Grassland Restoration Research Articles

Effect of Vegetation Structure on Lift-Off and Dispersal Velocities of Diaspores with Different Morphological Characteristics in Secondary Wind Dispersal

Diaspore dispersal is crucial in shaping plant population dynamics, biodiversity, and ecosystem functions. The effect of the vegetation structure on the secondary wind dispersal of diaspores with different appendage types is not well understood. Using a wind tunnel and a high-definition video camera, we accurately measured the lift-off and dispersal velocities of diaspores from sixteen plant species across six wind velocities (2, 4, 6, 8, 10, and 12 m s−1) under six simulated vegetation structures. Vegetation structure and appendage type were pivotal factors, explaining 41.1% and 42.3% of the variance in lift-off velocity and accounting for 12.0% and 25.3% of the variability in diaspore dispersal velocity, respectively. Vegetation coverage was the main factor influencing near-surface wind velocity, and the lift-off and dispersal velocities of diaspores changed significantly when vegetation coverage exceeded 40%. Diaspores with one wing, having high lift-off velocities and low dispersal velocities, adopt the anti-long-distance wind dispersal strategy, whereas diaspores with pappus, having low lift-off velocities and high dispersal velocities, adopt the long-distance wind dispersal strategy. In contrast, diaspores with thorn, discoid, balloon, and four wings adopt the non-long-distance wind dispersal strategy, suitable for environments such as low-coverage deserts and desert steppes but not high-coverage typical steppes. This study could help comprehend the effect of the vegetation structure on the dispersal process of diaspores, which facilitate habitat restoration and biodiversity conservation of grassland and forest ecosystems.

Restoring stone and dominant grass species cover in a Mediterranean grassland: 20‐year effects on soil, vegetation, and arthropod communities

Long‐term studies are needed to monitor recovery following restoration, as it may take decades or even centuries, particularly in the case of Mediterranean dry grasslands, for communities to reach their former equilibrium before the degradation occurred. A multi‐component approach is also needed to evaluate restoration success and better understand the complex impacts of former restoration projects on present‐day ecological interactions and ecosystem functions. The objective of this study was to address the restoration of a Mediterranean grassland in southern France, 20 years after implementation. Particularly, we examine the long‐term impact on soil, vegetation, and arthropods of the reintroduction of a dominant grass species (Brachypodium retusum) and the restoration of the natural stone cover on a degraded former cultivated field. Soil analyses revealed that reestablishing stone cover only slightly acidified the soil, while B. retusum presence enhanced soil fertility. Brachypodium retusum also decreased the nutritional value of forage and increased plant biomass and litter. Plant composition shifted with treatments: B. retusum and stone cover favored xeromesophilous species, while B. retusum alone encouraged less palatable species. The soil seed bank composition and abundance were positively influenced by stone cover but negatively impacted by B. retusum reintroduction. Negative outcomes on some arthropods and mesofauna were measured in treatments with both B. retusum and stones, except for Acari, which were positively impacted by the presence of stones. The findings emphasize that B. retusum is an ecological engineer with complex effects on the different ecosystem components.

Artemisia Frigida Distribution Mapping in Grassland with Unmanned Aerial Vehicle Imagery and Deep Learning

Artemisia frigida, as an important indicator species of grassland degradation, holds significant guidance significance for understanding grassland degradation status and conducting grassland restoration. Therefore, conducting rapid surveys and monitoring it is crucial. In this study, to address the issue of insufficient identification accuracy due to the large density and small size of Artemisia frigida in UAV images, we improved the YOLOv7 object detection algorithm to enhance the performance of the YOLOv7 model in Artemisia frigida detection. We applied the improved model to the detection of Artemisia frigida across the entire experimental area, achieving spatial mapping of Artemisia frigida distribution. The results indicate: In comparison across different models, the improved YOLOv7 + Biformer + wise-iou model exhibited the most notable enhancement in precision metrics compared to the original YOLOv7, showing a 6% increase. The mean average precision at intersection over union (IoU) threshold of 0.5 (mAP@.5) also increased by 3%. In terms of inference speed, it ranked second among the four models, only trailing behind YOLOv7 + biformer. The YOLOv7 + biformer + wise-iou model achieved an overall detection precision of 96% and a recall of 94% across 10 plots. The model demonstrated superior overall detection performance. The enhanced YOLOv7 exhibited superior performance in Artemisia frigida detection, meeting the need for rapid mapping of Artemisia frigida distribution based on UAV images. This improvement is expected to contribute to enhancing the efficiency of UAV-based surveys and monitoring of grassland degradation. These findings emphasize the effectiveness of the improved YOLOv7 + Biformer + wise-iou model in enhancing precision metrics, overall detection performance, and its applicability to efficiently map the distribution of Artemisia frigida in UAV imagery for grassland degradation surveys and monitoring.

