Online First
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:
, Available online , doi: 10.1007/s11769-023-1335-3
Abstract:
Conservation tillage as an effective alternative to mitigate soil degradation has attracted worldwide attention, but the influences of conservation tillage on soil microbial community and especially function remain unclear. Shotgun metagenomics sequencing was performed to examine the taxonomic and functional community variations of black soils under three tillage regimes, namely no-tillage with residue (maize straw) return (NTS), moldboard plow with residue return (MPS), and moldboard plow without residue return (MPN) in Northeast China. The results revealed: 1) Soil bacterial and archaeal communities differed significantly under different tillage regimes in contrast to soil fungal community. 2) The overlay of less tillage and residues return under NTS led to unique soil microbial community composition and functional composition. Specifically, in contrast to other treatments, NTS increased the relative abundances of some taxa such as Bradyrhizobium, Candidatus Solibacter, and Reyranella, along with the relative abundances of some taxa such as Sphingomonas, Unclassified Chloroflexi and Nitrososphaera decreased; NTS had a unique advantage of increasing the relative abundances of genes involved in ‘ATP-binding cassette (ABC) transporters’ and ‘quorum sensing (QS)’ pathways, while MPN favored the genes involved in ‘flagellar assembly’ pathway and some metabolic pathways such as ‘carbon’ and ‘glyoxylate and dicarboxylate’ and ‘selenocompound’ metabolisms. 3) Significantly different soil bacterial phyla (Acidobacteria, Gemmatimonadetes, and Chloroflexi) and metabolic pathways existed between MPN and another two treatments (NTS and MPS), while did not exist between NTS and MPS. 4) Dissolved organic carbon (DOC) and soil bulk density were significantly affected (P < 0.05) by tillage and accounted for the variance both in microbial (bacterial) community structure and functional composition. These results indicated that a change in tillage regime from conventional to conservation tillage results in a shift of microbial community and functional genes, and we inferred that residue return played a more prominent role than less tillage in functional shifts in the microbial community of black soils.
Conservation tillage as an effective alternative to mitigate soil degradation has attracted worldwide attention, but the influences of conservation tillage on soil microbial community and especially function remain unclear. Shotgun metagenomics sequencing was performed to examine the taxonomic and functional community variations of black soils under three tillage regimes, namely no-tillage with residue (maize straw) return (NTS), moldboard plow with residue return (MPS), and moldboard plow without residue return (MPN) in Northeast China. The results revealed: 1) Soil bacterial and archaeal communities differed significantly under different tillage regimes in contrast to soil fungal community. 2) The overlay of less tillage and residues return under NTS led to unique soil microbial community composition and functional composition. Specifically, in contrast to other treatments, NTS increased the relative abundances of some taxa such as Bradyrhizobium, Candidatus Solibacter, and Reyranella, along with the relative abundances of some taxa such as Sphingomonas, Unclassified Chloroflexi and Nitrososphaera decreased; NTS had a unique advantage of increasing the relative abundances of genes involved in ‘ATP-binding cassette (ABC) transporters’ and ‘quorum sensing (QS)’ pathways, while MPN favored the genes involved in ‘flagellar assembly’ pathway and some metabolic pathways such as ‘carbon’ and ‘glyoxylate and dicarboxylate’ and ‘selenocompound’ metabolisms. 3) Significantly different soil bacterial phyla (Acidobacteria, Gemmatimonadetes, and Chloroflexi) and metabolic pathways existed between MPN and another two treatments (NTS and MPS), while did not exist between NTS and MPS. 4) Dissolved organic carbon (DOC) and soil bulk density were significantly affected (P < 0.05) by tillage and accounted for the variance both in microbial (bacterial) community structure and functional composition. These results indicated that a change in tillage regime from conventional to conservation tillage results in a shift of microbial community and functional genes, and we inferred that residue return played a more prominent role than less tillage in functional shifts in the microbial community of black soils.
