Taking different forests in Aershan of Inner Mongolia as sample plots, diversity and dominant species of arthropods were studied. The results show that two classes, 17 orders, 68 families, 130 species and 3742 individ...Taking different forests in Aershan of Inner Mongolia as sample plots, diversity and dominant species of arthropods were studied. The results show that two classes, 17 orders, 68 families, 130 species and 3742 individuals were identified and 92.31% of total species appeared in natural forests, and 75.38% of total species appeared in plantations. The orders of Lepidoptera, Coleoptera, Diptera and Hymenoptera covered most of the collected arthropods. In different forest types, diversity indices is natural mixed forests （Betula platyphylla x Larix gmelinii）〉 natural pure B. platyphylla forests〉natural pure L. gmelinii forests〉plantations with pesticide treatment〉plantations without pesticide treatment. In natural forests, more than 70% of the arthropod families, species and individuals were distributed in shrub and herb layer, while in plantations 75% of the arthropod families, 78% of species and 80% of individuals were also distributed in shrub and herb layer. Lepidoptera, including Loxostege sticticalis （Linnaeus）, Chilo suppressalis （Walker） and Lymantria dispar （Linnaeus）, had the highest dominant degree.展开更多
Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully...Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.展开更多
Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can...Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can facilitate the development of this baseline knowledge across broad extents, but they first must be classified into forest community types. Here, we compared three alternative classifications across the United States using data from over 117,000 U.S. Department of Agriculture Forest Service Forest Inventory and Analysis （FIA） plots. Methods： Each plot had three forest community type labels： （1） ＂FIA＂ types were assigned by the FIA program using a supervised method; （2） ＂USNVC＂ types were assigned via a key based on the U.S. National Vegetation Classification; （3） ＂empirical＂ types resulted from unsupervised clustering of tree species information. We assessed the degree to which analog classes occurred among classifications, compared indicator species values, and used random forest models to determine how well the classifications could be predicted using environmental variables. Results： The classifications generated groups of classes that had broadly similar distributions, but often there was no one-to-one analog across the classifications. The Iongleaf pine forest community type stood out as the exception： it was the only class with strong analogs across all classifications. Analogs were most lacking for forest community types with species that occurred across a range of geographic and environmental conditions, such as Ioblolly pine types, indicator species metrics were generally high for the USNVC, suggesting that LJSNVC classes are floristically well-defined. The empirical classification was best predicted by environmental variables. The most important predictors differed slightly but were broadly similar across all classifications, and included slope, amount of forest in the surrounding landscape, average minimum temperature, and other climate variables. Conclusions： The classifications have similarities and differences that reflect their differing approaches and Dbjectives. They are most consistent for forest community types that occur in a relatively narrow range of Invironmental conditions, and differ most for types with wide-ranging tree species. Environmental variables at variety of scales were important for predicting all classifications, though strongest for the empirical and FIA, guggesting that each is useful for studying how forest communities respond to of multi-scale environmental processes, including global change drivers.展开更多
Canopy gaps play a significant role in maintaining structure and composition of tropical forests. This study was carried out in tropical evergreen forests of central Western Ghats in India to understand the influence ...Canopy gaps play a significant role in maintaining structure and composition of tropical forests. This study was carried out in tropical evergreen forests of central Western Ghats in India to understand the influence of canopy gap size and the relationship of gap regime attributes to diversity measures and regeneration. The average gap size in the study area was found to be 396 m2 and around half of gaps were 4–8 years old. Gaps created by natural single tree fall were smaller in size but significantly higher in number. Diversity and regeneration of woody species were compared with canopy gaps and intact vegetation. Species richness and diversity was higher in gaps than in intact vegetation. Macaranga peltata, a shade intolerant species dominated gaps while intact vegetation was dominated by shade tolerant Kingiodendron pinnatum.Gap size significantly influenced species diversity and regeneration. Gap area and age were significantly and negatively correlated with diversity measures but positively correlated with regeneration. Among all the attributes of gaps, regeneration was significantly positively correlated with light intensity. Gaps maintained species diversity and favored regeneration of woody species. In addition to gap size and age, other gap ecological attributes also affected species diversity and regeneration.展开更多
