Ferenc Jordán

Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation

Since the fragmentation of natural habitats is one of the most serious problems for many endangered species, it is highly interesting to study the properties of fragmented landscapes. As a basic property, landscape connectivity and its effects on various ecological processes are frequently in focus. First, we discuss the relevance of some graph properties in quantifying connectivity. Then, we propose a method how to quantify the relative importance of habitat patches and corridors in maintaining landscape connectivity. Our combined index explicitly considers pure topological properties and topographical measures, like the quality of both patches (local population size) and corridors (permeability). Finally, for illustration, we analyze the landscape graph of the endangered, brachypterous bush-cricket Pholidoptera transsylvanica. The landscape contains 11 patches and 13 corridors and is situated on the Aggtelek Karst, NE-Hungary. We characterize the importance of each node and link of the graph by local and global network indices. We show how different measures of connectivity may suggest different conservation preferences. We conclude, accordingly to our present index, by identifying one specific habitat patch and one specific corridor being in the most critical positions in maintaining connectivity.

Keystone species and food webs

Different species are of different importance in maintaining ecosystem functions in natural communities. Quantitative approaches are needed to identify unusually important or influential, ‘keystone’ species particularly for conservation purposes. Since the importance of some species may largely be the consequence of their rich interaction structure, one possible quantitative approach to identify the most influential species is to study their position in the network of interspecific interactions. In this paper, I discuss the role of network analysis (and centrality indices in particular) in this process and present a new and simple approach to characterizing the interaction structures of each species in a complex network. Understanding the linkage between structure and dynamics is a condition to test the results of topological studies, I briefly overview our current knowledge on this issue. The study of key nodes in networks has become an increasingly general interest in several disciplines: I will discuss some parallels. Finally, I will argue that conservation biology needs to devote more attention to identify and conserve keystone species and relatively less attention to rarity.

A reliability theoretical quest for keystones

Species are not equally important for the functioning of communities. This fact is widely recognized and the term keystone species has been introduced for the most important members of communities. In a recent paper, Power et al. called for methods suitable for a priori identification of keystone species, which is an urgent problem in conservation biology. Another problem is the scarcity of their quantitative description. In this paper, we propose an index for characterizing keystone species reflecting their role in food web flow networks. We present some calculations for characterizing the role of keystones in weighted webs and discuss some problems of food web dynamics. Our keystone index refers well to keystones only if trophic interactions are of prime importance in a community. We further analyse the relationship between keystone species and the reliability of network flow. Keystones make network flow less reliable Finally, we discuss some problems of stability and reliability in ecological systems.

Infectious disease and group size: more than just a numbers game

Increased risk of infectious disease is assumed to be a major cost of group living, yet empirical evidence for this effect is mixed. We studied whether larger social groups are more subdivided structurally. If so, the social subdivisions that form in larger groups may act as barriers to the spread of infection, weakening the association between group size and infectious disease. To investigate this ‘social bottleneck’ hypothesis, we examined the association between group size and four network structure metrics in 43 vertebrate and invertebrate species. We focused on metrics involving modularity, clustering, distance and centralization. In a meta-analysis of intraspecific variation in social networks, modularity showed positive associations with network size, with a weaker but still positive effect in cross-species analyses. Network distance also showed a positive association with group size when using intraspecific variation. We then used a theoretical model to explore the effects of subgrouping relative to other effects that influence disease spread in socially structured populations. Outbreaks reached higher prevalence when groups were larger, but subgrouping reduced prevalence. Subgrouping also acted as a ‘brake’ on disease spread between groups. We suggest research directions to understand the conditions under which larger groups become more subdivided, and to devise new metrics that account for subgrouping when investigating the links between sociality and infectious disease risk.

A reliability-theory approach to corridor design

Abstract Natural habitats are small islands in the sea of human environment. Area loss and fragmentation affect seriously the survival of species, for small, isolated populations are exposed to several risks. As the area of suitable habitats decreases, one way to escape local extinction is to migrate between habitats through ecological corridors, and utilize the whole metapopulation landscape. Thus, natural and designed corridors can be key elements for survival. Here, we present a method to study corridor pattern from a reliability-theory viewpoint. We analyze the probability of successful migration in a metapopulation landscape network of habitats, stepping stones and corridors. We examine the situation when individuals of a local population must migrate from a disturbed, critical habitat to others. In the landscape graph, points represent habitats and stepping stones, while edges represent corridors. If corridors can be destroyed, migration probability depends on the pattern of permeable corridors. Engineered corridors can enhance the reliability of migration, depending on their position in the network. We present some general rules for designing reliable landscape patterns (e.g. ‘necklace’ arrangement is less reliable for migration than ‘loop’). Then, we illustrate our viewpoint by presenting two hypothetical landscape networks and comparing the possibilities for designing reliable corridor topologies by creating one engineered corridor. Further, we determine the preferred topology for the engineered corridor. Our hope is that this reliability-theory analysis will stimulate further development of the method and in the fieldwork.

