Trees
DOI 10.1007/s00468-013-0891-z

ORIGINAL PAPER

Tree rings reveal extent of exposure to ionizing radiationin Scots pine Pinus sylvestris
Timothy A. Mousseau • Shane M. Welch • Igor Chizhevsky •Oleg Bondarenko • Gennadi Milinevsky • David J. Tedeschi •Andrea Bonisoli-Alquati • Anders Pape Møller

Received: 14 December 2012 / Revised: 12 April 2013 / Accepted: 30 May 2013
Ó Springer-Verlag Berlin Heidelberg 2013

Abstract Tree growth has been hypothesized to provide areliable indicator of the state of the external environment.
Elevated levels of background ionizing radiation may
impair growth trajectories of trees by reducing the annual
growth. Such effects of radiation may depend on theindividual phenotype and interact with other environmental
factors such as temperature and drought. We used standardized growth rates of 105 Scots pine Pinus sylvestris
located near Chernobyl, Ukraine, varying in the level ofbackground radiation by almost a factor 700. Mean growthrate was severely depressed and more variable in
1987–1989 and several other subsequent years, following
the nuclear accident in April 1986 compared to the situation before 1986. The higher frequency of years with poor
growth after 1986 was not caused by elevated temperature,

Communicated by A. Braeuning.
T. A. Mousseau  S. M. Welch  A. Bonisoli-Alquati
Department of Biological Sciences, University of South
Carolina, Columbia, SC 29208, USA
I. Chizhevsky  O. Bondarenko
Chornobyl Radioecological Centre, Chernobyl, Ukraine
G. Milinevsky
Space Physics Laboratory, Taras Shevchenko National
University of Kyiv, 64, Volodymyrska Str., Kyiv 01601, Ukraine
D. J. Tedeschi
Department of Physics and Astronomy, Universityof South Carolina, Columbia, SC 29208, USA
A. P. Møller (&)
Laboratoire d’Ecologie, Systématique et Evolution,
CNRS UMR 8079, Université Paris-Sud, Bâtiment 362,
91405 Orsay Cedex, France
e-mail: anders.moller@u-psud.fr

drought or their interactions with background radiation.
Elevated temperatures suppressed individual growth rates
in particular years. Finally, the negative effects of radioactive contaminants were particularly pronounced insmaller trees. These findings suggest that radiation has
suppressed growth rates of pines in Chernobyl, and thatradiation interacts with other environmental factors andphenotypic traits of plants to influence their growth trajectories in complex ways.
Keywords Chernobyl  Growth  Interaction between
stressors  Ionizing radiation  Tree height  Tree rings

