Grassland Areas Research Articles

How will ecosystem carbon sequestration contribute to the reduction of regional carbon emissions in the future? analysis based on the MOP-PLUS model framework

Carbon neutralization of land use and land cover (LULC) has become an important way for countries to cope with future climate change. Existing studies focus on the quantification and analysis of historical and current carbon storage and emissions but lack an understanding of future LULC carbon storage and emissions, which limits the practical guiding value of research findings for regional dynamic management and scientific decision-making. In this study, the temporal and spatial distribution patterns of carbon dynamics in different ecosystems, such as forest, cropland and grassland, in the West Liao River Basin (WLRB) since 1990 were quantitatively assessed. Grey multiple objective programming (G-MOP) and patch‑generating land use simulation (PLUS) models were used to predict the LULC distribution, carbon emissions and carbon storage under the sustainable development scenario (SDS) in the WLRB in 2030 and 2060, and a comparative analysis was performed with other development scenarios. The overall area of grassland and forest ecosystems showed an upwards trend from 1990 to 2020, while the area of farmland ecosystems slightly decreased. In the western part of the WLRB, net ecosystem production (NEP) showed high aggregation, and low NEP showed an aggregation effect in the urban area. Under the economic development scenario (EDS) in 2030 and 2060, cropland and impervious layers will be further expanded, carbon emissions will be the highest, and the carbon storage amount will be the lowest. Under the ecological protection scenario (EPS), the water area and forest area increased significantly, carbon emissions were the lowest, and carbon storage was the highest. Under the SDS scenario, the areas of cropland, forest, impervious layer and water body are moderate, and the carbon budget is better than that under the natural development scenario (NDS). Under these three scenarios, the barren area is lower than that of the natural development scenario. Considering the economic benefit, ecological benefit and carbon budget, the SDS scenario has the best performance. This study provides a new perspective for discussing the future carbon budget status of small-scale watershed areas and combines the goals of “sustainable development” and “dual carbon”. It provides a data-supported basis for discussing the diversified ecological compensation mechanism of the WLRB from the perspective of carbon neutrality as well as insights for the formulation of regional LULC optimization management policies.

Effectiveness of two mechanical shrub removal treatments for restoring sub-alpine grasslands colonized by re-sprouting woody vegetation

The extent of European sub-alpine grasslands and their associated ecosystem services are decreasing due to woody plant encroachment. Commonly used methods of woody vegetation suppression like prescribed burning or clearcutting usually cause little damage to belowground bud-banks, offering poor results against re-sprouting shrubs. In this study, we assessed the effects on vegetation and soil properties of two mechanical shrub removal methods for restoring sub-alpine grasslands colonized by the re-sprouting shrub Rosa sp. in the Central Spanish Pyrenees: a commonly used method based on clearcutting (Clearcutting); and a non-previously assessed method based on pulling shrubs off the soil to remove both the aerial and belowground bud-banks (Uprooting). We set a parallel experiment to test whether or not clustering Rosa sp. debris generated in Uprooting (which held many mature fruits) at certain grassland locations may promote colonization of new grassland spots by Rosa sp. seedlings. By the end of the study period, vegetation composition and structure was more similar to the reference grassland in Uprooting than in Clearcutting. Indeed, woody vegetation cover was 71 % smaller in Uprooting than in Clearcutting three years after shrub removal. Nevertheless, by the end of the study period, chemical and microbiological soil properties were slightly more similar to the reference grassland in Clearcutting than in Uprooting. Additionally, the results of our study showed that clustering unusually high number of mature fruits of Rosa sp. at certain grassland locations increased shrub seedling colonization in comparison with other areas of the reference grassland, indicating that operational planning needs to take into account shrub phenology. In conclusion, our work showed that Uprooting may be a useful tool for land managers aiming to restore sub-alpine grasslands colonized by re-sprouting shrubs, though it is advisable using it for scatter shrub patches to prevent significant medium to long-term soil disturbance at landscape scale.

