Tree species diversity and stand structure along major community types in lowland primary and secondary moist deciduous forests in Tripura,Northeast India

Tree species diversity and population structure at different community types were described and analyzed for primary and secondary lowland moist deciduous forests in Tripura. Overall 10,957 individual trees belonging to 46 family, 103 genera and 144 species were counted at ≥30 cm DBH （diameter at breast height） using 28 permanent belt transects with a size of 1 ha （10 m × 1000 m）. Four different tree communities were identified. The primary forests was dominated by Shorea robusta （mean density 464.77 trees.ha^-1, 105 species） and Schima wallichii （336.25 trees.ha^-1, 82 species）, while the secondary forests was dominated by Tectona grandis （333.88 trees.ha^-1, 105 species） and Hevea brasiliensis （299.67 trees.ha^-1, 82 species）. Overall mean basal area in this study was 18.01m2.ha^-1; the maximum value was recorded in primary Shorea forest （26.21 m2.ha^-1）. Mean density and diversity indices were differed significantly within four different communities. No significant differences were observed in number of species, genera, family and tree basal cover area. Significant relationships were found between the species richness and different tree population groups across the communities. Results revealed that species diversity and density were increased in those forests due to past disturbances which resulted in slow accumu- lation of native oligarchic small tree species. Seventeen species were recorded with 〈2 individuals of which Saraca asoka （Roxb.） de Wilde and Entada phaseoloides （L.） Men＇. etc. extensively used in local ethnomedicinal formulations. The present S. robusta Gaertn dominated forest was recorded richer （105 species） than other reported studies. Moraceae was found more speciose family instead of Papilionaceae and Euphorbiaceae than other Indian moist deciduous forests. Seasonal phenological gap in such moist deciduous forests influenced the population of Trachypithecus pileatus and capped langur. The analysis of FIV suggested a slow trend of shifting the population of Lamiaceae group by Moraceae species in secondary T. grandis L. dominated community.

Effects of Plant Community Type on Soil Methane Flux in Semiarid Loess Hilly Region,Central Gansu Province,China

Methane(CH_(4))is an important greenhouse gas second only to CO_(2)in terms of its greenhouse effect.Vegetation plays an important role in controlling soil CH_(4)fluxes,but the spatial variability of soil CH_(4)fluxes during vegetation restoration in Loess Hilly Region(LHR)is not fully understood.The effects of different plant community types[Medicago sativa grassland(MS);Xanthoceras sorbifolium forestland(XS);Caragana korshinskii bushland(CK);Hippophae rhamnoides shrubland(HR);and Stipa bungeana grassland(SB)]on soil CH_(4)flux in LHR were studied via the static chamber technique.The results showed that the five plant community types were sinks of soil CH_(4)in LHR,the plant community type significantly affected the soil CH_(4)flux,and the average CH_(4)uptake from high to low was in SB,HR,CK,MS,and XS.During the whole study period,the soil CH_(4)flux showed similar interannual variation.The maximum absorption of soil CH_(4)appeared in the growing season,while the minimum appeared in winter.Soil CH_(4)uptake was positively correlated with soil temperature and soil moisture.Soil temperature and moisture are important controlling factors for the temporal variability of soil CH_(4)flux.In LHR,the Stipa bungeana grassland is the more suitable plant community type for reducing soil CH_(4)emissions.In the process of vegetation restoration in LHR,the soil CH_(4)absorption potential of different plant community types should be considered,ecological benefits should be taken into account,and vegetation more suitable for mitigating the greenhouse effect should be selected.

