Grassland Changes Research Articles

Untangling the effects of climate variation and human interference on grassland dynamics in North China

AbstractClimatic and anthropogenic disturbances play pivotal roles in shaping the dynamics of grassland. Quantifying their impacts on grassland variation is essential to ensure sustainable grassland management. In this study, we employed the Thornthwaite Memorial and Carnegie–Ames–Stanford‐approach (CASA) models to investigate the spatiotemporal effects of these two variables on grassland variation in northern China from 2000 to 2016, using the net primary productivity (NPP) as a measure. Our findings reveal that approximately 25.92% of the grassland in northern China experienced degradation, while restored grasslands occupied 45% of the total grassland area. The average grassland actual NPP (ANPP) and human‐induced NPP decreased at rates of −0.60 and −5.62 gC m−2 a−1, respectively. Conversely, potential NPP exhibited an upward trend with an average increase of 2.27 gC m−2 a−1. Furthermore, grassland ANPP showed a projected increase in most parts of northern China. Climate change emerged as the primary driver for grassland restoration in Xinjiang, Qinghai, and Inner Mongolia, leading to an increase of 21582.79 Gg C in grassland NPP. In contrast, human activities were the dominant catalysts for grassland degradation, resulting in a reduction of 51932.3 Gg C in grassland NPP. Human‐induced grassland degradation was ubiquitous in northwest and northeast China. With the exception of slope grassland, climate change primarily influenced the restoration of most grassland types, while human activities were the primary cause of degradation. Our analysis indicated a strong correlation between temperature and grassland degradation, while precipitation played a pivotal role in grassland restoration in northern China. Human interference demonstrated both positive and negative impacts on grassland changes. In conclusion, the increase in precipitation and the implementation of ecological restoration plans have effectively promoted the restoration of grasslands in northern China.

Nothing lasts forever: Dominant species decline under rapid environmental change in global grasslands

Abstract Dominance often indicates one or a few species being best suited for resource capture and retention in a given environment. Press perturbations that change availability of limiting resources can restructure competitive hierarchies, allowing new species to capture or retain resources and leaving once dominant species fated to decline. However, dominant species may maintain high abundances even when their new environments no longer favour them due to stochastic processes associated with their high abundance, impeding deterministic processes that would otherwise diminish them. Here, we quantify the persistence of dominance by tracking the rate of decline in dominant species at 90 globally distributed grassland sites under experimentally elevated soil nutrient supply and reduced vertebrate consumer pressure. We found that chronic experimental nutrient addition and vertebrate exclusion caused certain subsets of species to lose dominance more quickly than in control plots. In control plots, perennial species and species with high initial cover maintained dominance for longer than annual species and those with low initial cover respectively. In fertilized plots, species with high initial cover maintained dominance at similar rates to control plots, while those with lower initial cover lost dominance even faster than similar species in controls. High initial cover increased the estimated time to dominance loss more strongly in plots with vertebrate exclosures than in controls. Vertebrate exclosures caused a slight decrease in the persistence of dominance for perennials, while fertilization brought perennials' rate of dominance loss in line with those of annuals. Annual species lost dominance at similar rates regardless of treatments. Synthesis. Collectively, these results point to a strong role of a species' historical abundance in maintaining dominance following environmental perturbations. Because dominant species play an outsized role in driving ecosystem processes, their ability to remain dominant—regardless of environmental conditions—is critical to anticipating expected rates of change in the structure and function of grasslands. Species that maintain dominance while no longer competitively favoured following press perturbations due to their historical abundances may result in community compositions that do not maximize resource capture, a key process of system responses to global change.

