From Individuals to Ecosystems: Scaling metabolic theory to predict ecosystem function with global change

Perturbations such as pollution and climate change can have large impacts across multiple ecological scales, a process driven in part by the modification of the metabolic rates of individual organisms. These effects are seen in the change of ecosystem function, as processes such as carbon sequestration and nitrogen cycling are altered. Though most research has focused on ecosystem function at a single tropic level (i.e. using just plant communities) recent work suggests that there is a significant feedback between the structure and dynamics of trophic interaction networks and ecosystem function as a whole [1,2]. It is therefore important that we understand how individual metabolism scales up to the structure and dynamics of whole ecological networks and how this relates to ecosystem function if we are to predict the impacts of human activities on natural communities and the resilience and recovery rate of their function. In particular, recent work suggests that variation in individual physiology can have important effects in ecological networks, by constraining interactions between consumer-resource species pairs, energy and matter flows, and stability of ecosystems [3].

This PhD project will use a novel combination of metabolic/physiological theory [4-7], dynamical network (graph) theory [8,9], and parameterizations using a global database on metabolic performance of individuals to address key questions about the effect of individual metabolism and environmental change on community dynamics, structure and ecosystem functioning: (1) How does variation in physiology across individuals and species scale to affect network structure and dynamics? (2) How do these changes alter total ecosystem function? (3) How do these factors affect the thermal response dynamics of whole ecosystem function? (4) Will between-species differences in physiology hinder resilience and recovery of ecosystem function to changing climate? (5) What motifs (components) of network structure strongly determine the thermal response dynamics of whole ecosystem function, and can therefore be used to mitigate climate change impacts?

To address such questions, the student will extend metabolic theory [3,6,7] to dynamically assembling interaction networks using mathematical and computational techniques [8,15]. The model will be parameterized using data on species-level variation in individual physiology induced by variation in size as well as thermal acclimation/adaptation, available in a global database on metabolic traits (BioTraits) of over 1000 species and 10,000's of measurements, currently maintained at Silwood Park. This will generate empirically-grounded theoretical predictions that will then be tested using burgeoning empirical data from geothermal stream communities sampled across temperature gradients and experimentally warmed aquatic mesocosms at Silwood Park [10-14], where ecosystem assembly and functional turnover are being recorded at an unprecedented resolution.

References: 1. Schneider et al. Nat. Commun. 7:12718; 2. Wang et al. Ecol. Lett 10.1111/ele.12865; 3. Dell et al J. Anim. Ecol. 82, (2013); 4. Dell et al Ecology 94, 1205 (2013); 5. Dell et al PNAS 108, 10591-10596 (2011); 6. Pawar et al Nature 486, 485--489 (2012); 7. Reuman et al J. Anim. Ecol. (2013); 8. Pawar, J. Theor. Biol. 259, 601-612 (2009); 9. Cohen et al PNAS 106, 22335-22340 (2009); 10. Perkins et al. Glob. Chang. Biol. 18, 1300-1311 (2012); 11. Yvon-Durocher et al Philos. Trans. R. Soc. Lond. B. 367, 2998-3007 (2012); 12. Dossena et al Proc. R. Soc. B 279, 3011-9 (2012); 13. O'Gorman et al. Adv. Ecol. Res. 47, 81-176 (2012); 14. Yvon-Durocher, G. et al. Nature 487, 472-6 (2012). 15. Allesina & Tang Nature 483, 205-208 (2012).