We are interested in biomass accrual – how cells, traits, individuals, populations, and ecosystems gain energy and materials – and why it varies. Accurate prediction of biomass accrual lies at the foundation of both basic and applied biology. Such capabilities are required to solve emerging environmental issues, and long-standing problems in basic ecology and evolution. 

To understand change in biomass, it helps to know what makes up biomass. This Voronoi tree diagram of the composition of a growing E. coli cell provides a general picture (Milo & Phillips 2015). Viewing this plot from a biogeochemical perspective, the common stoichiometry of protoplasmic life, and fundamental anabolic processes such as protein synthesis become readily apparent (e.g., see figure below about the proportion of nitrogen and phosphorus in various biomolecules; Sterner & Elser 2002).

Consequently, we know much about the relationship between growth and bulk elements (e.g., N, P) because they are required for ribosome biogenesis and protein synthesis. Agricultural demand for these elements has altered the cycles of these elements, impacting the functioning of non-target ecosystems and the ecology and evolution of biota in the Anthropocene. As such, sustainable management of biogeochemical cycles requires a fundamental understanding of biomass accrual. However, precise prediction of biomass accrual eludes us, largely because of diversity in nutrient-growth functions among genotypes, species, and ecosystems.  

Monod (1949) delves into his landmark review highlighting the need for formal models describing growth, enterprises that “have repeatedly proved sterile”. Seventy years on, there have been few efforts as fertile as Monod’s. Nevertheless, the performance of the model equating growth to nutrient supply varies considerably in natural conditions and is rather futile in describing growth at higher levels of organization (e.g., productivity of ecosystems). Droop (1973) discovered the role of nutrient quotas in growth that has performed better in field conditions, and in describing ecosystem productivity, although there is considerable variation in fit (Sommer 1991). The Droop model has the potential to generally explain growth and productivity, as captured in the integrative framework of ecological stoichiometry (ES) that aims to link energetics with biogeochemistry to understand a variety of ecological processes (Sterner & Elser 2002).  

We contend that the Law of Minimum (Sprengel 1838; Leibig 1855), on which aforementioned models are based upon, rarely holds. This is not surprising given genomic-era data on the system-wide adjustments organisms make in response to changes in supply of elements that are required for protein assembly (in the presence of enough energy, of course). Such responses should alter the quotas of multiple other elements, possibly with huge growth implications. As such, we measure the entire suite of elements involved in the system to discover dynamics in quotas of the 20-odd biogenic elements as a function of growth and production. We believe that such information illuminates the entire suite of mechanisms underlying growth dynamics as energy, nitrogen, and phosphorus supplies change (reflecting global change scenarios).

As a word of reassurance to chemistry-phobic biologists, we do not do much organic or biochemistry. We do bio-inorganic chemistry. We use simple rules of the Periodic Table, and basic physicochemical principles (e.g., mass balance) to dig into the foundations of biology. For example, we consider any biological system (e.g., cell, tissue, organism, population) as a collection of elements. These elements have to be acquired from the environment, assimilated, and allocated to various fitness enhancing functions (including of course, growth). Measuring an element in one pool enables predictions about others as shown in the simplified schematic above (Jeyasingh et al. 2014). We not only solve it numerically, but importantly also verify it empirically, Doing this for multiple elements simultaneously is challenging, but ridiculously fun and rewarding! 

We employ theory, lab experiments, field surveys, and metadata to improve our understanding of the fundamental links among energy/material supply and the quantity and quality of biomass accrued at different levels of organization (cells, organs, individuals, populations, ecosystems). We are set up to study freshwater taxa and ecosystems, although we continue to work collaboratively in a variety of systems. Positions for undergraduate, graduate, and postdoctoral research are available or can be developed. Email Puni (puni.jeyasingh@okstate.edu).

Droop M (1973) Some thoughts on nutrient limitation in algae. J Phycol 9:264–272.

Jeyasingh, P. D., R. D. Cothran, and M. Tobler. 2014. Testing the ecological consequences of evolutionary change using elements. Ecology and evolution 4:528–538.

Liebig J (1855) Principles of agricultural chemistry. Dowden, Hutchinson & Ross, London.

Milo R, Phillips R (2015) Cell Biology by the Numbers. Garland Science.

Monod J (1949) The growth of bacterial cultures. Annu Rev Microbiol 3:371–394.

Sommer U (1991) A comparison of the Droop and the Monod models of nutrient limited growth applied to natural populations of phytoplankton. Func Ecol 5: 535-544. 

Sprengel C (1838) The science of cultivation and soil amelioration. Immanuel Muller Co., Leipzig, Germany.

Sterner RW, Elser JJ (2002) Ecological Stoichiometry. Princeton University Press.