226

Biol. Rev. (2013), 88, pp. 226–254.
doi: 10.1111/j.1469-185X.2012.00249.x

The effects of natural variation in backgroundradioactivity on humans, animals and otherorganisms
Anders P. Møller1,∗ and Timothy A. Mousseau2
1
2

Laboratoire d’Ecologie, Systématique et Evolution, CNRS UMR 8079, Université Paris-Sud, Bâtiment 362, F-91405, Orsay Cedex, France
Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA

ABSTRACT
Natural levels of radioactivity on the Earth vary by more than a thousand-fold; this spatial heterogeneity may suffice tocreate heterogeneous effects on physiology, mutation and selection. We review the literature on the relationship between
variation in natural levels of radioactivity and evolution. First, we consider the effects of natural levels of radiation on
mutations, DNA repair and genetics. A total of 46 studies with 373 effect size estimates revealed a small, but highly
significant mean effect that was independent of adjustment for publication bias. Second, we found different mean effectsizes when studies were based on broad categories like physiology, immunology and disease frequency; mean weighted
effect sizes were larger for studies of plants than animals, and larger in studies conducted in areas with higher levelsof radiation. Third, these negative effects of radiation on mutations, immunology and life history are inconsistent witha general role of hormetic positive effects of radiation on living organisms. Fourth, we reviewed studies of radiation
resistance among taxa. These studies suggest that current levels of natural radioactivity may affect mutational input andthereby the genetic constitution and composition of natural populations. Susceptibility to radiation varied among taxa,
and several studies provided evidence of differences in susceptibility among populations or strains. Crucially, however,these studies are few and scattered, suggesting that a concerted effort to address this lack of research should be made.
Key words: adaptation, cancer, disease, DNA repair, hormesis, mutation, radioactivity, radio-resistance, radio-tolerance.
CONTENTS
I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
II. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228(1) Literature search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228(2) Extracting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229(3) Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
III. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229(1) Mean effect size and tests for publication bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229(2) Effect size and explanatory variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245(3) Variation in radiation resistance among natural populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
IV. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
V. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
VI. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
VII. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251

I. INTRODUCTION
Radiation can be divided into non-ionizing radiation (radio
waves, visible light and heat) and ionizing radiation thathas sufficient energy to ionize an atom. Ionizing radiationconsists of particles that cannot penetrate paper, particles
that can penetrate paper, but not an aluminium sheet, andrays that can penetrate paper, aluminium and thin layers* Address for correspondence (Tel: (+33) 1 69 15 56 88; Fax: (+33) 1 69 15 56 96; E-mail: anders.moller@u-psud.fr)
Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Evolution and natural variation in radioactivityof lead. Both ionizing and non-ionizing radiation can bedamaging for organisms, although ionizing radiation is moredamaging because the ions that are generated may directly
damage DNA and other molecules. Levels of backgroundionizing radiation (hereafter radiation) have always varied
spatially and temporally on Earth. Levels of backgroundradiation were very high during the Pre-Cambrian period
peaking around two billion years ago at a dose rate of 7 mGy
per year, but have decreased by a factor of 10 since life firstoriginated (Karam & Leslie, 2005). During the subsequent 2
billion years, radiation levels fluctuated considerably due tolarge solar flares, nearby supernovae and gamma ray bursts.
Large meteor impacts in Mexico, India, Russia and other sites
also likely caused the release of vast amounts of radioactive
material on Earth (e.g. Alvarez et al., 1980). Such fluctuations
may have contributed to current levels of resistance toradiation damage in free-living organisms. Today, typicalbackground radiation dose rates vary around a minimum of
only 0.01–0.10 with the natural level in Chernobyl before
the nuclear accident being 0.01–0.02. By contrast, there are
geographic regions where naturally occurring radiation canreach very high levels (3 orders of magnitude above global
mean levels). There are equally many sites with high levelsof radiation in the oceans, with thermal vents and theirassociated unique biodiversity being a well-known example(e.g. Fiala-Médioni, Alaysee & Cahet, 1986; Cherry et al.,
1992; Jollivet et al., 1995a, b, 2003). Maximum terrestrial
levels of radioactivity reach as high as 29.7 h in Ramsar,
Iran, 22 h in Morro do Ferro, Minas Gerais, Brazil, 12 hin Mombasa, Kenya, 10 /h in Lodeve, France, 4.0 Sv/h in
Kerala, India, 4.0 Sv/h in Tamil Nadu, India, and 0.7 /h in
Yangjiang, China (Ghiassi-Nejad et al., 2002). Such radiationis related to the presence of radionuclides in the rock or in theform of gases like radon that can be trapped inside buildings
or caves and increase human exposure to mutagens that
subsequently increase rates of cancer (e.g. Lubin & Boice,
1997; Hendry et al., 2009). These natural levels of radiation
are still 20-fold less than the maximum levels present today
at Chernobyl.
Mutations are changes in genomic sequences of DNA that
may occur as a consequence of breakage of a single or double
strand of DNA. DNA repair can restore sequences of DNA,
most readily single-strand, but also double-strand DNA(Lehman, 2006; von Sonntag, 2010). Somatic mutations are
sometimes the source of genetic diseases including cancer,
while germ-line mutations can be transferred to offspring.
Mutations are an important source of novel genetic variation(Hartl & Clark, 1997). That radiation is a powerful mutagen
was shown by classical laboratory experiments (Nadson &Philippov, 1925; Muller, 1954; UNSCEAR, 1988; National
Academy of Sciences – Natural Resources Council, 1990),
but it is less well known that natural variation in levels of
background radiation is also a significant cause of mutation(e.g. Forster et al., 2002); exposure to natural radon in homes
is the second leading cause of lung cancer in the US (e.g.
Lubin & Boice, 1997; WHO, 2009). However, we currently
do not know the relative importance of radiation and, for

227
example, dietary mutagens as causes of mutations, nor do
we understand the average effect of naturally occurring
background radiation on mutations.
What are the consequences of natural variation inbackground radiation for evolution? Given the current 1000fold difference in natural levels of background radiationsuch effects should be measurable in both past and current
rates of mutations, but we are unaware of any studies
investigating such effects. A partial answer may comefrom a recent study of the relationship between local
population density and radiation at Chernobyl arising fromthe catastrophe on 26 April 1986. Different species of birds
in the Chernobyl area vary enormously in their toleranceof radiation; some species have similar local densities athigh and low levels of radiation, while other species havedramatically reduced population densities at sites with highradiation levels. Møller et al. (2010) showed that historicalmitochondrial mutation rates in birds, as reflected by DNA
substitution rates, were positively correlated with the impact
of radiation from Chernobyl on local population density,
independent of all known confounding variables correlatedwith mitochondrial DNA (mtDNA) substitution rates. Thus,
species that were ecologically strongly impacted by radiation
around Chernobyl, as shown by reduced densities at highlevels of radiation, were also those most strongly impacted bymutagens in the past as reflected by high substitution rates.
Although other factors (e.g. variation in historical population
sizes, mutational biases related to DNA composition andinteractions, and selection) also likely affected historical
mtDNA substitution rates (e.g. Gaut et al., 2011), we canconclude that current sensitivity to radiation at least in partreflects past sensitivity to mutagens in general.
Very few mutations are beneficial; most are slightly
deleterious or neutral (e.g. Lynch et al., 1999; Eyre-Walker &Keightley, 2007). If mutation rates are elevated in areas withhigh natural levels of background radiation, we should be
able to demonstrate fitness costs of radiation. For example, itis well known that mutations are the source of many cancers
and other diseases (e.g. Valko et al., 2004). It is also wellknown that cancer caused by radon shows enormous spatial
variability so that foci of such cancers are concentrated inareas with specific rock substrata (e.g. Lubin & Boice, 1997).
Are there effects of such natural variation in radiation on theincidence of diseases such as cancer, and hence intensity of
selection to repair mutations more efficiently?
If radiation at ‘natural’ levels can be shown to havenegative fitness consequences for plants and animals, eventhough such natural levels may be modest, there is a reason
to expect that higher doses due to nuclear accidents will haveeven larger negative fitness consequences. The flipside ofnegative fitness consequences is evolutionary adaptation toradiation. If organisms are exposed to the negative effects ofradiation for long periods of time, we could expect that someindividuals may become radio-tolerant, showing normal
or even enhanced survival and reproduction in the faceof radiation. If such variation in the ability to cope withradiation had a genetic basis, resistance to radiation would

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

228
be selected, even if such resistance was associated with aphysiological cost. The end point of evolutionary adaptation
to radiation is exploitation of radiation to the advantageof the individual. For example, several micro-fungi andbacteria associated with thermal vents and deserts are able
to live under extremely high radiation levels (e.g. Brooks& Murray, 1981; Suzuki et al., 1988; Jolivet et al., 2003,
2004; de Groot et al., 2005; Chanal et al., 2006; Shravage
et al., 2007; Charmasson et al., 2009; Daly, 2009). Several
micro-fungi from irradiated areas are directly attracted byradionuclides (positive radiotropism), being able to growupon ‘hot particles’ and even degrade them (Zhdanova et al.,2004). Furthermore, in some cases ionizing radiation has
a positive stimulatory effect on spore germination (Tugay
et al., 2006). Finally, exposure to ionizing radiation increases
the growth of some melanized fungi while simultaneouslytransferring electrons to melanin. This has led to speculationthat these redox properties might even be used to transduce
energy for cell metabolism, thereby enhancing growth(Dadachova et al., 2007; Dadachova & Casadevall, 2008).
A slightly different aspect of adaptation to radiation andacquisition of fitness benefits from radiation exposure ishormesis; the suggestion that organisms may benefit froman hypothesised stimulatory effect of low levels of radiationcompared to the absence of radiation (e.g. Planel et al., 1987;
Wolff, 1989). There is an extensive literature on this subject
in humans and other organisms [see reviews in Kondo(1993) and Luckey (1991)]. Mossman (2001) emphasizedthat the evidence is open to alternative interpretations:data purported to provide evidence for radiation hormetic
effects in humans are based on epidemiological findings
used to test different hypotheses; hormetic effects are weakat best and inconsistent; there is no consensus on how
these presumed benefits are defined or quantified; and it
remains unclear how hormesis can be classified between
the Scylla of beneficial health effects and the Charybdis
of requirements for protection of health. Here we suggestthat the documented consequences of naturally increased
levels of background radiation have important implications
for hormesis. In particular, we would expect that radiation
hormetic effects should be found in areas with higher levels ofnatural background radiation because of adaptation to suchenhanced levels of radiation, and we predict that on averageradiation should have positive effects on the wellbeing of
humans and other organisms if hormesis operates at naturally
occurring low-dose radiation.
The objectives of this review of the effects of naturalvariation in radiation levels on free-living organisms were
fourfold. (i) To review the effects of natural levels ofradiation on mutation rates, DNA repair, and other genetic
mechanisms. (ii) To review the evidence for the effects ofnatural levels of radiation on physiology, immunology anddisease frequency. If there is adaptation to local radiationlevels, then the relationship between radiation levels and themeasured effect might be weaker than expected based solely
on the direct effect of radiation on mutation rates (i.e. there
is a confounding variable of the extent to which mutations

Anders P. Møller and Timothy A. Mousseau
are repaired). (iii) To review the evidence for radiation
resistance to assess its prevalence in natural populations.
(iv) To review the extent to which natural variation inbackground radiation has positive hormetic effects on health,fecundity and longevity. We emphasize that we do not review
literature on the effects of radiation from nuclear accidents,
nuclear weapons tests, medical treatments, or similar humaninduced exposures, although such studies may prove usefulfor testing whether radio-resistant organisms predominate insuch contaminated sites and whether resistance can change
in response to altered background radiation levels.
The information that is derived from this quantitative
meta-analysis will help us to understand the role of radiationin the balance between mutation, selection and evolution, a
topic of general interest in the field of evolutionary genetics.
Information on radio-tolerance may help to focus future
research in an attempt to understand the role of radiationin contemporary ecological and evolutionary processes.
Finally, this review attempts to provide baseline information
concerning the potential consequences of nuclear accidents
like those at Chernobyl and Fukushima.

