Users Login
Excellent Articles
More>
-
Measurement, spatial spillover and influencing factors of agricultural carbon emissions efficiency in China
WU Haoyue, HUANG Hanjiao, HE Yu, CHEN Wenkuan
-
Effects of tillage and straw returning method on the distribution of carbon and nitrogen in soil aggregates
ZHANG Yuming, HU Chunsheng, CHEN Suying, WANG Yuying, LI Xiaoxin, DONG Wenxu, LIU Xiuping, PEI Lin, ZHANG Hui
-
Relationship between policy incentives, ecological cognition, and organic fertilizer application by farmers: Based on a moderated mediation model
SANG Xiance, LUO Xiaofeng, HUANG Yanzhong, TANG Lin
-
Spatio-temporal evolution of carbon stocks in the Yellow River Basin based on InVEST and CA-Markov models
YANG Jie, XIE Baopeng, ZHANG Degang
-
Effects of straw returning and fertilization on soil bacterial and fungal community structures and diversities in rice-wheat rotation soil
ZHANG Hanlin, BAI Naling, ZHENG Xianqing, LI Shuangxi, ZHANG Juanqin, ZHANG Haiyun, ZHOU Sheng, SUN Huifeng, LYU Weiguang
QR Code
Official WeChat Account
Online Shopping Journals
Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
Effects of tillage measures and organic manure on soil heavy metal pollution in dryland wheat fields
, Available online ,
doi: 10.12357/cjea.20230431
Abstract:
, Available online ,
doi: 10.12357/cjea.20230414
Abstract:
Display Method:
2023, 31(12): 1873-1882.
doi: 10.12357/cjea.20230408
Abstract:
Biodiversity in rural landscapes plays a critical role in the vitalization and sustainable development of rural regions. We explored a set of methods for identifying biodiversity at different scales and uncovered the mechanisms that drive biodiversity in rural landscapes. We also formulated technical specifications for the maintenance of biodiversity from genes to ecosystems in rural landscapes. In addition, we developed a framework for biodiversity monitoring and warning systems in rural landscapes based on the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual mode. We developed a multiscale full-chain technology for biodiversity identification, maintenance, and warning in rural ecological landscapes. This study yielded powerful insights into the biodiversity maintenance mechanism in rural landscapes by integrating multidisciplinary research methods, such as literature research, field survey, and laboratory analysis, and filled the gap in biodiversity maintenance technology in rural ecological landscape construction. Our study plays a theoretical and practical foundation for the development of rural ecological construction models, planting design and configuration, and species selection for the construction of beautiful villages in China. Furthermore, this multiscale and full-chain technology developed for biodiversity identification, maintenance, and warning in rural ecological landscapes provides key technical support for the dynamic management of rural ecological resources and plays a fundamental role in rural revitalization and the construction of a beautiful China.
Biodiversity in rural landscapes plays a critical role in the vitalization and sustainable development of rural regions. We explored a set of methods for identifying biodiversity at different scales and uncovered the mechanisms that drive biodiversity in rural landscapes. We also formulated technical specifications for the maintenance of biodiversity from genes to ecosystems in rural landscapes. In addition, we developed a framework for biodiversity monitoring and warning systems in rural landscapes based on the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual mode. We developed a multiscale full-chain technology for biodiversity identification, maintenance, and warning in rural ecological landscapes. This study yielded powerful insights into the biodiversity maintenance mechanism in rural landscapes by integrating multidisciplinary research methods, such as literature research, field survey, and laboratory analysis, and filled the gap in biodiversity maintenance technology in rural ecological landscape construction. Our study plays a theoretical and practical foundation for the development of rural ecological construction models, planting design and configuration, and species selection for the construction of beautiful villages in China. Furthermore, this multiscale and full-chain technology developed for biodiversity identification, maintenance, and warning in rural ecological landscapes provides key technical support for the dynamic management of rural ecological resources and plays a fundamental role in rural revitalization and the construction of a beautiful China.
2023, 31(12): 1883-1895.
doi: 10.12357/cjea.20230359
Abstract:
Agricultural intensification has simplified agricultural landscapes through the expansion of agricultural land, enlargement of field size, and removal of non-crop habitats. Rural vegetation is a key component of agricultural landscapes as it produces food, fiber and fuel, and performs ecosystem services, such as recycling of nutrients, regulation of microclimate, and local hydrological processes. Vegetation classification is the basis for surveying, monitoring, and managing rural vegetation. However, to date, green space vegetation, a cultivated vegetation type, has not been listed in the vegetation classification system of China, and little is known about its functional role in the production and regulation of rural landscapes. Here, we reviewed the literatures on different vegetation classifications in China and developed a renewal framework for rural vegetation classification systems. The system includes nine classification units. First, rural vegetation is classified into three vegetation categories: natural and semi-natural vegetation, agricultural vegetation, and green space vegetation (level 0, the highest-level unit). Then, each of the highest-level units is classified into three upper level units (levels 1–3, including the vegetation formation group, vegetation formation, and vegetation subformation), three middle level units (levels 4–6, including the alliance group, alliance, and suballiance), and two lower level units (levels 7–8, including the association group and association). We clarified the division basis and nomenclature for each classification level unit with examples and proposed a reference scheme for the classification and nomenclature of rural vegetation. Following the common classification principle of “plant community ecology”, which is widely used in China, we revised the classification principles and nomenclature based on the functions of the three vegetation categories. Natural and semi-natural vegetation focus on comprehensive ecological conditions and community appearance; agricultural vegetation highlights the functional use, cultivation conditions, and farming system of crops; and green space vegetation focuses on landscape appearance and community assembly. Based on this scheme, rural vegetation in China is classified into three vegetation categories, 23 vegetation formation groups, 66 vegetation formations, and 142 vegetation subformations. Natural and semi-natural vegetation includes 6 vegetation formation groups (Forest, Shrubland, Herbaceous Vegetation, Desert, Alpine Tundra and Sparse Vegetation, and Swamp and Aquatic Vegetation), 30 vegetation formations, and 81 vegetation subformations. Agricultural vegetation includes 13 vegetation formation groups (Food Crop, Vegetable Crop, Fruit Crop, Flower Crop, Oilseed Crop, Fiber Crop, Sugar Crop, Medicine Crop, Beverage Crop, Forage Crop, Tobacco Crop, Spice Crop, and Other Crops), 23 vegetation formations, and 40 vegetation subformations. Green space vegetation includes 4 vegetation formation groups (Arbor Green Space, Shrub Green Space, Herb Green Space, and Wetland Green Space), 13 vegetation formations, and 21 vegetation subformations. This study clarified the definition boundaries of different classification units and illustrated the nomenclature of various types of vegetation in current vegetation classification research. Thus, this study modified some shortcomings in the classification and nomenclature of agricultural vegetation and renewed the vegetation classification system of China by including green space vegetation. The results of this study are beneficial for the protection, management, and spatial planning of rural landscapes.
Agricultural intensification has simplified agricultural landscapes through the expansion of agricultural land, enlargement of field size, and removal of non-crop habitats. Rural vegetation is a key component of agricultural landscapes as it produces food, fiber and fuel, and performs ecosystem services, such as recycling of nutrients, regulation of microclimate, and local hydrological processes. Vegetation classification is the basis for surveying, monitoring, and managing rural vegetation. However, to date, green space vegetation, a cultivated vegetation type, has not been listed in the vegetation classification system of China, and little is known about its functional role in the production and regulation of rural landscapes. Here, we reviewed the literatures on different vegetation classifications in China and developed a renewal framework for rural vegetation classification systems. The system includes nine classification units. First, rural vegetation is classified into three vegetation categories: natural and semi-natural vegetation, agricultural vegetation, and green space vegetation (level 0, the highest-level unit). Then, each of the highest-level units is classified into three upper level units (levels 1–3, including the vegetation formation group, vegetation formation, and vegetation subformation), three middle level units (levels 4–6, including the alliance group, alliance, and suballiance), and two lower level units (levels 7–8, including the association group and association). We clarified the division basis and nomenclature for each classification level unit with examples and proposed a reference scheme for the classification and nomenclature of rural vegetation. Following the common classification principle of “plant community ecology”, which is widely used in China, we revised the classification principles and nomenclature based on the functions of the three vegetation categories. Natural and semi-natural vegetation focus on comprehensive ecological conditions and community appearance; agricultural vegetation highlights the functional use, cultivation conditions, and farming system of crops; and green space vegetation focuses on landscape appearance and community assembly. Based on this scheme, rural vegetation in China is classified into three vegetation categories, 23 vegetation formation groups, 66 vegetation formations, and 142 vegetation subformations. Natural and semi-natural vegetation includes 6 vegetation formation groups (Forest, Shrubland, Herbaceous Vegetation, Desert, Alpine Tundra and Sparse Vegetation, and Swamp and Aquatic Vegetation), 30 vegetation formations, and 81 vegetation subformations. Agricultural vegetation includes 13 vegetation formation groups (Food Crop, Vegetable Crop, Fruit Crop, Flower Crop, Oilseed Crop, Fiber Crop, Sugar Crop, Medicine Crop, Beverage Crop, Forage Crop, Tobacco Crop, Spice Crop, and Other Crops), 23 vegetation formations, and 40 vegetation subformations. Green space vegetation includes 4 vegetation formation groups (Arbor Green Space, Shrub Green Space, Herb Green Space, and Wetland Green Space), 13 vegetation formations, and 21 vegetation subformations. This study clarified the definition boundaries of different classification units and illustrated the nomenclature of various types of vegetation in current vegetation classification research. Thus, this study modified some shortcomings in the classification and nomenclature of agricultural vegetation and renewed the vegetation classification system of China by including green space vegetation. The results of this study are beneficial for the protection, management, and spatial planning of rural landscapes.
