LINCX: Linking Network structure and species CoeXistence.
SIMPLEX: Simple models that capture the complexity of multi-species coexistence
Explora ciencia projects CGL2014-61590-EXP and CGL2017-92436-EXP.
Researchers: Ignasi Bartomeus and Oscar Godoy
This two linked projects explore how we can add multitrophic complexity to species coexistence models.
Lincx put forward the fundational theoretical work (Godoy et al 2019), and tested the models with experimental (Bartomeus et al. In prep) and observational data (Lanuza et al 2019).
Papers:
- Godoy, O., Bartomeus, I., Rohr, R. P., & Saavedra, S. (2018). Towards the integration of niche and network theories. Trends in Ecology & Evolution, 33(4), 287-300.
- Lanuza, J. B., Bartomeus, I., & Godoy, O. (2018). Opposing effects of floral visitors and soil conditions on the determinants of competitive outcomes maintain species diversity in heterogeneous landscapes. Ecology Letters, 21(6), 865-874.
- Bartomeus, I., & Godoy, O. (2018). Biotic controls of plant coexistence. Journal of Ecology, 106(5), 1767-1772.
- Bartomeus, I., Rohr, R. P., & Saavedra, S., Godoy, O. Experimental evaluation of network topolgy on species coexistence. In prep.
- Busche, Bartomeus, Godoy. Higher Order Interactions. In Prep.
SIMPLEX tries to operationalyze those models (MartYn et al In review), make them useful (Garcia-Callejas et al 2020), and predictive (Garcia-Algarra et al In Prep).
Papers:
- García‐Callejas, D., Godoy, O., & Bartomeus, I. cxr: A toolbox for modelling species coexistence in R. Methods in Ecology and Evolution. In press.
R Package: https://github.com/RadicalCommEcol/cxr
- Garcia-Algarra, Civantos, Garcia-Callejas, Godoy, Bartomeus. Using Machine Learning to predict species coexistance. In Prep.
- Garcia-Callejas, Hurtado, Godoy, Bartomeus. The multilayer structure of plant-pollinator-herbivore networks. In prep.
- Trace E. Martyn1, Daniel B. Stouffer, Oscar Godoy, Ignasi Bartomeus, Abigail Pastore, Margaret M. Mayfield. Identifying ‘useful’ fitness models: balancing the benefits ofadded complexity with realistic data requirements in modelsof individual plant fitness. In Review.