Explore the vast range of titles available.

1. Habitat loss is one of the greatest threats to biodiversity, exerting negative effects on the ecological viability of natural vegetation remnants. The south Brazilian grasslands belong to one of the largest temperate grassland regions in the world, but have lost 50% of their natural extent in the past 35 years. To date, there is no empirical evidence for the effects of habitat loss on these grasslands' biological diversity, undermining their conservation. 2. Using data from a large-scale biodiversity survey, we asked if local plant communities respond to levels of habitat loss representative of the entire region (≤50%). Vegetation in grassland remnants was sampled in 24 landscapes at three localities each, using nine plots per locality. To investigate whether species losses were a consequence of stochastic or nonrandom local extinctions and whether plant communities became more homogenized, we evaluated species richness, beta-diversity components (spatial turnover and nestedness), and phylogenetic diversity, in respect to landscape change. In part of the landscapes, arthropods were sampled to investigate if loss of plant diversity had a cascading effect on other trophic levels. We evaluated generic richness of ants, an omnivore group with high levels of plant associations, in respect to a plant community's phylogenetic diversity. 3. Local plant communities in landscapes with less grassland cover had fewer species, less spatial turnover, increased nestedness and lower phylogenetic diversity. Our results suggest that the observed species loss can be linked to taxonomic homogenization and is nonrandom, decreasing evolutionary diversity within the community. Furthermore, ant richness declined by 50% in plant communities with the lowest phylogenetic diversity, suggesting that effects of habitat loss propagate to higher trophic levels. 4. Policy implications. We conclude that the biological diversity of south Brazilian grasslands, at the producer and consumer level, is at risk under the current rate of land-use conversion, even at habitat losses below 50%. To avoid substantial biodiversity loss, conservation and more restrictive policies for conversion of native grasslands to different land uses in South Brazil are urgently needed.

Agriculture in the boreal and Arctic regions is perceived as marginal, low intensity and inadequate to satisfy the needs of local communities, but another perspective is that northern agriculture has untapped potential to increase the local supply of food and even contribute to the global food system. Policies across northern jurisdictions target the expansion and intensification of agriculture, contextualized for the diverse social settings and market foci in the north. However, the rapid pace of climate change means that traditional methods of adapting cropping systems and developing infrastructure and regulations for this region cannot keep up with climate change impacts. Moreover, the anticipated conversion of northern cold-climate natural lands to agriculture risks a loss of up to 76% of the carbon stored in vegetation and soils, leading to further environmental impacts. The sustainable development of northern agriculture requires local solutions supported by locally relevant policies. There is an obvious need for the rapid development of a transdisciplinary, cross-jurisdictional, long-term knowledge development, and dissemination program to best serve food needs and an agricultural economy in the boreal and Arctic regions while minimizing the risks to global climate, northern ecosystems and communities.

Aim: Agricultural intensification and urbanization are important drivers of biodiversity change in Europe. Different aspects of bee community diversity vary in their sensitivity to these pressures, as well as independently influencing ecosystem service provision (pollination). To obtain a more comprehensive understanding of human impacts on bee diversity across Europe, we assess multiple, complementary indices of diversity. Location: One Thousand four hundred and forty six sites across Europe. Methods: We collated data on bee occurrence and abundance from the published literature and supplemented them with the PREDICTS database. Using Rao's Quadratic Entropy, we assessed how species, functional and phylogenetic diversity of 1,446 bee communities respond to land-use characteristics including land-use class, cropland intensity, human population density and distance to roads. We combined these models with statistically downscaled estimates of land use in 2005 to estimate and map—at a scale of approximately 1 km²—the losses in diversity relative to semi-natural/natural baseline (the predicted diversity of an uninhabited grid square, consisting only of seminatural/natural vegetation). Results: We show that—relative to the predicted local diversity in uninhabited seminatural/natural habitat—half of all EU27 countries have lost over 10% of their average local species diversity and two-thirds of countries have lost over 5% of their average local functional and phylogenetic diversity. All diversity measures were generally lower in pasture and higher-intensity cropland than in semi-natural/natural vegetation, but facets of diversity showed less consistent responses to human population density. These differences have led to marked spatial mismatches in losses: losses in phylogenetic diversity were in some areas almost 20 percentage points (pp.) more severe than losses in species diversity, but in other areas losses were almost 40 pp. less severe. Main conclusions: These results highlight the importance of exploring multiple measures of diversity when prioritizing and evaluating conservation actions, as species-diverse assemblages may be phylogenetically and functionally impoverished, potentially threatening pollination service provision.

