Biotic filtering and mass effects in small shrub patches: is arthropod community structure predictable based on the quality of the vegetation?

We evaluated qualitatively and quantitatively the community structure of aquatic insects (Ephemeroptera, Plecoptera, and Trichoptera) in 19 streams in areas of Cerrado in the Paraguay, Paraná, and São Francisco river basins. The number of genera and taxonomic composition were compared at spatial (at the hydrographic basins level) and conservation levels (more preserved and less preserved areas). The influence of spatial and environmental factors in richness and abundance was also evaluated. The geographical distribution of Grumicha, Coryphorus, and Austrotinodes was expanded. The highest Trichoptera richness was found in the São Francisco river basin (F = 5,602, p = 0,004) and a higher number of Ephemeroptera genera occurred in the relatively less preserved sites (F = 6,835, p = 0,009). The pattern of genera distribution was different among basins (R = 0,0336, p = 0,001), but it was similar among relatively less and more preserved areas (R = -0,039, p = 0,737). These findings can be explained by the low impact level in these streams and also by the taxonomic resolution used in this study. Latitude and instream diversity were the most important factors to explain the variation in genera richness and abundance (p = 0.004 and p = 0.026, respectively). Hence, the regional differences can be attributed to spatial influences, quantity or quality of habitats and the original distribution of taxa within each basin.

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Does genomic variation in a foundation species predict arthropod community structure in a riparian forest?

Molecular Ecology ◽

10.1111/mec.14515 ◽

2018 ◽

Vol 27 (5) ◽

pp. 1284-1295 ◽

Cited By ~ 9

Author(s):

Shinnosuke Kagiya ◽

Masaki Yasugi ◽

Hiroshi Kudoh ◽

Atsushi J. Nagano ◽

Shunsuke Utsumi

Keyword(s):

Community Structure ◽

Riparian Forest ◽

Genomic Variation ◽

Foundation Species ◽

Arthropod Community

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The phenology and intrinsic quality of wild crucifers that determine the community structure of their herbivorous insects

Researches on Population Ecology ◽

10.1007/bf02513589 ◽

1993 ◽

Vol 35 (2) ◽

pp. 151-170 ◽

Cited By ~ 19

Author(s):

Shuichi Yano ◽

Naota Ohsaki

Keyword(s):

Community Structure ◽

Herbivorous Insects ◽

Intrinsic Quality

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Detecting communities from networks based on their intrinsic properties

International Journal of Modern Physics C ◽

10.1142/s0129183119501043 ◽

2019 ◽

Vol 30 (12) ◽

pp. 1950104 ◽

Cited By ~ 1

Author(s):

Haijuan Yang ◽

Jianjun Cheng ◽

Mingwei Leng ◽

Xing Su ◽

Wenbo Zhang ◽

...

Keyword(s):

Community Structure ◽

Intrinsic Properties ◽

Structure Quality ◽

Novel Method ◽

The Common ◽

Influential Nodes ◽

High Quality Result ◽

Full Utilization ◽

Entire Procedure

Communities in networks expose some intrinsic properties, each of them involves some influential nodes as its cores, around which the entire community grows gradually; the more the common neighbors that exist between a pair of nodes, the larger the possibility of belonging to the same community; the more the neighbors of any one node belong to a community, the larger the possibility that node belongs to that community too. In this paper, we present a novel method, which makes full utilization of these intrinsic properties to detect communities from networks. We iteratively select the node with the largest degree from the remainder of the network as the first seed of a community, then consider its first- and second-order neighbors to identify other seeds of the community, then expand the community by attracting nodes whose large proportion of neighbors have been in the community to join. In this way, we obtain a series of communities. However, some of them might be too small to make sense. Therefore, we merge some of the initial communities into larger ones to acquire the final community structure. In the entire procedure, we try to keep nodes in every community to be consistent with the properties as possible as we can, this leads to a high-quality result. Moreover, the proposed method works with a higher efficiency, it does not need any prior knowledge about communities (such as the number or the size of communities), and does not need to optimize any objective function either. We carry out extensive experiments on both some artificial networks and some real-world networks to testify the proposed method, the experimental results demonstrate that both the efficiency and the community-structure quality of the proposed method are promising, our method outperforms the competitors significantly.

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Community structure of arboreal and soil-dwelling arthropods in three different rice planting indexes in freshwater swamps of South Sumatra, Indonesia

Biodiversitas Journal of Biological Diversity ◽

10.13057/biodiv/d211050 ◽

2020 ◽

Vol 21 (10) ◽

Author(s):

Tili Karenina ◽

Siti Herlinda ◽

Chandra Irsan ◽

Yulia Pujiastuti ◽

Hasbi Hasbi ◽

...