II. METHODS(1) Literature search
We conducted an extensive search for all scientific papers onnatural levels of radiation, radioactivity, radio-tolerance andradio-resistance, using the Web of Science and Google Scholar andthe key words ‘radiation’, ‘radioactivity’, ‘radio-tolerance’,‘radio-resistance’ and ‘high background radiation’ combinedwith ‘natural’. This was followed by subsequent searches forliterature concerning natural radioactivity and ‘mutation*’,‘physiology’, ‘immunology’ and ‘disease’. We also attempted
to find all papers that cited Grüneberg et al. (1966), GopalAyengar et al. (1970), Ahuja et al. (1973), Barcinski et al.
(1975), Kochupillai et al. (1976) and Pillai, Thangavelu& Ramalingaswami (1976), which are considered seminal
papers in this field. We searched all reference lists in the
resulting list of publications for further papers that could
include relevant information. The inclusion criteria for all
publications were that: (i) they compared at least one control
population with a low level of background radiation and one
population with high background radiation; (ii) they had test
statistics that could be converted into effect sizes; and (iii)they reported background radiation levels for both control
and irradiated populations. We examined more than 5000
papers to arrive at the 46 publications included in our metaanalysis. These publications had 373 effect sizes, or 8.1 effectsizes per publication. These were reduced to 66 effect sizes
because some of the 46 publications reported effects on morethan1 species. We excluded the extensive literature on radon
because this literature has already been reviewed elsewhere(e.g. Lubin & Boice, 1997; Hendry et al., 2009), and its volume
would swamp the fewer publications reviewed herein. We
located 56 publications on radio-tolerant and radio-resistant

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Evolution and natural variation in radioactivity
species within the initial 5000 papers. The cut-off date forinclusion of studies was 31 December 2011.
Because many of these papers were difficult to acquire
through ordinary libraries, we have made available a
directory containing copies of the papers used for thisreview of natural sources of radiation (http://cricket.
biol.sc.edu/papers/natural/).
(2) Extracting data
We extracted test statistics (t, F , c2 ) for all studies together
with information on the number of populations understudy (this was typically one high background radiation
area and one control area) and the number of individuals
studied. If no statistics were reported, we extracted means(S.E.M.) and conducted standard parametric tests forcomparison of means, or we extracted all data and conducted
regression analyses. If only a maximum probability value
was reported, we conservatively estimated the Pearson
correlation coefficient required for the given sample sizeto achieve the reported probability. If several effects werereported, we used the effect that controlled for confounding
variables such as age or smoking in order to be conservative.
In five studies included in the mean effect size calculations see
Table 2 we conservatively used the number of populations
rather than the number of subjects because the latter was notreported; in cases of cancer deaths (Körblein & Hoffmann,2006) use of the size of the underlying total population would
seriously distort our study findings towards the effect sizein those studies. Therefore, for these five studies we used
the number of populations to be conservative. Effect sizes
estimated in the present review therefore are conservative.
In total we obtained 373 effect-size estimates (Table 1).
For each effect we also extracted information on the trait
involved and classified these into the following categories:
disease; fecundity; immunology; morphology including dermatoglyphics; phenodeviants and developmental instability;
mutation and DNA repair; physiology; and sex ratio. For
each effect size we also extracted information on the meanlevel of background radiation and report these as mSv per
year in Table 1. We assumed that 1 R = 10 mSv (Körblein& Hoffmann, 2006
(3) Meta-analysis
The test statistics were first transformed into Pearson
product-moment correlation coefficients, using the equations
reported by Rosenthal (1991). These correlation coefficientswere then converted to z-transformed correlation coefficients(zr ) using Fisher’s transformation. Based on zr and the sample
size of the study, we calculated an effect size for each study
and category (see below) using MetaWin 2.1 for meta-analysis(Rosenberg, Adams & Gurevitch, 2000). Thus in a study
with 10 effect sizes for 5 species, we calculated 5 effect sizes
weighted by sample size using MetaWin as described below.
Likewise, if a study reported an effect size for disease andimmunology, we included mean and variance in effect sizefor these two categories in the analyses. We used MetaWin

229
to calculate the mean effect size across all studies using
an unstructured, random-effects model by using individual
effect sizes and weighting these by sample size, while using resampling tests with 10000 iterations to determine confidence
intervals for the mean effect size (Raudenbush, 1994). A
random-effects model accounts for the fact that both true
random components and sampling error affect effect sizes.
Because effects may differ among categories of study(disease, fecundity, immunology, morphology, mutation,
physiology, sex ratio), we conducted a random-effects
categorical meta-analysis to compare mean effects for thesecategories (Rosenberg et al., 2000).
We used mean effect size per study for each species
relying on sample size N for the species in the study. Thisis equivalent to setting r = 1 (i.e. assuming that effects are
not independent within a study) when calculating the meaneffect so that the variance is not overly reduced by inflating
N (Slatyer et al., 2011).
There was no a priori reason to expect that there would
be any publication bias in the literature because ‘negative’effects of radiation would be expected under the mutation
hypothesis, while ‘positive’ effects would be expected under
the hormesis hypothesis. We are unaware of any unpublishedstudies in this area despite having worked on biologicaleffects of radiation for more than 20 years. We conductedfour indirect tests of publication bias by estimating the
Kendall rank order correlation coefficient between effectsizes and their variances, between effect size and sample
size, and between effect size and year of publication (Begg& Mazumdar, 1994; Møller & Jennions, 2001; Jennions &Møller, 2002). Finally, we conducted a trim-and-fill test to
estimate the effect of the apparently ‘missing’ studies that
may have caused the asymmetry in effect size distributions(Duval & Tweedie, 2000a, b). We estimated the number of‘missing’ studies using the L o parameter in the ‘trim and fill’
method (Duval & Tweedie, 2000a, b), which assumes thata plot of effect size on sample size should be symmetric ifthere is no bias. We then re-calculated the mean effect after
adding values for putative ‘missing’ studies.
Effect sizes can be judged using Cohen’s (1988) rule ofthumb that effects can be considered small, medium orlarge based on the proportion of variance that they explain
in a sample (1, 9, or 25%, respectively). On average, theproportion of variance explained by main effects in metaanalyses in the biological sciences is only 5–10%, but for
many published studies it is much lower (Møller & Jennions,
2002).

III. RESULTS(1) Mean effect size and tests for publication bias
All effect sizes and their attributes are listed in Table 1; meaneffect sizes and their confidence intervals are given in Table 2.
Mean effect size across all studies was 0.093 (Fig. 1, Table 2;

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Plant

Plant

Plant

Plant

Plant

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalCalotropis gigantea

Crotalaria verrucosa

Crotalaria verrucosa

Croton bonplandianum

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Kingdom

Allium cepa

Species

Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea
Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea
Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea
Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea
Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea

Total number of breaks

Chromatid aberrations

Rings

Dicentrics

Deletions

Chromatid aberrations

Aneuploid cells

Cytological abnormalities

Pollen sterility

Cytological abnormalities

DNA damage assessed bycomet assay
Cytological abnormalities

EffectReferences

0

0

0

Morphology Ahuja et al. (1973)

Morphology Ahuja et al. (1973)

0

0

1

1

1

1

1

1

1

0

0

0

0

1

Morphology Ahuja et al. (1973)

Morphology Ahuja et al. (1973)

Saghirzadeh et al.
(2008)
Mutation Gopal-Ayengar
et al. (1970)
Mutation Gopal-Ayengar
et al. (1970)
Mutation Gopal-Ayengar
et al. (1970)
Mutation Gopal-Ayengar
et al. (1970)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)
Mutation Barcinski et al.
(1975)Morphology Ahuja et al. (1973)
Mutation

Category

1.580

−1

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

F

F

F

1

2.050

1.620

1.340

−1

1

1.220

1

1.450

−1
F

F

4.910

1.580

2.490

2.380

1

1

1

1

2.550

0.029

−1

1

0.124

0.488

0.894

0.255

0.936

1

1

1

1

1

t

t

t

t

t

t

t

r

r

r

r

r

Confounding
Value
variables
Test Direction of test
controlled statistic of effect statistic

Table 1. Effect sizes for studies of effects of natural levels of radiation on biological response variables

9

3

5

7

13

N

349

349

349

349

349

130

0.126

0.112

130

130

−0.102 1300.097−0.106 130

0.255

0.085

0.132

0.127

0.136

−0.085 349−0.002 349

0.124

0.488

0.894

0.255

0.936

r

2

2

2

2

2

2

2

2

2

2

2

2

9

3

5

7

13

32.98

32.98

32.98

32.98

32.98

6.40

6.40

6.40

6.40

6.40

6.40

6.40

82.96

82.96

82.96

82.96

87.60

RadiationNo.
level
populations (mSv/year)

230

Anders P. Møller and Timothy A. Mousseau

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Table 1. (Cont.)