Response of Grassland Vegetation Growth to Drought in Inner Mongolia of China from 2002 to 2020

Drought poses a significant environmental risk and can deeply affect the growth of grasslands. However, there is still uncertainty regarding the precise impact of varying levels of drought on grassland growth. To address this gap, we utilized several key indicators, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Global Orbiting Carbon Observatory-2-based Solar-induced Chlorophyll Fluorescence (GOSIF), and Gross Primary Productivity (GPP), in conjunction with drought indices (the Standardized Precipitation Evapotranspiration Index (SPEI) and soil moisture (SM). Our study aimed to comprehensively assess the consistency of spatiotemporal patterns in grassland vegetation and its responsiveness to different drought levels in the Inner Mongolia region from 2002 to 2020. The results indicated that NDVI, EVI, GOSIF, and GPP in grassland vegetation across Inner Mongolia exhibited significant increasing trends from 2002 to 2020. Specifically, NDVI, EVI, GOSIF, and GPP all displayed consistent spatial patterns, with 25.83%, 21.18%, 22.65%, and 48.13% of the grassland area showing significant increases, respectively. Drought events, as described through SPEI and SM, from June 2007 to September 2007 and June 2017 to July 2017 were selected to evaluate the response of grassland vegetation to drought. The drought events of 2007 and 2017 resulted in reductions in NDVI, EVI, GOSIF, and GPP relative to the multi-year average (2002–2020). GOSIF exhibited a more intense response to drought, suggesting that GOSIF may reflect the inhibition of water stress on grassland photosynthesis better than NDVI and EVI for the drought in 2007 and 2017. The reductions in NDVI, EVI, GOSIF, and GPP in grassland increased significantly across different drought levels, with the sharpest reductions observed during extreme drought. Under the severe and extreme drought events, the most substantial reductions in NDVI, EVI, GOSIF, and GPP were observed in the temperate steppe (TS). Moreover, the effects of different drought severity levels within the same grassland type varied, with the most significant reductions in NDVI, EVI, GOSIF, and GPP observed during extreme drought. Our results provide new perspectives for developing and implementing effective strategies to address grassland carbon cycling management and climate change in Inner Mongolia.

Land use significantly improved grassland degradation and desertification states in China over the last two decades

China possesses extensive grasslands primarily located in dryland regions, which are highly susceptible and fragile to climate change and human intervention, making them prone to degradation and desertification. In recent decades, China has implemented numerous ecological projects to improve the states of ecosystems. Additionally, recent studies have revealed the critical roles of rising CO2 on dryland greening. However, it is still limited to understand the contributions of anthropogenic recovery and CO2 fertilization, as well as other climate factors, to the dynamics of grassland degradation and desertification in China. To address these gaps, we employed a two-step approach to differentiate between grassland degradation and desertification as distinct processes across the grasslands and sparsely vegetated lands in China. This involved assessing degradation within existing grassland areas and identifying the conversion of grasslands into desert regions. The study period of 2000–2020 was examined to determine the occurrence of grassland desertification, which suggested a significant decrease in the desertification area in China. Subsequently, the time series of the Enhanced Vegetation Index (EVI) during the growing season was analyzed to track vegetation dynamics. Since the beginning of the 21st century, a significant greening trend has been observed in approximately 97% of the study area. Furthermore, we quantified the effects of anthropogenic climate change (ACC), climate change, and land use change on grassland degradation and desertification in China. The analyses indicated that 50.7% of the observed vegetation changes in the study area from 2000 to 2020 were primarily driven by land use, followed by the effects of rising CO2, accounting for 42.1% of the changes. These findings provided some insights on developing regionally-targeted strategies for grassland conservation in China.

Evaluating changes with vegetation cover in PRISMA's spectral, spatial, and temporal attributes and their performance for classifying savannahs in Brazil