Revealing the Spatial Interactions and Driving Factors of Ecosystem Services: Enlightenments under Vegetation Restoration

Large-scale vegetation restoration has caused complex changes in ecosystem service (i.e., ES) interactions. However, current analysis on the spatial interactions of ESs and their driving mechanisms remains deficient, limiting the adaptive management in vegetation restoration areas. This study focused on a representative restoration area (Yan’an) to analyze the relationships among carbon sequestration, water yield, baseflow regulation, and soil conservation from 1990 to 2020. Employing the bivariate boxplot and spatial autocorrelation methods, we identified the overall changes and spatial patterns of ES interactions. The geographically and temporally weighted regression (i.e., GTWR) model was applied to elucidate the driving factors of these spatial ES interactions. The results indicated the following: (1) Over the past three decades, synergies between carbon sequestration and water yield emerged as the joint results of spatial ‘low–low’ interactions and ‘high–high’ interactions between the two ESs, while other ES pairs generally exhibited comparatively weaker synergies, due to their spatial ‘low–high’ interactions in southern semi-humid areas. (2) In the northern semi-arid areas, both fractional vegetation cover (i.e., FVC) and climatic factors consistently exerted negative influences on all ‘low–low’ ES interactions, which caused a reduced area in synergies, while in the southern semi-humid areas, FVC suppressed the ‘low–high’ trade-offs between ESs, indicating the adaptability of grassland restoration efforts. (3) The impact of human activities on ES interactions has increased in the last 10 years, and exhibited positive effects on the ‘low–low’ ES interactions in northern semi-arid areas. However, the expansion of trade-off between soil conservation and carbon sequestration warrants attention. This study offers important insights into understanding the spatial interactions among carbon, water, and soil-related ESs in drylands.

Vegetation diversity and structure influence small‐mammal communities in native and restored northern mixed grasslands

AbstractCurrent grassland restoration strategies aim to recreate grassland vegetation communities, and often rely on high‐diversity native seeding to promote vegetation diversity. Questions remain concerning the influence of vegetation richness and diversity on grassland fauna. Small‐mammal communities are integral parts of grassland ecosystems, but their responses to restoration are often mixed or overlooked. During July 2014 to 2016, we used Sherman live traps to survey grassland small‐mammal communities of 24 study sites in northeastern South Dakota and southeastern North Dakota, USA, to better understand their responses to vegetation cover type, diversity, richness, and site‐specific vegetation structure. Sites represented a vegetation species richness gradient and 3 vegetation cover types including low‐diversity restorations planted with dense nesting cover (DNC) seed mix, high‐diversity seeded restorations, and unseeded reference grasslands. Small‐mammal abundance was highest at low‐diversity DNC restoration sites and lowest in reference grassland. Small‐mammal diversity was highest at high‐diversity restoration sites and lowest at low‐diversity DNC restoration sites. Models assessing the influence of vegetation structure on the abundance of focal taxa differed. Deer mice (Peromyscus spp.) were negatively influenced by percent native vegetation cover, and voles (Microtus spp.) showed yearly variation and were influenced positively by litter depth and negatively by vegetation richness. Small‐mammal communities of low‐diversity DNC restorations differed from reference sites, but high‐diversity restorations were not different from reference or low‐diversity DNC sites. Thirteen‐lined ground squirrel (Ictidomys tridecemlineatus) abundance was higher at reference and high‐diversity restored sites, while low‐diversity DNC sites had higher deer mice abundance. Results indicate small mammals are unlikely to respond uniformly to vegetation characteristics, and diversity of seed mixes used in grassland restoration is likely to influence grassland small‐mammal communities.

