Search Results (34)

It is crucial to clarify the grassland carrying capacity (CC) and the balance between grass and livestock under different scenarios for ecological protection and sustainable development in the Three River Headwaters Region (TRHR). This study focused on the TRHR and used livestock data, MODIS Net Primary Productivity (NPP) data, and artificial supplementary feeding data to analyze grassland CC and explore changes in the grass–livestock balance across various scenarios. The results showed that the theoretical CC of edible forage under complete grazing conditions was much lower than that of crude protein under nutritional carrying conditions. Furthermore, without increasing the grazing intensity of natural grasslands, artificial supplementary feeding reduced overstocking areas by 21%. These results suggest that supplementary feeding effectively addresses the imbalance between forage supply and demand, serving as a key measure for achieving sustainable grassland livestock husbandry. Despite the effective mitigation of grassland degradation in the TRHR due to strict grass–livestock balance policies and ecological restoration projects, the actual livestock CC exceeded the theoretical capacity, leading to overgrazing in some areas. To achieve desired objectives, more effective grassland management strategies must be implemented in the future to minimize spatiotemporal conflicts between grasses and livestock and ensure the health and stability of grassland ecosystems. Full article

Seasonal climate variability and agronomic management profoundly influence both the productivity and nutritive value of temperate hay meadows. We analyzed five years of data (2019, 2020, 2022–2024) from 15 meadows in the central Spanish Pyrenees to quantify how environmental variables (January–June minimum temperatures, rainfall), management variables (fertilization rates (N, P, K), livestock load, cutting date), and vegetation (plant biodiversity (Shannon index)) drive total biomass yield (kg ha⁻¹), protein content (%), and Relative Feed Value (RFV). Using Random Forest regression with rigorous cross-validation, our yield model achieved an R² of 0.802 (RMSE = 983.8 kg ha⁻¹), the protein model an R² of 0.786 (RMSE = 1.71%), and the RFV model an R² of 0.718 (RMSE = 13.86). Variable importance analyses revealed that March rainfall was the dominant predictor of yield (importance = 0.430), reflecting the critical role of early-spring moisture in tiller establishment and canopy development. In contrast, cutting date exerted the greatest influence on protein (importance = 0.366) and RFV (importance = 0.344), underscoring the sensitivity of forage quality to harvest timing. Lower minimum temperatures—particularly in March and May—and moderate livestock densities (up to 1 LU) were also positively associated with enhanced protein and RFV, whereas higher biodiversity (Shannon ≥ 3) produced modest gains in feed quality without substantial yield penalties. These findings suggest that adaptive management—prioritizing soil moisture conservation in early spring, timely harvesting, balanced grazing intensity, and maintenance of plant diversity—can optimize both the quantity and quality of hay meadow biomass under variable climatic conditions. Full article

The Altay oasis, located at the heart of the transnational ecological conservation zone shared by China, Kazakhstan, Russia, and Mongolia, is a region with tremendous potential for water resource utilization. However, with the continued expansion of agriculture, its ecological vulnerability has become increasingly pronounced. Within this fragile balance lies a critical opportunity: efficient water resource management could pave the way for sustainable development across the entire arid oasis regions. This study uses a decision tree model based on a feature threshold to map the spatial distribution of major crops in the Altay Prefecture oasis, assess their water requirements, and identify the coupling relationships between agricultural water and land resources. Furthermore, it proposed optimization planting structure strategies under three scenarios: water-saving irrigation, cash crop orientation, and forage crop orientation. In 2023, the total planting area of major crops in Altay Prefecture was 3368 km², including spring wheat, spring maize, sunflower, and alfalfa, which consumed 2.68 × 10⁹ m³ of water. Although this area accounted for only 2.85% of the land, it consumed 26.23% of regional water resources, with agricultural water use comprising as much as 82.5% of total consumption, highlighting inefficient agricultural water use as a critical barrier to sustainable agricultural development. Micro-irrigation technologies demonstrate significant water-saving potential. The adoption of such technologies could reduce water consumption by 14.5%, thereby significantly enhancing agricultural water-use efficiency. Cropping structure optimization analysis indicates that sunflower-based planting patterns offer notable water-saving benefits. Increasing the area of sunflower cultivation by one unit can unlock a water-saving potential of 25.91%. Forage crop combinations excluding soybean can increase livestock production by 30.2% under the same level of water consumption, demonstrating their superior effectiveness for livestock system expansion. This study provides valuable insights for achieving sustainable agricultural development in arid regions under different development scenarios. Full article