Two community types occur in gut microbiota of large-sample wild plateau pikas(Ochotona curzoniae)

Studies on large-sample gut microbial sequencing data indicate that gut microbiota can be divided into multiple community types;different community types may influence the community function and ecosystem service.However,the knowledge on the classification,diversity,interaction,and assembling of microbial community types in the gut of wild animals is still insufficient.Here,we used pika gut microbiota data as an example to study the microbial community types in large-sample sequencing dataset.Cecal microbial communities from 118 wild plateau pika(Ochotona curzoniae)individuals at 5 elevational regions on the Qinghai–Tibet Plateau were analyzed.Our results show that pika gut microbiota can be separated into 2 community types(Cluster I and Cluster II).Cluster I was mainly distributed on the high-elevation regions with more than 3694 m and was most dominated by Firmicutes.Cluster II was from the low-elevation areas(lower than 3580 m),and was predominated by Bacteroidetes.Cluster I had a higher community alpha-diversity and predicted functional diversity than Cluster II,and the betadiversity and predicted functional profiles of these 2 clusters were significantly different.Network analysis revealed that there were more complex interactions between Cluster I,which had enhanced influence on the co-occurrences of other microbes in the bacterial community when compared to Cluster II.Phylogenetic analysis found that the environmental filtering in the Cluster I was stronger than Cluster II.The assemblages of pika gut bacterial communities were determined mainly by deterministic processes,while the relative importance of deterministic processes accounted for more percentages in the Cluster I than Cluster II.Our results demonstrated that 2 gut microbial community types in pikas had distinct diversity patterns and ecological functions.Current methods are also helpful for identifying gut community types and the related mechanisms behind gut microbiota types in large-sample sequencing data of wild animals.

Plant community and ecological analysis of woodland vegetation in Metema Area,Amhara National Regional State,Northwestern Ethiopia

We studied woodland vegetation in broad-leaved deciduous woodlands of Metema in northwestern Amhara regional state, Ethiopia to determine plant community types and species distribution patterns and their relationships with environmental variables, including altitude, pH, cation exchange capacity, electrical conductivity （EC）, and moisture. We used a selective approach with a systematic sampling design. A total of 74 quadrats, each 25m × 25m at intervals of 150-200 m were sampled along the established transect lines. For herbaceous vegetation and soil data collection, five subquadrats each lm x lm were established at the four corners and the center of each quadrat. Three community types were identified using TWINSPAN analysis. All three community types showed high diversity （Shannon-Weiner index）, the highest in community type II at 3.55. The highest similarity coefficient was 0.49 （49%） between community types II and III, reflecting 0.51 （51%） dissimilarity in their species richness. The canonical correspondence ordination diagram revealed that the distribution pattern of community type I was explained by moisture while that of community types III and II was explained by EC and altitude and moisture, respectively. Altitude was the most statistically significant environmental variable, followed by moisture and EC in determining the total variation in species composition and distribution patterns while pH and cation exchange capacity were non significant. In conclusion, we recommend that any intervention should take into account these three discrete community types and their environmental settings to make the intervention more successful.

Collaborative information seeking: An investigation of community members' behavior

Purpose： This article reports on an experiment that tested community members＇ collaborative information seeking （CIS） behavior, with an emphasis on how community type and task difficulty can affect user behavior and user awareness in collaboration.Design/methodology/approach： We carried out a laboratory study with 18 participants in 9 pairs using an experimental CIS system. Data were collected from questionnaires, Web logs and semi-structured interviews. Descriptive statistics and two-way analysis of variance （ANOVA） were used for data analysis. Findings： Compared with non-community members, community participants had a better understanding of search tasks and were aware of the ways of completing tasks successfully. They did not depend on the information retrieval system when constructing search queries and would adopt diversified cooperation strategies. They were more likely to recommend information to their partners. However, no significant difference was found between subject- based community and interest-based community in CIS practices and user awareness in collaboration. In addition, task difficulty only influenced user preference of issuing queries and confidence of completing search tasks. Research limitations： Our work was limited by the community type we chose and the small group size, which could affect the generalizability of our findings and should be addressed in future studies. Practical implications： The study results will help inform information system designers as they design collaborative systems to facilitate social communication in the information seeking process. Originality/value： Few studies have investigated community participants＇ information seeking practices. This study provides insights into community-based CIS behavior. The findings will help us understand social interactions among community members during their information seeking process.