Introduction
On 26 April 1986, one of the Chernobyl nuclear power
plant reactors exploded and a nuclear fire burned for
10 days releasing between 9.35 9 103 and 1.25 9 104
PetaBq of radionuclides into the atmosphere. By contrast,
the Three Mile accident in PA, USA on 27 March 1979
released just 0.0005 PetaBq. Although many of theseradionuclides either dissipated or decayed within hours,
days or weeks [e.g., iodine-131 (131I)], cesium-137 (137Cs)
still persists today in the environment even hundreds ofkilometers from Chernobyl (Shestopalov 1996; Zakharov
and Krysanov 1996; Møller and Mousseau 2006; Yablokov
et al. 2009). Likewise, strontium-90 (90Sr) and plutonium239 (e.g., 239Pu) isotopes are common within the Chernobyl Exclusion Zone and in areas in Russia and Belarus.
Given the 30, 29 and 24,000 years half-life for Cs-137,
Sr-90 and Pu-239, respectively, these contaminants arelikely to be of significance in the health of plants andanimals including humans for many years to come. This
accident provides a unique, but relatively unexploited123Treesopportunity to study the effects of ionizing radiation underfield conditions. Many recent studies have documented thelarge effects of radiation on the abundance and reproductive success of different taxa (e.g., Møller and Mousseau
2007a, b, 2008, 2009). In particular, the accident provides aunique opportunity to conduct common garden or reciprocal transplant experiments (e.g., Kovalchuk et al. 2000)
that will allow tests of environmental and genetic effects ofradiation, and hence tests of adaptation to radiation.
Trees are particularly suitable for studies of the negative
impact of environmental conditions (such as ionizing
radiation) on growth, because growth parameters of thesame individual are stored permanently in tree rings andthese can readily be compared between years with andwithout exposure to the environmental condition, while
simultaneously using trees in control areas as untreatedcontrols (e.g., Ceulemans and Mousseau 1994; Cherubini
et al. 2003; Ufar 2007). Previous studies of the effects ofradiation on tree growth are few and the scope of thesestudies is very limited. Based on subjective and qualitative
assessments, Arkhipov et al. (1994) suggested that doses ofless than 0.1 Gy did not cause any immediate visible
external damage to trees, although internal damage was notquantified. Although many studies have indicated thatradioactive fallout from nuclear tests or nuclear bombs canbe traced in tree rings, this effect may vary among radioactive isotopes due to differences in migration amongisotopes across the tree trunk (e.g., Kagawa et al. 2002).
Schmitt et al. (2000) showed for a very small sample of
Pinus sylvestris pine trees grown near Chernobyl thatxylem formation decreased during 1987–1989, but had
recovered by 1990. Ionizing radiation had no direct effecton the cambium in 1986, but affected the differentiation of
xylem mother cells in that year. Schmitt et al. (2000)
concluded that reduced wood formation was due to massive loss of needles in 1986 rather than uptake of radiobiologically active elements, although this conclusion was
based on only three trees felled at 1, 8 and 20 km from
Chernobyl. Woodwell and Miller (1963) reported that pitch
pine Pinus rigida exposed to chronic levels of radiation forseveral years in the 1950s at the Brookhaven facility
reduced the width of growth rings, with reductions being
the greatest at the base of the tree. This reduction wasaffected by the size of the crown and climate, with trees
with large crowns showing small effects, and such effects
increasing in years with greater climate perturbations.
Again, these results were based on just a few trees making
it difficult to draw general conclusions.
The objectives of our study were to investigate to what
extent radiation from Chernobyl affected means and variances in the growth rate of trees. We relied on comparisonsof growth rate before and after 1986 in the same individual
trees, using the additional design feature of including trees

123that ranged in exposure from normal background radiationof 0.05 lSv/h to 34.5 lSv/h, or an increase in level ofradiation by almost a factor 690 compared to normal
background radiation. This sampling design allowed us toassess the change in mean and variance in growth rate
before and after 1986 for a large number of trees. Scots
pines were not often found in areas of contamination above
30 lSv/h, having been killed by exposure during thedisaster with little or no recruitment in the more highly
contaminated areas since that time.
All previous studies of the effects of radiation on growthrate suffered from problems of small sample sizes, and we
avoided this problem by studying more than 100 trees
across 12 different sites. A second objective of our study
was to investigate the effects of alpha and beta radiationcompared to gamma radiation on trees differing in size,
assuming that small trees would be more susceptible to thenegative impact of radiation (Woodwell and Miller 1963)
because they could only extract water and nutrients fromthe topmost part of the soil where most of the radioactive
material resided (Shestopalov 1996). A third objective wasto investigate variation in annual mean growth rates due toradiation and other environmental factors, because radiation is not the only possible environmental stressor and theeffects of radiation could interact with other stressors. In
fact, we expected that radiation would have an effect on
growth rate, but that this effect would be exacerbated by
the impact of other environmental factors such as hightemperatures and drought in the sandy soils of Chernobyl.
We used Scots pine as a study organism because it iscommon and widespread in the region, but also because
previous studies have shown that these pines are more
susceptible to the negative impact of radiation than manyother species of trees (Arkhipov et al. 1994; Kal’chenko
and Fedotov 2001; Kal’chenko et al. 1993a, b; Kovalchuk
et al. 2003; Rubanovich and Kal’chenko 1994; Shevchenko
et al. 1996).

Methods
Study sites and choice of study specimens
A radiation protection suit was worn in the most contaminated areas. With permission from the Ukrainian authorities, we collected tree cores from Scots pine during 30
January to 5 February 2009 within the Chernobyl Exclusion Zone or in areas adjacent on the southern and westernborders ensuring that we covered a wide range of radiationlevels (Fig. 1). A total of 8 Scots pine trees from each of 14
different sites, in total 112, were selected based on theirsize, to enhance the likelihood of sampling trees older than
30 years of age and hence present before 1986. We couldTreesFig. 1 Location of Scots pine trees and levels of background radiation at the ground level from Cs-137 around Chernobyl. Partly developed from
Shestopalov (1996)

