Rangeland Ecosystems Research Articles

Assessing the proximate compositions of indigenous forage species in Yemen's pastoral rangelands.

Plant diversity in southern Yemen is crucial for maintaining rangeland ecosystem functions. This diversity contributes to the resilience of local pastoral communities, by providing essential forage and resources. However, high stocking density has led to the overuse of palatable species, resulting in increased competition for forage. This study evaluates the nutritional value of 25 indigenous forage species from the natural rangelands of Lahij Governorate. Significant variations were observed among the Forage species, with moisture content ranging from 4 to 39.6%, crude protein from 5.5 to 21.4%, non-fiber carbohydrates from 31.8 to 66.4%, crude fiber from 8.3 to 42.65%, and ash content from 9.2 to 34.6%. Clitoria ternatea, Lycium barbarum, Senegalia mellifera, Vigna sinensis, Albizia lebbeck, and Acacia trees with crude protein content higher than 16% showed substantial potential as livestock feed due to their favorable proximate compositions. Incorporating these high-potential species into regular livestock diets could significantly enhance the sustainability and productivity of pastoral systems in southern Yemen, addressing the current fodder shortage.

ВЛИЯНИЕ ИЗМЕНЕНИЯ КЛИМАТА НА ПАСТБИЩНЫЕ ЭКОСИСТЕМЫ АТЫРАУСКОЙ ОБЛАСТИ РЕСПУБЛИКИ КАЗАХСТАН

Grasslands are an important and vulnerable resource among many ecosystems that occupy a large part of the earth's surface. These ecosystems are constantly exposed to various climatic factors, and climate change is becoming one of the main threats to them. Pastures occupy 9612.9 thousand hectares of the territory of Atyrau oblast, which is 81% of the total territory. These lands are an important source for livestock breeding. In this paper we assessed the potential impact of climate change on pasture ecosystems of Atyrau oblast of the Republic of Kazakhstan. The spatial and temporal variability of precipitation for 30 years (1992-2022) was investigated using meteorological data. The fluctuations of precipitation amount in vegetation period (April - September) for 1992-2022 were determined. Multiyear series of average annual air temperature and precipitation during vegetation vegetation period were analysed and their predicted cyclic fluctuations for the next two years were modelled. Degradation points of pasture ecosystems were identified by counting 622 points in 1992, 585 points in 2002, 412 points in 2012 and 387 points of former and current cattle stands in 2022 through Google Earth map. The heat and moisture availability of the growing season of pasture plants under climate change was predicted. The results of this study show how increasing temperature, decreasing precipitation, and management history affect pasture quality, and highlight the important role of vegetation of rangeland ecosystems. The results can be used in the process of establishing effective rangeland management practices, mechanisms for adaptation of rangeland vegetation or ecosystems to climate change.

Invasive annual grasses destabilize plant communities in a northern mixed‐grass prairie

AbstractTemporal community stability, here defined as temporal mean divided by temporal SD, plays an important role in predicting certain ecosystem services. However, temporal stability can change with invasion, with greater abundances of invasive species potentially having greater impacts on native community stability. The exact consequences of invasion for temporal stability are unclear and, in part, depend on the particular metric of stability measured. In rangeland ecosystems, predicable forage is important for livestock production but can be threatened by invasion. Therefore, using an observational field study conducted over three years in Wyoming, we assessed which metrics of plant community stability were altered by invasion and whether those effects were mediated by two environmental variables (light and soil moisture). Bromus arvensis and Bromus tectorum are two invasive annual weeds found across US rangelands, including the northern mixed‐grass prairies of Wyoming. We established plots along natural invasion blocks of B. arvensis and B. tectorum abundance and collected plant species composition data over three growing seasons. We tested associations between seven different metrics of plant community stability and invasion by B. arvensis and B. tectorum. We found that species turnover increases with invasion by both species, while stability of forb (both brome species), C4 grass (B. arvensis only), and C3 grass (B. tectorum only) cover decreases with invasion. All metrics of stability associated with invasion supported the hypothesis of a destabilizing effect of invasion on the native plant community. Further, we found that light and soil moisture did mediate some associations between stability and invasion. Overall, our results align with previous work suggesting that invasive annual bromes can lead to decreased native plant stability, which has important implications for forage production and, thus, food security.