Livestock population surveys are crucial for grassland management tasks such as health and epidemic prevention, grazing prohibition, rest grazing, and forage–livestock balance assessment. These tasks are integral to the modernization and upgrading of the livestock industry and the sustainable development of grasslands. Unmanned aerial vehicles (UAVs) provide significant advantages in flexibility and maneuverability, making them ideal for livestock population surveys. However, grazing livestock in UAV images often appear small and densely packed, leading to identification errors. To address this challenge, we propose an efficient Livestock Network (LSNET) algorithm, a novel YOLOv7-based network. Our approach incorporates a low-level prediction head (P2) to detect small objects from shallow feature maps, while removing a deep-level prediction head (P5) to mitigate the effects of excessive down-sampling. To capture high-level semantic features, we introduce the Large Kernel Attentions Spatial Pyramid Pooling (LKASPP) module. In addition, we replaced the original CIoU with the WIoU v3 loss function. Furthermore, we developed a dataset of grazing livestock for deep learning using UAV images from the Prairie Chenbarhu Banner in Hulunbuir, Inner Mongolia. Our results demonstrate that the proposed module significantly improves the detection accuracy for small livestock objects, with the mean Average Precision (mAP) increasing by 1.47% compared to YOLOv7. Thus, this work offers a novel and practical solution for livestock detection in expansive farms. It overcomes the limitations of existing methods and contributes to more effective livestock management and advancements in agricultural technology. Full article

In integrated crop–livestock systems (ICLSs), grazing intensity and crop rotation influence residue dynamics, making it essential to assess shoot and root contributions to soil carbon (C) and nitrogen (N) inputs. This study aimed to assess the shoot and root biomass of Italian ryegrass, soybean, and maize; the distribution of roots within the soil profile; and the contributions of shoot and root biomass to soil C and N under varying winter grazing intensities and summer crop rotations. The experiment was conducted within a long-term (12-year) field protocol, arranged in a randomized complete block design with split plots and four replicates. Grazing intensity was defined as the following: (i) moderate grazing—forage allowance equivalent to 2.5 times the potential dry matter intake of sheep, and (ii) low grazing—forage allowance equivalent to 5.0 times the intake potential. Grazing intensities (moderate and low) were allocated to the main plots, while cropping systems—monoculture (soybean/soybean) and crop rotation (soybean/maize)—were assigned to the subplots. Soil depth layers (0–10, 10–20, 20–30, and 30–40 cm) were treated as sub-subplots. Root samples of Italian ryegrass, soybean, and maize were collected using the soil monolith method. Low grazing intensity (8.6 Mg ha⁻¹) promoted greater aboveground biomass production of Italian ryegrass compared to moderate intensity (6.6 Mg ha⁻¹). Maize exhibited a higher capacity for both root and shoot biomass accumulation, with average increases of 85% and 120%, respectively, compared to soybean. Root biomass was primarily concentrated in the surface soil layer, with over 70% located within the top 10 cm. Italian ryegrass showed a more uniform root distribution throughout the soil profile compared to soybean and maize. Carbon inputs were higher under crop rotation (17.2 Mg ha⁻¹) than under monoculture (15.0 Mg ha⁻¹), whereas nitrogen inputs were greater in soybean monoculture (0.23 Mg ha⁻¹) than in crop rotation (0.16 Mg ha⁻¹). Low grazing intensity in winter and summer crop rotation with high-residue and quality species enhance the balance between productivity and soil C and N inputs, promoting the sustainability of ICLSs. Full article

Fenugreek (Trigonella foenum-graecum L.) is an emerging forage crop known for its high nutritional value and adaptability to diverse environmental conditions, making it a promising alternative in sustainable livestock feeding systems in the Mediterranean region. A field experiment was established at the Agricultural University of Athens during the growing season 2020–2021 in a split-plot design with five fertilization treatments (Biocyclic-Vegan Humus Soil; BHS, Farmyard Manure; FMA, Organic Compost; OCP, Inorganic Fertilizer; IFZ, and No Treatment Control; CTRL, and two main salinity treatments (High Salinity Level; HSL, and Normal Salinity Level; NSL). The Forage Quality Index (FQI) was the highest under BHS at NSL (45) and lowest under CTRL at HSL (32), emphasizing the positive impact of organic fertilization. Crude ash (CA) was higher under NSL (9.7%), with OCP and IFZ performing best, while salinity reduced CA under CTRL. Crude fiber (CF) increased under salinity, particularly with OCP and IFZ, whereas BHS and FMA at NSL showed the lowest CF (15.8%), enhancing digestibility. Total fat (TF) was the highest under BHS and FMA at NSL (5.8%) and lowest under IFZ and CTRL at HSL (4.0%), underscoring the importance of balanced fertilization in maintaining fat content. These results highlight the potential of organic amendments to improve nutrient availability, digestibility, and overall feed value. Full article