The recent advent of hyperspectral satellites with larger swath width than that of previous sampling missions brings new perspectives for mapping savannahs in Brazil. Here, we evaluated changes with vegetation cover in different spectral, spatial, and temporal attributes, derived from the PRecursore IperSpettrale della Missione Applicativa (PRISMA), and their performance for Random Forest (RF) classification of savannah physiognomies at the Brasília National Park (BNP). To obtain the spectral attributes, we selected a PRISMA image acquired during the local dry season (August 17, 2020). We evaluated the classification performance of the reflectance of 166 bands, 22 vegetation indices (VIs), and four endmember fractions derived from a linear spectral mixture model (SMA). In addition, 24 parameters describing the depth, area, width, and asymmetry of the absorption bands centred at 680 nm (chlorophyll), 980 nm and 1200 nm (leaf water), and 1750 nm, 2100 nm and 2300 nm (lignin-cellulose) were also considered in the analysis. For the spatial attributes, we tested the performance of 8 Gray Level Co-occurrence Matrix (GLCM) metrics of image texture associated with the 864-nm near-infrared (NIR) band. In order to determine the temporal attributes, we considered other three PRISMA images obtained in 2020 (11 May, 4 September, and 3 October). Using these images, we calculated the rate of changes for each of the 22 VIs in the browning and greening periods of the savannah environment. A feature selection procedure was applied to the datasets. The results showed that the vegetation gradient from savannah grassland to woodland areas controlled the behavior of most attributes. For instance, the reflectance of the PRISMA NIR bands and the depth of the chlorophyll (680 nm) and leaf water (980 nm and 1200 nm) absorption bands increased with increasing vegetation cover. On the other hand, the reflectance of the visible and shortwave infrared (SWIR) bands and the depth of spectral features associated with non-photosynthetic vegetation followed the opposite pattern. Except for the metrics of image texture, the other spectral (reflectance, VIs, endmember fractions, and absorption band parameters) and temporal (browning and greening rates of vegetation changes) attributes had close classification performance before or after feature selection. When combined into a single dataset, gains of 15% in overall classification accuracy were observed when compared to the individual use of reflectance data in the analysis. From the seven savannah classes tested for classification, areas of woodland savannah, savannah grassland, and riparian forest were adequately mapped using this approach (F1-scores between 0.72 and 0.91). In contrast, areas of wooded savannah, with and without Trembleias species, had low F1-scores (0.28 and 0.20, respectively). Our findings reinforce the need of considering different hyperspectral attributes in classification approaches of the savannahs in Brazil.

The potential of hay for graminoid introduction in the restoration of subtropical grasslands: Results from a greenhouse experiment

IntroductionSubtropical grasslands have been severely impacted. Due to their low resilience after degradation, active restoration is necessary; however, knowledge still is incipient. Hay transfer is a successfully employed technique to restore other grassland ecosystems and its use is promising in subtropical grasslands. We evaluated the potential of hay transfer for the restoration of the subtropical grasslands in Southern Brazil by assessing the effects of (1) the date of hay harvest and (2) the amount of dry hay used. MethodsIn two protected areas in South Brazilian grasslands, we harvested hay on three dates (mid-Spring, early-Summer, and mid-Summer) and placed it into a greenhouse for seeds in the hay to germinate. Two different amounts of dry hay (375 g/m² and 750 g/m²) were used for each date. We assessed the number of emerging seedlings, species richness, and seedling species composition in each treatment, separately for each site. Emerging forbs were identified as soil seed bank contamination, and only data for graminoids (grasses and sedges) are presented. ResultsThe number of seedlings varied among harvest dates, with mid-Spring and early-Summer resulting in more emergencies in both sites. No common pattern to both sites regarding the effect of the amount of dry hay on seedling emergence was found for the two sites, but interaction with the harvest date is important. Species composition and richness also varied across harvest dates, and, independent of the donor site, more hay resulted in more species. Nevertheless, few species were transferred overall. ConclusionsHay transfer has the potential to introduce seeds of graminoids and appears to be a promising tool for the restoration of South Brazilian grasslands. There is not a single optimal time for hay harvest nor a pattern regarding hay amount. Few species are established from hay and more than one harvest should be done to increase species richness.

Assessing Water Resource Carrying Capacity and Sustainability in the Cele–Yutian Oasis (China): A TOPSIS–Markov Model Analysis

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt.

Multi-scale habitat selection throughout the annual cycle of a long-distance avian migrant

Long-distance migrants are constrained by widely separated hospitable habitats in geographically isolated locations, making them vulnerable to environmental change, both through natural and anthropogenic causes. Knowledge about their resource selection decisions is imperative to understand the drivers of their declines. The distinct periods within an annual cycle, when individuals experience different environmental circumstances, are inextricably linked through carry-over effects which can have important consequences for the individual, and consequently the population. In this study, we employ precise archival GPS-tracking data of European Nightjars (Caprimulgus europaeus) and high-resolution global land cover data to examine habitat selection during the sedentary wintering and breeding periods, as well as during autumn and spring migration, using a correlational approach. We demonstrate how nightjars use general habitat characteristics, such as landscape diversity, for high-order habitat selection, while resource selection at a finer spatial scale is reliant on fine-scale variables related to a habitat’s suitability, such as surface area of grassland and shrubland. We show that nightjars favour spatially diverse landscapes, which allows them to minimize time spent searching for optimal habitats. The considerable variation in the drivers of habitat selection between and within seasons shows how anthropogenic land-use change can have an array of different impacts on migrants by influencing large- and fine-scale habitat selection. This study shows the advantages of an individual based GPS-tracking approach, combined with high spatial resolution remote sensing data, and highlights the need for full annual-cycle research on scale dependent habitat selection of long-distance avian migrants.