2023, 31(12): 1896-1908.
doi: 10.12357/cjea.20230326
Abstract:
The incorporation of rural landscape plants plays a pivotal role in the development and establishment of ecotourism. By studying the genetic diversity of plants in rural landscapes, the richness of genetic variation and the stability of the genetic structure within a population can be revealed. This serves as an important theoretical foundation for the construction of rural ecological landscapes and biodiversity maintenance and is of great significance for the construction of beautiful villages. In this study, eight native landscape species were selected from two ecotourism villages (Changkou Village, Sanming City, Fujian Province; and Paifang Community, Nanjing City, Jiangsu Province). Native rural landscape plant samples were collected from the whole village area. Phenotypic characteristics were measured, and ISSR-PCR experiments were performed. Through analysis of phenotypic features and detection of molecular markers, the Shannon index and Nei’s genetic diversity indexes were calculated to elucidate the levels of genetic diversity of native landscape plant species in different areas. Cluster analysis using phenotypic features identified five types of Liquidambar formosana, six types of Cyclobalanopsis chungii, four types of Quercus glauca, sixteen types of Zelkova serrata, seven types of Toona sinensis, ten types of Aster indicus, five types of Chrysanthemum indicum, and six types of Rubus hirsutus. The phenotypic coefficient variation and Shannon index of the eight native landscape plant species ranged from 0.23 to 0.58, and from 1.51 to 6.74, respectively. In the total area, artificial area and natural area, the Nei’s genetic diversity indexes of the eight native landscape plant species ranged from 0.240 to 0.536, 0.244 to 0.540, and 0.193 to 0.367, respectively. For the eight native landscape plant species, the percentage of polymorphic loci varied from 45.00% to 100.00%, the number of alleles varied from 1.45 to 2.00, and the number of effective alleles varied from 1.30 to 1.64. The results revealed that the phenotypic (Shannon index) and molecular (Nei’s genetic diversity index) genetic diversity levels of the eight native landscape plant species were higher than the average diversity level in numerous other landscape plant species. Additionally, the rural landscape plant species exhibited abundant genetic variation. The genetic diversity of certain rural landscape plant species exhibited a notable degree of variability; however, there were significant differences in the levels of genetic diversity observed between natural and artificial areas. In the context of rural landscape construction, it is important to prioritize the assessment of genetic diversity in rural landscape plant populations. Appropriate measures should be implemented to enhance the even distribution of genetic polymorphisms within the population and preserve the genetic diversity of native landscape plant species. This approach is essential to ensure the long-term stability of rural ecological landscapes.
The incorporation of rural landscape plants plays a pivotal role in the development and establishment of ecotourism. By studying the genetic diversity of plants in rural landscapes, the richness of genetic variation and the stability of the genetic structure within a population can be revealed. This serves as an important theoretical foundation for the construction of rural ecological landscapes and biodiversity maintenance and is of great significance for the construction of beautiful villages. In this study, eight native landscape species were selected from two ecotourism villages (Changkou Village, Sanming City, Fujian Province; and Paifang Community, Nanjing City, Jiangsu Province). Native rural landscape plant samples were collected from the whole village area. Phenotypic characteristics were measured, and ISSR-PCR experiments were performed. Through analysis of phenotypic features and detection of molecular markers, the Shannon index and Nei’s genetic diversity indexes were calculated to elucidate the levels of genetic diversity of native landscape plant species in different areas. Cluster analysis using phenotypic features identified five types of Liquidambar formosana, six types of Cyclobalanopsis chungii, four types of Quercus glauca, sixteen types of Zelkova serrata, seven types of Toona sinensis, ten types of Aster indicus, five types of Chrysanthemum indicum, and six types of Rubus hirsutus. The phenotypic coefficient variation and Shannon index of the eight native landscape plant species ranged from 0.23 to 0.58, and from 1.51 to 6.74, respectively. In the total area, artificial area and natural area, the Nei’s genetic diversity indexes of the eight native landscape plant species ranged from 0.240 to 0.536, 0.244 to 0.540, and 0.193 to 0.367, respectively. For the eight native landscape plant species, the percentage of polymorphic loci varied from 45.00% to 100.00%, the number of alleles varied from 1.45 to 2.00, and the number of effective alleles varied from 1.30 to 1.64. The results revealed that the phenotypic (Shannon index) and molecular (Nei’s genetic diversity index) genetic diversity levels of the eight native landscape plant species were higher than the average diversity level in numerous other landscape plant species. Additionally, the rural landscape plant species exhibited abundant genetic variation. The genetic diversity of certain rural landscape plant species exhibited a notable degree of variability; however, there were significant differences in the levels of genetic diversity observed between natural and artificial areas. In the context of rural landscape construction, it is important to prioritize the assessment of genetic diversity in rural landscape plant populations. Appropriate measures should be implemented to enhance the even distribution of genetic polymorphisms within the population and preserve the genetic diversity of native landscape plant species. This approach is essential to ensure the long-term stability of rural ecological landscapes.
2023, 31(12): 1909-1920.
doi: 10.12357/cjea.20230360
Abstract:
Analyzing rural plant diversity in relation to landscape spatial morphology is necessary to improve rural living environments and maintaining stable rural ecosystems and biodiversity. Fourteen villages in Jiangning District, Nanjing City, Jiangsu Province were selected as experimental areas, and models such as stepwise regression and NMDS-Envfit were used to explore the impact of rural landscape spatial indicators on the α diversity and β diversity of rural plants in the Yangtze River Delta region. Landscape indicators included two-dimensional plane forms, three-dimensional surface features, and four-dimensional historical dynamics. The research conclusions can be summarized as follows: 1) Landscape spatial morphological indicators, such as the percentage of the landscape area covered with semi-natural patches, landscape cohesion index, surface roughness, and patch Euclidean nearest neighbor distance, had relatively significant impact on plant diversity. The patch Euclidean nearest-neighbor distance and patch area significantly and negatively affected the diversity of the arborous layer. Patch fragmentation, higher road density, and higher comprehensive dynamic degree of land use had a negative impact on the α diversity of shrub layer, while the distance from the road obviously affected the α diversity of herbaceous layer. 2) Rural landscape spatial morphological indicators had an impact on plant β diversity. Specifically, in the arborous layer, surface roughness and percentage of landscape area covered with semi-natural patches were the most important influencing factors. In the shrub layer, surface roughness and Shannon diversity index were the most important influencing factors. In the herbaceous layer, patch area and rural road density were the most important influencing factors. 3) Considering the significance of landscape indicators, landscape ecological indicators and three-dimensional surface characteristics had the most significant impact on plant diversity. The main manifestations were the positive correlation between the proportion of semi-natural patch area, patch area, cohesion degree, surface roughness, and plant diversity. The historical dynamics of the four-dimensional landscape had a weak impact on plant diversity, mainly manifesting as a positive correlation with the dynamic degree of semi-natural patches. Two-dimensional landscape indicators based on urban spatial morphology had the weakest impact on plant diversity, mainly manifesting as the negative effects of rural spatial accessibility and road density on plant diversity. Based on the above results, landscape response strategies are proposed to provide guidance for the rural landscape construction process, such as effectively increasing the proportion of semi-natural habitat areas and landscape heterogeneity, comprehensively improving rural landscape cohesion, scientifically maintaining rural high-value woodland landscapes, and fully focusing on rural historical land use. This study provides a reference for the maintenance of biodiversity during rural landscape construction and useful quantitative guidance for rural spatial planning in the Yangtze River Delta region.