The Spatiotemporal Change in Land Cover and Discrepancies within Different Countries on the Qinghai–Tibet Plateau over a Recent 30-Year Period

The Qinghai–Tibet Plateau is a unique global natural geographical unit with a high altitude and fragile ecology, where land cover change has been affecting its regional ecological security and sustainable development. The plateau covers nine countries with different variations in climate change and human activities, which cause significant spatial variations in its land cover change. This paper uses land cover data to reveal the spatiotemporal characteristics and multi-country differences in land cover change on the Qinghai–Tibet Plateau from 1992 to 2020 by applying spatiotemporal characteristic analysis and mapping methods. The results show that grassland (65.70%), bare land (15.56%), and woodland (10.25%) are the main types of land cover on the plateau, accounting for 91.51% of the total area. The interconversion of bare land and grassland was dominant in 1992–2020, with an area share of 67.83%. The turning point year of grassland change occurred in 2015. The grassland area increased by 6312 km2 in 1992–2015, while it decreased by 14,646 km2 in the plateau in 2015–2020. The areas of woodland, cropland, and water increased by 2.77%, 5.85%, and 7.57%, respectively, and the area of built-up land increased from 299.17 km2 to 1206.29 km2. Overall, a warming and wetting trend of the climate in the Qinghai–Tibet Plateau has driven the expansion of natural vegetation and water in the central plateau within China, with its natural vegetation area increasing by 0.11%. However, the development of regional warming and drying caused local grassland degradation, where Kyrgyzstan and India within the Qinghai–Tibet Plateau experienced the most prominent vegetation degradation. Human activities are relatively frequent in the Qinghai–Tibet Plateau within China and India, causing higher growth rates of built-up land and cropland than in other countries. The establishment of reserves and effective forest management policies have led to significant increases in woodland areas in China and Nepal within the plateau, while weak forest management and limited investment in forest conservation have led to high rates of deforestation in India and Myanmar. Accelerated temperature rises and regional differences in precipitation are the main drivers of large-scale land cover change on the plateau and differences in human activities and land use policies are responsible for the dramatic and diverse localized land cover change.

Land-Use-Change-Induced Cooling and Precipitation Reduction in China: Insights from CMIP6 Models

In the 21st century, the effect of land use/land cover change (LULCC) on climate has become an area of active research. To explore the effects of LULCC on temperature and precipitation in China, we used outputs from the BCC-CSM2-MR, CESM2, IPSL-CM6A-LR, and UKESM1 models, which participated in the Land Use Model Intercomparison Project (LUMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on these models, we identified temporal variations in precipitation and near-surface air temperature (hereinafter temperature) with and without historical land use changes and their relation with LULCC in China during 1850–2014. We then determined the significant changing period (1972–2012) and revealed the relation between the spatial distribution of historical change in vegetation cover types, precipitation, and temperature. The results showed that annual historical precipitation decreased faster (132.23 mm/(1000 a) faster), while annual historical temperature increased slower (2.70 °C/(1000 a) slower) than that without LULCC during 1850–2014. LULCC not only influenced surface properties to change local precipitation and temperature distributions and mean values, but also affected other components through atmospheric circulations due to typical monsoon characteristics in China. The relative contribution of grassland change to precipitation variation was the largest, while relatively, cropland change contributed the most to temperature variation. Our study innovatively used new model outputs from LUMIP to analyze the impacts of LULCC on precipitation and temperature, which can help to guide and improve future land use management and predictions of precipitation and temperature.

Vegetation structural shift tells environmental changes on the Tibetan Plateau over 40 years

Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm.

Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River

Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices and NPP changes in three major vegetation types (forest, grassland, and shrubland) in the upper and middle reaches of the Yellow River Basin using a random forest model. The results showed that landscape fragmentation increased, leading to higher landscape heterogeneity and edge effects. Patch shapes became more irregular, and spatial distribution became more dispersed. From 2000 to 2015, both vegetation types and NPP showed significant spatial heterogeneity in the study area. The number of patches (NP), largest patch index (LPI), and percent-like adjacency (PLADJ) metrics were used to determine the core landscape characteristics to assess the NPP changes in forest, shrubland, and grassland, respectively. This study provides a basis for understanding the relationships among landscape patterns, vegetation types, and NPP and serves as a reference for developing NPP predictive models in the Loess Plateau region.

