Through the integration of Ecology, Mathematics, and Computer Science in Theoretical Ecosystem Ecology (TEE), the ecosystems can now be understood as a whole. Hence, it is possible to simulate and/or predict complex ecosystem dynamics by modeling their processes with equations. Indeed, these models have guided the formulation of new experiments and ecosystem management projects. The Ecosystems provide important services; the vegetation, in particular, alliviates the environmental impact of the green house gas, CO2, by sequestering it from the atmosphere. Once the carbon is fixed in the plants, it can rapidly return to the atmosphere by respiration, or be allocated, transfered, to different organs with fast or slow resident times (e.g., leaves and woody tissues, respectively). Considering the former service of vegetation, it is of interest to predict its response to changing environmental conditions (increase in CO2 concentration and temperature). Current models of carbon allocation in vegetation often disagree in their simulations. This disagreement could result from differences in the mathematical relation between their driving variables, which could be linear or non-linear.
With my PhD project I intend to show that the ability of a model to simulate ecosystems complex dynamics relies on whether it is linear or not; linear models can only portray systems with one stable state, whereas non-linear models better represent the systems that have alternative states to which they can switch when the environmental conditions change. Granted that, our contribution could enrich the robust framework that would guide the modelers through the selection of suitable equations for specific problems. The level of abstraction of the mathematics behind TEE will allow us to focus in the main processes that should be taken into account when modeling carbon allocation in vegetation. So far, this approach has improved our understanding of the stability of the systems, and hopefully it will impact the formulation of more suitable management strategies that, for example, are aware of the warning signs of ecosystems with alternative stable states.
The following diagram represents the question addressed in this project, as well as the stages through which it will be developed:
Some preliminary results can be found in the following poster:
- Ceballos-Núñez, V., Müller, M., & Sierra, C. A. (2020). Towards better representations of carbon allocation in vegetation: a conceptual framework and mathematical tool. Theoretical Ecology, 13(3), 317–332. https://doi.org/10.1007/s12080-020-00455-w
- Sierra, C. A., Ceballos-Núñez, V., Metzler, H., & Müller, M. (2018). Representing and Understanding the Carbon Cycle Using the Theory of Compartmental Dynamical Systems. Journal of Advances in Modeling Earth Systems, 10(8), 1729–1734. https://doi.org/10.1029/2018MS001360
- Ceballos-Núñez, V., Richardson, A. D., & Sierra, C. A. (2018). Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models. Biogeosciences, 15(5), 1607–1625. https://doi.org/10.5194/bg-15-1607-2018
- Ceballos-Núñez, V. (2018). Nonlinearities in Carbon Allocation and Vegetation Functioning Dissertation (pp. 124 p.) [PhD thesis, Friedrich-Schiller-Universiät Jena]. http://www.clib-jena.mpg.de/theses/bgc/BGC18006.pdf
January 2015 - Today
PhD student @ Max Planck Institute for Biogeochemistry @ Department of Biogeochemical Processes
October 2013 - December 2013
Visitor student @ Max Planck Institute for Molecular Plant Physiology @ in the group Systembiologie und mathematische Modellierung
February 2006 - November 2011
BSc. Biology Universidad del Valle, with emphasis in Genetics