Farmland Area Research Articles

Spatial-temporal distribution and source apportionment of riverine dissolved organic carbon in the Miyun section of the Chaobai River in Beijing, China

Dissolved organic carbon (DOC) is indicative of water quality in drinking source water and has an impact on drinking water treatment. Exploring occurrence of DOC in drinking source water is of great significance for the drinking water safety in Beijing. This study elucidated spatial-temporal DOC dynamics in the Miyun section of Chaobai River in Beijing of China and identified sources of DOC based on DOC fluorescent spectral characteristics. Results showed that the average riverine DOC concentration was 30.60 mg/L. DOC concentrations in the Miyun section of the Chaobai River were 30.40, 30.24, and 31.09 mg/L in spring, summer and autumn, respectively. DOC concentrations at the three segments of the Miyun section of the Chaobai River (the Chaohe River, the Baihe River and the Chaobai River) were 29.93, 30.29 and 32.57 mg/L, respectively. Land use contributed to DOC variations rather than season and river segment. Significant increases in DOC concentration were observed in river water flowing through farmland and urban areas, and DOC concentration presented the highest after flowing through the farmland area. The results of FI, HIX and BIX showed that DOC mainly came from endogenous sources such as aquatic biological activities, and was less affected by terrestrial inputs. Special attentions ought to be paid on prevention and control of endogenous DOC inputs.

Revealing soil erosion and sediment sources using 137Cs and fingerprinting in an agroforestry catchment

Soil erosion and accompanying sediment issues have a significant impact on environmental sustainability. However, there is not currently a clear understanding of the relationship between soil erosion and sediment sources at the catchment scale, which has led some researchers to regard areas with severe soil erosion as the main sediment source. This view does not apply in all circumstances.•This paper uses 137Cs to study the average annual erosion rate of different land use types. The results show that the erosion rates of woodland, sparse woodland and farmland areas were 400, 1756, and 2771 t·km−2·a−1, respectively, multiplied by the corresponding area. Surface soil erosion levels in the catchments of the three types accounted for 11%, 26% and 25%, respectively, and the total accounted for 62% when the gully bank accounted for 38%.•Fingerprinting technique results show that the relative source contributions of woodland, farmland, sparse woodland and gully bank areas to sediment at the small catchment outlet were 4%, 10%, 48% and 38%, respectively. The results reveal that the detachment process of soil and the transport process of sediment with runoff were internally related and independent of each other.•By comparing on-site erosion rates with downstream source contributions, we have a clearer understanding of soil erosion and subsequent sediment transport process in the agroforestry catchment in mountainous areas.We emphasize the importance of governance and management in areas with severe soil erosion, mainly targeting types such as hillslope framland. In addition, sparse woodland and gully banks should be given more attention, as they account for a large proportion of sediment in the downstream catchment.

The Impact of Land Use/Cover Change on Ecological Environment Quality and Its Spatial Spillover Effect under the Coupling Effect of Urban Expansion and Open-Pit Mining Activities

Suburban open-pit mining concentration areas are both the frontline of urban expansion and the main battlefield in mineral resource development. These dual forces have resulted in significant land use/cover changes (LUCC), which play a crucial role in determining the ecological environment quality (EEQ). However, research examining how LUCC affects EEQ under the coupled impact of these two development events is currently lacking. In this study, the response of EEQ to LUCC was evaluated using Landsat images from 2000, 2010, and 2020 for the southern suburban open-pit mining concentration area in Jinan City. A relative contribution index was used to address the ecological and environmental effects of non-dominant land use/cover types, and the impact of LUCC on EEQ and its spatial spillover effects were revealed by also carrying out a buffer zone analysis. The findings of this study indicate that: (1) the dominant land use/cover types that influence the EEQ spatial pattern are farmland, grassland, and construction land. Among them, the area of farmland was the largest, with more than 1800 km2. Changes in non-dominant land use/cover types to mining land and mine rehabilitation made the most significant relative contribution to the changes in EEQ, i.e., 0.0735 and 0.0184, respectively. (2) The transformation of farmland into construction land and mining land and woodland into mining land was shown to exacerbate the deterioration of the EEQ in the study area, with a deterioration area of 1367.54 km2 and spatial spillovers of up to 1000 m. (3) Returning farmland to woodland and grassland, as well as returning mine rehabilitation, were found to be the main factors contributing to the improvement of EEQ in the study area, with an improvement area of 1335.67 km2 and spatial spillover extending from 500 to 800 m. (4) Nevertheless, uneven changes in land use/cover continue to aggravate the agglomerative effect of EEQ deterioration. Further refinement and enhancement of the methods and standards of ecological governance are urgently needed to counterbalance the uneven spatial spillover effects between ecological degradation and improvement. This study provides a scientific reference for the promotion of ecological protection and sustainable development in mining cities.