Meta-analysis shows the impacts of ecological restoration on greenhouse gas emissions

International initiatives set ambitious targets for ecological restoration, which is considered a promising greenhouse gas mitigation strategy. Here, we conduct a meta-analysis to quantify the impacts of ecological restoration on greenhouse gas emissions using a dataset compiled from 253 articles. Our findings reveal that forest and grassland restoration increase CH4 uptake by 90.0% and 30.8%, respectively, mainly due to changes in soil properties. Conversely, wetland restoration increases CH4 emissions by 544.4%, primarily attributable to elevated water table depth. Forest and grassland restoration have no significant effect on N2O emissions, while wetland restoration reduces N2O emissions by 68.6%. Wetland restoration enhances net CO2 uptake, and the transition from net CO2 sources to net sinks takes approximately 4 years following restoration. The net ecosystem CO2 exchange of the restored forests decreases with restoration age, and the transition from net CO2 sources to net sinks takes about 3-5 years for afforestation and reforestation sites, and 6-13 years for clear-cutting and post-fire sites. Overall, forest, grassland and wetland restoration decrease the global warming potentials by 327.7%, 157.7% and 62.0% compared with their paired control ecosystems, respectively. Our findings suggest that afforestation, reforestation, rewetting drained wetlands, and restoring degraded grasslands through grazing exclusion, reducing grazing intensity, or converting croplands to grasslands can effectively mitigate greenhouse gas emissions.

Soil stoichiometric imbalances constrain microbial-driven C and N dynamics in grassland

Grassland restoration leads to excessive soils with carbon (C) and nitrogen (N) contents that are inadequate to fulfill the requirements of microorganisms. The differences in the stoichiometric ratios of these elements could limit the activity of microorganisms, which ultimately affects the microbial C, N use efficiencies (CUE, NUE) and the dynamics of soil C and N. The present study was aimed at quantifying the soil microbial nutrient limitation and exploring the mechanisms underlying microbial-induced C and N dynamics in chrono-sequence of restored grasslands. It was revealed that grassland restoration increased microbial C, N content, microbial C, N uptake, and microbial CUE and NUE, while the threshold elemental ratio (the C:N ratio) decreased, which is mainly due to the synergistic effect of the microbial biomass and enzymatic stoichiometry imbalance after grassland restoration. Finally, we present a framework for the nutrient limitation strategies that stoichiometric imbalances constrain microbial-driven C and N dynamics. These results are the direct evidence of causal relations between stoichiometric ratios, microbial responses, and soil C, N cycling.

Convolutional transformer attention network with few-shot learning for grassland degradation monitoring using UAV hyperspectral imagery

ABSTRACT In recent years, the desertification of grasslands has increased due to various factors, including both global warming and human activities. It is an essential basis for grassland degradation monitoring to monitor the dynamic change of desert grassland vegetation communities and distribution statistics. Although unmanned aerial vehicle (UAV) remote sensing images have allowed us to achieve dynamic real-time grassland monitoring, the distribution of desert grassland ground objects can be random and narrow, thus increasing the difficulty of sample labelling of remote sensing imagery. Therefore, to reduce the number of samples required for the model, this research proposes a convolutional transformer attention network (CTAN) to identify desert grassland ground objects and validate it on a self-collected desert grassland dataset. The network utilizes the transformer model to enhance its learning of global pixels so that it suppresses the transmission of background pixels within the network. Furthermore, the edge convolution module is designed to strengthen the network’s learning for edge pixels, improving its identification effect. The results show that the network provides 97.22% of overall accuracy (OA), 94.35% of average accuracy (AA), and 0.9398 of Kappa for ground object recognition in desert grassland. The model improves OA by 2.36–9.85% points compared to methods in the same field and 0.8–6.35% points compared to methods in hyperspectral imagery classification. The experimental results show the superior performance of the CTAN model for recognizing desert grassland objects, which helps the management and restoration of desert grasslands.