Analyzing rural plant diversity in relation to landscape spatial morphology is necessary to improve rural living environments and maintaining stable rural ecosystems and biodiversity. Fourteen villages in Jiangning District, Nanjing City, Jiangsu Province were selected as experimental areas, and models such as stepwise regression and NMDS-Envfit were used to explore the impact of rural landscape spatial indicators on the α diversity and β diversity of rural plants in the Yangtze River Delta region. Landscape indicators included two-dimensional plane forms, three-dimensional surface features, and four-dimensional historical dynamics. The research conclusions can be summarized as follows: 1) Landscape spatial morphological indicators, such as the percentage of the landscape area covered with semi-natural patches, landscape cohesion index, surface roughness, and patch Euclidean nearest neighbor distance, had relatively significant impact on plant diversity. The patch Euclidean nearest-neighbor distance and patch area significantly and negatively affected the diversity of the arborous layer. Patch fragmentation, higher road density, and higher comprehensive dynamic degree of land use had a negative impact on the α diversity of shrub layer, while the distance from the road obviously affected the α diversity of herbaceous layer. 2) Rural landscape spatial morphological indicators had an impact on plant β diversity. Specifically, in the arborous layer, surface roughness and percentage of landscape area covered with semi-natural patches were the most important influencing factors. In the shrub layer, surface roughness and Shannon diversity index were the most important influencing factors. In the herbaceous layer, patch area and rural road density were the most important influencing factors. 3) Considering the significance of landscape indicators, landscape ecological indicators and three-dimensional surface characteristics had the most significant impact on plant diversity. The main manifestations were the positive correlation between the proportion of semi-natural patch area, patch area, cohesion degree, surface roughness, and plant diversity. The historical dynamics of the four-dimensional landscape had a weak impact on plant diversity, mainly manifesting as a positive correlation with the dynamic degree of semi-natural patches. Two-dimensional landscape indicators based on urban spatial morphology had the weakest impact on plant diversity, mainly manifesting as the negative effects of rural spatial accessibility and road density on plant diversity. Based on the above results, landscape response strategies are proposed to provide guidance for the rural landscape construction process, such as effectively increasing the proportion of semi-natural habitat areas and landscape heterogeneity, comprehensively improving rural landscape cohesion, scientifically maintaining rural high-value woodland landscapes, and fully focusing on rural historical land use. This study provides a reference for the maintenance of biodiversity during rural landscape construction and useful quantitative guidance for rural spatial planning in the Yangtze River Delta region.
2023, 31(12): 1921-1931.
doi: 10.12357/cjea.20230378
Abstract:
Plant diversity plays a fundamental role in rural ecological revitalization and sustainable development. Studying the characteristics and influencing factors of rural plant diversity has important theoretical and practical implications for maintaining and enhancing rural biodiversity. In this study, we identified the composition and community types of plant species and explored the effects of natural and human activities in Changkou Village, an ecologically protected village in western Fujian Province. We identified 578 plant species belonging to 130 families and 378 genera, including 396 wild plant species and 53 cultivated agricultural species, exhibiting high plant diversity. Seventeen species of invasive plants have not yet posed a threat to rural biodiversity. The seed plant flora in this rural area was complex, with 14 types of genera, including 188 tropical genera, and showed transitional features from tropical to temperate zones. There were 106 plant vegetation alliances, including 52 natural and semi-natural vegetation, 25 agricultural vegetation, and 29 green space vegetation alliances, which were representative of this region. Natural and semi-natural vegetation were mainly composed of different natural and semi-natural forests, such as the Castanopsis fargesii Forest Alliance and Pinus massoniana + Castanopsis fargesii Forest Alliance, whereas agricultural and green space vegetation areas were very small. Green space vegetation was mainly composed of Cinnamomum camphora and Osmanthus fragrans, and green space tree species predominated in subtropical rural areas. Furthermore, there was a significant positive correlation between the differences in species composition in different rural areas and differences in comprehensive environmental factors. Specifically, the plant species composition of natural and semi-natural vegetation was mainly driven by natural factors, whereas the differences of plant species composition of green space vegetation significantly increased with the increasing distance to roads and residential areas. Overall, these results indicate that ecologically protected rural areas are important reserves for plant diversity and have important maintenance value. The composition of plant species and vegetation alliances completely differs between different vegetation categories in rural areas, and altitude plays a key role. We highlight the necessity of incorporating ecological conservation-oriented rural areas into biodiversity conservation management, and emphasize various maintenance and improvement strategies, such as zoning management of rural plant diversity and building habitat networks. This study could provide useful references for promoting plant diversity in the process of rural revitalization in other regions of China.
Plant diversity plays a fundamental role in rural ecological revitalization and sustainable development. Studying the characteristics and influencing factors of rural plant diversity has important theoretical and practical implications for maintaining and enhancing rural biodiversity. In this study, we identified the composition and community types of plant species and explored the effects of natural and human activities in Changkou Village, an ecologically protected village in western Fujian Province. We identified 578 plant species belonging to 130 families and 378 genera, including 396 wild plant species and 53 cultivated agricultural species, exhibiting high plant diversity. Seventeen species of invasive plants have not yet posed a threat to rural biodiversity. The seed plant flora in this rural area was complex, with 14 types of genera, including 188 tropical genera, and showed transitional features from tropical to temperate zones. There were 106 plant vegetation alliances, including 52 natural and semi-natural vegetation, 25 agricultural vegetation, and 29 green space vegetation alliances, which were representative of this region. Natural and semi-natural vegetation were mainly composed of different natural and semi-natural forests, such as the Castanopsis fargesii Forest Alliance and Pinus massoniana + Castanopsis fargesii Forest Alliance, whereas agricultural and green space vegetation areas were very small. Green space vegetation was mainly composed of Cinnamomum camphora and Osmanthus fragrans, and green space tree species predominated in subtropical rural areas. Furthermore, there was a significant positive correlation between the differences in species composition in different rural areas and differences in comprehensive environmental factors. Specifically, the plant species composition of natural and semi-natural vegetation was mainly driven by natural factors, whereas the differences of plant species composition of green space vegetation significantly increased with the increasing distance to roads and residential areas. Overall, these results indicate that ecologically protected rural areas are important reserves for plant diversity and have important maintenance value. The composition of plant species and vegetation alliances completely differs between different vegetation categories in rural areas, and altitude plays a key role. We highlight the necessity of incorporating ecological conservation-oriented rural areas into biodiversity conservation management, and emphasize various maintenance and improvement strategies, such as zoning management of rural plant diversity and building habitat networks. This study could provide useful references for promoting plant diversity in the process of rural revitalization in other regions of China.
2023, 31(12): 1932-1942.
doi: 10.12357/cjea.20230377
Abstract:
Invasive plants pose a serious threat to plant diversity in rural areas, weaken their ecosystem service functions, and have become a prominent issue that urgently needs to be addressed in rural revitalization and beautiful rural construction. In this study, based on survey data from 127 sampling sites, we aimed to explore the degree of invasion and influencing factors of the invasive plant Solidago canadensis in a leisure-tourism village located in south of the Yangtze River. The height of S. canadensis showed a normal distribution, whereas its coverage showed a significantly positively skewed distribution. In rural areas, it displayed a multipoint scattered distribution pattern, forming a single optimal community locally and exhibiting a trend of further potential dispersal. We also found that the height and coverage of S. canadensis were significantly affected by various factors in rural environments. Specifically, the height of S. canadensis was negatively correlated with the species number and coverage of native plant species in the community, in which the number of native plant species played a more important role. In contrast, the coverage of S. canadensis showed a decreasing trend with increasing distance from the farmland, and the species number and coverage of native plant species. The interaction between the number of native plant species and coverage significantly suppressed the coverage of S. canadensis, and the inhibitory effect of native plant coverage on the coverage of S. canadensis increased with the increase in the number of native plant species in the rural community. In conclusion, leisure-tourism villages have been severely affected by the invasion and spread of S. canadensis. This study also identified the fundamental role of multiple community attributes of native plant species in resisting the invasiveness of single alien plant species and broadened our current understanding of the invasion mechanism of single invasive plants in rural landscapes. These findings emphasize the urgent need to incorporate the monitoring and prevention of invasive plant species into rural ecological landscape planning for the development of leisure tourism in the future, thus providing a solid scientific basis for the comprehensive prevention and control of invasive plants in different rural areas and the maintenance of rural biodiversity during the construction of beautiful rural areas.