Forest management planning often relies on Airborne Laser Scanning(ALS)-based Forest Management Inventories(FMIs)for sustainable and efficient decision-making.Employing the area-based(ABA)approach,these inventories es...Forest management planning often relies on Airborne Laser Scanning(ALS)-based Forest Management Inventories(FMIs)for sustainable and efficient decision-making.Employing the area-based(ABA)approach,these inventories estimate forest characteristics for grid cell areas(pixels),which are then usually summarized at the stand level.Using the ALS-based high-resolution Norwegian Forest Resource Maps(16 m×16 m pixel resolution)alongside with stand-level growth and yield models,this study explores the impact of three levels of pixel aggregation(standlevel,stand-level with species strata,and pixel-level)on projected stand development.The results indicate significant differences in the projected outputs based on the aggregation level.Notably,the most substantial difference in estimated volume occurred between stand-level and pixel-level aggregation,ranging from-301 to+253 m^(3)·ha^(-1)for single stands.The differences were,on average,higher for broadleaves than for spruce and pine dominated stands,and for mixed stands and stands with higher variability than for pure and homogenous stands.In conclusion,this research underscores the critical role of input data resolution in forest planning and management,emphasizing the need for improved data collection practices to ensure sustainable forest management.展开更多
Taking the communities of the sample sites in Aershan of Inner Mongolia as an investigation object, the indices affecting plant diversity were studied. The investigation was carried out in three different forest types...Taking the communities of the sample sites in Aershan of Inner Mongolia as an investigation object, the indices affecting plant diversity were studied. The investigation was carried out in three different forest types （natural forests, plantations and regenerated forests after fire）. Results show that 95 plant species belonging to 19 families and 50 genera were identified in total. Of these species, nine were arbors, six were shrubs and the other 80 were herbs. We found some differences in the dominant species of different layers in three forest types. Natural forests had the largest importance value for the total number of species, followed by plantations and regenerated forests after fire. Plantations and natural forests had a similar change in richness indices. The largest value of richness indices was obtained in natural forests, while the lowest value was in regenerated forests after fire. Three diversity indices （Simpson＇s, Shannon-Wiener and Pielou＇s indices） indicate a similar trend in all sample plots. With an increase in elevation, values of diversity indices first increased and then decreased. In different forest types, similarity between natural forests was largest, while similarity between the regenerated forests and plantations was lowest.展开更多
Pine wilt disease caused by pine wood nema-todes is a deadly disease of the genus Pinus requiring strong quarantine measures.Since its discovery,it has been widely distributed throughout the world.China is one of the ...Pine wilt disease caused by pine wood nema-todes is a deadly disease of the genus Pinus requiring strong quarantine measures.Since its discovery,it has been widely distributed throughout the world.China is one of the coun-tries with a severe rate of infections due to its abundant pine resources.In this study,nematode-trapping fungi were collected from pine trees in Ninghai City,Zhejiang Prov-ince,which is the key area of pine wilt control in Febru-ary,May,September,October and November.The results showed that nematode-trapping fungi of pine are abundant,especially the number and species detected in each month and are quite different;species of fungi in July,Septem-ber and November were more numerous and had higher separation rates.The dominant species in November was Arthrobotrys oligospora followed by Arthrobotrys cladodes;July and September it was A.cladodes.In each part of the tree,A.cladodes was the most widely distributed with a high separation rate.Therefore,it is the dominant fungal species in the area.Arboreal Bursaphelenchus xylophilus-trapping fungi are dependent on pine wood nematodes,and none were isolated from healthy pine trees.More arboreal B.xylophilus-trapping fungi were found under the bark than in the xylem.There is a close relationship between arboreal B.xylophilus-trapping fungi and pine wood nematodes.How to make use of these resources to reduce the damage of pine wood nematode fusarium is the focus of future research.展开更多
