Grassland Conditions Research Articles

South-central Laurentide Ice Sheet dynamics and the formation of proglacial Lake Vita during MIS 3

Abstract An understanding of the growth and demise of ice sheets over North America is essential to inform future climate models. One poorly studied subject is the glacial dynamics during interstadial Marine Isotope Stage (MIS) 3 (57–29 ka). To better constrain the southern margin of the Laurentide Ice Sheet during this time period, we re-examined a stratigraphic sequence in southeast Manitoba, Canada, and provide robust evidence for advance and retreat of ice. Around 46.6 ± 5.1 ka (1σ error), fluvial sands were deposited under similar precipitation and significantly cooler summer temperatures than present-day. Ice then advanced south over the area, before retreating once again and a return to boreal forest and grassland conditions. The area was then covered by proglacial Lake Vita, dammed by ice to the north. Geochronology constraints indicate Lake Vita existed from ca. 44.3 ± 3.6 to 30.4 ± 2.3 ka (1σ error), although gaps in the optical and finite radiocarbon ages suggest either a lack of data or plausible temporary ice-margin advances during this time period. Ice covering most of Manitoba during MIS 3 is in line with global δ18O records, and glacially influenced sediment deposition in the Mississippi River basin.

Habitat management interventions for a specialist mid- successional grassland butterfly, the Lulworth Skipper

Evidence-based management is needed to reverse declines in insect abundance. The Lulworth Skipper Thymelicus acteon is a range-restricted and declining species in the UK and northern Europe associated with mid-successional grassland, which presents management challenges because interventions are necessary to prevent long-term habitat deterioration but can result in short-term reductions in quality. In addition, site management should be compatible for the focal species and for wider plant and insect diversity. We conducted factorial experimental management trials to understand effects of cutting and rotovation on the height and structure of vegetation containing the larval host plant Tor-grass Brachypodium rupestre. We monitored vegetation height, B. rupestre cover and plant diversity, and T. acteon larval presence over four years. Rotovation and cutting differed in their effects on habitat structure and larval occupancy relative to controls. Vegetation height and host plant cover, the most important components of habitat quality for T. acteon, were faster to recover to suitable levels on cut plots. However, larval occupancy increased more quickly on rotovated plots, where plant species diversity was also higher. Results suggest that due to initial negative impacts of interventions on T. acteon occupancy, low frequency or low-intensity management, such as managing sections of a site every three years, is advisable. Our results show that rotovation or cutting the sward can be suitable for mid-successional grassland species such as Lulworth Skipper on sites where grazing might be problematic. Rotational grazing or rotovation can maintain suitable conditions for habitat specialist insects requiring a range of different grassland conditions, serving wider conservation goals.

Sustainable Land Use Strengthens Microbial and Herbivore Controls in Soil Food Webs in Current and Future Climates.

Climate change and land-use intensification are threatening soil communities and ecosystem functions. Understanding the combined effects of climate change and land use is crucial for predicting future impacts on soil biodiversity and ecosystem functioning in agroecosystems. Here, we used a field experiment to quantify the combined effects of climate change (warming and altered precipitation patterns) and land use (agricultural type and management intensity) on soil food webs across nematodes, micro-, and macroarthropods. Specifically, we investigated two types of agricultural systems-croplands and grasslands-under both high- and low-intensity management. We focused on assessing the functioning of soil food webs by investigating changes in energy flux to consumers in the main trophic groups: decomposers, microbivores, herbivores, and predators. While the total energy flux and detritivory, herbivory and predation in the soil food web remained unchanged across treatments, low-intensity land use-compared to high intensity-led to higher microbivory and microbial control under future climate conditions (i.e., warming and summer drought) in croplands and grasslands. At the same time, microbial and herbivore control were higher under low-intensity land use in croplands and grasslands. Overall, our results underscore the potential benefits of less intensive, more sustainable management practices for soil food-web functioning under current and future climate scenarios.