Variance smaller for threeout of six dermatoglyphic
traits in contaminatedarea
Antioxidant levels reduced
Neutrophil activity
Phagocytosis
Locomotion of peripheral
neutrophils
Interleukine-2
Interleukine-4
Interleukine-10
Interferon-gamma
Proliferation
Whorls, loops and arches
Whorls, loops and arches
Whorls, loops and arches
Whorls, loops and arches
Finger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countEffectReferences

Immunology
Immunology
Immunology
Immunology
Immunology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Physiology
Immunology
Immunology
Immunology
Attar et al. (2007)
Attar et al. (2007)
Attar et al. (2007)
Attar et al. (2007)
Attar et al. (2007)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Attar et al. (2007)
Attar et al. (2007)
Attar et al. (2007)
Attar et al. (2007)

Morphology Ahuja et al. (1973)

Category

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

1
1
1
1

0

Confounding
variables
controlled

t
t
t
t
t
Chi-squareChi-squareChi-squareChi-square
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F

t
t
t
t

F

Test
statistic

1
1
1
−1
−1
1
1
1
1
1
−1
−1
1
1
−1
1
−1
−1
−1
−1
−1
1
−1
−1
1
1
1
1
1
1
1

1
1
1
1

−1

14.15024.19025.71011.110
2.670
3.315
4.304
12.818
0.480
0.576
1.526
1.017
0.681
1.748
1.051
0.816
1.530
1.069
1.023
1.100
1.085
0.993
1.317
2.137
0.724
0.714
0.461
0.576
0.714
0.643
0.484

27.99015.20020.34032.650

2.190

Value
Direction of testof effect statistic
N

0.819
0.925
0.933
−0.747−0.260
0.226
0.257
0.573
0.099
0.092
−0.149−0.1220.100
0.159−0.1240.110−0.149−0.125−0.123−0.131-0.1300.125−0.143−0.181
0.103
0.103
0.083
0.092
0.103
0.131
0.114

0.943
0.838
0.899
0.957
100
100
100
100
100
65
65
39
49
69
69
69
69
69
69
69
69
69
69
65
65
65
65
65
69
69
69
69
69
39
39

100
100
100
100

−0.130 130

r

4
4
4
4
4
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2

4
4
4
4

2

260.00260.00260.00260.00260.00
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52

260.00260.00260.00260.0032.98

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
231

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Table 1. (Cont.)

Finger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge countFinger ridge count
Main line formulae
Main line formulae
Main line formulae
Main line formulaeLine D distribution
Line D distribution
Line D distribution
Line D distribution
Hypothenar
Hypothenar
Hypothenar
Hypothenar
Thenar I
Thenar I
Thenar I
Thenar I
Thenar II
Thenar II
Thenar II
Thenar II
Thenar III
Thenar III
Thenar III
Thenar III

EffectMorphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Category
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

References
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Confounding
variables
controlled
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
Chi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-square

Test
statistic
1
−1
1
1
1
1
1
−1
−1
1
1
1
1
1
1
1
1
1
1
1
1
1
−1
−1
−1
1
−1
−1
−1
1
−1
−1
−1
−1
−1
−1
−1
−1
−1
−1
−1
−1

0.385
1.303
0.415
0.587
0.962
0.646
0.368
1.188
1.043
0.642
0.565
0.516
0.664
0.548
0.587
0.752
0.575
0.924
3.202
0.241
5.938
2.199
0.966
0.051
0.702
6.365
0.024
0.118
2.669
5.929
1.615
0.082
0.045
1.969
0.172
1.436
0.363
0.220
0.150
0.603
0.563
0.163

Value
Direction of testof effect statistic
0.101−0.184
0.105
0.125
0.159
0.131
0.099
−0.157−0.147
0.116
0.109
0.104
0.118
0.107
0.111
0.125
0.110
0.139
0.222
0.061
0.390
0.212
−0.122−0.028−0.1340.360−0.019−0.043−0.2620.348−0.158−0.036−0.034−0.200−0.051−0.149−0.096−0.067−0.048−0.096−0.120−0.058

r
39
39
39
39
39
39
39
49
49
49
49
49
49
49
49
49
49
49
65
65
39
49
65
65
39
49
65
65
39
49
65
65
39
49
65
65
39
49
65
65
39
49

N
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2

17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52

RadiationNo.
level
populations (mSv/year)

232

Anders P. Møller and Timothy A. Mousseau

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

Thenar IV
Thenar IV
Thenar IV
Thenar IV
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b

EffectBhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

References

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Morphology Bhasin et al. (1980)

Morphology Bhasin et al. (1980)

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

1

1

1
1
1
1
1
1

1

Morphology Bhasin et al. (1980)
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

1
1
1
1
1
1

1

1
1
1
1
1
1

1

1
1
1
1
1
1
1
1
1
1

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Category

Confounding
variables
controlled

F

F

F
F
F
F
F
F

F

F
F
F
F
F
F

F

F
F
F
F
F
F

F

Chi-squareChi-squareChi-squareChi-square
F
F
F
F
F
F

Test
statistic

1.201

−1

2.186
0.973
0.699
0.308
1.043
0.653

−1
−1
1
1
−1
−1

0.736

0.371

−1

1

0.874
1.613
0.965
0.511
0.396
0.497

1
−1
−1
1
1
−1

3.667

1.453
2.053
1.529
1.010
1.335
3.172

−1
−1
−1
1
−1
1
1

5.035

0.090
0.688
1.108
4.443
0.846
2.120
0.639
0.828
1.189
3.398

1

−1
−1
−1
1
1
−1
1
1
−1
1

Value
Direction of testof effect statistic

65−0.177 39

0.107

2

2

2
2
2
2
2
2

65
65
65
65
65
65

−0.183−0.1230.105
0.070−0.128−0.101

2
2
2
2
2
2

2

2
2
2
2
2
2

2

2
2
2
2
2
2
2
2
2
2

2

65
65
65
65
65
65

65

65
65
65
65
65
65

65

65
65
39
49
65
65
65
65
65
65

N

−0.077 65

0.117−0.158−0.1230.090
0.079−0.0880.235−0.150−0.178−0.1540.126−0.144
0.219

0.272

−0.037−0.103−0.1690.301
0.115−0.1800.100
0.114−0.136
0.226

r

17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52
17.52

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
233

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Table 1. (Cont.)

Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
Interdigital ridge count a-b
Interdigital ridge count b-c
Interdigital ridge count c-d
Interdigital ridge count a-d
Interdigital ridge count d-tInterdigital ridge countangle atd
Interdigital ridge countdistance c-t
SRBC right S1
SRBC right S2
SRBC right S3
SRBC right S4
SRBC right S5
SRBC left S1

EffectBhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

References

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)
Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology

Morphology Bhasin et al. (1980)

Morphology
Morphology
Morphology
Morphology
Morphology

Category

1
1
1
1
1
1

1

1
1
1
1
1
1

1

1
1
1
1
1
1

1

1
1
1
1
1
1

1

1
1
1
1
1

Confounding
variables
controlled

Chi-squareChi-squareChi-squareChi-squareChi-squareChi-square

F

F
F
F
F
F
F

F

F
F
F
F
F
F

F

F
F
F
F
F
F

F

F
F
F
F
F

Test
statistic

0.812
0.983
1.741
0.832
0.735
0.310
0.606
0.566
2.179
2.462
0.747
1.525
0.601
0.682
0.736
2.340
1.231
0.062
2.489
0.303
0.207

1
−1
−1
1
1
1
−1
−1
−1
−1
1
−1
1
−1
−1
−1
1
−1
1
−1
−1

0.361
1.378
1.311
1.073
0.300
0.437

0.353

−1
1
−1
−1
−1
1
1

1.327
0.651
1.027
0.132
1.305

−1
1
−1
1
1

Value
Direction of testof effect statistic−0.1900.134−0.031
0.196−0.068−0.056−0.124−0.210−0.2230.125−0.1770.112−0.120−0.109−0.143−0.189
0.132
0.124
0.081
−0.113

0.147

0.098
−0.189−0.185−0.1680.090
0.108−0.097−0.1860.131−0.164
0.060
0.185

r

130
130
130
130
130
130

49

49
49
49
49
49
49

49

49
49
49
49
49
49

39

39
39
39
39
39
39

39

39
39
39
39
39

N

2
2
2
2
2
2

2

2
2
2
2
2
2

2

2
2
2
2
2
2

2

2
2
2
2
2
2

2

2
2
2
2
2

15.00
15.00
15.00
15.00
15.00
15.00

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52
17.52

17.52

17.52
17.52
17.52
17.52
17.52

Radiationlevel
No.
populations (mSv/year)234

Anders P. Møller and Timothy A. Mousseau

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

SRBC left S2
SRBC Left S3
SRBC left S4
SRBC Left S5
DRBC right S1
DRBC right S2
DRBC right S3
DRBC right S4
DRBC right S5
DRBC left S1
DRBC left S2
DRBC left S3
DRBC left S4
DRBC left S5
DRBC right S6
DRBC left S6
TRBC right
TRBC left
Cancer rate
Lymphocyte chromosomal
aberrations dicentrics
and rings
Lymphocyte chromosomal
aberrations dicentrics
and rings
Lymphocyte chromosomal
aberrations translocations
and inversions
Lymphocyte chromosomal
aberrations translocations
and inversions
Lymphocyte chromosomal
aberrations dicentrics
and rings
Lymphocyte chromosomal
aberrations dicentrics
and rings
Lymphocyte chromosomal
aberrations translocations
and inversions

EffectMutation

Mutation

Mutation

Mutation

Mutation

Mutation

Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
Morphology
DiseaseMutation

Category

Chen & Wei (1991)

Chen & Wei (1991)

Chen & Wei (1991)

Chen & Wei (1991)

Chen & Wei (1991)

Chen & Wei (1991)

Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Bhasin et al. (1982)
Binu et al. (2005)
Chen & Wei (1991)

References

1

1

1

1

1

1

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Confounding
variables
controlled

1
1

t

1

1

1

1

−1
−1
1
1
−1
1
−1
−1
1
1
1
−1
−1
1
1
1
−1
−1
1
1

4.210

2.933

0.105

2.667

2.000

3.294

0.381
0.088
1.868
0.000
0.383
0.000
0.992
0.273
0.000
0.000
0.000
0.656
0.004
0.000
0.000
0.000
0.010
0.010
0.100
1.867