Forests in Northeast China in the Greater and Lesser Khingan Mountains(GKM and LKM)account for nearly 1/3 of the total state-owned forests in the country.Regional and historical comparisons of forest plants and macrof...Forests in Northeast China in the Greater and Lesser Khingan Mountains(GKM and LKM)account for nearly 1/3 of the total state-owned forests in the country.Regional and historical comparisons of forest plants and macrofungi will favor biological conservation,forest management and economic development.A total of 1067 sampling plots were surveyed on forest composition and structure,with a macrofungi survey at Liangshui and Huzhong Nature Reserves in the center of two regions.Regional and historical differences of these parameters were analyzed with a redundancy ordination of their complex associations.There were 61-76 families,189-196 genera,and 369-384 species,which was only 1/3 of the historical records.The same dominant species were larch and birch with Korean pine(a climax species)less as expected from past surveys in the LKM.Shrub and herb species were different in the two regions,as expected from historical records.There was 10-50%lower species diversity(except for herb evenness),but 1.8-to 4-time higher macrofungi diversity in the GKM.Compared with the LKM,both tree heights and macrofungi density were higher.Nevertheless,current heights averaging 10 m are half of historical records(>20 m in the 1960s).Edible macrofungi were the highest proportion in both regions,about twice that of other fungal groups,hav-ing important roles in the local economy.A major factor explaining plant diversity variations in both regions was herb cover,followed by shrubs in the GKM and herb-dominant species in the LKM.Factors responsible for macrofungi variations were tree density and shrub height.Vaccinium vitis-idaea and Larix gmelinii in the GKM but tree size and diversity were important factors in the LKM.Our findings highlighted large spatial and historical differences between the GKM and LKM in plant-macrofungal composition,forest structure,and their complex associations,which will favor precise conservation and management of forest resources in two region in the future.展开更多
To understand the potential impact of the Three Gorges Reservoir on the aquatic ecosystem after the damming of the Yangtze River,we studied the community composition and temporal abundance distribution of algae in two...To understand the potential impact of the Three Gorges Reservoir on the aquatic ecosystem after the damming of the Yangtze River,we studied the community composition and temporal abundance distribution of algae in two types of water bodies:a segment of the Jialing River near its confluence with the Yangtze River as an example of the river-lake type,and Shuanglong Lake in Chongqing as an example of the lake type.In total,107 species belonging to 58 genera of 7 phyla were identified in the study area of the Jialing River,dominated by three groups with 49.5% diatoms,29.0% chlorophytes,and 11.4% cyanobacteria in the community composition.There were 122 species belonging to 66 genera of 8 phyla in Shuanglong Lake,dominated by the same three groups with 19.7% diatoms,48.4% chlorophytes,and 22.2% cyanobacteria.The densities of total algae and individual dominant groups were all much higher in the lake.More species of diatoms were found in the river-lake segment;whereas more chlorophyte species and cyanobacteriaum species were in the lake.There were 17 dominant species including 8 diatoms,4 chlorophytes,3 cyanobacteria and 2 cryptophytes in the river-lake segment,and 21 species in the lake,including 2 diatoms,9 chlorophytes,6 cyanobacteria,3 cryptophytes and a dinoflagellate.In eutrophic conditions,chlorophytes and cyanobacteria may proliferate in a lake-type area and diatoms may cause algal bloom in a relatively faster-flow lake-river type area.展开更多
基金supported by Biodiversity and Forest Pest Problems in Northeast China (BIOPROC)a cooperative project between Beijing Forestry University and Helsinki Universitythe Program for Changjiang Scholars and Innovative Research Team in Universities (PCSIRT0607)
文摘Taking different forests in Aershan of Inner Mongolia as sample plots, diversity and dominant species of arthropods were studied. The results show that two classes, 17 orders, 68 families, 130 species and 3742 individuals were identified and 92.31% of total species appeared in natural forests, and 75.38% of total species appeared in plantations. The orders of Lepidoptera, Coleoptera, Diptera and Hymenoptera covered most of the collected arthropods. In different forest types, diversity indices is natural mixed forests （Betula platyphylla x Larix gmelinii）〉 natural pure B. platyphylla forests〉natural pure L. gmelinii forests〉plantations with pesticide treatment〉plantations without pesticide treatment. In natural forests, more than 70% of the arthropod families, species and individuals were distributed in shrub and herb layer, while in plantations 75% of the arthropod families, 78% of species and 80% of individuals were also distributed in shrub and herb layer. Lepidoptera, including Loxostege sticticalis （Linnaeus）, Chilo suppressalis （Walker） and Lymantria dispar （Linnaeus）, had the highest dominant degree.
基金supported by the National Technology Extension Fund of Forestry,Forest Vegetation Carbon Storage Monitoring Technology Based on Watershed Algorithm ([2019]06)Fundamental Research Funds for the Central Universities (No.PTYX202107).
文摘Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.
