Introduction
All organisms require trace amounts of metals to function and produce
new biomass. However, elevated metal concentrations quickly becomes
toxic (Lemire et al., 2013; Waldron & Robinson, 2009), with structural
effects on polluted ecosystems (Blanck, 2002; Blanck & Dahl, 1996;
Pesce et al., 2010; Schmitt et al., 2005). Field studies on plant
communities growing on polluted mine tailings have shown that dominant
species rely primarily on migration of tolerant individuals from
adjacent populations, rather than de-novo mutations (Macnair,
1987). More recently, the critical role of standing genetic variability
in evolution of metal tolerance has been shown also for invertebrates
(Janssens et al., 2009), yeast (Grangeteau et al., 2017), mycorrhizal
fungi (Bazzicalupo et al., 2020), and bacteria (Carlson et al., 2019).
With their rapid generation turn over and huge population sizes,
phytoplankton might evolve metal tolerance from either standing genetic
variation or new mutations. Metal tolerant species of phytoplankton have
been reported to dominate polluted aquatic environments (Foster, 1982;
Kalinowska & Pawlik-Skowrońska, 2008) but, it is not know to what
extent these tolerant species relies on adaptation through selection
from standing genetic variation, or novel mutations (Xu et al., 2018;
Zhao et al., 2017).
It has been argued that selection from standing genetic variation could
enable phytoplankton populations to rapidly adapt to changing
environmental conditions (Godhe & Rynearson, 2017; Rengefors et al.,
2017). These selection arguments are based on indirect observations such
as large population sizes (Sassenhagen et al., 2021), high dispersal
rates (Hutchinson, 1961), and high genetic diversity in phytoplankton
(Flowers et al., 2015; Kashtan et al., 2014; Osuna-Cruz et al., 2020).
However, empirical evidence of phytoplankton phenotypic variability and
capacity of adaptation is limited, with knowledge limited to a few key
climate change traits and model species (Lohbeck et al., 2012; Schaum et
al., 2017; Schaum et al., 2018; Wolf et al., 2019). The evolutionary
potential of phytoplankton has mostly been assayed through artificial
evolution experiments using a low-diverse genetic background. In such
artificial evolution experiments, a single strain or, in some cases, a
mixture of a few strains – often a random assembly of strains from
different culture collections and geographical origins – is subjected
to strong directional selection pressure, and the change in growth rate
is recorded as a proxy for evolutionary potential (Collins & Bell,
2004; Lohbeck et al., 2012; Reusch & Boyd, 2013; Schaum et al., 2018).
Such experiments reveal how unexposed populations may respond to novel
selection pressures, like metal stress, through de-novo mutations
and they can also explore how plastic responses contribute to phenotypic
changes over time (Schaum & Collins, 2014; Xu et al., 2018). However,
they contain insufficient diversity to account for selection from the
standing genetic diversity already present in natural populations
composed of thousands of unique clones (Sassenhagen et al., 2021).
We have identified the local populations of the diatom Skeletonema
marinoi Sarno & Zingone, in and around the Baltic Sea, as a
system to study intraspecific diversity and adaptation in phytoplankton.
The genetic structure of S. marinoi in the Baltic Sea is
primarily linked to the strong salinity gradient (Godhe et al., 2016;
Pinseel et al., 2022; Sjöqvist et al., 2015). However, like many other
coastal phytoplankton (McQuoid et al., 2002; Montresor et al., 2013),S. marinoi produces benthic resting stages that can anchor it to
geographical locations (Sundqvist et al., 2018). Consequently,
population structure can develop over distances as short as a few
kilometers (Härnström et al., 2011; Sefbom et al., 2018), although the
drivers of such differentiations have not been identified. The Baltic
Sea also has an extensive and well-documented history of human pollution
(HELCOM, 2010; Lehtonen et al., 2017; Reusch et al., 2018), which could
be one driving force of local adaptation, as has been shown forDaphnia populations (Kerfoot et al., 1999). At a small (ca. 5
km2) copper mining polluted inlet in the Baltic Sea,
we have previously observed that strains of S. marinoi appear
overly tolerant to several metals present in the mining ore (Andersson
et al., 2020) and that toxic metal stress can affect interspecific
competition between diatoms (Andersson et al., 2022). The mine is
located on the shoreline and was active from the 17thuntil the early 20th century (Söderhielm & Sundblad,
1996). The sediment in the inlet is polluted with several metals whose
concentrations across depth layers correlate negatively with the
abundance of S. marinoi micro-fossils (Ning et al., 2018),
suggesting that metal pollution has had an adverse effect on this
species.
The present study aimed to test if copper tolerance has evolved in the
mining-exposed S. marinoi population and to what extent
intraspecific trait variation enables the population to adapt rapidly to
a toxic environment. Our primary hypotheses were that centuries of
mining exposure have caused copper tolerant strains to evolve and that
during renewed exposure to toxic stress, the copper-exposed population
has an evolutionary advantage over an unexposed reference population. To
test these hypotheses, we isolated a large number S. marinoistrains from the mining-exposed inlet (30 strains) and an unexposed
reference inlet (28 strains) and quantified their copper tolerance in
mono-clonal experiments. We then assembled the populations back together
and performed a 42-day long artificial evolution experiment (Fig. S1)
where we tracked the strain selection process using amplicon sequencing
of a recently developed nuclear locus with exceptional intraspecific
diversity (Pinder et al., 2023). This metabarcoding approach allowed us
to observe the selection process with unprecedented resolution, and to
quantify how selection from intraspecific diversity allow phytoplankton
populations to adapt to adverse environmental conditions.