not record tree rings for seven of these trees because thetree core disintegrated, resulting in a final sample of 105
trees. All trees were at the edge of forests and all wereundamaged, because we excluded trees that had lost major
branches, had large holes or showed signs of fungal attack.
Tree cores and phenotype of trees
We extracted tree cores at a height of 1.5 m using a 7 mmincrement borer (Suunto). We measured the height of trees
at an accuracy of 0.5 m using a Nikon hypsometer. The
diameter of the tree at 1.5 m was measured at an accuracyof 1 cm with a DBH tape. Tree cores were subsequently
removed and stored for later treatment and measurement at
the laboratory.
Quantifying tree growth rates
We used standard dendrochronology methods (Cook andKairiukstis 1990) and digital imaging software to measure

the annual growth rings and quantify tree growth rates
before and after the 1986 Chernobyl accident. Tree increment cores were properly oriented and mounted in grooved
wooden boards. Increment cores were then sanded withsuccessively finer grades of abrasive paper until a polishedsurface was obtained and individual cell walls were clearlyvisible under a 209 dissecting microscope. Cores werethen scanned at a 1,200 dpi resolution on a flatbed scanner(Canon, Canoscan 8800f). To ensure suitable detail to be
captured in the digital images, a dissecting microscope wasused to compare each core to its scanned image. The digital
imaging software, (CooRecorder 7, Cybis Elektronik andData AB, http://www.cybis, Larsson 2008a), was used toregister coordinates for the annual growth ring boundaries
in the scanned images. The distances between annual ringboundary coordinates were recorded at an accuracy of
0.1 mm and used to calculate raw annual growth rates. We
used the software program CDendro (Larsson 2008b) tostandardize the annual growth rate by applying the Baillie
and Pilcher normalization and negative exponential

123Treesdetrending procedure that uses a 2-year running average tocalculate the proportion of growth attributable to the current year relative to the previous year, followed by the useof a negative exponential regression of within-tree variation in growth to remove (i.e., detrend) the effects of systematic changes in growth as the tree ages. Standardized
data were used to control the effects of tree age and sitespecific conditions (e.g., soil type) on annual tree ringwidth, allowing comparisons among differently aged trees
and sampled sites. Thus, we derived standardized growth
rates and detrended growth rates as a second standardized
measure of tree growth rate. All annual growth rings weredated to year based on the time of collection. All measurements were made blindly with respect to the level ofbackground radiation for the trees.
To quantify measurement errors, we randomly chose 18
cores and scanned each twice, and each image was digitized twice. Repeatability R between scans was 0.99
(SE = 0.00), F = 2,129.80, d.f. = 450, 1,349, r2 = 0.999,
P \ 0.0001, and repeatability between digitizing eventswas 0.99 (SE = 0.00), F = 2,117.79, d.f. = 452, 1,347,
r2 = 0.999, P \ 0.0001.
Measuring background radiation levels
We measured radiation levels in the field and cross-validated these with measurements by the Ministry of Emergencies, at ground level at each tree using a handheld
dosimeter (Model: Inspector, SE International, Inc., Summertown, TN, USA). We measured levels two to threetimes at each site and averaged the measurements. Suchdata have previously been validated with correlation against
data from governmental measurements at ground level published by Shestopalov (1996), estimated as the midpoint of theranges published. These analyses showed a high degree ofconsistency between the two methods (Møller and Mousseau
2007a). Radiation levels vary greatly at a local scale due toheterogeneity in deposition of radioactive material after the
Chernobyl accident (Fig. 1; Shestopalov 1996).
Dosimetry
A subsample of 44 trees was used to estimate radionuclide
activity within cores using gamma spectrometry. All
measurements were conducted using a Berkeley Nucleonics SAM940 radionuclide identifier system equipped with a
10 9 10 cm NaI detector housed within a ‘‘cave’’ comprising about 1,200 kg of lead shielding. This amount ofshielding resulted in a very low background radiation levelof about 7.5 gcps, thus permitting very high sensitivity.
System calibration was accomplished using a 0.204 microCi source. Counts were recorded for the known source toproduce a calibration factor used to convert the counts from123

