The framework of an agricultural land-use decision support system based on ecological environmental constraints

Synergizing economic growth and carbon emission reduction in China: A path to coupling the MFLP and PLUS models for optimizing the territorial spatial functional pattern

Carbon emissions caused by economic growth are the main cause of global warming, but controlling economic growth to reduce carbon emissions does not meet China's conditions. Therefore, how to synergize economic growth and carbon emission reduction is not only a sustainable development issue for China, but also significant for mitigating global warming. The territorial spatial functional pattern (TSFP) is the spatial carrier for coordinating economic development and carbon emissions, but how to establish the TSFP of synergizing economic growth and carbon emission reduction remains unresolved. We propose a decision framework for optimizing TSFP coupled with the multi-objective fuzzy linear programming and the patch-generating land use simulation model, to provide a new path to synergize economic growth and carbon emission reduction in China. To confirm the reliability, we took Qionglai City as the demonstration. The results found a significant spatiotemporal coupling between TSFP and the synergistic states between economic growth and carbon emission reduction (q ≥ 0.8220), which resolves the theoretical uncertainty about synergizing economic growth and carbon emission reduction through the path of TSFP optimization. The urban space of Qionglai City in 2025 and 2030 obtained by the decision framework was 6497.57 hm2 and 6628.72 hm2 respectively, distributed in the central and eastern regions; the rural space was 60,132.92 hm2 and 56,084.97 hm2, concentrated in the east, with a few located in the west; and the ecological space was 71,072.52 hm2 and 74,998.31 hm2, mainly located in the western and southeastern areas. Compared with the TSFP in 2020, the carbon emission intensity of the TSFP obtained by the decision framework was reduced by 0.7 and 4.7 tons/million yuan, respectively, and realized the synergy between economic growth and carbon emission reduction (decoupling index was 0.25 and 0.21). Further confirming that TSFP optimization is an effective way to synergize economic growth and carbon emission reduction, which can provide policy implications for coordinating economic growth and carbon emissions for China and even similar developing countries.

AI can empower agriculture for global food security: challenges and prospects in developing nations

Food and nutrition are a steadfast essential to all living organisms. With specific reference to humans, the sufficient and efficient supply of food is a challenge as the world population continues to grow. Artificial Intelligence (AI) could be identified as a plausible technology in this 5th industrial revolution in bringing us closer to achieving zero hunger by 2030-Goal 2 of the United Nations Sustainable Development Goals (UNSDG). This goal cannot be achieved unless the digital divide among developed and underdeveloped countries is addressed. Nevertheless, developing and underdeveloped regions fall behind in economic resources; however, they harbor untapped potential to effectively address the impending demands posed by the soaring world population. Therefore, this study explores the in-depth potential of AI in the agriculture sector for developing and under-developed countries. Similarly, it aims to emphasize the proven efficiency and spin-off applications of AI in the advancement of agriculture. Currently, AI is being utilized in various spheres of agriculture, including but not limited to crop surveillance, irrigation management, disease identification, fertilization practices, task automation, image manipulation, data processing, yield forecasting, supply chain optimization, implementation of decision support system (DSS), weed control, and the enhancement of resource utilization. Whereas AI supports food safety and security by ensuring higher crop yields that are acquired by harnessing the potential of multi-temporal remote sensing (RS) techniques to accurately discern diverse crop phenotypes, monitor land cover dynamics, assess variations in soil organic matter, predict soil moisture levels, conduct plant biomass modeling, and enable comprehensive crop monitoring. The present study identifies various challenges, including financial, infrastructure, experts, data availability, customization, regulatory framework, cultural norms and attitudes, access to market, and interdisciplinary collaboration, in the adoption of AI for developing nations with their subsequent remedies. The identification of challenges and opportunities in the implementation of AI could ignite further research and actions in these regions; thereby supporting sustainable development.

Coupling coordination and spatio-temporal evolution of land-use benefits under the dual carbon goal: A case study in Anhui, China

