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Species are embedded in a network of trophic interactions known as a food web. We propose to measure functional diversity of an ecosystem from a network perspective. Our approach is based on the concept of regular equivalence (REGE), which can quantify the similarity in species trophic roles in a food web. Using the outcome of REGE analysis, we define three REGE-based functional diversity indices. First is the average dissimilarity in species trophic roles, second is the optimal number of trophic role groups, and the third is the degree of evenness that species are partitioned into trophic role groups. We quantified these three REGE-based functional diversity indices for 92 aquatic food webs and compared the results with that from random food webs. We found that most food webs had higher average trophic role dissimilarity and more trophic role groups than random food webs. However, real food webs and random food webs showed no difference in the evenness of species partition into trophic role groups. We also determined the relationship between REGE-based functional diversity and the structural properties of food webs. We found that food webs with high functional diversity were those with sparse network organization, highly modular structure, or low network cohesion. Furthermore, we also investigated the relationship between our REGE-based functional diversity indices and their trait-based and interaction-based counterparts; their weak-to-moderate correlation suggests our REGE-based approach offers a complementary view to functional diversity of an ecosystem. [ABSTRACT FROM AUTHOR]

Parasites are ubiquitous and constitute a substantial amount of natural biomass. Host species differ greatly in how many parasite species they harbor. In this idea paper, we ask what may cause the distribution of parasite diversity in an ecosystem. Since host species interact trophically in a food web and parasites are often transmitted along trophic links, we argue that trophic transmission can be a potential mechanism for explaining parasite diversity distribution. We propose a modeling framework for investigating this issue. The feasibility of our idea is demonstrated by fitting a simulation model to data derived from the Carpinteria ecosystem. Our preliminary analysis suggests that a model with trophic transmission is able to produce parasite diversity distribution similar to the empirical data better than a model without trophic transmission can. We also discuss possible extensions of our preliminary work for future research. [ABSTRACT FROM AUTHOR]

Understanding the mechanism shaping species assemblages is a fundamental goal in ecology. In the past, two hypotheses have been suggested. One is the filtering hypothesis, where environmental factors select for species of similar traits such that they co-occur in similar niches. The other is the competitive exclusion hypothesis, where related species are driven far apart by competition such that they overdisperse across various niches. Here, we investigate the relationship between species assemblages and their phylogenetic relatedness from a network perspective by using five separate ecosystems ranging from oceans to an inland lake. We quantified the similarity in species network positions in a food web and clustered them into different trophic role groups; using an online database, we quantified their phylogenetic distances. We then investigated whether related species tend to underdisperse or overdisperse across different trophic role groups. In general, our results suggest that the environmental filtering process is the dominant force shaping the species assemblage of those ecosystems. However, there are some possible cases where related species are driven by competition such that they evolve to adopt different trophic roles in relatively closed ecosystems. [ABSTRACT FROM AUTHOR]

Species uniqueness can be measured from the network perspective offering an alternative view to species importance. Direct and indirect effects between species can be quantified to construct a matrix that represents the interaction structure of the food web. Such a matrix is then used to determine the trophic fields of individual species; and the uniqueness of a species is defined based on the extent of overlap between its trophic field and those of other species (TFO-based index). In this paper, we revisit this former idea of species uniqueness and demonstrate how its computation can be simplified. Here, from the interaction matrix we construct a distance matrix where an element of this matrix is the distance between the interaction profiles of a particular species pair; and the row sums of this distance matrix are the uniqueness values of species in the food web. We offer two approaches depending on the type of distance calculated. The Manhattan distance-based index produces identical ranking of species uniqueness as the TFO-based index, while the Euclidean distance-based index shows strong correlation with the TFO-based index. Lastly, we describe a basic framework for quantifying species uniqueness from the network perspective as a potential direction for future research. [ABSTRACT FROM AUTHOR]