The Qinghai–Tibet Plateau (QTP), a critical ecological buffer for Asia, faces intensifying pressures from climate change and infrastructure expansion. The Qinghai–Tibet Railway (QTR), as the world’s highest-altitude railway, traverses this fragile yet economically vital region, where balancing ecosystem integrity and development remains a global sustainability challenge. While previous studies have documented localized environmental impacts of the QTR, systematic assessments of long-term ecological-economic interactions—particularly the synergies and trade-offs between ecosystem service value (ESV) and economic growth—are lacking. This gap hinders targeted policy design to reconcile conservation and development in extreme environments. The present research integrates an enhanced ecosystem service valuation framework with spatial econometric modeling to quantify environmental changes and ecological-economic coordination in the Qinghai–Tibet Railway Region (QTRR) during 1990–2020. The analysis reveals a cumulative ESV increase of USD 54.4 billion over the past 30 years, driven primarily by grassland restoration and regulated land use transitions. Notably, county-level ecological-economic coordination improved significantly, with harmonization indices rising by 32–68% across all jurisdictions. However, latent risks emerged: five counties exhibited severe ecosystem-health-to-economy mismatches by 2020. These findings demonstrate that infrastructure corridors in fragile ecosystems can achieve partial ecological-economic coordination through policy interventions, yet persistent local disparities demand spatially differentiated management. By linking ESV dynamics to governance pathways—including livestock–forage balance mechanisms and green urban zoning—the present study provides a transferable framework for assessing sustainability trade-offs in extreme environments. Broader implications highlight the necessity of embedding adaptive ecological thresholds into infrastructure planning, offering experiences for the Belt and Road Initiative and other high-altitude development frontiers. Full article

The livestock sector is crucial for global food security and economic development, particularly in developing nations, as it supports the livelihoods of approximately 1.3 billion people. However, with the global population expected to reach 9.2 billion by 2050, the sector must address increasing demand for livestock products while ensuring environmental sustainability. This study used the available literature to evaluate the economic viability of sustainable pasture and rangeland management practices to enhance livestock production. The key findings demonstrate that strategies such as rotational grazing and nitrogen fertilization can decrease winter feed costs by up to 40% while simultaneously improving pasture productivity and animal weight gains. Initial investments in these improved forage practices offer high internal rates of return, indicating their profitability. To guide sustainable pasture production and rangeland management, we propose a conceptual framework that balances cultivated pastures and natural rangelands. This framework assesses critical factors, including input costs, expected outputs (enhanced biodiversity and livestock production), and interventions to mitigate land degradation. For successful adoption of these practices, targeted policies are essential. Governments should develop financial support mechanisms for smallholder farmers, improve transportation infrastructure for efficient feed logistics, and provide technical assistance to educate producers on sustainable practices. Engaging stakeholders to align policies with local needs is also vital. By implementing these strategic interventions, the resilience of livestock systems can be strengthened, contributing to long-term sustainability and supporting food security and rural community well-being. Full article

Climate change is a global challenge that impacts rangeland and pastureland landscapes by inducing shifts in temperature variability, precipitation patterns, and extreme weather events. These changes alter soil and plant conditions, reducing forage availability and chemical composition and leading to nutritional stress in cattle. This stress occurs when animals lack adequate water and feed sources or when these resources are insufficient in quantity, composition, or nutrient balance. Several strategies are essential to address these impacts. Genetic selection, epigenetic biomarkers, and exploration of epigenetic memories present promising avenues for enhancing the resilience of cattle populations and improving adaptation to environmental stresses. Remote sensing and GIS technologies assist in locating wet spots to establish islands of plant diversity and high forage quality for grazing amid ongoing climate change challenges. Establishing islands of functional plant diversity improves forage quality, reduces carbon and nitrogen footprints, and provides essential nutrients and bioactives, thus enhancing cattle health, welfare, and productivity. Real-time GPS collars coupled with accelerometers provide detailed data on cattle movement and activity, aiding livestock nutrition management while mitigating heat stress. Integrating these strategies may offer significant advantages to animals facing a changing world while securing the future of livestock production and the global food system. Full article

