Geographic
Patterns of Haplogroup R1b in the British Isles
Kevin D. Campbell
Abstract
The recent availability of Y-STR databases has provided the
opportunity to further explore geographic and subclade patterns of Haplogroup
R1b in the British Isles. However, works
based upon this data leave gaps in the published analyses that make it
difficult to link conclusions to the supporting data. This paper identifies haplotypes in the Oxford Genetic Atlas Project data and
links these to Bryan Sykes’ book, Blood of the Isles. The analysis provides support for Sykes’
conclusions and posits the genetic signatures for the Dal Riada Celts and Picts
identified in Sykes’ book.
Address for correspondence: [email protected]
Received: January 1, 2007; accepted:
April 27,
2007.
Introduction
While DNA testing has evolved rapidly,
there is a dearth of reliable Y-STR DNA data for serious analysis. This absence is particularly surprising given
the heavy concentration of the R1b haplogroup in Western Europe and the bias of certain key
databases such as YSearch, SMGF, and FTDNA toward
participants from North America and Western Europe.
The lack of reliable data can be
attributed to a number of causes. These
include: inconsistent use of markers and nomenclature, cost involved with
extensive panels of markers, and a number of other issues that are familiar to
most academic and amateur genetic researchers.
However, it is suggested that there are two root causes that have
significantly hindered population analysis – (1) the lack of uniformly
collected, independently verified data sets and (2) the tendency of researchers
to shield and obfuscate
their analysis.
The major factor contributing to
the first is the nature of the submission process at the largest databases,
which results in non-validated and unsubstantiated data. The sad truth is that many of this field’s
largest databases rely on data and geographic inputs provided by enthusiastic,
but uninformed individuals. While
transcription and upload errors for YSearch and SMGF may be very low, many
errors creep in related to marker translation and geographic speculation. Though some might dismiss marker translation
as insignificant, errors in geographic data are not. In fact the essence of population analysis is
the deduction and inferences that can be made about how the Y-STR data relates
to specific geographic areas or population migrations.
As an example, in the Campbell project 73% of the participants
(123 out of 169) do not have a reliable paper trail that places their genetic
ancestor in either Scotland or Ireland. Of those that do, 39% have a
paper trail or some level of confidence that their ancestors came from Ireland and 61% believe that their
ancestors came from Scotland.
Given that the majority of Campbell participants can only reliably
document the birth location of their oldest proven ancestor to the 18th
and 19th centuries,
it is also likely that even much of the Ireland/Scotland split is further
confused by the Scotch-Irish migrations of that period. In short, it is suggested that much of the
location data provided by DNA participants to the large voluntary databases is, at
best, of marginal reliability when performing large population genetic studies.
The aforementioned statistics call
into question the reliability of information provided by individual
participants and suggests that possible organized and structured data gathering
studies might provide better sources of data.
However, some respected researchers have published popular texts with
new theories while providing insufficient information or omitting critical
linkages that might facilitate a formal and critical review.
For example, though Capelli’s
study of Britain has been published for several
years (Capelli et al, 2003), only recently has the underlying data been made
available. While EthnoAncestry
has introduced a DNA test for “Pictishness” they have not yet published any
details regarding their analyses.
Though Bryan Sykes has made the
data available that he used in his recent popular book “Blood of the Isles”, he
also leaves out critical linkages between the particular haplotypes and
conclusions that he draws in the text.
This is particularly frustrating since while the haplogroups in his
study are reasonably distinguishable, the assertions and theories that he makes
about specific subclades are not easily reviewed in the context of the
supporting data. The present article
will fill in some of this missing information.
Similarly, most people would
consider the recent book, The Origins of the British, by Stephen
Oppenheimer’s (2006) to be an authoritative work in this rapidly evolving
field. While a substantial portion of
Oppenheimer’s Y-STR study also uses the Capelli data, he assigns new haplotype
labels to the data – “16 distinct types
of R1b” -- without ever providing the detail necessary to link his
haplotypes to the underlying data. As is
the case with Sykes’s work, this makes any real academic or juried review of
his conclusions impossible and lessens the usefulness of his work to other
researchers. In some cases like the
aforementioned Pict test, researchers have been quick to partner with testing
companies to make money from their private theories.
