The deep sea holds vital resources and spatial potential for future human survival and development,reflecting the common interests and concerns of all mankind.Amidst unprecedented global transformations in a hundred y...The deep sea holds vital resources and spatial potential for future human survival and development,reflecting the common interests and concerns of all mankind.Amidst unprecedented global transformations in a hundred years,the deep sea has emerged as a critical area of international competition and serves as a new frontier for resource extraction,a strategic space for military competition,and a contested space for great power rivalry and rule-making.展开更多
Along with the coming of the low-carbon era, people have paid more and more attention to the natural environment and eco-tourism will embrace a huge development. From the perspectives of the market relationship of sup...Along with the coming of the low-carbon era, people have paid more and more attention to the natural environment and eco-tourism will embrace a huge development. From the perspectives of the market relationship of supply-demand in economics and of field competition in physics, this paper has discussed upon the present status of the spatial structure of eco-tourism, and analyzed the relationship between supply-demand and field, in order to clarify the direction for the balance between supply and demand in the field and to guide eco-tourism to the way of sustainable development.展开更多
Reforestation or natural forest regeneration is an alternative measure for controlling soil erosion in degraded land on the Chinese Loess Plateau（CLP）. However, our understanding of the temporal dynamics and the spa...Reforestation or natural forest regeneration is an alternative measure for controlling soil erosion in degraded land on the Chinese Loess Plateau（CLP）. However, our understanding of the temporal dynamics and the spatial patterns of forest regeneration remains inadequate. Two oak forests at different development stages were investigated to determine the spatial patterns of competitions（intraspecies and interspecies） during different successional stages. The intraspecies and interspecies spatial relationships among different tree diameters at breast height were analyzed at multiple scales by Kriging interpolation method and univariate and bivariate O-ring statistics. Our analytical results indicated that self-correlation and competition intensity were relatively high between oak and pine trees in the early development stage of oak forests due to their clumped distributions of heavy seeds. Birch trees had a lower competition in comparison to oak trees although birch was the dominant species. Therefore, asymmetric competition of oak trees was most likely to have led to their edge dispersal and their success in replacing the pioneer species. Asymmetric competition means that larger individuals obtained a disproportionately large share of the resources and suppressed the growth of smaller individuals. Kriging interpolation analysis showed a tendency towards homogenization caused by interspecies competition during the succession of oak forests. Our results demonstrated that the competition was the driving factor in the spatial distribution of oak forests on the CLP.展开更多
Competition,spatial pattern,and regeneration are important factors affecting community composition,structure,and dynamics.In this study,we surveyed 300 quadrats from three dunes(i.e.,fixed dunes,semifixed dunes,and mo...Competition,spatial pattern,and regeneration are important factors affecting community composition,structure,and dynamics.In this study,we surveyed 300 quadrats from three dunes(i.e.,fixed dunes,semifixed dunes,and mobile dunes)in the Gurbantunggut Desert,Northwest China,from late May to early June in 2021.The intraspecific and interspecific competition,spatial pattern,and regeneration of Haloxylon ammodendron and Haloxylon persicum were studied using the Hegyi competition index and point pattern analysis methods.The results showed that the optimal competition distance of the objective tree in the H.ammodendron and H.persicum communities was 6 m.The intraspecific and interspecific competition of H.ammodendron was the greatest in fixed dunes,while the competition intensity of H.persicum in semifixed dunes and mobile dunes was greater than that in fixed dunes.The order of competition intensity of the two populations was seedlings>saplings>adults,and the competition intensity gradually decreased with the increase in plant diameter.The spatial distribution pattern of the three life stages of H.ammodendron and H.persicum was random,and there were no correlations between seedlings and saplings,adults and saplings,and seedlings and adults.The density of regenerated seedlings and saplings of H.ammodendron in the three dunes followed the order of fixed dunes>semifixed dunes>mobile dunes,and that of H.persicum in the three dunes followed the order of mobile dunes>semifixed dunes>fixed dunes.Therefore,when artificially planting H.ammodendron and H.persicum for sand control,the planting interval should be 6 m,and seedlings should be planted next to adults to minimize the competition between plants,which can promote the renewal of H.ammodendron and H.persicum and the stabilization of the ecosystem.展开更多
Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness...Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness and mapped the effects of ecosystem services on agricultural competitiveness using multiple models.In this study,multi-source data from 2000 to 2020 were utilized to establish the indicator system of agricultural competitiveness;five ecosystem services were quantified using computation models;Geographic Information System(GIS)spatial analysis was used to explore the spatial patterns of agricultural competitiveness and ecosystem services;geographic detector models were applied to investigate the effects and driving mechanisms of ecosystem services on agricultural competitiveness.Shandong Province of China was selected as the case study area.The results demonstrated that:1)there was a significant increase in agricultural competitiveness during the study period,with high levels observed mainly in the east region of the study area.2)The spatial distribution patterns of ecosystem services and agricultural competitiveness primarily exhibited High-High and Low-Low Cluster types.3)Habitat quality emerged as the main driving factor of agricultural competitiveness in 2000 and 2020,while water yield played a substantial role in 2010.4)The coupling of two ecosystem services exerted a greater effect on agricultural competitiveness compared to individual ecosystem service.The innovations of this study are constructing an indicator system to quantify agricultural competitiveness,and exploring the effects of ecosystem services on agricultural competitiveness.This study proposed an indicator system to quantify agricultural competitiveness,which can be applied in other regions,and explored the effects of ecosystem services on agricultural competitiveness.The findings of this study can serve as valuable insights for policymakers to formulate tailored agricultural development policies that take into account the synergistic effects of ecosystem services on agricultural competitiveness.展开更多
The aim of this paper is to investigate a Volterra-Lotka competition model of quasilinear parabolic equations with large interaction. Some existence, uniqueness and convergence results for the system are given. Also i...The aim of this paper is to investigate a Volterra-Lotka competition model of quasilinear parabolic equations with large interaction. Some existence, uniqueness and convergence results for the system are given. Also investigated is its spatial segregation limit when the interspecific competition rates become large. We show that the limit problem is similar to a free boundary problem.展开更多
Crown development is closely related to the biomass and growth rate of the tree and its width(CW)is an important covariable in growth and yield models and in forest management.To date,various CW models have been propo...Crown development is closely related to the biomass and growth rate of the tree and its width(CW)is an important covariable in growth and yield models and in forest management.To date,various CW models have been proposed.However,limited studies have explicitly focused on additive and inherent correlation of crown components and total CW as well as the influence of competition on crown radius from the corresponding direction.In this study,two model systems were used,i.e.,aggregation method system(AMS)and disaggregation method system(DMS),to develop crown width additive model systems.For calculating spatially explicit competition index(CI),four neighbor tree selection methods were evaluated.CI was decomposed into four cardinal directions and added into the model systems.Results show that the power model form was more proper for our data to fit CW growth.For each crown radius and total CW,height to the diameter at breast height(HDR)and basal area of trees larger than the subject tree(BAL)significantly contributed to the increase of prediction accuracy.The 3-m fixed radius was optimal among the four neighborhoods selection ways.After adding decomposed competition Hegyi index into model systems AMS and DMS,the prediction accuracy improved.Of the model systems evaluated,AMS based on decomposed CI provided the best performance as well as the inherent correlation and additivity properties.Our study highlighted the importance of decomposed CI in tree CW modelling for additive model systems.This study focused on methodology and could be applied to other species or stands.展开更多
Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ.Spatial transcriptomics can provide multimodal and compl...Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ.Spatial transcriptomics can provide multimodal and complementary information simultaneously,including gene expression profiles,spatial locations,and histology images.However,most existing methods have limitations in efficiently utilizing spatial information and matched high-resolution histology images.To fully leverage the multi-modal information,we propose a SPAtially embedded Deep Attentional graph Clustering(SpaDAC)method to identify spatial domains while reconstructing denoised gene expression profiles.This method can efficiently learn the low-dimensional embeddings for spatial transcriptomics data by constructing multi-view graph modules to capture both spatial location connectives and morphological connectives.Benchmark results demonstrate that SpaDAC outperforms other algorithms on several recent spatial transcriptomics datasets.SpaDAC is a valuable tool for spatial domain detection,facilitating the comprehension of tissue architecture and cellular microenvironment.The source code of SpaDAC is freely available at Github(https://github.com/huoyuying/SpaDAC.git).展开更多
Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based ...Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based and ground-based LiDAR struggles to capture complete crown information in dense stands,making parameter extraction challenging such as maximum crown width height(HMCW).This study proposes a canopy spatial relationship-based method for constructing forest spatial structure units and employs five ensemble learning techniques to train 11 machine learning model combinations.By coupling spatial competition with phenotype parameters,the study identifies the optimal fitting model for HMCW of Chinese fir.The results demonstrate that the constructed spatial structure units align closely with existing research while addressing issues of incorrectly selected or omitted neighboring trees.Among the 10,191 trained HMCW models,the Bagging model integrating XGBoost,Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting(GB),and Ridge exhibited the best performance.Compared to the best single model(RF),the Bagging model achieved improved accuracy(R^(2)=0.8346,representing a 1.6%improvement;RMSE=1.4042,reduced by 6.66%;EVS=0.8389;MAE=0.9129;MAPE=0.0508;and MedAE=0.5076,with corresponding improvements of 1.63%,1.49%,0.1%,and 7.06%,respectively).This study provides a viable solution for modeling HMCW in all species with similar structural characteristics and offers a method for extracting other hard-to-measure parameters.The refined spatial structure units better link 3D structural phenotypes with environmental factors.This approach aids in canopy morphology simulation and forest management research.展开更多
文摘The deep sea holds vital resources and spatial potential for future human survival and development,reflecting the common interests and concerns of all mankind.Amidst unprecedented global transformations in a hundred years,the deep sea has emerged as a critical area of international competition and serves as a new frontier for resource extraction,a strategic space for military competition,and a contested space for great power rivalry and rule-making.
文摘Along with the coming of the low-carbon era, people have paid more and more attention to the natural environment and eco-tourism will embrace a huge development. From the perspectives of the market relationship of supply-demand in economics and of field competition in physics, this paper has discussed upon the present status of the spatial structure of eco-tourism, and analyzed the relationship between supply-demand and field, in order to clarify the direction for the balance between supply and demand in the field and to guide eco-tourism to the way of sustainable development.
基金funded by the National Natural Science Foundation of China (41301601)the Special Fund for Forest Scientific Research in the Public Interest (201304312)
文摘Reforestation or natural forest regeneration is an alternative measure for controlling soil erosion in degraded land on the Chinese Loess Plateau（CLP）. However, our understanding of the temporal dynamics and the spatial patterns of forest regeneration remains inadequate. Two oak forests at different development stages were investigated to determine the spatial patterns of competitions（intraspecies and interspecies） during different successional stages. The intraspecies and interspecies spatial relationships among different tree diameters at breast height were analyzed at multiple scales by Kriging interpolation method and univariate and bivariate O-ring statistics. Our analytical results indicated that self-correlation and competition intensity were relatively high between oak and pine trees in the early development stage of oak forests due to their clumped distributions of heavy seeds. Birch trees had a lower competition in comparison to oak trees although birch was the dominant species. Therefore, asymmetric competition of oak trees was most likely to have led to their edge dispersal and their success in replacing the pioneer species. Asymmetric competition means that larger individuals obtained a disproportionately large share of the resources and suppressed the growth of smaller individuals. Kriging interpolation analysis showed a tendency towards homogenization caused by interspecies competition during the succession of oak forests. Our results demonstrated that the competition was the driving factor in the spatial distribution of oak forests on the CLP.
