NetLogoR: a package to build and run spatially explicit agent‐based models in R

Bauduin, Sarah; McIntire, Eliot J. B.; Chubaty, Alex M

doi:10.1111/ecog.04516

Cited by 15 publications

(10 citation statements)

References 21 publications

(37 reference statements)

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“…The R language is largely used by ecologists and coding the model in this language should likely ease its understanding and adaptation. We used the R package NetLogoR (Bauduin et al, 2019) to facilitate the implementation of the individual-based model structure in R language and the package pedantics (Morrissey, 2018) to calculate relatedness between individuals using their mother and father IDs. We also used the packages SciViews (Grosjean, 2018) and testthat (Wickham et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

Exploring the impact of lesser-known social dynamics on wolf populations through an individual-based approach

Bauduin¹,

Grente²,

Santostasi

et al. 2020

Preprint

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Highlights-We developed an individual-based model (IBM) simulating wolf population dynamics.-The IBM incorporates up-to-date knowledge of pack structure and dynamics.-The IBM is flexible and modular and can be adapted to any wolf populations.-The IBM is written in R language to make its use by ecologists easy. AbstractThe presence 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.Here we present an individual-based model (IBM) to project wolf population dynamics. 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 processes based on up-to-date scientific literature. The model extends previous attempts to represent wolf population dynamics, as we included important biological processes that were not previously considered such as pack dissolution, asymmetric male and female breeder replacement by dispersers or subordinates, inbreeding avoidance, establishment of dispersing individuals by budding, adoption of young dispersing wolves, long distance dispersal, and density-dependent mortality. We demonstrate two important aspects of our IBM (i.e., modularity and flexibility) by running different series of the processes representing the wolf life cycle. The simulations point out the importance of data records on these biological components when managers are willing to promote wolf population conservation and management strategies. This exercise also shows that the model can flexibly include or exclude different processes therefore being applicable to wolf populations experiencing different ecological and demographic conditions. The model is coded in R to facilitate its understanding, appropriation and adaptation by ecologists. Overall, our model allows testing different scenarios of wolf dynamics, disturbances and alternative management strategies to project wolf populations, and therefore inform decision making to improve wolf management and conservation.

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Section: Methodsmentioning

confidence: 99%

Exploring the impact of lesser-known social dynamics on wolf populations through an individual-based approach

Bauduin¹,

Grente²,

Santostasi

et al. 2020

Preprint

Self Cite

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“…At their new location, dispersing males check if they The model is coded using R 4.1.0 (R Core Team, 2014). We used the package NetLogoR (Bauduin et al, 2019) to facilitate the IBM structure implementation in R language and the package SpaDES (Chubaty and McIntire, 2018) to schedule SE-IBM rules with different time females and road mortality territory may change at every dispersal step. The steps variable is updated each day, and age and status are updated once a year.…”

Section: Se-ibm Rules According To Lynx Ecology (Se-ibm 4 Th Component)mentioning

confidence: 99%

“…The model is coded using R 4.1.0 (R Core Team, 2014). We used the package NetLogoR (Bauduin et al, 2019) to facilitate the IBM structure implementation in R language and the package SpaDES (Chubaty and McIntire, 2018) to schedule SE-IBM rules with different time units. We also used the packages data.table (Dowle and Srinivasan, 2019), randomcoloR (Ammar, 2019), raster (Hijmans and Van Etten, 2018), and testthat (Wickham et al, 2019).…”

Section: Se-ibm Rules According To Lynx Ecology (Se-ibm 4 Th Component)mentioning

confidence: 99%

Eurasian lynx populations in Western Europe: What prospects for the next 50 years?

Bauduin¹,

Germain²,

Zimmermann

et al. 2021

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Persistence of viable populations may be uncertain for large carnivore species, especially for those established in human-dominated landscapes. Here, we studied the Eurasian lynx in Western Europe established in the Upper Rhine metapopulation (i.e., Jura, Vosges-Palatinian and Black Forest populations) and in the Alpine population. These populations are currently considered as endangered or critically endangered due to high anthropogenic mortality and isolation. We assessed lynx persistence over a 50-year time horizon by implementing a spatially-explicit individual-based model while accounting for road mortality and habitat selection. For the Alpine and Jura populations, forecasts showed a steady growth rapidly reaching a stabilization phase with high resident female occupancy, and a positive growth for the newly re-established Vosges-Palatinian population. Moreover, this population showed a difference in female occupancy between the northern part, where a recent reintroduction program was conducted in the Palatinate Forest, and the southern part. Only the group of individuals in the Black Forest had an irregular growth probably due to the small number of only male lynx at start of the simulation and poor connectivity to surrounding populations. Exchanges of individuals between populations were limited, and the Jura population played the role of a crossroad. Persistence of lynx in Western Europe seems likely on a large scale over the next 50 years. However, lynx persistence in the southern part of the Vosges-Palatinian population and in the Black Forest appears challenging without long-term conservation management.

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“…For this, we use the life-cycle of the ground squirrel Spermophilus dauricus presented in Box 2. The simulations were done in R using the package NetLogoR (Bauduin et al, 2019), and correspond to a female-based population. At each time step, the individuals went through the following events, successively:…”

Section: Spermophilus Dauricusmentioning

confidence: 99%

The Kinship Matrix: Inferring the Kinship Structure of a Population from its Demography

Coste¹,

Bienvenu

Ronget

et al. 2021

Preprint

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The familial structure of a population and the relatedness of its individuals are determined by its demography. There is, however, no general method to infer kinship directly from the life-cycle of a structured population. Yet this question is central to fields such as ecology, evolution and conservation, especially in contexts where there is a strong interdependence between familial structure and population dynamics. Here, we give a general formula to compute, from any matrix population model, the expected number of arbitrary kin (sisters, nieces, cousins, etc) of a focal individual ego, structured by the class of ego and of its kin. Central to our approach are classic but little-used tools known as genealogical matrices, which we combine in a new way. Our method can be used to obtain both individual-based and population-wide metrics of kinship, as we illustrate. It also makes it possible to analyze the sensitivity of the kinship structure to the traits implemented in the model.

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NetLogoR: a package to build and run spatially explicit agent‐based models in R

Cited by 15 publications

References 21 publications

Exploring the impact of lesser-known social dynamics on wolf populations through an individual-based approach

Exploring the impact of lesser-known social dynamics on wolf populations through an individual-based approach

Eurasian lynx populations in Western Europe: What prospects for the next 50 years?

The Kinship Matrix: Inferring the Kinship Structure of a Population from its Demography

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