Invasive plants pose a serious threat to plant diversity in rural areas, weaken their ecosystem service functions, and have become a prominent issue that urgently needs to be addressed in rural revitalization and beautiful rural construction. In this study, based on survey data from 127 sampling sites, we aimed to explore the degree of invasion and influencing factors of the invasive plant Solidago canadensis in a leisure-tourism village located in south of the Yangtze River. The height of S. canadensis showed a normal distribution, whereas its coverage showed a significantly positively skewed distribution. In rural areas, it displayed a multipoint scattered distribution pattern, forming a single optimal community locally and exhibiting a trend of further potential dispersal. We also found that the height and coverage of S. canadensis were significantly affected by various factors in rural environments. Specifically, the height of S. canadensis was negatively correlated with the species number and coverage of native plant species in the community, in which the number of native plant species played a more important role. In contrast, the coverage of S. canadensis showed a decreasing trend with increasing distance from the farmland, and the species number and coverage of native plant species. The interaction between the number of native plant species and coverage significantly suppressed the coverage of S. canadensis, and the inhibitory effect of native plant coverage on the coverage of S. canadensis increased with the increase in the number of native plant species in the rural community. In conclusion, leisure-tourism villages have been severely affected by the invasion and spread of S. canadensis. This study also identified the fundamental role of multiple community attributes of native plant species in resisting the invasiveness of single alien plant species and broadened our current understanding of the invasion mechanism of single invasive plants in rural landscapes. These findings emphasize the urgent need to incorporate the monitoring and prevention of invasive plant species into rural ecological landscape planning for the development of leisure tourism in the future, thus providing a solid scientific basis for the comprehensive prevention and control of invasive plants in different rural areas and the maintenance of rural biodiversity during the construction of beautiful rural areas.
2023, 31(12): 1943-1952.
doi: 10.12357/cjea.20230622
Abstract:
In view of the potential threats to biodiversity in the process of rural revitalization and the needs of conservation and management, this study organically combined the theories and methods of biodiversity with society, economy, population, etc., and built the early warning index system of biodiversity in rural ecological landscape based on the DPSIR (Driving Force-Pressure-State-Impact-Response) model. Based on the principles of scientificity, relevance, practicality and comparability, the index system reflects the impact of human interference, global change, major disasters, measures and inputs taken by human to maintain the biodiversity of rural ecological landscape, and other factors on rural biodiversity, including 12 factors and 25 indicators of the driving force, pressure, state, impact and response of biodiversity. The mean square deviation method was used to determine the weight value of each index, divide the evaluation level. And the comprehensive index method was used to warn the biodiversity of the rural ecological landscape. The rural biodiversity in this study comprehensively considered the “Ecology, Production, Living” functions of the countryside. Therefore, the species of wild animals and plants, crop species, and rural green plants were all included in the calculation of the biodiversity index. This research method has been applied in the Paifang Community of Nanjing to give early warning to the high risk area. This study provides a new idea and method for biodiversity protection and evaluation in the revitalization and planning of green livable countryside, and it is of great significance to build a beautiful countryside with green harmony.
In view of the potential threats to biodiversity in the process of rural revitalization and the needs of conservation and management, this study organically combined the theories and methods of biodiversity with society, economy, population, etc., and built the early warning index system of biodiversity in rural ecological landscape based on the DPSIR (Driving Force-Pressure-State-Impact-Response) model. Based on the principles of scientificity, relevance, practicality and comparability, the index system reflects the impact of human interference, global change, major disasters, measures and inputs taken by human to maintain the biodiversity of rural ecological landscape, and other factors on rural biodiversity, including 12 factors and 25 indicators of the driving force, pressure, state, impact and response of biodiversity. The mean square deviation method was used to determine the weight value of each index, divide the evaluation level. And the comprehensive index method was used to warn the biodiversity of the rural ecological landscape. The rural biodiversity in this study comprehensively considered the “Ecology, Production, Living” functions of the countryside. Therefore, the species of wild animals and plants, crop species, and rural green plants were all included in the calculation of the biodiversity index. This research method has been applied in the Paifang Community of Nanjing to give early warning to the high risk area. This study provides a new idea and method for biodiversity protection and evaluation in the revitalization and planning of green livable countryside, and it is of great significance to build a beautiful countryside with green harmony.
2023, 31(12): 1953-1962.
doi: 10.12357/cjea.20230270
Abstract:
Farmland ecosystems are essential sources and sinks of antibiotic resistance genes (ARGs), and the application of livestock manure is a major contributor to ARGs in soil. The massive application of livestock manure to vegetable fields has intensified the pollution caused by ARGs in soil. Raw consumption of edible vegetables is one of the most direct ways to introduce ARGs from the soil–plant system to humans, which poses a potential threat to human health. However, few studies have investigated the effects of different fertilizer types on ARGs and bacterial communities in vegetable fields. In this study, 21 soil samples (0–20 cm) were collected from vegetable fields in Hebei Province using different fertilizer types (fresh fowl manure, fresh sheep manure, fresh cattle manure, commercial organic fertilizer, and chemical fertilizer). The distributions and characteristics of ARGs and bacterial communities in vegetable fields were investigated using real-time quantitative polymerase chain reaction (PCR) and high-throughput sequencing techniques. Eight tetracycline resistance genes (tetA, tetC, tetG, tetL, tetO, tetM, tetW, and tetQ), two sulfonamide resistance genes (sul1 and sul2), and one intI1 gene were detected in all vegetable fields. The absolute abundance of sulfonamide resistance genes (9.96×109 copies·g−1 in dry soil) was significantly higher than that of tetracycline resistance genes (1.07×109 copies·g−1 in dry soil). The application of livestock manure and chemical fertilizer both significantly increased the abundance of ARGs in vegetable fields. The highest abundance of ARGs (6.34×109 copies∙g−1 in dry soil) was found in vegetable fields with higher chemical fertilizer amendment, while the lowest abundance of ARGs (3.09×108 copies∙g−1 in dry soil) was found in vegetable soil with commercial organic fertilizer. In addition, the Shannon and Chao1 indices, representing the α diversity of the soil bacterial community, were significantly higher in soil fertilized with livestock manure compared to high-chemical fertilizer application but not in low-chemical fertilization soil, indicating that livestock manure application significantly increased the abundance and diversity of the soil bacterial community. Pearson’s correlation analysis showed that soil bacterial community structure was an important factor influencing the distribution of ARGs. Proteobacteriota, Bacteroidota, Actinobacteriota, and Firmicutes were the dominant potential hosts of ARGs and were significantly correlated with sulfonamide and tetracycline resistance genes (P<0.05). The distribution of ARGs was also affected by soil organic matter and total nitrogen content. The intI1 gene had significant and positive correlations with the sul2, tetG, tetQ, and tetW genes, suggesting its crucial role in ARGs dissemination. In the present study, the use of higher concentrations of chemical fertilizers led to a significantly increased abundance of ARGs in the soil of vegetable fields, whereas the application of commercial organic fertilizers had the least effect on ARGs abundance. This study serves as a guide for evaluating the status of ARGs pollution in vegetable fields with different fertilizer types.
Farmland ecosystems are essential sources and sinks of antibiotic resistance genes (ARGs), and the application of livestock manure is a major contributor to ARGs in soil. The massive application of livestock manure to vegetable fields has intensified the pollution caused by ARGs in soil. Raw consumption of edible vegetables is one of the most direct ways to introduce ARGs from the soil–plant system to humans, which poses a potential threat to human health. However, few studies have investigated the effects of different fertilizer types on ARGs and bacterial communities in vegetable fields. In this study, 21 soil samples (0–20 cm) were collected from vegetable fields in Hebei Province using different fertilizer types (fresh fowl manure, fresh sheep manure, fresh cattle manure, commercial organic fertilizer, and chemical fertilizer). The distributions and characteristics of ARGs and bacterial communities in vegetable fields were investigated using real-time quantitative polymerase chain reaction (PCR) and high-throughput sequencing techniques. Eight tetracycline resistance genes (tetA, tetC, tetG, tetL, tetO, tetM, tetW, and tetQ), two sulfonamide resistance genes (sul1 and sul2), and one intI1 gene were detected in all vegetable fields. The absolute abundance of sulfonamide resistance genes (9.96×109 copies·g−1 in dry soil) was significantly higher than that of tetracycline resistance genes (1.07×109 copies·g−1 in dry soil). The application of livestock manure and chemical fertilizer both significantly increased the abundance of ARGs in vegetable fields. The highest abundance of ARGs (6.34×109 copies∙g−1 in dry soil) was found in vegetable fields with higher chemical fertilizer amendment, while the lowest abundance of ARGs (3.09×108 copies∙g−1 in dry soil) was found in vegetable soil with commercial organic fertilizer. In addition, the Shannon and Chao1 indices, representing the α diversity of the soil bacterial community, were significantly higher in soil fertilized with livestock manure compared to high-chemical fertilizer application but not in low-chemical fertilization soil, indicating that livestock manure application significantly increased the abundance and diversity of the soil bacterial community. Pearson’s correlation analysis showed that soil bacterial community structure was an important factor influencing the distribution of ARGs. Proteobacteriota, Bacteroidota, Actinobacteriota, and Firmicutes were the dominant potential hosts of ARGs and were significantly correlated with sulfonamide and tetracycline resistance genes (P<0.05). The distribution of ARGs was also affected by soil organic matter and total nitrogen content. The intI1 gene had significant and positive correlations with the sul2, tetG, tetQ, and tetW genes, suggesting its crucial role in ARGs dissemination. In the present study, the use of higher concentrations of chemical fertilizers led to a significantly increased abundance of ARGs in the soil of vegetable fields, whereas the application of commercial organic fertilizers had the least effect on ARGs abundance. This study serves as a guide for evaluating the status of ARGs pollution in vegetable fields with different fertilizer types.