Evaluating variation of respiration:photosynthesis ratio in sagebrush species: Implications for carbon flux modeling

AbstractPlant respiration and photosynthesis are the two main processes influencing carbon (C) flux balance at leaf‐to‐ecosystem scales. The ratio of respiration to photosynthesis (R:A) or carbon use efficiency (CUE) is considered an important trait for determining global carbon storage in the near future. One school of thought assumes that R:A is constant in terrestrial productivity models, irrespective of biomass, climate, and species. Others believe it is variable, although within a limited range. Semiarid systems dominated by woody vegetation, such as sagebrush steppe, have been recognized as potentially important C sinks on regional to global scales in the context of future climate scenarios. Therefore, there is a critical need to study R:A over different organizational scales (i.e., at the leaf, whole plant, and ecosystem scales) to use this approach for future C flux predictions under climate change scenarios. The objective of this study was to compare leaf‐, shrub‐, and ecosystem‐scale R:A among three sagebrush (Artemisia spp.) communities, and to determine how R:A varies throughout the growing season (i.e., early, mid‐, and late summer) among these communities. We measured photosynthesis and respiration monthly in three sagebrush communities spanning a 685‐m elevation gradient at the Reynolds Creek Experimental Watershed and Critical Zone Observatory in southwestern Idaho. Consistent with our expectations, we found large seasonal variations in R and A at all scales, but with differences in A among the three sagebrush communities significant only at the leaf scale. The R:A ratio was not significantly different among the three species at all organizational scales. However, the R:A ratio did vary among months at the leaf level and there was a statistical interaction between species and month at both leaf and shrub levels. Our study indicates that the R:A ratio is generally conservative, although not tightly constrained (range: 0.12–0.77) among three sagebrush species. Therefore, approaches that assume conservative R:A ratios in terrestrial productivity models need to be considered carefully to evaluate the impact of projected climatic changes on future C cycling in shrub‐dominated rangeland ecosystems.

Granular Bait Applications for Management of Rangeland Grasshoppers Using a Remotely Piloted Aerial Application System

Rangeland grasshoppers are an endemic species that play an essential role in the rangeland ecosystem but can cause severe economic damage when populations reach outbreak levels. Remotely piloted aerial application systems (RPAASs) offer an alternative method to carry out aerial insecticide applications in relatively small areas. The objective of this study was to investigate the efficacy of a granular bait, 2% Sevin (with the active ingredient carbaryl), applied by an RPAAS. The bait was applied on four replicated 4.05-hectare (10-acre) plots at a rate of 2.27 kg/ha (5 lbs/acre) with an RPAAS on a private ranch in New Mexico. Applications resulted in a normalized population reduction of 70.32% ± 16.54% standard error of the mean (SEM) of bait-susceptible species. Although some of the observed reduction in population may be attributed to aging, the net effect was most likely due to the ingestion of bait based on field observations of rapid mortality after ingestion and other factors, like past experience with carbaryl bait treatments on grasshoppers. Plots required at least two flights due to the Federal Aviation Administration’s (FAA) maximum takeoff weight requirement for small RPAASs. Combined, these results indicate that RPAASs can provide treatment capabilities in relatively small areas, i.e., population hotspots, preferably before outbreak levels are reached.

Exploring Relationships Between Drought Indices and Ecological Drought Impacts Using Machine Learning and Explainable AI

