Network effects in multi-species fisheries.

Managing sustainable marine fisheries is one of the greatest challenges for humanity. The complexity of the issue calls for the development of socio-ecological models and the integration of our knowledge from several disciplines. Here we focus on the ecological aspects of sustainability: how can we increase the catch and, at the same time, possibly decrease negative effects on the marine ecosystem. Coexisting species live in richly interconnected interaction networks. This means that changes in their biomass are caused and may cause various direct and indirect effects on all other coexisting species in the food web. The assessment of maximum sustainable yield values is typically based on single-species analyses, poorly considering this multi-species context. If several fish species are exploited in particular combinations, their effects may not be additive and non-additivity may mean dampening. In these cases, the community response to fishing species A and B together may be smaller than the sum of fishing species A and B separately. We report on some preliminary results on how to develop a network algebra framework for better understanding food web simulation results for pairwise perturbations and their counter-intuitive effects.

Variable Effect of HIV Superinfection on Clinical Status: Insights From Mathematical Modeling.

HIV superinfection (infection of an HIV positive individual with another strain of the virus) has been shown to result in a deterioration of clinical status in multiple case studies. However, superinfection with no (or positive) clinical outcome might easily go unnoticed, and the typical effect of superinfection is unknown. We analyzed mathematical models of HIV dynamics to assess the effect of superinfection under various assumptions. We extended the basic model of virus dynamics to explore systematically a set of model variants incorporating various details of HIV infection (homeostatic target cell dynamics, bystander killing, interference competition between viral clones, multiple target cell types, virus-induced activation of target cells). In each model, we identified the conditions for superinfection, and investigated whether and how successful invasion by a second viral strain affects the level of uninfected target cells. In the basic model, and in some of its extensions, the criteria for invasion necessarily entail a decrease in the equilibrium abundance of uninfected target cells. However, we identified three novel scenarios where superinfection can substantially increase the uninfected cell count: (i) if the rate of new infections saturates at high infectious titers (due to interference competition or cell-autonomous innate immunity); or when the invading strain is more efficient at infecting activated target cells, but less efficient at (ii) activating quiescent cells or (iii) inducing bystander killing of these cells. In addition, multiple target cell types also allow for modest increases in the total target cell count. We thus conclude that the effect of HIV superinfection on clinical status might be variable, complicated by factors that are independent of the invasion fitness of the second viral strain.

Additivity of pairwise perturbations in food webs: Topological effects.

Food webs dynamically react to perturbations and it is an open question how additive are the effects of single-species perturbations. Network structure may have topological constraints on additivity and this influences community response. Better understanding the relationships between single-species and multi-species perturbations can be useful for systems-based conservation management. Here we study a single model food web by (1) characterising the positional importance of its nodes, (2) building a dynamical network simulation model and performing sensitivity analysis on it, (3) determining community response to each possible single-species perturbation, (4) determining community response to each possible pairwise species perturbation and (5) quantifying the additivity of effects for particular types of species pairs. We found that perturbing pairs of species that are either competitors or have high net status values in the network is less additive: their combined effect is dampened.