Keyword(s):

Community Structure ◽

Species Diversity ◽

Rice Fields ◽

Herbivorous Insects ◽

Arthropod Community ◽

Pitfall Traps ◽

Sogatella Furcifera ◽

Pardosa Pseudoannulata ◽

Arthropod Species ◽

Predatory Arthropods

Abstract. Karenina T, Herlinda S, Irsan C, Pujiastuti Y, Hasbi, Suparman, Lakitan B, Hamidson H, Umayah A. 2020. Community structure of arboreal and soil-dwelling arthropods in three different rice planting indexes in freshwater swamps of South Sumatra, Indonesia. Biodiversitas 21: 4839-4849. Differences in the index of rice planting can cause differences in the structure of the arthropod community. This study aimed to characterize the community structure of the arboreal and soil-dwelling arthropods in the three different rice planting indexes (PI) in the freshwater swamps of South Sumatra. Sampling of the arthropods using D-vac and pitfall traps was conducted in the three different rice planting, namely one (PI-100), two (PI-200), and three (PI-300) planting indexes of the rice. The results of the study showed that the dominant predatory arthropod species in the rice fields were Pardosa pseudoannulata, Tetragnatha javana, Tetragnatha virescens, Pheropsophus occipitalis, Paederus fuscipes, and the dominant herbivorous insects were Leptocorisa acuta, Nilavarpata lugens, and Sogatella furcifera. The abundance of arboreal predatory arthropods was the highest in the PI-300 rice and the lowest in the PI-100 rice. The abundance of soil-dwelling arthropods was the highest in the rice PI-100, and low in the rice PI-200 and PI-300, but the rice PI-100 had the highest abundance of the herbivorous insects. The rice PI-300 was the most ideal habitats to maintain the abundance and the species diversity of the arboreal predatory arthropods. Thus, the rice cultivation throughout the year was profitable in conserving and maintaining the abundance and species diversity of the predatory arthropods.

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Aboveground and belowground arthropod communities experience different relative influences of stochastic and deterministic assembly processes following disturbance

10.7287/peerj.preprints.1674v1 ◽

2016 ◽

Author(s):

Scott Ferrenberg ◽

Alexander S. Martinez ◽

Akasha M. Faist

Keyword(s):

Community Structure ◽

Stochastic Processes ◽

Community Assembly ◽

Tree Mortality ◽

Species Turnover ◽

Mineral Soil ◽

Relative Influence ◽

Subalpine Forest ◽

Arthropod Community ◽

Arthropod Communities

Background. Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods. Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species) and belowground (species active in organic and mineral soil layers) arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community) and modified Winkler funnels (belowground community) and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies diversity and assemblages. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models calculated from observed vs. expected levels of species turnover (Beta diversity) among samples. Results. Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the aboveground arthropod communities and vegetation and soil properties, but no significant association among belowground arthropod communities and environmental factors. Discussion. Our results suggest context-dependent influences of stochastic and deterministic community assembly processes across different fractions of a ground-dwelling arthropod community following a disturbance. This variation in assembly may be linked to contrasting ecological strategies and dispersal rates within above- and below-ground communities. Our findings add to a growing body of evidence indicating concurrent influences of different processes in community assembly, and highlight the need to consider potential variation across different fractions of biotic communities when testing community ecology theory.

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A Seed-Expanding Method Based on TOPSIS for Community Detection in Complex Networks

Complexity ◽

10.1155/2020/9017239 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Jianjun Cheng ◽

Wenbo Zhang ◽

Haijuan Yang ◽

Xing Su ◽

Tao Ma ◽

...

Keyword(s):

Decision Making ◽

Community Structure ◽

Community Detection ◽

Centrality Measures ◽

Ideal Solution ◽

Centrality Measure ◽

Detection Algorithms ◽

Pros And Cons ◽

Topsis Technique

The centrality plays an important role in many community-detection algorithms, which depend on various kinds of centralities to identify seed vertices of communities first and then expand each of communities based on the seeds to get the resulting community structure. The traditional algorithms always use a single centrality measure to recognize seed vertices from the network, but each centrality measure has both pros and cons when being used in this circumstance; hence seed vertices identified using a single centrality measure might not be the best ones. In this paper, we propose a framework which integrates advantages of various centrality measures to identify the seed vertices from the network based on the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) multiattribute decision-making technology. We take each of the centrality measures involved as an attribute, rank vertices according to the scores which are calculated for them using TOPSIS, and then take vertices with top ranks as the seeds. To put this framework into practice, we concretize it in this paper by considering four centrality measures as attributes to identify the seed vertices of communities first, then expanding communities by iteratively inserting one unclassified vertex into the community to which its most similar neighbor belongs, and the similarity between them is the largest among all pairs of vertices. After that, we obtain the initial community structure. However, the amount of communities might be much more than they should be, and some communities might be too small to make sense. Therefore, we finally consider a postprocessing procedure to merge some initial communities into larger ones to acquire the resulting community structure. To test the effectiveness of the proposed framework and method, we have performed extensive experiments on both some synthetic networks and some real-world networks; the experimental results show that the proposed method can get better results, and the quality of the detected community structure is much higher than those of competitors.

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