Soil, Plant, and Microorganism Interactions Drive Secondary Succession in Alpine Grassland Restoration.

Plant secondary succession has been explored extensively in restoring degraded grasslands in semiarid or dry environments. However, the dynamics of soil microbial communities and their interactions with plant succession following restoration efforts remain understudied, particularly in alpine ecosystems. This study investigates the interplay between soil properties, plant communities, and microbial populations across a chronosequence of grassland restoration on the Qinghai-Tibet Plateau in China. We examined five succession stages representing artificial grasslands of varying recovery durations from 0 to 19. We characterized soil microbial compositions using high-throughput sequencing, enzymatic activity assessments, and biomass analyses. Our findings reveal distinct plant and microbial secondary succession patterns, marked by increased soil organic carbon, total phosphorus, and NH4+-N contents. Soil microbial biomass, enzymatic activities, and microbial community diversity increased as recovery time progressed, attributed to increased plant aboveground biomass, cover, and diversity. The observed patterns in biomass and diversity dynamics of plant, bacterial, and fungal communities suggest parallel plant and fungal succession occurrences. Indicators of bacterial and fungal communities, including biomass, enzymatic activities, and community composition, exhibited sensitivity to variations in plant biomass and diversity. Fungal succession, in particular, exhibited susceptibility to changes in the soil C: N ratio. Our results underscore the significant roles of plant biomass, cover, and diversity in shaping microbial community composition attributed to vegetation-induced alterations in soil nutrients and soil microclimates. This study contributes valuable insights into the intricate relationships driving secondary succession in alpine grassland restoration.

The effects of grazing on flowering and fruiting phenology in South Brazilian subtropical grasslands

In subtropical grasslands, characterized by the coexistence of species with different physiology, for example C3 and C4 grasses, studies on the reproductive patterns of plants at the community level are scarce. Most available studies are limited to plant-pollinator interactions, and do not include grasses, even though knowledge on phenology of this species group is highly relevant, e.g., for grazing management or ecological restoration. In this study, we monthly evaluated flowering and fruiting in Brazilian subtropical grasslands under different grazing intensities (high, moderate, low, very low, ungrazed) over one year. To estimate the effect of the seasonal variation on the phenology of functional groups (C3 grass, C4 grass, monocots, dicots, shrubs) we used circular statistics. The highest flowering activity occurred in October and November, while fruiting peaked in March and April. Shrubs had the highest number of flowers and fruits, and C4 grasses contributed the largest number of fruiting species. The flowering peak of most functional groups occurred in October, except for C4 grasses and shrubs that peaked in February and November, respectively. Fruiting of C3 grasses peaked in December, C4 grasses and shrubs were most abundant in April and dicots, and monocots peaked in October. Grazing treatments differed considerably in flowering and fruiting patterns for all species groups. Monocots and dicots herbs showed high flowering activity under intense grazing. C3 grasses presented highest peaks in moderate and low grazing intensities, while C4 grasses peaked in very low grazing, and shrubs showed the highest peaks in ungrazed plots. Flowering and fruiting occurred throughout the year in our study system, with clear variation among functional groups in response to climatic and management patterns. Our results can guide seed collection in the field or vegetation cutting for hay transfer, and thus should lead to improvements in the ecological restoration of subtropical grasslands.

