Figure 5.

Figure 2. Simulations produced tracks with the same autocorrelation structure in turning angles s and distance moved per half-hour step d as observed in telemetry data. The panel to the right shows a simulated track. Details on movement simulations are provided in Nabe-Nielsen et al. 2013 (Oikos, doi: 10.1111/ j.1600-0706.2013.00069.x).

Figure 4. The move per half-hour time step in the absence of noise is represented by the vector A. It is calculated from a combination of CRW behaviour and a memory of the locations of previously visited food patches. The effect of noise is represented by B. The length of B is proportional to the sound pressure level, which decreased linearly with the distance to the source. The actual move taken is represented by D.

Figure 1. Harbour porpoises are caught in pound nets used in commercial fisheries and subsequently equipped with telemetry tags in order to study their movement behaviour.

Figure 5. Variations in energy and number of super-individuals. Food and energy in relative measures. Each simulation year started on 1 Jan.

Figure 3. Simulation including existing wind farms in the IDW and large ships along the main shipping routes. Porpoises were simulated as super-individuals, each representing several real female porpoises. The colour of the food patches changed from yellow to orange and green as the food level increased.

Figure 6. Average yearly population sizes over 30 simulation years for scenarios including existing wind farms (e), planned wind farms (p), large ships (s) and different yearly by-catch rates (b) measured in number of super-individuals. Error bars indicate ±1 SD. Five replicates were run for each scenario.

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Food in patchesMean porpoise energy

Noise from ships and wind farms can cause marine mammals to change behaviour. They may forage less efficiently if disturbed, or they may avoid dispersing through some areas. Although behavioural changes are sometimes observed for individual animals, little is known about how populations are affected. The aim of this study is to investigate how the dynamics and survival of the harbour porpoise population in the Inner Danish Waters (IDW) is affected by the combined effects of noise and by-catch using an individual-based population model.

In order to study how the porpoise population responds to different noise scenarios it is important to simulate the movements of undisturbed animals as realistically as possible. We used a combination of correlated random walk (CRW) and spatial memory behaviour to produce movement patterns that strongly resembled those of satellite-tracked animals (Fig. 2). The spatial memory behaviour allowed the simulated animals to navigate back to food patches they had visited in the past if the CRW behaviour was not sufficiently profitable.

The energy levels of the simulated porpoises depended on their ability to find food and the time spent foraging. As the spatial distribution of the porpoises’ prey is unknown, we simulated food as being distributed in randomly dispersed, equal-sized patches (Fig. 3). Patches located where porpoises frequently occur in nature could contain more food than the ones in less used areas. In the model the porpoises consumed the food they encountered on their way. Subsequently the food level increased logistically in the patches where it had been depleted.

Noise caused the simulated animals to deviate from the behaviour they would have had in the absence of disturbances (Fig. 4). This caused them to forage less efficiently which in turn caused them to have an increased risk of dying.

In the model the population dynamics emerged from the balance between recruitment and mortality. The risk of dying increased as the animals’ energy levels decreased. Their energy use increased when they were lactating and during winter, causing the average energy level and the population size to fluctuate (Fig. 5). The parameters that controlled the animals‘ chances of giving birth, their temperature- dependent energy use, when they should mate etc. were obtained from literature.

When introducing wind turbines and ships into the model it caused the equilibrium population size to decrease approx. 10 percent (Fig. 6). This was based on the worst-case assumption that post construction noise from turbines caused animal densities to be strongly reduced at a distances of up to 300 m from the turbine, and the results also depended on how fast food replenished in the patches.

Although the population carrying capacity decreased when introducing wind farms and ships, none of the shown scenarios resulted in a population collapse. Only the inclusion of by-catch rates of ~10 percent resulted in continuous population declines.

The study was funded by The Environmental Group under the Danish Environmental Monitoring Programme and by the European Union under the 7th Framework Programme (project acronym: CREAM, contract number PITN-GA-2009-238148, http://cream-itn.eu/).

The study illustrates how a spatially explicit, behaviour-based model can be used for investigating the relative impacts of various management scenarios. This has not previously been attempted for marine mammals. Rather than providing exact predictions, this type of study could be used to produce worst-case scenarios and to identify parameters that have a particularly large impact on population survival, and where further research is needed.

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