Livestock Distribution Research Articles

Assessing The Extent Of Habitat Overlap And Resource Partitioning Between Ibex And Livestock In Khyber valley Pakistan

Ibex and livestock distribution and habitat preferences were assessed using ecological niche factor analysis (ENFA). The study area was divided into 45 grid cells of 500 x 500 m pixels. Ibex and livestock were documented to occupy 30.61% and 26.5% of the study area, respectively, from June to November. Male and female ibex showed significant sexual segregation during this period. From November to May, male ibex occupied 32.6% of the study area and female ibex 34%. Livestock occupied 19% of the study area from June to September and 14.2% from September to May. The ENFA results indicated that both ibex and livestock show selective habitat preferences but are selecting for the same resources. The first two principal components (PCs) explained 49.3% and 17.88% of the variation in the data, respectively. The first PC was related to distance to settlements, distance to rivers, distance to roads, and rangelands. The second PC was related to rangelands and snow covers. The biplot of ENFA differentiated available habitats from habitat used (by ibex/livestock) through shades of grey, where light grey areas correspond to all the available habitat and dark grey area represented the used area (ecological niche of the animal). The ENFA plot indicated that though ibex and livestock have selective approach towards habitat usage, but selecting for the same resources

Desa Tangguh Penyakit Mulut Dan Kuku (PMK) Berbasis Peternakan Rakyat

Foot and Mouth Disease (FMD) in Bukek village is an alarming condition considering that Bukek village is a strategic area for the distribution of livestock between regions in Tlanakan district. The need for treatment from this point in the prevention of the spread and treatment of sick livestock. The output of this service is expected to increase the knowledge of breeders, control FMD, and the formation of an independent PMK task force in Bukek village. The methods used in service activities include; cattle breeding counseling, supplementary feeding (UMB), vitamin injection and livestock stimulation and the establishment of a FMD task force. Monitoring and evaluation are carried out to measure the success of activities. As a result of the service activities, the people of Bukek village were very enthusiastic about participating in counseling activities and understanding the pattern of cattle breeding, prevention and treatment of FMD. The provision of UMB and herbal booster FMD is given to farmers as many livestock as they have between 1-2ltr / livestock. The provision of vitamins and vaccination of livestock was carried out with relevant officials covering the ernak population in Bukek village. Vaccination data recording was submitted to the relevant service, assisted by a veterinarian from Madura University. The establishment of the PMK task force in the village was ratified by a decree of the village head for each hamlet there is representation, who has the task and obligation to record and report livestock indicated to be affected by FMD. Babinsa and Bhabinkantibmas also help in sanitary spraying of the pen using disinfectants periodically.

Aggravation of nitrogen losses driven by agriculture and livestock farming development on the Qinghai-Tibet Plateau

Nitrogen (N) losses from crop-livestock production is a major threat to the environment and human health at regional, national and global scales. A comprehensive understanding of the sources, spatiotemporal distribution and drivers of N losses is of great significance for mitigating its negative impacts and promoting N sustainable management. Here, we used the county-scale N flow model to quantitatively analyze the N losses and their driving forces of crop-livestock production on the Qinghai-Tibet Plateau (QTP). Between 2000 and 2018, the total N losses increased for more than 79% of counties on the QTP. The hotspot areas accounted for over 80% of total N losses, expanding from the east and south to the north and west of the QTP. NH3 was the main source of atmospheric N losses (over 80%) while the direct discharge of manure was the main source of water N losses. Structural equation modeling (SEM) showed that chemical fertilizer caused the largest driving effect on atmospheric N losses, and the total output value of agriculture and forestry was the main driver of water N losses. Uneven distribution of crop production and livestock contributed to the aggravation of N losses. Over 70% of counties had grater manure N excretion than crops could take up, and large proportion of manure could not be returned to the field. More than 90% of the counties used grater amount of chemical fertilizer N than crops could take up, indicating that livestock manure has not yet fully replaced chemical fertilizer N. The results provide effective guidance and support for N utilization and management of livestock in agricultural and pastoral areas.