基金the Open Project of Xinjiang Laboratory of Lake Environment and Resources in Arid Zone(XJDX0909-2022-4)the PhD Early Development Program of Xinjiang Normal University(XJNUBS2113).
文摘Competition,spatial pattern,and regeneration are important factors affecting community composition,structure,and dynamics.In this study,we surveyed 300 quadrats from three dunes(i.e.,fixed dunes,semifixed dunes,and mobile dunes)in the Gurbantunggut Desert,Northwest China,from late May to early June in 2021.The intraspecific and interspecific competition,spatial pattern,and regeneration of Haloxylon ammodendron and Haloxylon persicum were studied using the Hegyi competition index and point pattern analysis methods.The results showed that the optimal competition distance of the objective tree in the H.ammodendron and H.persicum communities was 6 m.The intraspecific and interspecific competition of H.ammodendron was the greatest in fixed dunes,while the competition intensity of H.persicum in semifixed dunes and mobile dunes was greater than that in fixed dunes.The order of competition intensity of the two populations was seedlings>saplings>adults,and the competition intensity gradually decreased with the increase in plant diameter.The spatial distribution pattern of the three life stages of H.ammodendron and H.persicum was random,and there were no correlations between seedlings and saplings,adults and saplings,and seedlings and adults.The density of regenerated seedlings and saplings of H.ammodendron in the three dunes followed the order of fixed dunes>semifixed dunes>mobile dunes,and that of H.persicum in the three dunes followed the order of mobile dunes>semifixed dunes>fixed dunes.Therefore,when artificially planting H.ammodendron and H.persicum for sand control,the planting interval should be 6 m,and seedlings should be planted next to adults to minimize the competition between plants,which can promote the renewal of H.ammodendron and H.persicum and the stabilization of the ecosystem.
基金Under the auspices of the National Key Research and Development Program of China(No.2022YFC3204404)。
文摘Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness and mapped the effects of ecosystem services on agricultural competitiveness using multiple models.In this study,multi-source data from 2000 to 2020 were utilized to establish the indicator system of agricultural competitiveness;five ecosystem services were quantified using computation models;Geographic Information System(GIS)spatial analysis was used to explore the spatial patterns of agricultural competitiveness and ecosystem services;geographic detector models were applied to investigate the effects and driving mechanisms of ecosystem services on agricultural competitiveness.Shandong Province of China was selected as the case study area.The results demonstrated that:1)there was a significant increase in agricultural competitiveness during the study period,with high levels observed mainly in the east region of the study area.2)The spatial distribution patterns of ecosystem services and agricultural competitiveness primarily exhibited High-High and Low-Low Cluster types.3)Habitat quality emerged as the main driving factor of agricultural competitiveness in 2000 and 2020,while water yield played a substantial role in 2010.4)The coupling of two ecosystem services exerted a greater effect on agricultural competitiveness compared to individual ecosystem service.The innovations of this study are constructing an indicator system to quantify agricultural competitiveness,and exploring the effects of ecosystem services on agricultural competitiveness.This study proposed an indicator system to quantify agricultural competitiveness,which can be applied in other regions,and explored the effects of ecosystem services on agricultural competitiveness.The findings of this study can serve as valuable insights for policymakers to formulate tailored agricultural development policies that take into account the synergistic effects of ecosystem services on agricultural competitiveness.
文摘The aim of this paper is to investigate a Volterra-Lotka competition model of quasilinear parabolic equations with large interaction. Some existence, uniqueness and convergence results for the system are given. Also investigated is its spatial segregation limit when the interspecific competition rates become large. We show that the limit problem is similar to a free boundary problem.