unknown samples to Ci. The source was approximately thesame size and shape as the samples and was placed in thesame configuration for reading as the samples, thus
ensuring the same geometry. Cores were usually counted
between 2 and 12 h, depending on the expected activity
levels, with higher activities requiring shorter counting
times for measurement. Twenty-cm-long cores were cut
into four 5-cm pieces to fit atop the scintillation detector.
The average 20-cm3 core had a dry mass of 0.81 g. A
subsample of 12 cores was counted twice to determine therepeatability of measurements. Activity measurements onthese cores was highly repeatable [linear regression:
activity (2) = 0.034 ? 1.056 * activity (1); F = 7.39,
d.f. = 1, 10, P \ 0.0001, r2 = 0.92]. The outer 5-cm pieces for 13 cores were counted individually to assess whether radionuclides were evenly distributed throughout thecore or concentrated toward the outer regions of the tree
trunk. Gamma spectra generated for each sample were
inspected and compared to a background reference spectrum. 137Cs activity was estimated by integrating theactivity above the background threshold at 662 keV, theenergy level for 137Cs photon decay products. Following
counting, cores were weighed on a Mettler electronic balance and individual mass was used to standardize radioactivity across samples for most samples. Small pieces ofsome cores were destroyed during the measurement process and a mass based on the average for all cores was used
to estimate mass for these damaged samples.
Meteorology
We used the E-OBS gridded dataset (version 2.0) maintained by the European Climate Assessment & Dataset(ECA&D) for studying temperature and rainfall (Haylock
et al. 2008). We calculated mean temperature and rainfall
for the main growing season April–August for each year.
Statistical analyses
The background radiation level was log10-transformed. We
developed statistical models to assess the relationshipbetween standardized growth rate and radiation, as implemented in the statistical software JMP (SAS 2012). We
tested for differences in the mean growth rate using Welch
ANOVA, while simultaneously testing for the significanceof a difference in variance among years using Bartlett’s
test.
We tested for differences in means and variances ingrowth rates in relation to the level of background radiation
using a repeated-measures design that allowed for tests
among periods. Means and standard deviations wererecorded for the five 5-year periods 1981–1985, 1986–1990,
1991–1995, 1996–2000 and 2001–2005.

TreesWe developed three generalized linear models. First, wedeveloped a model of the relationship between the mean
standardized tree growth rate in 1981–1985 and1986–1990, using a repeated-measures design to partition
the effects of radiation and period. We used a similar
model for standard deviation in standardized tree growthrate for the two periods. Second, we used a model of thedifference in standardized growth rate between 1981–1985
and 1986–1990 as the response variable, and radiation,height and their interaction as predictors. Third, wedeveloped a full-factorial model of standardized growthrate as the response variable, and background radiation,
temperature, rainfall, period (1950–1985 vs. 1986–2008)
and their two-way interactions and the only three-way
interaction that approached statistical significance aspredictors.
We calculated the mean residual standard growth rate
for different years and used these data in a logistic
regression model with suppressed growth (1—suppressed
growth less than -0.10 for mean standardized growth rate,
0—for normal growth) as the response variable, and period(0—before 1986, 1—1986 or later), temperature, precipitation and their two-way interactions as predictors.
A more detailed investigation of the relationshipbetween radioactivity contained within the tree cores andannual growth rates was performed by calculating the meandifference in absolute growth (mm per year) for the 5 years
after the disaster versus the growth for the 5 years before
1986 and relating this to the level of radioactivity measured
within each tree core (Fig. 5b). To minimize the potential
effects of tree size on changes in growth, only large trees
older than 10 years (mean = 22.6 years) at the time of theaccident in 1986 were included.
We evaluated the magnitude of associations using effectsizes estimated as Pearson product–moment correlation
coefficients. Cohen (1988) proposed explicit criteria forevaluation of small (Pearson r = 0.10, explaining 1 % of
the variance), intermediate (9 % of the variance) and large
effects (25 % of the variance).