Value
Direction of testof effect statistic

t

t

t

t

t

Chi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-square
r
t

Test
statistic

0.279

0.227

0.007

0.176

0.137

0.216

−0.077−0.0370.170
0.000−0.1080.000−0.152−0.065
0.000
0.000
0.000
−0.050−0.008
0.000
0.000
0.000
−0.012−0.012
0.100
0.128

r

212

161

221

224

210

224

130
130
130
130
130
130
130
130
130
130
130
130
130
130
130
130
130
130
205
210

N

2

2

2

2

2

2

2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2

3.30

3.30

3.30

3.30

3.30

3.30

15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
15.00
82.96
3.30

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
235

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

Lymphocyte chromosomal
aberrations translocations
and inversions
Cancer mortality
Cancer mortality
Mitotic cell divisions
Mitotic cell divisions
Mitotic cell divisions
Unscheduled DNA
synthesis
Unscheduled DNA
synthesis
Unscheduled DNA
synthesis
Unscheduled DNA
synthesis
Chromosomal aberrations
dicentrics
Chromosomal aberrationstranslocations
Chromosomal aberrations
inversions
Chromosomal aberrations
centric fragments
Chromosomal aberrations
acentric fragments
Chromosomal aberrations
minutes
Chromosomal aberrations
multiple aberrations
Chromosomal aberrations
chromosome breaks
Chromosomal aberrations
chromosome gaps
Chromosomal aberrations
chromatid breaks
Chromosomal aberrations
chromatid gaps
Chromosomal aberrations
polyploids
Chromosomal aberrations
endoreplications

EffectReferences

Chen & Wei (1991)
Chen & Wei (1991)
Chen & Wei (1991)
Chen & Wei (1991)
Chen & Wei (1991)
Chen & Wei (1991)

Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)
Mutation Cheriyan et al.
(1999)

Mutation Chen & Wei (1991)

Mutation Chen & Wei (1991)

Mutation Chen & Wei (1991)

Disease
DiseaseMutation
Mutation
Mutation
Mutation

Mutation Chen & Wei (1991)

Category

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1
1
1
1
1
1

1

t

t

t

t

t

t

t

3.230

−1

0.820

2.000

−1

−1

3.430

−1

2.150

4.900

−1

1

2.200

0.000
1

1

4.060

−1
t
t

2.800

1.000

−1
1

1.250

0.056

−1
1

1.960

1.242

1

1

1.568

.—
.—
2.090
4.920
1.600
0.910

−1
−1
1
1
1
1
1

3.250

1

t

t

t

t

t

t

t

r
r
t
t
t
t

t

Confounding
Value
variables
Test Direction of test
controlled
statistic of effect statistic−0.0080.021−0.032−0.020−0.034−0.048

0.022

0.000

−0.0400.028−0.0100.012−0.001

0.359

0.203

0.324

0.000
0.001
0.135
0.359
0.140
0.133

0.219

r

10230

10230

10230

10230

10230

10230

10230

10230

10230

10230

10230

10230

10230

28

38

23

1035410968429
239
166
130
48

212

N

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2
2
2
2
2
2

2

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

3.30

3.30

3.30

3.30
3.30
3.30
3.30
3.30
3.30

3.30

RadiationNo.
level
populations (mSv/year)

236

Anders P. Møller and Timothy A. Mousseau

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalHomo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

AnimalHomo sapiens

Homo sapiens

AnimalHomo sapiens

AnimalAnimalHomo sapiens

Homo sapiens

Kingdom

Species

Table 1. (Cont.)

Telomere length
Mitochondrial DNA
mutationsSurface proteins
CD4+/CD69+ on T
helper cells unstimulated
Surface proteins
CD8+/CD69+ on T
helper cells unstimulated
Surface proteins
CD4+/CD69+ on T
helper cells stimulated
Surface proteins
CD8+/CD69+ on T
helper cells stimulated
Percentage stable cellaberrations
Percentage unstable cellaberrations
Chromosomal aberrations

Chromosomal aberrations
autosomal trisomies
Chromosomal aberrations
48 XXY + 21
Chromosomal aberrations
48 XXY + 21 + centric
fragments
Chromosomal aberrations
sex chromosomal
Chromosomal aberrations
deletions
Chromosomal aberrations
inversions
Chromosomal aberrations
Robertsoniantranslocations
Chromosomal aberrations
other translocations
Frequency of micronuclei

EffectCheriyan et al.
(1999)Das &Karuppasamy(2009)
Das et al. (2009)
Forster et al. (2002)

Cheriyan et al.
(1999)
Cheriyan et al.
(1999)
Cheriyan et al.
(1999)
Cheriyan et al.
(1999)

Cheriyan et al.
(1999)
Cheriyan et al.
(1999)
Cheriyan et al.
(1999)

References

Mutation

Mutation

Mutation

Hayata et al. (2000)

Ghiassi

Ghiassi

Immunology Ghiassi

Immunology Ghiassi

Immunology Ghiassi

Immunology Ghiassi-Nejad et al.
(2004)

Physiology
Mutation

Mutation

Mutation

Mutation

Mutation

Mutation

Mutation

Mutation

Mutation

Mutation

Category

1

1

1

1

1

1

1

1
1

1

1

1

1

1

1

1

1

1

Confounding
variables
controlled

0.880
8.983
1.020

−1
1
−1

r

t

t

t

t

t

t

1.762
0.100

−1

2.690

0.520

2.200

1

1

1

1

0.000

0.003

−1

t

1

0.140

−1

t

t
Chi-square

1.210

1

t

1.210

2.760

−1
1

1.310

0.180

−1
1

1.290

1.140

1

−1

Value
Direction of testof effect statistic

t

t

t

t

t

t

Test
statistic
N

16169

16169

16169

16169

0.100

0.196

0.291

0.059

0.242

0.000

−0.115−0.0500.097−0.004

17

80

80

80

80

80

80

310
795

271

−0.001 16169

0.010

0.010

−0.022 16169

0.010−0.001 16169

0.010−0.009 16169

r

2

2

2

2

2

2

2

2
2

2

2

2

2

2

2

2

2

2

3.12

13.00

13.00

13.00

13.00

13.00

13.00

4.00
11.00

4.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

35.00

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
237

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Number of micronuclei
before irradiation
No. micronuclei after
irradiation

Vitamin C in urine

Vitamin C in plasma

Induced DNA damage

Initial DNA damage

Child mortality

Cancer mortality

Severe mental retardation

Chromosome aberrations

Chromatid aberrations

Chromosomal aberrations
with fragments
Chromosomal aberrations
without fragments
Down’s syndrome

Female cancer rate

Male cancer rate

Stillbirths

Chromosomal aberrations
dicentric and ring
chromosomes
Chromosomal aberrations
Congenital malformations

EffectHayata et al. (2004)

References

Mutation

Mutation

Physiology

Physiology

Mutation

Mutation

Disease

Disease

DiseaseMutation

Mutation

DiseaseMutation
Kochupillai et al.
(1976)
Kochupillai et al.
(1976)
Kochupillai et al.
(1976)
Kochupillai et al.
(1976)
Körblein &Hoffmann(2006)
Körblein &Hoffmann(2006)
Masoomi et al.
(2006)
Masoomi et al.
(2006)
Masoomi et al.
(2006)
Masoomi et al.
(2006)
Mohammadi et al.
(2006)
Mohammadi et al.
(2006)

Jiang et al. (2000)

Mutation Hayata et al. (2004)
Morphology Jaikrishan et al.
(1999)
Mutation Jaikrishan et al.
(1999)
Disease
Jayalekshmi et al.
(2005)
Disease
Jayalekshmi et al.
(2005)
Mutation Jiang et al. (2000)

Mutation

Category

0

0

1

1

1

1

1

1

0

0

0

0

1

1

1

1

1

1
1

1

Confounding
variables
controlled

t

t

t

t

1.200
1.840
0.832
2.905

−1
−1
−1

128.40727.627

3.223

3.289

4.880

10.527

2.058

4.480

3.669

1

1

1

F
F

1

1

t
t

1

1

1

1

1

5.823

0.169

−1
1

0.022

1.040

5.182
0.349

0.410

1

1

1
1

1

Value
Direction of testof effect statistic

Chi-squareChi-squareChi-squareChi-square

F

F

r

r

Chi-squaret
Chi-squarerTeststatistic−0.502−0.164

0.046

0.020

0.802

0.529

0.315

0.321

0.613

0.498

0.220

0.870

0.297

0.365

0.169

0.022

0.008

0.544
0.004

0.410

r

27

27

73

73

73

73

96

96

13

85

85

12

40

40

179810179810

36805

66
36805

39

N

2

2

3

3

3

3

96

96

2

2

2

2

2

2

12

12

2

2
2

2

13.00

13.00

10.20

10.20

10.20

10.20

0.67

0.67

22.50

22.50

22.50

22.50

149.00149.00

1.72

1.72

2.84

3.11
2.84

3.11

RadiationNo.
level
populations (mSv/year)

238

Anders P. Møller and Timothy A. Mousseau

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalHomo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

AnimalHomo sapiens

Homo sapiens

AnimalHomo sapiens

AnimalAnimalHomo sapiens

Homo sapiens

Kingdom

Species

Table 1. (Cont.)

Chromosome aberrations
per cell
Chromosome aberrations
per cell after exposure to
1.5 GyChromosome aberrations
per cell
Chromosome aberrations
per cell after exposure to
2 Gy gamma rays
Chromosome aberrations
per cell
Chromosome aberrations
per cell after exposure to
1.5 GyCancer rates
Cancer rates women
Chromosomal and Down
syndrome
Autosomal dominantanomalies
De novo cases of autosomal
dominant anomalies
Autosomal and X-linked
recessives

Cancer rate

Cell apoptosis before
irradiation
Cell apoptosis after
irradiation
DNA damage before
irradiation
DNA damage after
irradiation
Residual DNA damage
after irradiation
Residual DNA damage
after irradiation
DNA repaired

EffectReferences

Disease Nair et al. (1999)
Disease Nair et al. (1999)
Mutation Padmanabhan
et al. (2004)
Mutation Padmanabhan
et al. (2004)
Mutation Padmanabhan
et al. (2004)
Mutation Padmanabhan
et al. (2004)

Mutation Mortazavi et al.
(2005)
Mutation Mortazavi et al.
(2005)

Mutation Mortazavi et al.
(2005)
Mutation Mortazavi et al.
(2005)

Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Mutation Mohammadi et al.
(2006)
Disease Monfared et al.
(2010)
Mutation Mortazavi &Karam (2005)
Mutation Mortazavi &Karam (2005)

Category

1

1

1

0
0
1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Confounding
variables
controlled

