Search Results (137)

Mapping Plant Ecological Units (PEUs) support sustainable rangeland management. Yet, distinguishing them from multispectral imagery remains challenging due to high intra-class variability and spectral overlap. This study evaluates the contribution of auxiliary data layers to improve PEU classification from Landsat-8 OLI imagery in semi-arid rangelands of northeastern Iran. A random forest (RF) classifier was trained using field samples and multiple feature combinations, including spectral indices, topographic variables (DEM, slope, aspect), and principal component analysis (PCA) components. Classification performance was assessed using overall accuracy (OA), kappa coefficient, and non-parametric Friedman and post hoc tests to determine significant differences among scenarios. The results show that auxiliary features consistently enhanced classification performance as opposed to spectral bands alone. Integrating DEM and PCA layers yielded the highest accuracy (OA = 79.3%, κ = 0.71), with statistically significant improvement (p < 0.05). The findings demonstrate that incorporating topographic and transformed spectral information can effectively reduce class confusion and improve the separability of PEUs in complex rangeland environments. The proposed workflow provides a transferable approach for ecological unit mapping in other semi-arid regions facing similar environmental and management challenges. Full article

This paper examines an approach to local-level community action for the global Sustainable Development Goals (SDGs), amid the growing importance of context-specific implementations to accelerate progress. Land-use governance is critical for contributions to the SDGs, as it shapes a wide range of environmental, social, and economic outcomes. Wildlife conservancies provide an innovative community-driven land-stewardship model that has proliferated across rangelands in various African countries as a sustainable development strategy. This study explores the potential contribution and capacity of conservancies, as a form of land-use governance, in advancing the SDGs at local levels. Using case studies from Kenya’s Maasai Mara, the research draws on qualitative primary data collected through in-depth interviews, a focus group discussion, observation, and document review, supplemented by secondary data obtained from a literature review. The data was analyzed thematically. The results show that conservancies address key socio-ecological challenges corresponding with multiple SDGs, particularly those related to poverty reduction, food security, climate action, and life on land. However, significant segments of local communities remain marginalized in decision making and benefit sharing, a situation rooted in pre-existing social hierarchies and weak governance institutions, raising concerns about social justice. Other major limitations are related to the conservancies’ over-reliance on tourism, and local people’s high dependence on natural resources. To resolve these limitations, the study recommends improving local governance via institutional strengthening, capacity building, gender empowerment, and stakeholder partnerships; diversifying income sources to reduce financial vulnerability; and adopting strategies to alleviate high dependence on natural resources in the long term. Full article

The advancement of hyperspectral remote sensing technology has enhanced the ability to assess and characterize land cover in complex ecosystems. In this study, a linear spectral unmixing algorithm was applied to NEON hyperspectral imagery in 2018 and 2022 to quantify the fractional abundance of dominant land cover classes, namely herbaceous vegetation, mixed forbs, and bare soil, across the Marvin Klemme Experimental Rangeland in Oklahoma. UAV imagery acquired during the 2023 field campaign provided high resolution reference data for model training. The LSU results revealed a decline in herbaceous cover from 16.02 ha to 11.56 ha and an expansion of bare soil from 3.37 ha to 6.39 ha, while mixed forb cover remained relatively stable (12.38 ha to 13.82 ha). Accuracy assessment using the UAV-derived validation points yielded overall accuracy of 84% and 60% at fractional thresholds of 50% and 75%, respectively. Although statistical tests indicated no significant change in mean fractional abundance (p > 0.05), slope-based trend maps captured localized vegetation loss and regrowth patterns. These findings demonstrate the effectiveness of integrating LSU with UAV data for detecting subtle yet ecologically meaningful shifts in semi-arid grassland composition. Full article