Rangeland ecosystems in the United States hold great ecological, economic, and cultural value. However, the increasing frequency and severity of droughts pose potential threats to these ecosystems. This study used remotely sensed data, machine learning, and explainable artificial intelligence (XAI) to explore relationships between drought indices and vegetation health in the Cheyenne River Basin, USA. The study employed XGBoost Regressor and Extra Trees Regressor models in conjunction with SHapley Additive exPlanations (SHAP) to identify the most influential drought indices and environmental variables for predicting Normalized Difference Vegetation Index (NDVI), thereby uncovering indicators of vegetation stress in the basin. The XGBoost regressor was moderately successful at predicting NDVI, making the model suitable for subsequent XAI analysis using SHAP. SHAP results revealed that the Palmer Drought Severity Index (PDSI), the 90-day Standardized Precipitation Index (SPI), and snow water equivalent (SWE) were the most influential predictors of NDVI, indicating their strong association with changes in vegetation health in the Cheyenne River Basin. This study demonstrates the feasibility and value of applying XAI methods to investigate both the strength and directionality of ecological drought indicators—an approach that has been underutilized in drought research. These insights can inform future drought research, improve monitoring efforts, and help anticipate ecological drought impacts in the region.

Fine spatial scale assessment of structure and configuration of vegetation cover for northern bobwhites in grazed pastures

BackgroundMonitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat. Traditional ground-based sampling methods have been widely used and provide valuable information; however, they are time-consuming, labor-intensive, and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems. Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms. Our objectives were to (1) assess the accuracy of vegetation cover height in grasses using drones, (2) quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant (fall–winter) and growing seasons (spring–summer), and (3) evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite (Colinus virginianus) habitat in South Texas. We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration.ResultsEstimated heights from drone imagery had a significant relationship with the field height measurements in September (r2 = 0.83; growing season) and February (r2 = 0.77; dormant season). Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022–2023 following grazing. Dormant season pasture had an increase in bare ground cover, and a shift from many large patches of tall herbaceous cover (40–120 cm) to few large patches of low herbaceous cover (5–30 cm) (p < 0.05).ConclusionsDrones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing. This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.

Controlled Grazing as a Pathway for Enhancing Investment in Multipurpose Trees and Welfare

AbstractIn Africa, rangeland ecosystems have been exploited due to heavy and unsustainable grazing. Policy and institutional mechanisms such as integrating silvopastoral systems with sustainable grazing practices have been devised to mitigate the negative effects. In this study, we investigated whether the uptake of sustainable grazing management in the form of controlled grazing spurs investment in multipurpose trees (MPTs) and enhances income. Using instrumental variable regression, we find that controlled grazing increases not only the propensity to plant MPTs but also the number of tree species. More importantly, IV and treatment effect results indicate that controlled grazing enhances income from MPTs.

No Field Evidence of Grass Fuel Structure effects on Postfire Tree Mortality in Juniperus virginiana

Prescribed fires are an important management tool for containing woody plant encroachment in rangeland ecosystems. Grasses are the dominant fuel type in rangelands. Past work has shown that grass canopy architecture, which varies among grass species, can influence flammability. Whether variation in grass fuel structure can influence postfire plant responses has not yet been tested. To bridge this gap, we set up field burning experiments with different fuel treatments and examined postfire mortality of Juniperus virginiana L. in a tallgrass prairie in southwestern Missouri. We sampled 60 trees and measured tree height and diameter at breast height before the fire. Fuels surrounding each tree were manipulated to vary independently in both fuel load and fuel structure. Flame temperatures were measured during the fire, and both stem and canopy injuries were evaluated 1 d after the fire. We surveyed tree mortality 7 mo after the fire. We found no effects of either fuel load or fuel structure on postfire mortality or on canopy injury in J. virginiana. Canopy injury was a critical fire severity measurement determining postfire mortality in J. virginiana, and taller trees are more fire resilient. Despite laboratory-observed fuel structure effects on flammability, this study finds no evidence for the importance of grass fuel load and canopy architecture in influencing postfire tree response. This result might arise from the low crown depth and low canopy water content of J. virginiana, which can promote canopy fire and result in a high mortality rate across fuel treatments. Notwithstanding the negative results, testing laboratory-based findings in field settings is important for further examining laboratory observations and upscaling individual-level processes to ecosystems to help identify the key ecological processes determining population dynamics and community assembly. Our study also suggests that prescribed fire is an effective tool to remove encroaching J. virginiana in tallgrass prairies at an early stage.

