelling bluetongue risk in Kazakhstan

Background Bluetongue is a serious disease of ruminants caused by the bluetongue virus (BTV). BTV is transmitted by biting midges (Culicoides spp.). Serological evidence from livestock and the presence of at least one competent vector species of Culicoides suggests that transmission of BTV is possible and may have occurred in Kazakhstan. Methods We estimated the risk of transmission using a mathematical model of the reproduction number R0 for bluetongue. This model depends on livestock density and climatic factors which affect vector density. Data on climate and livestock numbers from the 2466 local communities were used. This, together with previously published model parameters, was used to estimate R0 for each month of the year. We plotted the results on isopleth maps of Kazakhstan using interpolation to smooth the irregular data. We also mapped the estimated proportion of the population requiring vaccination to prevent outbreaks of bluetongue. Results The results suggest that transmission of bluetongue in Kazakhstan is not possible in the winter from October to March. Assuming there are vector-competent species of Culicoides endemic in Kazakhstan, then low levels of risk first appear in the south of Kazakhstan in April before spreading north and intensifying, reaching maximum levels in northern Kazakhstan in July. The risk declined in September and had disappeared by October. Conclusion These results should aid in surveillance efforts for the detection and control of bluetongue in Kazakhstan by indicating where and when outbreaks of bluetongue are most likely to occur. The results also indicate where vaccination efforts should be focussed to prevent outbreaks of disease. Graphical abstract

Reconciling Biome-Wide Conservation of an Apex Carnivore with Land-Use Economics: Jaguars (Panthera Onca) in the Increasingly Threatened Pantanal Wetlands

Conservation of carnivores involves finding solutions to minimize habitat loss and human-wildlife conflicts, and understanding the nature of land-use economics can allow us to mitigate both threats. In the Pantanal, the two main economic activities are cattle ranching and ecotourism, each of which directly and indirectly affect the persistence of jaguars (Panthera onca). To understand how the geography of these economic activities is related to jaguar populations, we developed a jaguar distribution model (JDM), livestock density model, and ecotourism lodge density model for the Pantanal. Due to the recent wildfires within the Pantanal, we also assess the impact of burnt areas that are suitable for jaguars, cattle ranching, and tourism. Our JDM indicate that 64% of the Pantanal holds suitable habitat for jaguars. However, jaguar habitat suitability was positively correlated with ecotourism, but negatively correlated with areas most suitable for intensive cattle-ranching. This demonstrates a biome-wide scenario compatible with jaguar conservation. Of particular concern, recent wildfires overlap most suitable areas for jaguars. If wildfires become increasingly frequent, this would represent a serious threat to jaguars and many other wildlife populations. We emphasize the global importance of the Pantanal wetland ecoregion as a key stronghold for long-term jaguar conservation.