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. 2020 Jun 24;287(1929):20200732.
doi: 10.1098/rspb.2020.0732. Epub 2020 Jun 17.

Herbaria macroalgae as a proxy for historical upwelling trends in Central California

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Herbaria macroalgae as a proxy for historical upwelling trends in Central California

Emily A Miller et al. Proc Biol Sci. .

Abstract

Planning for future ocean conditions requires historical data to establish more informed ecological baselines. To date, this process has been largely limited to instrument records and observations that begin around 1950. Here, we show how marine macroalgae specimens from herbaria repositories may document long-term ecosystem processes and extend historical information records into the nineteenth century. We tested the effect of drying and pressing six macroalgae species on amino acid, heavy metal and bulk stable isotope values over 1 year using modern and archived paper. We found historical paper composition did not consistently affect values. Certain species, however, had higher variability in particular metrics while others were more consistent. Multiple herbaria provided Gelidium (Rhodophyta) samples collected in southern Monterey Bay from 1878 to 2018. We examined environmental relationships and found δ15N correlated with the Bakun upwelling index, the productivity regime of this ecosystem, from 1946 to 2018. Then, we hindcasted the Bakun index using its derived relationship with Gelidium δ15N from 1878 to 1945. This hindcast provided new information, observing an upwelling decrease mid-century leading up to the well-known sardine fishery crash. Our case study suggests marine macroalgae from herbaria are an underused resource of the marine environment that precedes modern scientific data streams.

Keywords: herbaria; historical ecology; ocean memory; seaweed; stable isotopes; upwelling.

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Conflict of interest statement

We declare we have no competing interests.

Figures

Figure 1.
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.
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.
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.
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.)

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