Meta-analysis of primary producer amino acid δ\u3csup\u3e15\u3c/sup\u3eN values and their influence on trophic position estimation

Compound-specific stable isotope analysis of individual amino acids (CSIA-AA) has emerged as a transformative approach to estimate consumer trophic positions (TPCSIA) that are internally indexed to primary producer nitrogen isotope baselines. Central to accurate TPCSIA estimation is an understanding of beta (β) values—the differences between trophic and source AA δ15N values in the primary producers at the base of a consumers’ food web. Growing evidence suggests higher taxonomic and tissue-specific β value variability than typically appreciated. This meta-analysis fulfills a pressing need to comprehensively evaluate relevant sources of β value variability and its contribution to TPCSIA uncertainty. We first synthesized all published primary producer AA δ15N data to investigate ecologically relevant sources of variability (e.g., taxonomy, tissue type, habitat type, mode of photosynthesis). We then reviewed the biogeochemical mechanisms underpinning AA δ15N and β value variability. Lastly, we evaluated the sensitivity of TPCSIA estimates to uncertainty in mean βGlx-Phe values and Glx-Phe trophic discrimination factors (TDFGlx-Phe). We show that variation in βGlx-Phe values is two times greater than previously considered, with degree of vascularization, not habitat type (terrestrial vs. aquatic), providing the greatest source of variability (vascular autotroph = –6.6 ± 3.4‰; non-vascular autotroph = +3.3 ± 1.8‰). Within vascular plants, tissue type secondarily contributed to βGlx-Phe value variability, but we found no clear distinction among C3, C4, and CAM plant βGlx-Phe values. Notably, we found that vascular plant βGlx-Lysvalues (+2.5 ± 1.6‰) are considerably less variable than βGlx-Phe values, making Lys a useful AA tracer of primary production sources in terrestrial systems. Our multi-trophic level sensitivity analyses demonstrate that TPCSIA estimates are highly sensitive to changes in both βGlx-Phe and TDFGlx-Phe values but that the relative influence of β values dissipates at higher trophic levels. Our results highlight that primary producer β values are integral to accurate trophic position estimation. We outline four key recommendations for identifying, constraining, and accounting for β value variability to improve TPCSIA estimation accuracy and precision moving forward. We must ultimately expand libraries of primary producer AA δ15N values to better understand mechanistic drivers of β value variation

Meta‐analysis of primary producer amino acid δ15N values and their influence on trophic position estimation

Abstract Compound‐specific stable isotope analysis of individual amino acids (CSIA‐AA) has emerged as a transformative approach to estimate consumer trophic positions (TPCSIA) that are internally indexed to primary producer nitrogen isotope baselines. Central to accurate TPCSIA estimation is an understanding of beta (β) values—the differences between trophic and source AA δ15N values in the primary producers at the base of a consumers’ food web. Growing evidence suggests higher taxonomic and tissue‐specific β value variability than typically appreciated. This meta‐analysis fulfils a pressing need to comprehensively evaluate relevant sources of β value variability and its contribution to TPCSIA uncertainty. We first synthesized all published primary producer AA δ15N data to investigate ecologically relevant sources of variability (e.g. taxonomy, tissue type, habitat type, mode of photosynthesis). We then reviewed the biogeochemical mechanisms underpinning AA δ15N and β value variability. Lastly, we evaluated the sensitivity of TPCSIA estimates to uncertainty in mean βGlx‐Phe values and Glx‐Phe trophic discrimination factors (TDFGlx‐Phe). We show that variation in βGlx‐Phe values is two times greater than previously considered, with degree of vascularization, not habitat type (terrestrial vs. aquatic), providing the greatest source of variability (vascular autotroph = −6.6 ± 3.4‰; non‐vascular autotroph = +3.3 ± 1.8‰). Within vascular plants, tissue type secondarily contributed to βGlx‐Phe value variability, but we found no clear distinction among C3, C4 and CAM plant βGlx‐Phe values. Notably, we found that vascular plant βGlx‐Lys values (+2.5 ± 1.6‰) are considerably less variable than βGlx‐Phe values, making Lys a useful AA tracer of primary production sources in terrestrial systems. Our multi‐trophic level sensitivity analyses demonstrate that TPCSIA estimates are highly sensitive to changes in both βGlx‐Phe and TDFGlx‐Phe values but that the relative influence of β values dissipates at higher trophic levels. Our results highlight that primary producer β values are integral to accurate trophic position estimation. We outline four key recommendations for identifying, constraining and accounting for β value variability to improve TPCSIA estimation accuracy and precision moving forward. We must ultimately expand libraries of primary producer AA δ15N values to better understand the mechanistic drivers of β value variation

A Guide to Using Compound-Specific Stable Isotope Analysis to Study the Fates of Molecules in Organisms and Ecosystems

The measurement of stable isotopes in ‘bulk’ animal and plant tissues (e.g., muscle or leaf) has become an important tool for studies of functional diversity from organismal to continental scales. In consumers, isotope values reflect their diet, trophic position, physiological state, and geographic location. However, interpretation of bulk tissue isotope values can be confounded by variation in primary producer baseline values and by overlapping values among potential food items. To resolve these issues, biologists increasingly use compound-specific isotope analysis (CSIA), in which the isotope values of monomers that constitute a macromolecule (e.g., amino acids in protein) are measured. In this review, we provide the theoretical underpinnings for CSIA, summarize its methodology and recent applications, and identify future research directions. The key principle is that some monomers are reliably routed directly from the diet into animal tissue, whereas others are biochemically transformed during assimilation. As a result, CSIA of consumer tissue simultaneously provides information about an animal’s nutrient sources (e.g., food items or contributions from gut microbes) and its physiology (e.g., nitrogen excretion mode). In combination, these data clarify many of the confounding issues in bulk analysis and enable novel precision for tracing nutrient and energy flow within and among organisms and ecosystems