0.068
0.057
4.310

−1
−1
1

Chi-squareChi-squareChi-squarerr
Chi-square

1

1

9.096

0.940

6.270

9.213

−1
t

1

−0.194
0.625

−1

0.012

0.004

0.010

0.068
0.057
0.008

−0.94615.241 −0.919−1tt

16.667

0.931

0.676
1

5.273

0.288

−0.430

0.666

0.739

0.860

0.871

0.896

0.649

−0.132

r

t

1

t

1.725

0.430

−1
1

4.467

5.491

8.442

8.856

10.074

4.261

0.668

1

1

1

1

1

1

−1

Value
Direction of testof effect statistic

t

r

t

t

t

t

t

t

t

Test
statistic

62914

62914

62914

195962
198848
62914

12

12

45

45

35

35

184

27

27

27

27

27

27

27

N

2

2

2

2
2
2

2

2

2

2

2

2

184

2

2

2

2

2

2

2

5.63

5.63

5.63

2.03
2.03
5.63

1.36

1.36

1.36

1.36

13.00

13.00

0.53

13.00

13.00

13.00

13.00

13.00

13.00

13.00

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
239

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens

Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

Category

References

Morphology Padmanabhan
et al. (2004)
Multifactorial anomalies
Morphology Padmanabhan
et al. (2004)
All thyroid swellings
DiseasePillai et al. (1976)
All nodular swellings
DiseasePillai et al. (1976)
Uninodular swellings
DiseasePillai et al. (1976)
Number of copies of the sex Mutation Premi et al. (2009)
determining SRY gene
Gene expression of sex
Mutation Premi et al. (2009)
determining SRY gene
Number of micro-deletions
Mutation Premi et al. (2009)
DBY1 and DBY2 genes on
Mutation Premi et al. (2009)
the Y chromosome
Microdeletions
Mutation Premi et al. (2009)
Extra amplicons for parts of Mutation Premi et al. (2009)
their genomes
Gene duplication of Y
Mutation Premi et al. (2009)chromosome
Loss of Y chromosome
Mutation Premi et al. (2009)
Sex ratio
Sex ratio Saadat (2003)
Sex ratio
Sex ratio Saadat (2003)
Down’s syndrome
DiseaseSundaram (1977)
Down’s syndrome
DiseaseTao & Wei (1986)
T-lymphocyte count
Immunology Tao & Wei (1986)
Cell proliferation
Immunology Tao & Wei (1986)
Morphological
Immunology Tao & Wei (1986)
transformation rate oflymphocytes
31 hereditary diseases
DiseaseTao & Wei (1986)
B-lymphocyte count
Immunology Tao & Wei (1986)
Cancer rates
DiseaseTao et al. (2000)
Down’s syndrome
DiseaseThampi et al.
(2005)
Malformations
Mutation Thampi et al.
(2005)
Stillbirths
Mutation Thampi et al.
(2005)
Karyotype anomalies
Mutation Thampi et al.
(2005)

Congenital anomalies

EffectBiological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

1

1

1

1
1
1
1

1
1
0
1
1
1
1
1

1

1
1

1
1

1

0
0
0
1

1

1

Confounding
variables
controlledtChi-squareChi-squareChi-squarett
Chi-squareChi-squareChi-squareChi-squareChi-squareChi-squarettt

Chi-squareChi-squareChi-squareChi-squareChi-squarer

Chi-squareChi-squareChi-squarer

Chi-squareChi-square

Test
statistic

0.002
2.150
0.145
6.085
2.080
0.000
0.282

−1
−1
−1

15.550
0.950
0.130
2.800
2.821
0.129
1.661
3.835

643.246583.7901144.208

1052.971
227.780

0.526

0.128
2.777
0.128
0.579

7.010

0.600

Value
of teststatistic

1
1
−1
1

1
1
−1
1
1
1
1
1

1

1
1

1
1

1

1
−1
1
1

1

1

Directionof effect

470

1869

26512
166
393
632

1180
21857
261509
12
26512
168
168
592

1180

1180
1180

1180
1180

21

250
250
250
21

62914

62914

N

−0.002 23844−0.003−0.033

0.000
0.012
0.000
0.098

0.115
0.007
0.001
0.483
0.010
0.000
0.016
0.024

0.738

0.703
0.985

0.945
0.439

0.526

0.023
0.023
0.001
0.579

0.011

0.003

r

2

2

2

2
2
2
2

3
2
2
2
2
2
2
2

3

3
3

3
3

2

2
2
2
2

2

2

82.96

82.96

82.96

3.36
3.36
6.40
82.96

2.03
13.00
13.00
22.50
3.36
3.36
3.36
3.36

2.03

2.03
2.03

2.03
2.03

9.00

15.00
15.00
15.00
2.03

5.63

5.63

RadiationNo.
level
populations (mSv/year)

240

Anders P. Møller and Timothy A. Mousseau

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Table 1. (Cont.)

Oesophagus cancer as acause of death
Stomach cancer as a causeof death
Larynx cancer as a cause ofdeath
Lung cancer as a cause of
death
Female breast cancer as acause of death

Oesophagus cancer as acause of death
Stomach cancer as a causeof death
Larynx cancer as a cause ofdeath
Lung cancer as a cause of
death
Female breast cancer as acause of death
Prostrate cancer as a causeof death
Leukaemia as a cause of
death
Cancer as a cause of deathAge-adjusted liver cancer
incidence linear model
for menStandardized mortality
ratio of leukemia for men
Stomach cancer mortality
in male population aged
more than 40 years
Age-adjusted liver cancer
incidence exponential
model for men
Standardized mortality ratioof leukemia for womenCancer as a cause of death

EffectDisease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

DiseaseCategory

Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)

Ujeno (1983)

Ujeno (1983)

Ujeno (1983)

Ujeno (1983)

Ujeno (1983)

References

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

1

1

1

1

Confounding
variables
controlled

t

t

t

t

t

t

t

t

t

t

t

t

t

t

r

1.524
0.091
1.372
1.156

−1
−1
−1
−1

1

1

3.155

2.660

0.761

3.121

−1
1

2.541

10.045

0.000

1

1

1

1.206

2.119

−1

1

0.000

0.110

0.694

1

1

1

r

0.802

0.211

−1
1

0.659

Value
of teststatistic

1

Directionof effect

r

r

r

Test
statistic

0.340

0.245

0.172

78

113

21

133

32

−0.421
0.263

1122

19

35

23

37

9

42

17

479

46

13

649

46

13

N

0.287

0.000

0.205

−0.245−0.226−0.034−0.234−0.480

0.000

0.110

0.694

0.802

−0.211

0.659

r

2

2

2

2

2

2

2

2

2

2

2

2

2

2

46

13

649

46

13

No.
populations

3.40

3.40

3.40

3.40

3.40

3.40

2.40

2.40

2.40

2.40

2.40

2.40

2.40

2.40

1.05

1.05

1.05

1.05

1.05

Radiation
level(mSv/year)

Evolution and natural variation in radioactivity
241

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Kingdom

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Homo sapiens
Homo sapiens

Table 1. (Cont.)

Oesophagus cancer as acause of death
Stomach cancer as a causeof death
Larynx cancer as a cause ofdeath
Lung cancer as a cause of
death
Female breast cancer as acause of death
Prostrate cancer as a causeof death
Leukaemia as a cause of
death
Other abnormalities
All nodular disease
Thyroxine-free serum (T4)
Tiiodo-thryroxine-freeserum (T3)
Anti-mitochondrial
antibody serum (AMA)
Urinary iodine-creatinine
Urinary iodine
Translocations
Inversions
Deletions
Unstable chromosomal
aberrations
Prevalence of 31 hereditarydiseases
Cancer mortality
Down’s syndrome
Down’s syndrome
Nodular disease

Prostrate cancer as a causeof death
Leukaemia as a cause of
death
Cancer as a cause of death

EffectBiological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Disease
Disease
Disease
Disease

Disease

Disease
DiseaseMutation
Mutation
Mutation
Mutation

Disease

Disease
Disease
Disease
Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

Disease

DiseaseCategory

Wei et al. (1990)
Wei et al. (1990)
Wei et al. (1990)
Wei et al. (1990)

Wei et al. (1990)

Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)

Wang et al. (1990)

Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Veiga & Koifman(2005)
Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)
Wang et al. (1990)

References

1
1
1
1

1

1
1
1
1
1
1

1

1
1
1
1

0

0

0

0

0

0

0

0

0

0

Confounding
variables
controlledrChi-squareChi-squareChi-squareChi-square

t
t
t
t
t
t

t

t
t
t
t

t

t

t

t

t

t

t

t

t

t

Test
statistic

2.053
1.325
0.417
0.400

−1
1
−1
1

0.002
0.002
2.820
5.624
0.017

−1
1
1
1

6.842
3.231
0.571
0.800
2.800
3.333
1

1
−1
1
1
1
1

0.600

0.035

−1

1

2.971

0.762

2.814

0.104

3.468

2.100

1.764

2.117

1.089

1

1

1

1

1

1

1

1

1

Value
Direction of testof effect statistic

0.002
0.010
0.011
0.003

0.000

0.380
−0.191
0.041
0.057
0.195
0.230

0.026

−0.0460.030−0.0180.017−0.008

0.401

0.148

0.309

0.039

0.347

0.315

0.081

0.295

0.145

r

632280
26572
47095
2006

26572

279
279
200
200
200
200

550

2006
2006
550
550

19

48

28

77

9

90

42

468

49

57

N

2
2
2
2

2

2
2
2
2
2
2

2

2
2
2
2

2

2

2

2

2

2

2

2

2

2

3.37
3.37
3.37
3.37

3.37

3.30
3.30
3.30
3.30
3.30
3.30

3.30

3.30
3.30
3.30
3.30

6.40

6.40

6.40

6.40

6.40

6.40

6.40

6.40

3.40

3.40

RadiationNo.
level
populations (mSv/year)

242

Anders P. Møller and Timothy A. Mousseau

Kingdom

AnimalAnimalAnimalAnimal
Plant

Plant

Plant

Plant

Plant

Plant

Plant

Plant

AnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalAnimalSpecies

Homo sapiens

Homo sapiens

Homo sapiens
Homo sapiens
Ipomoea pes-caprae

Ipomoea pes-caprae

Launaea pinnatifida

Launaea pinnatifida

Lochnera rosea

Lochnera rosea

Lochnera rosea

Lochnera rosea

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Rattus rattus

Table 1. (Cont.)