Spatio-temporal modelling of the effect of environmental and land-use factors on species-rich calcareous grasslands

The abundance of sensitive plant species in calcareous grasslands is threatened by agricultural intensification with nutrient addition and increased livestock densities as well as by land abandonment. The Hill-Shannon diversity is decreasing, and the species composition of Danish calcareous grassland is generally unstable and is expected to experience further change in the coming years. In order to quantify the effects of selected environmental and land-use factors on the observed variation and changes in the vegetation of calcareous grasslands, large-scale spatial and temporal pin-point plant cover monitoring data are fitted in a structural equation model. The analyzed vegetation data come from 100 Danish sites monitored over an eight-year period. The important sources of measurement and sampling uncertainties have been included using a hierarchical model structure. Furthermore, the measurement and sampling uncertainties are separated from the process uncertainty, which is important when generating ecological predictions that may feed into local conservation management decisions. There were significant negative effects of grazing and nitrogen deposition on the change in cover of sensitive plant species. Whereas the negative effect of nitrogen deposition on the cover of sensitive species was expected, it was surprising that the model results suggest that sensitive species may be subjected to overgrazing by the grazing regimes that are currently applied at protected Danish calcareous grasslands. The standardized regression coefficients suggest that the effects of both grazing and nitrogen deposition are relatively benign compared to the effects of soil type, soil pH and precipitation. The relatively large effect of precipitation is interesting, since it is predicted that the amount of precipitation and its distribution over the seasons will change due to climate change, and the results suggest that climate change may lead to important species compositional changes in calcareous grasslands. The fitted model may be used to quantify the uncertainties when generating ecological forecasting and local adaptive management plans. More specifically, this study suggests that it is relevant to rethink the currently used criteria for vegetation height when assessing the conservation status of calcareous grasslands.

Reconstruction of Forest and Grassland Cover for the Conterminous United States from 1000 AD to 2000 AD

Spatially explicit reconstruction of historical land cover change is a prerequisite for a more comprehensive understanding of environmental changes. Anthropogenic activities have dramatically altered the land cover of the conterminous United States (CONUS), encroaching heavily on the primary vegetation. However, few datasets exist that depict the historical trajectory of forest and grassland cover changes in CONUS over the last millennium, and previous efforts have only focused on reconstructions for the last four centuries. By integrating remote sensing-derived land use/cover change (LUCC) data and potential vegetation data, we determined the potential extent of natural forest (PENF) and grassland (PENG) in CONUS. Based on a qualitative analysis of the trends and driving forces of forest and grassland changes, we devised a method of subtracting reconstructed historical cropland (1000–2000 AD) and built-up land (1850–2000 AD) from PENG and PENF to reconstruct a 5 min × 5 min grid dataset of forest and grassland cover at 13 time-points over the past millennium. The results showed that forest and grassland cover in CONUS underwent a slow decline (1000–1600 AD), an accelerated decline (1600–1800 AD), a dramatic decline (1800–1950 AD), and finally, a recovery (1950–2000 AD) over the study period. The modelled forest fraction decreased from 49% in 1000 AD to 33% in 2000 AD, representing a 32% area reduction, whereas the modelled grassland fraction decreased from 37% to 22%, representing a 42% area reduction. The reduction occurred primarily in the last 200 years, with forest and grassland reductions accounting for 86% and 97% of the total reduction over the millennium, respectively. Spatially, more than 80% of the land was originally covered by forests and grasslands, and the loss occurred mainly in the eastern CONUS and Great Plains over the past millennium. After the 1930s, farmland abandonment began in central and eastern CONUS, simultaneously with environmental protection laws. Federal government regeneration programs for forest and grassland resources and the Shelterbelt Project all contributed to a slowdown in forest and grassland decline and recovery in cover.