Assessing Ecological Compensation Policy Effectiveness: A Case Study in the Inner Mongolia Autonomous Region, China

As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China’s Inner Mongolia Autonomous Region (IMAR). While conservation was carried out via the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems (TSESs) to assess how ecological systems respond to the ESAP, investigate the spatial heterogeneity of the ESAP, and explore the meddling effects of socio-environmental interactions on the ESAP. We integrated ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMMs) to investigate how these factors interact with the ESAP in the IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors positively related to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in future efforts to conserve grassland.

Plant roots affect free-living diazotroph communities in temperate grassland soils despite decades of fertilization

Fixation of atmospheric N2 by free-living diazotrophs accounts for an important proportion of nitrogen naturally introduced to temperate grasslands. The effect of plants or fertilization on the general microbial community has been extensively studied, yet an understanding of the potential combinatorial effects on the community structure and activity of free-living diazotrophs is lacking. In this study we provide a multilevel assessment of the single and interactive effects of different long-term fertilization treatments, plant species and vicinity to roots on the free-living diazotroph community in relation to the general microbial community in grassland soils. We sequenced the dinitrogenase reductase (nifH) and the 16S rRNA genes of bulk soil and root-associated compartments (rhizosphere soil, rhizoplane and root) of two grass species (Arrhenatherum elatius and Anthoxanthum odoratum) and two herb species (Galium album and Plantago lanceolata) growing in Austrian grassland soils treated with different fertilizers (N, P, NPK) since 1960. Overall, fertilization has the strongest effect on the diazotroph and general microbial community structure, however with vicinity to the root, the plant effect increases. Despite the long-term fertilization, plants strongly influence the diazotroph communities emphasizing the complexity of soil microbial communities’ responses to changing nutrient conditions in temperate grasslands.

Assessment of suitability for photovoltaic power generation in periurban seminatural grasslands: toward the coexistence of seminatural grasslands and photovoltaic power generation

Renewable energy has grown substantially in recent years due to its efficacy in mitigating climate change. The rapid proliferation of solar photovoltaic (PV) systems and subsequent alterations in land use have led to concerns about the impact on local ecosystems. Particularly in Japan, seminatural grasslands, which are valuable habitats, are being developed as solar PVs. Here, we focused on stilt-mounted agrivoltaic systems, capable of both photovoltaic power generation and plant growth beneath solar panels. By repurposing this technology, the coexistence of vegetation and solar PV systems can be possibly ensured. To assess the feasibility of this proposed approach, we initially examined the suitability of installing solar PV in seminatural grasslands. The suitability of seminatural grasslands, solar PVs, and random points for solar PV was evaluated in terms of electricity generation and construction costs. The environmental conditions of seminatural grasslands were found to be advantageous for electricity generation. On the other hand, in terms of construction costs, seminatural grasslands were comparable to randomly selected sites. These findings indicate that the suitability of existing seminatural grasslands for solar PV plant installations is not considerably lower than that of other land types. The idea of reconciling solar power generation with ecosystem conservation holds promise and warrants further investigation toward its realization.

Analyzing Spatiotemporal Variations and Driving Factors of Grassland in the Arid Region of Northwest China Surrounding the Tianshan Mountains