Disease
DiseaseMutation

Mutation

Mutation

Category

Zhang et al. (2004)

Zhang et al. (2003)

References

Zou et al. (2005)
Zou et al. (2005)
Gopal-Ayengar
et al. (1970)
Pollen sterility
Mutation Gopal-Ayengar
et al. (1970)
Cytological abnormalities
Mutation Gopal-Ayengar
et al. (1970)
Pollen sterility
Mutation Gopal-Ayengar
et al. (1970)
Cytological abnormalities
Mutation Gopal-Ayengar
et al. (1970)
Cytological abnormalities
Mutation Gopal-Ayengar
et al. (1970)
Cytological abnormalities
Mutation Gopal-Ayengar
et al. (1970)
Pollen sterility
Mutation Gopal-Ayengar
et al. (1970)
Standardized variance inMorphology Grüneberg et al.
tooth measurements(1966)
Mean skeletal character
Morphology Grüneberg et al.
(1966)
value
Variance in skeletal
Morphology Grüneberg et al.
character values(1966)
Fossa olecrani perforata
Morphology Grüneberg et al.
(1966)
Foramen hypoglossi double Morphology Grüneberg et al.
(1966)
Maxillary foramen double Morphology Grüneberg et al.
(1966)
Metoptic roots abnormal
Morphology Grüneberg et al.
(1966)
Pregancy rate
Fecundity Grüneberg et al.
(1966)
Dead embryos
Mutation Grüneberg et al.
(1966)
Pre-implantation loss
Mutation Grüneberg et al.
(1966)

Chromosomaltranslocations
Chromosomaltranslocations
Cancer rates
Non-cancer mortality
Cytological abnormalities

Effect

1

1

1

1

1

1

1

1

1

1

0

0

0

0

0

0

0

1
1
0

1

1

Confounding
variables
controlled

0.612 −0.021
38.494 −0.212
19.926 −0.153

−1
−1
−1

Chi-squareChi-squareChi-squareChi-squareChi-squareChi-squareChi-square

t

1.997

1

t

74.558 −0.295

−1

0.025

0.018 −0.007
1.258 −0.064

1
−1
−1

0.007

0.600

1

0.026

0.068

0.159 −0.005

−1

0.538

0.896

0.749

0.934

0.751

0.983

0.414

t

0.896

52

40

N

307

399

469

855

855

855

855

855

855

855

11

11

11

11

5

5

6

0.000 1202
0.020 10038
0.751
6

0.330

0.010

0.538

1

0.749

0.934

0.751

0.983

0.414

0.000
1.960
0.751

6.117

0.004

r

1

r

r

1

1

r
r

1

1

1

1
1
1

1

1

Value
Direction of testof effect statistic

r

r

r

t
t
r

F

F

Test
statistic

16

16

16

16

16

16

16

16

16

16

11

11

11

11

5

5

6

2
2
6

2

2

8.53

8.53

8.53

8.53

8.53

8.53

8.53

8.53

8.53

8.53

82.96

82.96

49.06

49.06

82.96

82.96

82.96

6.37
6.37
82.96

2.71

2.75

RadiationNo.
level
populations (mSv/year)

Evolution and natural variation in radioactivity
243

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

AnimalAnimalAnimal

Plant

Plant

Plant

Plant

Plant

Plant

Plant

Plant
AnimalRattus rattus

Rattus rattus

Rattus rattus

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.

Tradescantia sp.
Tyto alba

Stamen hair mutations
Intensity of pheomelanincolour

Stamen hair mutations

Stamen hair mutations

Stamen hair mutations

Stamen hair mutations

Stamen hair mutations

Stamen hair mutations

Stamen hair mutations

Standardized variance intooth measurements
females
Metoptic roots abnormal

Post-implantation loss

EffectReferences

Morphology Grüneberg et al.
(1966)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation de Azevedo Gomes
et al. (2002)
Mutation Nayar et al. (1970)
Physiology Galván &Alonso-Alvarez(2011)

Grüneberg et al.
(1966)Morphology Grüneberg et al.
(1966)
Mutation

Category

1
0

1

1

1

1

1

1

1

1

1

1

Confounding
variables
controlled

r
t

t

t

t

t

t

t

t

1
1

1

1

1

1

1

1

0.784
2.250

0.772

3.587

3.277

1.434

2.661

1.692

4.004

0.721

−1
1

0.718

−1

t
t

0.001

1

Value
Direction of testof effect statistic

Chi-square

Test
statistic
372

N

0.784
0.030

0.300

0.826

0.801

0.505

0.736

0.568

0.853

4
376

20

20

20

20

20

20

20

−0.025 855−0.025 855

0.002

r

2
18

2

2

2

2

2

2

2

16

16

16

95.09
1.40

526.00263.00215.66110.46

52.60

31.56

7.89

8.53

8.53

8.53

RadiationNo.
level
populations (mSv/year)

Confounding variables controlled: 0 – no, 1- yes; direction of effect: −1 implies decrease with increasing radiation level, 1 implies increase with increasing radiation level; r, Pearson r;
N , sample size. Note that radiation levels are estimates based on maximum dose rates.

Kingdom

Species

Table 1. (Cont.)

244

Anders P. Møller and Timothy A. Mousseau

Evolution and natural variation in radioactivity
bootstrap 95% CI = 0.039–0.171, N = 66 effects from 46
studies). Therefore, natural background radiation accounted
for 0.9% of the variance. Variation in individual effect sizes
was larger than expected from sampling error (Q T = 952.41,
d.f. = 65, P < 0.0001). We did find significant evidence of
publication bias when analyzing the relationship between
effect size and year of publication in a regression weighted bysample size [F = 20.457, d.f. = 1,64, P < 0.0001, slope (S.E.)= 0.0035 (0.0008)], and we did find a significant correlation
between standardized effect size estimates and their variance(r bias = 0.441, N = 66, P < 0.0001) and study sample size
(r bias = 0.446, N = 66, P < 0.0001). A funnel plot of the 66
effect sizes indicated asymmetry in distribution of effect sizes(Fig. 2A). There was similar asymmetry if the funnel plot was
restricted to studies of animals, mutational effects or disease
effects (Fig. 2B–D). A trim and fill analysis indicated that
there were 11 missing studies (according to the L o estimator= 11.25), and estimated mean effect size after inclusion ofthese 11 studies revealed a mean effect size across all studiesof 0.014 (P = 0.0012, bootstrap 95% CI = 0.006–0.022).
There was a weakly increasing effect size with year of
publication [slope (S.E.) = 0.0038 (0.0008), P < 0.0001,
bootstrap 95% CI = 0.038–0.167], with a heterogeneous
difference among studies (Q T = 25.09, d.f. = 1, P < 0.0001),
suggesting that more recent studies showed stronger effects.
However, the difference in predicted effect size across the46 years of publication only accounted for an increase ineffect size by 0.17, and the positive relationship is contrary to
expectations based on publication bias (Jennions & Møller,
2002).
(2) Effect size and explanatory variables
There was a significant difference in effect size between
studies of animals (which were nearly exclusively humans)and plants, with mean weighted effect for plants being almost
an order of magnitude greater than that for studies of animals(Table 2).
When effects were categorized with respect to predictor
variables, we found a significant difference in effect size
among categories (Table 2). Mean effect size was large
for immunology, decreasing to intermediate in studies ofphysiology and small in studies of mutation, disease andmorphology (Table 2). When only considering studies of
disease, there was no significant heterogeneity between
studies of cancer and studies of other types of disease, withboth effects being small (Table 2).
Because effect sizes for plants only consisted of studies ofmutation, we also compared plant and animal studies only
based on mutations. In this case mean effect size for plants
remained 0.749 (bootstrap 95% CI = 0.570–0.878), while it
was 0.017 (bootstrap 95% CI = 0.019–0.053) for animals; anon-significant difference (Q T = 1.72, d.f. = 1, P = 0.18).
We found no significant evidence of study quality as
estimated from effects being controlled for potentiallyconfounding variables affecting mean effect sizes (Table 2).
There was large overlap in confidence intervals between

245
studies that controlled or did not control for potentiallyconfounding variables.
A test for the importance of the number of study
populations as a basis for the individual studies suggested
no significant weighted effect [slope (S.E.) = −0.0009(0.0216), P = 0.97, bootstrap 95% CI = 0.035–0.161],
with a heterogeneous difference among studies (Q T = 0.002,
d.f. = 1, P = 0.97), suggesting no clear effects of replicationlevel.
Finally, we tested if the level of radiation predicted
mean weighted effect size as expected if radiation was theunderlying factor. There was a significant positive effect[slope (S.E.) = 0.0583 (0.0170), P = 0.0006, bootstrap 95%
CI = 0.038–0.167], with a heterogeneous difference amongstudies (Q T = 11.71, d.f. = 1, P < 0.0001), suggestingthat higher levels of radiation were associated with stronger
effects.

(3) Variation in radiation resistance among natural
populations
There are numerous examples of differences in radioresistance among strains, lines or populations since thefirst studies on Drosophila melanogaster by Strømnæs (1955)(Table 3). Evidence for strain differences in radio-sensitivity
has been replicated for fruitflies Drosophila melanogasterand domestic mice Mus musculus by different laboratories(Table 3).
We are only aware of a single negative result: Varanda,
Takahashi & Soares (1985) were unable to show radioresistance in Melittobia hawaiiensis exposed to high levels of
gamma radiation for many generations. Many studies haveshown that selection in the laboratory for radio-resistance iseffective (e.g. Wallace, 1952). We do not discuss such studies
further here.
By far the largest majority of studies showing radiotolerance or radio-resistance are concerned with bacteria(Table 3). Deinococcus deserti were able to survive levels ofradiation up to 15000 Gy (de Groot et al., 2005). Daly(2009) showed that manganese-based protein complexes
could provide protection to DNA repair machinery thus
permitting survival at very high radiation levels. Fungi
constitute the other major group showing extreme radiotolerance, even growing within the sarcophagus at Chernobyl(Zhdanova et al., 2000). Experimental studies have shown
hyphal growth directed towards radiation sources (Zhdanova
et al., 2004).
Some metazoan bdelloid rotifers (Gladyshev & Meselson,2008) and tardigrades (Horikawa et al., 2006) show an ability
to survive high radiation doses, although this is accompaniedby sterility. Drosophila spp., silkworm Bombyx mori and mouse
Mus musculus show differences in resistance to radiation,although tolerance levels are many orders of magnitude
lower than in bacteria and fungi (Table 3).

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Anders P. Møller and Timothy A. Mousseau

246

Table 2. Mean effect sizes weighted by sample size, their confidence intervals, number of studies, heterogeneity (Q T ) among studies(global test) or among categories, degrees of freedom (d.f.) for the heterogeneity test and probability (P) for this heterogeneity test fordifferent groupings of the data set listed in Table 1

Category
All studies
Animals
PlantsImmunology
Physiology
Mutation
DiseaseMorphology
CancerOther diseases
Confounding variables not controlled
Confounding variables controlled

Mean effect size

Bootstrap 95%
confidence interval

No. studies

QT

d.f.