Results
We measured 3,758 tree rings from 105 Scots pines.
Annual growth increments were on average 2.93 mm(SE = 0.03, median 2.55 mm, range 0.12–13.49 mm).
Residual growth rates were on average -0.042 (SE =0.004, median = -0.014, range -2.46 to 0.71). Detrended
standardized annual growth (det_bail) was on average-0.038 (SE = 0.004, median = -0.010, range 0.707 to-2.456). These two standardized growth rates werestrongly positively correlated (Pearson r = 0.999), and,
therefore, we used det_bail in all subsequent analyses(these are listed as standardized growth rates in the rest of
the paper). Individual annual standardized growth rates had
a lognormal distribution (KSL test, D = 0.00, P = 0.15).
Trees were 7–25 m tall, mean 15.6 m (SE = 0.4, median = 15.8 m), had a diameter of 19–49 cm, mean 29.3 cm(SE = 0.52, median = 29 cm), and were 9–94 years old,mean 42.1 years (SE = 0.3, median = 42 years).
Radioactivity within tree cores varied from below
detection levels to as high as 23,738 (SE = 135) Bq/kg of
cesium-137 on measuring the full 20-cm core (Table 1).
The highest readings were from trees located in the Red
Forest area. The average activity across all measured cores
was 3,530 Bq/kg (SE = 895). Radionuclides were not
evenly distributed across cores with approximately 46 % of
total core activity found within the outer 5 cm of the core(liner regression, outer activity = -0.005 ? 0.464 * Total
activity, F = 207.2, d.f. = 1, 11, P \ 0.0001; r2 = 0.95).
The highest estimated activity for outer wood cores was
65,815 (SE = 374) Bq/kg (Table 1).
The Cs-137 activity measured from the tree cores was
highly correlated with background radiation levels at thebase of the tree measured using a handheld Geiger counter[linear regression, log(Activity (Bq/kg)) = 1.33 ? 1.70 *log(Background), F = 93.3, d.f. = 1, 42, P \ 0.0001,
r2 = 0.68; Fig. 2], indicating that simple field measurements of background radiation provide a reliable estimateof the likely dose experienced by the tree.
The change in tree growth rate at the time of theChernobyl accident is clearly visible in pine logs from the
Chernobyl Exclusion Zone (Fig. 3). Growth varied significantly among years (Welch ANOVA: F = 4.54, d.f. = 90,
115.12, P \ 0.0001), with significant differences in variance among years (Bartlett’s test, F = 5.37, d.f. = 90,
P \ 0.0001). While growth varied little during 1914–1985(F = 1.86, d.f. = 67, 806.84, P = 0.0062; F = 2.08,
d.f. = 67, P \ 0.0001), there was considerably greater
variation during 1986–2008 (F = 15.72, d.f. = 22, 807.33,
P \ 0.0001; F = 15.72, d.f. = 22, P \ 0.0001). In fact,
the variance during 1986–2008 was significantly greaterthan during 1914–1985 (variance ratio test, F = 1.19,
d.f. = 1,521, 2,173, P \ 0.0001).
Closer inspection of mean annual values revealed
severely depressed growth less than -0.10 in 1987–1989,
and again in 1992, 1996, 2003 and 2006 (Fig. 4). In contrast, there was only a single year with clearly elevatedgrowth greater than ?0.10 (1982). The probability of
having 3 years in a row with depressed growth (1987–
1989) was 7/29 years = 0.2414 to the third power, whichequals 0.0141. A logistic regression with a poor yearwith reduced growth as the response variable (a score of
1—poor year, 0—normal year) and period (before or after
the accident in 1986), temperature, rainfall and all two-way
interactions as predictors produced a significant model

123

TreesTable 1 Radiation activity levels for Scots pine trees in the vicinity of the Chernobyl nuclear power plant
Location

Background radiation (lSv/h)Full core (Bq/kg)

SE

Outer 5 cm (Bq/kg)

