scholarly journals Alarm communication networks as a driver of community structure in African savannah herbivores

2019 ◽  
Vol 23 (2) ◽  
pp. 293-304 ◽  
Author(s):  
Kristine Meise ◽  
Daniel W. Franks ◽  
Jakob Bro‐Jørgensen
Keyword(s):  
Community Structure ◽  
Communication Networks ◽  
Alarm Communication

Detecting community structure by belonging intensity analysis of intermediate nodes

2019 ◽  
Vol 30 (11) ◽  
pp. 1950079
Author(s):  
Mengjia Shen ◽  
Dong Lv ◽  
Zhixin Ma
Keyword(s):  
Community Structure ◽  
Communication Networks ◽  
Community Detection ◽  
Real World ◽  
Intensity Analysis ◽  
Human Communication ◽  
Intermediate Node ◽  
Detection Algorithms ◽  
Interactive Behavior

Community structure is a common characteristic of complex networks and community detection is an important methodology to reveal the structure of real-world networks. In recent years, many algorithms have been proposed to detect the high-quality communities in real-world networks. However, these algorithms have shortcomings of performing calculation on the whole network or defining objective function and the number of commonties in advance, which affects the performance and complexity of community detection algorithms. In this paper, a novel algorithm has been proposed to detect communities in networks by belonging intensity analysis of intermediate nodes, named BIAS, which is inspired from the interactive behavior in human communication networks. More specifically, intermediate nodes are middlemen between different groups in social networks. BIAS algorithm defines belonging intensity using local interactions and metrics between nodes, and the belonging intensity of intermediate node in different communities is analyzed to distinguish which community the intermediate node belongs to. The experiments of our algorithm with other state-of-the-art algorithms on synthetic networks and real-world networks have shown that BIAS algorithm has better accuracy and can significantly improve the quality of community detection without prior information.

scholarly journals Community Structure Analysis using Fast Louvain Method in Real World Networks

2019 ◽  
Vol 8 (4) ◽  
pp. 3325-3330
Keyword(s):  
Community Structure ◽  
Complex Networks ◽  
Communication Networks ◽  
Real World ◽  
Online Social Networks ◽  
Computation Time ◽  
Greedy Method ◽  
Method Performance ◽  
Structure Detection ◽  
Hidden Patterns

Recently, in complex networks detection of Community structure has gained so much attention. It adds a lot of value to social, biological and communication networks. The community structure is a convoluted framework thus analyzing it helps in deep visualization and a better understanding of complex networks. Moreover, it also helps in finding hidden patterns, predicting link in various types of networks, recommending a product to name a few. In this context, this paper proposes an agglomerative greedy method, referred to as Fast Louvain Method (FLM), based on Jaccard cosine shared metric (JCSM) to deal with the issues of community structure detection. Specifically, Jaccard cosine shared metric (JCSM) is developed to find the similarity between the nodes in a network. We have utilized modularity quality function for assessing community quality considering the local changes in this network. We test the method performance in different real-world network datasets i.e. collaboration networks, communication networks, online social networks, as well as another miscellaneous networks. The results also determined the computation time for unveiling the communities. This proposed method gave an improved output of modularity, community goodness, along with computation time for detecting communities’ number as well as community structure. Extensive experimental analysis showed that the method outperforms the existing methods.

scholarly journals Animal soundscapes reveal key markers of Amazon forest degradation from fire and logging

2021 ◽  
Author(s):  
Danielle I. Rappaport ◽  
Anshuman Swain ◽  
William F. Fagan ◽  
Ralph Dubayah ◽  
Douglas C. Morton
Keyword(s):  
Community Structure ◽  
Communication Networks ◽  
Animal Communication ◽  
Field Studies ◽  
Forest Degradation ◽  
Airborne Lidar ◽  
Amazon Forest ◽  
Acoustic Space ◽  
Animal Communities ◽  
Over Time

