Rapid decay in the relative efficiency of quarantine to halt epidemics in networks

Several recent studies have tackled the issue of optimal network immunization by providing efficient criteria to identify key nodes to be removed in order to break apart a network, thus preventing the occurrence of extensive epidemic outbreaks. Yet, although the efficiency of those criteria has been demonstrated also in empirical networks, preventive immunization is rarely applied to real-world scenarios, where the usual approach is the a posteriori attempt to contain epidemic outbreaks using quarantine measures. Here we compare the efficiency of prevention with that of quarantine in terms of the tradeoff between the number of removed and saved nodes on both synthetic and empirical topologies. We show how, consistent with common sense, but contrary to common practice, in many cases preventing is better than curing: depending on network structure, rescuing an infected network by quarantine could become inefficient soon after the first infection.Comment: 10 pages, 7 figure

Human population density and tenebrionid richness covary in Mediterranean islands

Abstract. Human population growth is expected to drive several species to local extinction. Yet, an unexpected high biodiversity can be found even in densely populated areas. Although a positive correlation between human density and biodiversity can be explained by the intermediate disturbance hypothesis, an alternative possible explanation may come from the tendency of human settlements to be located in sites whose environmental conditions are particularly favourable also for many other animal species. To investigate this hypothesis, we studied the relationships between human population density and species richness of native tenebrionid beetles in small Italian islands. We used partial regression analysis to assess the individual contribution of island area (to account for the species–area relationship), elevation (used as a proxy of environmental diversity), and human density to species richness. We found that tenebrionid diversity increased with human population density even after controlling for area and elevation. This may suggest that islands that were (and are) more hospitable to humans are also those which can be more favourable for tenebrionids

Coextinctions dominate future vertebrate losses from climate and land use change

Although theory identifies coextinctions as a main driver of biodiversity loss, their role at the planetary scale has yet to be estimated. We subjected a global model of interconnected terrestrial vertebrate food webs to future (2020-2100) climate and land-use changes. We predict a 17.6% (+/- 0.16% SE) average reduction of local verte-brate diversity globally by 2100, with coextinctions increasing the effect of primary extinctions by 184.2% (+/- 10.9% SE) on average under an intermediate emissions scenario. Communities will lose up to a half of ecological interactions, thus reducing trophic complexity, network connectance, and community resilience. The model reveals that the extreme toll of global change for vertebrate diversity might be of secondary importance com-pared to the damages to ecological network structure.Peer reviewe

Bi-dimensional null model analysis of presence-absence binary matrices

Ecology, published by Wiley Periodicals, Inc., on behalf of the Ecological Society of America. Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either “random” or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the “Tuning Peg” algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be “tuned” in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices

Fish parasites resolve the paradox of missing coextinctions.

Models of coextinction identify parasites as one of the most menaced ecological groups. The number of host species a parasite uses should strongly affect its risk of coextinction. The naïve expectation is that the lower the number, the higher is the parasite's risk of being left with no hosts. Here we analyse the coextinction risk of 12,141 fish parasite species and find that highly specific parasites are not the most endangered, because they tend to use hosts with low vulnerability to extinction. This unexpected result may explain why the number of documented host-parasite coextinctions is much lower than predicted by theoretical studies. © 2013 Macmillan Publishers Limited. All rights reserved

Nestedness for Dummies (NeD): A User-Friendly Web Interface for Exploratory Nestedness Analysis

Recent theoretical advances in nestedness analysis have led to the introduction of several alternative metrics to overcome most of the problems biasing the use of matrix 'temperature' calculated by Atmar's Nestedness Temperature Calculator. However, all of the currently available programs for nestedness analysis lack the user friendly appeal that has made the Nestedness Temperature Calculator one of the most popular community ecology programs. The software package NeD is an intuitive open source application for nestedness analysis that can be used online or locally under different operating systems. NeD is able to automatically handle different matrix formats, has batch functionalities and produces an output that can be easily copied and pasted to a spreadsheet. In addition to numerical results, NeD provides a graphic representation of the matrix under examination and of the corresponding maximally packed matrix. NeD allows users to select among the most used nestedness metrics, and to combine them with different null models. Integrating easiness of use with the recent theoretical advances in the field, NeD provides researchers not directly involved in theoretical debates with a simple yet robust statistical tool for a more conscious performance of nestedness analysis. NeD can be accessed at http: //purl.oclc.org/ned

A patch-dynamic metacommunity perspective on the persistence of mutualistic and antagonistic bipartite networks

The structure of interactions between species within a community plays a key role in maintaining biodiversity. Previous studies have found that the effects of these structures might substantially differ depending on interaction type, for example, a highly connected and nested architecture stabilizes mutualistic communities, while the stability of antagonistic communities is enhanced in modular and weakly connected structures. Here we show that, when network dynamics are modelled using a patch-dynamic metacommunity framework, the qualitative differences between antagonistic and mutualistic systems disappear, with nestedness and modularity interacting to promote metacommunity persistence. However, the interactive effects are significantly weaker in antagonistic metacommunities. Our model also predicts an increase in connectance, nestedness and modularity over time in both types of interaction, except in antagonistic networks where nestedness declines. At steady state, we find a strong negative correlation between nestedness and modularity in both mutualistic and antagonistic metacommunities. These predictions are consistent with the structural trends found in a large dataset of real-world antagonistic and mutualistic communities

Ecological drift and competitive interactions predict unique patterns in temporal fluctuations of population size

Recent studies have highlighted the importance of higher-order competitive interactions in stabilizing population dynamics in multi-species communities. But how does the structure of competitive hierarchies affect population dynamics and extinction processes? We tackled this important question by using spatially explicit simulations of ecological drift (10 species in a homogeneous landscape of 64 patches) in which birth rates were influenced by interspecific competition. Specifically, we examined how transitive (linear pecking orders) and intransitive (pecking orders with loops) competitive hierarchies affected extinction rates and population dynamics in simulated communities through time. In comparison to a pure neutral model, an ecological drift model including transitive competition increased extinction rates, caused synchronous density-dependent population fluctuations, and generated a white-noise distribution of population sizes. In contrast, the drift model with intransitive competitive interactions decreased extinctions rates, caused asynchronous (compensatory) density-dependent population fluctuations, and generated a brown noise distribution of population sizes. We also explored the effect on community stability of more complex patterns of competitive interactions in which pairwise competitive relationships were assigned probabilistically. These probabilistic competition models also generated density-dependent trajectories and a brown noise distribution of population sizes. However, extinction rates and the degree of population synchrony were comparable to those observed in purely neutral communities. Collectively, our results confirm that intransitive competition has a strong and stabilizing effect on local populations in species-poor communities. This effect wanes with increasing species richness. Empirical assemblages characterized by brown spectral noise, density-dependent regulation, and asynchronous (compensatory) population fluctuations may indicate a signature of intransitive competitive interactions