Landowner Perceptions toward Adopting Patch-Burn and Mixed-Species Grazing for Rangelands in the U.S. Southern Great Plains

AbstractThe sustainability of grazed rangelands can be improved by adopting innovative management practices that enhance the ecological resilience, productivity, and long-term viability of rangeland ecosystems. This study applied a bivariate Multiple Indicator–Multiple Causation model to examine how landowner characteristics are associated with their perceptions concerning patch-burn grazing (PBG) and mixed-species grazing (MSG). Data were collected through a mail survey of landowners in the Southern Great Plains who own at least 100 acres. The significant and positive correlation between PBG and MSG suggests that their relative preference tends to change together, potentially allowing them to complement when implemented together.

Do we need post-tree thinning management? Prescribed fire and goat browsing to control woody encroacher species in an Ethiopian savanna

Worldwide, bush encroachment threatens rangeland ecosystem services, including plant biodiversity and forage for livestock. Various control methods for encroaching woody species and restoring herbaceous vegetation exist but have rarely been explored experimentally. We assessed the impact of post-tree thinning management on tree mortality, the herbaceous community, and overall rangeland condition in Borana, an Ethiopian savanna ecosystem. At two 1.4 ha areas of encroached mono-specific Vachellia drepanolobium (whistling thorn) stands, we set up twenty-four 20 × 10 m experimental plots with four post-tree-thinning treatments (goat browsing only (1), prescribed fire (2), fire and goat browsing (3), and control (4) (i.e., no management after tree cutting), with three replications in a complete block design. Over two growing periods, we monitored resulting tree mortality, coppicing, seedling mortality and recruitment, as well as herbaceous layer attributes (diversity, biomass) and overall rangeland condition. All three post-tree thinning management scenarios significantly enhanced tree mortalities, reduced seedling recruitment and increased the abundance of the dominant desirable grass species. Prescribed fire and fire and goat-browsing treatments resulted in significantly greater grass and forb species richness, forb diversity, and biomass, as well as the overall rangeland condition compared to goat browsing only and the control treatment. However, grass species diversity did not respond to treatments. Post-tree management significantly increased tree mortality, reduced seedling recruitment, and increased the abundance of desirable grass species. Our findings strongly suggest that post-thinning management, particularly prescribed fire or a combination of fire and browsing, is highly effective in suppressing woody encroachment and improving biomass and overall rangeland condition.

Utilizing Artificial Intelligence and Remote Sensing to Detect Prosopis juliflora Invasion: Environmental Drivers and Community Insights in Rangelands of Kenya.

The remarkable adaptability and rapid proliferation of Prosopis juliflora have led to its invasive status in the rangelands of Kenya, detrimentally impacting native vegetation and biodiversity. Exacerbated by human activities such as overgrazing, deforestation, and land degradation, these conditions make the spread and management of this species a critical ecological concern. This study assesses the effectiveness of artificial intelligence (AI) and remote sensing in monitoring the invasion of Prosopis juliflora in Baringo County, Kenya. We investigated the environmental drivers, including weather conditions, land cover, and biophysical attributes, that influence its distinction from native vegetation. By analyzing data on the presence and absence of Prosopis juliflora, coupled with datasets on weather, land cover, and elevation, we identified key factors facilitating its detection. Our findings highlight the Decision Tree/Random Forest classifier as the most effective, achieving a 95% accuracy rate in instance classification. Key variables such as the Normalized Difference Vegetation Index (NDVI) for February, precipitation, land cover type, and elevation were significant in the accurate identification of Prosopis juliflora. Community insights reveal varied perspectives on the impact of Prosopis juliflora, with differing views based on professional experiences with the species. Integrating these technological advancements with local knowledge, this research contributes to developing sustainable management practices tailored to the unique ecological and social challenges posed by this invasive species. Our results highlight the contribution of advanced technologies for environmental management and conservation within rangeland ecosystems.