The Tianshan Mountains, the largest arid mountain range in Central Asia, feature diverse terrains and significant landscape heterogeneity. The grasslands within the Xinjiang Tianshan region are particularly sensitive to climate change and human activities. However, until recently, the patterns and mechanisms underlying grassland changes in this region have been unclear. In this study, we analyzed spatial and temporal changes in grassland fractional vegetation cover (FVC) from 2001 to 2020, analyzed spatial and temporal changes in grassland, and predicted future trends using Global Land Surface Satellite (GLASS) FVC data, trend analysis, and the Hurst index method. We also explored the driving mechanisms behind these changes through the structural equation model (SEM). The results showed that from 2001 to 2020, the grassland FVC in the Tianshan region of Xinjiang was higher in the central and western regions and lower in the northern and southern regions, showing an overall fluctuating growth trend, with a change in the growth rate of 0. 0017/a (p < 0.05), and that this change was spatially heterogeneous, with the sum of significant improvement (20.6%) and slight improvement (29.9%) being much larger than the sum of significant degradation (0.6%) and slight degradation (9.5%). However, the Hurst index (H = 0.47) suggests that this trend may not continue, and there is a risk of degradation. Our study uncovers the complex interactions between the Tianshan barrier effect and grassland ecosystems, highlighting regional differences in driving mechanisms. Although the impacts of climatic conditions in grasslands vary over time in different regions, the topography and its resulting hydrothermal conditions are still dominant, and the extent of the impact is susceptible to fluctuations of varying degrees due to extreme climatic events. Additionally, the number of livestock changes significantly affects the grasslands on the southern slopes of the Tianshan Mountains, while the effects of nighttime light are minimal. By focusing on the topographical barrier effect, this study enhances our understanding of grassland vegetation dynamics in the Tianshan Mountains of Xinjiang, contributing to improved ecosystem management strategies under climate change.

Plant beta-turnover rather than nestedness shapes overall taxonomic and phylogenetic beta-diversity triggered by favorable spatial-environmental conditions in large-scale Chinese grasslands.

Although it is widely acknowledged that biodiversity maintains plant community assembly processes, exploring the patterns and drivers of beta-diversity (β-diversity; species variation among local plant communities) has received much less attention compared to alpha-diversity (α-diversity; species variation within a local plant community). Here, we aim to examine the patterns and spatial-environmental drivers of taxonomic and phylogenetic β-diversity, and their components such as species turnover and nestedness, in large-scale Leymus chinensis grassland communities. We collected plant community data from 166 sites across widely distributed L. chinensis communities in northern China, and then calculated the taxonomic and phylogenetic β-diversity indices (overall, turnover and nestedness) using a pairwise dissimilarity approach. To assess the effects and to explain the variation in the patterns of β-diversity, we collected data on geospatial, climate and soil conditions. We applied descriptive statistics, Mental correlations, and multiple linear regression models to assess the patterns and spatial-environmental drivers of β-diversity. The β-turnover, as compared to β-nestedness, exhibited a predominant influence, constituting 92.6% of the taxonomic β-diversity and 80.4% of the phylogenetic β-diversity. Most of the spatial-environmental variables were significantly positively correlated with the overall taxonomic and phylogenetic β-diversity and β-turnover, but not with β-nestedness. Climatic factors such as MAP and MAT were the strongest predictors of both taxonomic and phylogenetic β-diversity and β-turnover. The variance partitioning analysis showed that the combined effects of spatial and environmental factors accounted for 19% and 16% of the variation in the taxonomic and phylogenetic β-diversity (overall), 17% and 12% of the variation in the β-turnover, and 7% and 1% of the variation in the β-nestedness, respectively, which were higher than independent effects of either spatial or environmental factors. At larger spatial scales, the turnover component of β-diversity may be associated with the species complementarity effect, but dominant or functionally important species can vary among communities due to the species selection effect. By incorporating β-diversity into grassland management strategies, we can enhance the provision of vital ecosystem services that bolster human welfare, serving as a resilient barrier against the adverse effects of climate change at regional and global scales.

Hydrolases Control Soil Carbon Sequestration in Alpine Grasslands in the Tibetan Plateau

