Community Structure Characterization

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

The community structure and microbial linkage of rumen protozoa and methanogens in response to the addition of tea seed saponins in the diet of beef cattle

© 2020 The Author(s). Background: This study investigated changes in rumen protozoal and methanogenic communities, along with the correlations among microbial taxa and methane (CH4) production of six Belmont Red Composite beef steers fed tea seed saponins (TSS). Animals were fed in three consecutive feeding periods, a high-grain basal diet for 14 d (BD period) then a period of progressive addition of TSS to the basal diet up to 30 g/d for 20 d (TSS period), followed by the basal diet for 13 d without TSS (BDP post-control period). Results: The study found that TSS supplementation decreased the amount of the protozoal genus Entodinium and increased Polyplastron and Eudiplodinium genera. During BDP period, the protozoa community of steers did not return to the protozoal profiles observed in BD period, with higher proportions of Metadinium and Eudiplodinium and lower Isotricha. The addition of TSS was found to change the structure of methanogen community at the sub-genus level by decreasing the abundance of methanogens in the SGMT clade and increasing the abundance of methanogens in the RO clade. The correlation analysis indicated that the abundance of SGMT clade methanogens were positively correlated with Isotricha, and Isotricha genus and SGMT clade methanogens were positively correlated with CH4 production. While RO clade were positively correlated with the proportion of Metadinium genus, which was negatively correlated with CH4 emission. Conclusions: These results suggest that different genera of rumen protozoa ciliates appear to be selectively inhibited by TSS, and the change in methanogen community at the subgenus level may be due to the mutualistic relationships between methanogens and rumen ciliates

Community Structure in Jazz

Using a database of jazz recordings we study the collaboration network of jazz musicians. We define the network at two different levels. First we study the collaboration network between individuals, where two musicians are connected if they have played in the same band. Then we consider the collaboration between bands, where two bands are connected if they have a musician in common. The community structure analysis reveals that these constructions capture essential ingredients of the social interactions between jazz musicians. We observe correlations between recording locations, racial segregation and the community structure. A quantitative analysis of the community size distribution reveals a surprising similarity with an e-mail based social network recently studied.Comment: 12 pages, 6 figures, Revtex4 format, Acknowledgments update

Comparing community structure identification

We compare recent approaches to community structure identification in terms of sensitivity and computational cost. The recently proposed modularity measure is revisited and the performance of the methods as applied to ad hoc networks with known community structure, is compared. We find that the most accurate methods tend to be more computationally expensive, and that both aspects need to be considered when choosing a method for practical purposes. The work is intended as an introduction as well as a proposal for a standard benchmark test of community detection methods.Comment: 10 pages, 3 figures, 1 table. v2: condensed, updated version as appears in JSTA

The Community Structure of Collembola in Three Habitats Type Along the Upstream Brantas River Basin of Batu City

Collembola is one of a group of animals that generally live on the surface and in the soil. Collembola have an important role in the ecosystem due to its function as a consumer subsystem and decomposition subsystem that can be used as bio-indicators. Changing in habitat in the upstream of Brantas River Basin is cause disruption for Collembola community. This is a descriptive research, aims to uncover the information of community structure, including the type found, diversity, evenness, and relative abundance of Collembola in three type habitats (forest, agricultural, and residential). Soil sampling conducted in each habitat type using TBSF methods. Identification of Collembola samples conducted at the Biology Laboratory of UMM and verified at Basic Entomology Laboratory, Gadjah Mada University. This study results are; (1) the number of Collembola were found in forest were 21, agriculture were 5, and residential were 17. (2) There is difference in descriptive diversity of Collembola in forest, agricultural, and residential. Collembola species diversity index of forest higher (2.78) compared to agriculture (1.16) and residential (2.42). Forest and residential habitat have moderate diversity, while agriculture has a low diversity. (3) There is difference in descriptive evenness of Collembola in forest, agricultural, and residential. Evenness index Collembola in forest was higher (0.91) than agriculture (0.72) and residential (0.85). Evenness of Collembola in residential is higher than agriculture. All types of habitat, including having a high evenness. (4) There are differences in the relative abundance of descriptive Collembola in forest, agricultural, and residential. Relative abundance of forest, agricultural, and residential varied. The highest relative abundance in forest is Hypogastrura consanguinea, Ascocyrtus sp, and Homidia cingula. The highest relative abundance in agriculture is Pseudachorutes javanicus, Isotomurus palustris, and Ascocyrtus sp. The highest relative abundance in residential is Ascocyrtus sp., Cryptopygus thermophilus, and Isotomurus palustris