2023, 31(12): 1963-1975.
doi: 10.12357/cjea.20230395
Abstract:
Although the expansion of agricultural land and intensive production have contributed to increased food production, the resulting high-intensity human disturbances and excessive use of agrochemicals have caused significant environmental damage. This has led to the loss of biodiversity and degradation of ecosystem services, ultimately posing threats to both sustainable food production and human health. Therefore, it is crucial to develop sustainable production management strategies. Organic production at the field scale and the establishment of flowering boundaries are considered efficient measures for biodiversity and ecosystem services. However, few studies have investigated whether organic practices and flowering boundaries can effectively increase the natural enemies of arthropods and improve the control of pests in cultivated fields, particularly in paddy planting systems. In this study, we aimed to fill this knowledge gap by investigating the distribution and diversity of natural enemies and pests of arthropods in paddy fields and their field margins, and how vegetation on the field margin affect diversities of natural enemies and pests of arthropods in paddy fields. The following three treatments were established: conventional paddy fields with traditional field margins (Con), organic paddy fields with traditional field margins (Org), and organic paddy fields with flowering boundaries (OrgF). Arthropods were sampled at the field margins and in paddy fields 5 and 20 m away from the margin using a suction sampler. Vegetation coverage and diversity in the field margins were also investigated. The results are as follows: 1) a total of 9531 arthropods belonging to 50 families were caught, with 2653 individuals identified as natural enemies from 28 families (including 2253 individual spiders belonging to 14 families and 41 species), and a total of 3971 individual pests representing 18 families (dominated by Cicadellidae, accounting for 84.01% of the total pests). 2) The richness of the natural enemies in Org was greater than that in Con. The richness of natural enemies in OrgF was higher than that in Con and Org, and the abundance of natural enemies in OrgF was higher than that in Con. 3) In OrgF, the abundance and richness of natural enemies at different distances between the boundary of the paddy field and the interior of the paddy field were significantly different, with a greater richness of natural enemies in the paddy field 5 m away from the field margin than at 20 m. Furthermore, the abundance of natural enemies was significantly lower at the field margins than in paddy fields 5 m away from the boundary. 4) The richness and abundance of natural enemies and pests in paddy fields and their boundaries were positively correlated with vegetation coverage at the paddy field boundary. 5) The ratio of enemies to pests was the highest in the conventional paddy fields (Con), as most pests might be killed by broad-spectrum insecticides, followed by Org and OrgF, which had a large number of pests with only targeted bio-pesticides being used. In conclusion, organic practices in the fields and the flowering boundaries can effectively help to maintain arthropod diversity and increase the diversity of natural enemies in paddy fields. However, to effectively control pests and improve biological control services, an in-depth understanding of the plant-arthropod relationship and careful selection of the “correct” plant diversity are required.
Although the expansion of agricultural land and intensive production have contributed to increased food production, the resulting high-intensity human disturbances and excessive use of agrochemicals have caused significant environmental damage. This has led to the loss of biodiversity and degradation of ecosystem services, ultimately posing threats to both sustainable food production and human health. Therefore, it is crucial to develop sustainable production management strategies. Organic production at the field scale and the establishment of flowering boundaries are considered efficient measures for biodiversity and ecosystem services. However, few studies have investigated whether organic practices and flowering boundaries can effectively increase the natural enemies of arthropods and improve the control of pests in cultivated fields, particularly in paddy planting systems. In this study, we aimed to fill this knowledge gap by investigating the distribution and diversity of natural enemies and pests of arthropods in paddy fields and their field margins, and how vegetation on the field margin affect diversities of natural enemies and pests of arthropods in paddy fields. The following three treatments were established: conventional paddy fields with traditional field margins (Con), organic paddy fields with traditional field margins (Org), and organic paddy fields with flowering boundaries (OrgF). Arthropods were sampled at the field margins and in paddy fields 5 and 20 m away from the margin using a suction sampler. Vegetation coverage and diversity in the field margins were also investigated. The results are as follows: 1) a total of 9531 arthropods belonging to 50 families were caught, with 2653 individuals identified as natural enemies from 28 families (including 2253 individual spiders belonging to 14 families and 41 species), and a total of 3971 individual pests representing 18 families (dominated by Cicadellidae, accounting for 84.01% of the total pests). 2) The richness of the natural enemies in Org was greater than that in Con. The richness of natural enemies in OrgF was higher than that in Con and Org, and the abundance of natural enemies in OrgF was higher than that in Con. 3) In OrgF, the abundance and richness of natural enemies at different distances between the boundary of the paddy field and the interior of the paddy field were significantly different, with a greater richness of natural enemies in the paddy field 5 m away from the field margin than at 20 m. Furthermore, the abundance of natural enemies was significantly lower at the field margins than in paddy fields 5 m away from the boundary. 4) The richness and abundance of natural enemies and pests in paddy fields and their boundaries were positively correlated with vegetation coverage at the paddy field boundary. 5) The ratio of enemies to pests was the highest in the conventional paddy fields (Con), as most pests might be killed by broad-spectrum insecticides, followed by Org and OrgF, which had a large number of pests with only targeted bio-pesticides being used. In conclusion, organic practices in the fields and the flowering boundaries can effectively help to maintain arthropod diversity and increase the diversity of natural enemies in paddy fields. However, to effectively control pests and improve biological control services, an in-depth understanding of the plant-arthropod relationship and careful selection of the “correct” plant diversity are required.
2023, 31(12): 1976-1983.
doi: 10.12357/cjea.20230323
Abstract:
Global warming is becoming increasingly serious, and the complicated climate change situation has led to obvious changes in global snow cover patterns. Therefore, we explored the effects of future climate warming on the physical and chemical properties of black soil in Northeast China. This study adopted the method of artificial snow depth control from November 2020 to May 2022 and divided the plots in the test area into three treatment groups: snow increase (TS), snow removal (TR), and control (C). Soil environmental factors, available carbon and nitrogen contents, microbial biomass, urease activity, and sucrase activity were determined. The seasonal dynamic change process of each index was analyzed. Long-term field experiments showed that snow removal significantly reduced soil temperature and humidity. In addition, lower soil temperature and humidity accelerated the release of soil nutrients, and significantly increased the contents of soil nitrate nitrogen and ammonium nitrogen in early winter, while the opposite was true with snow increase treatment. However, from the beginning of the deep snow period, the snow removal treatment caused a loss of soil inorganic nitrogen to a certain extent while increased contents of soluble organic carbon and nitrogen. The snow removal treatment maintained soil microbial activity at a high level for most of the winter. However, at the end of winter, owing to the rapid release of soluble organic matter under snow treatment, soil microorganisms under snow treatment absorbed a large amount of nutrients and exist in a more suitable soil environment, which significantly increases the soil microbial activity under the snow treatment. However, owing to the loss of heat insulation from snow cover, a large number of microorganisms decomposed and died at this time, which significantly reduced soil microbial activity. Before and after the test period, snow treatment significantly increased the soil microbial activity by 23.07 mg∙kg−1, and snow removal treatment significantly increased the soil microbial activity by 11.92 mg∙kg−1, with a difference of 93.5%. The decrease in snow cover significantly decreased the activities of soil urease and sucrase during most of the winter, and the activities of soil urease and sucrase were significantly increased by snow treatment. These results show that the activities of these two enzymes increased significantly by more than 10.5%. In summary, this study demonstrated that changes in snow cover in the future will lead to changes in the dynamic change characteristics of soil available carbon and nitrogen and microbial activity, and the influence of snow cover change on soil enzyme activity will also indirectly affect the soil nutrient cycling process and physical and chemical properties of soil. The results of this study provide a theoretical foundation and scientific basis for further research on the material cycle of terrestrial ecosystems in the black soil region of northeast China in the context of climate warming.
