Biotic turnover rates during the Pleistocene-Holocene transition
Normunds Stivrins a, *
, Janne Soininen a
, Leeli Amon b
, Sonia L. Fontana c
,
Grazyna Gryguc d
, Maija Heikkil€a e
, Oliver Heiri f
, Dalia Kisielien_e d
, Triin Reitalu b
,
Migl_e Stancikait_e d
, Siim Veski b
, Heikki Sepp€a a
a
Department of Geosciences and Geography, University of Helsinki, P.O. Box 64, Helsinki, FI-00014, Finland
b
Institute of Geology at Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia
c
Department of Palynology and Climate Dynamics, Albrecht-von-Haller-Institute for Plant Sciences, University of G€ottingen, Karspüle 2, 37073, G€ottingen,
Germany
d
Nature Research Centre, Institute of Geology and Geography, Akademijos 2, LT-08412, Vilnius, Lithuania
e
Department of Environmental Sciences, ECRU, University of Helsinki, P.O. Box 65, Helsinki, FI-00014, Finland
f
Institute of Plant Sciences and Oeschger Centre for Climate Change Research, University of Bern, Altenbergrain 21, CH-3013, Bern, Switzerland
a r t i c l e i n f o
Article history:
Received 17 June 2016
Received in revised form
1 September 2016
Accepted 6 September 2016
Keywords:
Temperature change
Biotic turnover rates
Regional extinctions
Pollen
Plant macrofossils
Phytoplankton
a b s t r a c t
The Northern Hemisphere is currently warming at the rate which is unprecedented during the Holocene.
Quantitative palaeoclimatic records show that the most recent time in the geological history with
comparable warming rates was during the Pleistocene-Holocene transition (PHT) about 14,000 to 11,000
years ago. To better understand the biotic response to rapid temperature change, we explore the community
turnover rates during the PHT by focusing on the Baltic region in the southeastern sector of the
Scandinavian Ice Sheet, where an exceptionally dense network on microfossil and macrofossil data that
reflect the biotic community history are available. We further use a composite chironomid-based summer
temperature reconstruction compiled specifically for our study region to calculate the rate of
temperature change during the PHT. The fastest biotic turnover in the terrestrial and aquatic communities
occurred during the Younger Dryas-Holocene shift at 11,700 years ago. This general shift in species
composition was accompanied by regional extinctions, including disappearance of mammoth (Mammuthus
primigenius) and reindeer (Rangifer tarandus) and many arctic-alpine plant taxa, such as Dryas
octopetala, Salix polaris and Saxifraga aizoides, from the region. This rapid biotic turnover rate occurred
when the rate of warming was 0.17 
C/decade, thus slightly lower than the current Northern Hemisphere
warming of 0.2 
C/decade. We therefore conclude that the Younger Dryas-Holocene shift with its rapid
turnover rates and associated regional extinctions represents an important palaeoanalogue to the current
high latitude warming and gives insights about the probable future turnover rates and patterns of the
terrestrial and aquatic ecosystem change.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
The Northern Hemisphere has warmed rapidly over the last
century, with a mean warming trend of 0.2 C per decade during
the last 40 years (Smith et al., 2015). Comprehensive meta-analyses
of changes in plant, mammal, bird, fish, and invertebrate communities
show that this warming is causing a massive reorganization
of terrestrial and aquatic biota with rapidly changing species
abundance, immigration, speciation, and extinctions resulting in
emergence of communities with novel species compositions
(Dawson et al., 2011; Dornelas et al., 2014). Associated with the
ongoing state-shift has been an increasing interest in ecology to
investigate and measure the species turnover rates. Biotic community
turnover, a central concept in ecology since the seminal
work by Whittaker (1960), reflects the changes in species abundance
and composition over a spatial or temporal gradient. It thus
corresponds with the beta diversity in Whittaker (1977) and many
studies have focused on analyzing the spatial turnover rates, or beta
* Corresponding author.
E-mail addresses: normunds.stivrins@helsinki.fi (N. Stivrins), janne.soininen@
helsinki.fi (J. Soininen), leeli.amon@ttu.ee (L. Amon), sonia.fontana@biologie.unigoettingen.de
(S.L. Fontana), grazyna.gryguc@geo.lt (G. Gryguc), maija.heikkila@
helsinki.fi (M. Heikkil€a), oliver.heiri@ips.unibe.ch (O. Heiri), kisieliene@geo.lt
(D. Kisielien_e), triin.reitalu@ttu.ee (T. Reitalu), stancikaite@geo.lt (M. Stancikait_e),
siim.veski@ttu.ee (S. Veski), heikki.seppa@helsinki.fi (H. Sepp€a).
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journal homepage: www.elsevier.com/locate/quascirev
http://dx.doi.org/10.1016/j.quascirev.2016.09.008
0277-3791/© 2016 Elsevier Ltd. All rights reserved.
Quaternary Science Reviews 151 (2016) 100e110
diversity, of species assemblages (Arita and Rodríguez, 2002;
Gotelli et al., 2009; Koleff et al., 2003; Mittelbach, 2012; Plotkin
and Muller-Landau, 2002; Rodríguez and Arita, 2004).
In addition to spatial biotic turnover, temporal trends in biotic
turnover have been empirically investigated using long-term
observation-based species time series records for terrestrial
(Aggemyr and Cousins, 2012; Evans et al., 2008; Pergl et al., 2012;
White, 2004) and aquatic communities (Korhonen et al., 2010;
Shurin et al., 2007). Such observation-based studies of temporal
biotic turnover usually span only at most a few decades and can be
insufficient to account for slow ecological processes, such as
extinction debt or migration credit, that may influence the turnover
rates over decadal or centennial timescales (Dornelas et al., 2014).