Seasonal monitoring of biochemical variables in natural rangelands using Sentinel-1 and Sentinel-2 data

ABSTRACT Rangelands are natural ecosystems that serve as essential sources of forage for domesticated livestock and wildlife. Therefore, accurately mapping nutrient levels in rangelands is crucial for sustainable development and effective management of grazing animals. Remote sensing tools offer a reliable means to explore nutrient concentrations across large spatial areas. This study aimed to estimate and map seasonal foliar concentrations of nitrogen (N), phosphorus, and neutral detergent fibre (NDF) in mesic tropical rangelands of Limpopo using Sentinel-1, Sentinel-2, and the integration of S1 and S2 data. Fieldwork was conducted to collect samples for seasonal foliar nutrients (N, P, and NDF) during early-summer (November-January 2020), winter (July-August 2021), and late-summer (February-March 2022). Various conventional and red-edge-based vegetation indices were computed. The results demonstrate that integration data from S1 and S2 can effectively estimate and predict foliar concentrations of N, P, and NDF in mesic rangelands throughout the seasons, achieving R2 values of 0.76, 0.78, and 0.71, with corresponding RMSE values of 0.13, 0.04, and 2.52. Notably, red-edge variables emerged as the most significant parameters for predicting seasonal N, P, and NDF concentrations. Additionally, factors such as season and slope significantly influenced the distribution and occurrence of these foliage nutrients, with higher foliage production observed during late-summer and on steeper slopes. The study concludes that the integration of S1 and S2 data can effectively monitor the seasonal dynamics of biochemical parameters. This finding holds significant implications for policymakers and rangeland users, offering a comprehensive understanding of the intricate variations within rangeland ecosystems. Further research could expand on these findings by applying the knowledge to various datasets, exploring different rangelands, and examining additional ecological factors such as slope altitude to detect foliar fibre biochemicals. Finally, the applications of this research extend beyond individual properties, providing practical tools for sustainable rangeland management and informed decision-making in resource utilization and conservation.

Application of Normalized Radar Backscatter and Hyperspectral Data to Augment Rangeland Vegetation Fractional Classification

Rangeland ecosystems in the western United States are vulnerable to climate change, fire, and anthropogenic disturbances, yet classification of rangeland areas remains difficult due to frequently sparse vegetation canopies that increase the influence of soils and senesced vegetation, the overall abundance of senesced vegetation, heterogeneity of life forms, and limited ground-based data. The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project provides fractional vegetation cover maps across western North America using Landsat imagery and artificial intelligence from 1985 to 2023 at yearly time-steps. The objectives of this case study are to apply hyperspectral data from several new data streams, including Sentinel Synthetic Aperture Radar (SAR) and Earth Surface Mineral Dust Source Investigation (EMIT), to the RCMAP model. We run a series of five tests (Landsat-base model, base + SAR, base + EMIT, base + SAR + EMIT, and base + Landsat NEXT [LNEXT] synthesized from EMIT) over a difficult-to-classify region centered in southwest Montana, USA. Our testing results indicate a clear accuracy benefit of adding SAR and EMIT data to the RCMAP model, with a 7.5% and 29% relative increase in independent accuracy (R2), respectively. The ability of SAR data to observe vegetation height allows for more accurate classification of vegetation types, whereas EMIT’s continuous characterization of the spectral response boosts discriminatory power relative to multispectral data. Our spectral profile analysis reveals the enhanced classification power with EMIT is related to both the improved spectral resolution and representation of the entire domain as compared to legacy Landsat. One key finding is that legacy Landsat bands largely miss portions of the electromagnetic spectrum where separation among important rangeland targets exists, namely in the 900–1250 nm and 1500–1780 nm range. Synthesized LNEXT data include these gaps, but the reduced spectral resolution compared to EMIT results in an intermediate 18% increase in accuracy relative to the base run. Here, we show the promise of enhanced classification accuracy using EMIT data, and to a smaller extent, SAR.

