The altitudinal pattern of vegetation is usually identified by field surveys,however,these can only provide discrete data on a local mountain.Few studies identifying and analyzing the altitudinal vegetation pattern on...The altitudinal pattern of vegetation is usually identified by field surveys,however,these can only provide discrete data on a local mountain.Few studies identifying and analyzing the altitudinal vegetation pattern on a regional scale are available.This study selected central Inner Mongolia as the study area,presented a method for extracting vegetation patterns in altitudinal and horizontal directions.The data included a vegetation map at a 1∶1 000 000 scale and a digital elevation model at a 1∶250 000 scale.The three-dimensional vegetation pattern indicated the distribution probability for each vegetation type and the transition zones between different vegetation landscapes.From low to high elevations,there were five vegetation types in the southern mountain flanks,including the montane steppe,broad-leaved forest,coniferous mixed forest,montane dwarf-scrub and sub-alpine shrub-meadow.Correspondingly,only four vegetation types were found in the northern flanks,except for the montane steppe.This study could provide a general model for understanding the complexity and diversity of mountain environment and landscape.展开更多
Mass occurrence of Salpafusiformis June 2007. In order to investigate its population was observed in the Southern Yellow Sea in May and recruitment and environmental adaptation, temporal variation of abundance, diel v...Mass occurrence of Salpafusiformis June 2007. In order to investigate its population was observed in the Southern Yellow Sea in May and recruitment and environmental adaptation, temporal variation of abundance, diel vertical migration （DVM） and length frequency distribution of both aggregate and solitary forms were studied with samples collected from eight months during September 2006 to August 2007. S. fusiformis presented in six months other than September and October 2006, and average abundance of aggregate and solitary forms peaked in June and May, respectively. In December, aggregate forms were absent in the bottom layer and performed irregular DVM from surface to 50 m depth, while solitary forms was too scarce to perform diel vertical distribution analysis. Both aggregate and solitary forms presented reverse DVM in May and June. They migrated upwards during daytime and concentrated in surface layer at sunset. The bimodal distribution of aggregate forms was found in April and the average size was largest in this month. In other months, the smaller aggregate forms （1-5 ram） dominated in populations except for May, when the modal size ranged from 2 to 8 mm. The average size of solitary forms was largest in December, followed by April. The skewed nomal distribution of solitary forms was found in May and June, with the modal size of 2-7 mm and 5-13 ram, respectively.展开更多
A vegetation evolution model influenced by a degeneration of soil ecological functions was set up. Three ideal communities of a) trees, b) shrubs, and c) herbage populations were first simulated. Then numerical simula...A vegetation evolution model influenced by a degeneration of soil ecological functions was set up. Three ideal communities of a) trees, b) shrubs, and c) herbage populations were first simulated. Then numerical simulations of the evolutionary and developmental processes of a natural forest community, which is composed of over 100 species,were conducted. Results of the study showed that a) in all communities, soil degeneration not only drove some weaker species to extinction, but also a few dominant ones; b) there were different response scales with species in an ideal tree metapopulation that could persist as long as a thousand years, with shrubs in an ideal shrub metapopulation that could persevere for several hundred years, and with species in an ideal herbage metapopulation that could become extinct within 10 years; and c) each metapopulation experienced three evolutionary stages during adaptation to the environment: a) the stage of compelled adaptation or resistance, b) the adjusted stage, and c) the stabilized stage.展开更多
This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vege...This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41001111,41030528)
文摘The altitudinal pattern of vegetation is usually identified by field surveys,however,these can only provide discrete data on a local mountain.Few studies identifying and analyzing the altitudinal vegetation pattern on a regional scale are available.This study selected central Inner Mongolia as the study area,presented a method for extracting vegetation patterns in altitudinal and horizontal directions.The data included a vegetation map at a 1∶1 000 000 scale and a digital elevation model at a 1∶250 000 scale.The three-dimensional vegetation pattern indicated the distribution probability for each vegetation type and the transition zones between different vegetation landscapes.From low to high elevations,there were five vegetation types in the southern mountain flanks,including the montane steppe,broad-leaved forest,coniferous mixed forest,montane dwarf-scrub and sub-alpine shrub-meadow.Correspondingly,only four vegetation types were found in the northern flanks,except for the montane steppe.This study could provide a general model for understanding the complexity and diversity of mountain environment and landscape.
基金Supports by the National Basic Research Program of China (973 Program) (No. 2011CB403604)the National Natural Science Foundation of China (No. 40631008)
文摘Mass occurrence of Salpafusiformis June 2007. In order to investigate its population was observed in the Southern Yellow Sea in May and recruitment and environmental adaptation, temporal variation of abundance, diel vertical migration （DVM） and length frequency distribution of both aggregate and solitary forms were studied with samples collected from eight months during September 2006 to August 2007. S. fusiformis presented in six months other than September and October 2006, and average abundance of aggregate and solitary forms peaked in June and May, respectively. In December, aggregate forms were absent in the bottom layer and performed irregular DVM from surface to 50 m depth, while solitary forms was too scarce to perform diel vertical distribution analysis. Both aggregate and solitary forms presented reverse DVM in May and June. They migrated upwards during daytime and concentrated in surface layer at sunset. The bimodal distribution of aggregate forms was found in April and the average size was largest in this month. In other months, the smaller aggregate forms （1-5 ram） dominated in populations except for May, when the modal size ranged from 2 to 8 mm. The average size of solitary forms was largest in December, followed by April. The skewed nomal distribution of solitary forms was found in May and June, with the modal size of 2-7 mm and 5-13 ram, respectively.
基金Project supported by the National Natural Science Foundation of China (No. 40371108) the National "211" Key Project of China: The environmental evolution and ecological construction on multi-spatio-temporal scales.
文摘A vegetation evolution model influenced by a degeneration of soil ecological functions was set up. Three ideal communities of a) trees, b) shrubs, and c) herbage populations were first simulated. Then numerical simulations of the evolutionary and developmental processes of a natural forest community, which is composed of over 100 species,were conducted. Results of the study showed that a) in all communities, soil degeneration not only drove some weaker species to extinction, but also a few dominant ones; b) there were different response scales with species in an ideal tree metapopulation that could persist as long as a thousand years, with shrubs in an ideal shrub metapopulation that could persevere for several hundred years, and with species in an ideal herbage metapopulation that could become extinct within 10 years; and c) each metapopulation experienced three evolutionary stages during adaptation to the environment: a) the stage of compelled adaptation or resistance, b) the adjusted stage, and c) the stabilized stage.
基金Under the auspices of National Natural Science Foundation of China(No.41001363)
文摘This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.
