Grassland Conservation Research Articles

Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic vegetation model: Case study in Wallonia, Belgium.

Accurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R2>0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R2=0.77) and ESA-CCI (R2=0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480gC m-2 yr-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110MtC under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728gC m-2 yr-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.

Depletion of fenbendazole sulfone residues in Northern Bobwhite (Colinus virginianus) liver following medicated feed treatment.

Northern bobwhite quail (Colinus virginianus) are an important game bird that generates substantial revenue for rural communities and is also an important grassland conservation species. Unfortunately, Northern bobwhite populations have been declining across their range for over 50 years. In the southwest bobwhite range, parasites are suspected to contribute substantially to the decline. To test the relationship of parasites and wild Northern bobwhite populations, an anthelmintic medicated feed was developed. The medicated feed was then tested as part of the U.S. Food and Drug Administration registration process. Because Northern bobwhite are a game species and harvested birds are ingested by people, it was necessary to estimate the tissue clearance rate of the drug. This study examined how quickly the conjugated metabolite fenbendazole sulphone was cleared from quail liver. A validated LC/MS-MS method was used to determine clearance rate from pen-reared northern bobwhite fed the anthelmintic at 110 ppm in feed. Results of the tissue clearance study found the drug never exceeded the maximum allowable concentration of 6 ppm and was cleared from the liver in 9.38 hours. Based on the Center for Veterinary Medicine guidance for industry #3, a 0-day withdrawal period was assigned to the recently registered medicated feed in wild northern bobwhite. Thus, the anthelmintic fenbendazole was shown to be rapidly cleared from Northern bobwhite and represents a viable option for treating wild populations for parasite infections while treated game birds remain safe for human consumption.

Combining local monitoring data and scientific models to prioritize conservation for European ground squirrel and safeguard grassland habitats

ContextPromoting grassland habitat networks within agricultural landscapes is essential for supporting biodiversity. However, the characteristics of these networks are often poorly documented, making it difficult to prioritize conservation strategies and effectively protect grassland-dependent species.ObjectivesWe set to identify conservation priorities for (semi)natural grasslands by assessing habitat network characteristics based on a combination of monitoring data and scientific model output for European Ground Squirrel (EGS), a keystone grassland specialist, in agricultural settings of northern Serbia.MethodsWe used the spatially explicit model, LARCH, to determine the current habitat networks and available monitoring data on presence/absence and habitat suitability together with Circuitscape to better understand the characteristics of those networks. The combination of modeling results and monitoring data was used to prioritize conservation measures for each network to support a stable and viable EGS metapopulation.ResultsWe identified 15 habitat networks. Our analysis showed that two of these need no interventions, but most of them need a mix of improving habitat quality and connections within and between the networks to support local populations and the metapopulation overall.ConclusionsResults revealed areas in which spatial adaptation measures (e.g., grassland restoration and corridor development) should be deployed to accommodate the long-term survival of EGS. It might be considered to stop conservation efforts in some abandoned networks as the network characteristics are too poor, and resources should be used to improve habitat networks that are still occupied. Our findings may guide the conservation of (semi)natural grasslands and future sustainable land-use planning in intensively farmed landscapes.

Grazing Intensity Modifies Soil Microbial Diversity and Their Co-Occurrence Networks in an Alpine Steppe, Central Tibet.

Grazing intensity is one of the crucial anthropogenic activities on alpine grasslands. However, how grazing intensity affects soil microorganism diversities and their co-occurrence networks in alpine steppe remains uncertain. We carried out a controlled grazing experiment (null grazing, CK; moderate grazing, MG; and heavy grazing, HG) on a typical alpine steppe in the Lhasa River Basin, Central Tibet, China. We used high-throughput sequencing to find the sequences of bacterial 16S rRNA and fungal ITS gene amplicons. Then, we analyzed their alpha and beta diversities and set up co-occurrence networks that show how often they occur together. MG significantly increased the bacterial Shannon index and changed the bacterial community structure. In contrast, HG decreased the fungal ACE and Chao1 indices and also changed the fungal community structure (p < 0.05). Linear mixed-effect model revealed that available phosphorus in soil significantly impacted on soil bacterial Shannon, ACE, and Chao1 indices across grazing intensities, while total carbon in subsoil significantly affected these indicators of soil fungi. Moreover, MG increased the complexity of the co-occurrence network in the bacterial community, while HG simplified it. However, both MG and HG made the co-occurrence networks in the fungal community less complicated. This shows that the intensity of grazing has different impacts on how microbes interact with each other. Therefore, sustainable grazing intensity necessitates a deeper understanding of biodiversity conservation in alpine grasslands.