基金supported by the National Natural Science Foundation of China,“Study on crown models for L arix olgensis based on tree growth” (No.31870620)。
文摘Crown development is closely related to the biomass and growth rate of the tree and its width(CW)is an important covariable in growth and yield models and in forest management.To date,various CW models have been proposed.However,limited studies have explicitly focused on additive and inherent correlation of crown components and total CW as well as the influence of competition on crown radius from the corresponding direction.In this study,two model systems were used,i.e.,aggregation method system(AMS)and disaggregation method system(DMS),to develop crown width additive model systems.For calculating spatially explicit competition index(CI),four neighbor tree selection methods were evaluated.CI was decomposed into four cardinal directions and added into the model systems.Results show that the power model form was more proper for our data to fit CW growth.For each crown radius and total CW,height to the diameter at breast height(HDR)and basal area of trees larger than the subject tree(BAL)significantly contributed to the increase of prediction accuracy.The 3-m fixed radius was optimal among the four neighborhoods selection ways.After adding decomposed competition Hegyi index into model systems AMS and DMS,the prediction accuracy improved.Of the model systems evaluated,AMS based on decomposed CI provided the best performance as well as the inherent correlation and additivity properties.Our study highlighted the importance of decomposed CI in tree CW modelling for additive model systems.This study focused on methodology and could be applied to other species or stands.
基金supported by National Natural Science Foundation of China(62003028).X.L.was supported by a Scholarship from the China Scholarship Council.
文摘Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ.Spatial transcriptomics can provide multimodal and complementary information simultaneously,including gene expression profiles,spatial locations,and histology images.However,most existing methods have limitations in efficiently utilizing spatial information and matched high-resolution histology images.To fully leverage the multi-modal information,we propose a SPAtially embedded Deep Attentional graph Clustering(SpaDAC)method to identify spatial domains while reconstructing denoised gene expression profiles.This method can efficiently learn the low-dimensional embeddings for spatial transcriptomics data by constructing multi-view graph modules to capture both spatial location connectives and morphological connectives.Benchmark results demonstrate that SpaDAC outperforms other algorithms on several recent spatial transcriptomics datasets.SpaDAC is a valuable tool for spatial domain detection,facilitating the comprehension of tissue architecture and cellular microenvironment.The source code of SpaDAC is freely available at Github(https://github.com/huoyuying/SpaDAC.git).
基金funded by Fundamental Research Funds of CAF(CAFYBB2023PA003)Science and Technology Innovation 2030-Major Projects(2023ZD0406103)National Natural Science Foundation of China(32271877).
文摘Accurate acquisition of forest spatial competition and tree 3D structural phenotype parameters is crucial for exploring tree-environment interactions.However,due to the occlusion between tree crowns,current UAV-based and ground-based LiDAR struggles to capture complete crown information in dense stands,making parameter extraction challenging such as maximum crown width height(HMCW).This study proposes a canopy spatial relationship-based method for constructing forest spatial structure units and employs five ensemble learning techniques to train 11 machine learning model combinations.By coupling spatial competition with phenotype parameters,the study identifies the optimal fitting model for HMCW of Chinese fir.The results demonstrate that the constructed spatial structure units align closely with existing research while addressing issues of incorrectly selected or omitted neighboring trees.Among the 10,191 trained HMCW models,the Bagging model integrating XGBoost,Random Forest(RF),Support Vector Regression(SVR),Gradient Boosting(GB),and Ridge exhibited the best performance.Compared to the best single model(RF),the Bagging model achieved improved accuracy(R^(2)=0.8346,representing a 1.6%improvement;RMSE=1.4042,reduced by 6.66%;EVS=0.8389;MAE=0.9129;MAPE=0.0508;and MedAE=0.5076,with corresponding improvements of 1.63%,1.49%,0.1%,and 7.06%,respectively).This study provides a viable solution for modeling HMCW in all species with similar structural characteristics and offers a method for extracting other hard-to-measure parameters.The refined spatial structure units better link 3D structural phenotypes with environmental factors.This approach aids in canopy morphology simulation and forest management research.