Microbial-sourced carbon is an important component of soil organic carbon (SOC) and influences SOC’s size and turnover. Soil extracellular enzymes can participate in the degradation of plants in the soil to produce substances needed by microorganisms, which in turn affects microbial sources of carbon. Most of the current studies focus on the effects of soil extracellular enzymes on SOC pools, while there is a lack of clarity regarding the effects on microbial sources of carbon during SOC pool formation. In this paper, three typical grassland types (alpine meadow, alpine grassland, and desert grassland, respectively) on the Tibetan Plateau were selected as research objects to investigate the effects of grassland type and soil depth on microbial-sourced carbon (amino sugars) and soil extracellular enzymes (hydrolytic enzymes: β-glucosidase and cellulase; oxidative enzymes: peroxidase and polyphenol oxidase) in the soil profiles. Our study shows that the content of amino sugars in the three grassland types followed the order: alpine meadow > alpine grassland > desert grassland; the content of hydrolytic enzyme followed the order of alpine meadow > alpine grassland > desert grassland; the content of oxidative enzyme followed the order of desert grassland > alpine grassland > alpine meadow; amino sugars content showed a positive correlation with hydrolytic enzymes and a negative correlation with oxidative enzymes; and the hydrolytic enzyme was the main factor promoting the accumulation of amino sugars. The environmental conditions of alpine meadows and alpine grasslands are more favorable for the formation of microbial-derived carbon and have greater sequestration potential, while desert grasslands are not favorable for the formation of microbial-derived carbon. The results of this study provide a reference basis for exploring the model of organic carbon sequestration in the Tibetan Plateau.

Efficacy of Multiseason Sentinel-2 Imagery for Classifying and Mapping Grassland Condition

Assessing the condition of ecosystems is imperative for understanding their degree of degradation and managing their conservation. The increasing availability of remote sensing products offers unprecedented opportunities for mapping vegetation with high detail and accuracy. However, mapping complex ecosystems, like grasslands, remains challenging due to their heterogeneity in vegetation composition and structure. Furthermore, degraded ecosystems affected by invasive vegetation present different condition levels within vegetation classes, limiting the accuracy of classifications and condition assessment. Here, we evaluated the capacity of Sentinel-2 multispectral time series imagery as an input for classifying different levels of cover within a vegetation class to detect the subtle differences needed to assess the condition of degraded ecosystems. Our study was conducted in the iron-grasslands of South Australia, a perennial tussock grassland dominated by iron-grasses (Lomandra spp.) and severely affected by invasive annual grasses. We developed random forest models to discriminate classes defined by the cover of iron-grasses, wild oats (Avena barbata), and woodland (training points = 250). We tested the importance of data seasonality, spatial resolution, spectral bands, and vegetation indices. The combination of spatial, temporal, and spectral detail produced the best classification results. Random forest classifications performed best at 10 m resolution, suggesting that detailed resolution outweighs spectral detail for discriminating vegetation patterns in systems with high spatial heterogeneity. The model at 10 m resolution combining all periods and all variables (spectral bands and vegetation indices) produced a mean kappa coefficient of 56% and a mean overall accuracy of 67%. The dry season imagery and vegetation indices emerged as the most informative, suggesting that vegetation classes presented different phenological properties critical for their discrimination. Our study contributes to mapping complex ecosystems, facilitating the discrimination of different levels of condition in grasslands degraded by invasive species, and thus benefits the conservation of native grasslands and other ecosystems.

Can mulching or composting be applied to maintain semi-natural grassland managed for biodiversity?

Traditional, extensive management systems in grasslands have played a fundamental role in the formation, maintenance and conservation of grassland of high natural value. Contemporary processes in the agricultural economy make this type of management unprofitable. Simplified management systems are implemented as part of agricultural and environmental programmes and in protected areas, but these can cause changes in botanical composition. An experiment was conducted for six years on grassland in the Carpathian Mountains to compare mulching and compost application with late cutting and biomass removal. In the conditions of mountain grassland of medium fertility, the level of biomass and the species composition of the vegetation were the same following mulching as in the case of cutting and biomass removal. Mulching was only found to affect the temperature of the topsoil. Compost application caused a significant increase in the amount of biomass. The species composition was the same as for the other management types, but there were changes in the proportions of individual species and functional groups. High grasses were dominant, while the proportion of legume plants was small. Moreover, the N:P ratio was lower following the use of compost, indicating a shift from P limitation to N limitation. Mulching can be used as a simplified means of management in the case of certain types of grassland communities, but its effects must be monitored. Compost application would necessitate modification of other elements of management, e.g. increased frequency of cutting.

