Agent-based model meant to explore the effects of inequalities on crop-livestock integration in Sahel agrosylvopastoral systems.
Model developped for the 3rd CID held in Dakar, on November 2021. Poster (French)
Using GAMA Platform v. 1.8.2 (developper build ff11705a).
To run the model, launch from main.gaml. To run sensivity analysis, launch from batch.gaml.
10 000 000 lists of random numbers in ⟦0,1⟧ were generated and had their gini index computed. A sample of 10 of them was extracted with varying Gini indexes (see GenerGini.gaml for details). These lists were then used as input parameters for the model, as to set up the repartition of herd sizes and fertilised parcels area (using empirical factors). Sensivity analysis is then run on these indexes (i.e. on the lists they correspond to) with ICR (system integration metric, computed on nutrient fluxes) as the computed output of the model.
Random numbers lists used for the poster are included as a CSV file in ./includes/. New lists and afferent Gini indexes can be generated using GenerGini.gaml.
Achard, F., Banoin, M., 2003. Fallows, forage production and nutrient transfers by livestock in Niger. Nutrient Cycling in Agroecosystems 7.
Audouin, E., Odru, M., Vayssières, J., Masse, D., Lecomte, P., 2014. Reintroducing livestock to improve village-scale agricultural productivity, nutrient balance and nutrient use effciency: the case of Senegalese groundnut basin.
Balandier, M.-L., 2017. Describing diversity and crop-livestock integration in smallholder mixed farming systems in Sub-Saharan Africa: An application of network analysis in the former Senegalese Groundnut Basin (Master 2). Wageningen University, Wageningen.
Chirat, G., Groot, J.C.J., Messad, S., Bocquier, F., Ickowicz, A., 2014. Instantaneous intake rate of free-grazing cattle as affected by herbage characteristics in heterogeneous tropical agro-pastoral landscapes. Applied Animal Behaviour Science 157, 48–60. https://doi.org/10.1016/j.applanim.2014.06.003
Gersie, S., 2020. Predicting Cattle Grazing Distributions: An Agent-Based Modeling Approach (MSc Thesis). Colorado State University.
Grange, G., 2015. Suivi du cycle de l’azote en fermes réelles : Cas des systèmes agropastoraux du bassin arachidier du Sénégal (Ingénieur agronome - Master 2). Montpellier SupAgro, Montpellier.
Grillot, M., Guerrin, F., Gaudou, B., Masse, D., Vayssières, J., 2018. Multi-level analysis of nutrient cycling within agro-sylvo-pastoral landscapes in West Africa using an agent-based model. Environmental Modelling & Software 107, 267–280. https://doi.org/10.1016/j.envsoft.2018.05.003
INRA, 2018. L’alimentation des ruminants.
Latham, L.G., 2006. Network flow analysis algorithms. Ecological Modelling 192, 586–600. https://doi.org/10.1016/j.ecolmodel.2005.07.029
Stark, F., Vayssières, J., Vigne, M., García, E.G., Moulin, C.-H., 2016. Ecological network analysis used to assess the agroecological properties of farming systems, in: EcoSummit 2016 Ecological Sustainability: Engineering Change. p. np.
Wade, C., 2016. Analyse des flux d’azote en milieu paysan : Cas des systèmes agropastoraux du bassin arachidier du Sénégal (Ingénieur agronome - Master 2). Ecole Nationale Supérieure d’Agriculture de Thies, Thies, Sénégal.
Zampaligré, N., Schlecht, E., 2018. Livestock foraging behaviour on different land use classes along the semi-arid to sub-humid agro-ecological gradient in West Africa. Environ Dev Sustain 20, 731–748. https://doi.org/10.1007/s10668-017-9907-y