Earthquakes Have Accelerated the Carbon Dioxide Emission Rate of Soils on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau (QTP) has an extensive frozen soil distribution and intense geological tectonic activity. Our surveys reveal that Qinghai-Tibet Plateau earthquakes can not only damage infrastructure but also significantly impact carbon dioxide emissions. Fissures created by earthquakes expose deep, frozen soils to the air and, in turn, accelerate soil carbon emissions. We measured average soil carbon emission rates of 968.53 g CO2 m-2·a-1 on the fissure sidewall and 514.79 g CO2 m-2·a-1 at the fissure bottom. We estimated that the total soil carbon emission flux from fissures caused by M ≥ 6.9 earthquakes on the Qinghai-Tibet Plateau from 326 B.C. to 2022 is 1.83 × 1012 g CO2 a-1; this value is equivalent to 0.51% ~ 1.48% and 2.34% ~ 5.14% of the increased annual average carbon sink resulting from the national ecological restoration projects targeting forest protection and grassland conservation in China, respectively. These earthquake fissures thus increased the soil carbon emission rate by 0.71 g CO2 m-2·a-1 and significantly increased the total carbon emissions. This finding shows that repairing earthquake fissures could play a very important role in coping with global climate change.

Performance of Reward, Punishment, and Communication in Common-Pool Resource Management: Evidence from Grassland Conservation

Performance of Reward, Punishment, and Communication in Common-Pool Resource Management: Evidence from Grassland Conservation

Multi‐scale habitat selection and nest survival of whinchats and stonechats: implications for grassland conservation management

Effective management for endangered grassland birds requires a sound understanding of habitat requirements and factors shaping reproductive success. We studied multi‐level habitat selection of endangered whinchats Saxicola rubetra and locally increasing stonechats Saxicola rubicola in a nature reserve using Sentinel‐2 images, LiDAR data, and habitat variables measured onsite. We monitored nest fates, and estimated how the causes of nest mortality varied with nest initiation date. Further, we analyzed how nest‐site selection, precipitation, nest initiation date, and nest age influenced daily nest survival.At the landscape‐ and site‐level, both species primarily selected for territories in lightly farmed meadows. However, stonechats appeared to be less specialized and used most available habitat types. Within home‐ranges, both species selected for nest‐sites in fallow patches, but in contrast to stonechats, whinchats also selected for large viewsheds.In both species, the main causes of nest failure were predation by red foxes Vulpes vulpes, weather‐related factors, and nest desertion. In whinchats, the probability of nest desertion increased and predation risk decreased with nest initiation date, possibly due to better nest concealment in the later season. Daily nest survival decreased with nest age and precipitation in both species, and increased with nest initiation date in whinchats. None of the habitat variables examined were positively linked to daily nest survival, and viewshed was negatively related to whinchat daily nest survival.Our study suggests that extending core habitat may help to promote settlement and potentially reproductive success of whinchats. However, as habitat selection was not positively associated with daily nest survival, land management measures alone might not be sufficient to halt rapid population declines. To effectively conserve whinchats and other grassland bird populations, the causes of nest failures must be identified and addressed. Within the examined reserve and similar habitats, flood management and predator control may yield the biggest short‐term conservation gains.

Structural Characteristics and Driving Factors of Rhizosphere Microbial Communities in the Rhizosphere of Six Stipa Species Across the Ningxia Steppe