Land surface temperature (LST) is increasing due to land use land cover (LULC) conversion in the world. Global warming was caused by highly expansion of agricultural land, expansion of human settlements and removal of vegetation cover. Here, we analyzed the impacts of LULC dynamics on LST from the year 1991 to 2020 in the Anger River Sub-basin, western Ethiopia. The LST and LULC changes were derived from thermal infrared and multispectral band of Landsat 5 TM (1991), Landsat 7 ETM+ (2003) and Landsat 8 OLI/TIRS (2020), respectively. The LULC map of the study area was produced using the supervised classification method with the maximum likelihood algorithm. Our study results revealed that agricultural land was increased by the rate of 30.4 km2/year. Between 1991 and 2020, about 650.3 km2 of grassland was converted to agricultural land while 305.4 km2 was converted from forest to agricultural land. The mean minimum LST was 21.2 °C in 1991 and increased to 23.50 °C and 26.80 °C in the years 2003 and 2020, respectively. Thus, the mean LST of the study area was increased by 5.6 °C between 1991 and 2020. Consequently, the conversion of LULC is the main factor for the increment of the LST. The LST was highly increased when forestland and grassland were converted to agricultural land. Similarly, when forestland was converted to bare land, the LST was increased. Our results suggest the need for environmental protection to respond to the increasing trend of LST and rapid conversion of LULC change in the study area.

Land cover is being continuously transformed at an accelerating pace because of urbanization and economic development, which is, in turn, impacting ecosystem services and human well-being. Consequently, there is a need to enhance sustainable land use management to achieve high levels of land eco-efficiency across different regions in China. Accomplishing this entails adjustments not only in terms of the spatial layout of land but also in land use management. The relationship between land use management and land eco-efficiency was explored taking Hebei, a province of China, as a case study. With the help of Stochastic Frontier Analysis (SFA) and other statistical analysis, we analyzed land use conversions and land eco-efficiency in Hebei, China. In this study, we first explored the relationship between land use conversion, ratio of cultivated land, and crop production using scatter plots. Further, we analyzed the land eco-efficiency and ecological performance of cities in Hebei based on SFA. The findings of the study revealed that land use output is the key factor linking land use management and land eco-efficiency. Spatial differences of land eco-efficiency are clearly apparent in Hebei, and the results of the study showed a corresponding decrease in land eco-efficiency with a reduction in the distance to the city center. In conclusion, a step-by-step regulatory process for improving land eco-efficiency within China’s land use management scheme is proposed.

The center of gravity of China’s new cropland has shifted from Northeast China to the Xinjiang oasis areas where the ecological environment is relatively fragile. However, we currently face a lack of a comprehensive review of the cropland expansion in oasis areas of Xinjiang, which is importantly associated with the sustainable use of cropland, social stability and oasis ecological security. In this study, the land use remote sensing monitoring data in 1990, 2000, 2010 and 2018 were used to comprehensively analyze the process characteristics, different modes and driving mechanisms of the cropland expansion in Xinjiang, as well as its spatial heterogeneity at the oasis area level. The results revealed that cropland in Xinjiang continued to expand from 5803 thousand hectares in 1990 to 8939 thousand hectares in 2018 and experienced three stages of expansion: steady expansion, rapid expansion, and slow expansion. The center of gravity of cropland showed the characteristic of shifting to the South. Edge expansion and encroachment on grassland were the dominant spatial pattern mode and land use conversion mode of Xinjiang’s cropland expansion, respectively. The expansion of cropland in Xinjiang was affected by multiple factors. Irrigation conditions played a dominant role. Topography indirectly affected cropland expansion by affecting the suitability of agricultural production and development. Population growth and farmers’ income were important driving forces. There was significant spatial heterogeneity in the intensity, mode and driving force of cropland expansion among different oasis areas in Xinjiang. The spatial shift of China’s new cropland has occupied a large amount of water resources and ecological land in Xinjiang and exacerbated the vulnerability of the ecosystem in arid regions. The key to sustainable management of cropland in Xinjiang in the future lies in maintaining an appropriate scale of cropland and promoting the coordinated development of cropland, population, water resources and industry.

Population dynamics in terms of population growth is experiencing an unremitting increase in the developing countries leading to significant pressure on obtainable land resources in urban locations as well as adjoining rural hinterland. The growth of urban population is one of the most important driving forces of change in urban environment, which ultimately are manifested by the development of suburban growth. Under such backdrop, other land uses like agricultural land and forests at urban fringes are lost their identity as well as converted to the built-up area which reduces different ecosystem services. In order to get better the process knowledge of land use planning, information on present land use patterns and its changes over the certain course of time is indispensable for effective plan formulation in any region. Present inquiry concerns with land use dynamics in close proximity to the Durgapur urban industrial region in Kanksa Community development Block of Paschim Bardhaman District which is a part of a lateritic forested tract as well as experienced with phenomenal population growth in the last 2 decades with a doubling of urban population in 1 decade mainly in the Census towns around the Durgapur industrial complex. The overall objective of this study is to understand the land use land cover change in Kanksa Block and its spatiotemporal aspects with special emphasis on urban growth. Increase in urban area is massive in first 10 years in comparison to rest of the 10 years in cost of other land uses. This will help to recognize the conversion of land use that has mostly been affected by this massive urban growth, physical and temporal pattern of urban growth and finally to establish the interrelationship between this landuse land cover change and population dynamics. The use of Geographical Information system would also identify the most critical zone for future landuse planning for better sustainability.

