Identifying Communities and Key Vertices by Reconstructing Networks from Samples

Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample "hidden" populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network.Comment: 15 pages, 17 figure

Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C:N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right

A stationary visual census technique for quantitatively assessing community structure of coral reef fishes

A new method is described and evaluated for visually sampling reef fish community structure in environments with highly diverse and abundant reef fish populations. The method is based on censuses of reef fishes taken within a cylinder of 7.5 m radius by a diver at randomly selected, stationary points. The method provides quantitative data on frequency of occnrrence, fish length, abundance, and community composition, and is simple, fast, objective, and repeatable. Species are accumulated rapidly for listing purposes, and large numbers of samples are easily obtained for statistical treatment. The method provides an alternative to traditional visual sampling methods. Observations showed that there were no significant differences in total numbers of species or individuals censused when visibility ranged between 8 and 30 m. The reefs and habitats sampled were significant sources of variation in number of species and individuals censused, but the diver was not a significant influence. Community similarity indices were influenced significantly by the specific sampling site and the reef sampled, but were not significantly affected by the habitat or diver (PDF file contains 21 pages.

Phytoplankton Community and Algal Toxicity at a Recurring Bloom in Sullivan Bay, Kabetogama Lake, Minnesota, USA

Kabetogama Lake in Voyageurs National Park, Minnesota, USA suffers from recurring late summer algal blooms that often contain toxin-producing cyanobacteria. Previous research identified the toxin microcystin in blooms, but we wanted to better understand how the algal and cyanobacterial community changed throughout an open water season and how changes in community structure were related to toxin production. Therefore, we sampled one recurring bloom location throughout the entire open water season. The uniqueness of this study is the absence of urban and agricultural nutrient sources, the remote location, and the collection of samples before any visible blooms were present. Through quantitative polymerase chain reaction (qPCR), we discovered that toxin-forming cyanobacteria were present before visible blooms and toxins not previously detected in this region (anatoxin-a and saxitoxin) were present, indicating that sampling for additional toxins and sampling earlier in the season may be necessary to assess ecosystems and human health risk

Respondent-driven sampling bias induced by community structure and response rates in social networks

Sampling hidden populations is particularly challenging by using standard sampling methods mainly because of the lack of a sampling frame. Respondent‐driven sampling is an alternative methodology that exploits the social contacts between peers to reach and weight individuals in these hard‐to‐reach populations. It is a snowball sampling procedure where the weight of the respondents is adjusted for the likelihood of being sampled due to differences in the number of contacts. The structure of the social contacts thus regulates the process by constraining the sampling within subregions of the network. We study the bias induced by network communities, which are groups of individuals more connected between themselves than with individuals in other groups, in the respondent‐driven sampling estimator. We simulate different structures and response rates to reproduce real settings. We find that the prevalence of the estimated variable is associated with the size of the network community to which the individual belongs and observe that low degree nodes may be undersampled if the sample and the network are of similar size. We also find that respondent‐driven sampling estimators perform well if response rates are relatively large and the community structure is weak, whereas low response rates typically generate strong biases irrespectively of the community structure

Is scuba sampling a relevant method to study microhabitat in lakes? Examples and comparisons for three European species

We compared fish microhabitat use patterns in the littoral zone of a lake using a new direct method (i.e. Point Abundance Sampling by Scuba, PASS) and the widely used Point Abundance Sampling by Electrofishing technique (PASE). We collected microhabitat data for age 0+ roach (Rutilus rutilus L.), perch (Perca fluviatilis L.), and pike (Esox lucius L.). The two methods yelded different results for fish assemblage structure and microhabitat patterns. Using PASE, fish were mainly found in "shelter habitats" such as shallow waters and dense vegetation. It is likely that this behaviour is caused by the disturbance of the observer stamping around. Using PASS, fish escapement behaviour was rarely observed. Therefore, we concluded that this direct and non-destructive sampling technique is able to provide an accurate microhabitat estimation of a fish community and is assumed to be more suitable than PASE for fish habitat studies