Prioritizing livestock grazing right buyouts to safeguard Asiatic cheetahs from extinction

AbstractLivestock husbandry exerts major pressures on wildlife across the world. Large carnivores are particularly at risk because they are often killed by pastoralists as a preventive or precautionary response to livestock depredation. Minimizing the overlap between pastures and carnivore habitat can thus be a conservation strategy, but it remains often unclear which pastures should be targeted to maximize conservation benefits given a limited budget. We addressed this question for the last viable population of the Asiatic cheetah (Acinonyx jubatus venaticus) in northeastern Iran. By combining species distribution modeling with a spatial prioritization framework, we aimed to identify where grazing right buyouts should take place to reduce cheetah killing by herders and their dogs. We assessed the Asiatic cheetah habitat using species distribution models, highlighting large, contiguous areas that overlap with livestock pastures (5792 km2, equaling 72% of the total predicted suitable habitat). Subsequently, we used data on the number and distribution of livestock (~47,000 animals in 80 pastures) and applied a spatial prioritization method to identify pastures for grazing right buyouts for a range of budget scenarios (US$100,000–600,000). Pastures selected had a high level of irreplaceability and were generally stable across budget scenarios. Our results provide a novel approach to minimize encounter rates between cheetah and livestock, and thus the mortality risk, for one of the world's most endangered felids and highlight the potential of spatial prioritization as a tool to devise urgent conservation actions.

Defining ecological and socially suitable habitat for the reintroduction of an apex predator

Reintroducing native carnivores risks creating conflict with people and consequently reducing support for coexistence and conservation efforts. Determining the interface between areas of ecological suitability and conflict risk can help enhance success of carnivore restoration, but this is often difficult because accurate data on risks and tolerance are lacking. Gray wolves ( Canis lupus ), a focus of reintroduction efforts in the US, require tolerance to persist in human-dominated landscapes but also catalyze societal-level conflicts throughout their global range. Via an unprecedented process to restore an apex predator, in November 2020, citizens in the state of Colorado, USA voted to reintroduce wolves to the state where they had been extirpated ~70 years prior. We leveraged voting records of over three million citizens to quantify and map an index of tolerance for wolves and combined it with spatially explicit data on livestock distributions and land ownership to create predictions of direct conflict risk between wolves and humans. Conflict risk was juxtaposed with estimates of wolf ecological suitability developed using seasonal prey densities along with environmental and anthropogenic features that influence wolf habitat use. Our social-ecological modeling approach predicted that ~56 % of the West Slope of Colorado contained ecologically suitable habitat and relatively low conflict risk. Our models also delineated possible conflict hotspots where ecological suitability and conflict risk converge, thus facilitating targeted proactive management. We demonstrate how voting patterns can provide unique, spatially explicit insight on tolerance that can be integrated with other information to help facilitate human-carnivore coexistence and carnivore restoration success.

Watershed-scale optimum livestock distribution and crop pattern planning constrained to the minimum nitrogen and phosphorus load in the runoff.

Sustainable crop and livestock planning encounter serious challenges when tasked with reducing the associated nutrient pollution entering the watershed environment. To overcome these challenges, approaches for specifying optimal crop pattern and livestock distribution to limit the pollution in the catchment are advised. In this research, a simulation-optimization approach is used in which the Soil and Water Assessment Tool (SWAT) is employed for simulating the complex soil-water-plant quantity and quality relations, and the Harmony Search (HS) algorithm linked with SWAT is used to discover the optimal crop pattern and distribution of livestock in the Ilam Dam basin, Iran. In the developed HS-SWAT model, the cultivation area and the number of livestock in SWAT's hydrologic response units (HRU) are the decision variables for maximizing the net benefit obtained from the crop's and livestock's productions, while the nitrate and phosphate calculated in the outflow of the basin are restrained to meet the allowable rates. Results show that the scattered livestock in the basin have a great impact on the generated pollution where about 90% of the nitrate entering the downstream reservoir is the consequence of animal waste. In the optimum state, by reduction of the cultivation area and the number of livestock across the watershed, the concentration of N and P in the surface runoff is reduced significantly to meet the allowable level. According to the results, the HS-SWAT model performance indicates its capability for solving watershed crop pattern and livestock planning problems.

