Cascades in the Barents Sea

Mass mortality events are events that cause elevated mortality that may reduce the population size over a short period. Such events are likely on the rise across the globe and for several taxa (Fey et al. 2015). We recently investigated how such events may affect the community of interacting species in the Barents Sea. For this investigation, we constructed a multi-species model of a key component of the Barents Sea ecosystem consisting of fish and zooplankton

Figure 1. Illustration of the study system.

Movie 1. Animated illustration of the community response to mass mortality over time. This scenario describe the community level effects of a loss of 90% of the krill biomass in a single year between 1972-2007.The arrows indicate the year the mortality impact, the solid line indicate the median simulated population, while the dotted lines indicate the 95% confidence bands, diamonds are the observed values and the light and dark grey regions indicate the 50% and 95% unperturbed confidence bands.

In a paper recently published in Global Change Biology (Langangen et al. 2016) We used the classical Gompertz model, which was developed by Benjamin Gompertz almost 200 years ago (Gompertz 1825). The model incorporated effects of species interactions, fishing and effects of temperature.

            To investigate how a reduction in population size may propagate in the community, we constructed several scenarios. We assumed that everything else was fixed but the population of one species were reduce by 10%, 50% or 90% in one singe historic year (1972-2011, the years with available data). This resulted in a series of possible outcomes of a mass mortality event on all modelled species. For an example, see movie 1, were the mortality event is affecting the Krill population at the bottom of the community.

            If the mortality event is caused by human activity, it may be necessary to take a precautionary approach. By this we mean that we should take into account the uncertainty in the projected outcome, and make a decision on the uncertainty we can accept. Such a decision is outside the realm of science, but decision makers such as managers or politicians should be informed about the possibilities. We showed that the impact in the community can vary significantly when taking different levels of precaution, see Figure 2.

Figure 2. Scenarios with mortality event in krill and how this may affect capelin (dashed line) or cod  (dotted line) at different levels of precaution. Lines with diamonds shows duration of event  and non diamond lines shows maximal population decline. The three panels shows 10 %, 50% or 90% reduction in krill (from the top to bottom).




Langangen, Ø., Ohlberger, J., Stige, L., Durant, J.M., Ravagnan, E., Stenseth, N., & Hjermann, D.Ø. (2016). Cascading effects of mass mortality events in Arctic marine communities Global Change Biology DOI: 10.1111/gcb.13344

Fey, S., Siepielski, A., Nusslé, S., Cervantes-Yoshida, K., Hwan, J., Huber, E., Fey, M., Catenazzi, A., & Carlson, S. (2015). Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events Proceedings of the National Academy of Sciences, 112 (4), 1083-1088 DOI: 10.1073/pnas.1414894112

Gompertz, B. (1815). On the Nature of the Function Expressive of the Law of Human Mortality, and on a New Mode of Determining the Value of Life Contingencies. Proceedings of the Royal Society of London, 2, 252-253 DOI: 10.1098/rspl.1815.0271

Tags: Bayesian, JAGS, Mass mortality, Barents Sea By Øystein Langangen
Published June 8, 2016 9:05 AM - Last modified June 8, 2016 9:05 AM
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