, Available online , doi: 10.1007/s11769-023-1337-1
Abstract:
Vegetation is an important factor linking the atmosphere, water, soil, and biological functions, and it plays a specific role in the climate change response and sustainable development of regional economies. However, little information is available on vegetation vulnerability and its driving mechanism. Therefore, studying temporal and spatial change characteristics of vegetation and their corresponding mechanisms is important for assessing ecosystem stability and formulating ecological policies in the Kherlen River Basin. We used MOderate-resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) remote sensing images from 2000 to 2020 to analyse temporal changes in NDVI with the autoregressive moving average model (ARMA) and the breaks for additive season trend (BFAST) in the basin and to assess natural, anthropogenic and topographic factors with the Geodetector model. The results show that: 1) the long NDVI time series remained stable in the Kherlen River Basin from 2000 to 2020, with a certain significant mutation period from 2013 to 2017; 2) the coefficient of variation (CV) in the analysis of the spatial NDVI was generally constant, mainly at the level of 0.01–0.07, and the spatial NDVI change was minimally impacted by external interference; and 3) temperature and precipitation are the key factors affecting the NDVI in the basin, and changes in local hydrothermal conditions directly affect the local NDVI. The results of this study could provide a scientific basis for the effective protection of the ecological environment and will aid in understanding the influence of vegetation change mechanisms and the corresponding factors.
Vegetation is an important factor linking the atmosphere, water, soil, and biological functions, and it plays a specific role in the climate change response and sustainable development of regional economies. However, little information is available on vegetation vulnerability and its driving mechanism. Therefore, studying temporal and spatial change characteristics of vegetation and their corresponding mechanisms is important for assessing ecosystem stability and formulating ecological policies in the Kherlen River Basin. We used MOderate-resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) remote sensing images from 2000 to 2020 to analyse temporal changes in NDVI with the autoregressive moving average model (ARMA) and the breaks for additive season trend (BFAST) in the basin and to assess natural, anthropogenic and topographic factors with the Geodetector model. The results show that: 1) the long NDVI time series remained stable in the Kherlen River Basin from 2000 to 2020, with a certain significant mutation period from 2013 to 2017; 2) the coefficient of variation (CV) in the analysis of the spatial NDVI was generally constant, mainly at the level of 0.01–0.07, and the spatial NDVI change was minimally impacted by external interference; and 3) temperature and precipitation are the key factors affecting the NDVI in the basin, and changes in local hydrothermal conditions directly affect the local NDVI. The results of this study could provide a scientific basis for the effective protection of the ecological environment and will aid in understanding the influence of vegetation change mechanisms and the corresponding factors.
, Available online , doi: 10.1007/s11769-023-1334-4
Abstract:
Cultivated land pressure represents a direct reflection of grain security. Existing relevant studies rarely approached the spatiotemporal pattern of cultivated land pressure or the spatial heterogeneity of its influencing factors from the level of economic zones. Taking the Huaihai Economic Zone (HEZ), China for case analysis, this study investigated the spatiotemporal pattern of cultivated land pressure in diverse periods from 2000 to 2018 based on a modified cultivated land pressure index and spatial correlation models. On this basis, it explored the influencing factors of the spatial differentiation of cultivated land pressure in the late stage of the study using geographical detector as well as multi-scale geographically weighted regression model. The results indicated that: 1) in the study period, the global cultivated land pressure index of the study area decreased gradually, but cultivated land pressure increased locally in a significant way, especially in the central and southern Shandong Province; 2) the spatial pattern of cultivated land pressure manifested global clustering features. Hot and secondary-hot spots presented a narrowing and clustering trend, whereas cold and secondary-cold spots manifested a spreading and clustering trend; 3) average slope, the proportion of non-grain crops, population urbanization rate, and multiple cropping index have significant effects on the spatial differentiation of cultivated land pressure. The former three factors were positively correlated with cultivated land pressure, and the last factor was negatively correlated with cultivated land pressure; and 4) the amount of cultivated land has increased in the central and southern Shandong Province through land consolidation which, nonetheless, failed to improve the grain production. In regards to major grain producing areas similar to the HEZ in China, the authors suggest that great importance should be given to the balance of the quality and quantity of cultivated land, the optimization of agricultural production factors and the rational control of non-grain crops, thus providing a powerful guarantee for grain security in China.