Sustainable and climate-resilient livestock systems are increasingly necessary to balance food production demands with environmental conservation. Breeds such as Galloway (Ga) and Highland (Hi) cattle are recognized for their adaptability to extensive grazing systems, low input requirements, and ability to thrive on marginal lands. Despite their potential, research on the performance of Ga and Hi cattle in low-resource, extensive grazing systems, particularly in Romania, remains scarce. This study evaluated the performance of Ga and Hi beef cattle raised under low-input conditions with a focus on the following: (1) the average daily gain (ADG) on low- and medium-quality forage and (2) the cattle’s adaptability to extensive grazing systems. The study, conducted at Cojocna Farm, Transylvania, Romania (2023–2024), involved five male and three female calves from each breed. Calves were weighed five times in the entire observation period, and feed quality was analyzed. The results showed that Ga calves, especially males, had a higher ADG than Hi calves (Ga = 676.91 g, Hi = 581.14 g), while females showed more consistent performance during winter feeding. Both breeds demonstrated strong adaptability and satisfactory performance under the extensive conditions of Transylvania, as evidenced by the comparison of the obtained ADG with the values provided by the National Breed Register. Future research should explore the long-term sustainability of these breeds in varying environmental conditions, to investigate genetic factors influencing performance, and assess the broader ecological and economic benefits of integrating Galloway and Highland cattle into diverse farming systems. Full article

As an important ecological barrier and a crucial base for animal husbandry in China, the forage–livestock balance in the Three-River-Source Region (TRSR) directly impacts both the degradation and recovery of grassland. This study examines the forage–livestock balance in the TRSR over the past 13 years (2010–2022) by calculating both the theoretical and actual livestock carrying capacity, thereby providing a scientific basis for regional animal husbandry policies. Firstly, the Carnegie–Ames–Stanford Approach (CASA) model was improved to fit the specific characteristics of alpine grassland ecosystem in the TRSR. This enhanced model was subsequently used to calculate the net primary productivity (NPP) of the grassland, from which the regional grassland yield and theoretical livestock carrying capacity were derived. Secondly, the actual livestock carrying capacity was calculated and spatialized based on the number of regional year-end livestock. Finally, the livestock carrying pressure index was determined using both the theoretical and actual livestock carrying capacity. The results revealed several key findings: (1) The average grassland NPP in the TRSR was 145.44 gC/m², the average grassland yield was 922.7 kg/hm², and the average theoretical livestock carrying capacity was 0.55 SU/hm² from 2010 to 2022. Notably, all three metrics showed an increasing trend over the past 13 years, which indicates the rise in grassland vegetation activities. (2) The average actual livestock carrying capacity over the 13-year period was 0.46 SU/hm², showing a decreasing trend on the whole. The spatial distribution displayed a pattern of higher capacity in the east and lower in the west. (3) Throughout the 13 years, the TRSR generally maintained a forage–livestock balance, with an average livestock carrying pressure index of 0.96 (insufficient). However, the trend of livestock carrying pressure is on the rise, with serious overloading observed in the western part of Qumalai County and the northern part of Tongde County. Slight overloading was also noted in Zhiduo, Maduo, and Zeku Counties. Notably, Tanggulashan Town, Zhiduo, Qumalai, and Maduo Counties showed significant increases in livestock carrying pressure, while Zaduo County and the eastern regions experienced significant decreases. In conclusion, this study not only provides feasible technical methods for assessing and managing the forage–livestock balance in the TRSR but also contributes significantly to the sustainable development of the region’s grassland ecosystem and animal husbandry industry. Full article

A thorough understanding of the development process of grazing activities and an elucidation of their complex mechanisms are crucial for the formulation and adjustment of livestock management policies. In the Selinco region of the Qinghai–Tibet Plateau, we conducted a comprehensive analysis of year-end livestock numbers and densities over the past 30 years. The results indicate a gradual decline in overall livestock numbers in the Selinco region during this period, with a notable decrease between 2004 and 2014, followed by stabilization. Notably, the number of yaks has significantly increased, whereas the numbers of sheep, goats, and horses have markedly decreased. Regarding livestock density, there is a spatial pattern of decrease from northwest to southeast, with the density order being Seni District > Bange County > Anduo County > Shenzha County > Nima County > Shuanghu County. Between 2004 and 2014, most counties experienced a significant decline in livestock density, exhibiting a trough–peak pattern. However, after 2014, a complex spatiotemporal dynamic emerged. Concerning driving factors, from 1990 to 2004, rural population and economic development were the primary influences on livestock density. After 2004, forage–livestock balance management policies, snowstorms, and fluctuations in livestock prices likely became the main influencing factors. Further detailed analysis of these factors is essential for developing more effective management strategies. Full article