Conservation of Bewick’s swans (Cygnus columbianus bewickii): Insights from the identification of critical stopover sites and migration corridors

Migratory birds face diverse threats during migration. Critical stopover sites (CSSs) are essential refueling and resting sites for migratory birds that ensure their complete migration and survival. Therefore, identifying bird migration patterns, routes, and critical habitats is vital for conservation. From 2018–2022, we deployed satellite tracking devices on 30 Bewick’s swans (Cygnus columbianus bewickii) wintering in China to determine their migration routes. Using a dynamic Brownian bridge movement model, we identified migration corridors, core movement areas, and CSSs for Bewick’s swans. Combining protected area databases and human settlement types, we further assessed the swans’ conservation status and human impacts on CSSs. The results showed that Bewick’s swans migrated north from their wintering grounds using one of three routes (west, middle, and east), passing through Mongolia to reach the Russian Arctic (breeding grounds) in spring. They followed similar routes during autumn to return to wintering grounds. We found a new middle route within the East Asian–Australasian Flyway (EAAF) and several northward expanded wintering sites. Our study revealed similarities and differences in the spring and autumn migrations, with longer stopover durations in spring due to migration strategies and ice conditions. Moreover, our findings identified the Inner Mongolia region, the Songnen Plain, the Bohai Rim of China, and the main streams of the Lena River and the Ob River of Russia as CSSs for Bewick’s swans. However, the conservation status of the CSSs was relatively low; and the situation was more severe in spring than in autumn, only 4.3% of the total area was protected, likely due to the distribution of farmland and urban areas. Specifically, 14.3% of the CSSs in China were in urban areas during spring, while in Mongolia and Russia this figure was less than 1%. Therefore, it is necessary to balance waterbird conservation with sustainable agriculture and urban development. This research contributes to our understanding of the migratory ecology of Bewick’s swans wintering in China. The identified migration corridors and CSSs are crucial for the future conservation of swans along the EAAF.

National organic action plans and organic farmland area growth in Europe

The expansion of organic agricultural production methods has been tendered as a critical factor in the development of a sustainable global food system. The European Union has led efforts to expand organic farming, with a current target share of 25% organic farmland area by 2030 through the Farm-to-Fork strategy. Many member states have set organic area targets through the initiation of organic action plans, but systematic, quantitative, empirical research into the effectiveness of such organic policies is lacking. This study analyses the effect of four different national organic action plans - the 1st French Organic Action Plan (2008 to 2012), the 2nd Swedish Organic Action Plan (2006 to 2010), the 2nd Czech Organic Action Plan (2011 to 2015) and the 5th Austria Organic Action Plan (2011 to 2013) - on organic farmland area extent. This was achieved using a balanced country-level panel dataset consisting of 26 OECD states between 2001 and 2019 (N = 494). The synthetic control method was applied systematically to predict the counterfactual organic area growth paths, enabling the quantification of the treatment effects for the selected action plans. The model specifications were vigorously tested with leave-out-one robustness tests and in-space placebo tests. The results indicated robust, large, positive and significant effects for the French and Swedish organic action plans on organic farmland area. However, the Czech and Austrian plans were found to be ineffectual. Whilst organic action plans appear useful agenda-setting tools, caution is advised in relying on them to produce consistent results, particularly if numerous plans have been previously implemented and the organic area share is already high. This finding is also likely indicative of decreasing marginal returns to action plans. A deeper understanding of the effectiveness of previously implemented plans is critical for the optimisation of future interventions.