Cultivated land pressure represents a direct reflection of grain security. Existing relevant studies rarely approached the spatiotemporal pattern of cultivated land pressure or the spatial heterogeneity of its influencing factors from the level of economic zones. Taking the Huaihai Economic Zone (HEZ), China for case analysis, this study investigated the spatiotemporal pattern of cultivated land pressure in diverse periods from 2000 to 2018 based on a modified cultivated land pressure index and spatial correlation models. On this basis, it explored the influencing factors of the spatial differentiation of cultivated land pressure in the late stage of the study using geographical detector as well as multi-scale geographically weighted regression model. The results indicated that: 1) in the study period, the global cultivated land pressure index of the study area decreased gradually, but cultivated land pressure increased locally in a significant way, especially in the central and southern Shandong Province; 2) the spatial pattern of cultivated land pressure manifested global clustering features. Hot and secondary-hot spots presented a narrowing and clustering trend, whereas cold and secondary-cold spots manifested a spreading and clustering trend; 3) average slope, the proportion of non-grain crops, population urbanization rate, and multiple cropping index have significant effects on the spatial differentiation of cultivated land pressure. The former three factors were positively correlated with cultivated land pressure, and the last factor was negatively correlated with cultivated land pressure; and 4) the amount of cultivated land has increased in the central and southern Shandong Province through land consolidation which, nonetheless, failed to improve the grain production. In regards to major grain producing areas similar to the HEZ in China, the authors suggest that great importance should be given to the balance of the quality and quantity of cultivated land, the optimization of agricultural production factors and the rational control of non-grain crops, thus providing a powerful guarantee for grain security in China.
, Available online , doi: 10.1007/s11769-023-1338-0
Abstract:
Mastering the pattern of food loss caused by droughts and floods aids in planning the layout of agricultural production, determining the scale of drought and flood control projects, and reducing food loss. The Standardized Precipitation Evapotranspiration Index is calculated using monthly meteorological data from 1984 to 2020 in Shandong Province of China and is used to identify the province’s drought and flood characteristics. Then, food losses due to droughts and floods are estimated separately from disaster loss data. Finally, the relationship between drought/flood-related factors and food losses is quantified using methods such as the Pearson correlation coefficient and linear regression. The results show that: 1) there is a trend of aridity in Shandong Province, and the drought characteristic variables are increasing yearly while flood duration and severity are decreasing. 2) The food losses caused by droughts in Shandong Province are more than those caused by floods, and the area where droughts and floods occur frequently is located in Linyi City. 3) The impact of precipitation on food loss due to drought/flood is significant, followed by potential evapotranspiration and temperature. 4) The relationship between drought and flood conditions and food losses can be precisely quantified. The accumulated drought duration of one month led to 1.939 × 104 t of grain loss, and an increase in cumulative flood duration of one month resulted in 1.134 × 104 t of grain loss. If the cumulative drought severity and average drought peak increased by one unit, food loss due to drought will increase by 1.562 × 104 t and 1.511 × 106 t, respectively. If the cumulative flood severity and average flood peak increase by one unit, food loss will increase by 8.470 × 103 t and 1.034 × 106 t, respectively.
Mastering the pattern of food loss caused by droughts and floods aids in planning the layout of agricultural production, determining the scale of drought and flood control projects, and reducing food loss. The Standardized Precipitation Evapotranspiration Index is calculated using monthly meteorological data from 1984 to 2020 in Shandong Province of China and is used to identify the province’s drought and flood characteristics. Then, food losses due to droughts and floods are estimated separately from disaster loss data. Finally, the relationship between drought/flood-related factors and food losses is quantified using methods such as the Pearson correlation coefficient and linear regression. The results show that: 1) there is a trend of aridity in Shandong Province, and the drought characteristic variables are increasing yearly while flood duration and severity are decreasing. 2) The food losses caused by droughts in Shandong Province are more than those caused by floods, and the area where droughts and floods occur frequently is located in Linyi City. 3) The impact of precipitation on food loss due to drought/flood is significant, followed by potential evapotranspiration and temperature. 4) The relationship between drought and flood conditions and food losses can be precisely quantified. The accumulated drought duration of one month led to 1.939 × 104 t of grain loss, and an increase in cumulative flood duration of one month resulted in 1.134 × 104 t of grain loss. If the cumulative drought severity and average drought peak increased by one unit, food loss due to drought will increase by 1.562 × 104 t and 1.511 × 106 t, respectively. If the cumulative flood severity and average flood peak increase by one unit, food loss will increase by 8.470 × 103 t and 1.034 × 106 t, respectively.
