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1. Quantifying the  d15N trophic offset in a cold-water scleractinian coral (CWC): implications for the CWC diet and coral  15N as a marine N cycle proxy

   Mottram, J; Gothmann, A; Prokopenko, M; Cordova, A; Rollinson, V; Dobkowski, K; Granger, J (March 2024, Biogeosciences)

   The nitrogen (N) isotope composition (δ15N) of cold-water corals is a promising proxy for reconstructing past ocean N cycling, as a strong correlation was found between the δ15N of the organic nitrogen preserved in coral skeletons and the δ15N of particulate organic matter exported from the surface ocean. However, a large offset of 8 ‰–9 ‰ between the δ15N recorded by the coral and that of exported particulate organic matter remains unexplained. The 8 ‰–9 ‰ offset may signal a higher trophic level of coral dietary sources, an unusually large trophic isotope effect or a biosynthetic δ15N offset between the coral's soft tissue and skeletal organic matter, or some combinations of these factors. To understand the origin of the offset and further validate the proxy, we investigated the trophic ecology of the asymbiotic scleractinian cold-water coral Balanophyllia elegans, both in a laboratory setting and in its natural habitat. A long-term incubation experiment of B. elegans fed on an isotopically controlled diet yielded a canonical trophic isotope effect of 3.0 ± 0.1 ‰ between coral soft tissue and the Artemia prey. The trophic isotope effect was not detectably influenced by sustained food limitation. A long N turnover of coral soft tissue, expressed as an e-folding time, of 291 ± 15 d in the well-fed incubations indicates that coral skeleton δ15N is not likely to track subannual (e.g., seasonal) variability in diet δ15N. Specimens of B. elegans from the subtidal zone near San Juan Channel (WA, USA) revealed a modest difference of 1.2 ± 0.6 ‰ between soft tissue and skeletal δ15N. The δ15N of the coral soft tissue was 12.0 ± 0.6 ‰, which was ∼6 ‰ higher than that of suspended organic material that was comprised dominantly of phytoplankton – suggesting that phytoplankton is not the primary component of B. elegans' diet. An analysis of size-fractionated net tow material suggests that B. elegans fed predominantly on a size class of zooplankton ≥500 µm, implicating a two-level trophic transfer between phytoplankton material and coral tissue. These results point to a feeding strategy that may result in an influence of the regional food web structure on the cold-water coral δ15N. This factor should be taken into consideration when applying the proxy to paleo-oceanographic studies of ocean N cycling. 

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2. Meta‐analysis of primary producer amino acid δ ¹⁵ N values and their influence on trophic position estimation

   https://doi.org/10.1111/2041-210X.13678  

   Ramirez, Matthew_D; Besser, Alexi_C; Newsome, Seth_D; McMahon, Kelton_W (August 2021, Methods in Ecology and Evolution)

   Abstract Compound‐specific stable isotope analysis of individual amino acids (CSIA‐AA) has emerged as a transformative approach to estimate consumer trophic positions (TP_CSIA) that are internally indexed to primary producer nitrogen isotope baselines. Central to accurate TP_CSIAestimation 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‐specificβvalue variability than typically appreciated.This meta‐analysis fulfils a pressing need to comprehensively evaluate relevant sources ofβvalue variability and its contribution to TP_CSIAuncertainty. 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 andβvalue variability. Lastly, we evaluated the sensitivity of TP_CSIAestimates to uncertainty in meanβ_Glx‐Phevalues and Glx‐Phe trophic discrimination factors (TDF_Glx‐Phe).We show that variation inβ_Glx‐Phevalues 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 toβ_Glx‐Phevalue variability, but we found no clear distinction among C₃, C₄and CAM plantβ_Glx‐Phevalues. Notably, we found that vascular plantβ_Glx‐Lysvalues (+2.5 ± 1.6‰) are considerably less variable thanβ_Glx‐Phevalues, making Lys a useful AA tracer of primary production sources in terrestrial systems. Our multi‐trophic level sensitivity analyses demonstrate that TP_CSIAestimates are highly sensitive to changes in bothβ_Glx‐Pheand TDF_Glx‐Phevalues but that the relative influence ofβvalues dissipates at higher trophic levels.Our results highlight that primary producerβvalues are integral to accurate trophic position estimation. We outline four key recommendations for identifying, constraining and accounting forβvalue variability to improve TP_CSIAestimation accuracy and precision moving forward. We must ultimately expand libraries of primary producer AA δ¹⁵N values to better understand the mechanistic drivers ofβvalue variation. 

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3. High‐precision measurement of phenylalanine and glutamic acid δ ¹⁵ N by coupling ion‐exchange chromatography and purge‐and‐trap continuous‐flow isotope ratio mass spectrometry

   https://doi.org/10.1002/rcm.9085  

   Zhang, Lin; Lee, Wing‐man_Charlotte; Kreider‐Mueller, Ava; Kuhnel, Evelyn; Baca, Jesus; Ji, Chongxiao; Altabet, Mark (May 2021, Rapid Communications in Mass Spectrometry)