Estimation of Bale Grazing and Sacrificed Pasture Biomass through the Integration of Sentinel Satellite Images and Machine Learning Techniques

Quantifying the forage biomass in pastoral systems can be used for enhancing farmers’ decision-making in precision management and optimizing livestock feeding systems. In this study, we assessed the feasibility of integrating Sentinel-1 and Sentinel-2 satellite imagery with machine learning techniques to estimate the aboveground biomass and forage quality of bale grazing and sacrificed grassland areas in Virginia. The workflow comprised two steps, each addressing specific objectives. Firstly, we analyzed the temporal variation in spectral and synthetic aperture radar (SAR) variables derived from Sentinel-1 and Sentinel-2 time series images. Subsequently, we evaluated the contribution of these variables with the estimation of grassland biomass using three machine learning algorithms, as follows: support vector regression (SVR), random forest (RF), and artificial neural network (ANN). The quantitative assessment of the models demonstrates that the ANN algorithm outperforms the other approaches when estimating pasture biomass. The developed ANN model achieved an R2 of 0.83 and RMSE of 6.68 kg/100 sq. meter. The evaluation of feature importance revealed that VV and VH polarizations play a significant role in the model, indicating the SAR sensor’s ability to perceive changes in plant structure during the growth period. Additionally, the blue, green, and NIR bands were identified as the most influential spectral variables in the model, underscoring the alterations in the spectrum of the pasture over time.

Palynology of sedimentary soils in the Pampa biome: Grassland-forest mosaics and landscape-soil-pollen relationships

Pampa biome vegetation is characterized by extensive areas of native grassland, interspersed with forests close to water courses. An understanding is been searched on how grassland and forest dynamics to contribute for the conservation and management practices suitable for the biome. The objective of this study was to asses if landscape-soil-pollen relationships are determinant of grassland-forest mosaics, by analyzing summit, footslope and toeslope positions in the landscape, in the Campanha region of the Pampa biome. We collected 32 samples in three soil profiles in topossequence under natural grassland of the Pampa biome, in southern Brazil. These samples were treated following standard methodology used in palynology studies. The pollen percentage diagrams were generated to represent the identified pollen set, while cluster analysis was used to define the paleoecological zones. The results found were supported by radiocarbon dating (age of subsurface soil varying from 3,460 to 4,090 calibrated years before present), and particle-size analysis. The paleoecological zones, for each soil profile, indicate a predominance of grassland vegetation, especially Poaceae pollen, whereas Fabaceae and Piper were predominant in forest sites. The pollen set obtained in the three soil profiles indicates hegemony of the sites, even under climatic conditions of increased moisture. Rare pollen grains from forest taxa suggests that trees and shrubs existed in isolated form. The presence of bryophyte spores and taxa associated with soil wetness indicates that the region was once dominated by extensive wetlands and moist landscapes. Our findings enhance the comprehension of the Pampa flora, and are applicable in restoration of degraded areas. The preservation of pollen grains in soil profiles shows the potential of minerals soils to reconstitute Pampa biome vegetation, representing a site for palynological research advance, and demonstrate grassland formations maintain their supremacy even under unfavorable climatic conditions. Thus, this study expands the frontier of palynological work, encompassing new sites and new opportunities to evaluate land use/land cover changes.

What can we learn from the past? Tracking sustainability indicators for the Swedish dairy sector over 30 years

