Ecologists have long been intrigued by the ways co-occurring species divide limiting resources. Such resource partitioning, or niche differentiation, may promote species diversity by reducing competition. Although resource partitioning is an important determinant of species diversity and composition in animal communities, its importance in structuring plant communities has been difficult to resolve. This is due mainly to difficulties in studying how plants compete for below-ground resources. Here we provide evidence from a 15N-tracer field experiment showing that plant species in a nitrogen-limited, arctic tundra community were differentiated in timing, depth and chemical form of nitrogen uptake, and that species dominance was strongly correlated with uptake of the most available soil nitrogen forms. That is, the most productive species used the most abundant nitrogen forms, and less productive species used less abundant forms. To our knowledge, this is the first documentation that the composition of a plant community is related to partitioning of differentially available forms of a single limiting resource.

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Variations of the 13C content of marine participate organic carbon (δ13CPOC) in the modern ocean were studied using literature data to test the assumptions underlying the calculation of atmospheric pCO2 through geological time from the δ13C of sedimentary organic matter. These assumptions are that (1) concentrations of CO2 in the atmosphere and the surface ocean are at equilibrium at all times and latitudes and that (2) carbon isotopic fractionation of phytoplankton (ϵp) covaries primarily with concentrations of dissolved molecular CO2 ([CO2]aq). Previous studies and compilations have shown that the first assumption does not strictly hold, although [CO2]aq may be predicted with a reasonable degree of accuracy from sea surface temperature for specific regions of the world ocean. The second assumption is shown to be questionable due to the weak covariation of ϵp and [CO2]aq in the modern ocean. The large residual variance for regressions of ϵp against [CO2]aq suggests that factors other than [CO2]aq strongly affect carbon isotopic fractionation in phytoplankton. It is concluded that the relationship between ϵp and [CO2]aq cannot be easily calibrated using δ13CPOC data from the modern ocean.

Compound-specific isotopic analysis of amino acids (CSIA-AA) has emerged in the last decade as a powerful approach for tracing the origins and fate of nitrogen in ecological and biogeochemical studies. This approach is based on the empirical knowledge that source AAs (i.e., phenylalanine), fractionate 15 N very little (<0.5‰) during trophic transfer, whereas trophic AAs (i.e., glutamic acid), are greatly (~6-8‰) enriched in 15 N during each trophic step. The differential fractionation of these two AA groups can provide a valuable estimate of consumer trophic position that is internally indexed to the baseline δ 15 N value of the integrated food web. In this paper, we critically review the analytical methods for determining the nitrogen isotopic composition of AAs by gas chromatography/isotope-ratio mass spectrometry. We also discuss methodological considerations for accurate trophic position assessment of organisms using CSIA-AA. We then discuss the advantages and challenges of the CSIA-AA approach by examining published studies including trophic position assessment in various ecosystems, reconstruction of ancient human diets, reconstruction of animal migration and environmental variability, and assessment of marine organic matter dynamics. It is clear that the CSIA-AA approach can provide unique insight into the sources, cycling, and trophic modification of organic nitrogen as it flows through systems. However, some uncertainty still exists in how biochemical, physiological, and ecological mechanisms affect isotopic fractionation of trophic AAs. We end this review with a call for continued exploration of the mechanisms of AA isotopic fractionation, through various studies to promote the evolution of the rapidly growing field of CSIA-AA.

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