Contamination Characteristics and Source Apportionment of Potentially Toxic Elements in Soil around the Coal-fired Power Plant Using APCS-MLR and PMF Models

To investigate the characteristics and sources of potentially toxic elemental contamination in soils around the coal-fired power plant, we selected the soil around the Jingyuan power plant as the object of investigation. Thirty-six and 27 soil samples collected from the urban and farmland areas were analyzed for PTEs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn), respectively. We employed the geoaccumulation index, single-factor pollution index, and improved Nemerow integrated pollution index to evaluate the contamination characteristics of PTEs, and combined correlation analysis with absolute principal component scores-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) receptor models were used to quantitatively analyze the pollution sources of PTEs. The results revealed that all the average concentrations of other soil metals around Jingyuan power plant exceeded their corresponding background values of Gansu Province, except for As, in agricultural soil, and Hg exhibited significant spatial non-homogeneity, and thus it was visibly affected by anthropogenic activities. The values of the single-factor pollution and geoaccumulation indices indicated that the soils of both sites were mainly contaminated with Cd, Cr, Ni, and Pb, and Hg contamination was reflected in wide areas for both sites. Additionally, the results of the improved Nemerow index demonstrated that the investigated soil was between moderately contaminated and heavily contaminated. Further, the comprehensive pollution degree of urban soil was higher than that of agricultural soil. Moreover, source apportionment revealed that PTEs in urban soil were derived from mixed sources of traffic activities and coal combustion, mixed sources of traffic activities and industrial and mining activities, and atmospheric deposition from industrial activities, with contribution rates of APCS-MLR of 35.2%, 25.1%, and 23.4%, respectively. The PMF contribution rates were 40.2%, 12.4%, and 47.7%, respectively. PTEs in agricultural soil were from one mixture source of industrial, mining, agricultural, and traffic sources, and the other mixed source was of traffic activities and coal combustion, with a APCS-MLR contribution rate of 40.3% and 35.9% and a contribution rate of PMF of 36.2% and 18.0%, respectively. In addition, another mixed source of agricultural activities and coal combustion was obtained using the PMF model, with a contribution rate of 48.5%.

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.

A Kriging Method for the Estimation of ALS Point-Cloud Accuracy without Ground Truth

Airborne LiDAR scanning is a promising approach to providing high-resolution products that are appropriate for different applications, such as flood management. However, the vertical accuracy of airborne LiDAR point clouds is not constant and varies in space. Having a better knowledge of their accuracy will assist decision makers in more accurately estimating the damage caused by flood. Data producers often report the total estimation of errors by means of comparison with a ground truth. However, the reliability of such an approach depends on various factors including the sample size, accessibility to ground truth, distribution, and a large enough diversity of ground truth, which comes at a cost and is somewhat unfeasible in the larger scale. Therefore, the main objective of this article is to propose a method that could provide a local estimation of error without any third-party datasets. In this regard, we take advantage of geostatistical ordinary kriging as an alternative accuracy estimator. The challenge of considering constant variation across the space leads us to propose a non-stationary ordinary kriging model that results in the local estimation of elevation accuracy. The proposed method is compared with global ordinary kriging and a ground truth, and the results indicate that our method provides more reliable error values. These errors are lower in urban and semi-urban areas, especially in farmland and residential areas, but larger in forests, due to the lower density of points and the larger terrain variations.

Long-term responses of the water cycle to climate variability and human activities in a large arid irrigation district with shallow groundwater: Insights from agro-hydrological modeling

Climate variability and human activities are the two major driving forces of changes in the hydrological cycle. However, how these two factors separately influence the water cycle in arid irrigation districts with shallow groundwater tables is still unknown. This study aimed to investigate the long-term changes in the water cycle and then quantify the individual contributions of climate variability and human activities to the changes in the water cycle in a large irrigation district. The Hetao Irrigation District (HID), located in the upper Yellow River Basin in Northwest China, was selected as the case study area, and an agro-hydrological model (SWAT-AG), which has powerful capabilities to model complex agro-hydrological processes, was employed as the simulation tool. The results showed that from 2000 to 2018, evapotranspiration (ET) of growing season in the HID remained relatively stable, but there were significant decreases in evaporation and dramatic increases in transpiration. For the subsurface hydrological processes, deep percolation and capillary rise of growing season both showed a decreasing trend, while groundwater drainage showed an increasing trend. The water exchange between the atmosphere layer and the root zone (i.e., ET, including evaporation and transpiration) was more significantly dominated by climatic conditions. In contrast, the subsurface hydrological processes were mainly affected by human activities, e.g., irrigation management, canal seepage, farmland area and cropping pattern. Climate variability contributed to approximately 60% of the changes in ET, whereas human activities introduced over 70% of the changes in deep percolation, capillary rise, and groundwater drainage, respectively. This study provides valuable insights into the impacts of climate variability and human activities on the changes in the water cycle and enhancements of water management practices in arid irrigation districts with shallow groundwater tables.