CONTEXTThe dairy sector has undergone profound transformation over recent decades, resulting in considerably fewer but larger and more specialised farms, with unclear implications across sustainability dimensions. OBJECTIVEThe objective was to develop and employ a framework for assessing sustainability in the Swedish dairy sector to shed light on how recent historical developments (1990–2020) have influenced sustainability outcomes. METHODSUsing a data-driven, multidisciplinary approach, main areas of concern for sustainability in the primary production stages of the dairy sector were identified. These were then populated with indicators to track developments over time and highlight synergies and trade-offs. RESULTS AND CONCLUSIONSFour areas of concern were identified and populated with eight indicators (listed in brackets): ‘supporting ecosystems’ (semi-natural grassland area, ley area, mean field size), ‘climate impact’ (methane from enteric fermentation), ‘animal welfare’ (veterinary treatments, percentage of culled cows due to diseases) and ‘farm viability’ (competitive wages, farmer age structure). The results showed that area of semi-natural grassland per dairy cow decreased by 27% from 2003 to 2020. Area of ley per cow decreased slightly but the proportion of arable land on dairy farms devoted to ley cultivation increased, due to improved roughage quality enabling an increase in proportion of roughage in feed rations. In terms of climate impact, enteric methane emissions per kg milk decreased by 21%. Regarding animal welfare, veterinary treatments of diseases decreased from 45% to 21% over the 30 years, with declining trends for most recorded diseases except hoof disease. The indicators for farm viability showed that the average dairy farm was unable to pay a wage comparable to the national average throughout most of the period 2004–2020, but a slightly positive trend was observed, although with large year-on-year variability. A rapid change in age structure was seen between 2003 and 2020, with the proportion of land managed by older farmers (+60 years) increasing from 12% to 22%, indicating challenges with demographic viability. SIGNIFICANCETracking changes over time across sustainability dimensions gives important insights into improvements made and challenges that remain to be solved. Overall, developments in the Swedish dairy sector have diminished its capacity to support ecosystems, particularly related to semi-natural grasslands, while reducing its climate impacts and improving animal welfare. An increased specialisation has also resulted in spillover effects where services and impacts have shifted from dairy herds to specialised beef herds. These findings are important in navigating policy processes targeting developments in the dairy sector.

Climate Change Impacts on Grassland Vigour in Northern Portugal

Grasslands are key elements of the global agricultural system, covering around two-thirds of all agricultural areas and playing an important role in biodiversity conservation, food security, and balancing the carbon cycle. Climate change is a growing challenge for the agricultural sector and may threaten grasslands. To address these challenges, it is vital to conduct in-depth climate studies to understand the vulnerability of grasslands. In this study, machine learning was used to build an advanced model able to evaluate the future impact of climate change on grassland vigour. The objective was to identify the most vulnerable grassland areas, analyse the interaction between climate and grassland performance, and outline management strategies against the detrimental implications of climate change. A Random Forest (RF) regression was used to model the Normalised Difference Vegetation Index (NDVI) using the Standardised Precipitation-Evapotranspiration Index (SPEI). The model explained 76% of the NDVI variability. The foremost significant predictors of grassland vigour are the SPEI with temporal lags of 1, 4, and 12 months. These findings suggest that the vegetative status of grasslands exhibits high sensitivity to short-term drought while also being influenced by the memory of past climatic events over longer periods. Future projections indicate an overall reduction in grassland vigour, mostly in RCP8.5. The results indicate that negative effects will be more pronounced in mountainous regions, which currently host the most vigorous grasslands. Dry lowlands in the north should continue to have the lowest vigour in the future. A substantial reduction in vigour is expected in autumn, with an effect on grassland phenology. The development of grasslands in winter, favoured by increasing temperatures and precipitation, can advance the harvesting of grassland (cutting) and the grazing of livestock. To ensure that vigour is maintained in less favourable zones, adaptation measures will be needed, as well as more efficient management of highlands to provide an adequate level of production.

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau

Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Post-Fire Soil Nutrient Dynamics in Seriphium plumosum L. Encroached Semi-Arid Grassland of Gauteng Province, South Africa

Seriphium plumosum L. is an indigenous unpalatable shrub that occurs in fire-prone semi-arid South African grassland areas, yet research proposes the use of fire to control its encroachment of rangelands. This study investigated the interaction effects of burning and soil depth on components of soil fertility. Soil samples were collected from the surface (<10 cm) and subsurface (>10 ≤ 20 cm) soil, before and after burning in randomly selected paired subplots (25 m × 25 m), with six replicates. Data was analysed as a randomised complete block design, with repeated measures (before and after burning) in a 2 × 2 factorial analysis of variance (ANOVA) using generalised linear model (GLM) procedures. Components of soil fertility measured (K, Ca, Mg, Org C, P, pH and TN) showed a significant decrease with increasing soil depth both before and after burning, except for K and P, which were significantly higher in surface soils after burning. The results showed that the response of soil nutrients to fire depends on the temperature tolerance threshold of individual soil nutrient elements. Increasing surface soil available K and P concentrations after burning may improve the conditions for S. plumosum encroachment, with implications for similar environments and species worldwide.