The relation and interaction of rhizosphere microbial communities with local environmental factors and root traits is currently a vibrant research hotspot. Yet little is known about how the morphological and functional properties of roots in steppe plants affect microbial community structure. Hence, this study investigated the rhizosphere soil of six Stipa species across the Ningxia steppe in China to examine how the composition of their microbial communities responds to both root traits as well as surrounding environmental factors. Our results reveal significant differences (p &lt; 0.001) in the composition of rhizosphere microbial communities among different Stipa species. The dominant bacterial and fungal phyla are Proteobacteria and Ascomycota, respectively; further, Mortierellomycota plays a key role in the fungal community and is closely associated with other fungal taxa. According to the functional gene predictions for bacteria and fungi, the rhizosphere microbes associated with Stipa species are mainly related to organic matter metabolism and nitrogen cycling. We find that soil physicochemical properties (SOC, TN, TP, AP, SWC, FL, SL) and root traits (RTD, Rtn) are pivotal factors which directly influence the structure of microbial communities dwelling in the rhizosphere of Stipa species. The dominant phyla of fungi and bacteria can respond to those properties in two contrasting ways. One group, consisting of bacteria such as Acidobacteria and fungi like Mortierellomycota, has a relative abundance that is positively correlated with soil nutrients (SOC, TN, AN, TP), whereas the second group, which includes bacteria such as Bacteroidetes and fungi like Ascomycota, is characterized by a negative correlation. More importantly, our results show that root traits significantly impact (p &lt; 0.001) fungal diversity, whereby the morphological and functional properties indirectly affect the composition of bacterial and fungal communities by modulating soil properties. Altogether, the findings suggest that the morphological and functional properties of Stipa roots play a prominent role in shaping the community structure of rhizosphere microbes in steppe, providing a theoretical basis for exploring changes in these communities across space and time, as well as offering insights for grassland conservation and sustainable management.

Landscape diversity, habitat connectivity, age and size determine the conservation value of limestone quarries for diverse wild bee communities

Abstract Abandoned and even active limestone quarries (excavation sites) can represent important secondary habitats for many species, including wild bees, associated with dry grasslands, which are threatened biodiversity hotspots in Europe. However, is not well understood how interactions between local habitat and landscape characteristics influence the value of limestone quarries for wild bees and how this could guide conservation schemes. We studied how wild bee communities in limestone quarries are affected by landscape variables (connectivity to neighbouring dry grasslands, landscape diversity), local quarry characteristics (area, age, woody vegetation cover, flowering plant species) and their interactions. We surveyed bee communities during 208 transects in 19 quarries in southern Lower Saxony, Germany. In total, we recorded 114 bee species (2360 individuals), including 35 endangered species. High flowering plant species richness positively affected bee abundance and richness. Large quarry area was important for determining the presence of endangered bee species. High levels of woody vegetation cover had a negative effect on bee abundance and richness. Bee abundance and richness can increase with quarry age, but only at sites with moderate woody vegetation cover. We found potentially positive interactions between quarry age and landscape diversity and/or habitat connectivity to neighbouring dry grasslands. In particular, high habitat connectivity ensured stable richness of endangered species in old quarries. Synthesis and applications. Observed negative effects of high woody vegetation cover on bee communities highlight the importance of local management to reduce shrub encroachment and reset successional processes in limestone quarries. Local management is particularly important in old quarries of great ecological value, where the adverse impact of high woody vegetation cover on wild bees appears to be most severe. Large and old quarries with high connectivity to neighbouring dry grasslands are especially valuable for endangered bee species. Therefore, landscape‐scale restoration and conservation of dry grasslands is the most promising approach to promote endangered bee species through enhanced habitat connectivity.

Unveiling and advancing grassland degradation research using a BERTopic modelling approach

Grassland degradation presents overwhelming challenges to biodiversity, ecosystem services, and the socio-economic sustainability of dependent communities. However, a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has <pg=>not been achieved due to the limitations of traditional scientometrics methods. The present synthesis of information employed BERTopic, an advanced natural language processing tool, to analyze the extensive ecological literature on grassland degradation. We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject. Our analysis identified key topics in the global grassland degradation research domain, including the effects of grassland degradation on ecosystem functions, grassland ecological restoration and biodiversity conservation, erosion processes and hydrological models in grasslands, and others. The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature. Compared to traditional scientometrics analysis, BERTopic provides a more comprehensive perspective on the research areas, revealing not only popular topics but also emerging research areas that traditional methods may overlook, although scientometrics offers more specificity and detail. Therefore, we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas. This study represents an emerging application of BERTopic algorithms in ecological research, particularly in the critical research focused on global grassland degradation. It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion. Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems, and it marks an important stride towards more sophisticated, data-driven analysis in ecology.