Rangelands and Pastoralism in Globalized Economies: Policy Paralysis and Legal Requisites

Growing quest for globalization and expanding economies have resulted into fragmentation, enclosure, grabbing, militarization and devastation of rangelands. Grasslands – covering 70% of the global agricultural area – are the basis for livestock production. In most of the countries, governments have little recognition of communal tenures of agro-pastoralists. Consequently, both pastoralists and rangeland ecosystems have suffered a grim fate. On the contrary, the subsistence pastoralism is an established sustainable strategy of livelihood and ecosystem conservation in the rangelands. Unfortunately, some of the most nutritive foods and other sustainable products of nomadic pastoralists have not desirably been priced in modern markets. With the demonstrated cases exhibiting the nomadic pastoralists, such as Hutsul shepherd communities of Ukraine, as most sustainable societies on planet Earth, there is urgent need for reshaping the popular paradigm and State policies on rangeland commons. In isolation of pastoralist people, the rangelands cannot truly be conserved or protected. To begin with, the resilience of pastoralists to the changing environments and their (unique) rangeland management can first be pondered. Accordingly, the policy and legal frameworks of States need to be reoriented and revised. In particular, Eurasian countries should review their laws and policies on rangeland sustainability and pastoral grazing.

A comparison and development of methods for estimating shrub volume using drone‐imagery‐derived point clouds

AbstractShrub volume is used to calculate numerous, essential ecological indicators in rangeland ecosystems such as biomass, fuel loading, wildlife habitat, site productivity, and ecosystem structure. Field techniques for biomass estimation, including destructive sampling, ocular estimates, and allometric techniques, use shrub height and canopy widths to estimate volume and translate it to biomass with species‐specific allometric equations. These techniques are time‐consuming and pose challenges, including removal of plant material and training of observers. We compared canopy volume estimates from field‐based measurements with drone‐collected canopy volume estimates for seven dominant shrub species within mountain big sagebrush (Artemisia tridentata subsp. vaseyana) plant communities in southern Idaho, USA. Canopy height and two perpendicular width measurements were taken from 103 shrubs of varying sizes, and volume was estimated using a traditional allometric equation. Overlapping aerial images captured with a DJI Mavic 2 Professional drone were used to create a 3D representation of the study area using structure‐from‐motion photogrammetry. Each shrub was extracted from the point cloud, and volume was estimated using allometric and volumetric methods. The volumetric method, which involved converting point clouds to raster canopy height models with 2.5‐ and 5‐cm grid cells, outperformed the allometric method (R2 &gt; 0.7) and was more reproducible and robust to user‐related variability. Drone‐estimated volume best‐matched field‐estimated volume (R2 &gt; 0.9) for three larger species: A. tridentata subsp. tridentata, A. tridentata subsp. vaseyana, and Purshia tridentata. The volume of smaller shrubs (canopy widths &lt;1 m) was slightly overestimated from drone‐based models. We argue that drone‐based models provide a suitable alternative to field methods, while having the added benefit of being less time‐consuming, with fewer limitations, and more easily scaled to larger study areas than traditional field techniques. Finally, we demonstrate a proof of concept for automating canopy volume estimates using point‐cloud‐based automatic shrub detection algorithms. These findings demonstrate that drone‐collected images can be used to assess shrub canopy volume for at least five upland sagebrush steppe shrub species and support the integration of drone data collection into rangeland vegetation monitoring.

Effects of land-use intensity on vegetation dynamics across elevation in Savanna Grassland, Southern Ethiopia

The rangeland ecosystem is currently one of the area’s most sensitive to biodiversity because of both natural and human effects. There is still much to learn about the sustainable management of dry and semi-arid rangelands in order to protect their rich biodiversity resources. This is due to the uncertain indirect effects of environmental factors, such as dryness, on vegetation species, which are mediated by shifting both living and non-living components. The purpose of this project was to ascertain the effects of land use intensity (LUI) on the various species of rangeland flora along the elevation gradient in the Borana Rangeland. We gathered a total of 37 plant species, comprising 22 grasses, 7 graminoids, and 8 forbs, from the nine sampling locations, which were exposed to LUI and included three locations within each elevation range of 500–900, 1000–1400, and 1500–1900 m.a.s.l. At every sampling site, we evaluated the dynamics of the plant species, taking into account their diversity, richness, percentage of undesirable species, and properties of the soil. We used structural equation modeling (SEM) to examine the effects of LUI on the different vegetation species along the elevation gradient. We found that the density and diversity of vegetative species decreased and the fraction of undesired species increased as elevation climbed (from lower to higher). Because of the heavy livestock grazing, these impacts were substantially linked with high LUI at lower elevations. According to our research, the complex relationships between elevation gradient and LUI have a big influence on the diversity and density of the flora. This demonstrates that we need to account for environmental gradients in order to generalize LUI's effects on rangeland biodiversity. This study sheds important light on the complex interactions between vegetation dynamics and LUI in savanna grasslands. To create practical strategies for maintaining ecosystem health and biodiversity in the Southern Ethiopian Savanna Grasslands, policymakers, environmentalists, and land managers should take these findings into account.