Precipitation and plant community-weighted mean traits determine total transpirable soil water in a desert grassland

The desert grassland has low precipitation, high evaporation and a limited soil water supply. Thus the tension between water shortage and sustainable vegetation restoration is increasingly evident. Change in total transpirable soil water (TTSW) reflects the water utilization and extraction capacity of plant communities, which are the basis for maintaining productivity and stability in communities, as well as the key ecological processes alleviating the above tension. Change in TTSW is influenced by precipitation, vegetation and soil. Quantifying the relative contribution of these factors to change in TTSW is key to the sustainable restoration of desert grassland. However, the current understanding of such effects remains limited. This study examined four typical plant communities in the Ningxia desert grassland, monitoring soil water content and evaluating plant community characteristics and diversity over three consecutive years. Using redundancy analysis and hierarchical partitioning methods, the influence of annual precipitation, vegetation (functional and species diversity, community characteristics) and soil physical properties on TTSW variation were investigated. Findings revealed: (1) The factors contributing to TTSW variation were annual precipitation (41 %-68 %,), vegetation (29 %-45 %), and soil physical properties (0 %-6.7 %). Specifically, community-weighted mean traits (CWM) and functional diversity (FD) explained TTSW variation by 24–37 % and 0.25–11 % respectively. In Gramineae communities, the influence of annual precipitation and vegetation on TTSW variation was consistent across soil depths. However, in degraded Sophora alopecuroides + Artemisia scoparia (SA) communities, the influence of vegetation (CWM, FD, community composition and community function) on TTSW variation was more pronounced in shallow soils (45 %) than in deeper soils (33 %), while annual precipitation effects were more substantial in the deep soil layers (66 %) than in the shallow soil layers (42 %). (2) Annual precipitation and CWM were the main biological and abiotic factors affecting TTSW. Interestingly, increased annual precipitation was negatively correlated with TTSW. Similarly, the primary controlling factor, CWM, also showed a significant negative relationship with TTSW. This relationship varied across community types and could be linear or quadratic, highlighting the need to understand the selection effects mediated by CWM in ensuring sustainable vegetation restoration. This research offers insights into the relationship between plant functional diversity and soil water retention function.

Dynamic monitoring of aboveground biomass in inner Mongolia grasslands over the past 23 Years using GEE and analysis of its driving forces

Aboveground biomass (AGB) in grasslands directly reflects the net primary productivity, making it a sensitive indicator of grassland resource quality and ecological degradation. Accurately estimating AGB over large regions to reveal long-term AGB evolution trends remains a formidable challenge. In this study, we divided Inner Mongolia Autonomous Region (IMAR) grasslands into three study regions based on their spatial distribution of grassland types. We combined remote sensing data with ground-based sample data collected over the past 19 years from 6114 field plots using the Google Earth Engine platform. We constructed random forest (RF) and traditional regression AGB inversion models for each region and selected the best-performing model through accuracy assessment to estimate IMAR grassland AGB for the period 2000–2022. We also examined the trends in AGB changes and identified the driving forces affecting IMAR grasslands through the application of Theil-Sen estimation, Mann-Kendall trend analysis, and the Geodetector model. The main findings are as follows: (1) Compared with the univariate parametric traditional regression model, the AGB monitoring accuracy of the multivariate non-parametric RF model in the three study regions increased by 5.94%, 5.08% and 19.14%, respectively. (2) The average AGB per unit area of IMAR grasslands from 2000 to 2022 was 731.41 kg/hm2, with alpine meadow having the highest average AGB (1271.70 kg/hm2) and temperate grassland desertification having the lowest (469.06 kg/hm2). IMAR grasslands exhibited an overall increasing trend in AGB over the past 23 years (6.01 kg/hm2•yr), with the increasing trend covering 83.52% of the grassland area and the decreasing trend covering 16.48%. (3) Spatially, IMAR grassland AGB showed a gradual decline from northeast to southwest and exhibited an increasing trend with increasing longitude (45.423 kg/hm2 per degree) and latitude (71.9 kg/hm2 per degree). (4) Meteorological factors were the most significant factors affecting IMAR grassland AGB, with precipitation (five-year average q value of 0.61) being the most prominent. In the western part of IMAR, where precipitation is consistently limited throughout the year, the primary drivers of influence were human activities, with particular emphasis on the number of livestock (with a five-year average q value of 0.44). It is evident that reducing human activity disturbance and pressure in fragile grassland areas or implementing near-natural restoration measures will be beneficial for the sustainable development of grassland ecosystems. The results of this research hold substantial reference importance for the protection and restoration of grasslands, the supervision and administration of grassland resources, as well as the development of policies related to grassland management.