SE

Red Forest

25.1

23,738135

65,815374

Red Forest

18.6

19,917169

27,499233

Red Forest

18.9

17,545292

44,171736

Red Forest

16.7

15,362129

39,007328

Red Forest

21.4

14,383

171

18,312218

Red Forest

17.7

13,303

145

21,443233

Korohod

34.5

6,322

126

11,489230

Vesniane

10.6

6,072

164

11,928322

Korohod

26.9

3,928

123

8,131

254

Red Forest

23.5

3,828

153

6,199

248

Korohod
Korohod

26
8.1

3,692
3,172

119
198

6,105
6,190

197
387

Red Forest

16.7

2,961

141

4,737

226

Red Forest

16

2,896

152

5,253

276

Red Forest

16

2,840

123

2,868

125

Fish pond

3.6

2,796

164

1,891

111

Red Forest

13

2,438

163

5,342

356

Red Forest

11

1,168

130

2,247

250

Korohod

9.1

1,005

167

2,121

353

Red Forest

12

949

136

2,743

392

Vesniane

17

943

157

1,212

202

Korohod

31.8

897

112

1,973

247

Korohod

9.9

873

146

1,566

261

Yampil

0.17

568

189

948

316

Vesniane

18.7

510

128

458

114

Fish pond

4.7

435

145

748

249

Vesniane
Red Forest

7.3
11

423
296

141
99

682
566

227
189

Red Forest

11

291

146

506

253

Prypiat

1.4

182

182

257

257

Varo

1.5

181

181

395

395

Prypiat

2.8

178

178

318

318

Stari

0.6

146

146

240

240

Stari

0.7

146

146

240

240

Stari

0.8

146

146

240

240

Varo

4

146

146

240

240

Dytiaku

0.18

146

146

240

240

Krashytichi

0.09

146

146

240

240

Bobor

0.8

146

146

240

240

Bobor

1.3

146

146

240

240

Varo

3

0

0

0

0

Krashytichi
Bobor

0.08
1.4

0
0

0
0

0
0

0
0

Pisky

0.11

0

0

0

0

Full-core estimates are for complete 20-cm cores that reflect average tree activity, while activity levels for the outer 5 cm are on averagesignificantly more radioactive on a per weight basis reflecting a higher concentration of Cs-137 in the cambium and the bark123

TreesFig. 2 The relationship between Cs-137 activity (Bq/kg dry weight)
in tree cores and background radiation level (lSv/h) at the base ofeach tree

Fig. 3 Difference in width of tree rings in pine logs from Chernobyl.
The year of the accident in 1986 is clearly visible from the change inthe color of the wood(v2 = 13.68, P = 0.033) that fitted the data (v2 = 25.55,
P = 0.95). There was a significant effect of period(v2 = 9.35, P = 0.0022), while all other effects were small
and not significant (likelihood-ratio v2 \ 0.45, P [ 0.50).
Among the 23 years 1986–2008, there were 7 years withsignificant correlations between standardized annual growth(det_bail) and background radiation (1986, 1988,1989, 1990,
1996, 1998, 2006), while 1.15 would be expected by chance.
The mean correlation coefficient was only -0.075(SE = 0.031), which was significantly different from zero(one-sample t test based on z transformed Pearson correlation
coefficients: t = -2.45, d.f. = 22, P = 0.023).
Repeated-measures ANOVA revealed a highly significant negative effect of background radiation on mean
growth rate, a significant effect of period (1981–1985 vs.
1986–1990) and a significant interaction (Table 2). This is
as expected, if tree growth was reduced only after 1986 andFig. 4 Mean (?SE) annual standardized growth rates of 105 Scots
pine trees around Chernobyl during 1980–2008. Severely depressed
growth is visible during 1987–1989 and also in several subsequent
years

only in trees from contaminated areas. A second repeatedmeasures ANOVA revealed a significant positive effect ofbackground radiation on variation in growth rate asreflected by the standard deviation (Table 2). In addition,
there was a significant effect of period and a significant
interaction.
When analyzing the level of depression of standardized
growth after and before 1986, we found that growth wasdisproportionately reduced at high radiation levels with aneffect size that was intermediate (Table 3; Fig. 5a). Background radiation levels explained 13 % of the variance instandardized tree growth. There was a highly significant
negative relationship between the change in mean growthrate and the radioactivity measured within tree cores [linear
regression: change in mean growth rate = -0.42 radioactivity in the wood (Bq/kg) ? 0.91; F = 6.87, d.f. = 1, 23,
P = 0.016] indicating that growth was significantly lower
following the disaster for trees with contaminated wood
Table 2 Repeated-measures analysis of variance of mean and standard deviation in residual standardized growth rate in relation to
background radiation level, period and their interaction for 105 Scots
pine trees
Source ofvariation

Factor

F

d.f.

P

Slope
(SE)

Radiation (R)25.39

1, 103\0.0001-0.052(0.011)

Period (P)7.894, 100\0.0001

R9P

6.75

4, 100\0.0001

Radiation (R)16.15

1, 102\0.0001

Period (P)

7.35

4, 99

\0.0001

R9P

7.90

4, 99

\0.0001

Means
Betweensubjects
Withinsubjects

Standard deviations
Betweensubjects
Withinsubjects

0.061(0.006)123

TreesTable 3 Difference in mean residual standardized growth rate of
Scots pine trees between 1986–1990 and 1981–1985 in relation to thelevel of background radiation, tree height and their interaction
Variable

Sum ofsquares

d.f.