This study employs an integrated framework that combines field-based measurements, remote sensing, and Geographic Information Systems (GISs) to monitor vegetation dynamics and assess the suitability of a steppe range reserve for livestock grazing. Forty-three surface and subsurface soil samples were collected in April and November 2021 to capture seasonal variations. Above-ground biomass (AGB) measurements were recorded at five sampling locations across the reserve. Six Sentinel-2 satellite imageries, acquired around mid-March 2016–2021, were processed to derive time-series Normalized Difference Vegetation Index (NDVI) data, capturing temporal shifts in vegetation cover and density. The GIS-based Multi-Criteria Decision Analysis (MCDA) was employed to model the suitability of the reserve for livestock grazing. The results showed higher salinity, total dissolved solids (TDSs), and nitrate (NO₃) values in April. However, the percentage of organic matter increased from approximately 7% in April to over 15% in November. The dry forage productivity ranged from 111 to 964 kg/ha/year. On average, the reserve’s dry yield was 395 kg/ha/year, suggesting moderate productivity typical of steppe rangelands in this region. The time-series NDVI analyses showed significant fluctuations in vegetation cover, with lower NDVI values prevailing in 2016 and 2018, and higher values estimated in 2019 and 2020. The grazing suitability analysis showed that 13.8% of the range reserve was highly suitable, while 24.4% was moderately suitable. These findings underscore the importance of tailoring grazing practices to enhance forage availability and ecological resilience in steppe rangelands. By integrating satellite-derived metrics with in situ vegetation and soil measurements, this study provides a replicable methodological framework for assessing and monitoring rangelands in semi-arid regions. Full article

Accurate estimation of aboveground biomass (AGB) is essential for monitoring forage availability and guiding sustainable management in high-altitude pastures, where grazing sustains livelihoods but also drives ecological degradation. Although remote sensing has advanced biomass modeling in rangelands, applications in Andean–Amazonian ecosystems remain limited, particularly using UAV-based structural and spectral data. This study evaluated the potential of UAV LiDAR and multispectral imagery to estimate fresh and dry AGB in ryegrass (Lolium multiflorum Lam.) pastures of Amazonas, Peru. Field data were collected from subplots within 13 plots across two sites (Atuen and Molinopampa) and modeled using Random Forest (RF), Support Vector Machines, and Elastic Net. AGB maps were generated at 0.2 m and 1 m resolutions. Results revealed clear site- and month-specific contrasts, with Atuen yielding higher AGB than Molinopampa, linked to differences in climate, topography, and grazing intensity. RF achieved the best accuracy, with chlorophyll-sensitive indices dominating fresh biomass estimation, while LiDAR-derived height metrics contributed more to dry biomass prediction. Predicted maps captured grazing-induced heterogeneity at fine scales, while aggregated products retained broader gradients. Overall, this study shows the feasibility of UAV-based multi-sensor integration for biomass monitoring and supports adaptive grazing strategies for sustainable management in Andean–Amazonian ecosystems. Full article

Accurately quantifying grazing intensity (GI) is crucial for assessing grassland utilization and supporting sustainable management. Traditional livestock-based approaches cannot capture the spatial heterogeneity of grazing or its dynamic response to climate variability. The objective of this study was to develop a remote sensing-based quantitative framework for estimating GI across the Inner Mongolian grasslands. The framework integrates MODIS vegetation indices, ERA5-Land climate variables, topographic factors, and field-measured data and GI was quantified as the proportional difference between potential and satellite-derived aboveground biomass (AGB), providing a spatially explicit measure of forage utilization. In this framework, potential AGB (AGBp) represents the climate-driven growth capacity under ungrazed conditions reconstructed using machine learning models, whereas satellite-derived AGB (AGBs) denotes the standing AGB remaining under current grazing pressure. Validation using 324 paired grazed–ungrazed plots demonstrated strong agreement between modeled and observed GI (R² = 0.65, RMSE = 0.18). This AGB-difference-based approach provides an effective and scalable tool for large-scale rangeland monitoring, offering quantitative insights into grass–livestock balance, ecological restoration, and adaptive management in arid and semi-arid regions. Full article