Carabids (Coleoptera: Carabidae) in a forest patchwork: a connectivity analysis of the Bereg Plain landscape graph

For many species, one important key to persistence is maintaining connectivity among local populations that allow for dispersal and gene flow. This is probably true for carabid species (Coleoptera:Carabidae) living in the fragmented forests of the Bereg Plain (NE Hungary and W Ukraine). Based on field data, we have drafted a landscape graph of the area representing the habitat network of these species. Graph nodes and links represented two kinds of landscape elements: habitat (forest) patches and corridors, respectively. The quality of habitat patches and corridors were ranked (from low (1) to high (4)), reflecting local population sizes in the case of patches and estimated permeability in the case of corridors. We analysed (1) the positional importance of landscape elements in maintaining the connectivity of the intact network, (2) the effect of inserting hypothetical corridors into the network, (3) the effects of improving the quality of the existing corridors, and (4) how to connect every patch in a cost-effective way. Our results set quantitative priorities for conservation practice by identifying important corridors: what to protect, what to build and what to improve. Several network analytical techniques were used to account for the directed (source-sink) and highly fragmented nature of the landscape graph. We provide conservation priority ranks for the landscape elements and discuss the conditions for the use of particular network indices. Our study could be of extreme relevance, since a new highway is being planned through the area.

Graph theory in action: evaluating planned highway tracks based on connectivity measures

Maintaining connectivity among local populations in a fragmented landscape is crucial for the survival of many species. For isolated habitat patches, stochastic fluctuations and reduced gene flow can lead to high risk of extinction. The connectivity of the landscape is especially crucial for the carabid species living in the fragmented forests of the Bereg plain (NE Hungary and W Ukraine) because a highway will be constructed through the plain. Our purpose is to (1) evaluate the impacts of three possible highway tracks, (2) suggest a solution that is realistic with less impact on connectivity than other plans and (3) discuss how to decrease the disadvantageous effects of each track. Our results, based on a network analysis of landscape graph of patches and ecological corridors, indicate that the intended highway could have deleterious consequences on forest-living carabids. Relatively simple actions, like the establishment of stepping stones, could compensate for the loss of habitat connectivity and promote the survival of carabids, or minor modifications in one possible track could diminish its adverse effects. While many other studies would be needed for a comprehensive assessment of the biotic impact of the highway, we provide an example on the usefulness of network analysis for land use management.

A network perspective on the topological importance of enzymes and their phylogenetic conservation

BackgroundA metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node; closeness centrality, which measures how close a node is to others; and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes.ResultsEnzyme phylogenetic profile correlates best with betweenness centrality and also quite closely with degree, but poorly with closeness centrality. Both betweenness and closeness centralities are non-local measures of topological importance and it is intriguing that they have contrasting power of predicting phylogenetic profile in bacterial species. We speculate that redundancy in an enzyme network may be reflected by betweenness centrality but not by closeness centrality. We also discuss factors influencing the correlation between phylogenetic profile and topological importance.ConclusionOur analysis falsifies the hypothesis that phylogenetic profile of enzymes is independent of enzyme network importance. Our results show that phylogenetic profile correlates better with degree and betweenness centrality, but less so with closeness centrality. Enzymes that occur in many bacterial species tend to be those that have high network importance. We speculate that this phenomenon originates in mechanisms driving network evolution. Closeness centrality reflects phylogenetic profile poorly. This is because metabolic networks often consist of distinct functional modules and some are not in the centre of the network. Enzymes in these peripheral parts of a network might be important for cell survival and should therefore occur in many bacterial species. They are, however, distant from other enzymes in the same network.

Software, Data and Modelling News: CoSBiLab Graph: The network analysis module of CoSBiLab

We present CoSBiLab Graph 1.0, the freely available network visualisation and analysis module of CoSBiLab (http://www.cosbi.eu). Most of available network analysis softwares are developed by either sociologists or (molecular) systems biologists: our purpose was to create a tool that is designed by considering ecological principles but general enough for supporting multidisciplinary research. It offers classical (e.g. status) and new (e.g. trophic overlap) network indices, as well as provides a fast and comfortable environment for network ecologists. Instead of competing, we aim to cooperate with other existing softwares, by providing compatible input and output and focusing on what is missing in other applications. The key features of this software are (1) the customisable layout, representing node attributes, (2) the implementation of novel network indices and (3) the rich linkage to other modules of the CoSBiLab platform (tools for modelling reaction-diffusion systems, stochastic dynamical simulators, statistical analysis and parameter inference).

A quantitative approach to study indirect effects among disease proteins in the human protein interaction network.

BackgroundSystems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases.ResultsBased on the i2d and OMIM databases, we have constructed (i) a network of proteins causing five selected diseases (DP, disease proteins) plus their interacting partners (IP, non-disease proteins), the DPIP network and (ii) a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1) various cancers, (2) heart diseases, (3) obesity, (4) diabetes and (5) autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins.ConclusionsWe show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand particular pathways. We have found that the mediators between heart diseases and obesity, as well as heart diseases and diabetes are of relatively high functional importance in the cell. The mediator proteins suggested here should be experimentally tested as products of hypothetical disease-related proteins.