Changes in grassland soil types lead to different characteristics of bacterial and fungal communities in Northwest Liaoning, China.

Soil microbial communities are critical in regulating grassland biogeochemical cycles and ecosystem functions, but the mechanisms of how environmental factors affect changes in the structural composition and diversity of soil microbial communities in different grassland soil types is not fully understood in northwest Liaoning, China. We investigated the characteristics and drivers of bacterial and fungal communities in 4 grassland soil types with 11 sites across this region using high-throughput Illumina sequencing. Actinobacteria and Ascomycota were the dominant phyla of bacterial and fungal communities, respectively, but their relative abundances were not significantly different among different grassland soil types. The abundance, number of OTUs, number of species and diversity of both bacterial and fungal communities in warm and temperate ecotone soil were the highest, while the warm-temperate shrub soil had the lowest microbial diversity. Besides, environmental factors were not significantly correlated with soil bacterial Alpha diversity index. However, there was a highly significant negative correlation between soil pH and Shannon index of fungal communities, and a highly significant positive correlation between plant cover and Chao1 index as well as Observed species of fungal communities. Analysis of similarities showed that the structural composition of microbial communities differed significantly among different grassland soil types. Meanwhile, the microbial community structure of temperate steppe-sandy soil was significantly different from that of other grassland soil types. Redundancy analysis revealed that soil total nitrogen content, pH and conductivity were important influencing factors causing changes in soil bacterial communities, while soil organic carbon, total nitrogen content and conductivity mainly drove the differentiation of soil fungal communities. In addition, the degree of connection in the soil bacterial network of grassland was much higher than that in the fungal network and soil bacterial and fungal communities were inconsistently limited by environmental factors. Our results showed that the microbial community structure, composition and diversity of different grassland soil types in northwest Liaoning differed significantly and were significantly influenced by environmental factors. Microbial community structure and the observation of soil total nitrogen and organic carbon content can predict the health changes of grassland ecosystems to a certain extent.

Disentangling the Complexity of Regional Ecosystem Degradation: Uncovering the Interconnected Natural-Social Drivers of Quantity and Quality Loss

In the face of the combined effects of economic development and climate change, ecosystems are experiencing unprecedented pressures. It is imperative to diagnose changes in the quantity and quality of ecosystems, as well as identify the integrated natural and social driving mechanisms that underlie these changes, in order to facilitate ecosystem restoration and maintenance. In this study, we analyzed the changes in forest, grassland, farmland, and water ecosystems in Hubei Province, China from 2000 to 2020. We examined the changes in ecosystem quantity by assessing their area, and for evaluating ecosystem quality, we utilized an ecosystem quality index (EQI). To further understand the integrated natural–social driving mechanisms behind the degradation of different types of ecosystems, we selected four natural factors and fifteen socio-economic factors, based on the influences of climate change and human activities. We employed stepwise regression models for analysis. Our study reveals significant degradation of farmland and grassland ecosystems in Hubei Province from 2000 to 2020, reducing by 5.16% and 82.46%, respectively. The water ecosystems have slightly decreased by 1.08%, while and the forest ecosystems has increased by 2.64%. The analysis further highlights that the total area of ecosystem quality degradation in Hubei Province reached 5.34%. Additionally, our findings indicate that human activities have a greater impact on the quantitative degradation of ecosystems, while climate change has a greater impact on the quality degradation of ecosystems. Specifically, the forestry output value has a significant negative impact on the area of farmland and grassland ecosystems, while rural per capita net income and fishery output value have a significant negative impact on water area. Annual precipitation and annual average temperature have a significant positive effect on the quality of ecosystems in the good-quality level, while ecosystems in the low-quality level are mainly influenced by annual evaporation. Our results provide valuable insights for policymakers seeking to restore and manage ecosystems effectively in order to promote regional sustainable development.