P

0.093
0.089
0.749
0.451
0.278
0.177
0.054
−0.005
0.057
0.026
0.056
0.098

0.039, 0.171
0.071, 0.108
0.570, 0.878
0.018, 0.750−0.029, 0.767
0.059, 0.376
0.004, 0.124−0.049, 0.006−0.017, 0.158
0.010, 0.063−0.079, 0.199
0.041, 0.184

66
57
9
3
4
31
19
6
11
8
17
49

952.41
39.45
—
70.86
—
—
—
—
1.49
—
2.08
—

65
1
—
4
—
—
—
—
1
—
1
—

<0.0001<0.0001—<0.0001
—
—
—
—
0.22
—
0.15
—

Fig. 1. Plot of the 66 effect size estimates of the relationship between level of natural background radiation and biological response
variables, ordered by increasing effect size. Effect sizes are z-transformed Pearson product-moment correlation coefficient estimates(Z r ), shown here with 95% confidence intervals. Vertical line indicates overall mean effect size of 0.093.

IV. DISCUSSION
The objectives of this review were to examine the effectsof radiation on DNA, health, and radiation resistance,
and to investigate evidence for the presence of hormesis(positive effects of radiation). We found extensive evidence ofsmall, but significant negative effects of natural variation inbackground radiation on immunology, mutation and diseaseacross a range of different species of animals and plants. Thissignificant effect was robust to indirect tests for effects ofpublication bias as provided by the trim and fill procedure(Duval & Tweedie, 2000a, b). The effects for plants weremuch stronger than for animals, and studies conducted at
higher natural radiation levels showed stronger effect sizes.
Numerous studies have shown evidence of radio-resistance,
mainly in bacteria and fungi, but also in Metazoa including

fruitflies and mice; the extent of this radio-resistance differs
among taxa.
The studies reviewed herein generally had a design thatcompared one or more control populations with a ‘normal’level of background radiation with one or more populations
that had a ‘high’ level of background radiation. More than
75% of all effect sizes consisted of comparisons of one
control and one high-radiation population. If effects wereentirely due to chance alone, we should expect equally
many ‘positive’ and ‘negative’ effect sizes, with an expected
mean of zero, which was clearly not the case. An explicit
test for effects of level of replication showed no significant
confounding effects. Typically the level of radiation in
the high-radiation population was an order of magnitude
above the level in the control population. Because such
population comparisons are correlational in nature, they
may be confounded by uncontrolled third variables. As

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Evolution and natural variation in radioactivity

247

(A)

(C)

(B)

(D)

Fig. 2. Funnel plots of z-transformed effect size in relation to log10 -transformed sample size for (A) all 66 effect sizes, (B) animalstudies, (C) mutation studies and (D) disease studies.

a case in point, one of the first studies of the effects ofhigh background radiation in Kerala, India, by Kochupillai
et al. (1976) was subsequently criticised for not having
properly controlled the incidence of Down’s syndrome fordifferences in age of mothers in the control populationand the high-radiation-level population (Sundaram, 1977).
However, subsequent studies of the incidence of Down’s
syndrome in Kerala corrected for such confounding effects,
and studies in other areas also have confirmed the initialobservation. Subsequent studies have carefully tested andcontrolled study design for the confounding effects of age, sex,ethnicity, religion, consanguinity, smoking, unemployment
rate and other factors. In fact, most studies of humans inhigh-radiation areas are characterized by extreme ethnic
homogeneity because populations have been living in the
study area for many generations. A case in point is the studyof effects of radiation in the Guangdong Province in Southern
China, where the study populations consist of homogeneous
Han Chinese that have lived in the region for many centuries(Wang et al., 1990). Many studies report effects before andafter statistical control for confounding variables, and we
consistently used such robust effect sizes in this review. Whentesting for a difference in mean effect size between more andless rigorous studies, we found no significant difference.
The distribution of effect sizes in relation to sample size
is usually assumed to be funnel-shaped with larger variancearound the true mean effect size at smaller sample sizes(the so-called funnel plot) (Light & Pillemer, 1984; Begg,
1994). Asymmetric plots may be due to publication bias,
heterogeneity in effect sizes or other factors (e.g. Egger et al.,
1997; Thornhill, Møller & Gangestad, 1999). We foundevidence of asymmetric funnel plots (Fig. 2), but also showedthat elimination of such asymmetry by adoption of the ‘trim

and fill’ procedure (Duval & Tweedie, 2000a, b) did not
eliminate an overall significant mean effect size.
Radiation causes mutations even at the modest levels ofnatural radiation. There is extensive evidence for naturallyhigh levels of radiation being associated with increased rates
of genetic damage, including mutations. This effect was the
predominant finding in most studies, showing a small, buthighly significant effect size (Tables 1 and 2). In other words,
effects of natural radiation are reported at a much higher
frequency than would be expected by chance alone. Thisimplies that natural radiation effects like those reported here
are frequent and significant. The magnitude of the overall
effect was ‘only’ small, accounting for less than 1% of thevariance. However, in an evolutionary context even a small
effect may have large consequences when considered acrossthe large number of generations of evolutionary time scales.
It is important to notice that we found a mean differencein effect size of almost an order of magnitude between
animals and plants, suggesting that the sessile habits of plants
subject them to chronic radiation. However, the differencein effect size for mutations between animals and plants was
not statistically significant, although the difference in meaneffects was large, probably due to low statistical power.
More studies are required to assess this effect. In addition,
reduced levels of migration in plants compared to mammals
should result in greater levels of local adaptation in plants.
Indeed, recent studies of DNA repair and gene expressionin plants in Chernobyl seem to be consistent with suchan interpretation (Boubriak et al., 2008; Danchenko et al.,2009; Klubicová et al., 2010). Despite this expectation we
still found stronger negative effects of radiation on plants
than on animals. Therefore, we can conclude that there iscurrent selection for local adaptation in plants to cope with

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Anders P. Møller and Timothy A. Mousseau

248

Table 3. Studies of genetic variation in radiation tolerance and resistance in different taxa
Species

Evidence

Comments

References

Hyphal growth directed towards
radioactive source. Threeother taxa fromuncontaminated areas showedno similar directed growth
Melanized genera predominant
inside the containment
structure of the Chernobyl
Nuclear Power Plant
Melanized genera predominant
after 1986, but not before, andonly in contaminated areas
around Chernobyl

No distinction between β- andγ -radiation

Zhdanova et al. (2004)

Could partly be an effect of reduced
interspecific competition from
non-melanized fungi

Zhdanova et al. (2000)

Could partly be an effect of reduced
interspecific competition from
non-melanized fungi

Zhdanova et al. (1994)

Resistance to γ -radiation

Maximum of 1.7 megarad

Saleh et al. (1988)

Resistance to γ -radiation
Resistance to γ -radiation—
Maximum of 6000 Gy

Kimura et al. (2006)
Holliday (1971) and Leaper
et al. (1980)

Resistance to γ -radiation source

4000 Gy

Billi et al. (2000)

Two radio-resistant lociidentified
Resistance to high γ -radiation
sourceResistance to γ -radiation source
Resistance to γ -radiation source—

Greenberg (1964a, b)

Soil populations more resistant thanlaboratory populations
Mechanisms unknown
1000 Gy

Vela & Wyss (1965)

Resistance to γ -radiation source

2000 Gy

Acinetobacter radioresistens
Kineococcus radiotolerans
Thermococcus
gammatolerans
Thermococcus marinus
Thermococcus stetteri
Rubrobacter radiotolerans

Resistance to γ -radiation source
Resistance to γ -radiation source
Resistance to γ -radiation source

2000 Gy
2000 Gy—

Resistance to γ -radiation source
Resistance to γ -radiation source
Resistance to γ -radiation source—>1000 Gy
Resistance to 11000 Gy

Rubrobacter xylanophilus
Desulfurococcus
amyloliticus
Deinococcus radiodurans

Resistance to γ -radiation source
Resistance to γ -radiation source

Resistance to 5500 Gy> 2500 Gy

Resistance to γ -radiation source

10000 Gy

Deinococcus deserti
Deinococcus radiopugnans
Deinococcus proteolyticus
Deinococcus radiophilus
Deinococcus geothermalis
Deinococcus murrayi
Deinococcus
Deinobacter grandis
Cryptococcus neoformans
Histoplasma capsulatum
Pyrococcus abyssi
Pyrococcus furiosus

Resistance to γ -radiation source
Extremely efficient DNA repair
Extremely efficient DNA repair
Extremely efficient DNA repair
Resistance to γ -radiation
Resistance to γ -radiation
Nine new species—
Resistance to γ -radiation source
Resistance to γ -radiation source
Resistance to γ -radiation source
Resistance to high γ -radiation
sourceGeodermatophilus sp.
Hymenobacter actinosclerus

Resistance to γ -radiation source
Resistance to γ -radiation source

15000 Gy
1500 rad1500 rad1500 rad7300 Gy
3700 Gy
Resistance to 30000 Gy—
Resistance to 4000 Gy
Resistance to 4000 Gy
Maximum of 2500 Gy
Chromosome fully restored
following fragmentation caused
by 2500 Gy
Resistance to 30000 Gy
Resistance to 3500 Gy

Fungi:
Penicillium hirsutum, P.
lanosum, P. westlingii,
Cladosporium
cladosporiodes
19 genera of fungi

Stachybotrys, Ulocladium,
Preussia, Plenodomus,
Humicola,
Aureobasidium,
Alternaria
Curvularia geniculatan
Alternaria alternata
Saccharamysis cerevisiae
Ustilago maydis
Cyanobacteria:
Chroococcidiopsis spp.
Bacteria:
Escherichia coli
Azotobacter
Bacillus subtilis
Methylobacterium
radiotolerans
Locurio rosea

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Setlow (2006)
Ito & Iizuka (1971) andGreen & Bousfield (1983)
Rainey et al. (1997) and
Brooks & Murray (1981)
Nishimura et al. (1994)
Phillips et al. (2002)
Jolivet et al. (2003, 2004)
Jolivet et al. (2004)
Kopylov et al. (1993)
Suzuki et al. (1988) andFerreira et al. (1999)
Ferreira et al. (1999)
Kopylov et al. (1993)
Brooks & Murray (1981) and
Ito et al. (1983)
De Groot et al. (2005)
Minton (1994)
Minton (1994)
Minton (1994)
Ferreira et al. (1997)
Ferreira et al. (1997)
Rainey et al. (2005)
Minton (1994)
Dadachova et al. (2004)
Dadachova et al. (2004)
Gérard et al. (2001)
DiRuggiero et al. (1997)
Rainey et al. (2005)
Collins et al. (2000)

Evolution and natural variation in radioactivity

249

Table 3. (Cont.)
Species

Evidence

Comments

References

Hymenobacter sp.
Metazoa:
Caenorhabditis elegans

Resistance to γ -radiation source

Resistance to 30000 Gy

Rainey et al. (2005)

Resistance to irradiation, but
subsequently sterile
Resistance to irradiation, but
subsequently sterile

Resistance to 5000 Gy

Johnson & Hartman (1988)