Impact of Hydrological Changes on Wetland Landscape Dynamics and Implications for Ecohydrological Restoration in Honghe National Nature Reserve, Northeast China

Marsh wetlands are significant ecosystems located between land and water bodies which can both protect species diversity and provide habitats. Changes in the hydrological situation of marsh wetlands as a result of climate change and human activities have led to the degradation of wetland landscapes. Taking the Honghe National Nature Reserve (HNNR) in Heilongjiang Province, China, as an example, this paper gathered information on the reserve’s wetland landscape before and after dam construction. The information was obtained using field survey data and a random forest classification method based on Landsat data powered by the Google Earth Engine (GEE) cloud platform. Then, on the basis of the water level data and the digital elevation model, the wetland landscape dynamics of HNNR under three water level conditions were simulated. The findings were as follows: (1) From 1998 to 2008, the area of marsh and meadow had a downward trend, while the area of forest, farmland and water showed a gradual and upward trend; a marked rise in the area of marsh and a continued rise in the area of forest, farmland and water, and a sharp decline in the area of meadow during 2008 to 2018 was observed. (2) There was a significant increase in the area of marsh under the 20 and 40 cm water level simulation scenarios, with a decrease in the number of patches, and an increase in the aggregation index with rising water levels; in contrast, when the water level rose to 60 cm, the area of marsh and the number of patches decreased, but the aggregation index continued to increase. (3) The correlation between wetland landscape and the water level was a nonlinear one. The area of marsh increased and then decreased with increasing water level, reaching a maximum at the 40 cm water level; therefore, 40 cm was the optimal water level regulation scenario. Hydrological processes are the most fundamental ecological processes in marsh wetlands. Understanding the scientific pattern of the spatial pattern characteristics of species as a function of water level environment is important for scientifically guiding the restoration of marsh vegetation.

Heavy Metal Contamination in Topsoil in Mining-Plagued Communities in the Amansie West District, Ghana

ABSTRACT This study was conducted in five randomly selected small-scale mining communities in the Amansie West District of Ashanti Region, Ghana to assess the impacts of small-scale mining activities on heavy metal presence in three different land use types (mined site, farmland and forest area). Using a random sampling design, a total of 60 soil samples were collected from 0–20 cm depth and analyzed for soil heavy metals: arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg) and copper (Cu) using Two-way ANOVA. Heavy metal concentrations for As (5.571 mg/kg), Cd (0.002 mg/kg), Cu (1.158 mg/kg), Pb (0.076 mg/kg) in the communities did not exceed the FAO/WHO permissible limits with the exception of Hg concentrations for the respective communities (0.68 mg/kg, 1.07 mg/kg, 1.26 mg/kg, 1.28 mg/kg, 17.03 mg/kg) whose levels were 2.3 to 56.8 times higher than FAO/WHO permissible limits (0.3 mg/kg). The distribution of heavy metals in the soil was not uniform across the different land use types in the mining landscape. Differences in heavy metal concentrations were significant (p < .05) at the community, land use and their interaction (community*land use) levels with the exception of As concentration at the land use level (p > .05). The study concludes that soils of the major land use types in the study area (mined sites, farmlands and forest area) are all contaminated by Hg accumulation. Therefore, effective rehabilitation of mined sites in mining-plagued-communities should include measures for removing mercury from the soil.

Ecological Water Requirement of Vegetation and Water Stress Assessment in the Middle Reaches of the Keriya River Basin

Desert oases are vital for maintaining the ecological balance in arid regions’ inland river basins. However, fine-grained assessments of water stress in desert oasis ecosystems are limited. In our study, we aimed to evaluate the water stress in desert oasis ecosystems in the middle reaches of the Keriya River Basin, with a specific focus on their ecological functions and optimizing water resource management. We hypothesized that evapotranspiration has significant effects on ecological water consumption. First, we estimated the actual evapotranspiration (ET) and potential evapotranspiration (PET) based on the SEBS (surface energy balance system) model and remote sensing downscaling model. Then, the ecological water requirement (EWR) and ecological water stress (EWS) index were constructed to evaluate the ecological water resource utilization. Finally, we explored the influencing factors and proposed coping strategies. It was found that regions with higher ET values were mainly concentrated along the Keriya River and its adjacent farmland areas, while the lower values were observed in bare land or grassland areas. The total EWR exhibited the sequence of grassland &gt; cropland &gt; forest, while the EWR per unit area followed the opposite order. The grassland’s EWS showed a distinct seasonal response, with severe, moderate, and mild water shortages and water plenitude corresponding to spring, summer, autumn, and winter, respectively. In contrast, the land use types with the lowest EWS were water areas that remained in a state of water plentitude grade (0.08–0.20) throughout the year. Temperature and vegetation index were identified as the primary influencing factors. Overall, this study provides a reliable method for evaluating the EWR and EWS values of basin scale vegetation, which can serve as a scientific basis for formulating water resource management and regulation policies in the region.

