ORIGINALARTICLE

Long-term drivers of forest compositionin a boreonemoral region: the relativeimportance of climate and humanimpactTriin Reitalu1*, Heikki Sepp€a2, Shinya Sugita3, Mihkel Kangur3,

Tiiu Koff3, Eve Avel3, Kersti Kihno4,5, J€uri Vassiljev1, Hans Renssen6,

Dan Hammarlund7, Maija Heikkil€a8,9,10, Leili Saarse1,

Anneli Poska1 and Siim Veski1

1Institute of Geology, Tallinn University of

Technology, EE-19086, Tallinn, Estonia,2Department of Geosciences and Geography,

University of Helsinki, FI-00014, Helsinki,

Finland, 3Institute of Ecology, Tallinn

University, EE-10120, Tallinn, Estonia,4Institute of Ecology and Earth Sciences,

University of Tartu, EE-50411, Tartu,

Estonia, 5Institute of History, Tallinn

University, EE-10130, Tallinn, Estonia,6Department of Earth Sciences, VU

Amsterdam, NL-1081HV, Amsterdam, The

Netherlands, 7Department of Geology, Lund

University, SE-22362, Lund, Sweden, 8Centre

for Earth Observation Science, Department of

Environment and Geography, University of

Manitoba, Winnipeg, MB, R3T 2N2, Canada,9Freshwater Institute, Fisheries and Oceans

Canada, Winnipeg, MB, R3T 2N6, Canada,10Department of Environmental Sciences,

ECRU, FI-00014 University of Helsinki,

Helsinki, Finland

*Correspondence: Triin Reitalu, Institute of

Geology, Tallinn University of Technology,

Ehitajate tee 5, EE-19086 Tallinn, Estonia.

E-mail: triin.reitalu@mail.ee

ABSTRACT

Aim To assess statistically the relative importance of climate and human

impact on forest composition in the late Holocene.

Location Estonia, boreonemoral Europe.

Methods Data on forest composition (10 most abundant tree and shrub taxa)

for the late Holocene (5100–50 calibrated years before 1950) were derived from

18 pollen records and then transformed into land-cover estimates using the

REVEALS vegetation reconstruction model. Human impact was quantified with

palaeoecological estimates of openness, frequencies of hemerophilous pollen

types (taxa growing in habitats influenced by human activities) and

microscopic charcoal particles. Climate data generated with the ECBilt-CLIO-

VECODE climate model provided summer and winter temperature data. The

modelled data were supported by sedimentary stable oxygen isotope (d18O)records. Redundancy analysis (RDA), variation partitioning and linear mixed

effects (LME) models were applied for statistical analyses.

Results Both climate and human impact were statistically significant predic-

tors of forest compositional change during the late Holocene. While climate

exerted a dominant influence on forest composition in the beginning of the

study period, human impact was the strongest driver of forest composition

change in the middle of the study period, c. 4000–2000 years ago, when per-

manent agriculture became established and expanded. The late Holocene cool-

ing negatively affected populations of nemoral deciduous taxa (Tilia, Corylus,

Ulmus, Quercus, Alnus and Fraxinus), allowing boreal taxa (Betula, Salix, Picea

and Pinus) to succeed. Whereas human impact has favoured populations of

early-successional taxa that colonize abandoned agricultural fields (Betula,

Salix, Alnus) or that can grow on less fertile soils (Pinus), it has limited taxa

such as Picea that tend to grow on more mesic and fertile soils.

Main conclusions Combining palaeoecological and palaeoclimatological data

from multiple sources facilitates quantitative characterization of factors driving

forest composition dynamics on millennial time-scales. Our results suggest that

in addition to the climatic influence on forest composition, the relative abun-

dance of individual forest taxa has been significantly influenced by human

impact over the last four millennia.

Keywords

Anthropogenic impact, community history, Estonia, forest composition, forest

ecology, meta-analysis, millennial time-scale, palaeoecology, pollen data, varia-

tion partitioning.

ª 2013 Blackwell Publishing Ltd http://wileyonlinelibrary.com/journal/jbi 1doi:10.1111/jbi.12092

Journal of Biogeography (J. Biogeogr.) (2013)

INTRODUCTION

Forest composition changes in Europe during the Holocene

are attributable to changing climate (Birks, 1986; Huntley,

1990), climate-associated migration processes with possible

time-lags (Huntley & Birks, 1983; Svenning & Skov, 2005),

species competition and replacement (Bennett & Lamb,

1988; Sepp€a et al., 2009), and long-term soil development

(Birks, 1986). In addition, human activities have influenced

European forest composition, especially during the late

Holocene (Iversen, 1973; Behre, 1988; Bradshaw & Hannon,

1992; Keller et al., 2002; Magny et al., 2002). The impact of

growing human population and agriculture on boreonemoral

forests is clearly demonstrated by an increase of crop-fields

and other open habitats (Poska et al., 2004; Mitchell, 2005;