Herders’ willingness to accept for grassland grazing ban in northwest China

Payment for Ecosystem Services (PES) has been widely acknowledged as an effective tool for mitigating grassland degradation and enhancing ecosystem services provision. However, critical factors such as herders’ willingness to accept (WTA) preferences and their compensation expectations, are often overlooked, leading to insufficient effectiveness of PES initiatives. This study focused on grassland ecological compensation policy (GECP), quantifying herders’ WTA compensation for grassland grazing bans. Through face-to-face surveys and employing the contingent valuation method, we estimated households’ WTA for participating in a grassland conservation program aimed at bolstering ecosystem service provision. Our findings indicate that herders required an average compensation of 237 CNY mu-1 yr-1 to engage in the grazing ban program. Notably, our study revealed that herders’ environmental awareness positively influenced their willingness to participation, whereas larger family sizes were negatively correlated with WTA. Additionally, herders in better health, with higher livestock incomes or categorized as semi-herders, tended to accept lower compensation levels. These insights are crucial for improving the effectiveness of GECP and provide valuable reference points for similar analyses in economically disadvantaged and ecologically fragile regions.

Moderate grazing intensity and pika disturbance can enhance plant diversity and soil nutrient cycling in the alpine grasslands of the Qinghai-Xizang Plateau

Grazing livestock and pikas, as the primary herbivores in grasslands, influence the health of grassland ecosystems through activities such as feeding, burrowing, and trampling. This study reviews 86 articles and examines the effects of varying grazing levels and pika activity on alpine grassland vegetation and soil in the Qinghai-Xizang Plateau, providing scientific insights to guide grassland conservation efforts. The research shows that: 1) Both grazing and pika disturbance significantly reduce aboveground biomass (AGB) in alpine grasslands (p < 0.05). Moderate grazing increases diversity indices, while pika disturbance has the opposite effect. 2) As grazing intensity increases, there is a significant decrease in total nitrogen (TN), total phosphorus (TP), and soil organic matter (SOM) content (p < 0.05). However, moderate pika disturbance leads to a significant increase in TP and TN content (p < 0.05). 3) In grazing trials, bulk density (BD) and the Shannon-Wiener index are significant positive drivers. Conversely, during pika disturbance, the Shannon-Wiener index and total nitrogen (TN) act as significant positive drivers, while BD is a significant negative driver. The study's findings indicate that moderate grazing intensity and pika disturbance can enhance plant diversity indices in grasslands, as well as improve soil structure and nutrient levels. Therefore, establishing a reasonable grazing system and controlling the pika population are effective methods for managing alpine grasslands.

Grassland albedo as a nature-based climate prospect: the role of growth form and grazing

Abstract Nature-based solutions for mitigating climate change focus largely on land management to reduce carbon emissions and enhance carbon sequestration. Tree planting, commonly advocated for carbon offset, threatens grassland biodiversity and may induce positive radiative forcing (warming) by lowering albedo. Before making decisions about land-use changes in grasslands, an understanding of the fine-scale albedo of grassy versus woody vegetation is needed. Existing satellite-based albedo products offer global coverage with temporally fine, but spatially coarse, resolution, whereas fine-scale in situ grassland albedo data are sparse. We examined the hypotheses that albedo varies seasonally between grass type patches, between shrub and grass patches, and with grazing at the patch scale. Using a tripod-mounted albedometer, we quantified albedo of seven distinct grassland patches in South Africa’s eastern Karoo during early and late dormancy and growing seasons. Patches included intensely-grazed grazing lawn (Cynodon dactylon), grazed and less-grazed red tussock grass (Themeda triandra), grazed and less-grazed white tussock grass (Eragrostis lehmanniana), shrub (Pentzia incana) encroached grass, and bare ground. Season influenced albedo in all patches and, additionally, we found strong differences for the same period between years due to varying rainfall and temperature patterns. For grass-dominated patches, albedo differences were most pronounced during early dormancy, likely due to an effect of grass inflorescences. Albedo of intensely-grazed grazing lawns was consistently higher than other patches, except during early dormancy when white tussock grass albedo was equally high. We found no albedo difference between grazed and less-grazed tussock patches of either red or white grass. Shrub-encroached patches exhibited consistently lower albedo than other patches. Our findings underscore the nuanced relationship between grassland patches and albedo, with shrub encroachment, proposed afforestation, and certain grasses possibly increasing warming potential through reduced albedo. As climate initiatives extend into grasslands, understanding these patterns is essential for climate change mitigation and grassland conservation.