, Available online , doi: 10.1007/s11769-023-1339-z
Abstract:
Air pollution is a problem that directly affects human health, the global environment and the climate. The air quality index (AQI) indicates the degree of air pollution and effect on human health; however, when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored. In the present study, multi-source data were combined to map the distribution of the AQI and population data, and the analyze their pollution population exposure of Beijing in 2018 was analyzed. Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018. Using Luojia-1 nighttime light remote sensing data, population statistics data, the population of Beijing in 2018 and point of interest data, the distribution of the permanent population in Beijing was estimated with a high precision of 200 m × 200 m. Based on the spatialization results of the AQI and population of Beijing, the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level (PWEL) formula. The results show that the southern region of Beijing had a more serious level of air pollution, while the northern region was less polluted. At the same time, the population was found to agglomerate mainly in the central city and the peripheric areas thereof. In the present study, the exposure of different districts and towns in Beijing to pollution was analyzed, based on high resolution population spatialization data, it could take the pollution exposure issue down to each individual town. And we found that towns with higher exposure such as Yongshun Town, Shahe Town and Liyuan Town were all found to have a population of over 200 000 which was much higher than the median population of townships of 51 741 in Beijing. Additionally, the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same, with the peak value being in winter and the lowest value being in summer. The exposure intensity in population clusters was relatively high. To reduce the level and intensity of pollution exposure, relevant departments should strengthen the governance of areas with high AQI, and pay particular attention to population clusters.
Air pollution is a problem that directly affects human health, the global environment and the climate. The air quality index (AQI) indicates the degree of air pollution and effect on human health; however, when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored. In the present study, multi-source data were combined to map the distribution of the AQI and population data, and the analyze their pollution population exposure of Beijing in 2018 was analyzed. Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018. Using Luojia-1 nighttime light remote sensing data, population statistics data, the population of Beijing in 2018 and point of interest data, the distribution of the permanent population in Beijing was estimated with a high precision of 200 m × 200 m. Based on the spatialization results of the AQI and population of Beijing, the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level (PWEL) formula. The results show that the southern region of Beijing had a more serious level of air pollution, while the northern region was less polluted. At the same time, the population was found to agglomerate mainly in the central city and the peripheric areas thereof. In the present study, the exposure of different districts and towns in Beijing to pollution was analyzed, based on high resolution population spatialization data, it could take the pollution exposure issue down to each individual town. And we found that towns with higher exposure such as Yongshun Town, Shahe Town and Liyuan Town were all found to have a population of over 200 000 which was much higher than the median population of townships of 51 741 in Beijing. Additionally, the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same, with the peak value being in winter and the lowest value being in summer. The exposure intensity in population clusters was relatively high. To reduce the level and intensity of pollution exposure, relevant departments should strengthen the governance of areas with high AQI, and pay particular attention to population clusters.
, Available online , doi: 10.1007/s11769-023-1336-2
Abstract:
The extant literature on international immigrants has discussed migrants’ entrepreneurial activities in the context of Western countries but has paid little attention to return-home entrepreneurial intention (RHEI). Rural migrant workers (RMWs) in China, who used to promote rural development by remittances and were characterized by similarities with early international migrants, have gradually returned to their hometowns to initiate entrepreneurial activities. Based on the structured questionnaire conducted in 2015 and 2020 in Anhui Province, China, this article combines the concept of mixed embeddedness with the idea of double-layered embeddedness and analyzes the impacts of the social, economic and institutional context in RMWs’ hometowns and migration destinations on RMWs’ RHEI by using binary logistic regression. The article shows that the social, economic, and institutional environments of RMWs’ hometowns and migration destinations have effects on their RHEI. The embeddedness in the economic and informal institutional context in RMWs’ RHEI is even more important than personal characteristics. Compared with migration destinations, RMWs’ hometowns exert a more influential effect on their RHEI. However, that does not mean that the role of migration destinations can be undervalued. Actually, the better the social, economic, and institutional environments of migration destinations RMWs moved into is, the higher entrepreneurial intention they will have after returning to their hometowns. The article proposes a modified framework in combination of mixed embeddedness with double-layer embeddedness and proves that it is suitable for analyzing RMWs’ RHEI. The framework has important implications for strengthening China’s RMWs to return home to start their own businesses.
The extant literature on international immigrants has discussed migrants’ entrepreneurial activities in the context of Western countries but has paid little attention to return-home entrepreneurial intention (RHEI). Rural migrant workers (RMWs) in China, who used to promote rural development by remittances and were characterized by similarities with early international migrants, have gradually returned to their hometowns to initiate entrepreneurial activities. Based on the structured questionnaire conducted in 2015 and 2020 in Anhui Province, China, this article combines the concept of mixed embeddedness with the idea of double-layered embeddedness and analyzes the impacts of the social, economic and institutional context in RMWs’ hometowns and migration destinations on RMWs’ RHEI by using binary logistic regression. The article shows that the social, economic, and institutional environments of RMWs’ hometowns and migration destinations have effects on their RHEI. The embeddedness in the economic and informal institutional context in RMWs’ RHEI is even more important than personal characteristics. Compared with migration destinations, RMWs’ hometowns exert a more influential effect on their RHEI. However, that does not mean that the role of migration destinations can be undervalued. Actually, the better the social, economic, and institutional environments of migration destinations RMWs moved into is, the higher entrepreneurial intention they will have after returning to their hometowns. The article proposes a modified framework in combination of mixed embeddedness with double-layer embeddedness and proves that it is suitable for analyzing RMWs’ RHEI. The framework has important implications for strengthening China’s RMWs to return home to start their own businesses.