Overland & Hjelle, 2009; Fyfe et al., 2010). However, the

possible long-term influence of human impact on species

composition in the remaining tree-covered areas is less clear,

and the relative importance of human impact and climatic

factors in determining the late Holocene forest composition

is largely unknown. One way to assess the relative impor-

tance of climatic and anthropogenic factors on long-term

community dynamics is to use dynamic vegetation models in

combination with pollen records (Keller et al., 2002; Lischke

et al., 2002; Bradshaw, 2008; Miller et al., 2008). This model-

ling approach requires considerable knowledge about the

bioclimatic optima and tolerances, dispersal capacities and

disturbance responses of the species. Pollen records are then

used to assess simulation outcomes. This approach has been

effective in evaluating model performance in relation to past

and future climate changes; however, the incorporation of

human impacts into dynamic vegetation modelling has

hitherto been limited (but see Keller et al., 2002).

Here, we provide a novel approach for evaluating the

relative importance of climate change and human impact on

forest dynamics based on fossil pollen. We utilized recent

advances in pollen-based vegetation reconstruction and in

palaeoclimatic modelling to test statistically the significance

of climatic and anthropogenic factors on long-term vegeta-

tion dynamics in Estonia. Estonia is situated in the boreo-

nemoral zone of northern Europe and is well suited for this

study because of an exceptionally dense network of pollen

sites and a long history of human impact. Furthermore,

independent palaeoclimatological proxy records are available

from regions adjacent to Estonia. We focused on the late

Holocene (5150–50 cal. yr bp, calibrated years before 1950)

because it was the period of expanding anthropogenic land

use in Estonia (Poska & Saarse, 2002; Poska et al., 2004) and

the pollen records show that all the major tree taxa currently

growing in Estonia were present in the region over the entire

study period (Saarse et al., 1999; Saarse & Veski, 2001).

Sedimentary pollen records provide insight into past

vegetation dynamics, but interpreting these data in terms of

vegetation composition is not straightforward. Notably, the

representation of surrounding vegetation in the pollen sam-

ples depends on numerous factors such as intertaxonomic

differences in pollen productivity and dispersal, the patchi-

ness of the surrounding vegetation and the size of the sedi-

mentary basin. However, recent theoretical and modelling

advances in pollen analysis (Sugita, 2007a,b) have improved

reconstructions of regional and local vegetation composition

(Hellman et al., 2008; Nielsen & Odgaard, 2010; Sugita et al.,

2010). We used the REVEALS (regional estimates of vegeta-

tion abundance from large sites) model (Sugita, 2007a) to

reconstruct regional vegetation composition at 18 sites in

Estonia during the 5100-year study period. The REVEALS-

reconstructed tree and shrub composition was compared

with simulated and reconstructed records of climate and

human impact. The simulated temperatures were based on

the palaeoclimatic model ECBilt-CLIO-VECODE (Renssen

et al., 2009). As complementary palaeoclimatic data indepen-

dent of vegetation dynamics, we used stable oxygen isotope

records from lacustrine sediments in neighbouring regions

(Hammarlund et al., 2003; Heikkil€a et al., 2010).

The quantity of past archaeological finds has been used to

indicate the intensity of past human impact on the natural

environment (Magny et al., 2002; P€artel et al., 2007; Talla-

vaara & Sepp€a, 2011). However, such data are seldom avail-

able for larger regions and at sufficiently high temporal

resolution. In Estonia, numerous case studies show a corre-

spondence between agricultural establishment phases of

human populations as revealed by archaeological finds and

increases in landscape openness as inferred from pollen data,

particularly from the occurrence of hemerophilous (growing

in habitats influenced by human activities) and cultivated

plant taxa (e.g. Poska & Saarse, 1999; Poska et al., 2004). The

abundance of charcoal particles in lake sediments is also a

good indicator of human activities in northern Europe

(Behre, 1981; Bradshaw & Hannon, 1992; Koff et al., 1998).

Thus, we used landscape openness, percentage cover of

hemerophilous and cultivated taxa, and charcoal concentra-

tion as indicators of human impact.

This study addresses the following questions through sta-

tistical analyses of the combined long-term records of forest

composition, climate and human impact.

1. Are climate and human impact statistically significant

predictors of late Holocene forest composition change?

2. To what extent was the forest composition change during

the late Holocene influenced by climate, human impact, and

their combined effect?

3. What are the responses of individual tree and shrub taxa

to climate and human impact?