A 10-m annual grazing intensity dataset in 2015–2021 for the largest temperate meadow steppe in China

Mapping grazing intensity (GI) using satellites is crucial for developing adaptive utilization strategies according to grassland conditions. Here we developed a monitoring framework based on a paired sampling strategy and the classification probability of random forest algorithm to produce annual grazing probability (GP) and GI maps at 10-m spatial resolution from 2015 to 2021 for the largest temperate meadow in China (Hulun Buir grasslands), by harmonized Landsat 7/8 and Sentinel-2 images. The GP maps used values of 0–1 to present detailed grazing gradient information. To match widely used grazing gradients, annual GI maps with ungrazed, moderately grazed, and heavily grazed levels were generated from the GP dataset with a decision tree. The GI maps for 2015–2021 had an overall accuracy of more than 0.97 having significant correlations with the statistical data at city (r = 0.51) and county (r = 0.75) scales. They also effectively captured the GI gradients at site scale (r = 0.94). Our study proposed a monitoring approach and presented annual 10-m grazing information maps for sustainable grassland management.

Multidecadal grassland fractional cover time series retrieval for Germany from the Landsat and Sentinel-2 archives

Time series data provided by the Sentinel-2 and Landsat satellite missions offer manifold opportunities for grassland monitoring. The high intra-annual observation density of Sentinel-2 combined with the continuous long-term data record of Landsat enable analyses at seasonal, annual, and decadal scales. Fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil provide essential information to describe grassland conditions and processes. Yet, retrieving consistent grassland fractional cover time series from Landsat and Sentinel-2 imagery represents a major challenge. In this study, we implemented a multisensor spectral unmixing approach for retrieving multidecadal (i.e., 1984 to 2021) fractional cover time series of PV, NPV, and soil for Germany's permanent grasslands from the Landsat and Sentinel-2 archives. The spectral consistency of Landsat 5/7/8 and Sentinel-2A/B imagery as well as the coherency of a Sentinel-2-based spectral library to be used across Landsat and Sentinel-2 sensors served as the foundation for implementing the unmixing approach. We then employed regression-based unmixing using synthetic training data from spectral libraries for developing spatially and temporally generalized models. Applying these models to the Landsat and Sentinel-2 data facilitated multidecadal fractional cover mapping at a national-scale. We evaluated the quality of our multidecadal grassland fractional cover time series using statistical validation and linear correspondence analysis. The statistical validation was based on a multitemporal reference dataset spanning 2017 to 2021, derived from very high-resolution (VHR) imagery. Landsat 7/8- and Sentinel-2A/B-derived fractions showed similar Mean Absolute Errors (MAEs), i.e., 0.067 and 0.08 for PV, 0.149 and 0.15 for NPV, and 0.135 and 0.129 for soil. Linear correspondence analysis confirmed consistent PV and NPV fractional cover estimates among Landsat and Sentinel-2 sensors, suggesting similar errors beyond the statistical validation period. However, higher errors and weaker linear correspondence pointed to remaining uncertainties in soil fractional cover estimates. We further showed that the differences in spatial and spectral resolutions, i.e., the pixel size and the number of spectral bands, between Landsat and Sentinel-2 had a minor effect and were well mitigated by the spectral unmixing approach. We finally illustrated the value of the dense time series available for more recent years for describing seasonal trajectories of grassland conditions and land use intensities, as well as the use of the entire time series for analyzing long-term grassland dynamics based on annual fraction anomalies. Our study emphasizes the efficacy of generalized multisensor spectral unmixing approaches for retrieving consistent PV, NPV, and soil cover fractions across space, time, and sensors, providing a valuable means for grassland monitoring.