Land use changes are of critical importance in understanding and managing environmental sustainability and resource utilization. Machine learning algorithms (MLAs) have emerged as powerful tools for analyzing and predicting land use changes, offering the potential to uncover patterns and trends that may not be readily apparent through traditional methods. This study is aimed at evaluating the efficiency of various MLAs (such as SVM, KNN, CART, Naïve Bayes, and Random Forest) in analyzing LULC changes in Northeast Iran. The analysis utilized the Google Earth Engine (GEE) to process satellite imagery spanning the years 1994 to 2021, covering a period of 27 years. Landsat 5 and TM sensor data from 1994 and 2001, as well as Landsat 8 and OLI sensor data from 2014 and 2021, were employed in this research. Additionally, post-processing tasks on the classified images were carried out using ArcGIS 10.8 software. Based on the validation results, it is evident that the Random Forest machine learning algorithm outperformed other algorithms. In contrast, for the years 2014 and 2021, the support vector machine algorithm had the highest accuracy of 85%, making it the most optimal choice during those years. The results indicated a decrease in rangeland, with a significant difference (34.04%) observed in 1994–2021. This decline could be attributed to factors such as rangeland degradation and a shift in LULC towards agriculture and orchards. Conversely, agricultural land had significant increases of 275.83%, 223.77%, and 61.97% in 2021 compared to 1994, 2001, and 2014, respectively. However, the area of forest lands decreased notably over the studied periods, with reductions of 81.66%, 64.21%, and 30.56% in 2021 compared to 1994, 2001, and 2014, respectively. The study results reveal distinction shifts in LULC patterns, indicating declines in rangelands and significant expansions in agricultural areas, which need to be considered in land use planning and environmental conservation programs.

Irrigation has been applied on a large scale for the improvement of grain yield per hectare and production stability. However, the dryland-to-paddy conversion affects the ecological environment of areas of long-term dry farming, especially soil microorganisms. Little attention has been paid to the changes in microbial communities and the interactions between their populations in this process. Therefore, in this paper, the compositions and diversity of soil bacterial and fungal communities were explored through a combination of high-throughput sequencing technology and molecular ecological network methods using bacterial 16S rRNA and fungal ITS. The results showed that: (1) both the abundance and diversity of soil bacteria and fungi decreased in a short time, and the abundance of Actinobacteria, Firmicutes and Olpidiomycota varied greatly. (2) Compared to dry land, the modular structure of interaction networks and interspecific relationships of bacterial and fungal communities in paddy soil were simpler, and the network became more unstable. A cooperative relationship dominated in the molecular ecological network of bacteria, while a competitive relationship was dominant in the network of fungi. Actinobacteria and Firmicutes were the dominant bacterial species in dry land and paddy field, respectively. Ascomycota was dominant in the fungal communities of both dry land and paddy field. (3) The change in soil environmental factors, such as pH, electrical conductivity (EC), organic matter (OM) and available potassium (AK), directly affected the soil microbial community structure, showing a significant correlation (p < 0.05). These environmental factors also influenced the dominant microbial species. Microorganisms are the most important link in the carbon and nitrogen cycles of soil, and a large-scale dryland-to-paddy conversion may reduce the ecological stability of regional soil.

The construction of terraces and vegetation restoration in the hillslope are major soil and water conservation measures on the Chinese Loess Plateau and contributed to the distribution patterns of soil organic carbon (SOC) and soil total nitrogen (STN). Topography influences soil erosion and changes SOC and STN contents. However, little information is available regarding the effects of ecological construction and topography on SOC and STN. A study was undertaken in the Loess Plateau, to evaluate the effects of land use conversion and topographic factors on the topsoil SOC and STN content at three hillslope positions (upper, middle, and foot slopes) under four land uses types: artificial forest, grassland, terraced fields, and sloping cropland. The results showed that land use conversion from sloping cropland to artificial forest and grassland improved the SOC and STN content. Slope position was an important topographic factor governing the SOC and STN distribution at the slope scale in artificial forest, grassland, and sloping cropland, with the foot slope having the highest SOC and STN content, followed by the upper slope, while the middle slope had the lowest values. SOC and STN showed positive correlation with Caesium-137 (137Cs) content. Land use types, slope position, and soil erosion had significant relationships with SON and STN. The results suggested that vegetation restoration of sloping cropland will contribute to soil carbon (C) and nitrogen (N) sequestration in the loess hilly region. The quantitative estimation of land use change and topography effects on SOC and STN could improve the accuracy of SOC and STN predictions in the region with a complex topography.