MATERIALS AND METHODS

Study area

Estonia (58–60° N, 22–28° E) is situated in the boreonemor-

al forest zone (Fig. 1). The vegetation is characterized by a

mixture of boreal coniferous and deciduous tree species

(Picea abies, Pinus sylvestris, Betula pendula and Betula pubes-

cens), with nemoral deciduous species (e.g. Corylus avellana,

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

2

T. Reitalu et al.

Tilia cordata, Ulmus glabra and Quercus robur) being also

widespread but much less frequent. Climatically, Estonia lies

in the northern part of the temperate climate zone and

at the transition between moderately continental (to the

east) and slightly more maritime climate (to the west). At

present (mean values of 1971–2000), mean temperature is

16.7 °C in July and �4.7 °C in February, and annual precip-

itation is 650 mm (EMHI, 2011). Based on sedimentary

pollen records, the warmest period in the Holocene was

c. 8000–4400 years ago, when mean annual temperature was

c. 2–3 °C warmer and effective moisture was lower than

today (Sepp€a & Poska, 2004).

The earliest records of Stone Age human activities date to

11,000–10,000 cal. yr bp. The early anthropogenic impact on

vegetation was probably limited and only small areas of for-

est were cleared in the immediate surroundings of the settle-

ments (Veski et al., 2005). The earliest evidence of

cultivation in different parts of Estonia dates back to the

Neolithic (6900–3800 cal. yr bp) (Poska et al., 2004). Agri-

culture became a major source of subsistence during the

Bronze Age (3800–2500 cal. yr bp) (Lang, 2007). The study

period (5150–50 cal. yr bp) covers most of the period of

agricultural development in Estonia except for the last

100 years when rapid political and socio-economic changes

caused major land-cover shifts.

Site selection

Pollen records from small lakes and bogs reflect the local

vegetation within c. 10–100 km2 and those from large sites

reflect the regional vegetation within c. 10,000–100,000 km2

(Sugita, 1993). We focused on regional-scale changes in for-

est composition and selected pollen records from sites 250–

2800 m in radius (Fig. 1, and Appendix S1 in Supporting

Information). In two regions where there were no data

available from large sites – Viitna (site no. 18) and southern

Estonia (site no. 17) (Fig. 1) – data from small sites were

pooled by summing up the pollen counts from respective

time periods (Sugita, 2007a). In the case of site 5 (Kiilaspere/

Velise, Fig. 1), two closely situated pollen records that cover

different time periods were combined and treated as one site.

Chronologies

Based on the conventional and accelerator mass spectrometry

(AMS) radiocarbon dates, the chronologies of the selected

sequences were calculated using a standardized methodology

based on the weighted averages of the ranges of the cali-

brated radiocarbon dates using the IntCal09 calibration data

set (Reimer et al., 2009) and the OxCal 4.1 program (Bronk

Ramsey, 2009). To combine radiocarbon ages and lithologi-

cal data, sedimentary deposition models (Bronk Ramsey,

2008) were used. The 5100-year study period was divided

into seventeen 300-year time windows, which were used as

study units. All data were averaged within each of the 300-

year time windows.

REVEALS modelling

We ‘translated’ pollen count data to abundances (% cover) of

the corresponding plant taxa in the surroundings of the study

sites using the REVEALS model (Sugita, 2007a). The details of

the model are provided in Appendix S2. Similar to earlier

studies that have used the REVEALS model (e.g. Hellman

et al., 2008; Nielsen & Odgaard, 2010; Sugita et al., 2010), the

assumed extent of reconstructed vegetation was approximately

100 km 9 100 km for each site. In total, the REVEALS

reconstruction included 22 taxa (trees, shrubs and herbs) that

were abundant in our pollen records (Appendix S2).

Forest composition

Forest composition was characterized by the REVEALS abun-

dance estimates of the 10 most common shrub and tree taxa:

Figure 1 Map of the study area (Estoniawith county borders). Locations of the sites

included in the study: (1) Ermistu; (2)Kahala lake; (3) Kahala bog; (4) Kalsa; (5)

Kiilaspere/Velise; (6) Konsu; (7) Liivj€arve;(8) Maardu; (9) Mustj€arve; (10) Parika;(11) Raigastvere; (12) Ruila; (13) Saha; (14)

Saviku; (15) Surusoo; (16) Vedruka; (17)southern Estonia, combining data from

Kirikum€ae, Plaani and Verij€arv; and (18)Viitna, combining data from Viitna Linaj€arvand Viitna Pikkj€arv. Appendix S1 providesdetailed information about the pollen sites.

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

3

Forest composition, climate and human impact

one shrub (Corylus), eight trees (Alnus, Betula, Fraxinus,

Pinus, Picea, Quercus, Tilia and Ulmus), and one taxon

including both shrubs and trees (Salix). This taxonomic sim-

plification was necessary because pollen identification is

mostly at the genus level (Appendix S2). The REVEALS-esti-

mated percentages of the 10 taxa were recalculated to sum to

100% to quantify the taxon composition of the forested area

instead of the entire landscape.