Spatial-Temporal Characteristics and Driving Forces of Aboveground Biomass in Desert Steppes of Inner Mongolia, China in the Past 20 Years

The desert steppe serves as a transitional zone between grasslands and deserts, and long-term monitoring of aboveground biomass (AGB) in the desert steppe is essential for understanding grassland changes. While AGB observation techniques based on multisource remote-sensing data and machine-learning algorithms have been widely applied, research on monitoring methods specifically for the desert steppe remains limited. In this study, we focused on the desert steppe of Inner Mongolia, China, as the study area and used field sampling data, MODIS data, MODIS-based vegetation indices (VI), and environmental factors (topography, climate, and soil) to compare the performance of four commonly used machine-learning algorithms: multiple linear regression (MLR), partial least-squares regression (PLS), random forest (RF), and support vector machine (SVM) in AGB estimation. Based on the optimal model, the spatial–temporal characteristics of AGB from 2000 to 2020 were calculated, and the driving forces of climate change and human activities on AGB changes were quantitatively analyzed using the random forest algorithm. The results are as follows: (1) RF demonstrated outstanding performance in terms of prediction accuracy and model robustness, making it suitable for AGB estimation in the desert steppe of Inner Mongolia; (2) VI contributed the most to the model, and no significant difference was found between soil-adjusted VIs and traditional VIs. Elevation, slope, precipitation, and temperature all had positive effects on the model; (3) from 2000 to 2020, the multiyear average AGB in the study area was 58.34 g/m2, exhibiting a gradually increasing distribution pattern from the inner region to the outer region (from north to south); (4) from 2000 to 2020, the proportions of grassland with AGB slightly and significantly increasing trend in the study area were 87.08% and 5.13%, respectively, while the proportions of grassland with AGB slightly and significantly decreasing trend were 7.76% and 0.05%, respectively; and (5) over the past 20 years, climate change, particularly precipitation, has been the primary driving force behind AGB changes of the study area. This research holds reference value for improving desert steppe monitoring capabilities and the rational planning of grassland resources.

Seasonal Spatiotemporal Changes in the NDVI and Its Driving Forces in Wuliangsu Lake Basin, Northern China from 1990 to 2020

In the context of global climate change, many studies have focused on the interannual vegetation variation trends and their response to precipitation and temperature, but ignored the effects of seasonal variability. This study explored the relationship between normalized difference vegetation index (NDVI) and seasonal climate elements in the Wuliangsu Lake Basin area from 1990 to 2020, and quantified the impacts of human activities on vegetation dynamics. We used Landsat series data to analyze the spatial and temporal variation of the NDVI using the trend analysis method, the Theil–Sen median, the Mann–Kendall test, and the Hurst index. Then, we used meteorological data and land use data to quantify the effects of human activities using residual analysis, and correlation methods to determine the driving forces of NDVI variations. The results showed that the NDVI changes presented obvious regional characteristics, with a decreasing trend from southeast to northwest in Wuliangsu Lake Basin. Due to global warming, the start of the growing season (SOS) is 4.3 days (2001 to 2010) and 6.8 days (2011 to 2020) earlier compared with 1990 to 2000. The end of the season (EOS) is advanced by 3.6 days (2001 to 2010), and delayed by 8.9 days (2011 to 2020). Seasonal (spring, summer, autumn, and winter) NDVIs with precipitation and temperature show spatial heterogeneity. Further, changes in grasslands and woodlands were vulnerable to climate change and human activities. Since the beginning of the 21st century, human activity was the driving force for vegetation improvement in the Dengkou, west-central, north and southwest regions, where ecological instability is weak. This finding can provide a theoretical basis for the implementation of the same type of ecological restoration projects and the construction of ecological civilization, and contribute to the regional green and sustainable development.