Palaeoecological records are rich sources to investigate past
changes in terrestrial plant and animal communities as well as
aquatic plant and phytoplankton communities because they make
it possible to reconstruct past biotic community changes and
turnover rates over centuries or millennia (Cooper et al., 2015;
Jackson and Sax, 2009). Furthermore, palaeoecological records are
long enough to reflect regional and global extinction events, which
in paleontological and palaeoecological context are often defined as
major turnover events. In general, the fossil data unambiguously
show that while the current global turnover may be extremely
rapid periods of fast species turnover have occurred frequently in
the history of the Earth, including periods of particularly massive
extinctions (Barnosky, 2008; Barnosky et al., 2011; Plotnick et al.,
2016). Palaeoecological studies further show that while the
drivers of the turnover events are often ambiguous to detect, biotic
turnover results from processes that ultimately trace back to
alteration of the abiotic environment causing simultaneous
response in multiple species (Blois and Hadly, 2009; Puzachenko
and Markova, 2014).
For discerning the biotic turnover and its drivers from fossil and
palaeoenvironmental data there are several requirements. Most
importantly, precisely dated fossil datasets that reflect the dynamics
of past communities and ecosystems are needed. Secondly,
to elucidate the drivers of the turnover rates, quantitative data on
climate and other environmental factors are necessary. The PleistoceneeHolocene
transition (PHT) 14,000e11,000 years ago (14e11
ka BP), during which northern Europe became ice free in tune with
the melting of the Scandinavian Ice Sheet (SIS), fulfils these criteria
better than most other geological time periods. There exist abundant
fossil records and independent quantitative palaeoclimate
data over this transition period from various biotic, physical and
chemical records. Moreover, independent palaeoclimate records,
based for example on Greenland ice core data (Steffensen et al.,
2008) and chironomid-based temperature reconstructions from
Europe (Heiri et al., 2014), show that the PHT is characterized by
rapid warming from the glacial conditions of the late Pleistocene to
the interglacial temperature level in the early Holocene, with a
general summer warming of 5e6 C over few centuries. It thus
represents the last natural abrupt warming event and provides a
critically important opportunity to use fossil data to investigate the
biotic response to high-magnitude warming.
Here, we focus on analysing the biotic turnover rates during PHT
in the Baltic region (Lithuania, Latvia, and Estonia) in Europe
(Fig. 1). This region became gradually ice free during the deglaciation
of the SIS from 15 to 13 ka BP ago and we are therefore able to
investigate the biotic patterns from the first deglacial colonization
of plants and animals to the establishment of the forest in the early
Holocene. This area is also special because of a long-lasting project
of collecting terrestrial and aquatic fossil records, which now results
in an exceptionally dense network of pollen, plant macrofossil
and fossil phytoplankton data from sediment cores (Amon, 2012;
Amon et al., 2010, 2012, 2014; Amon and Saarse, 2010; Heikkil€a
et al., 2009; Stancikait_e et al., 2004, 2008, 2009, 2015; Stivrins
et al., 2014, 2015; Veski et al., 2012). Our aim is to synthesize
these data and use them to estimate temporal biotic turnover rates
of the terrestrial and aquatic communities and to establish to what
extent the climate influenced turnover and regional extinctions of
plants and animals during the PHT. We further make use of the
recent quantitative summer (July) mean temperature reconstruction
based on fossil chironomid remains (Heiri et al., 2014). This
reconstruction covers the PHT period and is specifically constructed
from our study area. It therefore allows us to directly compare the
regional biotic turnover patterns and rates with regional summer
temperature rate of change and provides thus a reference point to
ongoing climatic warming and its biotic impacts.
2. Materials and methods
2.1. Data collection
The plant macrofossil, pollen and fossil phytoplankton data are
obtained from sediment cores sampled from eight lakes and one
bog in the Baltic region (Fig. 1, Supplementary material 1). The size
range of selected sites is 2e160 ha. High-quality data are required in
terms of consistent site selection, careful field sampling, laboratory
and analytical procedures, and taxonomic precision for the use of
fossil data for quantitative turnover and diversity analyses (Birks,
2014; Birks et al., 2016). There are tens of lake and bog study sites
Fig. 1. The study area is located in the Baltic region (Estonia, Latvia and Lithuania) that
extends from 53 to 60N and from 21 to 28E. Location of the sites included in the
study: (1) Lake Udriku; (2) Lake Prossa; (3) Lake Nakri; (4) Lake Lielais Svetin¸ u; (5)
Lake Kurjanovas; (6) Lake Kasuciai; (7) Lake Ginkunai; (8) Bog Juodonys; (9) Lake
Petrasiunai. During the last glaciation, the Baltic region was fully covered by the
Scandinavian Ice Sheet (SIS) and became ice free about 15,000e13,000 BP. In the map
the dotted lines show the SIS ice margin distribution at 14,000 and 11,000 BP (according
to Hughes et al., 2016) that corresponds to the beginning and end of our study
time frame.
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110 101
available from the region, but many of them have been analyzed
with low sample resolution or are too poorly dated to be useful in
analyzing biotic turnover rates. After screening the records, nine
sites covering the period from 14 to 11 ka BP with most reliable
chronology were selected. Descriptions of these sites have been
published previously (see Supplementary material 1). Pollen data
are available from eight of these sites, plant macrofossil data from
nine sites and fossil phytoplankton data from three sites. All cores
have been dated using few conventional but mostly AMS radiocarbon
datings. The original radiocarbon dates were recalibrated
utilizing the IntCal13 calibration dataset (Reimer et al., 2013) with a
two s (95.4%) confidence level and the age-depth models of each
sequence were developed using software Bacon 2.2 (Blaauw and
Christen, 2011) in the R environment (version 3.0.3) (R Core
Team, 2014). In addition, biostratigraphic correlation was used to
define the boundaries of major stratigraphic changes between
Bølling-Allerød-Younger Dryas and Younger Dryas-Holocene. These
levels were identified in pollen, plant macrofossil and lithological
features and the ages derived from the Greenland ice core records
were assigned to them (Lowe et al., 2008; Rasmussen et al., 2014).