Integrated Predictive Modeling and Policy Factor Analysis for the Land Use Dynamics of the Western Jilin

The external environment in the transitional zone of the ecological barrier is fragile, and economic growth has resulted in a series of land degradation issues, significantly impacting regional economic development and the ecological environment. Therefore, monitoring, assessing, and predicting land use changes are crucial for ecological security and sustainable development. This study developed an integrated model comprising convolutional neural network, cellular automata, and Markov chain to forecast the land use status of western Jilin, located in the transitional zone of the ecological barrier, by the year 2030. Additionally, the study evaluated the role of land use policies in the context of land use changes in western Jilin. The findings demonstrate that the coupled modeling approach exhibits excellent predictive performance for land use prediction in western Jilin, yielding a Kappa coefficient of 93.26%. Policy drivers play a significant role in shaping land use patterns in western Jilin, as evidenced by the declining farmland accompanied by improved land utilization, the sustained high levels of forest aligning with sustainable development strategies, the ongoing restoration of waters and grassland, which are expected to show positive growth by 2030, and the steady growth in built-up areas. This study contributes to understanding the dynamics of land use in the transitional zone of the ecological barrier, thereby promoting sustainable development and ecological resilience in the region.

Effect of green infrastructure on restoration of pollination networks and plant performance in semi‐natural dry grasslands across Europe

Abstract Agricultural intensification, afforestation and land abandonment are major drivers of biodiversity loss in semi‐natural grasslands across Europe. Reversing these losses requires the reinstatement of plant–animal interactions such as pollination. Here we assessed the differences in species composition and patterns of plant‐pollinator interactions in ancient and restored grasslands and how these patterns are influenced by landscape connectivity, across three European regions (Belgium, Germany and Sweden). We evaluated the differences in pollinator community assemblage, abundance and interaction network structure between 24 ancient and restored grasslands. We then assessed the effect of surrounding landscape functional connectivity (i.e. green infrastructure, GI) on these variables and tested possible consequences on the reproduction of two model plants, Lotus corniculatus and Salvia pratensis. Neither pollinator richness nor species composition differed between ancient and restored grasslands. A high turnover of interactions across grasslands was detected but was mainly due to replacement of pollinator and plant species. The impact of grassland restoration was consistent across various pollinator functional groups, whereas the surrounding GI had differential effects. Notably, bees, butterflies, beetles, and dipterans (excluding hoverflies) exhibited the most significant responses to GI variations. Interestingly, networks in restored grasslands were more specialised (i.e. less functionally redundant) than in ancient ones and also showed a higher number of insect visits to habitat‐generalist plant species. Landscape connectivity had a similar effect, with habitat‐specialist plant species receiving fewer visits at higher GI values. Fruit set in S. pratensis and L. corniculatus was unaffected by grassland type or GI. However, the fruit set in the specialist S. pratensis increased with the number of pollinator visits, indicating a positive correlation between pollinator activity and reproductive success in this particular species. Synthesis and applications. Our findings provide evidence of the necessity to enhance ecosystem functions while avoiding biotic homogenisation. Restoration programs should aim at increasing landscape connectivity which influences plant communities, pollinator assemblages and their interaction patterns. To avoid generalist species taking over from specialists in restored grasslands, we suggest reinforcing the presence of specialist species in the latter, for instance by means of introductions, as well as increasing the connectivity to source populations.

Photovoltaic systems promote grassland restoration by coordinating water and nutrient uptake, transport and utilization