The purpose of this paper is to
take a look at the underlying Sykes R1b data and see if it can be linked to his
founder haplotypes and the conclusions of his analysis. The goal of this paper is to attempt to
provide additional insights to the work of these researchers to make it more
useful to the individual genetic genealogist who look to their data as a link
to the past.
Methods
This study focuses on Haplogroup
R1b, which comprises the vast majority of the British Isles.
R1b data was extracted from the targeted data set and two types on
analysis were done to identify patterns – affinity analysis and network
analysis. Network analysis was performed
using the Fluxus Engineering’s phylogenetic network analysis software (Network
4.201). For the affinity analysis of
haplotypes, an Excel spreadsheet was developed to look at patterns and
anomalies of the data. An algorithm was
developed that took as input the 10 marker values of the haplotype signature
and then compared this against the overall distribution of that haplotype in
the full database. A sequential summary
of the method is as follows:
- Code Sykes’ Oxford Genetic Atlas Project (OGAP) data
by haplogroup.
- Separate the data into haplogroups and limit the
analysis to R1b only.
- Group similar R1b haplotypes.
- Look for geographic patterns or anomalies in the
distribution of major individual haplotypes.
- Review the data “in the large” to see if individual
patterns can be explained in a larger context and against Sykes’ published
conclusions.
Results
Step 1 - Coding of the OGAP Data
For data collection, Oxford
Genetic Atlas Project (OGAP) data was downloaded from Bran Sykes web site and
converted from PDF to Microsoft Excel format.
2,322 samples were then coded by haplogroup using Whit Athey’s improved Bayesian haplogroup
calculator (Athey 2005, 2006).
Hereafter, “OGAP” will refer to the R1b subset of Sykes’s data.
Sykes included the following
description of the data in the supplementary data file:
Y-chromosome DNA
(yDNA) - Samples collected early in
OGAP were amplified across the following seven markers: DYS 19, DYS 389i,
DYS389ii, DYS 390, DYS 391, DYS 392, DYS 393 using conditions described by de
Knijff et al (International Journal of Legal Medicine, 110: 134-140, 1997).
Later samples were typed for these and three additional markers: DYS 388, DYS
425 and DYS 426, using the two-stage multiplex conditions described by Thomas
et al. (Human Genetics, 105: 577-581, 1999). Alleles are reported as the number
of repeat units. For reasons of continuity within OGAP, DYS 389i is reported as
three repeats lower than the allele size produced by the ABI 3100. DYS 398ii-i
reports the difference between 389i and 389ii, the reason being that the repeat
size at 389ii is not independent of 389i whereas the difference between them
is. Although Y-chromosomes were assigned to clades, largely by RFLP [Author
- restriction fragment length polymorphism] analysis, these
assignments are not reported here as they do not necessarily correspond to the
SNP-based system recommended by the Chromosome Consortium (Genome Research
12:339-348, 2002).
Geographical
distribution - Genetic data are assigned to
geographical regions based on the birthplace/residence of the paternal
grandfather. This was done to minimize the effect of very recent migration. The
regional boundaries are shown on a map which precedes the Prologue in Blood of
the Isles. These data are copyrighted
and must not be reproduced without permission. Other formats and additional
details may be available for academic collaborations.
Several things are worth noting
about the data. First, the Sykes data
only uses 10 markers (DYS19, DYS389i, DYS389ii, DYS390, DYS391, DYS392, DYS393,
DYS388, DYS425 and DYS426). In addition,
only approximately 64% of the data are complete with 36% of the data missing
four markers, DYS439, DYS388, DYS425 and DYS426. While the missing markers appear to be a
serious shortcoming, 94% of all the DYS425 and DYS439 markers and 73% and 74%
of the DYS426 and DYS388 markers in Sykes full data set, respectively, have a
value of 12. This means that these markers do not have
sufficient spread and variability and are, in general, of limited use in
discriminating between haplotype patterns within this set of data.
Another interesting fact is the
haplogroup distribution of the data. Due
to lack of haplogroup designations in the original data, Athey’s haplogroup
calculator was used as a proxy to classify each haplotype. With several haplotypes being removed because
of missing data, Table 1 shows a comparison of the results of the
haplogroup calculator with Sykes published “Clans.”