Global warming is becoming increasingly serious, and the complicated climate change situation has led to obvious changes in global snow cover patterns. Therefore, we explored the effects of future climate warming on the physical and chemical properties of black soil in Northeast China. This study adopted the method of artificial snow depth control from November 2020 to May 2022 and divided the plots in the test area into three treatment groups: snow increase (TS), snow removal (TR), and control (C). Soil environmental factors, available carbon and nitrogen contents, microbial biomass, urease activity, and sucrase activity were determined. The seasonal dynamic change process of each index was analyzed. Long-term field experiments showed that snow removal significantly reduced soil temperature and humidity. In addition, lower soil temperature and humidity accelerated the release of soil nutrients, and significantly increased the contents of soil nitrate nitrogen and ammonium nitrogen in early winter, while the opposite was true with snow increase treatment. However, from the beginning of the deep snow period, the snow removal treatment caused a loss of soil inorganic nitrogen to a certain extent while increased contents of soluble organic carbon and nitrogen. The snow removal treatment maintained soil microbial activity at a high level for most of the winter. However, at the end of winter, owing to the rapid release of soluble organic matter under snow treatment, soil microorganisms under snow treatment absorbed a large amount of nutrients and exist in a more suitable soil environment, which significantly increases the soil microbial activity under the snow treatment. However, owing to the loss of heat insulation from snow cover, a large number of microorganisms decomposed and died at this time, which significantly reduced soil microbial activity. Before and after the test period, snow treatment significantly increased the soil microbial activity by 23.07 mg∙kg−1, and snow removal treatment significantly increased the soil microbial activity by 11.92 mg∙kg−1, with a difference of 93.5%. The decrease in snow cover significantly decreased the activities of soil urease and sucrase during most of the winter, and the activities of soil urease and sucrase were significantly increased by snow treatment. These results show that the activities of these two enzymes increased significantly by more than 10.5%. In summary, this study demonstrated that changes in snow cover in the future will lead to changes in the dynamic change characteristics of soil available carbon and nitrogen and microbial activity, and the influence of snow cover change on soil enzyme activity will also indirectly affect the soil nutrient cycling process and physical and chemical properties of soil. The results of this study provide a theoretical foundation and scientific basis for further research on the material cycle of terrestrial ecosystems in the black soil region of northeast China in the context of climate warming.
2023, 31(12): 1984-1996.
doi: 10.12357/cjea.20230283
Abstract:
Energy is a major component in enhancing agricultural productivity. Accounting for energy efficiency at the production stage of crop is essential for achieving sustainable agriculture. Due to the high level of production and consumption of oil in China, it is of great importance to pay attention to energy consumption and its negatively environmental impacts in the oil production process. Measures of optimizing energy utilization structure, reducing excessive and ineffective energy consumption and improving energy utilization efficiency can be used, in order to increase income, save cost and reduce greenhouse gas emissions synthetically. Academically, a large number of previous studies have contributed to energy use and environmental impacts in the production of oil crops, fruits, vegetables, and food crops on various scales. However, there is a lack of studies related to energy use efficiency and greenhouse gas emissions in oil production which concentrate in major oil crops production areas nationally so far. Generally, in terms of models used in relevant study areas, methods including life cycle assessment (LCA), data envelopment analysis (DEA), process analysis, energy analysis have been used commonly, which provide valuable references to the present study. Given that oil crops production is inherently a life process, this paper combined LCA+DEA methods to estimate the energy utilization efficiency and greenhouse gas emissions of oil crops, which helped to rank efficient and inefficient provincial production units. In further, the underlying reasons which caused inefficient energy use were deeply identified in different provinces. Additionally, for purpose of practical application, this paper explored the possibility and potential of energy saving and GHG emission reduction in each province. The results showed as follows. 1) There was no significant difference in the output capacity per unit energy consumption among the three studied oil crop systems. However, the energy use efficiency of three oil crops displayed remarkably differently, which showed peanut > oilseed rape > soybean. 2) Among the three oil crops, peanut had the highest GHG emissions [874.96 kg(CO2 eq)∙hm−2], followed by oilseed rape [660.16 kg(CO2 eq)∙hm−2] and soybean [507.07 kg(CO2 eq)∙hm−2]. In addition, the contributions of substantiality inputs and agricultural operations to GHG emissions varied greatly from different oil crops. Specifically, the significant GHG emission source of oilseed rape and peanut was fertilizer. Nevertheless, contribution of fertilizer, diesel fuel and irrigation to the GHG emissions of soybean showed less difference. 3) There was great potential for energy utilization optimization and GHG emission reduction. Estimates resulted from this study displayed that about 11.97%, 16.38% and 15.89% of resources invested to oilseed rape, soybean and peanut in inefficient provinces could be saved respectively, which were capable of reducing 20.60−616.32 kg(CO2 eq)∙hm−2 GHG emissions as well. Therefore, it is necessary to optimize the energy utilization structure of low efficiency areas according to the actual situation, and explore the production mode of double optimal yield and carbon emissions. This will play an important role in saving money and increasing income for regional oilseed cultivation, as well as green development.
Energy is a major component in enhancing agricultural productivity. Accounting for energy efficiency at the production stage of crop is essential for achieving sustainable agriculture. Due to the high level of production and consumption of oil in China, it is of great importance to pay attention to energy consumption and its negatively environmental impacts in the oil production process. Measures of optimizing energy utilization structure, reducing excessive and ineffective energy consumption and improving energy utilization efficiency can be used, in order to increase income, save cost and reduce greenhouse gas emissions synthetically. Academically, a large number of previous studies have contributed to energy use and environmental impacts in the production of oil crops, fruits, vegetables, and food crops on various scales. However, there is a lack of studies related to energy use efficiency and greenhouse gas emissions in oil production which concentrate in major oil crops production areas nationally so far. Generally, in terms of models used in relevant study areas, methods including life cycle assessment (LCA), data envelopment analysis (DEA), process analysis, energy analysis have been used commonly, which provide valuable references to the present study. Given that oil crops production is inherently a life process, this paper combined LCA+DEA methods to estimate the energy utilization efficiency and greenhouse gas emissions of oil crops, which helped to rank efficient and inefficient provincial production units. In further, the underlying reasons which caused inefficient energy use were deeply identified in different provinces. Additionally, for purpose of practical application, this paper explored the possibility and potential of energy saving and GHG emission reduction in each province. The results showed as follows. 1) There was no significant difference in the output capacity per unit energy consumption among the three studied oil crop systems. However, the energy use efficiency of three oil crops displayed remarkably differently, which showed peanut > oilseed rape > soybean. 2) Among the three oil crops, peanut had the highest GHG emissions [874.96 kg(CO2 eq)∙hm−2], followed by oilseed rape [660.16 kg(CO2 eq)∙hm−2] and soybean [507.07 kg(CO2 eq)∙hm−2]. In addition, the contributions of substantiality inputs and agricultural operations to GHG emissions varied greatly from different oil crops. Specifically, the significant GHG emission source of oilseed rape and peanut was fertilizer. Nevertheless, contribution of fertilizer, diesel fuel and irrigation to the GHG emissions of soybean showed less difference. 3) There was great potential for energy utilization optimization and GHG emission reduction. Estimates resulted from this study displayed that about 11.97%, 16.38% and 15.89% of resources invested to oilseed rape, soybean and peanut in inefficient provinces could be saved respectively, which were capable of reducing 20.60−616.32 kg(CO2 eq)∙hm−2 GHG emissions as well. Therefore, it is necessary to optimize the energy utilization structure of low efficiency areas according to the actual situation, and explore the production mode of double optimal yield and carbon emissions. This will play an important role in saving money and increasing income for regional oilseed cultivation, as well as green development.
2023, 31(12): 1997-2010.
doi: 10.12357/cjea.20230229
Abstract:
To quantitatively analyze the impact of foliar Se application on grain yield, quality, and Se accumulation in winter wheat in China, 41 published studies (36 in Chinese and 5 in English) with a total of 379 pairs of samples were collected. A Meta-analysis was used to comprehensively analyze the effects of foliar Se application on the yield, grain protein, and Se content of winter wheat, and a subgroup analysis was used to evaluate the effects of different factors on response of winter wheat to foliar Se application, with no Se application as the control group and foliar Se application as the experimental group. The results showed that compared with no Se application, the yield, grain protein, and Se contents of winter wheat were increased by foliar Se application, with incremental rates of 3.80%, 2.44%, and 764.56%, respectively. In terms of the different regions, the effect of foliar Se application on yield and quality improvement was greater in the east and south than in the west and north, respectively. Overall, the effect of grain Se enrichment gradually decreased from west to east. In terms of foliar Se application management factors, it was most worthwhile to apply 15−60 g·hm−2 once at the early filling stage or twice at the boot stage and early filling stage, which would meet the standard of Se enrichment and human needs. Soil fertility was an important factor influencing the effect of foliar Se application on the yield and quality of winter wheat. Soil contents of Se and total N had a significant effect on yield-increasing effect of foliar Se application. The effect of foliar Se application on yield improvement was the highest when the Se content of soil was between 0.2–0.4 mg·kg−1. The effect of foliar Se application on winter wheat yield decreased with increasing total soil N. Soil Se, total N, available P, and available K contents significantly affected the effects of foliar Se application on protein content. The effect of foliar Se application on grain protein was higher when the soil Se content was between 0.2−0.4 mg·kg−1, total N>1.5 g·kg−1, available P>20 mg·kg−1, and available K=100−200 mg·kg−1. Soil fertility (soil Se content, organic matter content, and available K content) was the main factor affecting Se accumulation in grain when Se fertilizer was applied to the foliar. When the soil organic matter and available K contents were enhanced, foliar Se application had significantly increased the Se accumulation; however, the effect of Se accumulation caused by foliar Se application was high in Se-poor soil (<0.2 mg·kg−1). Therefore, foliar Se application measures and soil conditions for optimization in different regions not only synergistically achieve the goals of high yields, good quality, and Se accumulation standards of wheat, but also reduce environmental contamination, which provides support for sustainable wheat production management with Se enrichment.