Evaluating the Land Use and Land Cover change of unprotected wetland situated in the Khultabad Tehsil of Aurangabad District, Maharashtra

The study investigated the effects of Land Use and Land Cover (LULC) change dynamics on the state and status of an unprotected wetland in semi-arid regions of India. The effects of the LULC shift on the wetland during a 15-year period were mapped and quantified using the long-term satellite image data collection. Using the supervised analysis approach, a multi-source satellite image analysis was carried out. The complete research area's Landsat data series were utilised to evaluate, map, and track LULC change over time. Wetland detection maps created for the 2007–2013–2016–2022 temporal periods were examined. According to the findings, the amount of agricultural land remained essentially constant during the comparative period, ranging from 29.71% to 31.43%. The percentage of waste land progressively grew from 14.29% to 22.86% between 2007 and 2016. By 2022, the plantation area will have shrunk from 15.43% in 2007 to 5%. Similarly, it is anticipated that the habitat would grow from 8.07% in 2007 to 12.93% in 2022. Farmland and fallow area figures are different because both land uses were determined using different season satellite pictures. But there is no obvious increase or decrease in the total agricultural area. These results may be used to create specialised wetland management plans and perhaps even a framework for restoring wetlands that are not currently under protection

Low-carbon transformation of China's smallholder agriculture: exploring the role of farmland size expansion and green technology adoption.

Farmland size and green technology have a significant impact on agricultural carbon emissions. However, more research needs to consider the impact of their interaction on agricultural carbon neutralization. In this paper, the impact of farmland size on the net carbon effect and its underlying mechanisms from the perspective of green agricultural technology adoption were empirically examined using a tracking survey of 2600 farming households. The results show that farmland size expansion at both household and plot levels can increase the net carbon effect of the planting industry, which is more pronounced for grain crops than cash crops. Specifically, a 1% increase in the total area of household farmland or the largest contracted plot area can increase the net carbon effect by more than 3%. Green technology also plays a mediation effect in their relationship. Increasing farmland size can generate sufficient economic incentives to encourage green technology adoption, contributing to carbon sequestration and emissions reduction and increasing the crop's net carbon effect. Furthermore, we find that farmland expansion can significantly encourage the adoption of efficiency-enhancing technologies but not environmentally friendly technologies. Our findings suggest that promoting farmland expansion and green technology extension is effective for the low-carbon transformation of Chinese agriculture. The government should make distinct promotion policies for various green agricultural technologies and differentiating incentives and support policies for different-sized farmers. Our study provides insights into the path to Chinese-style agricultural modernization in the context of a smallholder economy.

Multi-Scale Stereoscopic Hyperspectral Remote Sensing Estimation of Heavy Metal Contamination in Wheat Soil over a Large Area of Farmland

With the rapid development of China’s industrialization and urbanization, the problem of heavy metal pollution in soil has become increasingly prominent, seriously threatening the safety of the ecosystem and human health. The development of hyperspectral remote sensing technology provides the possibility to achieve the rapid and non-destructive monitoring of soil heavy metal contents. This study aimed to fully explore the potential of ground and satellite image spectra in estimating soil heavy metal contents. We chose Xushe Town, Yixing City, Jiangsu Province as the research area, collected soil samples from farmland over two different periods, and measured the contents of the heavy metals Cd and As in the laboratory. At the same time, under field conditions, we also measured the spectra of wheat leaves and obtained HuanJing-1A HyperSpectral Imager (HJ-1A HSI) satellite image data. We first performed various spectral transformation pre-processing techniques on the leaf and image spectral data. Then, we used genetic algorithm (GA) optimized partial least squares regression (PLSR) to establish an estimation model of the soil heavy metal Cd and As contents, while evaluating the accuracy of the model. Finally, we obtained the best ground and satellite remote sensing estimation models and drew spatial distribution maps of the soil Cd and As contents in the study area. The results showed the following: (1) spectral pre-processing techniques can highlight some hidden information in the spectra, including mathematical transformations such as differentiation; (2) in ground and satellite spectral modeling, the GA-PLSR model has higher accuracy than PLSR, and using a GA for spectral band selection can improve the model’s accuracy and stability; (3) wheat leaf spectra provide a good ability to estimate soil Cd (relative percent difference (RPD) = 2.72) and excellent ability to estimate soil As (RPD = 3.25); HJ-1A HSI image spectra only provide the possibility of distinguishing high and low values of soil Cd and As (RPD = 1.87, RPD = 1.91). Therefore, it is possible to indirectly estimate soil heavy metal Cd and As contents using wheat leaf hyperspectral data, and HJ-1A HSI image spectra can also identify areas of key pollution.