Plant macrofossils are presented as concentration data. The
weakness of the plant macrofossil record is scarcity of plant remains
in the sediment cores, which results in discontinuous
occurrence of the plant taxa in the diagrams. It is likely that such
discontinuous occurrence does not reflect real changes in presence
of a given taxa in the vicinity of the study site, but is an artefact
associated with low concentration of the macrofossils (Birks, 2014).
We minimized this effect by pooling together all plant macrofossil
data into one composite plant macrofossil diagram for the Baltic
countries. To do that, a known age was set for each macrofossil
sample. The resulting composite plant macrofossil diagram includes
102 taxa. Such a composite record should come from the
same vegetation type in a rather restricted and small region. In our
case, this requirement is mostly fulfilled because the dominant
vegetation was fairly uniform over the Baltic region during the Late
Glacial (Amon, 2012; Amon et al., 2014; Stancikait_e et al., 2009,
2015; Veski et al., 2012).
The percentages of terrestrial pollen taxa for eight sites were
calculated using arboreal and non-arboreal pollen sums, excluding
pollen and spores of aquatic and wetland plants. Tree pollen that
were considered exotic, such as Alnus, Corylus, Tilia, Quercus, Ulmus,
Fraxinus and Carpinus, were excluded from the data earlier than
11.7 ka BP. Sporadic grains of these pollen types occur in the highly
inorganic sediment in the basal part of the cores and are mostly
likely washed into the lake from the unvegetated terrain during and
after the deglaciation as suggested by Reitalu et al. (2015) and Veski
et al. (2012). Occurrence of such redeposited pollen grains is a
common problem in the earliest post-glacial sediment sequences in
the glaciated regions in eastern and northern Europe.
In addition of using pollen and plant macrofossil data for
measuring biotic turnover rates, the evaluation of the regional extinctions
of the plant taxa during the PHT was carried out by analysing
all published plant macrofossil diagrams in the region. The
regional extinctions of terrestrial vascular plant species were
defined on the basis of the last occurrence of plant macrofossils of
such species which are at present absent in the Baltic region.
The animal communities of the study period can be reconstructed
using the fossil bone and dental records from the Baltic
region. Such records are too scattered and biased by preservation
factors to attempt any detailed or quantitative analysis of turnover
patterns. However, there exist tens of bone findings of reindeer
(Rangifer tarandus) (Ukkonen et al., 2006) and few bone and tooth
findings of woolly mammoth (Mammuthus primigenius) (Ukkonen
et al., 2011) in the region, presumably representing in situ findings
of these species. These two mammal species went regionally
extinct in the study region and we compare their records to explore
whether their Late Glacial occurrences show features which can be
related to plant community turnover and rapid climate changes.
To analyse the turnover rates of aquatic biota, we used fossil
phytoplankton percentage data. Phytoplankton are primary producers
in lakes and their abundance and composition is generally
determined by light conditions, temperature and nutrient concentration
of a lake (De Senerpont Domis et al., 2013). Hence fossil
phytoplankton community reflects aquatic ecosystem changes in
the past. The types of phytoplankton remains that can be preserved
in the lake sediment cores include chlorophyta (Botryococcus,
Pediastrum, Scenedesmus and Tetra€edron) and cyanobacteria (Anabaena,
Glaucospira and Gloeotrichia). Diatom valves are generally
among the most common fossil phytoplankton types in lake sediments.
However, in contrast to Lithuania where majority of the
sediment sequences contain diatoms, in Estonia and Latvia diatom
remains are rare or absent during the PHT, possibly due to high
alkalinity of the lakes (Veski et al., 2012). Due to this preservation
issue, diatom data were not included in this study.
Chironomid-based mean July temperature reconstruction (TJuly)
for the Baltic region published by Heiri et al. (2014) was used as
independent climate proxy to characterize the overall climatic
change. Reconstruction of TJuly uses a modern chironomidtemperature
calibration data set consisting of records from 274
lakes in Norway and Switzerland (Heiri et al., 2011). TJuly was
reconstructed based on fossil chironomid assemblages from two
sites Lake Nakri and Kurjanovas (Fig. 1) using weighted-averaging
partial least-squares regression and calibration procedure. As
chironomid data can be affected by site-specific factors, a stacked
TJuly curve was produced to summarize the temperature trends of
the Baltic region (Heiri et al., 2014). Dating errors in radiocarbondated
Late Glacial lake sediment records amount from several decades
to a few centuries in most cases. For the Kurjanovas and the
Nakri records the situation for individual radiocarbon dates is
similar (Amon et al., 2014; Heikkil€a et al., 2009). Based on TJuly data,
we estimated the rate of temperature change per decade without
any smoothing or interpolation of the data prior or later. This was
done by dividing the temperature difference between two successive
data points with the time difference in years and by averaging
to decades.
2.2. Data analyses
For quantifying local vegetation turnover, we used Sørensen
dissimilarity index. Along with the Jaccard index, Sørensen index is
one of the most widely used (dis)similarity indices and it is regarded
as one of the most effective presence/absence measures
(Magurran, 2004). We used Sørensen index also because it allows
us to partition total beta diversity (bSOR) into turnover and nestedness
components following Baselga (2010). Sørensen dissimilarity
index is calculated by bSOR ¼ 1e (2a/(2a þ b þ c)), where ‘a’
indicates the total number of species present in both samples, ‘b’
refers to the number of species present only in sample one and ‘c’ to
the number of species present only in sample two. The index ranges
from zero to one, where zero indicates that the communities have
identical species composition while one indicates that two communities
have no shared species and thus full turnover.