According to the dual carbon goal, urban development should adhere to the principle of low-carbon sustainable development in order to reach the "carbon peak" in 2030 and "carbon neutrality" in 2060. To achieve the dual carbon goal and sustainable land resource utilization, it is necessary to seek ways to improve land-use benefits and promote the coordinated development of economic, social, and ecological benefits. Therefore, the study analysed the coupling coordination and spatio-temporal evolution of land-use benefits in Anhui province, aiming to provide a reference for improving the level of regional land-use benefits. First, we developed a land-use benefit evaluation indicator system that took into account the dual carbon goal from three perspectives: economic benefits, social benefits, and ecological benefits or economic, social, and ecological benefits. Following that, we evaluated the spatial-temporal characteristics of land-use benefits using the coupling coordination model and coupling coordination gravity model. The results showed: (1) From the time scale, the comprehensive land-use benefits showed an increasing trend from 2011 to 2020, the coordination state changed from "moderately uncoordinated" to "on the verge of uncoordinated". (2) From the perspective of spatial differences, the coupling coordination level of land-use benefits in 16 prefecture-level cities increased year by year, but no prefecture-level cities reached the coordination stage. (3) As for the spatial linkage strength of coupling coordination of land-use benefits, 16 prefecture-level cities in 2011, 2015 and 2020 presented a similar spatial linkage pattern, and the coupling coordination of prefecture-level cities in southeast Anhui province was strongly influenced by regional factors.

A Deep Learning-Based Decision Support Tool for Plant-Parasitic Nematode Management

Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task. This study developed a state-of-the-art deep learning model-based decision support tool to detect and estimate the nematode population. The decision support tool is integrated with the fast inferencing YOLOv5 model and used pretrained nematode weight to detect plant-parasitic nematodes (juveniles) and eggs. The performance of the YOLOv5-640 model at detecting RKN eggs was as follows: precision = 0.992; recall = 0.959; F1-score = 0.975; and mAP = 0.979. YOLOv5-640 was able to detect RKN eggs with an inference time of 3.9 milliseconds, which is faster compared to other detection methods. The deep learning framework was integrated into a user-friendly web application system to build a fast and reliable prototype nematode decision support tool (NemDST). The NemDST facilitates farmers/growers to input image data, assess the nematode population, track the population growths, and recommend immediate actions necessary to control nematode infestation. This tool has the potential for rapid assessment of the nematode population to minimise crop yield losses and enhance financial outcomes.

The development and future frontiers of global ecological restoration projects in the twenty-first century: a systematic review based on scientometrics

Ecological restoration projects are becoming a mainstream of research, and their studies are widely followed by scholars worldwide, yet there is no comprehensive review of this research. Nowadays, bibliometrics has attracted much attention from the scientific community, and its methodological approach allows quantitative and qualitative analysis of research performance in journals or subject areas. This paper provides a systematic and comprehensive description of the progress and hotspots of ecological restoration projects from a bibliometric perspective, based on 1173 articles in the Web of Science Core Collection (WOSCC) database. Research on ecological restoration projects has shown a positive growth trend since the twenty-first century. China and the USA are the most active countries in terms of the number of relevant articles published, and more than half of the top 10 active institutions are from China, but there is less collaboration between different countries/institutions. Research in ecological restoration projects is summarized into three main research areas: the main ecological damage problems, the impact of human beings on ecological damage, and the main methods of ecological restoration. Finally, some challenges and outlooks conducive to the rapid and balanced development of ecological restoration projects are presented, which provide valuable references and help for future researchers.

The Impact of Land Use Structure Change on Utilization Performance in Henan Province, China

Because of the trends in population growth and rapid industrialization and urbanization, the intensity and structure of land use are undergoing great changes. Henan Province is an important economic province and a major grain producing and energy consumption area, and its land use plays a key role in the sustainable development of the whole of China. This study takes Henan Province as the research object, selects panel statistical data from 2010 to 2020, and discusses the land use structure (LUS) in Henan Province in terms of three aspects: information entropy, analysis of land use dynamic change, and land type conversion matrix. Based on the indicator system "social economy (SE)-ecological environment (EE)-agricultural production (AP)-energy consumption (EC)", a land use performance (LUP) evaluation model was constructed to judge the performance of various land use types in Henan Province. Finally, the relational degree between LUS and LUP was calculated through the grey correlation. The results show that among the eight land use types in the study area since 2010, land used for water and water conservancy facilities increased by 4%. In addition, transport and garden land changed significantly, and was mainly converted from cultivated land (decreased by 6674 km²) and other land. From the perspective of LUP, the increase in ecological environment performance is the most obvious, while agriculture performance is lagging behind; it is worth paying attention to the energy consumption performance, which is decreasing year by year. There is an obvious correlation between LUS and LUP. LUS in Henan Province presents a gradually stable state, and the transformation of land types promotes LUP. Proposing an effective and convenient evaluation method to explore the relationship between LUS and LUP is very beneficial in helping stakeholders to actively focus more on optimizing land resource management and decision making for the coordinated and sustainable development among agricultural, socio-economic, eco-environmental, and energy systems.