The extensive use of fossil fuels puts ecological and economic coordinated development at risk. Photovoltaic systems relieve the pressure of resource extraction and energy generation on climate change, and their installation and module operation affect vegetation productivity and grassland restoration by changing the microenvironment and ecosystem processes. However, it is still unclear whether plants adapt to these changes in photovoltaic systems to sustain their growth. Here, combined stable isotope techniques with plant traits, plant adaptations to photovoltaic systems at different scales were analyzed from the perspectives of water and nutrient sources, uptake, transport, and utilization. The results showed that photovoltaic systems increased water uptake by the dominant species Leymus chinensis from the top 10 cm of the soil and the aboveground biomass. This was associated with strong plasticity of roots and conduction tissues, which improved resource uptake from the fertile surface soil and transport within the plant, and promoted photosynthesis and leaf water loss by inducing stomatal opening. Different from fixed photovoltaic systems, tracking photovoltaic systems improved ecosystem water use efficiency and surface soil nutrient availability by reducing soil temperature. Tilting tracking photovoltaic systems especially promoted biomass accumulation and grassland restoration. The study suggested that photovoltaic systems promoted vegetation restoration of grassland ecosystem in semi-arid region through the water and nutrient coordination and the carbon-water coupling, and provides a solution for reasonable planning of photovoltaic industry and sustainable socio-economic development.

Planting grass enhances relations between soil microbes and enzyme activities and restores soil functions in a degraded grassland.

Forage culture is a common way to restore degraded grasslands and soil functions, in which the reconstruction of the soil microbial community and its relationship with extracellular enzyme activity (EEAs) can characterize the recovery effects of degraded grasslands. However, the impacts of forage culture on the interaction between soil microbes and EEAs and whether the recovery effect of soil functions depends on the varying degradation statuses remain unclear. We conducted a plantation of a dominant grass, Leymus chinensis, in the soil collected from severe, moderate, light, and non-degradation statuses in the Songnen grassland in northeastern China. We measured soil microbial diversity and soil EEAs, and predicted microbial functional groups using FUNGuild. The results showed that L. chinensis culture promoted soil bacterial alpha diversity and soil EEAs only in the moderate degradation status, indicating a dramatic dependence of the recovery effects of the grass culture on degradation status of the grassland. After planting L. chinensis for 10 weeks, a decreasing trend in the chemoheterotrophy and nitrate-reduction microbial functional groups was found. In contrast, the abundance of the nitrogen (N)-fixing microbial functional group tended to increase. The positive correlation between soil EEAs and the nitrate-reduction and N-fixing microbial functional groups was enhanced by planting L. chinensis, indicating that grass culture could promote soil N cycle functions. We illuminate that grass culture may promote the restoration of soil functions, especially soil N cycling in degraded grasslands, and the recovery effect may depend on the grassland degradation status. We emphasized that selection of the plant species for restoration of grasslands needs to consider the restoration effects of microbial functional groups and soil functions.

Trends of Land Cover Change and Conservation Challenges of Grevy’s Zebra (Equus grevyi, Oustalet 1882) in Hallaydeghe Asebot Proposed National Park, Southeast Ethiopia

Large parts of biodiversity in protected areas (PAs) and their ecosystem services have been deteriorated due to land cover change over time. To reverse these effects, analysis of land cover change is essential. One of the protected areas, Hallaydeghe Asebot Proposed National Park (HAPNP), was assumed its land cover change and was undergone from one habitat type to others during the last three decades. As a result, wildlife species particularly Grevy’s zebra (Equus grevyi) in HAPNP are facing conservation challenges. Here, we aimed to examine the land cover changes of HAPNP for the period of 1990–2021 and assess Grevy’s zebra conservation challenges so as to improve the protection of the park and conservation of the species. Landsat images for the years 1990, 2006, and 2021 were generated to analyze land cover change of the study area. In addition, ground control points and information from elder and knowledgeable informants were collected to substantiate the result. Household survey, key informant interviews, and field observation checklist were utilized to collect data on conservation challenges. To generate land cover change maps, the satellite image for each period was classified using supervised classification. Content analysis was used to analyze conservation challenges of the species. The findings of this study revealed that 12.2% of grassland cover lost from 1990 to 2021 (i.e., an estimated annual average loss 0.4%). The remaining grassland cover in the HAPNP was aggregated in a small land area. On the other hand, the size of bushland increased by 26.4% during the same year (i.e., an estimated annual average gain 0.9%). These findings have implications for conservation and management of grazers. Major drivers for conservation challenges of Grevy’s zebra were habitat degradation, unintegrated development, and poor law enforcement practices. Grassland restoration program and species conservation challenges’ intervention strategy should be designed and implemented to safeguard the natural habitat and the species that occur in the HAPNP.