A time-series approach to mapping livestock density using household survey data

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 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, 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.

Livestock Management on Grazing Field: A FANET Based Approach

In recent times, designated grazing areas/fields or routes for livestock grazing are usually defined. Hence, their herding activities’ success relies on data extracted from aerial photographs. As such, a direct and cost-effective way of monitoring livestock for perimeter coverage and in other natural situations is required. This paper presents a coverage solution involving multiple interacting unmanned aerial vehicles. The presented approach is built on a graph, with geographic coordinates set such that several Unmanned Aerial Vehicles (UAVs) can successfully cover the area. The maximum flying time determines the number of UAVs employed for coverage. The proposed solution is thought to solve some practical problems encountered during the execution of the task with actual UAVs. It is suitable for long-term monitoring of animal behavior under various weather conditions and observing the relationship between livestock distribution and available resources on a grazing field. The simulation was carried out using MATLAB and aerial images from Google Earth.

Identification of temporary livestock enclosures in Kenya from multi-temporal PlanetScope imagery

The use of night-time livestock enclosures, often referred to as “bomas”, “corrals”, or “kraals”, is a common practice across African rangelands. Bomas protect livestock from predation by wildlife and potential theft. Due to the concentration of animal faeces inside bomas, they not only become nutrient-rich patches that can add to biodiversity, but also hotspots for the emission of nitrous oxide (N2O), an important greenhouse gas, especially when animals are kept inside for long periods. To provide an accurate estimate of such emissions for wider landscapes, bomas need to be accounted for. Moreover, initial experiments indicated that more frequent shifts in the boma locations could help to reduce N2O emissions. This stresses the need for better understanding where bomas are located, their numbers, as well as when they are actively used. Given the recent advances in satellite technology, resulting in high-frequent spectral measurements at fine spatial resolution, solutions to address these needs are now within reach. This study is a first effort to map and monitor the appearance of bomas with the use of satellite image time series. Our main dataset was a dense times series of 3 m resolution PlanetScope multispectral imagery. In addition, a reference dataset of boma and non-boma locations was created using GPS-collar tracking data and 0.5 m resolution Pléiades imagery. The reduction of vegetation cover and increase of organic material following boma installation result in typical spectral changes when contrasted against its surroundings. Based on these spectral changes we devised an empirical approach to infer approximate boma installation dates from PlanetScope's near infrared (NIR) band and used our reference dataset for setting optimal parameter values. A NIR spatial difference index resulted in clear temporal patterns, which were more apparent during the wet season. At landscape scale our approach reveals clear spatio-temporal patterns of boma installation, which could not be revealed from less frequent sub-meter resolution imagery alone. While further improvements are possible, we show that small-sized (150–500 m2) temporary surface changes, such as those that occur when pastoralists use mobile bomas, can be detected with dense image time series like those offered by the PlanetScope constellation. In future, this could lead to better assessment of a) spatio-temporal livestock distribution, b) the contribution of bomas to N2O emissions and soil fertility at landscape scale, and c) the uptake of enclosure rotation practices at large spatial scales.

Multi-parallel structure and a generalized conceptual model of livestock track network

Striking networks of livestock tracks are commonplace in hilly rangelands throughout the world. Formed largely through biogenic processes, they transform micro-topography, soil properties, vegetation distribution, and forage behaviors of livestock, and have significant implications to hydrological and biogeochemical processes and livestock forage efficiency. The conventional conceptual model suggests that the network of livestock tracks is consisted of parallel and conjunctive tracks, with parallel tracks nearly parallel to the contour and connected by shorter, inclined conjunctive tracks. This conventional model of network of livestock tracks captures the most salient characteristics for some of the networks but not the full range of structural variations and possible mechanisms. We quantified goat track networks, which disconform to the conventional model, using a multi-parallel structure and proposed a generalized conceptual model of livestock track network. Livestock track networks consist of multiple groups of parallel tracks and the key properties of networks, scale and geometric complexity, are functions of animal body size as well as landscape heterogeneity. Network scale increases and geometric complexity decreases with body size, and geometric complexity increases with landscape heterogeneity. The generalized conceptual model can serve as a unifying framework for studies of various livestock track networks and potential mechanisms. It can also facilitate effective characterization of livestock track networks, monitoring of their structural changes, and assessment of policy implications to ecosystem services in hilly rangelands throughout the world.