基金Funding for this work came from the USDA Forest Service Resources Planning Act Assessment,via an agreement with North Carolina State University
文摘Background： Knowledge of the different kinds of tree communities that currently exist can provide a baseline for assessing the ecological attributes of forests and monitoring future changes. Forest inventory data can facilitate the development of this baseline knowledge across broad extents, but they first must be classified into forest community types. Here, we compared three alternative classifications across the United States using data from over 117,000 U.S. Department of Agriculture Forest Service Forest Inventory and Analysis （FIA） plots. Methods： Each plot had three forest community type labels： （1） ＂FIA＂ types were assigned by the FIA program using a supervised method; （2） ＂USNVC＂ types were assigned via a key based on the U.S. National Vegetation Classification; （3） ＂empirical＂ types resulted from unsupervised clustering of tree species information. We assessed the degree to which analog classes occurred among classifications, compared indicator species values, and used random forest models to determine how well the classifications could be predicted using environmental variables. Results： The classifications generated groups of classes that had broadly similar distributions, but often there was no one-to-one analog across the classifications. The Iongleaf pine forest community type stood out as the exception： it was the only class with strong analogs across all classifications. Analogs were most lacking for forest community types with species that occurred across a range of geographic and environmental conditions, such as Ioblolly pine types, indicator species metrics were generally high for the USNVC, suggesting that LJSNVC classes are floristically well-defined. The empirical classification was best predicted by environmental variables. The most important predictors differed slightly but were broadly similar across all classifications, and included slope, amount of forest in the surrounding landscape, average minimum temperature, and other climate variables. Conclusions： The classifications have similarities and differences that reflect their differing approaches and Dbjectives. They are most consistent for forest community types that occur in a relatively narrow range of Invironmental conditions, and differ most for types with wide-ranging tree species. Environmental variables at variety of scales were important for predicting all classifications, though strongest for the empirical and FIA, guggesting that each is useful for studying how forest communities respond to of multi-scale environmental processes, including global change drivers.
基金funded by the National Remote Sensing Centre,Hyderabad,India under NRSC-DOS-DBTGovt.of India project entitled‘‘Biodiversity Characterization in Southern parts of Karnataka’’(Project Number:UAS(B)/DR/GOI/245/2011-12)
文摘Canopy gaps play a significant role in maintaining structure and composition of tropical forests. This study was carried out in tropical evergreen forests of central Western Ghats in India to understand the influence of canopy gap size and the relationship of gap regime attributes to diversity measures and regeneration. The average gap size in the study area was found to be 396 m2 and around half of gaps were 4–8 years old. Gaps created by natural single tree fall were smaller in size but significantly higher in number. Diversity and regeneration of woody species were compared with canopy gaps and intact vegetation. Species richness and diversity was higher in gaps than in intact vegetation. Macaranga peltata, a shade intolerant species dominated gaps while intact vegetation was dominated by shade tolerant Kingiodendron pinnatum.Gap size significantly influenced species diversity and regeneration. Gap area and age were significantly and negatively correlated with diversity measures but positively correlated with regeneration. Among all the attributes of gaps, regeneration was significantly positively correlated with light intensity. Gaps maintained species diversity and favored regeneration of woody species. In addition to gap size and age, other gap ecological attributes also affected species diversity and regeneration.
文摘Forest management planning often relies on Airborne Laser Scanning(ALS)-based Forest Management Inventories(FMIs)for sustainable and efficient decision-making.Employing the area-based(ABA)approach,these inventories estimate forest characteristics for grid cell areas(pixels),which are then usually summarized at the stand level.Using the ALS-based high-resolution Norwegian Forest Resource Maps(16 m×16 m pixel resolution)alongside with stand-level growth and yield models,this study explores the impact of three levels of pixel aggregation(standlevel,stand-level with species strata,and pixel-level)on projected stand development.The results indicate significant differences in the projected outputs based on the aggregation level.Notably,the most substantial difference in estimated volume occurred between stand-level and pixel-level aggregation,ranging from-301 to+253 m^(3)·ha^(-1)for single stands.The differences were,on average,higher for broadleaves than for spruce and pine dominated stands,and for mixed stands and stands with higher variability than for pure and homogenous stands.In conclusion,this research underscores the critical role of input data resolution in forest planning and management,emphasizing the need for improved data collection practices to ensure sustainable forest management.
基金supported by Biodiversity and Forest Pest Problems in northeast China (BIOPROC)a cooperative project between Beijing Forestry University and Helsinki Universitythe Program for Changjiang Scholars and Innovative Research Team in Universities (PCSIRT0607)
文摘Taking the communities of the sample sites in Aershan of Inner Mongolia as an investigation object, the indices affecting plant diversity were studied. The investigation was carried out in three different forest types （natural forests, plantations and regenerated forests after fire）. Results show that 95 plant species belonging to 19 families and 50 genera were identified in total. Of these species, nine were arbors, six were shrubs and the other 80 were herbs. We found some differences in the dominant species of different layers in three forest types. Natural forests had the largest importance value for the total number of species, followed by plantations and regenerated forests after fire. Plantations and natural forests had a similar change in richness indices. The largest value of richness indices was obtained in natural forests, while the lowest value was in regenerated forests after fire. Three diversity indices （Simpson＇s, Shannon-Wiener and Pielou＇s indices） indicate a similar trend in all sample plots. With an increase in elevation, values of diversity indices first increased and then decreased. In different forest types, similarity between natural forests was largest, while similarity between the regenerated forests and plantations was lowest.
基金The work was supported by the Fundamental Research Funds for the Central University(No.2572020DY11).