   RationaleNitrogen isotopic compositions (δ¹⁵N) of source and trophic amino acids (AAs) are crucial tracers of N sources and trophic enrichments in diverse fields, including archeology, astrobiochemistry, ecology, oceanography, and paleo‐sciences. The current analytical technique using gas chromatography‐combustion‐isotope ratio mass spectrometry (GC/C/IRMS) requires derivatization, which is not compatible with some key AAs. Another approach using high‐performance liquid chromatography‐elemental analyzer‐IRMS (HPLC/EA/IRMS) may experience coelution issues with other compounds in certain types of samples, and the highly sensitive nano‐EA/IRMS instrumentations are not widely available. MethodsWe present a method for high‐precision δ¹⁵N measurements of AAs (δ¹⁵N‐AA) optimized for canonical source AA‐phenylalanine (Phe) and trophic AA‐glutamic acid (Glu). This offline approach entails purification and separation via high‐pressure ion‐exchange chromatography (IC) with automated fraction collection, the sequential chemical conversion of AA to nitrite and then to nitrous oxide (N₂O), and the final determination of δ¹⁵N of the produced N₂O via purge‐and‐trap continuous‐flow isotope ratio mass spectrometry (PT/CF/IRMS). ResultsThe cross‐plots of δ¹⁵N of Glu and Phe standards (four different natural‐abundance levels) generated by this method and their accepted values have a linear regression slope of 1 and small intercepts demonstrating high accuracy. The precisions were 0.36‰–0.67‰ for Phe standards and 0.27‰–0.35‰ for Glu standards. Our method and the GC/C/IRMS approach produced equivalent δ¹⁵N values for two lab standards (McCarthy Lab AA mixture and cyanobacteria) within error. We further tested our method on a wide range of natural sample matrices and obtained reasonable results. ConclusionsOur method provides a reliable alternative to the current methods for δ¹⁵N‐AA measurement as IC or HPLC‐based techniques that can collect underivatized AAs are widely available. Our chemical approach that converts AA to N₂O can be easily implemented in laboratories currently analyzing δ¹⁵N of N₂O using PT/CF/IRMS. This method will help promote the use of δ¹⁵N‐AA in important studies of N cycling and trophic ecology in a wide range of research areas. 

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4. Omnivorous summer feeding by juvenile Antarctic krill in coastal waters

   https://doi.org/10.1002/lno.12533  

   Conroy, John A; Steinberg, Deborah K; Nardelli, Schuyler C; Schofield, Oscar (April 2024, Limnology and Oceanography)

   Abstract The Antarctic krillEuphausia superbais often considered an herbivore but is notable for its trophic flexibility, which includes feeding on protistan and metazoan zooplankton. Characterizing krill trophic position (TP) is important for understanding carbon and energy flow from phytoplankton to vertebrate predators and to the deep ocean, especially as plankton composition is sensitive to changing climate. We used repeated field sampling and experiments to study feeding by juvenile krill during three austral summers in waters near Palmer Station, Antarctica. Our approach was to combine seasonal carbon budgets, gut fluorescence measurements, imaging flow cytometry, and compound‐specific isotope analysis of amino acids. Field measurements coupled to experimentally derived grazing functional response curves suggest that phytoplankton grazing alone was insufficient to support the growth and basal metabolism of juvenile krill. Phytoplankton consumption by juvenile krill was limited due to inefficient feeding on nanoplankton (2–20 μm), which constituted the majority of autotrophic prey. Mean krill TP and the metazoan dietary fraction increased in years with higher mesozooplankton biomass, which was not coupled to phytoplankton biomass. Comparing TP estimates using δ¹⁵N of different amino acids indicated a substantial and consistent food‐web contribution from heterotrophic protists. Phytoplankton, metazoans, and heterotrophic protists all were important contributors to a diverse krill diet that changed substantially among years. Juvenile krill fed mostly on heterotrophic prey during summer near Palmer Station, and this food web complexity should be considered more broadly throughout the changing Southern Ocean. 

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5. The CoralHydro2k database: a global, actively curated compilation of coral δ ¹⁸ O and Sr ∕ Ca proxy records of tropical ocean hydrology and temperature for the Common Era

   https://doi.org/10.5194/essd-15-2081-2023  

   Walter, Rachel M.; Sayani, Hussein R.; Felis, Thomas; Cobb, Kim M.; Abram, Nerilie J.; Arzey, Ariella K.; Atwood, Alyssa R.; Brenner, Logan D.; Dassié, Émilie P.; DeLong, Kristine L.; et al (January 2023, Earth System Science Data)

   Abstract. The response of the hydrological cycle to anthropogenic climatechange, especially across the tropical oceans, remains poorly understood due to the scarcity of long instrumental temperature and hydrological records. Massive shallow-water corals are ideally suited to reconstructing past oceanic variability as they are widely distributed across the tropics,rapidly deposit calcium carbonate skeletons that continuously record ambient environmental conditions, and can be sampled at monthly to annualresolution. Climate reconstructions based on corals primarily use the stable oxygen isotope composition (δ18O), which acts as a proxy for sea surface temperature (SST), and the oxygen isotope composition ofseawater (δ18Osw), a measure of hydrological variability. Increasingly, coral δ18O time series are paired with time series of strontium-to-calcium ratios (Sr/Ca), a proxy for SST, from the same coral to quantify temperature and δ18Osw variabilitythrough time. To increase the utility of such reconstructions, we presentthe CoralHydro2k database, a compilation of published, peer-reviewed coral Sr/Ca and δ18O records from the Common Era (CE). The database contains 54 paired Sr/Ca–δ18O records and 125 unpaired Sr/Ca or δ18O records, with 88 % of these records providing data coverage from 1800 CE to the present. A quality-controlled set of metadata with standardized vocabulary and units accompanies each record, informing the useof the database. The CoralHydro2k database tracks large-scale temperatureand hydrological variability. As such, it is well-suited for investigationsof past climate variability, comparisons with climate model simulationsincluding isotope-enabled models, and application in paleodata-assimilation projects. The CoralHydro2k database is available in Linked Paleo Data (LiPD) format with serializations in MATLAB, R, and Python and can be downloaded from the NOAA National Center for Environmental Information's Paleoclimate Data Archive at https://doi.org/10.25921/yp94-v135 (Walter et al., 2022). 

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