Inexact fuzzy-flexible left-hand-side chance-constrained programming for agricultural nonpoint-source water quality management

In this study, an inexact fuzzy-flexible left-hand-side chance-constrained programming (IFLCCP) method is proposed for optimizing an agricultural nonpoint-source water quality management problem under uncertainty. The developed method can address complex uncertainties resulted from system fuzzy flexible under various level of decision-making requirements and randomness parameters appeared on the left-hand side of the constraints, and deal with the conflict between water quality protection and agricultural system economic development. The IFLCCP model is formulated through incorporating inexact left-hand-sided chance-constrained programming into interval fuzzy flexible programming framework. The decision schemes obtained by the IFLCCP are analyzed under scenarios at different confidence level of environmental constraint. The results demonstrate that the scale of crop planting and breeding industries reduces as the confidence coefficient of environmental constraint (1-pi) increases, in order to satisfy pollutant discharge constraints, which results in the reduction of the system net benefit from scenarios 1 to 3. Meanwhile, the interval control variables λ± are introduced for quantifying the degrees of overall satisfaction for the objective function and the constraints, which get optimal adjustment to guarantee the net benefit to be as close as possible to the upper bound. The IFLCCP is able to provide management schemes with high system benefits under different levels of acceptable environmental risk, taking full consideration of decision makers' environmental management requirements. This study is a new application of the IFLCCP model to agricultural water quality management problem, demonstrating its applicability to practical environmental problems with high complexity and uncertainty.

Impacts of droughts on agricultural and ecological systems based on integrated model in shallow groundwater area

Agricultural and ecological developments are increasingly paid attention in light of climate change. It is expected to comprehensively macroscopically control agricultural and ecological developments in shallow groundwater area that ecology is closely related to agricultural development. This study synthesizes multi models, including process-based crop growth model, water status model of shelterbelt, and vegetation-soil-groundwater interactions to identify responses of crops, shelterbelt, and natural vegetation to different level droughts. Obtained results show that the rank of vulnerabilities to droughts is: maize (the most vulnerable crop) > wheat > sunflower > shelterbelt (the least vulnerable vegetation). Under three drought scenarios, the natural vegetation biomass is all in stable states that fluctuations of groundwater salinity and precipitation cannot largely change the natural vegetation biomass. The natural vegetation biomass in equilibrium states is decreased by 4.08 % and 9.19 % respectively when available irrigation water is reduced to 70 % and 50 % levels. The results indicate that controlling and decreasing initial soil salt content before crop growth may be an effective way to avoid the decrease in the yield loss caused by salinization. It is suggested that vulnerable crops and the possible evolution of natural vegetation towards degradation in extreme droughts should be concerned and taken certain measures. This study also implies that optimizing planting structure is a possible strategy to improve adaptabilities to droughts and decrease economic losses. The established model contributes to provide an effective approach to handle large-scale decision-making problems about comprehensively developing agriculture and ecology in changing environments. Obtained results can provide reference strategies for managers to achieve sustainable development.

Global simulation of fine resolution land use/cover change and estimation of aboveground biomass carbon under the shared socioeconomic pathways

Land use change driven by human activities plays a critical role in the terrestrial carbon budget through habitat loss and vegetation change. Despite the projections of the global population and economic growth under the framework of the Shared Socioeconomic Pathways (SSPs), little is known of land use/cover change (LUCC) at a fine spatial resolution and how carbon pools respond to LUCC under different SSPs. This study projected the future global LUCC with 1 km spatial resolution and a 10-year time step from 2010 to 2100 and then explored its direct impacts on aboveground biomass carbon (AGB) under SSPs. Scenario SSP3 yields the highest global cropland expansion, among which approximately 48% and 46% is expected to be located in the current forest land and grassland, respectively. Scenario SSP1 has the largest forest expansion and is mainly converted from grassland (54%) and cropland (30%). Due to the spatial change in land use/cover, global AGB loss is expected to reach approximately 3.422 Pg C in 2100 under scenario SSP3 and increases by approximately 0.587 Pg C under scenario SSP1. Africa is expected to lose 30% of AGB under the scenario SSP3. Aboveground biomass in Asia will fix 0.774 Pg C to reverse the AGB loss in 2100 under scenario SSP1. The global carbon loss estimated by the land use products with 10 km and 25 km resolution are less than that with 1 km by 1.5% (ranging from -11.2% in Africa to +34.0% in Oceania) and 2.9% (ranging from -11.8% in Africa to +24.0% in Oceania), respectively. These findings suggest that sufficient spatial details in the existing SSP scenario projections could reduce the uncertainties of AGB assessment, and reasonable land use development and management is a key measure to mitigate the negative impacts of LUCC on the biomass carbon pool.