Although nine sites contain a record of plant macrofossils, only
five of them (Nakri, Lielais Svetin¸ u, Kurjanovas, Ginkunai and
Kasuciai) have continuous record that covers the whole study
period from 14 to 11 ka BP. Data from these five sites were utilised
further in the statistical analyses. For the statistical analyses, the
data were organized into 300-year bins. Defining the bins is critically
important. If the bins are too few and cover a too long time
period, important details can be lost; conversely if the bins are
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110102
many and short, they contain too few samples and the random
fluctuations in the data may be obscured (Birks, 2014). We used 300
years as our bin length as in this way we were able to include all
three subregions (Lithuania, Latvia, Estonia) at the same time into
the analyses and to ensure an even number of samples (eight) per
bin which is important for reliable Sørensen index calculation. To
unravel whether the variation in species composition between two
successive bins was due to species turnover (i.e., species replacement
between samples) or nestedness (i.e., species loss between
samples), we used beta diversity partitioning proposed by Baselga
(2010). This method partitions the total community dissimilarity
into turnover and nestedness components. Three pairwise
dissimilarity metrics were calculated: i) Sørensen dissimilarity index
(bSOR) measures the total variation in species composition between
samples accounting for both turnover and nestedness; ii)
Simpson dissimilarity index (bSIM) accounts for changes in community
composition due to species turnover only; and iii) nestedness
component (bNES), calculated as bSOR ÀbSIM, captures
community variation due to nestedness. Using presence-absence
data, the dissimilarity metrics were calculated using function
beta.pair in R package betapart (Baselga and Orme, 2012). In addition,
we calculated Sørensen index and beta diversity partitioning
separately for terrestrial and aquatic plant macrofossil data, but the
results were not statistically significant (not presented here)
probably due to low number of samples or taxa per bin, hence we
used the combined macrofossil (terrestrial and aquatic) data that
was statistically significant.
Palynological and phytoplankton turnover were estimated by
Detrended Canonical Correspondence Analysis (DCCA) with time as
the constraining variable. The reason of using DCCA instead of
Sørensen index is that the pollen records differ from the plant
macrofossil records in some fundamental ways. Unlike the plant
macrofossil data, pollen percentages provide relative abundance
data. In addition, the source area of pollen is larger, with pollen
transported by wind to the sites from tens of kilometres. Thus the
pollen records provide a general picture of the vegetation composition,
but do not reliably reflect the presence of the plant taxa
directly around the study sites. Contrary to plant macrofossil
samples which are commonly analyzed continuously throughout
the sediment sequence, pollen samples are analyzed within intervals
that may vary. Because of this, the number of the pollen
samples per time unit at each site can differ, leading to uneven
number of pollen samples per given time interval. For DCCA, we
used 500-year time intervals that ensured the adequate number of
samples within a time interval while we were still able to estimate
turnover for relatively short climatic periods. DCCA expresses
turnover results in standard deviations (SD) and the turnover can
be estimated as the difference between the highest and lowest
values for each time sequence (Birks, 2007; Birks and Birks, 2008).
A complete turnover of species, with no species in common at
either end of the gradient, would have a gradient length of 4 SD
(Hill and Gauch, 1980) or 100% of the total changes in sequence.
Prior to the analysis, we square-root transformed the datasets, and
detrended by segments with no down-weighting of rare taxa and
non-linear rescaling. The DCCA was performed individually for each
subregion and the results were combined to generate an average
palynological and phytoplankton turnover curves for the whole
study region. CANOCO 5.04 (ter Braak and Smilauer, 2012) was used
for DCCA.
3. Results
The study period begins at 14 ka BP. This dates to the BøllingAllerød
interstadial, a warm period (Fig. 2) during which a rapid
post-glacial migration of tree species and forest development in the
southern Baltic region began (Fig. 3) while the northern part
remained treeless (Amon, 2012, Amon et al., 2014; Heikkil€a et al.,
2009). The TJuly increased to ~14 C at 13.8 ka BP, and remained at
this level until a sudden cooling at 12.9e12.7 ka BP to about ~11 C.
This cooling represents the beginning of the Younger Dryas stadial,
a cold period which lasted about 1200 years and ended with rapid
warming of TJuly to above 12 C around 11.7 ka BP (Fig. 2a). This
warming corresponds with the beginning of the Holocene interglacial,
and on the basis of our data, during the first centuries of the
Holocene TJuly was still rising, and reached 15 C by 11.2 ka BP. The
change of temperature rate was highest, ~0.3 C per decade, from
12.85 to 12.5 ka BP, during the Bølling-Allerød-Younger Dryas shift
(Fig. 2b). The transition from Younger Dryas to Holocene at 11.7 ka
BP was marked by temperature change of 0.17 C per decade.
Based on DCCA results, the palynological turnover showed
generally similar trends in all subregions (Fig. 4). It decreased from
14 to 13.5 to 13e13.5 ka BP and increased at 13e12.5 ka BP, during
the Bølling-Allerød-Younger Dryas shift. The values remained low
during the Younger Dryas and reached the maximum in two subregions
(Estonia and Lithuania) at 11.5e12 ka BP, i.e. during the
Younger Dryas-Holocene shift (Fig. 4, Supplementary material 2).
Fossil phytoplankton turnover rates were roughly similar with
the palynological turnover trends, with fairly high values during
the Bølling-Allerød interstadial from 14 to 13.5 ka BP, lower values
at 13.5e12 ka BP, and a minimum during the Younger Dryas (Fig. 5).