Indicators of human impact

To estimate the openness (OPEN), we used the sum

of REVEALS estimates of the pollen taxa that indicate non-

forested conditions (Artemisia, Filipendula, Plantago lanceola-

ta, Plantago major/media, Poaceae, Cyperaceae, Rumex

acetosa/acetosella, Juniperus and Cerealia). Because OPEN was

strongly dependent on Poaceae and Cyperaceae that are also

present in natural habitats, we used an additional variable

(HEMER) to reflect the occurrence of taxa that are more

closely related to human impact. HEMER was calculated as

the sum of REVEALS estimates of hemerophilous (Artemisia,

Plantago major/media, Plantago lanceolata, Rumex acetosa/

acetosella) and cultivated taxa (Cerealia).

Charcoal particle counts from pollen samples spiked with

Lycopodium marker grains were available from seven lakes in

Estonia (Appendix S1). In each sample, charcoal concentra-

tion was calculated as: (added Lycopodium 9 counted char-

coal)/(counted Lycopodium 9 sample volume), giving the

number of charcoal particles per cm3 of sediment. The aver-

age charcoal concentration for each of the 300-year time

windows gave an estimate of CHARC.

Climate

For the temperature changes over the study period, we used

the results from a transient simulation experiment with the

ECBilt-CLIO-VECODE climate model, forced by annually

changing values of orbital parameters, atmospheric CO2 and

CH4 concentrations, ice sheet surface albedo, topography

and melt flux. An overview of this simulation (named OG-

MELTICE) has been published by Renssen et al. (2009). The

model reconstructions cover the whole world at 5.6° 9 5.6°spatial resolution and monthly temporal resolution. The

average summer (May–August) and winter (December–Feb-

ruary) temperatures (SUMM_T and WINT_T, respectively)

for Estonia (two grid-cells) were used for the 300-year time

windows. Temperatures were expressed as the differences

from the pre-industrial mean simulated in the climate model

(250–550 cal. yr bp).

In addition to the simulated temperatures, we used stable

oxygen isotope (d18O) records from two sites near Estonia: a

lacustrine carbonate record from Lake Igelsj€on (d18O_IGEL)

in southern Sweden (Hammarlund et al., 2003; Jessen et al.,

2005) and an aquatic cellulose record from Lake Saarikko

(d18O_SAAR) in southern Finland (Heikkil€a et al., 2010). At

these two sites, d18O reflects mainly centennial-scale changes

in effective moisture. In general, high d18O values reflect

drier and warmer climate, and low d18O values reflect colder

and moister climate (Hammarlund et al., 2003; Heikkil€a

et al., 2010).

The present-day climate in Estonia is relatively maritime

in the coastal areas and more continental further inland. We

assume that this gradient has been consistent over the late

Holocene. To account for that gradient, we calculated a coef-

ficient of continentality for each pollen site based on the

present-day winter and summer temperatures. The mean

temperature of the coldest quarter of the year and the mean

temperature of the warmest quarter of the year for the pollen

sites were extracted from the WorldClim global climate data-

base (BIOCLIM database at 2.5-arc-minute resolution, http://

www.worldclim.com/; Hijmans et al., 2005). The difference

between the temperature of the warmest and coldest quarters

gave an estimate of continentality (CONT) (Tuhkanen,

1980).

Statistical analyses

For all the statistical analyses we used the 300-year time win-

dows as study units. Some pollen records did not cover the

entire 5100-year study period (Appendix S1) and altogether

the data set used for statistical analyses consisted of 277

study units (n = 277).

To evaluate general trends in the associations among forest

composition, human impact and climate, we used redun-

dancy analysis (RDA). We assigned forest composition data

as the response matrix and climate and human impact data

as constraining variables. The forest composition data were

square-root transformed prior to the RDA to ensure a more

even distribution of data in the ordination space. Signifi-

cances of the marginal effects of single constraining variables

were evaluated using Monte Carlo permutation tests (999

randomizations) and non-significant (P < 0.05) constraining

variables were removed by a backward selection procedure.

To illustrate the community change through time at individ-

ual sites, we superimposed the time-trajectories of the sites

on the RDA plot.

Variation partitioning (Borcard et al., 1992) was used to

provide insight into the relative impacts of the three groups

of variables – ‘human impact’ (OPEN, HEMER, CHARC),

‘climate’ (WINT_T, SUMM_T, d18O_IGEL, d18O_SAAR,CONT) and SITE. To understand how the relative roles of

climate and human impact change over time, we repeated

the variation partitioning analysis in subsets of the data

defined by a moving period of 1200 years (four 300-year

study units). This resulted in 14 analyses of overlapping data

sets. The significances of the individual effects of the parti-

tions were estimated with Monte Carlo permutation tests

(999 randomizations) in each of the analyses.