Rangeland degradation in arid and semi-arid regions is a serious ecological challenge, damaging soil health and reducing plant growth. This study evaluated the comparative effects of Almarai organic and inorganic fertilizers on the growth performance of three native rangeland species across three semi-arid locations of Saudi Arabia, including Al-Tamiryyat (Al-Jouf), Al-Sahwa (Al-Madina), and Al-Fuhaihil (Thadiq), in a randomized complete block design. The study revealed that fertilization significantly influenced plant height and stem diameter, with organic fertilizers yielding superior results compared to inorganic treatments across most regions (p < 0.001). Specifically, plant height for Pl3 demonstrated a substantial increase of 71% and 159% under Almarai organic fertilization in the Al-Tamiryyat and Al-Fuhaihil regions, respectively, while inorganic fertilization yielded an improvement of 61% and 132% only in the Al-Tamiryyat and Al-Fuhaihil sites, respectively. Stem diameter also exhibited significant growth under both fertilizer types (p < 0.001), with the most significant increases observed in Pl1, particularly under organic amendment in Al-Tamiryyat (184%) and inorganic fertilizer in Al-Sahwa (151%). Conversely, the effect of fertilization on crown size ratio was minimal in Al-Tamiryyat and Al-Fuhaihil (p > 0.05) but was significantly improved in Al-Sahwa region (p < 0.001) under Almarai organic fertilization. Conclusively, results of current research suggest that organic fertilization is effective way of restoring rangelands in arid environments compared to inorganic amendments. Full article

The Community-Based Conservation (CBC) approach views local people as interested parties who should actively participate in and control conservation efforts, which contrasts with the conventional 'fortress conservation' common in government-protected areas isolated from human disturbance. The transition from fortress conservation to CBC, however, has not been a smooth journey for many African countries, especially in the sub-Saharan Africa region. This is because, in some cases, local communities do not see themselves as part of the governance structure of these conservancies, which affects the long-term ecological sustainability of the conservancies. Using eight (8) conservancies in the arid and semi-arid counties of Isiolo and Samburu, Kenya, this study used exploratory research to gather data from 24 Focus Group Discussions (FDGs) and forty-eight (48) key informant interviews (KIIs) to assess the influence of communities’ involvement on ecological outcomes of the conservancies. Other secondary sources also supported the primary data sources. Our findings showed that the governance model does influence community support for conservancies, and the benefits that communities receive or expect from the conservancies also have a strong influence on their support for conservation. However, it was established that community conservancies have brought positive changes to the wildlife population trends and habitat health. The study recommends the development of the National Rangelands Resources Management Policy and institutional arrangements to strengthen and safeguard the future of wildlife conservation within those conservancies and to provide clarity on the roles of different stakeholders. The study also recommends further studies on the actual impact of governance on community perception, the value of existing investments in community benefits, and the long-term implications of climate change impacts on conservancy ecosystems. Full article

The yak (Bos grunniens) is a key species in high-altitude rangelands of Asia. Despite their ecological and economic importance, yak production faces persistent challenges, including low milk yields, vulnerability to climate changes, emerging diseases, and a lack of systematic breeding programs. This review presents the genomic, physiological, and environmental dimensions of yak biology and husbandry. Genes such as EPAS1, which encodes hypoxia-inducible transcription factors, underpin physiological adaptations, including enlarged cardiopulmonary structures, elevated erythrocyte concentrations, and specialized thermoregulatory mechanisms that enable their survival at elevations of 3000 m and above. Copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) present promising markers for improving milk and meat production, disease resistance, and metabolic efficiency. F1 and F2 generations of yak–cattle hybrids show superior growth and milk yields, but reproductive barriers, such as natural mating or artificial insemination, and environmental factors limit the success of these hybrids beyond second generation. Infectious diseases, such as bovine viral diarrhea and antimicrobial-resistant and biofilm-forming Enterococcus and E. coli, pose risks to herd health and food safety. Rising ambient temperatures, declining forage biomass, and increased disease prevalence due to climate changes risk yak economic performance and welfare. Addressing these challenges by nutritional, environmental, and genetic interventions will safeguard yak pastoralism. This review describes the genes associated with different yak traits and provides an overview of the genetic adaptations of yaks (Bos grunniens) to environmental stresses at high altitudes and emphasizes the need for conservation and improvement strategies for sustainable husbandry of these yaks. Full article