An increase occurred during the Younger Dryas-Holocene shift at
11.7 ka BP (Supplementary material 3) and the highest turnover
rate occurred in the early Holocene at 11.3 ka BP. In the early Holocene,
the phytoplankton turnover was comparable to that during
the Bølling-Allerød interstadial. Thus the aquatic community
turnover during the Younger Dryas-Holocene shift was less marked
than the terrestrial one.
The Sørensen dissimilarity index suggests relatively stable
terrestrial plant communities (range 0.43e0.48) from 14 to 13 ka BP
(Fig. 5d). No notable increase in the terrestrial vegetation turnover
can be observed during the cooling at the Bølling-Allerød-Younger
Dryas shift at 13e12.7 ka BP. The turnover rose to a maximum of
0.55 during the Younger Dryas-Holocene shift at 12e11.5 ka BP and
decreased afterwards. Thus the highest turnover in the local
terrestrial plant communities occurred during the warming of the
Younger Dryas-Holocene shift. Beta diversity partitioning analyses
using combined data of terrestrial and aquatic taxa revealed that
turnover was the dominant beta diversity component (r ¼ 0.317;
p ¼ 0.001), whereas nestedness was negligible (r ¼ 0.121;
p ¼ 0.073) (Supplementary material 4).
4. Discussion
4.1. The use of palaeoecological data
Before interpreting the results in terms of biotic turnover rate
and its drivers, it is necessary to explore the special characteristics
of different types of fossil data in biotic turnover analyses. Critical
features of the types of fossil data used here are a) the spatial
representation of the data, b) the questions of true and false presence
and true and false absence of species, c) taxonomical resolution,
d) temporal resolution of the data, e) and whether the data
should be considered as binary or quantitative data.
Pollen data are generally stratigraphically more detailed than
plant macrofossil data. Pollen data are also quantitative, making it
possible to investigate the turnover based not only on species
presence/absence but on relative abundance. However, the difficulty
with the pollen data is that pollen grains are carried by wind
and especially in the open, non-forested environment, such as
much of the Late Glacial in the Baltic region a part of the fossil
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110 103
pollen do not represent local vegetation, but some pollen grains can
be transported by wind over tens or hundreds of kilometres. This
phenomenon is reflected in the modern pollen samples, e.g. from N
Scandinavia or Svalbard, where tree taxa such as Pinus are present
in the pollen diagrams with values up to 5e25% although these
species are not present (Birks et al., 2016; Sepp€a, 1998). In pollen
data these pollen types can be termed as “false richness” (Birks
et al., 2016), similarly as redeposited pollen grains. Consequently,
the pollen values of many wind-pollinated plant taxa, for example
Pinus, Betula, and Alnus in our diagrams may be partly or fully
arrived by long-distance transport and thus do not represent the
abundance of such taxa in our study region (Birks, 2008). In general,
pollen data from Late Glacial environment provide an approximate
picture of the structure and composition of vegetation on regional
or landscape-ecological scale, but do not provide firm evidence of
the presence of plant species in the catchment or vicinity from
where the sediment cores are collected.
To overcome the problem of false presence that would induce
misleading turnover results, we used the plant macrofossil data to
provide a more local picture of plant communities, as plant macrofossils
generally reflect the presence of plant in the catchment or
vicinity (few km) from the lakes and bogs reliably. In principle, a
plant macrofossil record provides a time series record of plant
community composition comparable with a permanent vegetation
plot monitored over certain time period and permits analysing
temporal plant community turnover around the bogs or lakes.
However, there are some important caveats also in plant macrofossil
data. First, plant macrofossil data are binary data, as they
reflect the presence of plant species but not their abundances
(Birks, 2014). In the case of plant macrofossils, the non-zero values
almost certainly reflect true presence of a plan species in the local
vegetation in contrast to fossil pollen where non-zero values may
reflect the presence of the relevant taxon locally or regionally (true
presence) or far-distance extra-regional pollen (false presence)
(Birks et al., 2016). However, zero values in macrofossil data do not
necessarily indicate true absence of species, because zero values in
macrofossil data may result either from the macrofossil of the taxon
in question not being found in the sediment sample examined
(false absence) or from the genuine absence of the taxon near the
site of deposition (true absence). False absences are common in
both macrofossil and pollen data whereas false presences are rare
in macrofossil data but can be common in pollen data (Birks, 2014;
Birks and Birks, 2014).
Associated with the false absence of macrofossils is the scarcity
of plant remains in the sediment cores, which results in the
discontinuous occurrence of the plant taxa in the diagrams. It is
very likely that such discontinuous occurrence does not reflect a
real presence-absence variation of a given taxa in the vicinity of the
study site, but is an artefact associated with low concentration of
the macrofossils. We minimized this effect by stacking all plant
macrofossil data into one composite plant macrofossil diagram to
generate a more complete and reliable record of occurrence of the
plant species in the study region (Fig. 3). While such stacked
composite diagrams are rarely used in macrofossil-based studies,
they may be the most realistic way to use macrofossil data for
calculating turnover rates and can be seen as equivalents to the
practise of analysing a number of vegetation plots from one vegetation
zone and averaging their results in modern spatial vegetation
turnover studies.
Fossil phytoplankton percentage data were included in the
study to examine the biotic turnover rate of the aquatic communities
and to compare them with terrestrial communities. As with
the terrestrial plant macrofossils and pollen, fossil phytoplankton
records from the sediment samples do not reflect the entire taxonomic
diversity. Several ways with different taxonomical resolution
exist to recover past information on phytoplankton, including fossil
representatives recovered from pollen slides (Stivrins et al., 2015;
Turner et al., 2014), through diatom analysis (Rühland et al.,
2015), by measuring algal pigments and by determining ancient
DNA (Pal et al., 2015). Nevertheless, fossil records of phytoplankton
have been successfully used to evaluate climate impact on phytoplankton
turnover rates over the last 150 years (Smol et al., 2005).