Identifying the influence of natural and human factors on seasonal water quality in China: current situation of China's water environment and policy impact.

Agricultural production, urbanization, and other anthropogenic activities, the major causes of surface water pollution in China, have dramatically altered hydrological processes and nutrient cycles. Identifying and quantifying the key factors affecting water quality are essential for the better prevention and management of water pollution. However, due to the limitations of traditional statistical analysis methods, it is difficult to evaluate the spatial changes and interactions of influencing factors on water quality. In addition, research on a national scale is difficult, as it involves large-scale and long-term water quality monitoring work. In this study, we collected and collated the monthly average concentrations of four water quality parameters, dissolved oxygen, ammonia nitrogen, chemical oxygen demand, and total phosphorous, based on data from 1547 water quality monitoring stations in China. The combined pollution level of the water quality was assessed using the water quality index. Based on the water quality characteristics, water quality monitoring sites in the dry and wet seasons were grouped using k-means clustering. Eleven environmental factors were evaluated using geodetector software, including six human factors and five natural factors. The results showed that there are high-risk areas for water quality pollution in the eastern and southeastern coastal regions of China in both the dry and wet seasons and that surface water pollution in China is highly spatial heterogenous in both the dry and wet seasons. Among the anthropogenic factors, urban land area is the main factor of water quality pollution in the dry season, and the explanation rate of spatial heterogeneity of integrated water quality pollution index is 20.3%. The number of poultry farms and the area of farmland explained 12.4% and 12.1% of the integrated water quality pollution index in the wet season. The nonlinear relationship between these three anthropogenic and natural factors and their interaction exacerbated water quality pollution. Based on this analysis, we identified the key factors affecting surface water quality in China during the dry and wet seasons, evaluated the achievements of the water environmental protection policies in China in recent years, and proposed future management measures for the effective prevention and control of water quality pollution in high-risk areas.

On Land Use and Biodiversity Resilience: Hydrology, Temperature Regulation and the Fractal Nature of the Woodland-Grassland Interface

The coverage of land territorial areas with either natural forests and grasslands, or instead with cultured farmland or urbanized areas, plays a primary role in climate regulation of the planet. The contribution of forest hydrology and local temperature regulation to global climate change, however, is not simply an area surface-dependent measure, like some global surveys suggest. There is also an important vertical component to it, affecting the atmospheric conditions and turning the land coverage into a volumetric, beneficial effect on the climate. Wood fires, on the contrary, constitute an additional climate threat. Historically, a certain health risk resulting from monotonous wood coverage has been foretold almost two centuries ago, without an exact knowledge of how these man-made plantations would impact the future climate. A case study based on comparing the Alpujarra and Low Country forests is included to indicate the different approaches followed in divergent cultures. In this paper, moreover, the notion of Woodland-Grassland Interface is introduced as a fractal model system. It not only describes the fractal geometry of the border, but also indicates the complex ecological interactions that constitute the biodiversity of an ecosystem. The same approach may be fruitful for modeling coral reefs and mangrove forests, all displaying some form of fractal network system. The appreciation of a border interface in all of these ecosystems is found crucial, both for mitigating climate adaptation and for improving biodiversity resilience.