Large-herbivore nemabiomes: patterns of parasite diversity and sharing.

Amidst global shifts in the distribution and abundance of wildlife and livestock, we have only a rudimentary understanding of ungulate parasite communities and parasite-sharing patterns. We used qPCR and DNA metabarcoding of fecal samples to characterize gastrointestinal nematode (Strongylida) community composition and sharing among 17 sympatric species of wild and domestic large mammalian herbivore in central Kenya. We tested a suite of hypothesis-driven predictions about the role of host traits and phylogenetic relatedness in describing parasite infections. Host species identity explained 27–53% of individual variation in parasite prevalence, richness, community composition and phylogenetic diversity. Host and parasite phylogenies were congruent, host gut morphology predicted parasite community composition and prevalence, and hosts with low evolutionary distinctiveness were centrally positioned in the parasite-sharing network. We found no evidence that host body size, social-group size or feeding height were correlated with parasite composition. Our results highlight the interwoven evolutionary and ecological histories of large herbivores and their gastrointestinal nematodes and suggest that host identity, phylogeny and gut architecture—a phylogenetically conserved trait related to parasite habitat—are the overriding influences on parasite communities. These findings have implications for wildlife management and conservation as wild herbivores are increasingly replaced by livestock.

Spatial Distribution and Habitat Selection of Sarda Cattle in a Silvopastoral Mediterranean Area.

Simple SummarySilvopastoral systems support multiple uses, such as cattle grazing, timber harvesting and the provision of many ecosystem services. The management of livestock movement patterns plays a pivotal role in the sustainable use of silvopastoral systems. Uneven livestock distribution can lead to over- and under-grazed areas, negatively affecting plant and animal diversity, as well as ecosystem services. This study was conducted in a Mediterranean silvopastoral area grazed by autochthonous Sarda cattle to determine the spatial distribution and habitat selection of the cows, who were fitted with GPS tracking collars for this purpose. The total time spent by the animals in different areas was mapped to show the spatial distribution of the cattle in the landscape. Moreover, a preference index was computed for different areas and across different seasons. Overall, the areas where the animals drank and received supplementation were strongly preferred, whereas areas with predominantly rocks were strongly avoided. Grasslands were normally used in proportion to their presence in the area. Forest area was frequented by the cows more in the spring and the summer. These results, representing the first findings concerning Sarda cow grazing in silvopastoral areas, could help farmers to implement actions that help exploit the area more evenly by cows, limiting over- and under-grazing.The beef livestock system in Sardinia is based on suckler cows, often belonging to autochthonous breeds, such as the Sarda breed, and they often graze silvopastoral areas. Besides beef meat, silvopastoral systems (SPSs) provide several Ecosystem Services (ESs), such as timber provision, harvested as wood, and watershed protection. Livestock distribution is a critical factor for the sustainable use of SPSs (e.g., to avoid uneven grazing patterns) and information on patterns of spatial use are required. A study was conducted to determine: (i) the spatial distribution and (ii) the habitat selection of Sarda cattle grazing in a Mediterranean silvopastoral area. Over different seasons, 12 free-roaming adult Sarda cows were fitted with Global Positioning System (GPS) Knight tracking collars to calculate an index mapping of the incidence of livestock in the landscape (LRI) and a preference index (PI) for different areas. Since the PI data were not normally distributed, the Aligned Rank Transform (ART) procedure was used for the analysis. LRI was able to represent the spatial variability in resource utilization by livestock as a LRI map. Overall, the areas where the animals drank and received supplementation were strongly preferred by the cows, reaching PI values in the summer of 19.3 ± 4.9 (median ± interquartile range), whereas areas with predominantly rocks were strongly avoided (the worst PI value in the spring was 0.2 ± 0.6). Grasslands were, in general, used in proportion to their presence in the area, with slightly increased use in the spring (PI 1.1 ± 0.5). Forest area was avoided by cows, except in the spring when it was used in proportion to their presence in the area.