4.2. Biotic turnover during the Pleistocene-Holocene transition
Both terrestrial and aquatic biotic turnover rates indicate
July
RateofTJulychange
(a)
(c)
0.2
0.3 (b)
0.1
0.0
-0.1
-0.2
-0.3
Age, BP
Fig. 2. Climate data and the geochronological periods: (a) chironomid based July temperature reconstruction (TJuly) for Baltic region from Heiri et al. (2014); (b) rate of TJuly change
per decade (based on curve (a)); (c) the geochronological periods Bølling-Allerød, Younger Dryas and the Holocene (Lowe et al., 2008; Rasmussen et al., 2014) and age at the bottom
(BP).
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110104
periods of marked change and stability during the PHT. The periods
of lowest turnover and hence stable communities date to 13.5e13
ka BP and 12.5e12 ka BP (Fig. 5bec). The former period represents
the Bølling-Allerød interstadial when the study region was mostly
covered by pine-birch forest except for the northernmost part
where the tundra remained (Amon et al., 2014). The latter period
represents the Younger Dryas stadial, characterized by low temperature
and the predominance of the tundra or steppe-tundra
ecosystems in our study region. These two periods of community
stability correspond with periods of low rates of the temperature
change. For example, there was a period of practically no summer
temperature change from 13.5 to 13.1 ka BP and this period was
characterized by the lowest turnover rates in the pollen data in all
three subregions (Fig. 4). We therefore conclude that the BøllingAllerød
and Younger Dryas were periods of little climatic and biotic
change in the region, at least at the multidecadal to centennial time
scales captured by our sediment records.
The Younger Dryas-Holocene shift at 11.7 ka BP represents the
most abrupt turnover event in both terrestrial and aquatic communities
in our study region. It is obvious that the underlying
reason for this rapid turnover was the rapid climate warming. In the
chironomid-based TJuly reconstruction this warming begins at 11.7
ka BP and continues during the several centuries in the early Holocene.
The same fast warming can be seen in the Greenland ice
core data. Steffensen et al. (2008) argued that this warming was
triggered by an abrupt change in atmospheric circulation which
initiated a warming over about 50 years and lasted about 60 years
(Steffensen et al., 2008). In the European lake sediment records, the
same abrupt warming can be seen, for example in the highresolution
records from United Kingdom, Norway and
Switzerland (Bakke et al., 2009; Birks et al., 2012; Heiri et al., 2015).
Arctic lakes are responsive to climate change, because even
slight warming results in decreased ice cover and, hence, longer
growing seasons for algae and other organisms (Douglas and Smol,
1999; Rouse et al., 1997; Smol et al., 2005). As the summer temperatures
during the PHT in the study region were comparable to
modern arctic and boreal regions, it is not surprising that the DCCA
results show that the trends in the phytoplankton turnover rates in
general followed rates of temperature change and were hence
mostly consistent with the turnover rates of the terrestrial communities
(Fig. 5). In a comparable study of the recent community
change in the arctic lakes, Smol et al. (2005) used DCCA to analyse
compositional turnover in diatom community rates over the last
150 years and discovered that many arctic freshwater ecosystems
have experienced dramatic and unidirectional regime shifts within
the last 150 years.
An intriguing aspect is that while the Younger Dryas-Holocene
shift is characterized by rapid TJuly warming and higher turnover,
an even more pronounced temperature change is indicated during
the Bølling-AllerødeYounger Dryas shift, when there was a rapid
TJuly cooling with a rate of 0.31 C per decade (Fig. 5a). This is the
fastest rate of temperature change in our dataset, but it had relatively
muted effect on biotic turnover (Fig. 5bed). There may be a
number of reasons explaining this difference. Our July mean temperature
record differs from other high-resolution temperature
reconstructions from Europe. For example, in the high-resolution
records from Kråkenes from western Norway (Bakke et al., 2009;
Birks and Birks, 2008), from Scotland (Brooks et al., 2016) and
from the NGRIP ice core data from Greenland (Buizert et al., 2014)
the amplitude of warming at the Younger Dryas-Holocene shift is
Fig. 3. Composite Baltic plant macrofossil diagram from 14,000 to 11,000 BP with a 102
taxa from nine sites organized according their first appearance from left to right. Three
chronozones indicated: Bølling-Allerød, Younger Dryas and the Holocene.
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110 105
faster than during the cooling at the Bølling-Allerød-Younger Dryas
shift. It is thus possible that the Baltic chironomid-based temperature
record during the Younger Dryas-Holocene shift is smoother
than the real temperature change, possibly because of bioturbation
that can occur in non-varved lakes and can cause sediment mixing,
thus blurring the palaeoclimatic signal.
Another potential explanation is that other climatic variables
may have influenced the biotic responses and turnover rates.
Summer or July mean temperatures are strong predictors of distribution
and abundance for a plant or algal species that require
some minimum of consecutive frost-free days to complete their
growth and reproductive cycles (Woodward, 1987). However, TJuly
might serve as a poor predictor of range or population shifts for
other species, which are more dependent on long growing season.
Winter temperature can be another important variable, as it can
limit beginning and length of growing season (Alfano et al., 2003;
Cooper, 2014). Similarly, mean temperatures and temperature extremes
during spring or autumn may have a significant effect on
terrestrial biota and changes in these temperature variables will not
have been captured in our temperature reconstruction. Moisture
availability is another important variable for terrestrial plants, and
it is often expressed as mean annual or seasonal precipitation or as
actual or potential deficit. Birks and Birks (2014) showed that TJuly
does not explain all changes in vegetation and argued that precipitation
was an important climatic component during the Late
Glacial. No independent quantitative winter temperature or precipitation
data exist for the PHT from Europe yet, but climate
simulations suggest higher temperature changes during the
Younger Dryas-Holocene shift in winter than in summer (Buizert
et al., 2014).