To explore the individual responses of different forest taxa

to the factors reflecting human impact and climate, we used

linear mixed effects (LME) models with each of the 10 taxa

(Fig. 2a) as response variables. LME models allow one to

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

4

T. Reitalu et al.

estimate the effects of fixed explanatory variables (OPEN,

HEMER, CHARC, SUMM_T, WINT_T, d18O_IGEL,

d18O_SAAR, CONT) and to account for variation due to

random effects, such as among-site variability and temporal

autocorrelation (Zuur et al., 2009). The abundances of forest

taxa were square-root transformed prior to the analysis and

the explanatory variables were standardized to zero mean

and unit variance. In the random part of the models, we

included SITE to account for the fact that samples from one

site tended to be similar and temporal autocorrelation struc-

ture with autoregressive moving average (corARMA) model

where the number of autoregressive parameters and the

number of moving average parameters were both set to one.

We used a stepwise backward selection procedure with the

likelihood ratio test (Zuur et al., 2009) where, at each step,

the variable (or quadratic term) giving the highest P-value

was left out until only significant (P < 0.05) terms remained.

To evaluate the goodness of fit of the LME model, we calcu-

lated squared correlation coefficient (r2) between the

response variable and the model-estimated values.

We used the R environment (version 2.10.1) (R Develop-

ment Core Team, 2009) with the packages vegan (RDA and

variation partitioning), and nlme (LME models) for statisti-

cal analyses.

RESULTS

All environmental variables except CHARC and WINT_T were

significantly (P < 0.05) associated with forest composition in

the RDA. The triplot (Fig. 3a) indicated that the nemoral

deciduous taxa were mainly related to the climate variables;

among boreal taxa, Picea was positively associated with conti-

nentality, and Pinus, Betula and Salix were mainly related to

the indicators of human impact. Time-series of individual sites

(Fig. 3b–d, Appendix S3) showed that in the beginning of the

5100-year period, all sites were dominated by nemoral decidu-

ous taxa (Ulmus, Tilia, Corylus and Fraxinus). Thereafter,

three distinctive trajectories can be separated: (1) development

of Picea-dominated forest, followed by the dominance of

Pinus, Betula and Salix (exemplified by Kiilaspere/Velise,

Fig. 3b); (2) development and persistence of Picea-dominated

forest (exemplified by Parika, Fig. 3c); (3) development of

forest dominated by Pinus, Betula and Salix without the Picea-

dominated phase (exemplified by Surusoo, Fig. 3b). The tra-

jectories of all 18 sites are given in Appendix S3.

The results of the variation partitioning analysis showed

that the variable groups ‘climate’ (SUMM_T, WINT_T,

d18O_SAAR, d18O_IGEL, CONT) and ‘human impact’

(CHARC, OPEN, HEMER), together with SITE, explained

69.0% of the variation in the forest composition across the

whole 5100-year study period (Fig. 4a). The decomposition

of the variation showed that the largest fraction of the vari-

ability was accounted for by SITE (27.7%), followed by the

shared effect of ‘climate’ and ‘human impact’ (21.3%). The

individual effect of ‘climate’ on forest composition was

10.2% and the individual effect of ‘human impact’ was 3.8%.

Variation partitioning within the 1200-year time periods

indicated a rapid increase in the relative importance of the

%%

%%

%%

%

δ18O_SAAR

δ18O_IGEL

Alnus

Betula

Corylus

Fraxinus

Picea

Pinus

Quercus

Salix

Tilia

Ulmus

6

(a) (b)

54

3

35

25

15

12

6

321

50

40

30

21

15

9

21

21

9

15

3

9

15

3

OPEN

HEMER

CHARC

WINT_T

SUMM_T

%%

%

%

30

20

10

6

3

%

5000

-7

-9

-14

-18

0.2

0.1

0.5

0.2

°C‰

‰

5000 4000 3000 2000 1000 0Time, cal. years BP

Time, cal. years BP

35000

Particles/cm

3

CONT20

21

22

°C°C

5000 4000 3000 2000 1000 0

Figure 2 Forest composition and

explanatory variables in Estonia through

time: (a) REVEALS estimates of theabundances of forest taxa, and (b)

indicators of human impact (OPEN,HEMER, CHARC) and climate

(d18O_SAAR, d18O_IGEL, SUMM_T,WINT_T, CONT). Mean (solid lines)

and � 2 standard errors of the mean(dashed lines) characterizing the amount of

variation.

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

5

Forest composition, climate and human impact

human impact from around 0% in the first time period (5150

–3950 cal. yr bp) to 14% in the fifth time period (3950–

2750 cal. yr bp) (Fig. 4b), after which the importance of

human impact slowly decreased. Climate explained 17–20% of

the variation in forest composition during the first two time

periods and < 10% during the rest of the study (Fig. 4b).