Temporal Stability of Grassland Soil Moisture Utilising Sentinel-2 Satellites and Sparse Ground-Based Sensor Networks

Soil moisture is important for understanding climate, water resources, water storage, and land use management. This study used Sentinel-2 (S-2) satellite optical data to retrieve surface soil moisture at a 10 m scale on grassland sites with low hydraulic conductivity soil in a climate dominated by heavy rainfall. Soil moisture was estimated after modifying the Optical Trapezoidal Model to account for mixed land cover in such conditions. The method uses data from a short-wave infra-red band, which is sensitive to soil moisture, and four vegetation indices from optical bands, which are sensitive to overlying vegetation. Scatter plots of these data from multiple, infrequent satellite passes are used to define the range of surface moisture conditions. The saturated and dry edges are clearly non-linear, regardless of the choice of vegetation index. Land cover masks are used to generate scatter plots from data only over grassland sites. The Enhanced Vegetation Index demonstrated advantages over other vegetation indices for surface moisture estimation over the entire range of grassland conditions. In poorly drained soils, the time lag between satellite surface moisture retrievals and in situ sensor soil moisture at depth must be part of the validation process. This was achieved by combining an approximate solution to the Richards’ Equation, along with measurements of saturated and residual moisture from soil samples, to optimise the correlations between measurements from satellites and sensors at a 15 cm depth. Time lags of 2–4 days resulted in a reduction of the root mean square errors between volumetric soil moisture predicted from S-2 data and that measured by in situ sensors, from ~0.1 m3/m3 to <0.06 m3/m3. The surface moisture results for two grassland sites were analysed using statistical concepts based upon the temporal stability of soil water content, an ideal framework for the intermittent Sentinel-2 data in conditions of persistent cloud cover. The analysis could discriminate between different natural drainages and surface soil textures in grassland areas and could identify sub-surface artificial drainage channels. The techniques are transferable for land-use and agricultural management in diverse environmental conditions without the need for extensive and expensive in situ sensor networks.

A spatio-temporal fusion strategy for improving the estimation accuracy of the aboveground biomass in grassland based on GF-1 and MODIS

The accurate estimation of the aboveground biomass (AGB) is crucial for the sustainable utilization and management of grassland resources. Spatio-temporal inconsistencies between field samples and satellite images are major source of error in the estimation of grassland AGB. To solve this problem, this study selected the Three Rivers Headwater Region as the study area and proposed a selection strategy for base-period images of spatio-temporal fusion that was suitable for use at a large spatial scale in which cloud-free images are difficult to obtain. The spatial and temporal adaptive reflectance fusion model (STARFM) based on the selection strategy was used to generate a synthetic Normalized Difference Vegetation Index (NDVI) dataset with high spatial-temporal resolution by using the maximum value composite of GF-1 NDVI and MODIS NDVI to enhance the spatial-temporal quality of the images for field-scale application. Three estimation models for grassland AGB were then constructed by the random forest algorithm using synthetic NDVI, MODIS NDVI, GF-1 NDVI respectively, together with ancillary data. Following this, the estimation model with the highest accuracy was used to generate a 16-m eight-day time-series AGB in the growing season. The results showed: (1) The synthetic NDVI was correlated closely with the observed GF-1 NDVI, with an average R of 0.825 and a RMSE of 0.087. The temporal trend of the synthetic NDVI for each grassland type was highly consistent with that of the MODIS NDVI in the growing season with a correlation higher than 0.9. (2) The synthetic NDVI reduced the spatial difference between field samples and images to 16-fold, and the temporal difference was controlled to within four days under ideal conditions. (3) The synthetic NDVI improved the estimation accuracy of grassland AGB by about 15.9% and 19.7% (R2), and 13.7% and 17.5% (RMSE) relative to MODIS NDVI and GF-1 NDVI, respectively. (4) The time-series AGB revealed accurately the spatial distribution of and seasonal temporal variations in the grassland biomass. The results of this study may serve as scientific guidance for timely monitoring of grassland conditions and precise management of grassland resources in China.

