From individual behavior and pack dynamics to population responses: An individual-based approach to model the wolf social life cycle

Bauduin, S.; Grente, O.; Santostasi, N.; Ciucci, P.; Duchamp, C.; Gimenez, O.

doi:10.1101/2020.01.24.918490

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bioRxiv · 10.1101/2020.01.24.918490

From individual behavior and pack dynamics to population responses: An individual-based approach to model the wolf social life cycle

Bauduin, S.·Grente, O.·Santostasi, N.·Ciucci, P.·Duchamp, C.·Gimenez, O.

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Abstract

The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to predict wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM predicts wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different types of breeder replacement. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the most the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model predictions. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.

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Bauduin, S., Grente, O., Santostasi, N., Ciucci, P., Duchamp, C., Gimenez, O.. 2020-01-25. From individual behavior and pack dynamics to population responses: An individual-based approach to model the wolf social life cycle. https://doi.org/10.1101/2020.01.24.918490

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