Separate LME models for each taxon produced roughly

the same results as the RDA. Nemoral deciduous taxa (Cory-

lus, Tilia, Fraxinus, Quercus and Ulmus) were positively asso-

ciated with summer temperature and d18O (Table 1). Alnus,

Quercus and Ulmus were also positively associated with land-

scape openness. Betula, Pinus and Salix were strongly posi-

RDA1

RDA2

-0.6 -0.2 0.2 0.6

-0.8

-0.4

0.0

0.4

OPEN

HEMERBetula

PinusSalix

CONT Picea

Corylus

SUMM_TUlmus

Tilia

FraxinusAlnus

RDA1

RDA2

-0.6 -0.2 0.2 0.6

-0.8

-0.4

0.0

0.4

RDA1

RDA2

-0.6 -0.2 0.2 0.6

-0.8

-0.4

0.0

0.4

RDA1

RDA2

-0.6 -0.2 0.2 0.6

-0.8

-0.4

0.0

0.4

Kiilaspere/Velise

Parika Surusoo

(a) (b)

(c) (d)

δ18O_IGELδ18O_SAAR

Quercus

Figure 3 Results of redundancy analysis

(RDA) of Estonian forest composition: (a)RDA triplot indicating the positions of

forest taxa, climate and human impactvariables and sites along the first two

ordination axes; (b–d) ecological trajectoriesof forest composition from 5150 cal. yr bp

(open circle) to 50 cal. yr bp (circle with across) at three selected sites.

3950-2750

4250-3050

4550-3350

Time period (years BP)

Explainedvariation(%)

Climate10.2 %

Site27.7 %

3.9 %1.2 %

Undeterminedvariation31.0 %

Humanimpact3.8 %

0.9 %

21.3 %

ClimateHuman impact

(a) (b)30

25

20

15

10

5

0

5150-3950

4850-3650

3650-2450

3350-2150

3050-1850

2750-1550

2450-1250

2150-950

1850-650

1550-350

1250-50

Figure 4 Partitioning of Estonian forest composition in terms of the percentage of variation explained by ‘human impact’ (HEMER,OPEN, CHARC), ‘climate’ (SUMM_T, WINT_T, d18O_SAAR, d18O_IGEL, CONT) and SITE. The results are presented (a) for the

whole 5100-year study period where all three groups of predictors are highly significant (P < 0.001), and (b) for 14 subsets of data in

1200-year periods where black symbols indicate significant (P < 0.05) and grey symbols indicate non-significant individual effects ofclimate and human impact.

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

6

T. Reitalu et al.

tively associated with human impact, as shown by the posi-

tive association with the proportion of hemerophiles, with

Betula and Pinus also negatively associated with summer

temperature. The only taxon that was negatively associated

with human impact was Picea.

DISCUSSION

We demonstrated that over the 5100-year study period in

the late Holocene, climate explained about four times more

variation in forest composition in boreonemoral Estonia

than human impact. Many earlier palaeoecological studies

have qualitatively shown that the importance of human

impact on overall vegetation composition in Europe has

increased over the last few millennia with the expansion of

agriculture and forest management (e.g. Behre, 1988; Lind-

bladh et al., 2000; Poska et al., 2004; Feurdean et al., 2010).

In accordance with dynamic modelling studies (Easterling

et al., 2001; Keller et al., 2002), our analysis showed that

human activities have not only caused increased landscape

openness, but have also affected the species composition in

the remaining forests. The results of the variation partition-

ing analysis within shorter time periods revealed that human

impact became a dominating driver of forest compositional

change at 3950–1850 cal. yr bp, which is the period of estab-

lishment and expansion of permanent agriculture in Estonia

(Poska et al., 2004). Our results thus suggest that the first

opening of the landscape had effects on forest composition

exceeding the effects of increasing non-forested agricultural

land area over the last 2000 years of the study period.

In addition to the statistically significant individual effects

of climate and human impact, there is a large shared effect of

these two groups of variables on forest composition. The

shared effect can be attributed to climate influencing agricul-

ture and other human activities. In northern Europe, warmer

periods are believed to promote the expansion of agriculture

(Berglund, 2003). In our data set, however, all three indica-

tors of human impact increase when temperature decreases

(Fig. 2b), indicating that agricultural expansion occurred

irrespective of climatic trends (cf. Sillasoo et al., 2009). The

shared effect in our analysis suggests that, coincidentally, cli-

mate change and human impact have simultaneously affected

forest composition: the same tree taxa that benefited from

human disturbances (Betula, Pinus and Salix) were able to

better withstand the late Holocene cooling than the nemoral

deciduous taxa (Sepp€a et al., 2009). Similar parallel ecological

trajectories between human influence and climate have been

observed in the Mediterranean region (Jalut et al., 2009).