Rangeland afforestation is not a natural climate solution

Large‐scale tree planting on global rangelands is promoted as a natural climate solution (NCS), but there is little scientific evidence to support this narrative. The presumed benefits of rangeland afforestation originate from five major misconceptions: (1) conflation between reforestation and afforestation, (2) overestimation of carbon (C) sequestration potential, (3) insufficient recognition of rangeland ecosystem services, (4) potential for adverse ecological outcomes, and (5) neocolonial tendencies of afforestation programs. Rangeland afforestation possesses minimal potential for additional C storage, but it has high potential to reduce vital rangeland ecosystem services that benefit rangeland residents and non‐residents alike. Conservation of existing C—most of which is stored belowground, where it is less vulnerable to loss—may prove to be the most appropriate NCS for extensively managed rangelands. Stewardship strategies promoting rangeland multifunctionality will not only contribute to climate‐change mitigation but also support biodiversity conservation and sustainable production of high‐protein foods for marginalized populations.

Soil health reduction following the conversion of primary vegetation covers in a semi-arid environment

A degraded forest is the outcome of a degradation process that has adverse effects on ecosystem functions and services. This phenomenon results in alterations of soil physicochemical and biological properties, which serve as valuable indicators for assessing soil health that has been recognized as a crucial component of soil quality. For several decades, the conversion of forested areas into rangeland has been documented in specific regions of the world. There is a widespread lack of global understanding regarding the lasting consequences of land degradation on soil health indicators. The present study aims to investigate the impact of forest degradation on soil health indicators in a mountainous semi-arid region located in northern Iran. The study area was predominantly forested, but due to human activities over the past 30 years, it has been transformed into three distinct land uses: forest, forest-rangeland ecotones and rangeland. In each of these land covers, a total of 20 litter (O-horizon) and 20 soil (from two depths of 0–15 and 15–30 cm) samples were collected in the summer (August 2022) season. According to our results, the highest litter thickness, P and Mg were in forest ecosystem, the lowest in rangeland ecosystem. The findings indicated that following the conversion of forest to rangeland, there was a decrease in soil aggregate stability, porosity, soil organic matter, POC, PON, NH4+, NO3− and nutrient levels, while soil bulk density increased. The forest ecosystem showed notably higher C and N stocks (45 and 5.21 Mg ha−1) in comparison to the rangeland (38 and 3.32 Mg ha−1) ecosystem. In addition, P, K, Ca, and Mg exhibited elevated levels within the total root of the forest ecosystem (2.12, 1.23, 0.71, and 0.38 %, respectively), whereas the lower values (1.29, 1.01, 0.43, and 0.23 %, respectively) were found in the rangeland ecosystem. Following the shift of land cover from forest to rangeland, soil fauna, microflora populations, soil enzymes and microbial activities decreased (about 1–2 times higher in the forestland). This research emphasizes the urgent need to advance sustainable management practices to prevent further degradation and promote the implementation of restoration or rehabilitation techniques in degraded forests. Despite being conducted in a semi-arid region situated in northern Iran, the findings of this study have considerable value for the sustainable management of soil and land conservation in various other semi-arid regions around the world.

Shrub encroachment and stakeholder perceptions of rangeland ecosystem services: balancing conservation and management?

Shrub encroachment and stakeholder perceptions of rangeland ecosystem services: balancing conservation and management?