AbstractSafeguarding tropical forest biodiversity requires solutions for monitoring ecosystem composition over time. In the Amazon, logging and fire reduce forest carbon stocks and alter tree species diversity, but the long-term consequences for wildlife remain unclear, especially for lesser-known taxa. Here, we combined data from multi-day acoustic surveys, airborne lidar, and satellite timeseries covering logged and burned forests (n=39) in the southern Brazilian Amazon to identify acoustic markers of degradation. Our findings contradict theoretical expectations from the Acoustic Niche Hypothesis that animal communities in more degraded habitats occupy fewer ‘acoustic niches.’ Instead, we found that habitat structure (e.g., aboveground biomass) was not a consistent proxy for biodiversity based on divergent patterns of acoustic space occupancy (ASO) in logged and burned forests. Full 24-hr soundscapes highlighted a stark and sustained reorganization in community structure after multiple fires; animal communication networks were quieter, more homogenous, and less acoustically integrated in forests burned multiple times than in logged or once-burned forests. These findings demonstrate strong biodiversity co-benefits from protecting Amazon forests from recurrent fire activity. By contrast, soundscape changes after logging were subtle and more consistent with community recovery than reassembly. In both logged and burned forests, insects were the dominant acoustic markers of degradation, particularly during midday and nighttime hours that are not typically sampled by traditional field surveys of biodiversity. The acoustic fingerprints of degradation history were conserved across replicate recording locations at each site, indicating that soundscapes offer a robust, taxonomically inclusive solution for tracking changes in community composition over time.Significance StatementFire and logging reduce the carbon stored in Amazon forests, but little is known about how human degradation alters animal communities. We recorded thousands of hours of ecosystem sounds to investigate animal community assembly and the associations between biodiversity and biomass following Amazon forest degradation over time. 24-hr patterns of acoustic activity differed between logged and burned forests, and we observed large and sustained breakpoints in community structure after multiple burns. Soundscape differences among degraded forests were clearest during insect-dominated hours rarely sampled in field studies of biodiversity. These findings demonstrate that acoustic monitoring holds promise for routine biodiversity accounting, even by non-experts, to capture a holistic measure of animal communities in degraded tropical forests and benchmark change over time.

Game Theory in Wireless and Communication Networks

2009 ◽  
Author(s):  
Zhu Han ◽  
Dusit Niyato ◽  
Walid Saad ◽  
Tamer Basar ◽  
Are Hjorungnes
Keyword(s):  
Game Theory ◽  
Communication Networks

STRUKTUR KOMUNITAS MAKRO ALGA DI PESISIR PULAU KECAMATAN BULANG

SIMBIOSA ◽  
2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Notowinarto Notowinarto ◽  
Ramses Ramses ◽  
Mulhairi Mulhairi
Keyword(s):  
Community Structure ◽  
Diversity Index ◽  
Algal Species ◽  
Algal Communities ◽  
Marine Life ◽  
Ph Values ◽  
Abundance Patterns ◽  
Coastal Marine ◽  
Temperature Parameter ◽  
Important Value Index

Bulang districts Batam Islands of  Riau province (Riau Islands), its consists of many islands with as well as having the potential diversity of coastal marine life in particular kinds of macro algae or seaweed. Conducted research aimed to determine the structure of macro- algal communities in the intertidal zone islands. The results of the identification of algal species found 16 species are: the Order of Chlorophyceae as 6 spesies; Order Phaeophyceae as 2 spesies; and Order Rhodophyceae as 8 spesies. The community structure at the five stations showed the highest values were found in the island of dominance Cicir (D ' = 0.79) , uniformity index values on Tengah Island (E ' = 0.99) , while the island Balak had the highest diversity index (H ' = 0.88) , with the abundance patterns of population structure on the island is pretty good Central . Results of correlation analysis of regression between IVI types of algae with the conditions of environmental quality suggests that there is a significance (Fhit ˃ F table and the value of r = > 90 %) between IVI algae Halimeda sp and Cryptarachne polyglandulosa at each station with a temperature parameter surface (⁰C) , depth temperature (⁰C) and pH values. Keywords : Algae, Community Structure, Important Value Index.

Seasonal changes in phytoplankton community structure in a bioluminescent lagoon, St. Croix, US Virgin Islands

2018 ◽  
Vol 81 (2) ◽  
pp. 109-124 ◽  
Author(s):  
JL Pinckney ◽  
C Tomas ◽  
DI Greenfield ◽  
K Reale-Munroe ◽  
B Castillo ◽  
...  
Keyword(s):  
Community Structure ◽  
Seasonal Changes ◽  
Phytoplankton Community ◽  
Virgin Islands ◽  
Phytoplankton Community Structure ◽  
Us Virgin Islands
Sign in / Sign up

Export Citation Format

Share Document