The RDA results (Fig. 3, Appendix S3) showed that the

forest composition was relatively homogeneous at the begin-

ning of the study period, being mainly characterized by ne-

moral deciduous taxa, such as Tilia, Ulmus, Corylus, Fraxinus

and Quercus. Around 4000 cal. yr bp, however, geographical

differences in the vegetation started to evolve. Coastal sites

in northern and western Estonia became dominated by Pi-

nus, Betula and Salix, whereas sites in southern and eastern

Estonia became first characterized by Picea and thereafter by

Pinus, Betula and Salix at about half of the sites (Fig. 3b,

Appendix S3). One possible explanation for this geographical

pattern may be related to the differences in soil properties.

The coastal areas of Estonia have calcareous bedrock and the

soils are shallow and less suitable for the growth of Picea

than the deeper soils on top of sandstone and clay in south-

ern Estonia (Laasimer, 1965). Picea is also the latest of the

Table 1 Summary of the LME models explaining the occurrences of forest taxa in Estonia over the last 5100 years. The random part of

the models includes SITE (random intercept) and temporal autocorrelation with autoregressive moving average model. In the fixed partof the models, linear terms are marked with ‘+’ for positive and ‘�’ for negative associations; quadratic terms are marked with ‘∩’ forhump-back associations and with ‘∪’ for U-shaped associations; r2 is the squared correlation between response variable and modelestimation. WINT_T and CHARC were always excluded during the backward selection procedure and are the only fixed variables not

included in any of the final models. The significances of the fixed factors are given as: ***P < 0.001; **P < 0.01; *P < 0.05.

TaxonHuman impact Climate

HEMER OPEN d18O_IGEL d18O_SAAR SUMM_T CONT r2

Corylus + *** + *** � *** 0.54

Fraxinus + ***∪ *

+ *** 0.31

Tilia + *** + *** + *** 0.48

Ulmus + *** + *** + ***∪ **

+ *** 0.55

Quercus + ** + *** + *** 0.33

Alnus + **∪ **

+ **∪ *

0.18

Picea � *** � ***∩ ***

0.22

Betula + ** + *** � ** 0.52

Pinus + **∪ *

� *** � *** 0.64

Salix + *** + ** 0.34

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

7

Forest composition, climate and human impact

major tree species to immigrate to Estonia and began to

spread from the most continental part in the south-east

around 8000 cal. yr bp (Saarse et al., 1999). It is possible

that Picea never really became dominant in the coastal areas

because the relatively maritime climate favoured the nemoral

deciduous species and postponed the dominance of Picea

until the fertile areas suitable for the growth of Picea had

already become arable fields. In southern and eastern

Estonia, on the other hand, Picea had already become domi-

nant before the expansion of arable fields occurred. The sites

where Picea dominated throughout the end of the study

period (Saviku, Konsu, Ermistu and Parika; Appendix S3)

are the sites with the lowest human impact in the surround-

ings until the present day. It is likely that without human

impact, Picea would be more dominant in Estonia and else-

where in the boreonemoral zone.

The taxon-wise analyses of the 10 major tree and shrub taxa

showed that the nemoral deciduous taxa (Tilia, Corylus, Fraxi-

nus, Quercus and Ulmus) were positively associated with war-

mer (and drier) climate, as indicated by the significant

positive associations with SUMM_T and d18O_SAAR. The

decline of nemoral deciduous taxa during the late Holocene

has often been associated with increasing human impact in

central Europe (e.g. Behre, 1988; Bradshaw & Hannon, 1992;

Lindbladh et al., 2000; Cowling et al., 2001), but in Estonia

these taxa occur close to their climatic distribution limits

(Hult�en & Fries, 1986), and the influence of cooling is likely to

overshadow the influence of human impact. Sepp€a et al.

(2009) suggested that the interspecific competition associated

with the mid-Holocene expansion of Picea played a major role

in forest ecosystem change in Fennoscandia. Picea is a shade-

tolerant and competitively superior taxon, and its rapid popu-

lation rises may have suppressed nemoral deciduous taxa,

especially Tilia and Corylus. We did not explicitly test the asso-

ciations between Picea and deciduous taxa in our data but it is

notable that the initial decline of Tilia and Corylus coincided

with an increase of Picea around 4500 cal. yr bp (Fig. 2).