Assessing long-term trends in vegetation cover change in the Xilin River Basin: Potential for monitoring grassland degradation and restoration

Under the influence of climate change and human activities, the problem of grassland degradation is becoming increasingly severe. Detection of changes in vegetation cover is crucial for a better understanding of the interaction between humans and ecosystems. This study maps changes in vegetation cover using the Google Earth Engine (GEE). We used 36 years of Landsat satellite imagery (1985–2020) in the Xilin River Basin, China, to classify grassland conditions and validated the results with field observation data. The overall classification of the model accuracy assessment was 83.3%. The Dynamic Reference Vegetation Cover Method (DRCM) was adopted to remove the effect of interannual variation of rainfall, allowing to focus on the impact of human activities on vegetation cover changes. The results identify five categories of vegetation cover changes: significantly increased, potentially increased, stable, potentially decreased, and significantly decreased. The reference level is derived from the most persistent land surface coverage across different grassland types and all years. Overall, 9.3% of the study area had a significant increase in vegetation cover, 14.2% a potential increase, 48.6% of the area showed a stable vegetation condition, 9.8% showed a potential decrease, and 18.1% a significant decrease in vegetation cover. The largest proportion of combined potential and significant reduction was 35.2% for desert grassland, where the vegetation faced the most severe reduction. This study will provide a basis for identifying grassland degradation and developing scientific management policies.

Suitability Evaluation and Engineering Matching for Agricultural Development of Barren Grassland in Mountainous Area: A Case Study of County Scale

Barren grasslands are an important reserve resource of cultivated land in mountainous areas. The exploitation of barren grassland for agricultural use has played a role in ensuring food security and people’s livelihood in many countries and regions. The suitability evaluation of agricultural-use development, based on the conditions of barren grassland itself and the engineering matching, can not only ensure the sustainable development of agriculture but also avoid the ecological negative effects caused by excessive engineering. According to the research, the agricultural development of barren grassland needs to be evaluated from the two angles of natural suitability and engineering suitability, and an innovative “index level serial number summation method” is proposed. The suitability of barren grassland for agricultural use development was divided into three categories: barren grassland suitable for cultivation, barren grassland suitable for forestry, and barren grassland suitable for prataculture. The barren grassland suitable for cultivation was selected for type division and engineering-accurate matching. Taking Tang County as a research area, an example was provided through a combination of theoretical research. According to the characteristics of barren grassland in Tang County, the evaluation indexes of natural suitability and engineering suitability were selected, and the suitability of barren grassland for agricultural development was evaluated and graded. A classification system for the utilization of barren grassland suitable for cultivation is constructed, the required engineering types are explored to eliminate the main limiting factors, and the utilization types are matched with the engineering combination types. The barren grassland suitable for cultivation in the study area can be divided into 37 types, which can match eight engineering combinations. This study proposes a systematic method for the identification, classification, rating, and engineering matching for arable land reserve resources. The study can provide the basis for the effective utilization and accurate development of land resources.

Spatial-Temporal Pattern Analysis of Grassland Yield in Mongolian Plateau Based on Artificial Neural Network

Accurate and timely estimation of grass yield is crucial for understanding the ecological conditions of grasslands in the Mongolian Plateau (MP). In this study, a new artificial neural network (ANN) model was selected for grassland yield inversion after comparison with multiple linear regression, K-nearest neighbor, and random forest models. The ANN performed better than the other machine learning models. Simultaneously, we conducted an analysis to examine the spatial and temporal characteristics and trends of grass yield in the MP from 2000 to 2020. Grassland productivity decreased from north to south. Additionally, 92.64% of the grasslands exhibited an increasing trend, whereas 7.35% exhibited a decreasing trend. Grassland degradation areas were primarily located in Inner Mongolia and the central Gobi region of Mongolia. Grassland productivity was positively correlated with land surface temperature and precipitation, although the latter was less sensitive than the former in certain areas. These findings indicate that ANN model-based grass yield estimation is an effective method for grassland productivity evaluation in the MP and can be used in a larger area, such as the Eurasian Steppe.

