The importance of kelp to an intertidal ecosystem varies by trophic level: insights from amino acid δ¹³C analysis

Abstract

A fundamental question in ecology is understanding how energy and nutrients move through and between food webs, and which sources of production support consumers. In marine ecosystems, these basic questions have been challenging to answer given the limitation of observational methods. Stable isotope analysis of essential amino acids (EAA δ13C) has great potential as a tool to quantify energy and nutrient flow through marine food webs; however, it has been primarily utilized at large spatial scales. Here, we used EAA δ13C analysis to test for connectivity between adjacent subtidal and intertidal components of a nearshore ecosystem in south central Alaska. We measured δ13C of six EAA from four marine producer groups: subtidal kelp (Laminaria sp.), offshore particulate organic matter (POM), and intertidal red (Neorhodomela sp.) and green (Ulva sp.) algae. In addition, we sampled four intertidal invertebrate consumer species spanning a range of trophic/functional groups: Mytilus sp., Strongylocentrotus droebachiensis, Nucella sp., and Pycnopodia helianthoides. Using canonical analysis of principal coordinates (CAP) and isotope mixing models (MixSIAR), we tested for differences among producer EAA δ13C fingerprints and quantified the contribution of producer EAA to consumers. We compared these results to previously published EAA δ13C data on marine producers to examine the generality of this technique. We found the EAA δ13C fingerprints of subtidal kelps (Laminaria), Ulva, and Neorhodomela were highly distinct from one another. Further, our measured EAA δ13C patterns for kelp and red algae matched those previously reported from other localities, suggesting unique and universal EAA δ13C signatures for these groups. However, CAP could not distinguish between microalgae (POM) and Ulva, possibly due to similar biochemical pathways for the synthesis of EAA. Using these producer fingerprints, we found upper trophic‐level invertebrate consumers, Nucella and Pycnopodia, derived more than 60% of their essential amino acids from subtidal kelps. In contrast, the sampled primary consumers in the system, Mytilus and Strongylocentrotus, relied more heavily on Ulva and/or offshore POM. Our results provide evidence for connectivity between two adjacent nearshore ecosystems and exemplify EAA δ13C as a powerful new tool in tracing energy and nutrient flow within and among marine food webs.

Trophic plasticity in a common reef‐building coral: Insights from δ13C analysis of essential amino acids

“…Notably, patterns of AA ESS δ 13 C values from 19 colonies of P. meandrina separated cleanly (98% of variation explained) along a one‐dimensional continuum of autotrophic and heterotrophic nutrition, allowing for quantitative estimates of the proportion of heterotrophic carbon incorporated by individual corals (Figures a and a). Our results support previous observations that multivariate AA ESS δ 13 C fingerprints provided more robust separation among groups than δ 13 C values of individual AA ESS (Figures a,b and ) and support the quantitative power of developing source‐specific fingerprints with LDA based on multiple AA ESS (Arthur, Kelez, Larsen, Choy, & Popp, ; Elliott Smith et al, ; Larsen et al, , , ; Liew et al, ; McMahon et al, ). The definitive separation of source groups revealed by our analysis does not strongly support a missing or unquantified source of AA ESS in our model of coral nutrition for P. meandrina on Palmyra.…”

“…Lipid synthesis and catabolism are critical components of coral physiology that cannot be assessed with this technique (Baumann et al, ; Grottoli & Rodrigues, ) and future work that combines fatty acid δ 13 C and δ 13 C AA ESS analysis will likely develop a more holistic understanding of coral nutrition. Nevertheless, AAs are major conduits of carbon flow through food webs that provide reliable estimates of source contributions to consumer diets across multiple biomes (Elliott Smith et al, ; Larsen et al, ; Liew et al, ; McMahon et al, ) and our results suggest this holds true within mixotrophic corals.…”

“…Perhaps most importantly, taxa that can synthesize AA ESS de novo can use different biochemical pathways to do so, resulting in unique patterns among AA ESS δ 13 C values, or ‘fingerprints’ sensu Larsen, Taylor, Leigh, and O'Brien () that are characteristic of each taxon (e.g. bacteria, fungi, microalgae or macroalgae; Elliott Smith, Harrod, & Newsome, ; Larsen et al, ; McMahon et al, ). Because AA ESS δ 13 C fingerprints are typically multivariate representations of at least six different AA ESS , they can accurately track sources of AA ESS contribution to animal diets even when there is substantial overlap in δ 13 C values of bulk tissue or individual AA ESS among sources (Larsen et al, ).…”

“…The current evidence shows that AA ESS putatively synthesized by the coral host and/or coral‐associated microbial communities are produced in low quantities relative to those contributed by the endosymbionts or obtained through heterotrophy (Fitzgerald & Szmant, ), suggesting that de novo synthesis is likely not the primary source of AA ESS used by corals to maintain protein homeostasis. The fidelity of AA ESS δ 13 C fingerprints within producer groups is directly linked to taxon‐specific biochemical pathways of amino acid synthesis (Elliott Smith et al, ; Larsen et al, ), which suggests that the δ 13 C fingerprint of AA ESS synthesized by corals de novo would likely be distinct from those of their primary autotrophic or heterotrophic food sources. Corals thus represent a model system to explore the power of AA ESS isotope analysis to disentangle auto‐ versus heterotrophic nutrition in mixotrophs and to examine the possibility of de novo AA ESS synthesis in corals and other taxa.…”

Stable Isotope Studies of North American Arctic Populations: A Review

“…Essential amino acids are transferred intact from dietary protein to human tissues, allowing the δ 13 C and δ 15 N values of these amino acids to be used as tracers as negligible isotopic fractionation occurs during transfer (Fogel & Tuross, 2003;McClelland & Montoya, 2002;Popp et al, 2007). The δ 13 C values of essential amino acids, when combined in statistical models, can identify the 'isotope fingerprints' associated with different sources of primary production allowing the relative contributions of multiple foodwebs to a consumer isotope value to be characterized (Elliott Smith, Harrod, & Newsome, 2018;Larsen et al, 2009;Larsen et al, 2013;Wang et al, 2018). This method has potential for improving our understanding of arctic diets, particularly when the contributions of prey species are difficult to distinguish using bulk collagen δ 13 C and δ 15 N values alone.…”