4.3. Rapid turnover and regional extinctions
An important part of the biotic turnover was the regional
extinction of the arctic-alpine plant and animal species. Fig. 5
highlights the occurrence and disappearance of the plant taxa
which are considered regionally extinct in the region. These plants
comprise arctic-alpine plants, such as Saxifraga aizioides, S. cespitosa,
S. oppositifolia, S. stellaris, S. tenuis, Salix herbacea, Salix
polaris and Dryas octopetala. Macrofossils show that all these plant
species were locally present in the Baltic region during the study
period. Dryas octopetala, which is usually abundantly present in
plant macrofossil records (Birks, 2008; Godwin, 1975), is present
from 14 ka BP to the Younger Dryas-Holocene shift at 11.7 ka BP.
Given the continuous nature of the record, it is likely that its fossils
represent reliably its presence and regional extinction in the region.
Palynologicalturnover
Lithuania,SD
Palynologicalturnover
Estonia,SD
Age, BP
11000 11500 12000 12500 13000 13500 14000
Age, BP
11000 11500 12000 12500 13000 13500 14000
Palynologicalturnover
Latvia,SD
0.60
0.80
1.00
1.20
1.40
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.20
0.40
0.60
0.80
(a)
(b)
(c)
Fig. 4. Palynological turnover for Baltic from 14,000 to 11,000 BP in SD units: (a) Estonia, (b) Latvia and (c) Lithuania.
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110106
0.0
0.2
0.4
0.6
0.8
1.0
1.2
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)
(k)
(n)
Phytoplanktonturnover,
SD
RateofTJulychange
0.3 (a)
0.1
-0.1
-0.3
0.2
0.0
-0.2
Saxifraga cespitosa
Age, BP
Age, BP
(l)
(m)
Fig. 5. Biological turnover of Baltic region from 14,000 to 11,000 BP: (a) rate of TJuly change, (b) mean palynological turnover in SD units, (c) mean phytoplankton turnover in SD
units, (d) Sørensen dissimilarity index for plant macrofossil 300-year bins, and plant macrofossils (e) Saxifraga stellaris, (f) Saxifraga oppositifolia, (g) Saxifraga teius, (h) Salix herbacea,
(i) Salix polaris, (j) Saxifraga aizioides, (k) Dryas octopetala and (l) Saxifraga cespitosa. Information on mammals (m) Rangifer tarandus (reindeer) and (n) Mammuthus primigenius
(mammoth) obtained from Ukkonen et al. (2006, 2011).
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110 107
The plant macrofossils of other now extinct plant taxa are more
scattered. It is certain that the macrofossil records of these species
underestimate the presence of these taxa regionally and temporally.
For example, it is not likely that Saxifraga cespitosa would have
been present in the Baltic region only during the end of the Younger
Dryas, as indicated by the only found macrofossil of this species in
the Baltic region (Fig. 5). It is more likely that these species that are
common in modern arctic, as well as other arctic-alpine plant
species, were early colonizers of the deglaciated terrain during the
Late Glacial and may have been present throughout the BøllingAllerød
and Younger Dryas in the Baltic region. The disappearance
of these taxa seems to have happened either during the Younger
Dryas-Holocene shift or few decades after this shift at the latest.
The impact of Younger Dryas-Holocene shift on the disappearance
of the arctic-alpine plants can be seen elsewhere in northern
Europe as well. In Denmark and Scania in southernmost Sweden,
the Late Glacial presence of Dryas octopetala has been well documented
by pollen and plant macrofossils records, which indicate its
disappearance during the Younger Dryas-Holocene shift (e.g.
Bennike et al., 2004; Fischer Mortensen et al., 2011; LiedbergJ€onsson,
1988). Other arctic-alpine species which went regionally
extinct during the Younger Dryas-Holocene shift include Salix
polaris and S. herbacea, S. reticulata (Berglund and Malmer, 1971;
Liedberg-J€onsson, 1988), Arctostaphylos alpina (Berglund and
Digerfeldt, 1970; Liedberg-J€onsson, 1988), Selaginella selaginoides
(Fischer Mortensen et al., 2011; Liedberg-J€onsson, 1988) and
Potentilla nivea (Fischer Mortensen et al., 2011). Hence the strong
impact of the Younger Dryas-Holocene warming on terrestrial plant
communities can be observed widely in northern Europe, although
direct comparison with our results cannot be done due to lack of
quantitative turnover rate calculations elsewhere in Europe.
The fossil bone records give evidence of the mammal community
change and regional extinctions of the mammal species during
the PHT (Fig. 5men). Although they are too sparse to quantify the
animal community turnover during the PHT. Reindeer and woolly
mammoth, the two mammalian species for which bone records
exist from the study region, show different population dynamics
during the PHT. There are no bone findings of woolly mammoth
during the Bølling-Allerød 14e12.8 ka BP, and the species may
indeed have been absent fully or mostly from the Baltic region, as
the boreal forest that covered most of the region during this period
was poorly suitable for it. Its appearance during the Younger Dryas
12.8e11.7 ka BP may thus represent its return to the Baltic from
northern Russia where the open habitats remained throughout the
PHT (Stuart et al., 2002; Ukkonen et al., 2011). It went regionally
extinct at the Younger Dryas-Holocene shift at 11.7 ka BP, thus
simultaneously with the most rapid terrestrial vegetation turnover
phase. In contrast, the reindeer has been present in the Baltic region
possibly since the deglaciation throughout the PHT to its regional
extinction at about 11.2 ka BP. However, there is a gap in its bone
record at 13.4e13.2 ka BP, during the Bølling-Allerød period when
the TJuly was about 14 C and most of the region was covered by
pine-birch forest. It is therefore possible that during this short
period reindeer was absent or restricted to northern Estonia, where
predominantly open tundra prevailed even during the BøllingAllerød
interstadial (Amon et al., 2014).