Population genomics of a specialized insect, Tetraopes texanus (Coleoptera: Cerambycidae), across a fragmented grassland system

Specialist insects are especially susceptible to loss of genetic diversity in the face of habitat destruction and fragmentation. Implementing effective conservation practices for specialist insects will benefit from knowledge of population structure and genetic diversity. Because insects are hyper-diverse, characterizing the population structure of all species within the insect community is untenable, even if focused within a particular habitat type. Thus, concentrating on a single species specialized to a particular habitat type is needed to infer general trends. Here, we investigate the range-wide population genetics of Tetraopes texanus Horn 1878 (Coleoptera: Cerambycidae), which provides a useful model of grassland insects due to its’ habitat specificity and unique biology. Tetraopes texanus occurs primarily in Texas and Oklahoma, into Northern Mexico, and possibly into eastern New Mexico but also occurs in Black Belt prairies of Mississippi and Alabama. Mitochondrial and nuclear DNA (RAD-seq) analysis identified two distinct population clusters of T. texanus corresponding to the Texas and Oklahoma population and the Mississippi and Alabama population. Demographic models indicate ongoing, though incomplete, isolation of the two populations, with estimated dates of divergence in the mid-Pleistocene, coinciding with the end of a glacial period and a shift in glacial interval. These results can inform conservation of grassland adapted insects and offers insight to the biogeography of the Gulf Coastal Plain.

Livestock grazing strengthens the effect of vole activity on the soil microbial community

Livestock grazing may affect small mammalian herbivore-soil microbe interactions and their association with the structure and functions of the ecosystem. However, the role of factors such as vegetation and soil nutrients in regulating these impacts is not clear. Here we conducted a 9-year experiment in temperate steppe to study how Brandt’s vole (Lasiopodomys brandtii) affects the soil microbial community under different livestock grazing intensities. This experiment contained 12 field enclosures with three livestock grazing intensities: control (CK), light grazing (LG), and moderate grazing (MG). We found that vole activity does not significantly change soil microbial diversity under non-grazing conditions. However, under livestock grazing conditions, vole activity led to a significant reduction in soil bacterial diversity and an increase in fungal diversity, demonstrating the impacts of livestock grazing on rodents-soil microbe interactions. The activity of voles significantly altered soil bacterial community composition, with changes primarily attributed to variations in the relative abundance of the phyla Actinobacteria, Bacteroidetes, Firmicutes, Gemmatimonadetes, and Proteobacteria. The soil fungal community remained relatively stable despite vole activity, which can be attributed to the richness of fungal colonies in mycelium and their low sensitivity to changes in external conditions. Vole activity also influenced soil microbial functional groups, and the variations in these groups were further amplified by livestock grazing. Furthermore, the shift in the microbial community composition and diversity induced by vole activity were mainly associated with the reduction of plant aboveground biomass. Overall, our study suggested that livestock grazing enhanced the changes in the soil microbial community induced by rodents, underscoring the importance of managing livestock grazing regimes for grassland conservation.

Combining private and common property management: The impact of a hybrid ownership structure on grassland conservation

This study finds that a hybrid property structure, where private ownership and communal ownership coexist, outperforms pure private or pure public ownership in terms of grassland conservation after a grassland tenure reform in China. The tenure reform of privatization replaced public ownership gradually and led to a significant 5.4% increase in grassland quality on average. The grassland quality increase is twice as large for private grassland with additional access to public grassland compared to those without such access. Interestingly, public grassland quality did not decline, indicating sustainable utilization by herders. These findings are consistent with the literature which suggests that a properly structured hybrid ownership arrangement could benefit from the positive effects of grassland privatization while mitigating the negative impacts of natural disasters. We further provide empirical support and show that the gains from public grassland access are substantially larger when there are adverse climatic shocks. Our study provides important policy implications for property rights and sustainable grassland management under more frequent climate events.

Mechanical mowing of semi‐natural grasslands compromises soil quality and survival of a conservation target plant species

Mowing is a crucial management strategy for conservation and restoration of semi‐natural grasslands. In the past decades, dominant mowing methods have changed from manual to mechanical, using heavy machines causing soil compaction. Whereas the negative effects of compaction are well understood in agriculture and forestry, they have received little attention so far in nature management. This study aims to investigate the effects of compaction on soil quality, arbuscular mycorrhizal fungal communities, and survival of a target plant species. We subjected seven grasslands to three contrasting mowing types: manual mowing with a brush cutter, softtrack mowing—designed to minimize soil compaction—and tractor mowing. We compared compaction, soil properties, and arbuscular mycorrhizal communities among the types. Additionally, we experimentally subjected intact grassland sods containing Devil's bit scabious (Succisa pratensis Moench), a target species of grassland conservation, to compaction levels corresponding to the three mowing types. Subsequently, we assessed plant survival. We found that soil compaction, soil nutrient availability, and toxic soil elements were significantly higher in the softtrack‐ and tractor‐mown parts of grassland sites compared to the manually mown parts. Also, the arbuscular mycorrhizal community composition differed significantly among mowing types, with the largest differences between “manual” and “tractor.” Succisa pratensis survival significantly decreased by 43 and 71% on the short term and by 71 and 86% on the longer term with increasing compaction. Consequently, mowing‐associated soil compaction compromises nature management targets via at least four mechanisms: nutrient enrichment, soil toxicity, changes in arbuscular mycorrhizal communities, and decreased survival of the target plant species.