Black carbon, soil organic matter molecular signatures under different land uses in Shenyang, China and relationship with PAHs

The content, composition and molecular signatures of soil organic matter (SOM) have important influences on the cycle of soil organic carbon (SOC) and the partitioning of polycyclic aromatic hydrocarbons (PAHs) in soil. Seventy-nine soil samples from farmland, forest and urban areas were collected in Shenyang, China to investigate black carbon (BC) content, SOM molecular signatures varied with land use patterns, as well as the relationship with PAHs. The content of BC in urban soils was significantly higher than that of farmland and forest. BC was a key contributor of urban SOM which accounted for 0.35 ± 0.31 of SOC in urban soil. Based on BC/SOC ratio, the main sources of BC were identified as fossil fuel combustion for urban soils, while for farmland and forest soils, it is the mixed results of fossil fuel combustion and biomass burning. All categories of PAHs in urban soils showed the highest level compared to farmland and forest soils. Pearson's correlation analysis results showed there were significant positive correlations between BC and PAHs categories in urban soils, indicating the important role of BC in the accumulation of PAHs in soil. SOM from each of the two different land use patterns can be distinguished by molecular signatures. Urban SOM had abundant molecular markers derived from condensed organic carbon inputs, which was consistent with the BC/SOC value. Farmland SOM had abundant carbon from vegetation and microorganisms, and forest SOM was rich in organic carbon from fresh plant materials. The markers enriched in urban SOM showed significant correlations with most PAHs categories, highlighting the affinity of urban SOM for PAHs at the molecular level. This study contributed to understanding the impact of land management methods on SOM molecular composition signatures and its influence on PAHs occurrence in soil, providing a theoretical basis for regional soil pollution management.

Modeling of land use/land cover dynamics using artificial neural network and cellular automata Markov chain algorithms in Goang watershed, Ethiopia

Land Use/Land Cover (LULC) change has inhibited sustainable development for the last millennia by affecting climate, biological cycles, and ecosystem services and functions. In this regard, understanding the historical and future patterns of LULC change plays a crucial role in implementing effective natural resource management. This study aimed to model and characterize the spatiotemporal trajectories of landscape change between the 1984 and 2060 periods. The satellite image spectral information was segmented into seven LULC classes using a hybrid approach of image spectral recognition. The supervised classification technique of Support Vector Machine (SVM) was used to classify the satellite images, whilst the Land Change Modeler (LCM) Module in TerrSet software was used to assess the historical trend and future simulation of LULC dynamics. To predict future landscape changes, transition potential maps were generated using a Multi-layer Perceptron (MLP) neural network algorithm. The findings of the study demonstrated that the Goang Watershed has experienced significant LULC change since 1984. During the 1984–2001, 2001–2022, and 1984–2022 periods, farmland showed a dramatic increasing trend with 7.5 km2/yr−1, 110.3 km2/yr−1, and 64.3 km2/yr−1, respectively. A similar trend was also observed in built-up areas with 0.5 km2/yr−1, 3.2 km2/yr−1, and 2 km2/yr−1. The expansion of farmland and built-up area was at the expense of forest, shrubland, and grasslands. With a business-as-usual scenario, the extent of farmland will continue to increase between 2022 and 2060 while rapid reduction is expected by forest, shrubland, and grasslands. The alarming rate of farmland and built-up area expansion will put significant pressure on biodiversity and ecosystem services in the area. As a result, eco-friendly conservation approaches should be implemented as soon as possible to maintain ecosystem health and encourage sustainable development.

Analysis of spatiotemporal variations and influencing factors of soil erosion in the Jiangnan Hills red soil zone, China

Soil erosion is an important environmental problem in China. The hilly region of Jiangnan is characterized by severe soil erosion due to its unique climate and intensive human activities. Therefore, assessing soil erosion in this area is of great significance for achieving regional sustainable development. Based on the spatial zoning of natural resources and the spatial differences in precipitation, land cover, topographic features, and soil texture, we estimated soil erosion from 2000 to 2020 using the Revised Universal Soil Loss Equation (RUSLE) model. The study showed that micro-erosion dominates spatially in the subtropical forest subzone of the eastern hills, accounting for more than 60% of the total erosion area. Intense erosion was found in woodlands and grasslands and the erosion intensity tended to be lower in the plains. Erosion occurred mainly in areas with slopes >8°. The areas with significantly lower erosion were mainly distributed at the boundaries between forests, arable land, and artificial land surfaces. The areas where soil erosion significantly increased over the study period were mainly found in farmland areas (31.70%). Soil erosion occurred because of a combination of factors, among which vegetation cover played a prominent role. Elevation and slope were correlated with soil erosion intensity. Severe erosion in different parts of the study area showed two trends of spatial aggregation and discrete distribution. This analysis of soil erosion in the study area by the RUSLE model provides reference data for the eastern subtropical forest subregion including the Jiangnan Hills.