To quantitatively analyze the impact of foliar Se application on grain yield, quality, and Se accumulation in winter wheat in China, 41 published studies (36 in Chinese and 5 in English) with a total of 379 pairs of samples were collected. A Meta-analysis was used to comprehensively analyze the effects of foliar Se application on the yield, grain protein, and Se content of winter wheat, and a subgroup analysis was used to evaluate the effects of different factors on response of winter wheat to foliar Se application, with no Se application as the control group and foliar Se application as the experimental group. The results showed that compared with no Se application, the yield, grain protein, and Se contents of winter wheat were increased by foliar Se application, with incremental rates of 3.80%, 2.44%, and 764.56%, respectively. In terms of the different regions, the effect of foliar Se application on yield and quality improvement was greater in the east and south than in the west and north, respectively. Overall, the effect of grain Se enrichment gradually decreased from west to east. In terms of foliar Se application management factors, it was most worthwhile to apply 15−60 g·hm−2 once at the early filling stage or twice at the boot stage and early filling stage, which would meet the standard of Se enrichment and human needs. Soil fertility was an important factor influencing the effect of foliar Se application on the yield and quality of winter wheat. Soil contents of Se and total N had a significant effect on yield-increasing effect of foliar Se application. The effect of foliar Se application on yield improvement was the highest when the Se content of soil was between 0.2–0.4 mg·kg−1. The effect of foliar Se application on winter wheat yield decreased with increasing total soil N. Soil Se, total N, available P, and available K contents significantly affected the effects of foliar Se application on protein content. The effect of foliar Se application on grain protein was higher when the soil Se content was between 0.2−0.4 mg·kg−1, total N>1.5 g·kg−1, available P>20 mg·kg−1, and available K=100−200 mg·kg−1. Soil fertility (soil Se content, organic matter content, and available K content) was the main factor affecting Se accumulation in grain when Se fertilizer was applied to the foliar. When the soil organic matter and available K contents were enhanced, foliar Se application had significantly increased the Se accumulation; however, the effect of Se accumulation caused by foliar Se application was high in Se-poor soil (<0.2 mg·kg−1). Therefore, foliar Se application measures and soil conditions for optimization in different regions not only synergistically achieve the goals of high yields, good quality, and Se accumulation standards of wheat, but also reduce environmental contamination, which provides support for sustainable wheat production management with Se enrichment.
2023, 31(12): 2011-2021.
doi: 10.12357/cjea.20230172
Abstract:
The Taihang Mountain Region is the ecological barrier and water source of North China Plain. In recent decades, with the implementation of Taihang Mountains Greening Project and other projects, the vegetation coverage in Taihang Mountain Region is recovering continuously, but the runoff in the mountains is rapidly declining. The mechanism of how the vegetation restoration affects the water yield is not clear. The process of rainfall partitioning is an important part of hydrological cycle. It is of great significance for the formation process of regional water yield and water resources. Pinus tabulaeformis is the main afforestation tree species in Taihang Mountain Region, and it affects regional water resources. The rainfall partitioning of P. tabulaeformis forest in Taihang Mountain Region remains poorly understood. It is required to assess the applicability of the revised Gash model and revised Liu model. In this study, the rainfall partitioning in P. tabulaeformis forest is examined from July to November of 2022. The canopy interception was simulated by revised Gash model and revised Liu model. The results showed that 1) the rainfall amount was 450.8 mm during the study period, the average rainfall duration was 10.4 h, and the average rainfall intensity was 2.7 mm∙h−1. Furthermore, we found that the rainfall during the study period was mainly light rain. The canopy interception, throughfall and stemflow of P. tabulaeformis forest were 105.5, 338.2 and 7.1 mm, respectively, accounting for 23.4%, 75.0% and 1.6% of the rainfall amount. 2) Throughfall and stemflow began to occur when the rainfall amount reached 1.7 and 5.5 mm, respectively. Significant linear relationships were found between the rainfall amount and throughfall amount. However, the relationship between rainfall amount and interception followed a power function. The throughfall percentage increased quickly with increasing rainfall amount, but when rainfall amount reached 11 mm, the throughfall percentage increased slowly. The interception percentage firstly decreased and then stabilized with increasing rainfall amount. 3) Based on the revised Gash model, the canopy interception, throughfall, and stemflow were calculated to be 105.3, 340.7, and 4.6 mm, respectively. The relative errors between the measured and simulated values were 0.2%, 0.8%, and 34.7%. According to the revised Gash model simulation results, we found that the interception amount was dominated by canopy evaporation during rainfall, accounting for 55.0% of the interception simulation, followed by evaporation after cessation of rainfall, accounting for 27.8% of the interception simulation. The revised Liu model calculated the interception as 96.0 mm, with a relative error of 9.0% between the measured and simulated values. The revised Gash model had lower relative errors in the simulation than the Liu model. 4) Sensitivity of the revised Gash model parameters were mean evapotranspiration rate > mean rainfall intensity > canopy storage capacity > canopy cover > trunk storage capacity > stemflow coefficient. These results indicate that typical P. tabulaeformis forests in the Taihang Mountains can intercept 23.4% of rainfall, with 75.0% throughfall and 1.6% stemflow. The revised Gash model can be used to predict canopy interception in P. tabulaeformis forests and provides a theoretical basis for water resource assessment and water conservation capacity improvement in mountainous areas.
The Taihang Mountain Region is the ecological barrier and water source of North China Plain. In recent decades, with the implementation of Taihang Mountains Greening Project and other projects, the vegetation coverage in Taihang Mountain Region is recovering continuously, but the runoff in the mountains is rapidly declining. The mechanism of how the vegetation restoration affects the water yield is not clear. The process of rainfall partitioning is an important part of hydrological cycle. It is of great significance for the formation process of regional water yield and water resources. Pinus tabulaeformis is the main afforestation tree species in Taihang Mountain Region, and it affects regional water resources. The rainfall partitioning of P. tabulaeformis forest in Taihang Mountain Region remains poorly understood. It is required to assess the applicability of the revised Gash model and revised Liu model. In this study, the rainfall partitioning in P. tabulaeformis forest is examined from July to November of 2022. The canopy interception was simulated by revised Gash model and revised Liu model. The results showed that 1) the rainfall amount was 450.8 mm during the study period, the average rainfall duration was 10.4 h, and the average rainfall intensity was 2.7 mm∙h−1. Furthermore, we found that the rainfall during the study period was mainly light rain. The canopy interception, throughfall and stemflow of P. tabulaeformis forest were 105.5, 338.2 and 7.1 mm, respectively, accounting for 23.4%, 75.0% and 1.6% of the rainfall amount. 2) Throughfall and stemflow began to occur when the rainfall amount reached 1.7 and 5.5 mm, respectively. Significant linear relationships were found between the rainfall amount and throughfall amount. However, the relationship between rainfall amount and interception followed a power function. The throughfall percentage increased quickly with increasing rainfall amount, but when rainfall amount reached 11 mm, the throughfall percentage increased slowly. The interception percentage firstly decreased and then stabilized with increasing rainfall amount. 3) Based on the revised Gash model, the canopy interception, throughfall, and stemflow were calculated to be 105.3, 340.7, and 4.6 mm, respectively. The relative errors between the measured and simulated values were 0.2%, 0.8%, and 34.7%. According to the revised Gash model simulation results, we found that the interception amount was dominated by canopy evaporation during rainfall, accounting for 55.0% of the interception simulation, followed by evaporation after cessation of rainfall, accounting for 27.8% of the interception simulation. The revised Liu model calculated the interception as 96.0 mm, with a relative error of 9.0% between the measured and simulated values. The revised Gash model had lower relative errors in the simulation than the Liu model. 4) Sensitivity of the revised Gash model parameters were mean evapotranspiration rate > mean rainfall intensity > canopy storage capacity > canopy cover > trunk storage capacity > stemflow coefficient. These results indicate that typical P. tabulaeformis forests in the Taihang Mountains can intercept 23.4% of rainfall, with 75.0% throughfall and 1.6% stemflow. The revised Gash model can be used to predict canopy interception in P. tabulaeformis forests and provides a theoretical basis for water resource assessment and water conservation capacity improvement in mountainous areas.
