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

1993 ◽  
Vol 35 (2) ◽  
pp. 151-170 ◽  
Author(s):  
Shuichi Yano ◽  
Naota Ohsaki
Keyword(s):  
Community Structure ◽  
Herbivorous Insects ◽  
Intrinsic Quality

scholarly journals Understanding Completeness and Diversity Patterns of OSM-Based Land-Use and Land-Cover Dataset in China

2020 ◽  
Vol 9 (9) ◽  
pp. 531
Author(s):  
ShuZhu Wang ◽  
Qi Zhou ◽  
YuanJian Tian
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Quality Assessment ◽  
Socioeconomic Factors ◽  
Reference Dataset ◽  
Diversity Pattern ◽  
Diversity Patterns ◽  
Intrinsic Quality ◽  
Accuracy Measures

OpenStreetMap (OSM) data are considered essential for land-use and land-cover (LULC) mapping despite their lack of quality. Most relevant studies have employed an LULC reference dataset for quality assessment, but such a reference dataset is not freely available for most countries and regions. Thus, this study conducts an intrinsic quality assessment of the OSM-based LULC dataset (i.e., without using a reference LULC dataset) by examining the patterns of both its completeness and diversity. With China chosen as the study area, an OSM-based LULC dataset of the country was first generated and validated by using various accuracy measures. Both its completeness and diversity patterns were then mapped and analyzed in terms of each prefecture-level division of the country. The results showed the following: (1) While the overall accuracy was as high as 82.2%, most complete regions of China were not mapped well owing to a lack of diverse LULC classes. (2) In terms of socioeconomic factors and the number of contributors, higher correlations were noted for diversity patterns than completeness patterns; thus, the diversity pattern is a better reflection of socioeconomic factors and the spatial patterns of contributors. (3) Both the completeness and the diversity patterns can be combined to better understand an OSM-based LULC dataset. These results indicate that it is useful to consider diversity as a supplement for intrinsically assessing the quality of an OSM-based LULC dataset. This analytical method can also be applied to other countries and regions.

scholarly journals Community structure of aquatic insects (Ephemeroptera, Plecoptera, and Trichoptera) in Cerrado streams of Paraguay, Paraná, and São Francisco river basins

2013 ◽  
Vol 13 (1) ◽  
pp. 97-107 ◽  
Author(s):  
Renato de Mei Romero ◽  
Mônica Ceneviva-Bastos ◽  
Gustavo Henrique Baviera ◽  
Lilian Casatti
Keyword(s):  
Community Structure ◽  
Aquatic Insects ◽  
Regional Differences ◽  
River Basins ◽  
Taxonomic Composition ◽  
Taxonomic Resolution ◽  
Sao Francisco River ◽  
Original Distribution ◽  
São Francisco River

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.

Detecting communities from networks based on their intrinsic properties

2019 ◽  
Vol 30 (12) ◽  
pp. 1950104 ◽  
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.

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

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.

An Algebraic Approach to Data Quality Metrics for Entity Resolution over Large Datasets

2008 ◽  
pp. 3067-3084
Author(s):  
John Talburt ◽  
Richard Wang ◽  
Kimberly Hess ◽  
Emily Kuo
Keyword(s):  
Data Quality ◽  
Algebraic Approach ◽  
Entity Resolution ◽  
Quality Metrics ◽  
Quality Literature ◽  
Intrinsic Quality ◽  
Recognition Systems ◽  
Entity Identification ◽  
Data Quality Metrics

This chapter introduces abstract algebra as a means of understanding and creating data quality metrics for entity resolution, the process in which records determined to represent the same real-world entity are successively located and merged. Entity resolution is a particular form of data mining that is foundational to a number of applications in both industry and government. Examples include commercial customer recognition systems and information sharing on “persons of interest” across federal intelligence agencies. Despite the importance of these applications, most of the data quality literature focuses on measuring the intrinsic quality of individual records than the quality of record grouping or integration. In this chapter, the authors describe current research into the creation and validation of quality metrics for entity resolution, primarily in the context of customer recognition systems. The approach is based on an algebraic view of the system as creating a partition of a set of entity records based on the indicative information for the entities in question. In this view, the relative quality of entity identification between two systems can be measured in terms of the similarity between the partitions they produce. The authors discuss the difficulty of applying statistical cluster analysis to this problem when the datasets are large and propose an alternative index suitable for these situations. They also report some preliminary experimental results, and outlines areas and approaches to further research in this area.

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

Complexity ◽  
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.

scholarly journals Formulating Popular Policies for Peat Restoration Based on Livelihoods of Local Farmers

2018 ◽  
Vol 11 (3) ◽  
pp. 85 ◽  
Author(s):  
Elisa Wildayana ◽  
M. Edi M. Edi Armanto
Keyword(s):  
Political Institutions ◽  
Poverty Alleviation ◽  
Rural Livelihoods ◽  
Political Aspect ◽  
Qualitative And Quantitative ◽  
Peatland Restoration ◽  
Intrinsic Quality ◽  
Peatland Degradation ◽  
Local Farmers

Important peatland issues developed were how to restore peatlands and followed by increasing rural livelihoods. This research aimed to analyze how peatlands can be utilized to alleviate poverty? and how to integrate peatland restoration with poverty alleviation. This research has been conducted in peatlands of OKI district, South Sumatra Indonesia in 2017. Data about bio geophysical aspects of peatlands, social, economic and political institutions of farmers were surveyed in the fields, performed in qualitative and quantitative approach, and analyzed in forms of tables and descriptions. Important themes have been discussed in formulating popular policies for peat restoration based on livelihoods of local farmers, among others poor groups; characteristics of farmers from the socio-political aspect; concept of peatland restoration and other lessons-learnt; compatibility of peat-based poverty alleviation; and need to improve policy making. The chronic poor sites tend to overlap with peatland degradation; it is more important to cultivate peatlands to prevent farmers from falling into deeper poverty than to reduce farmers out of poverty, and the intrinsic quality of peatlands and their contents tends to conflict with poverty alleviation goals, but there are some possible trends to minimize peatlands degradation and to alleviate poverty simultaneously. The best approach is to apply the 'win-lose' or 'lose-win' approach, even though we are not able to avoid peatland degradation at a zero level, but at least it can be inhibited. Cooperation between investors and farmers in managing peatlands is needed, so that the peatland resources are not completely degraded.

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