Information entropy and elasticity analysis of the land use structure change influencing eco-environmental quality in Qinghai-Tibet Plateau from 1990 to 2015

Regional land use change affects eco-environmental quality by altering ecosystem structure and function. The primitive ecosystem and environment of the Qinghai-Tibet Plateau (QTP) occupies a special position in the world, but it is very fragile. Although land use activities on the plateau have increased gradually in past decades, its effects on eco-environmental quality and the underlying mechanisms of regional heterogeneity remain unclear. In this study, an eco-environmental quality assessment index system was established to characterize the QTP, and the information entropy and elasticity methods were introduced to quantify the impact of land use dynamic trajectory on the eco-environmental quality. It provides a statistical measurement of system structure and more information than the traditional methods to reveal the land use change. The area change in land use on QTP was small from 1990 to 2015. The unused land and forest decreased, but those of grassland, water body, built-up land, and cultivated land increased. The overall eco-environmental quality on the QTP was low, and increased at a rate of 9.39% over the past 25 years, presenting a distribution of decreasing from southeast to northwest. The improvement in eco-environmental quality attributed to land use change was mainly due to the conversion of unused land into grassland, and ecological conservation projects also improved the local ecological environment. Conversely, the expansion of built-up land and land degradation contributed to decline in local eco-environmental quality in the Hengduan Mountains, northeastern plateau, and Qaidam Basin. The results indicated that under the influence of climate change, the changes in land use and eco-environmental quality were inconsistent in part regions, mainly including the central and southern Tibet and the border zone. Regions in which eco-environmental quality has been degraded by unreasonable land use are urgent to optimize land use management.

Implementing a GIS-Based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint; Part I: A Deductive Approach

The agricultural sector has benefitted over the last century from several factors that have led to an exponential increase in its productive efficiency. The increasing use of new materials, such as plastics, has been one of the most important factors, as they have allowed for increased production in a simpler and more economical way. Various polymer types are used in different phases of the agricultural production cycle, but when their use is incorrectly managed, it can lead to different environmental impacts. In this study, an applied and simplified methodology to manage agricultural plastics monitoring and planning is proposed. The techniques used are based on quantification through the use of different datasets (orthophotos and satellite images) of the areas covered by plastics used for crop protection. The study area chosen is a part of the Ionian Coast of Southern Italy, which includes the most important municipalities of the Basilicata Region for fruit and vegetable production. The use of geographical techniques and observation methodologies, developed in an open-source GIS environment, enabled accurate location of about 2000 hectares of agricultural land covered by plastics, as well as identification of the areas most susceptible to the accumulation of plastic waste. The techniques and the model implemented, due to its simplicity of use and reliability, can be applied by different local authorities in order to realize an Atlas of agricultural plastics, which would be applied for continuous monitoring, thereby enabling the upscaling of future social and ecological impact assessments, identification of new policy impacts, market searches, etc.

Spatiotemporal Evaluation and Driving Mechanism of Land Ecological Security in Yan’an, a Typical Hill-Gully Region of China’s Loess Plateau, from 2000 to 2018

Forest landscape restoration and ecosystem of Loess Plateau have enhanced prominently, since the policy implementation (1999) of the Grain for Green Project in China. Land ecological security (LES) performs an extremely critical function for protecting vulnerable land resources and sustaining forest ecosystem stability. Predecessors’ studies substantially concentrate on biophysical and meteorologic variables using numerous grounded methodologies, little research has been launched on systematic natural-socio-economic-ecological relationships and how these contributions and regulations for LES evaluation. Here, pressure-state-response (PSR) model was used to establish the evaluation system of LES in regional-scale, and LES was classified into five levels measured by ecological security index (S), including high (S ≥ 0.75), medium−high (0.65 ≤ S < 0.75), medium (0.55 ≤ S < 0.65), medium−low (0.45 ≤ S < 0.55), and low (S < 0.45) level, for systematically analyzing its spatiotemporal distribution characteristic and response mechanism to explanatory variables in Yan’an, northwest China, from 2000 to 2018. The results demonstrated that: (1) LES status was mainly characterized by medium−high level and medium level, and maintained profound stability. (2) zone with medium−high LES level was mainly concentrated in western and southern regions, continuously expanding to northeast regions, and possessed the largest territorial area, accounting for 37.22–46.27% of the total area in Yan’an. (3) LES was primarily susceptible to normalized differential vegetation index, vegetation coverage, and land surface temperature with their optimal impacting thresholds of 0.20–0.64, 0.20–0.55, and 11.20–13.00 °C, respectively. (4) Normalized differential vegetation index and vegetation coverage had a significant synergistic effect upon LES based on their interactive explanation rate of 31% and had significant variation consistency (positive and negative) with LES, which were powerfully suggested to signal the intensification of the regional eco-security level in the persistent eco-greening process.

Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018

The land ecosystem provides essential natural resources for the survival and development of human beings. Therefore, land ecological security (LES) acts as a vital part of the sustainable development of human society and economy. This study included a dynamic analysis of land use change in Chaohu Lake Basin (CLB) in China from 1998 to 2018, evaluating the spatiotemporal patterns of LES at both the administrative district scale and grid scale (200 m × 200 m). Then, geographic detector was applied to analyze the influence of the assessment index on LES. The results show that in the 2008–2018 period, land use changed more significantly compared to the 1998–2008 period. The continuous extension of urban land led to a decrease in the areas of other land use types. In the CLB (administrative district scale), the LES levels varied throughout the study period. In Changfeng, Feixi, and the other three regions, the LES has been significantly improved. However, the LES in six other regions showed different degrees of decline, particularly in Hexian and Urban Hefei. Simultaneously, the LES showed a gradual improvement at a 200 m × 200 m grid scale level. The influence of anthropogenic factors on the LES was stronger than natural factors. Findings from this study provide reliable guidance for improving the ecosystem environment in ecologically fragile areas.

A systematic approach of determining compensation and allocation for river basin water environment based on total pollutants control

The compensation of upstream protective area should be determined carefully. This paper provides a comprehensive evaluation framework for economic assessments on the treatment of wastewater discharged into a river basin. We explore the rational costs of compensation and the funding allocation in the Xin'an River basin based on rate agreements. The compensation is determined in accordance with the total compensation model based on the opportunity cost method and allocated by the method of information entropy. In this study, we identify the total compensation payment and distribution of funds in each district and county in the upstream area (Huangshan). Results show that the She county can receive the highest compensation, and the Tunxi district deserves the lowest compensation. In addition, this paper demonstrates that the existing compensation is insufficient for the reduction of water pollutants in the upstream area. Our findings contribute to the existing schemes of ecosystem services payment and improve the environmental decision-making.

Allocation Efficiency, Influencing Factors and Optimization Path of Rural Land Resources: A Case Study in Fang County of Hubei Province, China

Land resource allocation efficiency (LRAE) is a significant indicator in weighing regional socioeconomic development. The study of LRAE can provide useful references for optimizing the layout of rural land use and conducting village planning against the background of rural revitalization strategy. Taking Fang County of Hubei Province as an example, we constructed an efficiency measurement index system based on economic, social, and ecological objectives. The slack-based measure with undesirable output (SBM-Undesirable) model and geodetector model were used to evaluate the rural LRAE, influencing factors and optimization paths from 2011 to 2017. The results suggest that: (1) the rural LRAE in Fang County shows a steady upward trend, with an average increasing rate of 9.204%. The townships in the north and south of the study area have a low LRAE value, and townships in the central area have a high LRAE value. The number of villages at low or medium-low LRAE is decreasing, and the number of villages with medium-high or high LRAE continued to increase from 2011 to 2017. (2) The spatial variation in LRAE in Fang County is affected by physical geography conditions, rural development conditions, and urban-rural relations. The impact of the proportion of primary industry and rural population has always been influential on the LRAE. Physical geography conditions have a relatively strong impact on the LRAE, but their values are decreasing. The influences of the Engel coefficient, urbanization rate and gap between the rural and urban resident's income have been continuously enhanced. (3) All land types have obvious input redundancies, and reducing these redundancies can help achieve the optimal allocation of rural land resources. In the future, it is of significance to prioritize low-carbon and green developments, and to promote sustainable rural development.

Exploring environmental efficiency and total factor productivity of cultivated land use in China

During cultivated land use, nonseparable relationships exist between certain inputs and outputs. This study explored the influence of the nonseparable characteristics of input and output variables on both the cultivated land use environmental efficiency (CLUEE) and the cultivated land use environmental total factor productivity (CLUETFP). To evaluate China's CLUEE and CLUETFP from 1997 to 2017, we used the nonseparable hybrid model with undesirable outputs (NSH-U) and the nonseparable hybrid Malmquist (NSH-M) productivity index. The results showed the following: (1) The CLUEE differed significantly among regions, with the CLUEE decreasing from the eastern region to the western, northeastern, and central regions. We observed large differences in the CLUEE among provinces. (2) Nonradial input inefficiency and radial output inefficiency were the primary sources of cultivated land use environmental inefficiency. (3) Technical progress was the primary driving force behind the growth of CLUETFP across the entire country and in the eastern, central, western, and northeastern regions; however, technical efficiency limited the growth of CLUETFP to a certain extent. Finally, we proposed policy implications to improve China's CLUEE and CLUETFP.