Spatiotemporal variations in the soil quality of agricultural land and its drivers in China from 1980 to 2018

Soil quality is essential for maintaining the sustainability of agroecosystems, especially under intensified agricultural activities and rapid land use change. The sampling and analysis of soil properties to assess the status of agricultural land is widely practiced at the field scale; however, the spatiotemporal variations in soil quality and its influencing factors at a large scale remain unclear. Here, we quantified spatiotemporal variations in the soil quality of agricultural land in China during 1980–2018 by using the soil quality index (SQI) area approach, and explored the drivers with a geographical detector method. The results showed that the distribution of the SQI in the two periods had a similar spatial trend, except for that in the southwest (SWC), and the SQI decreased from north to south regardless of land use type. The soil quality of woodland was comparatively good with mean SQI values of 1.55 and 1.53 in 1980 and 2018, respectively, followed by that in grassland and cropland. Soil organic carbon, total nitrogen and cation exchange capacity were the dominant soil indicators explaining the spatial heterogeneity of the SQI in all land uses; moreover, climatic factors (i.e., temperature and precipitation) showed a stronger effect on woodland. From 1980 to 2018, the SQI of grassland decreased deeply, especially in the SWC, which showed a severe decline of 12.5 %. The changes in precipitation and temperature were identified as the largest drivers of SQI temporal changes in woodland and grassland, respectively, and their interaction achieved the highest impact across all land uses. In addition, the bidirectional conversion between cropland and grassland in recent decades has aggravated the deterioration of soil quality. Therefore, quantifying spatiotemporal changes in the SQI and elucidating the role of factors influencing soil quality in agroecosystems can provide a guide for designing sustainable agriculture policies and improving environmental quality.

Beyond "greening" and "browning": Trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation.

Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long-term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modeling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002-2020 time series, and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non-photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote sensing-based monitoring of trends in grasslands so that underlying processes can be discerned.

Metagenomic insights into the response of rhizosphere microbial to precipitation changes in the alpine grasslands of northern Tibet

Water changes caused by precipitation may affect the elemental cycle of ecosystems by influencing soil microorganisms. In this study, precipitation control experiment was conducted in semi-arid alpine grasslands in northern Tibet, and plots were set up and divided into increased water (IW) and decreased water (DW) plots. Moreover, the link between functional genes and soil environmental factors, and the responses of the microbial community functions to precipitation-induced water variations were studied using metagenomic sequencing. To clarify the roles of various proteins and metabolites in the semi-arid alpine grasslands of northern Tibet, functional annotations of clusters of orthologous groups of proteins, Kyoto Encyclopedia of Genes and Genomes, and carbohydrate-active enzyme of the sequencing data were conducted. The results showed that the absolute abundance of microbial functional genes in IW was significantly higher than that in the control check (CK, natural precipitation) and DW. However, the absolute abundance did not significantly differ between CK and DW. There was no significant difference among the four plant species (Stipa purpurea, Carex moocroftii, Othropis microphylla, and Artemisia capillaris) considered in this study. These results indicated that microbial functions were mainly affected by water and do not depend on the species, and that the effect of IW was greater than that of DW. Further, we found that soil C, N, K, and other nutrients play vital roles in microbial growth, microbial functional genes were not affected by pH; however, soil C, N, and K nutrients and functional genes were negative correlated. Overall, this study enhances our understanding of the responses of microorganisms to precipitation and can be used as a valuable reference for understanding the drought resistance of soil microorganisms in semi-arid and alpine regions.

Impacts of watershed management on land use/cover changes and landscape greenness in Yezat Watershed, North West, Ethiopia.