The growing population, the transition dietary towards animal-based products, and the preference for the brand of grass-feeding livestock are bringing increasing pressure on natural grasslands, especially for dry-land areas. The Xilingol League of China is famous for its free-range livestock product, however, overgrazing and herders’ benefits damage are always serious issues for this semi-arid grassland region. This study focuses on the relationship between the supply of natural grassland and the consumption of free-range livestock in the Xilingol League, and this study employed the grassland carrying capacity as the index to judge the sustainability states and its trends of the local grass-feeding system. Satellite data production of net primary production was used for grassland production, statistical livestock data and the consumption model were used for actual forage consumption, and empirical key informant interview data were used to obtain a more comprehensive understanding. The results show that: (1) the natural grassland carrying capacity of the Xilingol League fluctuated, showing improvement from 2000 to 2021; (2) the grassland management needs to be more diversified in different regions with different natural conditions; and (3) while the demand for free-range, high-quality beef is increasing, attention should be paid to the carrying capacity of natural pastures and more consideration should be taken of the benefits of balancing the livelihood of herders, policy strategies, and the customers’ preferences. Potential ways of doing this include employing technologies to improve livestock production, and further exploring and promoting the economic value of the free-range livestock and the geographical indication to get the economic–ecological win-win situation. The research framework and results would be beneficial to reveal the potential threats in pastoral areas and provide support for the optimization of the regional grass-feeding breeding system, especially in middle-income countries. Full article

The provision and utilization of grassland resources connect grassland ecosystems and pastoral society. Revealing the mechanism behind the forage supply–demand relationship and balancing forage supply and demand is essential in pastoral socio-ecological systems. Taking Altay Prefecture as the case study, this study quantified the dynamics of natural forage supply, artificial supplemental forage, and forage demand. The ratio of forage supply to demand was calculated in the traditional grazing scenario and the grazing prohibition and supplemental feeding scenario. The results showed that during 2001–2018, the forage supplied by natural grasslands fluctuated, with the highest and lowest values in 2013 and 2008, respectively. The artificial supplemental forage increased at a higher rate in 2011–2018 than in 2001–2010. The overall trend of forage demand was upward, at approximately 2.98 × 10⁴ t/a. The ratio of forage supply to demand decreased in the traditional scenario with an average value of 0.4717 and increased in the grazing prohibition and supplemental feeding scenario with an average value of 0.8289. The influencing factors were analyzed from the perspective of the interactions between the socio-ecological system elements, and the forage supply–demand relationships were conceptualized based on the social–ecological system framework. This study concludes that natural grasslands cannot entirely meet the increasing forage demand without artificial supplemental forage. The increasing artificial supplemental forage has promoted a balance between forage supply and demand, indicating an optimized grassland utilization pattern. The factors that affect forage supply–demand relationships are interrelated, and a holistic perspective should be adopted when implementing management measures. Full article

As one of the most widespread and important types of terrestrial vegetation in the world, grasslands play an irreplaceable role in global climate change. The grasslands of Inner Mongolia, represented by the Xilin Gol League, are typical of Eurasian grasslands and have an important ecological status in the world. In this paper, taking the grassland of Xilin Gol League as the research object, based on the machine learning method, we mainly carry out two aspects of work: the prediction of grassland soil health and evaluation of grassland sustainable development. To address the issue of predicting soil health in grasslands, we focus on an important indicator in grasslands: soil moisture. By analyzing the characteristics of soil moisture time series values and related influencing factors, based on a NAR neural network model, three important factors of soil moisture were predicted: soil evaporation data, average air temperature, and precipitation. Subsequently, the corresponding soil moisture calculation model was trained using regression models based on hyperparameter optimization, and the final predicted soil moisture values were obtained for different months and depths in 2023 and 2024. To evaluate the sustainability of grassland development, we developed a model for the degree of grassland desertification based on the kernel principal component analysis, focusing on three dimensions: environmental factors, surface factors, and human factors. Based on this, a quantitative definition of soil denudation is given by analyzing the main influencing factors of grassland soil degradation. At the same time, a prediction model for the evaluation of soil slumping was established based on a fuzzy comprehensive evaluation matrix, and the evaluation weights of each major factor were given and analyzed. Based on the above research, this paper suggests a reasonable grazing strategy for the grassland areas of the Xilin Gol League: when the grazing intensity is medium and the total number of grazing days is [85, 104] days in a year, the degree of soil slumping and soil desertification in the pastures is minimized. The research results of this paper are useful for the future maintenance and management of the grasslands of Xilin Gol League and other similar areas. Full article