Survives 1120 Gy, which is muchhigher than in a
desiccation-intolerant rotifer
Resistance up to 6200 Gy in
hydrated animals and 5200 Gy in
anhydrobiotic animals. Survival
dose-dependent, but sterility
complete above 1000 Gy—

Gladyshev & Meselson (2008)

Bdelloid rotifers Adineta
vaga and Philodina
roseolaMilnesium tardigradum

Drosophila melanogaster

Drosophila melanogaster
Drosophila melanogaster

Drosophila nebulosa

Drosophila willistoni

Bombyx mori
Bombyx moriMus musculus
Mus musculus
Mus musculus

Resistance to γ -radiation sourceand heavy ionsDifferences between two strains
in maturation rates andmutation frequency linked toradiation
Differences in radio-resistanceamong three strains due todominant effects
Mortality analysis of iso-femalelines showed significant strain
and strain-by-dose effects.
Additive differences from a 4
× 4 diallelic cross, but low
dominance andinter-chromosomal interaction
effects
Mortality and reproductive
performance differed among
iso-female lines, and dialleliccrosses showed evidence ofadditive differences
Egg eclosion and reproductive
performance differedsignificantly among areas
ranging from 0.05 to 3.5
mR/h
Differences among lines
Differences among lines
LD50 was affected by a recessive
genetic factor
Difference among strains in
number of offspring andduration of the fertile period
Variance in sensitivity is additive
with a heritability of 0.55

Horikawa et al. (2006)

Strømnæs (1955, 1959)—

Ogaki & Nakashima-Tanaka(1966)

90000 and 110000 rads γ -radiation

Parsons et al. (1969)

90000 radKratz (1975)

1000 rad

Cordeiro et al. (1973)———

Tazima (1957)
Murakami & Tazima (1966)
Kohn & Kalman (1956)—

Ehling (1964)—

Grahn (1958)

LD50 is the dose at which 50% of the individuals have died.

elevated levels of background radiation. Forster et al. (2002)
showed that human mutation rates in naturally radioactive
areas were seven times higher than in control regions, ata background radiation level ten times higher than theworldwide average. This is a typical level of radiation in
so-called high-level radiation areas across the world, and thislevel of radiation is typically what is reported in the studies
reviewed here (Table 1). In addition, Forster et al. (2002)
showed that mutations were strongly aggregated at specificlocations on the chromosomes that have had an evolutionary

history of high mutation rates. This observation provides
evidence that these radiation-associated point mutations
are associated with a radiation-induced increase in thecell’s normal mutation mechanisms or a decrease in repair
mechanisms at these particular sites (Dubrova et al., 1997).
Chronic exposure to radiation is associated with significant
costs in terms of health. Here we have shown evidence ofsignificant negative effects on immunology, mutation anddisease frequency in a large number of studies (Tables 1
and 2). The observed high frequency of negative effects

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

250
is very unlikely to reflect random chance. The findings
reviewed here include reduced levels of antioxidants,
weakened immune responses and elevated frequencies of
disease including cancer. Antioxidant levels are typicallysuppressed in irradiated individuals as commonly reported
from radiation accidents (e.g. Yablokov, Nesterenko &Nesterenko, 2009). Attar, Kondolousy & Khansari (2007)
showed a similar effect on a number of different measures of
immunity in humans in Iran exposed to elevated backgroundradiation levels. This implies that elevated incidence ofdisease in contaminated areas may be caused by effectsof radiation on the immune system rather than being a
consequence of increased mutation rates directly causing
disease. Three epidemiological studies link cancer to elevatedlevels of background radiation, even after controlling forpotentially confounding variables (Ujeno, 1983; Tao et al.,
2000; Körblein & Hoffmann, 2006). These findings about
disease incidence and natural variation in backgroundradiation have implications for studies of the effects ofradiation accidents such as Chernobyl, Fukushima Daiichi
and Three Mile Island. Given that natural levels of radiation
typically are much lower than those reported for areas
subjected to radiation accidents we can predict that thesignificant effects reported here for natural radiation will beeven stronger in areas that are accidentally contaminatedwith high levels of radiation.
There is extensive evidence of radiation-resistance inbacteria and fungi, but also in higher organisms such as
Caenorhabditis elegans, bdelloid rotifers, tardigrades, insects andmice (Table 3). Some of these results, such as the tardigrades,
can be explained by an absence of replicating cells after
birth. While bacteria and fungi can survive exposure toeven 15000 Gy, sustainable levels for Metazoa are much
lower. However, it remains interesting that there is significant
variation in radio-resistance even in mammals. Our review
showed clear evidence of interspecific differences in resistanceto radiation. Resistance to ionizing radiation in Dinococcus
radiodurans and bdelloid rotifers appears to be derived fromtheir desiccation resistance (Mattimore & Battista, 1996;
Gladyshev & Meselson, 2008). A recent study showed thatbacterial biofilms resistant to desiccation and ultraviolet
radiation are pre-adapted to cope with ionizing radiationfrom Chernobyl (Ragon et al., 2011), apparently because thesame underlying mechanisms are responsible for resistancein both cases. In Deinococcus radiodurans there seems to havebeen an accumulation of genes involved in resistance toradiation that allowed it to cope successfully with different
kinds of environmental stresses (or vice versa) compared toa closely related radio-susceptible bacterium (Omelchenko
et al., 2005). Even large amounts of DNA damage in D.
radiodurans can be repaired without leaving any obvious
trace of mutations through homologous recombination, useof single-strand DNA for recombination, regulated DNA
replication, and export of damaged nucleotides from the cellfor mutation avoidance (Battista et al., 1999; Cox & Battista,2005).

Anders P. Møller and Timothy A. Mousseau
The underlying mechanisms responsible for radiation
resistance were originally thought to be efficient DNA repair;the current focus has switched towards mechanisms of repair
of DNA damage caused by reactive oxygen species. Bothdesiccation and irradiation result in oxidative stress (França,Panek & Eleutherio, 2007). High levels of reactive oxidative
species cause damage to DNA and proteins that require
correction through repair (Minton, 1994, 1996; DiRuggiero
et al., 1997; Battista et al., 1999). Daly et al. (2004) showedthat Deinococcus radiodurans and other radio-resistant bacteria
differ from non-radio-resistant species in their level ofaccumulation of intracellular manganese and low levels ofiron; melanin may play a similar role in fungi (Dadachova
et al., 2007 and trehalose in cyanobacteria (Shirkey et al.,2003). In experimental settings manganese seems to facilitate
recovery from radiation injury. When manganese combineswith ligands, the resulting products can act as powerfulscavengers of free radicals arising as a consequence ofionizing radiation (Daly, 2009). Because such bacterial cells
rely on homologous recombination for rejoining doublestrand breakage of DNA, the presence of multiple copiesof the genome in combination with antioxidant protection
would allow cells to survive even with multiple double-strand
breakages. It is interesting that it appears that protection
mechanisms against reactive oxygen species rather thanDNA repair as such is the basis for radio-resistance in bacteriasuch as Deinococcus radiodurans. Differences among bacterial
taxa in their level of radio-resistance appear to be related tothe importance of manganese in such antioxidant defence(Daly, 2009). Thus, it is probably not a coincidence thatinterspecific differences in the ability to survive the impact ofradiation at Chernobyl are associated with ecological factors
closely linked to antioxidant status (Møller & Mousseau,
2007). The antioxidant status of individuals (Bonisoli-Alquati
et al., 2010), and the amount of pheomelanic plumage in birds(Galván, Mousseau & Møller, 2011) predicts the ability tosustain radiation, apparently due to the action of the powerfulantioxidant glutathione. The effects of low-dose radiation
reported here emphasise a significant role of oxidative stressat even very low levels of natural background radiation. We
hypothesise that limited availability of antioxidants and theassociated physiological problems in terms of reduced ability
to repair damage to DNA and other molecules may accountfor such effects.
Hormesis is defined as a beneficial effect of normal
background radiation on life-history traits such as fecundity
and longevity compared to levels achieved in the complete
absence of radiation (reviews in Kondo, 1993; Luckey, 1991).
If hormetic effects of radiation on fitness exist, we should
expect that the optimal level of radiation should increase
with background radiation level. If hormesis has evolved
as a consequence of local adaptation to specific levels ofradiation, we might even find that all populations should
perform best at some local level of radiation; exceeding
their performance in the absence of radiation. The latter
scenario would suggest that fitness should be independentof level of natural background radiation. In either case,

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society

Evolution and natural variation in radioactivity
we should not expect to find increased mutation rates,
impaired immune function, increased incidence of disease
and increased mortality in areas with higher levels of normal
background radiation. Our findings are clearly inconsistent
with a general role for hormesis in adaptation to elevatedlevels of natural background radiation. We note that someeffect sizes reported herein were negative, thereby deviatingfrom this expectation. However, these effects were of alevel that would be expected by chance, inconsistent withexpectations for a hormesis hypothesis.
In conclusion, reported rates of mutation caused by naturalvariation in radiation levels are almost exclusively restricted
to studies of humans with only a few studies on otherspecies available. Information on physiology, immunology
and disease associated with radiation again are restricted
almost exclusively to studies of humans. Note, however,that there is no evidence of radio-tolerance or radioresistance in humans, and there are still no studies of disease
and mutation rates in species in which radio-tolerance
or radio-resistance has been documented. The present
review provides evidence for interspecific variation in radiotolerance and radio-resistance in a large number of taxa,
suggesting that there has been selection for and evolution ofsuch characteristics. The scarcity of studies on mutations anddisease in organisms other than humans clearly should be
addressed.

V. CONCLUSIONS(1) We reviewed the literature on responses to naturalvariation in background radiation. There was evidence of asignificant, but small effect of natural variation in backgroundradiation on mutation rates, DNA damage and DNA repair.
(2) There were significant effects of natural variation inbackground radiation on immunology and disease including
cancer.
(3) The findings reported here are inconsistent witha general role of hormesis from low levels of natural
background radiation.
(4) There was strong evidence for the existence of radioresistance in different taxa, with differences among taxa
recorded in a variety of studies.
(5) These findings concerning the relationship between
natural variation in background radiation and various
biological response variables have important implications
for assessment of the biological effects of radiation accidents.
(6) Future studies should address the underlying
mechanisms accounting for interspecific differences insusceptibility to radiation.

VI. ACKNOWLEDGEMENTS
P. Lopez helped with references S. Randic, M. D. Jennions
and two anonymous referees provided helpful suggestions
for the meta-analysis.

251
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(Received 6 February 2012; revised 26 September 2012; accepted 5 October 2012; published online 8 November 2012)

Biological Reviews 88 (2013) 226–254 © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society