In Ethiopia, watershed management interventions have been implemented since the 1980s to curve land degradation and improve the agricultural productivity of smallholder farmers. However, little effort has been made to investigate the impacts of watershed management on land use/cover changes and landscape greenness. Thus, this study was conducted to assess the long-term impacts of watershed management on land use/cover changes and landscape greenness in the Yezat watershed. Landsat images for 1990, 2000, 2010, and 2021 were employed and analyzed to produce maps of the respective years using GIS and remote sensing techniques. Data from satellite images, coupled with field observation and the socio-economic survey, revealed an effective approach for analyzing the extent, rate, and spatial patterns of land use/cover changes. Normalized difference vegetation index (NDVI) was also employed to detect vegetation greenness. The results of the study show that between 1990 and 2021, the built-up area, plantation, natural forest, shrubland, and grasslands were increased by + 254ha, + 712.3ha, 196.3ha, + 1070.8, and + 425.3ha respectively due to watershed management interventions. Conversely, cultivated land was decreased with a rate of - 2658.7ha, in the study area. However, the reverse is true between 1990 and 2000 due to large-scale land degradation. Besides, the result of the study also shows that a low landscape greenness value (- 0.11) was observed between 1990 and 2000, and a high landscape greenness value (+ 0.2) was observed between 1990 and 2021. The observed change in landscape greenness in the watershed was due to the change in shrubland (+ 1070.8ha), grassland (+ 425.3ha), plantation (+ 712.3ha), and forestland (+ 196.3ha) covers between 1990 and 2021years. Such observed changes in land use land covers, landscape greenness, and cultivated land in the study watershed have important implications for the improvement of soil moisture, soil fertility, biodiversity, groundwater recharge, carbon sequestration, soil erosion land, crop yield, and ecosystem services.

The role of dominant prairie species ecotypes on plant diversity patterns of restored grasslands across a rainfall gradient in the US Great Plains

AbstractQuestionsA robust ecosystem requires a functionally heterogeneous community of organisms with ecological traits that permit broad resource partitioning. Understanding community diversity patterns can help investigate drivers of community assembly and assess restoration success. Do biodiversity patterns differ among grassland communities sown with different ecotypes of dominant species during restoration along a rainfall gradient in the tallgrass prairie of the central US Great Plains?LocationFour field sites across a rainfall gradient within the North American Great Plains: Colby, Kansas (39°23′17.8″N, 101°04′57.4″W), Hays, Kansas (38°51′13.2″N, 99°19′08.6″W), Manhattan, Kansas (39°08′22.3″N, 96°38′23.3″W), and Carbondale, Illinois (IL, 37°41′47.0″N, 89°14′19.2″W).MethodsWe applied linear mixed models to assess the effect of dominant species ecotype, year, and location on grassland taxonomic, phylogenetic, and functional diversity.ResultsThe non‐local grass ecotype (compared to the local ecotype) promoted species richness. In contrast, the effect of the dominant species ecotype on phylogenetic or functional diversity was site‐specific over the 10‐year restoration. Richness decreased across the rainfall gradient from dry to moist sites, and the wettest site had the highest phylogenetic and functional diversity.ConclusionsOur results suggest that abiotic filtering by rainfall is a key assembly mechanism that could predict grassland changes in biodiversity in the early restoration phases. Given the community response across the tallgrass prairie, restoration practitioners should consider the impact of regional sources of dominant species used in restoration when biodiversity is a restoration goal. It is recommended for future grassland restoration to detect gaps and limitations in evolutionary and trait structure that will reveal which diversity components to evaluate.

Rangeland resilience to droughts: Changes across an intensification gradient

AbstractAimThe intensification of livestock systems generates structural and functional changes in native grassland, which alter their capacity to respond to disturbances. Our objective was to evaluate the resilience to an extraordinary consecutive‐droughts event, across an intensification gradient of livestock systems. Our prediction was that sites with more intensive management (less diverse) will have lower resilience (as resistance and/or recovery) to drought.LocationSouth‐central region of Uruguay.MethodsWe evaluated the resilience (as resistance and recovery) to consecutive droughts, across an intensification gradient of livestock systems. We analyzed the effect of diversity on resilience at two scales: (1) regional — an observational experiment with real commercial farms, where we compared three systems with an increasing level of intensification that determine changes in diversity, (2) patch — we carried out a manipulative experiment with different grazing management intensities determined by the level of biomass removal and fertilization. In both experiments, resistance and recovery were calculated from the Normalized Difference Vegetation Index.ResultsThe most intensified and less diverse management (sown pastures) had significantly lower resistance than native and overseeded grassland. Also, it showed the lowest recovery rate, and its productivity did not reach previous values after the drought's end. The grazing intensification gradient at the plot scale did not show clear differences among treatments both for resistance and recovery. However, resistance of the individual plots showed a positive significant association not only with species richness and diversity, but also with evenness and diversity of functional groups.ConclusionOur research supports the insurance hypothesis by demonstrating that farms with greater biodiversity (less intensive management) have higher resistance to drought. We found that species richness is not enough to account for the effect of diversity on resilience. Our results emphasize the importance of preserving grassland biodiversity to maintain resilient ecosystems in the face of climate change.

