| Literature DB >> 32546101 |
Emily A Miller1, Susan E Lisin1, Celia M Smith2, Kyle S Van Houtan1,3.
Abstract
Planning for future ocean conditions requires historical data to establish more informed ecological baselines. To date, this process hEntities:
Keywords: herbaria; historical ecology; ocean memory; seaweed; stable isotopes; upwelling
Mesh:
Year: 2020 PMID: 32546101 PMCID: PMC7329038 DOI: 10.1098/rspb.2020.0732
Source DB: PubMed Journal: Proc Biol Sci ISSN: 0962-8452 Impact factor: 5.349
Figure 1.The composition of marine macroalgae changed over the 1 year curing process for several components but many exhibited little change. Per cent change over the 1 year period is shown by archived and modern paper for (a) amino acids, (b) heavy metals and (c) total protein. Amino acid units are in per cent by weight, heavy metals in ppm and total protein in per cent by weight. Values were rescaled by species. Amino acid abbreviations: serine (S), threonine (T), phenylalanine (F), isoleucine (I), leucine (L), valine (V), histidine (H), arginine (R), glycine (G), methionine (M), aspartic acid or asparagine (B), proline (P), glutamic acid or glutamine (Z), tyrosine (Y), alanine (A), lysine (K). Heavy metal is noted by standard elemental abbreviations. (Online version in colour.)
Figure 2.Stable isotope signatures of dried marine macroalgae changed the least in red algae species, followed by green algae and the most in brown algae after 1 year of curing. Loess curves were fit to stable isotopic signatures ((a) δ13C, (b) δ15N and (c) δ18O) for combined archived and modern paper types by algae taxonomic group. Green algae species included: Cl. columbiana, U. californica; red algae species included: Cr. ruprechtiana, G. purpurascens, brown algae species included: M. pyrifera, S. compressa. Loess curves with a span of 0.5 are shown for each taxonomic group across both paper types. Sampling occurred three days after collection, one month, two months, four months, six months and 1 year.
Figure 3.Isotopic signatures of historical archived specimens varied and changed throughout the 140 year time series. Signatures of (a) δ13C, (b) δ15N, and (c) δ18O were corrected for differences owing to seasonality by a rescaling ratio informed by the data. Data points each represent one Gelidium sp. specimen and smoothed loess curves are shown with loess confidence intervals. (Online version in colour.)
Figure 4.δ15N values of Gelidium spp. can hindcast historical upwelling trends prior to index estimates. (a) Loess models (spans = 0.1–1, interval = 0.01) were fitted to both time series of three-degree monthly Bakun upwelling index and seasonally corrected δ15N of herbarium Gelidium spp., 1946–2018. Linear regressions were fitted to these modelled δ15N values as a function of the modelled upwelling index values. Linear regressions for all model spans are shown here. (b) Image of Gelidium collected from Cabrillo Point, Pacific Grove, CA in 2017. (c) Monthly Bakun upwelling index values are shown in six-year binned boxplots, from 1946–2018, with loess model. Hindcast upwelling index values (open circles) were derived from δ15N values from historical herbaria Gelidium spp., 1878–1945, using the optimal linear regression relationship obtained from (a). A loess model is fitted to the hindcast data. (Online version in colour.)