MarCPFS (Marine Central Place Foragers Simulator) is a spatially-explicit bio-energetic simulator which was developed to study the influence of body length, behavioural traits and environmental changes on breeding success of the Antarctic fur seal (Arctocephalus gazella; Massardier-Galatà et al., 2017), using the individual-based modelling technique. Only adult female fur seals are modeled in this study.

SEAPODYM (Spatial ecosystem and population dynamics model) model is a coupled physical-biological-fisheries model at ocean basin scale. It includes a nutrient-phytoplankton-zooplankton model, a forage sub-model and an age-structured model of a predator species driven by environmental ocean forcing fields (temperature, currents, dissolved oxygen and primary production) provided by a coupled biogeochemical-physical model.


Simulated movements of fur seal females in Kerguelen area overlaying seapodym micronekton (prey) model outputs

Foraging areas recorded by Lea and Dubroca, 2003

Foraging areas recorded by Lea and Dubroca, 2003

The coupling between MarCPFS and SEAPODYM allows the predators to operate in realistic dynamic environments. For instance the simulation includes the current effects on the females swimming effort, the daily displacement of the resource and the fishing constraint (here fishing means the action of predation) linked to water temperature in an attempt to predict the likely evolution of predator populations under various environmental conditions (Figure above). The main goal of the study was to assess how changes in abundance and accessibility of prey in the long term could alter the success of reproduction. To achieve this goal, a simulation of SEAPODYM was produced using a climate change scenario in line with the predictions of the IPCC scenario RCP8.5 from 1998 to 2100.

Success of the female-pup pairs for each breeding season. In blue, the simulator results and in red the average trend of the results.

Success of the female-pup pairs for each breeding season. In blue, the simulator results and in red the average trend of the results.

First results show strong interannual variability (Figure above), highlighting the alternation of favourable and unfavourable years. A rapid decrease of the breeding success and of the pup survival rate is noted from the year 2060. The results show that in an unfavourable year, particularly after 2060, females perform longer trips, implying that in correlation with the predicted increase of the Sea Surface Temperature and the isotherm shifts, females would have to travel further to reach their foraging ground. The analysis of fished zones showed a southward shift towards relatively poorer areas accompanied by a decrease in the fishing frequencies (Figure below).

 

Distribution of the fishing frequencies of 50 females in 2000 superimposed on the corresponding distribution maps of the resource (g / m²) with isothermal representation (January). The higher the circle radius, the higher the fishing frequencies on the grid cell. The warmer the color, the richer in prey.

Distribution of the fishing frequencies of 50 females in 2000 superimposed on the corresponding distribution maps of the resource (g / m²) with isothermal representation (January). The higher the circle radius, the higher the fishing frequencies on the grid cell. The warmer the color, the richer in prey.

Distribution of the fishing frequencies of 50 females in 2000 superimposed on the corresponding distribution maps of the resource (g / m²) with isothermal representation (January). The higher the circle radius, the higher the fishing frequencies on the grid cell. The warmer the color, the richer in prey.

Distribution of the fishing frequencies of 50 females in 2100 superimposed on the corresponding distribution maps of the resource (g / m²) with isothermal representation (January). The higher the circle radius, the higher the fishing frequencies on the grid cell. The warmer the color, the richer in prey.

 

 

Reference

  • Huston M, De Angeli D & Post W (1988). New Computer Models Unify Ecological Theory.
    BioScience Vol. 38 No. 10, pp. 682-691
  • Lea, M.-A., and Dubroca, L. (2003). Fine-scale linkages between the diving behaviour of Antarctic fur seals and oceanographic features in the southern Indian Ocean. ICES J. Mar. Sci. J. Cons. 60, 990–1002.
  • Lehodey, P., Senina, I., and Murtugudde, R. (2008). A spatial ecosystem and populations dynamics model (SEAPODYM) – Modeling of tuna and tuna-like populations. Prog. Oceanogr. 78, 304–318.
  • Massardier-Galatà, L., Morinay, J., Bailleul, F., Wajnberg, E., Guinet, C., and Coquillard, P. (2017). Breeding success of a marine central place forager in the context of climate change: A modeling approach. PLOS ONE 12, e0173797.