In addition to the strong associations with climate vari-

ables, three nemoral deciduous taxa (Quercus, Ulmus and

Alnus) were positively associated with landscape openness

(Table 1). The positive association of Quercus with open-

ness may be the result of its demand of light (Diekmann,

1996). Quercus was also preferred by human management

in the wooded meadows and wood pastures, which were

half-open seminatural habitat types common in Estonia

(covering up to 19% of the land area) and elsewhere in

northern Europe for thousands of years (Iversen, 1973;

Kukk & Kull, 1997; Fyfe et al., 2010). The declines of

Ulmus and Alnus have previously been associated with

increasing human impact in Estonia (Poska et al., 2004;

Saarse et al., 2010). Our present analysis, using multiple

linear models, however, revealed that when the climate

variables were accounted for, both Ulmus and Alnus were

more common in areas with high levels of openness. The

species of both taxa (especially A. glutinosa, A. incana and

U. laevis) are known to be associated with forest edges,

river banks and lake shores in the present-day landscape

(Kukk, 2004), which may explain their relative commonness

in more open areas. A. glutinosa and A. incana are both

early-successional species that are common invaders of

abandoned arable fields and pastures.

Contrary to the findings for the nemoral deciduous taxa

(Ulmus, Tilia, Corylus, Quercus and Fraxinus), the boreal taxa

(Picea, Pinus and Betula) were significantly negatively associ-

ated with SUMM_T and d18O_SAAR, showing that the

cooler and wetter climate has favoured these taxa. Human

impact was also significantly associated with all boreal taxa,

positively with Pinus, Salix and Betula, and negatively with

Picea. Agriculture has focused primarily on fertile and mesic

soils (Poska et al., 2004), causing the decline of Picea, and

nutrient-poor and wet soils have remained forested, explain-

ing the increasing relative abundances of Pinus, Betula and

Salix. Betula and Salix are also usual invaders of abandoned

arable fields, further increasing the relative importance of

these taxa in the agricultural landscape.

CONCLUSIONS

Although the effects of climate and human impact cannot be

fully decoupled, our results show that both climate and

human impact are statistically significant predictors of long-

term forest compositional change during the late Holocene.

While climatic influence on forest composition is dominant

in the beginning of the study period, the importance of

human impact becomes a dominating driver behind forest

compositional change in the middle of the study period

(c. 4000–2000 years ago), which is the period of establish-

ment and expansion of permanent agriculture. Late Holocene

cooling negatively affected the populations of nemoral decid-

uous taxa (Tilia, Corylus, Ulmus, Quercus, Alnus and Fraxi-

nus) and favoured the expansion of boreal taxa (Betula,

Salix, Picea and Pinus). Human impact in Estonia favoured

early-successional fast-growing taxa that can colonize aban-

doned fields (Betula, Salix and Alnus) or can grow on less

fertile soils (Pinus). Increased landscape openness and possi-

bly selective logging have favoured light-demanding taxa

such as Quercus.

Our study demonstrates that meta-analysis of palaeoeco-

logical and palaeoclimatic data has the potential to provide

an alternative and comparative approach to dynamic vegeta-

tion modelling in characterizing long-term ecological pro-

cesses. Compiling a large data set of pollen records helps to

overcome inter-site variation in pollen data and enables the

evaluation of general regional trends in vegetation types and

species composition. Combining palaeoecological and palaeo-

climatic data with statistical analyses allows us to reveal asso-

ciations that are unobservable in purely descriptive pollen

studies. The increasing availability of high-quality pollen

records (Fyfe et al., 2009) makes it possible to expand our

synthetic approach to larger data sets and other forest

ecosystems to assess the generality of the trends demon-

strated in Estonia.

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

8

T. Reitalu et al.

ACKNOWLEDGEMENTS

We thank Kai Kimmel for sharing pollen data, Meelis P€artel

and the LANDCLIM group for discussions, Oliver Purschke

for statistical advice, Aveliina Helm and Jesse Morris for

comments, and Jens-Christian Svenning, Thomas Giesecke

and Petr Kune�s for constructive criticism. This project was

supported by Estonian Science Foundation Mobilitas Pro-

gramme MJD4 to T.R. and MTT3 to S.S. and by ETF9031.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the

online version of this article:

Appendix S1 Details of pollen and charcoal data sets.

Appendix S2 Details of the REVEALS model.

Appendix S3 Site trajectories on RDA triplot.

BIOSKETCH

Triin Reitalu is a plant ecologist interested in historical pro-

cesses that influence the present-day vegetation patterns, with a

special interest in the role of human impact in the formation of

diversity patterns. Currently, she is a post-doctoral researcher

at the Institute of Geology, Tallinn University of Technology in

the group of Siim Veski, exploring various ecological hypothe-

ses using palaeoecological and palaeoclimatological records.

Author contributions: T.R. and S.V. conceived the ideas; M.

K., T.K., E.A., K.K., L.S., A.P. and S.V. provided the pollen

data; J.V. calibrated the chronologies of the pollen stratig-

raphies; H.R. provided the modelled climate data; H.S., M.H.

and D.H. provided the d18O data; T.R. conducted the statis-

tical analyses and wrote the paper, with substantial input

from S.S., H.S. and S.V.

Editor: Jens-Christian Svenning

Journal of Biogeographyª 2013 Blackwell Publishing Ltd

11

Forest composition, climate and human impact