F

P

Slope (SE)Radiation (R)

0.184

1

9.48

0.003

-0.050 (0.016)

Height (H)

0.043

1

2.20

0.141

0.005 (0.003)

R9H

0.109

1

5.60

0.020

0.009 (0.004)

Error

2.356

101

The model had the statistics F = 6.79, d.f. = 3, 101, r2 = 0.17,
P = 0.0003

relative to trees of low levels of contamination in the wood.
The level of radioactivity in wood accounted for 23 % of
the variance in standardized tree growth (Fig. 5b). Standardized growth was particularly reduced by radiation insmall trees (Fig. 5c).
Growth rate improved in warm and especially in rainy
years, and this effect was stronger when it was both warm
and rainy as shown by the temperature by precipitationinteraction (Table 4). The effects of temperature exacerbated the effect of radiation as shown by the temperatureby-radiation interaction. The effect of temperature changed
in 1986, as shown by the interaction between temperatureand period. Thus, the effects of radiation were mediated by
the impact of temperature and drought. The other effects
including the interactions were either not significant or
marginal effects.
Discussion
The main findings of this study of growth rate of Scots pine
were that reduced growth increments and increased variance in the size of growth increments were associated withelevated levels of background radiation. The magnitude of
the radiation effect depended on the size of trees, because
small trees showed disproportionately reduced growthwhen exposed to radiation compared to large trees. Other

environmental stressors (e.g., temperature and low annual
precipitation) interacted with radiation to reduce growth.
While our data showed a 3-year continuous effect ofradiation on growth suppression, our observations indicated greater variation in annual growth after 1986 andsuppressed growth in 1992, 1996, 2003 and 2006. Indeed,
standardized growth rate was significantly related tobackground radiation in 8 years, with a significant meaneffect across all years, suggesting a continual mean effectof the Chernobyl accident that extends to the present. Thiseffect size of an intermediate magnitude of 0.30 is similar
to the mean effect size of 0.28 found across all metaanalyses in the biological sciences including meta-analysesof the effects of CO2 on plants (Møller and Jennions 2002).
This conclusion is supported by the fact that these exceptionally poor years in terms of growth are not associatedwith elevated temperatures or drought, nor could we document any interaction between weather and radiation.
The degree of suppression of the mean level ofgrowth during 1986–1990 (post-Chernobyl) compared to
1981–1985 (pre-Chernobyl) of individual trees was causedby radiation interacting with tree height, with radiation
effects being disproportionately greater in small compared
to large trees. There are several possible interpretations.
First, more than 90 % of all radioactive material is locatedin the topmost 20 cm of the soil. Short trees having shallow
root systems that do not extend deep into the soil may
extract more radionuclides than tall trees with deep rootsystems. Second, growth rate effects may be more readily
discerned in small trees given the larger absolute growth
rates in short trees (Koch et al. 2004). Third, this may becaused by an interaction related to differential effects ofradiation on mycorrhizae, which may significantly influence radionuclide uptake (Dighton et al. 2008).
The mean growth rate of Scots pines from Chernobyl
varied significantly among years, with a highly significant
difference in variance among years. High levels of variation in growth were much more pronounced during
1986–2009 following the accident in 1986 than during

Fig. 5 Difference in mean standardized growth rate of 105 Scots pine trees around Chernobyl between 1986–1990 and 1981–1985 in relation toa background radiation level (lSv/h), b radioactivity of the wood (Bq/kg) and c height of trees (m)123TreesTable 4 Relationship between residual standardized growth rate of Scots pine trees between 1950 and 2008 in relation to the level ofbackground radiation, temperature and rainfall during April–August, and whether the data were obtained before or after 1986
Variable
Temperature (T)Sum of squares

d.f.

0.277

F

P

Slope (SE)

1

4.59

0.032

0.011 (0.005)

Precipitation (P)

1.213

1

20.08

\0.0001

0.054 (0.012)

Radiation (R)

0.077

1

1.28

0.26

-0.005 (0.005)

Before/after 1986 (B)

0.003

1

0.05

0.82

0.001 (0.005)

T9P

0.647

1

10.55

0.00120.048 (0.016)

T9R

0.472

1

7.67

0.0056-0.015 (0.005)

T9B
P9R

0.643
0.176

1
1

10.45
2.86

0.00120.091

0.016 (0.005)
0.020 (0.012)

P9B

0.034

1

0.56

0.46

0.009 (0.012)

R9B

0.570

1

9.26

0.0024-0.016 (0.005)

T9P9B

0.172

1

2.80

0.094

-0.026 (0.016)