Global trends in grassland carrying capacity and relative stocking density of livestock.

Although the role of livestock in future food systems is debated, animal proteins are unlikely to completely disappear from our diet. Grasslands are a key source of primary productivity for livestock, and feed‐food competition is often limited on such land. Previous research on the potential for sustainable grazing has focused on restricted geographical areas or does not consider inter‐annual changes in grazing opportunities. Here, we developed a robust method to estimate trends and interannual variability (IV) in global livestock carrying capacity (number of grazing animals a piece of land can support) over 2001–2015, as well as relative stocking density (the reported livestock distribution relative to the estimated carrying capacity [CC]) in 2010. We first estimated the aboveground biomass that is available for grazers on global grasslands based on the MODIS Net Primary Production product. This was then used to calculate livestock carrying capacities using slopes, forest cover, and animal forage requirements as restrictions. We found that globally, CC decreased on 27% of total grasslands area, mostly in Europe and southeastern Brazil, while it increased on 15% of grasslands, particularly in Sudano‐Sahel and some parts of South America. In 2010, livestock forage requirements exceeded forage availability in northwestern Europe, and southern and eastern Asia. Although our findings imply some opportunities to increase grazing pressures in cold regions, Central Africa, and Australia, the high IV or low biomass supply might prevent considerable increases in stocking densities. The approach and derived open access data sets can feed into global food system modelling, support conservation efforts to reduce land degradation associated with overgrazing, and help identify undergrazed areas for targeted sustainable intensification efforts or rewilding purposes.

Free-ranging livestock altered the spatiotemporal behavior of the endangered North Chinese leopard (Panthera pardus japonensis) and its prey and intensified human-leopard conflicts.

Widespread distribution of livestock in the natural habitats of large carnivores may negatively impact carnivore populations by reducing wild prey availability and increasing human-carnivore conflicts. In this study, we used camera-trapping data collected in the temperate forests of the Taihang Mountains in North China during 2016-2019 to examine whether and how free-ranging cattle affected habitat use and Diel activity patterns of the endangered North Chinese leopard (Panthera pardus japonensis) and its 2 wild prey species, Siberian roe deer (Capreolus pygargus), and wild boar (Sus scrofa). Residents were also interviewed to record livestock depredation events by leopards during 2015-2019. We found that roe deer spatially avoided sites frequented by cattle, but wild boar did not. In the growing seasons, leopards shared habitats with cattle and tended to increase their diurnal activities where cattle were present. All 3 study species exhibited fine-scale spatial-temporal segregation to cattle. Leopards selectively preyed on calves over adult cattle and livestock depredation frequency was positively correlated with the detection rates of cattle and wild prey, but not that of leopard. These findings not only show that through behavioral adaption large carnivores and their ungulate prey may persist under livestock disturbance, but also highlight how important proper livestock management is for conserving North Chinese leopards in this region. To enhance livestock management and mitigate human-leopard conflicts, we recommend specific actions, such as better guarding of free-ranging cattle or adoption of a captive farming system.

Personal subsidiary plots of Damsinsky rural district of Akmola region: analysis of agricultural production

The goal is to show the importance and consider the current state of agricultural production in personal subsidiary plots of the Damsinsky rural district of Akmola region. Methods – system-structural and system-functional approaches to the study of agricultural production in the households of the district, which requires the use of various methods of scientific analysis: comparative, statistical, mathematical and economic, etc. Results – the authors studied and assessed the structure of the natural and physical capital of this rural region. Also, for a complete assessment of the current state of the main performance indicators, an analysis of the income structure of these farms for the current year is given. The authors determined the degree of uniformity (not uniformity) of the distribution of agricultural land and livestock. Conclusions – the study showed that the majority of private subsidiary farms in the Damsinsky rural district of the Akmola region are either engaged in agricultural production to a small extent or produce agricultural products only for their own consumption and belong to the category of "nonmarketable" household plots. The low level of development of their marketability is determined by such factors as high cost of fodder, lack of independent fodder harvesting, lack of pasture lands around settlements and the high level of their degradation today.