Morphological changes in hooded crows (Corvus cornix) related to urbanization

IntroductionUrbanization has led to a recent surge of interest in urban biodiversity, and wildlife responses to urban environments have become a hot topic in environmental sciences and biodiversity conservation. However, adaptations to urbanization and the factors driving them are less understood.MethodologyWe studied possible morphological adaptations to urban environments by comparing body size and condition of adult and post-fledging juvenile Hooded Crows (Corvus cornix), a bird species that has recently colonised cities in eastern Europe, between two urban and two rural populations, between two different-sized cities and between locations within one city in Hungary.ResultsAdult crows from the rural cropland-woodland area were lighter and in poorer condition than crows from the rural grassland area or those from the medium-sized city. There were no differences in morphological traits of adults or juveniles between the large and the medium-sized cities. The comparison of multiple trapping locations within the city of Debrecen showed that juveniles in the Zoo area were larger, heavier, and in better condition than individuals in the other locations and that adults in the Zoo had longer wings and tarsi than adults in other locations. Our results indicated that urbanized Hooded Crows showed some morphological changes to live in urban environments, but we did not find large-scale, consistent differences between urban and rural areas. However, we found significant variation within one city.DiscussionOur results suggest that urban-rural environmental differences may be mediated by local factors, of which the year-round availability of anthropogenic food is fundamental. Such food is widely available in cities, although its quality may be suboptimal for bird development. Our study suggests that the variation in body size variables is probably more site-dependent than gradient-dependent and shows that documenting wildlife adaptations to urban environments requires multiple spatial scales ranging from regional to local (within-city) scales.

Mapping grasslands' preservation potential: A case study from the northern Carpathians

AbstractThe grasslands which are an important part of an ecosystem are endangered due to abandonment of traditional forms of land use. Preservation of biodiversity of semi‐natural grassland communities is of great importance, therefore it is important to identify threats and prepare a sustainable plan for their protection The goal of this study was to develop an approach to predict threatened grasslands hotspots, basing on multi‐factor machine learning analyses. The Gorce Mountains in the Polish Carpathians were chosen as a study area, as it is region partially protected by National Park, surrounded by villages with different socio‐economic conditions (agriculture or touristic oriented). The grasslands were identified and classified on Sentinel‐2 multispectral imagery. As lack of regular mowing of grasslands was found as main factor promoting forest succession. Therefore, in order to find endangered grasslands areas, support vector machines' algorithm was used to classify them in mowed and unmowed categories. Then the preservation potential of grasslands was modeled with the random forest method, based on the grasslands' mowing classification, digital terrain model, land‐use and population statistical data, and the historical forest extent. We found the grasslands above 750 m above sea level to be the most endangered. Also, the tourism activity and ongoing changes in employment structure from agriculture to services has had a negative influence on the grasslands preservation potential. On the other hand, the Gorce National Park's active grassland conservation by mowing and grazing was shown as a positive element in keeping with the high biodiversity of the area.

Analysis of Land Use/Cover Changes and Driving Forces in a Typical Subtropical Region of South Africa

Land use/cover change (LULCC) is an integral part of global environmental change and is influenced by both natural and socioeconomic factors. This study aims to comprehensively analyze land use and land cover (LULC) in Kwazulu-Natal and Mpumalanga provinces in eastern South Africa from 1995 to 2020 and to identify the driving force behind LULCC. Utilizing Landsat series satellite imagery as a data source and based on the Google Earth Engine (GEE) platform and eCognition software 9.0, two different classification methods, pixel-based classification and object-oriented classification, were adopted to gather LULC data every five years. The spatiotemporal characteristics of the data were then analyzed. Using an optimal parameter-based geodetector (OPGD), this study explored the driving factors of LULCC in this region. The results show the following: (1) Of the two classification methods examined, the object-oriented classification had higher accuracy, with an overall accuracy of 80–90%. The pixel-based classification had lower accuracy, with an overall accuracy of 62.33–72.14%. (2) From 1995 to 2020, the area of farmland in the study area showed a fluctuating increase, while the areas of forest and grassland declined annually. The area of constructed land increased annually, whereas the areas of water and unused land fluctuated over time. (3) Socioeconomic factors generally had greater explanatory power than natural factors, with population growth and economic development being the main drivers of LULCC in the region. This study provides a reliable scientific basis for the formulation of sustainable land resource development strategies in the area, as well as for the management and implementation of urban and rural planning, ecological protection, and environmental governance by relevant departments.