Keep sustainable livestock production without Grassland degradation: Future cultivated pasture development simulation based on agent-based model

Overgrazing on grasslands has caused grassland degradation in China during past decades, which could impair the production of livestock products, so it must be limited to maintain the supply ability of grasslands for human well-beings. Establishing cultivated pastures, which has been popularized and proved effective to increase forage yields and restore degraded grasslands in many developed countries, could also provide more powerful support for livestock production with a healthy livestock-grassland relationship in China where there are only few cultivated pastures now. To explore whether cultivated pasture construction is a promising approach for mitigating ecological pressure while satisfying herdsmen livelihood demands, we developed an Agent-Based Model based on herdsmen behaviors and grassland conditions. In this model, the cultivated pastures in future 30 years will be established by herdsmen in accordance with their livestock production plan, natural pasture supply and suitability of establishing cultivated pastures, and the suitable areas for establishing cultivated pastures was selected based on natural and social limitations. Focusing on Xilin Gol Grassland, one of the typical pastoral areas in China, the characters of herdsmen livelihood behaviors and willingness for cultivated pasture construction were investigated by household survey, and the spatio-temporal variations of cultivated pastures and relevant economic-ecological consequences in future 30 years were simulated using the Agent-Based Model. The results showed that most suitable areas are distributed in the south of Xilin Gol Grassland near the agro-pastoral ecotone, where cultivated pastures are few now but should be newly established later. The number of cultivated pastures will gradually increase while the increasing speed will gradually descend in each county. With the expanding cultivated pastures, herdsmen's income will rise quickly in the first ten years then keep stable at 70000∼80000RMB nearly twice the original income, while the ecological pressure of grasslands will descend fast from >3 to 1 in the first eight years, then slowly from 1 to 0.5 and stay <0.5 after 2035. Such results proved that establishing cultivated pastures will really bring economic-ecological coordination on grasslands, which provided evidences for popularizing cultivated pastures to keep sustainable production and supply of livestock products and realize modern animal husbandry development.

Resolving a heated debate: The utility of prescribed burning as a management tool for biodiversity on lowland heath

Abstract Lowland heath is a priority habitat for conservation, nowadays largely managed for biodiversity. Historically, prescribed burning has been the principal management tool, but there are increasing calls to substitute burning with cutting to improve biodiversity outcomes. However, poor understanding of potential impacts compromises decision making. Our study was carried out in the New Forest National Park, the largest area of lowland heath in Europe. Using a multi‐trophic approach, we compared the ecological impact of prescribed burning with two types of vegetation cutting (swiping and baling) as management tools for biodiversity outcomes for up to 20 years after management. Indicators included: common standards monitoring (CSM) assessment; vegetation species assemblage; below‐ and above‐ground invertebrate biodiversity; and available food resources for two characteristic heathland birds—the Dartford Warbler Sylvia undata and the Nightjar Caprimulgus europaeus. When compared with swiped sites, areas managed by prescribed burning resulted in: better habitat condition (assessed by CSM); higher cover of heathers; lower bracken cover; more areas of bare ground. We found no evidence that burning is detrimental for the investigated components of biodiversity. Cutting by swiping did not replicate the benefits of burning. Swiping supported grassland conditions that suit non‐heathland species. Baling resulted in habitat condition similar to prescribed burning but restricted replication of baled sites limited our conclusions. However, swiped sites supported high invertebrate abundance and diversity, including food resources for Dartford Warbler and Nightjar. Synthesis and applications. Removing burning from the management programme is likely to reduce heathland condition. Biodiversity is encouraged by a mosaic of management and more mobile species, such as birds, will exploit the resources provided by several management techniques. Including some cutting in a rotational regime is likely to be beneficial although prescribed burning should form the majority of the management programme, Lowland heathland differs fundamentally from upland heathland/moorland and it is not easy to transfer the results. Current heathland CSM does not adequately assess wider biodiversity on protected areas but is effectively an assessment of vegetation feature condition. Including invertebrates in surveys provides a more nuanced assessment of heathland condition.