Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology.
Publications
2021
Peace A, Frost PC, Wagner ND, Danger M, Accolla C, Antczak P, Brooks BW, Costello DM, Everett RA, Flores KB, et al. Stoichiometric Ecotoxicology for a Multisubstance World. BioScience. 2021;71(2):132–147. doi:10.1093/biosci/biaa160
2020
Nardini JT, Lagergren JH, Hawkins-Daarud A, Curtin L, Morris B, Rutter EM, Swanson KR, Flores KB. Learning equations from biological data with limited time samples. Bulletin of mathematical biology. 2020;82(9):1–33.
Everett R, Flores KB, Henscheid N, Lagergren J, Larripa K, Li D, Nardini JT, Nguyen PT, Pitman B, Rutter EM. A tutorial review of mathematical techniques for quantifying tumor heterogeneity. Mathematical Biosciences and Engineering. 2020;17(4).
Lagergren JH, Nardini JT, Lavigne M, Rutter EM, Flores KB. Learning partial differential equations for biological transport models from noisy spatio-temporal data. Proceedings of the Royal Society A. 2020;476(2234):20190800.
Stepien TL, Rutter EM, Kuang Y. A nondegenerate convective-reaction-density-dependent diffusion model of in vitro glioblastoma tumor growth. bioRxiv. 2020.
2019
Rutter EM, Lagergren JH, Flores KB. A convolutional neural network method for boundary optimization enables few-shot learning for biomedical image segmentation. Springer; 2019. pp. 190–198.
2018
Rutter EM, Langdale CL, Hokanson JA, Hamilton F, Tran H, Grill WM, Flores KB. Detection of bladder contractions from the activity of the external urethral sphincter in rats using sparse regression. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2018;26(8):1636–1644.
Rutter E, Banks HT, Flores K. Estimating intratumoral heterogeneity from spatiotemporal data. Journal of Mathematical Biology. 2018;77(6):1999–2022.
Banks H, Flores K, Rosen I, Rutter E, Sirlanci M, Thompson C. The Prohorov Metric Framework and aggregate data inverse problems for random PDEs. Commun. Appl. Anal. 2018;22:415–446.
Pell B, Phan T, Rutter EM, Chowell G, Kuang Y. Simple multi-scale modeling of the transmission dynamics of the 1905 plague epidemic in Bombay. Mathematical Biosciences. 2018;301:83–92.