Classification Model of Grassland Desertification Based on Deep Learning

Grasslands are one of the most important ecosystems on earth, and the impact of grassland desertification on the earth’s environment and ecosystem cannot be ignored. Accurately distinguishing grassland desertification types has important application value. The appropriate grazing strategies can be implemented based on these distinctions. Grassland conservation measures can be tailored accordingly. This contributes to further protecting and restoring grassland vegetation. This project takes color images labeled with the desertification types of grasslands as the research object, uses the currently popular deep learning model as the classification tool, and then establishes a color image-based grassland desertification classification model based on the feature extraction network, based on the Vision Transformer model, by comparing the various deep learning image classification models. The experimental results show that, despite the complex structure and large number of parameters of the grassland desertification classification model obtained in this project, the test accuracy rate reaches 88.72% and the training loss is only 0.0319. Compared with the popular classification models such as VGG16, ResNet50, ResNet101, DenseNet101, DenseNet169, and DenseNet201, and so on, the Vision Transformer demonstrates clear advantages in classification accuracy, fitting ability, and generalization capacity. By integrating with deep learning technology, the model can be applied to grassland management and ecological restoration. Mobile devices can be used to conveniently capture image data, and information can be processed quickly. This provides efficient tools for grazing managers, environmental scientists, and conservation organizations. These tools assist in quickly assessing the extent of grassland desertification, optimizing grassland management and conservation decisions. Furthermore, strong technical support is offered for the ecological restoration and sustainable management of desertification grasslands.

Characteristics of Vegetation and Soil of Degraded Grasslands and Their Relationships in Xizang

To investigate the characteristics of grassland degradation on a regional scale in Xizang, data on grassland degradation from the second grassland survey of Xizang and 12 vegetation and soil indicators from the National Tibetan Plateau Data Center were collected. Using ArcMap, 10 000 random sample points were selected on raster data （excluding non-grassland, desertification, and salinization data, leaving 7 949 valid sample points）. The multi-value extraction to-point method was applied to extract degradation and indicator data for each sample point. The characteristics of degraded grassland vegetation and soil and their relationships were analyzed in Xizang. Moreover, random forest modeling was conducted to predict the trend of grassland ecosystem changes. The results indicated that： ① The grasslands in Xizang were primarily composed of alpine steppe and alpine meadow types, accounting for 45.83% and 41.15% of the valid sample points, respectively. ② With the intensification of grassland degradation, the number of steppe-type species among the 17 grassland types gradually decreased, and the proportion of steppe dominated by species such as Stipa purpurea and Carex moorcroftii decreased, whereas the proportion of miscellaneous grasses and Dasiphora fruticosa increased. ③ As the degree of degradation increased, vegetation indicators generally showed a declining trend, with soil total nitrogen, total phosphorus, total potassium, and organic carbon decreasing, whereas soil pH and bulk density increased, and soil moisture content was not significant. ④ A positive correlation exists between soil moisture content, total nitrogen, total phosphorus, total potassium, organic carbon, vegetation cover, net primary productivity of vegetation, normalized difference vegetation index, aboveground biomass, and habitat quality. However, there was a negative correlation between pH and soil bulk density, and the correlation coefficients among various indicators decreased with the intensification of degradation. ⑤ The random forest simulation results showed that during the degradation process, the contribution rates of soil bulk density and habitat quality both exceeded 12%, with the model prediction accuracy reaching 78%. The study revealed that grassland degradation in Xizang was closely related to soil bulk density and habitat quality, indicating that higher soil bulk density or lower habitat quality may correspond to more severe grassland degradation. This provides a scientific basis for future grassland conservation and management.

Landscape-scale predictions of future grassland conversion to cropland or development.

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R2=0.89 [range: 0.83-0.96], root mean squared error [RMSE]=9.29ha [range: 2.83-22.77ha]; proportional loss model: weighted group mean R2=0.74 [range: 0.64-0.87], RMSE=0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.