2023, 31(12): 2022-2032.
doi: 10.12357/cjea.20230353
Abstract:
Under the carbon emission pattern of “carbon peak and carbon neutral”, agricultural carbon emissions, as one of the main sources of greenhouse gases, have become a key area for emission reduction. High-standard farmland construction is an important measure for promoting green, low-carbon, and high-quality agricultural development. An in-depth investigation of the effects and mechanisms of high-standard farmland construction policies on agricultural carbon emissions can provide an empirical basis for optimizing policy formulation and reducing agricultural carbon emissions. This is of great significance in promoting the development of low-carbon agriculture. Based on the theories of scale economy and division of labor, this study constructed a theoretical model of “high-standard farmland construction-agrochemical input intensity/socialized service-agricultural carbon emission”. Based on panel data from 30 provinces in China from 2007 to 2017, this study analyzed the effect and mechanism of the high-standard farmland construction policy on agricultural carbon emissions using a continuous differences-in-differences approach (DID) and mediation effect model. By measuring the agricultural carbon emissions of each province, this study found that national agricultural carbon emissions showed an inverted U-shaped trend, rising at the beginning, then declining, and peaking in 2015. Regions such as Henan, Shandong, Hebei, Jiangsu, and Anhui are at the forefront of agricultural carbon emissions nationwide, whereas regions such as Beijing, Shanghai, Tianjin, Hebei, and Shandong have higher rates of agricultural carbon emission reduction. The dynamic estimation results showed that the carbon reduction of the high-standard farmland construction policy had a lag effect, and the carbon reduction effect appeared in 2013 and continued to increase gradually. The results of the benchmark regression showed that a high-standard farmland construction policy significantly suppressed agricultural carbon emissions. On average, when all other conditions remained unchanged, implementing a high-standard farmland construction policy reduced agricultural carbon emissions significantly, i.e., by 10.1%. Robustness tests were conducted using the approach of substituting variables and considering the interference of other relevant policies. The results confirmed the positive effect of the high-standard farmland construction policy on reducing agricultural carbon emissions. The results of the mechanism analysis showed that agricultural chemical input intensity and agricultural socialized services played mediating roles in reducing agricultural carbon emissions through the construction of high-standard farmland. The construction of high-standard farmlands suppressed agricultural carbon emissions, mainly by reducing agricultural chemical input intensity and improving agricultural socialized services. Heterogeneity analysis revealed that the carbon reduction effect of the high-standard farmland construction policy mainly occurred in provinces with a high degree of land transfer and in non-food-producing areas. In contrast, it did not have a corresponding carbon reduction effect in provinces with a low degree of land transfer and in food-producing areas. Therefore, the government should strengthen the construction of high-standard farmlands and differentiate the implementation of high-standard farmland construction policies according to local conditions and classifications to give full play to the emission reduction effect. In addition, the government should pay great attention to the role of agricultural chemicalization and socialized agricultural services in carbon reduction effects.
Under the carbon emission pattern of “carbon peak and carbon neutral”, agricultural carbon emissions, as one of the main sources of greenhouse gases, have become a key area for emission reduction. High-standard farmland construction is an important measure for promoting green, low-carbon, and high-quality agricultural development. An in-depth investigation of the effects and mechanisms of high-standard farmland construction policies on agricultural carbon emissions can provide an empirical basis for optimizing policy formulation and reducing agricultural carbon emissions. This is of great significance in promoting the development of low-carbon agriculture. Based on the theories of scale economy and division of labor, this study constructed a theoretical model of “high-standard farmland construction-agrochemical input intensity/socialized service-agricultural carbon emission”. Based on panel data from 30 provinces in China from 2007 to 2017, this study analyzed the effect and mechanism of the high-standard farmland construction policy on agricultural carbon emissions using a continuous differences-in-differences approach (DID) and mediation effect model. By measuring the agricultural carbon emissions of each province, this study found that national agricultural carbon emissions showed an inverted U-shaped trend, rising at the beginning, then declining, and peaking in 2015. Regions such as Henan, Shandong, Hebei, Jiangsu, and Anhui are at the forefront of agricultural carbon emissions nationwide, whereas regions such as Beijing, Shanghai, Tianjin, Hebei, and Shandong have higher rates of agricultural carbon emission reduction. The dynamic estimation results showed that the carbon reduction of the high-standard farmland construction policy had a lag effect, and the carbon reduction effect appeared in 2013 and continued to increase gradually. The results of the benchmark regression showed that a high-standard farmland construction policy significantly suppressed agricultural carbon emissions. On average, when all other conditions remained unchanged, implementing a high-standard farmland construction policy reduced agricultural carbon emissions significantly, i.e., by 10.1%. Robustness tests were conducted using the approach of substituting variables and considering the interference of other relevant policies. The results confirmed the positive effect of the high-standard farmland construction policy on reducing agricultural carbon emissions. The results of the mechanism analysis showed that agricultural chemical input intensity and agricultural socialized services played mediating roles in reducing agricultural carbon emissions through the construction of high-standard farmland. The construction of high-standard farmlands suppressed agricultural carbon emissions, mainly by reducing agricultural chemical input intensity and improving agricultural socialized services. Heterogeneity analysis revealed that the carbon reduction effect of the high-standard farmland construction policy mainly occurred in provinces with a high degree of land transfer and in non-food-producing areas. In contrast, it did not have a corresponding carbon reduction effect in provinces with a low degree of land transfer and in food-producing areas. Therefore, the government should strengthen the construction of high-standard farmlands and differentiate the implementation of high-standard farmland construction policies according to local conditions and classifications to give full play to the emission reduction effect. In addition, the government should pay great attention to the role of agricultural chemicalization and socialized agricultural services in carbon reduction effects.
2023, 31(12): 2033-2043.
doi: 10.12357/cjea.20230301
Abstract:
Continuously promoting scientific fertilization is a powerful support for achieving a stable food supply and constructing an ecological civilization. To explore the effective strategies to promote scientific fertilization by Chinese farmers in the context of digital village construction, this study uses the Heckman two-stage model based on the data from 1256 surveys of farmers in the rice producing areas of Hubei Province to explore the influence of informatization of agricultural extension services on the adoption decision of scientific fertilization technology by farmers in terms of “adoption behavior” and “the degree of adoption”. Additionally, we analyzed the mechanism of informatization of agricultural extension services on scientific fertilization technology adoption decision by farmers using the stepwise regression method. The results are presented as follows: 1) The informatization of agricultural extension services had a significant positive effect on adoption behavior of farmers and the degree of adoption of scientific fertilization technologies. 2) There are differences in the effects of informatization of agricultural extension services on different types of scientific fertilization technologies. The informatization of agricultural extension services had a more significant effect on the adoption of efficient fertilization technologies by farmers than the application of new fertilizers. 3) The informatization of agricultural extension services promoted adoption behavior of farmers by improving benefit perception; it also promoted the adoption behavior of farmers and the degree of their adoption by reducing risk perception. Consequently, this study proposes policy recommendations to continuously enrich the forms and service contents of information-based agricultural extension services, improve the cooperative extension mechanism, and enhance the effectiveness of agricultural extension services through personalization and precision.
Continuously promoting scientific fertilization is a powerful support for achieving a stable food supply and constructing an ecological civilization. To explore the effective strategies to promote scientific fertilization by Chinese farmers in the context of digital village construction, this study uses the Heckman two-stage model based on the data from 1256 surveys of farmers in the rice producing areas of Hubei Province to explore the influence of informatization of agricultural extension services on the adoption decision of scientific fertilization technology by farmers in terms of “adoption behavior” and “the degree of adoption”. Additionally, we analyzed the mechanism of informatization of agricultural extension services on scientific fertilization technology adoption decision by farmers using the stepwise regression method. The results are presented as follows: 1) The informatization of agricultural extension services had a significant positive effect on adoption behavior of farmers and the degree of adoption of scientific fertilization technologies. 2) There are differences in the effects of informatization of agricultural extension services on different types of scientific fertilization technologies. The informatization of agricultural extension services had a more significant effect on the adoption of efficient fertilization technologies by farmers than the application of new fertilizers. 3) The informatization of agricultural extension services promoted adoption behavior of farmers by improving benefit perception; it also promoted the adoption behavior of farmers and the degree of their adoption by reducing risk perception. Consequently, this study proposes policy recommendations to continuously enrich the forms and service contents of information-based agricultural extension services, improve the cooperative extension mechanism, and enhance the effectiveness of agricultural extension services through personalization and precision.
Editor-in-chief：LIU Changming
Competent Authorities：Chinese Academy of Sciences
Sponsored by：Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; China Ecological Economics Society
Organizer：Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences
ISSN 2096-6237
CN 13-1432/S
- Chinese core periodicals
- Core Chinese Sci-Tech Periodicals
- China's Top Science and Technology Periodicals
- Covered by Chinese Science Citation Database (CSCD)
Download Center
More>
Links
More>
Video
More>