Regional water cycle sensitivity to afforestation: synthetic numerical experiments for tropical Africa

Afforestation as a climate change mitigation option has been the subject of intense debate and study over the last few decades, particularly in the tropics where agricultural activity is expanding. However, the impact of such landcover changes on the surface energy budget, temperature, and precipitation remains unclear as feedbacks between various components are difficult to resolve and interpret. Contributing to this scientific debate, regional climate models of varying complexity can be used to test how regional climate reacts to afforestation. In this study, the focus is on the gauged Nzoia basin (12,700 km2) located in a heavily farmed region of tropical Africa. A reanalysis product is dynamically downscaled with a coupled atmospheric-hydrological model (WRF-Hydro) to finely resolve the land-atmosphere system in the Nzoia region. To overcome the problem of Nzoia river flooding over its banks we enhance WRF-Hydro with an overbank flow routing option, which improves the representation of daily discharge based on the Nash-Sutcliffe efficiency and Kling-Gupta efficiency (from −2.69 to 0.30, and −0.36 to 0.63, respectively). Changing grassland and cropland areas to savannas, woody savannas, and evergreen broadleaf forest in three synthetic numerical experiments allows the assessment of potential regional climate impacts of three afforestation strategies. In all three cases, the afforestation-induced decrease in soil evaporation is larger than the afforestation-induced increase in plant transpiration, thus increasing sensible heat flux and triggering a localized negative feedback process leading to more precipitation and more runoff. This effect is more pronounced with the woody savannas experiment, with 7% less evapotranspiration, but 13% more precipitation, 8% more surface runoff, and 12% more underground runoff predicted in the Nzoia basin. This study demonstrates a potentially large impact of afforestation on regional water resources, which should be investigated in more detail for policy making purposes.

Grazing and right-of-way affect native rangeland 12 years after pipeline construction in southern Alberta

ABSTRACT Over the past 100 years, large areas of native grasslands have been lost due to human activities and natural disturbances. Construction of pipelines for oil and gas transportation continues to pose significant challenges to grassland ecosystems. Thus, reclamation of disturbed native grasslands is critical for their existence in North America and around the world. This study investigated long-term (12 years) effects of grazing and right-of-way (RoW) treatments on revegetation of native rangeland on two pipelines in southeastern Alberta, Canada. Grazing and RoW treatments influenced soil and vegetation parameters; and plant species group responded differently at Milo and Porcupine Hills. Grazing was associated with significantly greater bare ground and decreased litter at both sites and increased vegetation cover at Porcupine Hills. At Milo grass density and biovolume increased as RoW disturbance increased, but not at Porcupine Hills. Trenching increased rhizomatous grasses and all RoW disturbances reduced tufted grasses. Vegetation was dissimilar on the RoW from undisturbed prairie with intermediate levels of disturbance (work, storage) having greater plant species diversity, whereas grazing had no effect. This study suggests 12 years may not be long enough for restoration of native rangelands after pipeline construction although there was some progress.

Spatial-temporal variations of vegetation coverage and its driving force in Inner Mongolia grassland, China

Inner Mongolia grassland is rich in natural vegetation and mineral resources. Based on Landsat5/7/8 NDVI data, we used pixel binary model to invert vegetation coverage of Inner Mongolia grassland area, investigated the stability, spatial distribution, and future evolution trend of vegetation coverage by using Sen+MK and Hurst index, and analyzed the driving factors of the spatial differentiation of vegetation coverage by the optimal parameters-based geographical detector. The results showed that vegetation coverage of Inner Mongolia grassland showed an increasing trend from 2006 to 2020, and the overall spatial pattern was high in the east and low in the west, mainly with great fluctuation. The regions with slight or obvious improvement characteristics (64.8%) were much more than those with slight or severe degradation characteristics (23.2%). Compared with that in the past 15 years, the proportion of degraded vegetation in the future is expected to increase to 36.6%. The central part of Xilin Gol League and Wulanqab in the central grassland area, the western part of Hulunbuir and Erdos in the eastern grassland area, and Wuhai in the western grassland area were at the risk of degradation, which should be paid more attention. Precipitation was the dominant factor of spatial differentiation in Inner Mongolia grassland, while soil type, land use, and air temperature had the most significant synergistic effect.