High-resolution livestock distribution data on the Qinghai-Tibet Plateau in 2020

High-resolution livestock distribution data on the Qinghai-Tibet Plateau in 2020

Relocate 10 billion livestock to reduce harmful nitrogen pollution exposure for 90% of China's population.

Livestock production in China is increasingly located near urban areas, exposing human populations to nitrogen pollution via air and water. Here we analyse livestock and human population data across 2,300 Chinese counties to project the impact of alternative livestock distributions on nitrogen emissions. In 2012 almost half of China's livestock production occurred in peri-urban regions, exposing 60% of the Chinese population to ammonia emissions exceeding UN guidelines. Relocating 5 billion animals by 2050 according to crop-livestock integration criteria could reduce nitrogen emissions by two-thirds and halve the number of people exposed to high ammonia emissions. Relocating 10 billion animals away from southern and eastern China could reduce ammonia exposure for 90% of China's population. Spatial planning can therefore serve as a powerful policy instrument to tackle nitrogen pollution and exposure of humans to ammonia.

التباين المكاني لتوزيع الثروة الحيوانية في محافظة أربيل

This research dealt with the study of the spatial variation of livestock (cows, sheep, goats) in the districts of Erbil governorates and There appeared a discrepancy between those districts in the number of cows, sheep and goats. The different distribution of livestock is due to natural and human factors that led to the difference in numbers between the districts of Erbil Governorate. Where the number of cows in Erbil governorate reached (93029) for the year 2021 and (631381) of sheep for the same year, and the number of goats reached (386934) for the year 2021. These animals are raised for their meat, milk, wool and skins that benefit the residents of the study areas. The quantities of its production may be outside the boundaries of the study area, and the research concluded that natural factors have an effective role in the variation of livestock, although human factors have a role in that variation in all its aspects. Also, livestock faced a number of natural and human problems that led to a different distribution according to the districts. The study recommends providing breeds of good production with the provision of feed necessary for animal husbandry with the introduction of vaccines and treatments of good varieties with the increase of veterinary centers in order to increase the number of livestock in the study area.

Distribution of Salers cows in contrasting rangeland pastures relative to established slope and water guidelines

Topographical constraints, particularly steep slopes and far distances to water, have persistently challenged livestock distribution globally. Information gained from global positioning system (GPS) tracking devices have accelerated knowledge of cattle (Bos taurus) use of complex topography to potentially challenge established guidelines. In northern Wyoming, USA, we deployed 5 GPS collars on multiparous Salers cows with calves from July to November 2018–2019. Cattle rotated between 2 contrasting rangeland pastures: the Basin pasture (Foothills Shrublands and Low Mountains ecoregion; mean slope of 17.7% (range: 0.87–111.01%)) and Mountain pasture (transitioning to Absaroka-Gallatin Volcanic Mountain ecoregion; mean slope of 24.4% (range: 0.26–125.11%)). We estimated mean and maximum slope use and distances from water, along with daily distances traveled for each GPS-collared cow per pasture per year. We also generated utilization distributions with Brownian bridge movement models to compare mean slope and distances to water among quartiles of predicted use, and compared stocking rate adjustments per pasture between standard and GPS location derived methods. Mean daily distance traveled was 5126.5 km and 5011.6 km in the Basin and Mountain pastures, respectively, and average distance to water was <1.65 km. Cattle use was concentrated on gentler slopes than the average slope of the pasture. Mean and maximum slope use was 17.5% (9.9°) and 68.2% (34.3°) respectively in the Basin pasture and 8.9% (5.1°) and 57.1% (29.7°) in the Basin pasture. Compared to standard methods, GPS-derived grazeable area calculations suggested that there was less grazeable area in the Basin pasture but more in the Mountain pasture. Our results indicate that cattle adapted to mountainous terrain may challenge established guidelines for slope use, but not for distance to water. Such information could influence grazeable area calculations, stocking rates, and water development.

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.