Responses of arid plant species diversity and composition to environmental factors

An oasis is a unique natural landscape in arid and semi-arid areas,significant for regulating regional microclimates and hydrological processes in deserts.However,little is known regarding the response of natural oasis plants communities to various environmental factors.Nineteen sample plots(50 m×50 m)were selected in the Daliyabuyi Oasis in the Taklimakan Desert hinterland based on the location of groundwater monitoring wells and 76 vegetation quadrats(25 m×25 m)were established.A two-way indicator species analysis,Mantel test,detrended correspondence analysis,canonical correspondence analysis(CCA),and hierarchical partitioning were used to provide an in-depth analysis of community classification,species composition,and environmental interpretation of the oasis.A generalized linear model was used to verify the results which showed that the current oasis community could be divided into four types according to the dominant species,which is controlled by soil moisture.Measurement of species composition and distribution of communities showed significant differences between species diversity of individual community types.Variations in groundwater depth affects patterns of species diversity which is sensitive to richness,while the degree of surface water disturbance affects the pattern of species evenness.Moreover,the CCA ordination map showed that community distribution and diversity characteristics have their own preferences in habitat gradients.The study concluded that the species dominance of the community and the composition and distribution are not dominated by a single factor.There are differences in the scale and effect of different water resource types in maintaining community characteristics.

Species Composition and Diversity of Fagus longipetiolata in Leigong Mountain, Guizhou Province

[Objectives]To understand the species composition and diversity of Fagus longipetiolata community.[Methods]The F.longipetiolata community in Guizhou Province was investigated by typical plot method.[Results]There were 107 species of vascular plants belonging to 79 genera and 51 families in Leigong Mountain F.longipetiolata community,including 3 species of pteridophytes belonging to 3 genera and 3 families,104 species of spermatophytes belonging to 76 genera and 48 families,including 3 species of gymnosperms belonging to 3 genera and 3 families,and 101 species of angiosperms belonging to 73 genera and 45 families.The types of Leigong Mountain F.longipetiolata community were divided into 7 formations,and the top 10 important species of each formation were Fagaceae,followed by Lauraceae and Ericaceae.The change trend of tree layer richness index was formation I>formation IV>formation VI>formation III>formation VII>formation II>formation V;the dominance index was formation I>formation IV>formation V>formation VI>formation VII>formation III>formation II;H diversity index was formation V>formation II>formation I>formation III>formation VII>formation VI>formation IV;the evenness index is formation II>formation III>formation VI>formation VII>formation IV>formation I>formation V;the total diversity index of the community,formation I(3.67)was the highest,formation V(2.74)was the lowest,manifested as formation I>formation III>formation VI>formation II>formation IV>formation VII>formation V.[Conclusions]The community stability is closely related to its species composition,and the background species is the basis for the survival of the community;the existence of rare species can further enhance the community diversity index and enhance the community stability.

Discovering Typed Communities in Mobile Social Networks

Mobile social networks, which consist of mobile users who communicate with each other using cell phones are reflections of people＇s interactions in social lives. Discovering typed communities （e.g., family communities or corporate communities） in mobile social networks is a very promising problem. For example, it can help mobile operators to determine the target users for precision marketing. In this paper we propose discovering typed communities in mobile social networks by utilizing the labels of relationships between users. We use the user logs stored by mobile operators, including communication and user movement records, to collectively label all the relationships in a network, by employing an undirected probabilistic graphical model, i.e., conditional random fields. Then we use two methods to discover typed communities based on the results of relationship labeling： one is simply retaining or cutting relationships according to their labels, and the other is using sophisticated weighted community detection algorithms. The experimental results show that our proposed framework performs well in terms of the accuracy of typed community detection in mobile social networks.