In their recent critique, Qian et al. stated that the results of structural equation modeling analysis (SEM) in Chan et al. were flawed. Here, we show that the source of the difference, in their reanalysis, is that Qian et al. did not follow the standard, iterative strategy of SEM, which allows researchers to evaluate which model offers the best account of the data in both absolute and relative terms. Here, we provide step‐by‐step instructions to reproduce our published results. We address—and aim to resolve—Qian et al.'s concerns regarding SEM. Moreover, in our original paper, we used three distinct statistical methods—hierarchical partitioning, SEM and stationary bootstrap—to show that different temporal scales of environmental variability differentially impact the elevational range size (ERS) of species. We believe it is time to move on to probing the pressing issue of how and why climatic variability impacts ERS. [ABSTRACT FROM AUTHOR]

A food web is a representation of trophic interactions in an ecosystem. Food webs are often generated by a single dataset aggregated from one or several surveys. Point estimates of food web parameters can be calculated from the data, but it remains an open question as to how their corresponding interval estimates can be quantified. Although conventional methods such as bootstrapping represent potential solutions, they tend to underestimate several network parameters. Here, we propose a simple bootstrap-based resampling procedure for inferring food web parameters. First, for a particular food web parameter, we obtain its point estimate by calculating the corresponding statistics from the original food web. Second, we generate a resampled food web by sampling with replacement the same number of species from the original food web, and for each resampled species we record how many prey items it consumes in the original food web. Third, a resampled species is allowed to consume its original prey species if such a species is also present; if not present, it instead consumes the resampled species that is most topologically similar to its original prey species. Many resampled food webs can be generated in this manner, and we calculate particular food web statistics for each of them. These form a sampling distribution from which interval estimates of the true food web parameter can be determined. We demonstrate our methodology on two different food web datasets and discuss its application in comparing food webs of various sizes and connectance. [ABSTRACT FROM AUTHOR]

The impact of social influence causes people to adopt the behaviour of others when interacting with other individuals. The effects of social influence can be direct or indirect. Direct social influence is the result of an individual directly influencing the opinion of another, while indirect social influence is a process taking place when an individual’s opinion and behaviour is affected by the availability of information about others’ actions. Such indirect effect may exhibit a more significant impact in the on-line community because the internet records not only positive but also negative information, for example on-line written text comments. This study focuses on indirect social influence and examines the effect of preceding information on subsequent users’ opinions by fitting statistical models to data collected from an on-line bulletin board. Specifically, the different impacts of information on approval and disapproval comments on subsequent opinions were investigated. Although in an anonymous situation where social influence is assumed to be at minimum, our results demonstrate the tendency of on-line users to adopt both positive and negative information to conform to the neighbouring trend when expressing opinions. Moreover, our results suggest unequal effects of the local approval and disapproval comments in affecting the likelihood of expressing opinions. The impact of neighbouring disapproval densities was stronger than that of neighbouring approval densities on inducing subsequent disapproval relative to approval comments. However, our results suggest no effects of global social influence on subsequent opinion expression. [ABSTRACT FROM AUTHOR]

Numerous materials have been proposed for bone tissue engineering. In this study, a newly designed hybrid composite scaffold composed of poly (D,L-lactide-co-glycolide) and a naturally bioceramic hybrid material, nanonized pearl powder, were prepared and the biological activities and physical properties of the scaffold for bone tissue engineering were evaluated. It is a composite consisting calcium carbonate crystal in an aragonite structure, embedded in an organic matrix. Peral contains one or more signal molecules capable of stimulating bone formation. The nanonized pearl powder is considered as a promising osteoinductive biomaterial. This biomaterial is biocompatible and shows osteogenic activity. In this study, the designed biohybrid of nanonized pearl powder/poly (lactide-co-glycolide) (NPP/PLGA) biocomposite scaffolds would employ biodegradable material as MC3T3-E1 cells seeded scaffolds. Therefore, the biocomposite scaffolds would be used to culture with MC3T3-E1 cells under spinner bioreactor in vitro. Furthermore, it also detailed how these tissues were characterized, qualitatively and quantitatively, with scanning electron microscopy and biochemical testing. The identity and the mode of action of these molecules on the osteoblast differentiation were analyzed. This study indicates that the efficiency of nanonized pearl powders in bone cell differentiation are certainly different from that of proteins. Further sudy will look forward to manufacturing the promising new generation bone substitute, three dimensional biocomposite scaffolds to replace the implant and autogeneous bone graft, which combines basic research and clinical application. [ABSTRACT FROM AUTHOR]