, Available online , doi: 10.1007/s11769-023-1333-5
Abstract:
The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China (Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third, policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.
The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China (Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third, policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.
, Available online , doi: 10.1007/s11769-023-1332-6
Abstract:
Human-wildlife conflict (HWC) negatively impacts both humans and wildlife. Attitudes of local residents have been critical in promoting wildlife conservation. It is therefore necessary to understand the characteristics of HWC and identify influential factors on attitudes towards conservation to implement conservation strategies efficiently. This research focused on features of human-elephant interactions, while attitudes and values regarding the small population of Asian elephants (Elephas maximus) in Nangunhe National Nature Reserve (NNR), Yunnan, China. The total of 327 valid questionnaires were gathered around the area where Asian elephants were distributed. Logistic regression models were employed to analyze the correlations among five predictor variables (‘Area’, ‘Family size’, ‘Annual income’, ‘Quantity of family members in non-primary industries’ and ‘Experiencing loss or not’) and three response variables (‘Attitude towards elephants’, ‘Perception of the values of elephants’ and ‘Attitude towards tourism development’). The study area was densely forested with tea plants, rubber trees, corns and sugarcane. There, 25.99% of respondents reported the experience of human-elephant conflict (HEC), with crop raiding and cash crop damages being the major conflict types. To demonstrate respect for elephants and to mitigate HEC, a unique custom called ‘Giving tribute to elephants’ was developed long ago. Respondents’ township with an official annual festival of ‘Giving Tribute to Elephants’ (odds ratio (OR) = 2.75, P = 1.73 × 10−6) and higher annual income (OR = 2.09, P = 5.45 × 10−5) significantly contributed to forming a more positive attitude towards elephants, whereas HEC itself have contributed to a more negative attitude (OR = 0.50, P = 3.29 × 10−3). Therefore, we propose that: 1) reducing human-elephant conflict by testing multiple mitigation measures and adopting the most effective one of them; 2) enhancing local livelihoods through the development of ecological products and ecotourism; and 3) preserving and developing the Wa culture in this region. The study area deserves more attention and further research to explore and obtain endorsement from the public to achieve coexistence between human and wildlife.
Human-wildlife conflict (HWC) negatively impacts both humans and wildlife. Attitudes of local residents have been critical in promoting wildlife conservation. It is therefore necessary to understand the characteristics of HWC and identify influential factors on attitudes towards conservation to implement conservation strategies efficiently. This research focused on features of human-elephant interactions, while attitudes and values regarding the small population of Asian elephants (Elephas maximus) in Nangunhe National Nature Reserve (NNR), Yunnan, China. The total of 327 valid questionnaires were gathered around the area where Asian elephants were distributed. Logistic regression models were employed to analyze the correlations among five predictor variables (‘Area’, ‘Family size’, ‘Annual income’, ‘Quantity of family members in non-primary industries’ and ‘Experiencing loss or not’) and three response variables (‘Attitude towards elephants’, ‘Perception of the values of elephants’ and ‘Attitude towards tourism development’). The study area was densely forested with tea plants, rubber trees, corns and sugarcane. There, 25.99% of respondents reported the experience of human-elephant conflict (HEC), with crop raiding and cash crop damages being the major conflict types. To demonstrate respect for elephants and to mitigate HEC, a unique custom called ‘Giving tribute to elephants’ was developed long ago. Respondents’ township with an official annual festival of ‘Giving Tribute to Elephants’ (odds ratio (OR) = 2.75, P = 1.73 × 10−6) and higher annual income (OR = 2.09, P = 5.45 × 10−5) significantly contributed to forming a more positive attitude towards elephants, whereas HEC itself have contributed to a more negative attitude (OR = 0.50, P = 3.29 × 10−3). Therefore, we propose that: 1) reducing human-elephant conflict by testing multiple mitigation measures and adopting the most effective one of them; 2) enhancing local livelihoods through the development of ecological products and ecotourism; and 3) preserving and developing the Wa culture in this region. The study area deserves more attention and further research to explore and obtain endorsement from the public to achieve coexistence between human and wildlife.
Email
RSS