Structure Of Dispersal Networks Research Articles

Robustness of dispersal network structure to patch loss

Network theories have been largely applied to the investigation of spatial ecology, and there is a new trend to use them to explore the responses of complex dispersal networks to patch loss. Combining both network and metapopulation approaches, we used a spatially explicit patch model to compare the robustness of networks with different heterogeneities to both random and selective patch removal. We found that species in more heterogeneous networks can persist at higher extinction-to-colonization ratios. In addition, dispersal networks with higher heterogeneity display stronger robustness to random patch loss, suggesting that previous models based on lattice- or randomly-structured networks might underestimate species extinction thresholds. However, such strong tolerance to random patch removal comes at a high cost in that these networks are extremely vulnerable to selective removal of the most connected patches (so-called keystone patches), as this removal mode directly leads to a rapid decline in the total number of links among patches. We further explored the mechanism underlying these outcomes via network analysis, and found a strong positive correlation between overall metapopulation size and the largest cluster size. Concerning ecological conservation and management, our findings suggest that future efforts should focus on considering species dispersal networks by identifying and preserving the keystone patches, and as such, optimizing the connectivity between existing habitat patches should be an effective strategy to rescue the endangered species.

Dispersal network structure and infection mechanism shape diversity in a coevolutionary bacteria-phage system

Resource availability, dispersal and infection genetics all have the potential to fundamentally alter the coevolutionary dynamics of bacteria-bacteriophage interactions. However, it remains unclear how these factors synergise to shape diversity within bacterial populations. We used a combination of laboratory experiments and mathematical modeling to test how the structure of a dispersal network affects host phenotypic diversity in a coevolving bacteria-phage system in communities of differential resource input. Unidirectional dispersal of bacteria and phage from high to low resources consistently increased host diversity compared with a no dispersal regime. Bidirectional dispersal, on the other hand, led to a marked decrease in host diversity. Our mathematical model predicted these opposing outcomes when we incorporated modified gene-for-gene infection genetics. To further test how host diversity depended on the genetic underpinnings of the bacteria-phage interaction, we expanded our mathematical model to include different infection mechanisms. We found that the direction of dispersal had very little impact on bacterial diversity when the bacteria-phage interaction was mediated by matching alleles, gene-for-gene or related infection mechanisms. Our experimental and theoretical results demonstrate that the effects of dispersal on diversity in coevolving host-parasite systems depend on an intricate interplay of the structure of the underlying dispersal network and the specifics of the host-parasite interaction.

Predicting invasions: alternative models of human‐mediated dispersal and interactions between dispersal network structure and Allee effects

Summary Human‐mediated dispersal has been shown to be the most important vector for the spread of invasive species, yet there has been little evaluation of alternative models of dispersal in terms of differences in their predictions of invasion patterns. Moreover, no analyses have been attempted to elucidate the potential interaction between alternative models of human‐mediated dispersal and population dynamical characteristics, such as Allee effects, which are central to the probability of an invasion. Two prominent models in the literature which have previously been employed to predict human movement patterns are explored: (i) gravity models, which use the attractiveness of and distance to a location to predict travel patterns, and (ii) random utility models, which assume that individuals decide where to travel by maximizing the benefits that they receive according to some partially observable function of individual and site characteristics. While distinction is often drawn between them in the literature, we demonstrate that these two approaches can be reduced to alternative functional forms describing the trip‐taking decisions of individuals. Each model was empirically parameterized using a survey of recreational boaters in Ontario, Canada. Within each model, both boater‐ and site‐specific characteristics were important and the functional form provided by the gravity model was significantly better at capturing the behaviour of recreational boaters Synthesis and applications. The dispersal and establishment of species into novel habitats are central components of the invasion process and of quantitative risk assessments. However, predictions are dependent on the estimated spatial structure of the dispersal network and its potential interactions with species characteristics. This study demonstrates that Allee effects can interact with dispersal network structure to significantly alter predicted spread rates and that the consequences of these interactions manifest differently at the system and site levels. This modelling framework can be used to inform management interventions aimed at modifying human‐mediated dispersal to reduce the spread of invasive species.

Biodiversity Conservation in Metacommunity Networks: Linking Pattern and Persistence

A central goal of conservation science is to identify the most important habitat patches for maintaining biodiversity on a landscape. Spatial biodiversity patterns are often used for such assessments, and patches that harbor unique diversity are generally prioritized over those with high community similarity to other areas. This places an emphasis on biodiversity representation, but removing a patch can have cascading effects on biodiversity persistence in the remaining ecological communities. Metacommunity theory provides a mechanistic route to the linking of biodiversity patterns on a landscape with the subsequent dynamics of diversity loss after habitat is degraded. Using spatially explicit neutral theory, I focus on the situation where spatial patterns of diversity and similarity are generated by the structure of dispersal networks and not environmental gradients. I find that gains in biodiversity representation are nullified by losses in persistence, and as a result the effects of removing a patch on metacommunity diversity are essentially independent of complementarity or other biodiversity patterns. In this scenario, maximizing protected area and not biodiversity representation is the key to maintaining diversity in the long term. These results highlight the need for a broader understanding of how conservation paradigms perform under different models of metacommunity dynamics.

Strong effect of dispersal network structure on ecological dynamics

A central question in ecology with great importance for management, conservation and biological control is how changing connectivity affects the persistence and dynamics of interacting species. Researchers in many disciplines have used large systems of coupled oscillators to model the behaviour of a diverse array of fluctuating systems in nature. In the well-studied regime of weak coupling, synchronization is favoured by increases in coupling strength and large-scale network structures (for example 'small worlds') that produce short cuts and clustering. Here we show that, by contrast, randomizing the structure of dispersal networks in a model of predators and prey tends to favour asynchrony and prolonged transient dynamics, with resulting effects on the amplitudes of population fluctuations. Our results focus on synchronization and dynamics of clusters in models, and on timescales, more appropriate for ecology, namely smaller systems with strong interactions outside the weak-coupling regime, rather than the better-studied cases of large, weakly coupled systems. In these smaller systems, the dynamics of transients and the effects of changes in connectivity can be well understood using a set of methods including numerical reconstructions of phase dynamics, examinations of cluster formation and the consideration of important aspects of cyclic dynamics, such as amplitude.