Numerous materials have been proposed for bone tissue engineering. In this study, a newly designed hybrid composite scaffold composed of poly (D,L-lactide-co-glycolide) and a naturally bioceramic hybrid material, nanonized pearl powder, were prepared and the biological activities and physical properties of the scaffold for bone tissue engineering were evaluated. It is a composite consisting calcium carbonate crystal in an aragonite structure, embedded in an organic matrix. Peral contains one or more signal molecules capable of stimulating bone formation. The nanonized pearl powder is considered as a promising osteoinductive biomaterial. This biomaterial is biocompatible and shows osteogenic activity. In this study, the designed biohybrid of nanonized pearl powder/poly (lactide-co-glycolide) (NPP/PLGA) biocomposite scaffolds would employ biodegradable material as MC3T3-E1 cells seeded scaffolds. Therefore, the biocomposite scaffolds would be used to culture with MC3T3-E1 cells under spinner bioreactor in vitro. Furthermore, it also detailed how these tissues were characterized, qualitatively and quantitatively, with scanning electron microscopy and biochemical testing. The identity and the mode of action of these molecules on the osteoblast differentiation were analyzed. This study indicates that the efficiency of nanonized pearl powders in bone cell differentiation are certainly different from that of proteins. Further sudy will look forward to manufacturing the promising new generation bone substitute, three dimensional biocomposite scaffolds to replace the implant and autogeneous bone graft, which combines basic research and clinical application. [ABSTRACT FROM AUTHOR]

In order to better understand several cellular processes, it is helpful to study how various components make up the system. This systems perspective is supported by several modelling tools including network analysis. Networks of protein–protein interactions (PPI networks) offer a way to depict, visualize and quantify the functioning and relative importance of particular proteins in cell function. The toolkit of network analysis ranges from the local indices describing individual proteins (as network nodes) to global indicators of system architecture, describing the total interaction system (as the whole network). We briefly introduce some of these network indices and present a case study where the connectedness and potential functional relationships between certain disease proteins are inferred. We argue that network analysis can be used, in general, to improve databases, to infer novel functions, to quantify positional importance and to support predictions in pathogenesis studies. The systems perspective and network analysis can be of particular importance in studying diseases with complex molecular processes. [ABSTRACT FROM AUTHOR]

Examines data for replicated three-species ecological systems. Demonstration that the dynamic trajectories of both a predator and its prey within the system are determined by the sequence in which it is constructed; Possibility of construction-sequence alternative dynamic patterns for one trajectory.

Species are embedded in a web of intricate trophic interactions. Understanding the functional role of species in food webs is of fundamental interests. This is related to food web position, so positional similarity may provide information about functional overlap. Defining and quantifying similar trophic functioning can be addressed in different ways. We consider two approaches. One is of mathematical nature involving network analysis where unique species can be defined as those whose topological position is very different to others in the same food web. A species is unique if it has very different connection pattern compared to others. The second approach is of biological nature, based on trait-based aggregations. Unique species are not easy to aggregate with others because their traits are not in common with the ones of most others. Our goal here is to illustrate how mathematics can provide an alternative perspective on species aggregation, and how this is related to its biological counterpart. We illustrate these approaches using a toy food web and a real food web and demonstrate the sensitive relationships between those approaches. The trait-based aggregation focusing on the trait values of size (sv) can be best predicted by the mathematical aggregation algorithms. [ABSTRACT FROM AUTHOR]