In this table, percentages shown
in the middle column reflect the output of Athey’s calculator while the
percentages in the far right column correspond to the breakdown published by
Sykes in Appendix C of his book.
It is clear from this comparison
that Athey’s calculator appears to classify the data in similar proportions as
Sykes Clans and thus one may infer the underlying meaning of Sykes’ clan
nomenclature.
In addition, it is
important to note that Syke’s Clan categorizations were not based primarily on
single nucleotide polymorphism (SNP) testing.
As stated in the italicized quote above, “Y-chromosomes were assigned to clades, largely by RFLP analysis, these
assignments are not reported here as they do not necessarily correspond to the
SNP-based system recommended by the Chromosome Consortium.”
Finally, one should understand the
regional borders that Sykes uses in his study.
Since the purpose of this analysis is to draw geographic inferences, we
are limited in our insight by the definition of the geographic areas from which
the data is collected. Figure 1 shows
the regional borders that are coded in the OGAP data.
Table 1. Calculated Haplogroups vs. Sykes Clans
Step 2 – Extracting R1b (Oisin) Data
The 1625 haplotypes identified as
R1b in the previous step were extracted from the data set. These included all of the R1b haplotypes
shown in Sykes Table 1, plus those for Ireland.
It is also interesting to note that when only R1b is considered, the
frequency of markers DYS426, DYS388, DYS439 and DYS425 with a value of 12 rises to
97% in this subset of the database. This
further reinforces the notion that these markers (or the lack of them) are not
critical to the analysis of this set of data.
Figure
1. Regional Borders Used in the OGAP
Analysis to Classify Individuals
The first thing that was done to
better understand the data was to identify modal haplotypes for each region as
a descriptive view of the R1b data set.
However, examination of the modal haplotypes for the individual regions
was not informative because all regions and the full data set matched the
standard Atlantic Modal Haplotype.
A view of the R1b data in the form
of a connected graph – as shown in Figure 2 – shows a high degree of
“cubism.” By this I mean a high degree
of nodal interconnectivity among the data points that results in opposite
vertices “washing out” differences in the data.
Clearly, data analysis based upon
unique combinations of markers (i.e. haplotypes) instead of individual markers
would be necessary.
Figure
2. Network Analysis of the Top Twenty
R1b Haplotypes
Step 3 – Analysis of Haplotypes
Since descriptive statistics
tended to “average out” differences in the data, other methods were needed to
identify patterns and analyze the data.
To do this the most common haplotypes were identified and two methods of
analysis were performed. Appendix A
shows the haplotypes in the OGAP data.
The OGAP haplotypes roughly follow the frequency distribution of YSearch
and in McEwan’s (2007) groups if one takes into account that the OGAP data is
light on Irish samples in comparison with these other sources.
The OGAP designations in this
table were assigned sequentially in decreasing frequency of occurrence. The OGAP numbers from this table will be
referenced throughout the remainder of this report.
Two types of analysis were
conducted to identify patterns – affinity analysis and network analysis.
For affinity analysis of the
haplotypes, an Excel spreadsheet was developed to look for patterns and
anomalies in the data. An algorithm was
created that took as an input the 10 marker values for a haplotype or signature
to be reviewed and then compared that haplotype to the R1b subset of the
database. The algorithm calculated the
genetic distance and reported back the number of perfect (i.e., zero distance)
matches by OGAP region. To account for
the differing level of sampling in each region (e.g., small for Ireland and large for Northern England), the resulting number of matches
was normalized to frequencies in each region.
Table 2. Example of Identifying
OGAP8 Affinities
For example, haplotype OGAP8 which
is generally considered the quintessential Irish haplotype has 34 perfect
matches in the database. Because Ireland was not extensively sampled, the
OGAP database has twice as many hits for Grampian as for Ireland. However, when we adjust the
Grampian and Ireland percentages for the nearly six
times greater sampling of Grampian, we see that the greatest geographic
affinity for the OGAP8 haplotype is Ireland.
This calculation is shown in Table 2 above. The OGAP8 results with decreasing presence in
Ireland, Argyll, and the Hebrides also corresponds with what is
generally understood to be the geographic distribution of this haplotype.