Effect of litter decomposition on mowing and plant composition change during Solidago stand restoration

Decomposition of organic matter supports important soil ecosystem services. The rate of decomposition depends mostly on the type of plant material being decomposed and the abundance and diversity of organisms that process the organic matter. Consequently, any disturbance to the soil ecosystem will affect the decomposition process. Invasive plants, such as Solidago species, pose a serious ecological threat to natural habitats, so effective and environmentally safe methods of controlling their occurrence should be developed. In this study, decomposition rates were used as indicators of soil health during grassland restoration after Solidago invasion. Different seed mixtures (grasses, grasses with legumes, seeds collected from a seminatural meadow; use of fresh hay and no seeds) were sown during a field experiment and different mowing frequencies (1, 2 and 3 times per year) were established. Two hypotheses were tested: (1) plant species composition used in the restoration process affects litter decomposition rates, and (2) mowing regimes affect litter decomposition rates. It was found that decomposition rates were higher in plots with the highest species diversity. This indicates that an increase in species diversity has a positive effect on soil processes. Secondly, mowing two and three times per season has a positive effect on the decomposition process. In conclusion, decomposition rates can be used as a tool to identify adequate grassland management.

Effects of fencing project on wind erosion reduction in Alpine grassland and its impact on the development of climbing dunes in southern Tibetan Plateau

AbstractAlpine grassland in the Tibetan Plateau (TP) of China is one of the most susceptible regions to wind erosion in recent decades. The fencing project, grassland enclosure using fencing, has been a common strategy for land degradation counteraction in the TP. However, the wind erosion reduction effects of fencing project remain largely unclear, especially in the regions lacking continuous observations such as Southern TP. In this study, a sand source area with fencing protection (fencing land, a mainly eroded grazing grassland before being fenced) and a near‐source climbing dune were selected to illustrate the effect of fencing project on wind erosion using 137Cs and 210Pbex tracing techniques. An adjacent perennial grazing land was selected for comparison. The results showed that the wind erosion rate in sand source area was 17.18 t·ha−1·year−1 before the implementation of project, while that was −6.67 t·ha−1·year−1 since fencing. The wind erosion rates in perennial grazing land were 24.91 t·ha−1·year−1 for 20 years ago to 1963 and 24.33 t·ha−1·year−1 for almost 20 years. The normalized difference vegetation index (NDVI) of sand source area increased from 0.098 before fencing to 0.137 after fencing; the latter was 1.63 times higher than that of grazing land during the same period. After the implementation of fencing project in sand source area, it was found that the sand supply to the climbing dune was mainly reduced, thus stabilizing it and promoting NDVI increase, especially in the middle‐lower part of the climbing dune. These results would benefit the evaluation of grassland restoration effectiveness in the TP.

Scales of Diversity Affecting Ecosystem Function across Agricultural and Forest Landscapes in Louisiana

Current land use and extensive modifications of natural ecosystems across the state of Louisiana are generally similar to those across the southeastern USA where rainfall supports forest ecosystems. Both intentional and unintentional consequences of ecosystem modifications from the scales of water and sediment movement across a field edge to state-wide loss of functional grasslands are legacies from previous development across the state. While major investments and large-scale, long-term plans are aspects of some continuing ecological issues across the state, small-scale, volunteer-led restoration of native grassland plant communities in the Louisiana Coastal Prairie illustrates the value associated with the restoration of natural ecosystem function in drastically disturbed environments. As is now becoming increasingly recognized, Louisiana grasslands represent less obvious components of forest, woodland, and wetland landscapes across the state, where they have contributed essential wildlife habitat, and ecosystem functions. These are now largely missing from many landscapes across the state and region. The strategic restoration of grassland functions combining novel native grass pastures and fully functional native grassland plant communities as landscape components could provide both economic and ecosystem benefits. Specific native grassland seed resources are needed for various restoration activities to enhance ecosystem function at a range of scales across the state and region.