Rangelands form the ecological and economic backbone of Namibia, yet the woody plant dynamics that sustain these landscapes remain sporadically quantified across the semi-arid interior. We investigated the characteristics (stand structure, regeneration, richness, diversity, composition, ecological importance, and indicator species) of woody communities along a pronounced south-to-north rainfall gradient (85–346 mm yr⁻¹) at five representative sites: Warmbad, Gibeon, Otjimbingwe, Ovitoto, and Sesfontein. Field sampling combined point-centered quarter surveys (10 points site⁻¹) and belt transects (15 plots site⁻¹). The basal area increased almost ten-fold along the gradient (0.4–3.4 m² ha⁻¹). Principal Coordinates Analysis (PCoA) arranged plots in near-perfect rainfall order, and Permutational Multivariate Analysis of Variance (PERMANOVA) confirmed significant site differences (F_3,56 = 9.1, p < 0.001). Nanophanerophytes dominated hyper-arid zones, while microphanerophytes appeared progressively with increasing rainfall. Mean annual precipitation explained 45% of the variance in mean height and 34% of Shannon diversity but only 5% of stem density. Indicator value analysis highlighted Montinia caryophyllacea for Warmbad (IndVal = 100), Rhigozum trichotomum (75.8) for Gibeon, Senegalia senegal (72.6) for Otjimbingwe, and Senegalia mellifera (97.3) for Ovitoto. Rainfall significantly influences woody structure and diversity; however, other factors also modulate density and regeneration dynamics. This quantitative baseline can serve as a practical toolkit for designing site-specific management strategies across Namibia’s aridity gradient. Full article

The Qinghai–Tibet Plateau, a critical ecological barrier and major livestock region, faces deteriorating grasslands and rising forage demand under its harsh alpine climate. Oat (Avena sativa L.), valued for its cold tolerance, rapid biomass accumulation, and ability to thrive in nutrient-poor soils, can expand winter feed reserves and partly alleviate grazing pressure on native rangelands. However, genetic improvement alone has not been sufficient to address the environmental challenges. This issue is particularly severe in the Qaidam Basin, where soil salinization, characterized by high pH, poor soil structure, and low nutrient availability, significantly limits crop performance. Rhizosphere growth-promoting bacteria (PGPR) are environmentally friendly biofertilizers known to enhance crop growth, yield, and soil quality, but their application in the saline soil of the Qaidam Basin remains limited. We evaluated two PGPR application rates (B1 = 75 kg hm⁻² and B2 = 150 kg hm⁻²) on ‘Qingtian No. 1’ oat, assessing plant growth, soil physicochemical properties, and rhizosphere microbial communities. The results indicated that both treatments significantly increased oat productivity, raised the comprehensive growth index, augmented soil organic matter, and lowered soil pH; B1 chiefly enhanced above-ground biomass and fungal community stability, whereas B2 more strongly promoted root development and bacterial community stability. Structural equation modeling showed that PGPR exerted direct effects on the comprehensive growth index and indirect effects through soil and microbial pathways, with soil properties contributing slightly more than microbial factors. Notably, rhizosphere organic matter, fungal β-diversity, and overall microbial community stability emerged as positive key drivers of the comprehensive growth index. These findings provide a theoretical basis for optimizing PGPR dosage in alpine forage systems and support the sustainable deployment of microbial fertilizers under saline soil conditions in the Qaidam Basin. Full article

Aboveground biomass models are useful for assessing vegetation conditions and providing valuable information on the availability of ecosystem goods and services, including carbon stock and forest/rangeland products. This study aimed to develop aboveground biomass estimation models for the common woody species found in Borana woodland. Multispecies and species-specific models for aboveground biomass were developed using 114 destructively sampled trees representing five species. The dendrometric variables selected as predictors of the trees’ aboveground dry biomass for both multispecies and species-specific models were diameter at breast height, tree height, wood basic density (ρ), crown area (ca) and crown diameter (cd). The distribution of biomass across trees’ aboveground components was estimated using destructively sampled trees. Most tree biomass is allocated to branches, followed by the stems. The tree diameter, wood basic density, and crown diameter were significant predictors in generic and species-specific biomass models across all tree components. Incorporating wood basic density into the model significantly improved prediction accuracy, while tree height had a minimal effect on biomass estimation. The stem and twig biomasses were the highest and least predictable plant parts, respectively. Compared with the existing models, our newly developed models significantly reduced prediction errors, reinforcing the importance of location-specific models for accurate biomass estimation. Hence, this study fills the geographic and ecological gaps by developing models tailored with the unique conditions of the Borana lowland forest. The accuracy of species-specific biomass models varied among tree species, indicating the need for species-specific models that account for variations in growth architecture, ecological factors, and bioclimatic conditions. Full article