Error

223.7883,636
2

The model had the statistics F = 5.69, d.f. = 11, 3,587, r = 0.02, P \ 0.0001

1914–1985. Suppression of growth occurred during threesubsequent years 1987–1989, and during 1992, 1996, 2003
and 2006, and this suppression was associated with radiation, but not significantly with temperature, precipitation or
their interactions with radiation. Increasing variance ingrowth can be a consequence of increasing age and stem
diameter (e.g., Fritts 1976; Carrer and Urbinati 2004)
although this explanation is difficult to reconcile with asudden change in mean and variance in standardized tree
growth in 1986. Schmitt et al. (2000) reported suppressed
xylem growth in Scots pine during 1987–1989, but notduring 1986, when the accident happened in spring. The
probability of having three consecutive years of suppressed
growth was significantly less than expected randomly,
suggesting that the run of 3 years of suppressed growthduring 1987–1989 was exceptional. Given that radiation
effects were not observed in all years after 1986, we canconclude that other stressors interacted with radiation to
suppress growth. We hypothesize that the annual weather
patterns interacted synergistically with spatially congruent
patterns of site conditions (e.g., the sandy soils of Chernobyl)
and levels of Cs-137 deposition at the landscape scale toproduce significant growth suppression. This hypothesizedinteraction is supported by our observations of greater variation in annual growth after 1986 and suppressed growth in
1992, 1996, 2003 and 2006, when both spatial and temporal
patterns of environmental stressors matched to produce effects
on growth. Repeated-measures analyses of variance confirmed these conclusions by demonstrating that means werereduced and variances increased during some but not all
periods, that these effects were related to radiation, and thatradiation effects differed among periods. Thus, our data show
a 3-year continuous effect and ongoing effects for more than
20 years, which likely extends to the present.

There are uncertainties concerning the nature of Chernobyl effects on tree growth including the mechanisms
underlying the effects of radionuclides on tree growth. The
effects on somatic and germline mutation rates are well
documented (Arkhipov et al. 1994; Kal’chenko and Fedotov 2001; Kal’chenko et al. 1993a, b). The physiologicalmechanisms of uptake of mixtures of radionuclides byplants remain poorly known, as are the relative effects ofexternal exposure to radiation versus internal exposure toradioactive heavy metals that are carried through the xylem
to growing tissues. Our observation of a dose-dependent
response provides support for the hypothesis that radionuclides are in large part responsible for our results. By
using a sampling regime that included a relatively large
number of samples with a wide spatial distribution withrespect to contamination level (Fig. 1.), we were able totest our hypothesis. In other words, depressed growth wasobserved in trees exposed to even small levels of Chernobyl-derived radioactive contaminants exceeding thenatural background level by a factor ten independently of
distance from the reactor site and this is most parsimoniously explained by a direct effect of radioactive contaminants on growth.
Although we only investigated the effects of radiation
on growth rate, pines were clearly also affected in terms ofcomposition of the wood (Fig. 2). Changes in quality andquantity of wood may not only have important implications
for decomposition and use as a construction material, butalso for forest fires that are known to be a significant threat
by redistribution of radionuclides to inhabited areas evenfar outside the Chernobyl Exclusion Zone (Kashparov et al.
2000; Yoschenko et al. 2006a, b). The very high activity
levels of Cs-137 in tissues of trees in highly contaminatedareas reported here further emphasize the need for123Treesinvestigation concerning the potential impacts of forest
fires on the dispersal of radionuclides in populated regions.
In conclusion, we have demonstrated a landscape-scaleeffect of severely reduced growth in Scots pine during
three consecutive years following the nuclear disaster at
Chernobyl, and recurrently in several subsequent years
when environmental stressors were spatially and temporally congruent. Given that significant levels of radionuclides were dispersed across 200,000 km2 in Europe as aconsequence of the Chernobyl disaster, these findings
suggest that there may be ecosystem-scale impacts on
productivity that have not previously been suggested.
Acknowledgments We are grateful for logistic help during ourvisits to Ukraine and Belarus from M. Bondarkov and A. Litvinchuk.
We also thank L. Dobbs for assistance with radio-dosimetry at USC.
We received funding from the University of South Carolina School of
the Environment, Bill Murray and the Samuel Freeman Charitable
Trust, the National Science Foundation, NATO, the Fulbright Program, CRDF and the National Geographic Society to conduct our
research. We acknowledge the E-OBS dataset from the EU-FP6
project ENSEMBLES (http://www.ensembles-eu.org) and the data
providers in the ECA&D project (http://eca.knmi.nl).

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