Use of network analysis in food web conservation

Human pressure on marine and terrestrial ecosystems has increased in the past few decades leading to significant, often irreversible, changes. Some of the strongest sources of pressure include habitat destruction or degradation, contamination, fishing and hunting, all of which have caused changes in the abundance and distribution of species, the productivity of ecosystems, and even in the organisation required for the adequate functioning of these ecosystems. Although the organisation of ecosystems is resilient to natural stressors over long time scales, human action has induced strong pressures over time periods too short for these ecosystems to adapt.

This state of affairs has given rise to multiple approaches to try to understand how human activities have modified, and continue to modify, different ecosystems. On the way to gaining this understanding, numerous differences and controversies have emerged among researchers, not so much as to whether humans cause deleterious effects, but rather about the magnitude and extent of such effects. One of the most common approaches is the study of food webs and the effects of human activity on them. For example, some studies suggest that intense fishing pressure in the past 50 years has drastically modified the composition of marine food webs. In contrast, other researchers propose that the changes observed in the composition of marine food webs reflect effects on the species targeted by fisheries rather than network degradation. Some studies further suggest that human activity has substantially altered existing feeding relationships among species within the networks, leading to network reorganization only a few years after being impacted by humans.

The study of food webs has generated a lot of interest in the past few decades, especially recently, when the focus on ecosystems has become a central theme in fisheries management and conservation of ecosystem services around the world. A number of theoretical approaches have been developed to study food webs and associated tools to build, analyse, and interpret the network of interactions in food webs. Studies on the structure and function of these networks have generated the most attention. Research on network structure focuses on describing and interpreting the species composition of the food web and identifying guilds or functional groups of species that play similar roles in the web.

By contrast, studies on network function attempt to quantify energy flow among network components and the strength of interactions among species. The tools we described above allow us to model how food webs will respond to different kinds of management interventions, such as reducing fishing pressure, setting fish catch quotas, or selectively removing particular species from the web. These tools also help anticipate the consequences, on food webs, of natural changes such as decreases in abundance of top predators, structural simplification of food webs, and decreases in productivity. Using these approaches, studies have indicated that many ecosystems are transitioning to new organisational states that are more sensitive to natural changes.

These tools have also been used to compare highly impacted ecosystems to others that were relatively unchanged, showing that the latter are more stable and thus less susceptible to environmental modifications (this is called “resilience”). It is important to note that, for those interested in using this approach, the models we describe are highly dependent on information available, how the model itself is specified, and previous knowledge of the system modeled. Thus these models must be developed and applied with extreme caution and all assumptions and implications carefully examined. The structural analysis of trophic networks is a more recent approach that has borrowed very useful tools for ecology from the social sciences.

Based on information on the presence of interactions among predators and prey in food webs, structural analysis allows us to explore different properties of food webs such as which species have the highest connectivity, those that are the most central and important for maintaining network organisation, as well as the key species in terms of interactions or network cohesion. Recent findings suggest that not only species of high commercial value are the most important for organising or protecting ecosystems, but that, to the contrary, even species or groups of species without any apparent value may be those that contribute the most to maintaining the organisation of a trophic network, which means that management measures aimed at those species are needed to conserve the food web and its functions.
This approach allows studying direct and indirect trophic relationships between predators and their prey, considered important forces in network organisation, by analysing real or modeled scenarios of removing, or adding, species from the network under study. Regardless of the approach used, a good food web study hinges on the availability of basic information that allows one to build solid models from the outset. Knowledge of the diet and feeding ecology of species to the finest level of detail is desirable, since it enables nuanced modeling of important ecological effects such as temporal, spatial, and sex-specific diet shifts.

Depending on the approach used, it is also necessary to have population-level information on the species included in the model, such as production (i.e. biomass), productivity (i.e. mortality rates), and data on catches and discards among others. Tools for network analysis are particularly useful in large, difficult-to-delineate ecosystems, such as the oceans, or when populations under study cannot be manipulated, such as large cats in the African savannah, where experiments aimed at studying relationships between the loss of species and community stability cannot be conducted. It is in these situations that having a toolbox to partially reproduce the complexity of the ecosystem under study and conduct “experiments by computer” is especially useful: it allows researchers and decision-makers to have access to information that would otherwise be very difficult to obtain (such as the effects on predatory function, predator-prey relationships, and trophic interactions among species).

All in all, it is very important to consider the context of the assumptions and limitations of each mathematical model to avoid indiscriminate errors of extrapolation or overreaching conclusions. Although the different pressures on food web networks may at first appear to be disconnected from each other, in reality they are all interrelated and may even become magnified as pressures increase. For example, a “simple” imbalance in the proportion between predator and prey could spread a new indirect effect, which in turn could enhance a previously non-significant interaction in the web. If the species involved are not adapted to adjust to this new dynamic, it may lead to reductions in abundance of some of them, which in turn could spread another sequence of indirect effects that could even modify some ecosystem functions.

Thus, considering the complexity of food webs, tools such as those we described are needed because they allow researchers to gain an understanding of networks, their properties, complexity, and possible responses to human-induced effects. Up to now, different approaches to studying networks have typically been applied independently of one another, with few attempts at comparing and contrasting results. In the future, it is important that the best features of each of these tools are integrated with the aim of optimising results and increasing the efficiency of network studies. This will, in turn, give us a higher degree of confidence in the models we develop to plan the conservation and management of food webs in the future.

Suggested reading:
Christensen V & C Walters. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modelling 172:109-139.
Dunne JA. 2006. The Network Structure of Food Webs. pp 27.86. In Ecological Networks: Linking Structure to Dynamics in Food Webs. (Eds M Pascual and JA Dunne). Oxford University Press, USA.
Gaichas SK & RC Francis. 2008. Network models for ecosystem-based fishery analysis: a review of concepts and application to the Gulf of Alaska marine food web. Canadian Journal of Fisheries and Aquatic Sciences 65(9): 1965-1982.
Navia AF, E Cortés, F Jordán, VH Cruz-Escalona & PA Mejía-Falla. 2012. Changes to marine trophic networks caused by fishing. pp 417-452, In: Diversity of Ecosystems (Ed A Mahamane). Intech, Croatia.

This article is from issue


2012 Dec