Desertification, accompanied by the loss of perennial grasses and bush encroachment, affects more than 10% of the world’s drylands, thereby placing increasing pressure on rangelands and farmers’ livelihoods. In Namibia, rangeland desertification is exacerbated by external shocks such as droughts, market changes, and new regulatory frameworks that have led to profound social and ecological changes within this tightly coupled social–ecological system (SES). In this context, the interrelationship among system components, drivers, and external factors, as well as the impact of strategies to halt desertification, remain poorly understood. The present study employed a retrospective mixed-methods approach to investigate the drivers of desertification on Namibia’s freehold farms by applying the social–ecological trap (SET) concept. Our approach combined remote sensing methods with semi-structured interviews and a literature review. The aim was to decipher the underlying processes and self-reinforcing feedback loops and to identify associated changes in the social and ecological subsystem. Our results revealed that inadequate grass availability, coupled with income deficits, serves as a pivotal catalyst for rangeland desertification, perpetuating a self-reinforcing feedback loop. To avoid or mitigate the effects of ecological regime shifts and to help farmers escape the SET of desertification, it will be necessary to implement changes in the dominant feedback loops through long-term risk mitigation strategies, such as rangeland restoration measures, as well as on- and off-farm income diversification. These strategies will provide a foundation for subsequent research on effective long-term mitigation strategies to prevent further rangeland desertification and to secure the livelihoods of farmers. Full article

Island ecosystems are vulnerable, as natural disasters and inappropriate anthropogenic activities can easily disrupt the ecological balance, posing significant challenges to the delivery of ecosystem services. In order to evaluate the ecosystem service functions of the Zhoushan Archipelago, based on the InVEST model, the four services of water conservation, carbon storage, habitat quality, and soil conservation in the Zhoushan Archipelago in 2017, 2020, and 2023 were estimated, and the spatial pattern of comprehensive ecosystem service function was determined by principal component analysis. The results showed the following: (1) the spatial distribution of water conservation, carbon storage, habitat quality, and soil conservation values in 2017, 2020, and 2023 show the same trend, with high values distributed in the central areas of Zhoushan Island, Changtu Island, Taotao Island, and Qushan Island, and low values distributed in the coastal areas of Zhoushan Island, Yangshan Island, and Yushan Island; (2) land use types have a significant effect on four services. Trees, built areas, rangeland, and cropland were the primary contributors to these four ecosystem services; (3) from 2017 to 2023, the highly important areas and extremely important areas showed a decreasing trend. In 2023, the highly important areas and extremely important areas accounted for 17.29% and 2.33% of the total area, which are important for maintaining the virtuous cycle of the ecosystem. This study provides a scientific basis for the sustainable development of the island. Full article

Social conflict over rangeland-use priorities, especially near protected areas, has long pitted environmental and biodiversity conservation interests against livestock livelihoods. Social–ecological conflict limits management adaptation and creativity while reinforcing social and disciplinary divisions. It can also reduce rancher access to land and negatively affect wildlife conservation. Communities increasingly expect research organizations to address complex social dynamics to improve opportunities for multiple ecosystem service delivery on rangelands. In the Greater Yellowstone Ecosystem (GYE), an area of the western US, long-standing disagreements among actors who argue for the use of the land for livestock and those who prioritize wildlife are limiting conservation and ranching livelihoods. Researchers at the USDA-ARS US Sheep Experiment Station (USSES) along with University and societal partners are responding to these challenges using a collaborative adaptive management (CAM) methodology. The USSES Rangeland Collaboratory is a living laboratory project leveraging the resources of a federal range sheep research ranch operating across sagebrush steppe ecosystems in Clark County, Idaho, and montane/subalpine landscapes in Beaverhead County, Montana. The project places stakeholders, including ranchers, conservation groups, and government land managers, in the decision-making seat for a participatory case study. This involves adaptive management planning related to grazing and livestock–wildlife management decisions for two ranch-scale rangeland management scenarios, one modeled after a traditional range sheep operation and the second, a more intensified operation with no use of summer ranges. We discuss the extent to which the CAM approach creates opportunities for multi-directional learning among participants and evaluate trade-offs among preferred management systems through participatory ranch-scale grazing research. In a complex system where the needs and goals of various actors are misaligned across spatiotemporal, disciplinary, and social–ecological scales, CAM creates a structure and methods to focus on social learning and land management knowledge creation. Full article