文摘Pine wilt disease caused by pine wood nema-todes is a deadly disease of the genus Pinus requiring strong quarantine measures.Since its discovery,it has been widely distributed throughout the world.China is one of the coun-tries with a severe rate of infections due to its abundant pine resources.In this study,nematode-trapping fungi were collected from pine trees in Ninghai City,Zhejiang Prov-ince,which is the key area of pine wilt control in Febru-ary,May,September,October and November.The results showed that nematode-trapping fungi of pine are abundant,especially the number and species detected in each month and are quite different;species of fungi in July,Septem-ber and November were more numerous and had higher separation rates.The dominant species in November was Arthrobotrys oligospora followed by Arthrobotrys cladodes;July and September it was A.cladodes.In each part of the tree,A.cladodes was the most widely distributed with a high separation rate.Therefore,it is the dominant fungal species in the area.Arboreal Bursaphelenchus xylophilus-trapping fungi are dependent on pine wood nematodes,and none were isolated from healthy pine trees.More arboreal B.xylophilus-trapping fungi were found under the bark than in the xylem.There is a close relationship between arboreal B.xylophilus-trapping fungi and pine wood nematodes.How to make use of these resources to reduce the damage of pine wood nematode fusarium is the focus of future research.
基金This work was supported by the National Natural Science Foundation of China(Grant No.41730641)Project from Ministry of Science and Technology of China(Basic Research project:2014FY110600 and 13-5 Project:2016YFA0600802).
文摘Forests in Northeast China in the Greater and Lesser Khingan Mountains(GKM and LKM)account for nearly 1/3 of the total state-owned forests in the country.Regional and historical comparisons of forest plants and macrofungi will favor biological conservation,forest management and economic development.A total of 1067 sampling plots were surveyed on forest composition and structure,with a macrofungi survey at Liangshui and Huzhong Nature Reserves in the center of two regions.Regional and historical differences of these parameters were analyzed with a redundancy ordination of their complex associations.There were 61-76 families,189-196 genera,and 369-384 species,which was only 1/3 of the historical records.The same dominant species were larch and birch with Korean pine(a climax species)less as expected from past surveys in the LKM.Shrub and herb species were different in the two regions,as expected from historical records.There was 10-50%lower species diversity(except for herb evenness),but 1.8-to 4-time higher macrofungi diversity in the GKM.Compared with the LKM,both tree heights and macrofungi density were higher.Nevertheless,current heights averaging 10 m are half of historical records(>20 m in the 1960s).Edible macrofungi were the highest proportion in both regions,about twice that of other fungal groups,hav-ing important roles in the local economy.A major factor explaining plant diversity variations in both regions was herb cover,followed by shrubs in the GKM and herb-dominant species in the LKM.Factors responsible for macrofungi variations were tree density and shrub height.Vaccinium vitis-idaea and Larix gmelinii in the GKM but tree size and diversity were important factors in the LKM.Our findings highlighted large spatial and historical differences between the GKM and LKM in plant-macrofungal composition,forest structure,and their complex associations,which will favor precise conservation and management of forest resources in two region in the future.
基金Funded by the Natural Science Foundation of China (No.50178070)the Natural Science Foundation of Chongqing (Nos. 8091 and 7136)
文摘To understand the potential impact of the Three Gorges Reservoir on the aquatic ecosystem after the damming of the Yangtze River,we studied the community composition and temporal abundance distribution of algae in two types of water bodies:a segment of the Jialing River near its confluence with the Yangtze River as an example of the river-lake type,and Shuanglong Lake in Chongqing as an example of the lake type.In total,107 species belonging to 58 genera of 7 phyla were identified in the study area of the Jialing River,dominated by three groups with 49.5% diatoms,29.0% chlorophytes,and 11.4% cyanobacteria in the community composition.There were 122 species belonging to 66 genera of 8 phyla in Shuanglong Lake,dominated by the same three groups with 19.7% diatoms,48.4% chlorophytes,and 22.2% cyanobacteria.The densities of total algae and individual dominant groups were all much higher in the lake.More species of diatoms were found in the river-lake segment;whereas more chlorophyte species and cyanobacteriaum species were in the lake.There were 17 dominant species including 8 diatoms,4 chlorophytes,3 cyanobacteria and 2 cryptophytes in the river-lake segment,and 21 species in the lake,including 2 diatoms,9 chlorophytes,6 cyanobacteria,3 cryptophytes and a dinoflagellate.In eutrophic conditions,chlorophytes and cyanobacteria may proliferate in a lake-type area and diatoms may cause algal bloom in a relatively faster-flow lake-river type area.