To sum up, it is clear that although the PHT included a number of
rapid climate changes, the most fundamental turnover in terrestrial
and aquatic plant and animal communities occurred during the
Younger Dryas-Holocene shift at 11.7 ka BP. It is likely that this
fundamental change in the terrestrial and aquatic plant and animal
community structure was not caused only by the direct impact of
warming. Many arctic-alpine species can tolerate warm temperature
and can grow and regenerate under controlled conditions such
as gardens (Dahl, 1998). They succumb to competition, but if the
habitat remains open, they can survive in the lowlands (Birks,
2008). Hence the indirect influences of the warming can be more
important. Pollen and plant macrofossil data suggest that during
the Younger Dryas-Holocene shift the typical boreal species, such as
birch and pine, suddenly became common species in the study area
(Amon et al., 2014; Heikkil€a et al., 2009). Their expansion had a
major impact on the flora of the tundra or steppe-tundra vegetation
which prevailed during the Younger Dryas, and influenced the
interspecific competition by reducing light and nutrient availability,
eventually causing development of the boreal forest and the
regional extinction of the arctic-alpine plant species in the region.
Moreover, there is evidence that the permafrost prevailed in
northern Europe, including the Baltic region, during the Younger
Dryas and started to melt during the rapid warming at the Younger
Dryas-Holocene shift (Isarin, 1997; Lamsters and Zelcs, 2014;
Vandenberghe and Pissart, 1993). The permafrost and associated
periglacial soil processes, such as cryoturbation and other soil
disturbances, would have promoted the occurrence of the arcticalpine
plants, which can utilize the seasonally thawed soils above
the permafrost and survive in such unstable conditions (Peterson,
2014).
The fossil evidence is not precise enough to assess whether the
disappearance of the arctic-alpine elements happened during the
fast warming of the Younger Dryas-Holocene shift or more gradually
with the development of the dense boreal forest, but the evidence
points to fairly rapid disappearance, rather in decades than in
centuries. The indirect influences are likely the cause of the
regional extinction of the woolly mammoth as well. A typical dietary
pattern during the Younger Dryas probably consisted of
grasses, sedges and small-leaved dwarf willow (Salix sp.) twigs and
decayed plants during winter (Schwartz-Narbonne et al., 2015; van
Geel et al., 2008). With the reduction of suitable habitat and the
replacement of herbaceous and grassy plants, its key dietary plants,
by the pine and birch forest during the Younger Dryas-Holocene
shift woolly mammoth was unable to survive.
Unlike the arctic-alpine plants and mammoth, reindeer survived
a few hundreds of years into the Holocene both in the Baltic region
and in southern Sweden, where it went extinct as late as 10.3 ka BP
(Sommer et al., 2011). Although reindeer was a common mammal
species in the cold, open environments of the PHT and is at present
mainly confined to tundra, it can occur in northern boreal forests
too and is thus not exclusively confined to an open or semi-open
habitats. In any case, the fundamental trigger of its regional
extinction in the Baltic countries and southern Scandinavia was the
warming from the Late Glacial to the Holocene interglacial
(Sommer et al., 2011) and its regional extinction therefore represents
a palaeoecological example of the time-delayed impact of
habitat loss or “extinction debt” (Hanski and Ovaskainen, 2002;
Tilman et al., 1994).
5. Conclusions
The impact of rapid climate changes during the PleistoceneHolocene
transition (PHT) 14e11 ka BP on the biotic turnover
rates of terrestrial and aquatic communities were investigated in
the Baltic region using pollen, plant macrofossil, and fossil phytoplankton
data from lake and bog sediment cores. In general, the
terrestrial and aquatic communities showed comparable trends in
their biotic turnover rates. Periods of low turnover and hence stable
communities dated to Bølling-Allerød interstadial 13.4e13.1 ka BP
and to the Younger Dryas stadial 12.9e11.7 ka BP. During both
stable periods the rate of summer temperature change was minimal.
The highest biotic turnover rates occurred during the Younger
Dryas-Holocene shift at 11.7 ka BP. This rapid turnover event
included significant regional extinctions as the arctic-alpine and
N. Stivrins et al. / Quaternary Science Reviews 151 (2016) 100e110108
glacial elements of the flora and fauna in the Baltic region.
Over the last decades, the Northern Hemisphere has warmed by
a rate of 0.2 C/decade. Associated with this rapid warming are
accelerated biotic turnover and extinction rates, and fundamental
ecosystem reorganizations. One of the most important results of
the study is that the rapid biotic turnover during the Younger
Dryas-Holocene shift occurred when the rate of warming was
0.17 C/decade, thus slightly lower than the current Northern
Hemisphere warming. This can be combined with the fact that the
summer temperature values during the PHT in the Baltic region
were 11e14 C, thus comparable to the modern summer temperature
values of the southern arctic zone. We therefore conclude that
the Younger Dryas-Holocene shift with its rapid turnover rates and
associated regional extinctions represents an important palaeoanalogue
to the current high latitude warming and gives insights
about the probable future turnover rates and patterns of the
terrestrial and aquatic ecosystems change in the arctic.
Acknowledgements
We wish to thank EBOR and Institutional Research Funding
IUT1-8 for support.
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.quascirev.2016.09.008.
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