Vegetation change in acidic dry grasslands in Moravia (Czech Republic) over three decades: Slow decrease in habitat quality after grazing cessation

AbstractAimsShallow soils on acidic bedrock in dry areas of Central Europe support dry grasslands and heathlands that were formerly used as extensive pastures. These habitats are of high conservation value, but their abandonment in the 20th century triggered slow natural succession that poses a threat to specialized plant species. We asked how this vegetation and its plant diversity have changed over the past three decades and whether protected areas have positively affected habitat quality.LocationSouthwestern and central Moravia, Czech Republic.MethodsIn 2018–2019, we resurveyed 94 vegetation plots first sampled in 1986–1991 at 47 acidic dry grassland and heathland sites. We compared the number of all vascular plant species, Red List species and alien species per plot using parametric and non‐parametric tests, life‐form spectra using the chi‐square test, species composition using detrended correspondence analysis, and indicator values using a permutation test. We also compared these changes between sites within and outside protected areas.ResultsVegetation changes over the past three decades have been relatively small. However, we detected a decrease in total species richness, the number of Red List species and the number of characteristic species of dry grasslands. Neophytes were infrequent, while archaeophytes increased slightly. The competitive tall grass Arrhenatherum elatius, annual species and young woody plants increased in abundance or newly established at many sites. Indicator values did not change except for a slight increase in nutrient values. These negative trends occurred both within and outside protected areas but were more pronounced outside.ConclusionsFormerly grazed acidic dry grasslands and heathlands in Moravia are slowly losing habitat specialists, including threatened plant species, and are increasingly dominated by Arrhenatherum elatius. Conservation management, especially cutting in protected areas, slows down the negative trends of decline in plant diversity and habitat quality but is insufficient to halt these processes completely.

Clipping increases ecosystem carbon use efficiency by decreasing the dominance of grasses

Ecosystem carbon use efficiency (CUE) is a critical variable in quantifying the efficiency and capacity of an ecosystem to sequestrate carbon (C) from the atmosphere. However, how CUE responds to land-use change and climate warming remains elusive and lacks empirical evidence. We implemented a field manipulative experiment to examine the effects of clipping and warming on CUE in an alpine meadow on the Qinghai-Tibetan Plateau over 7 years. The results showed that clipping significantly increased CUE by 7.1%, which was mainly attributed to the stronger positive effects of clipping on gross ecosystem productivity (GEP, 13.0%) than on ecosystem respiration (ER, 5.3%). In contrast, warming had a minor effect on CUE due to the synchronized increase in GEP (8.8%) and ER (7.3%). There was no significant interactive effect of clipping and warming on CUE. Moreover, the dominance of grasses played a pivotal role in controlling the responses of CUE to clipping and warming by increasing ecosystem C uptakes but decreasing microbial decomposition. Soil temperature and above-ground net primary productivity also contributed to the changes in CUE under clipping and warming. These results suggest that clipping once a year at the end of the growing season could increase the efficiency of this alpine meadow for C sequestration, while climate warming could not change ecosystem C use efficiency. We highlight that the dominance of grasses is an emerging property in determining CUE under land-use change and climate warming in grasslands.