This analysis was repeated for the
top 20 haplotypes in the OGAP data.
These haplotypes, which cover 60% of all OGAP samples, appear sufficient
to identify major regional affinities. Analysis of additional haplotypes would
be increasingly subject to sampling error.
The results of the analysis of the
top 20 haplotypes are shown in Table 3.
It should be noted that in this table negative values were removed to
reduce the clutter and significant geographic anomalies were color coded to aid
in identifying tendencies. Finally,
especially interesting results were boxed to help in latter discussion in this
paper.
License was also taken in the
reordering of rows and columns of the table in an attempt to group similar
haplotypes and close regions. While such
analysis is called “affinity analysis” and can be conducted mathe-matically,
this analysis was done manually to better allow for subjective considerations
of the data.
The second type of analysis that
was performed was network analysis. This
analysis which is common in the genetic sciences was conducted using the Fluxus
Networking program version 4.2.0.0. Figure
3 shows the results of the network analysis for the top twenty OGAP
haplotypes.
It should be noted in Figure 3
that nodes have been relocated and line length changed for increased
readability. Nodes have also been
colored to reflect the regional affinities identified in Table 3.
Conclusions
Analysis of the Oxford Genetic
Atlas Project data has yielded interesting results. The combination of the geographic affinity
results shown in Table 3 and the network analysis results shown in Figure 3 are
synthesized in Figure 4. In this
graphic, key haplotypes with strong regional affinities were placed in their
rough geographic perspective. No attempt
was made to force every haplotype somewhere on the map as it is obvious that at
this level of analysis, some haplotypes are pervasive and ubiquitous and not
easily generalized to a single geographic region.
Table 3 – Haplotype Affinity by
OGAP Region
Once located, haplotypes that
differed by a single mutation were connected with lines. Figure 4 reflects the general
interconnectivity resulting from the network analysis of Figure 3. The lines in Figure 4 should be
thought of as one possible path of migrations – not necessarily the only
path. The interconnections shown in Figure
4 are not based on any individual mutation rates. The interconnections shown in Figure 4
are based upon the occurrence of mutations, the principle of parsimony, and the
general south-to-north flow of R1b discussed by Sykes and Oppenheimer. Parsimony, in this case, reflects the
generally acknowledged flow from higher concentrations of haplotypes to lower,
more diffused concentrations.
Figure 4. Geographic Patterns of R1b in the British Isles
Some of the observations and
conclusions of this analysis are as follows.
1. The methodology clearly identified and quantified
what has been previous called the Irish subclade. Whether called the Irish Modal Haplotype or
the “Ui Neill haplotype” as in the Trinity College paper,
the North-West Irish Haplotype by David Wilson and fellow researchers,
or R1bSTR19Irish as defined by McEwan (2007),
this corresponds to OGAP8 in the Oxford data. In addition, this analysis also identifies
the strong migration of OGAP8 to the Argyll area. This migration may be explained by the Dal
Riada migration
or as Sykes notes “Ar-gael was coined by
the kings of Dal Riada for their three colonies – Mull, Islay, and Kintyre peninsula.”
On page 217 he continues, “There
has certainly been a substantial settlement at some time from Ireland in the recent past and the Irish infiltration into the west of Scotland is almost certainly the signal of the relocation of the Dal Riada
from Ulster to Argyll in the first millennium.”
2. Similarly OGAP10 which shares the DYS390=25 allele is clearly
identified as an Irish haplotype. This
haplotype also shows up strongly in the Hebrides which supports Sykes and
Oppenheimer’s general conclusion of a Mesolithic northern migration along the
coast of Ireland.
3. Interestingly, OGAP5 is a very
prevalent haplotype that also shows up predominately in Ireland.
What is interesting is that this haplotype has DYS390=24 instead of the generally
accepted value of 25. This haplotype,
which has only one difference from the AMH modal (DYS389-1 = 14) may be a transitional
haplotype.
4. OGAP19 is interesting in that it
shows an extreme correlation with both Ireland and the Scottish Highlands.
Because of the low sampling of Irish participants, it is best to be
cautious about drawing strong conclusions concerning Irish population genetics
but clearly OGAP8, OGAP10, and OGAP19 show the strong ties that are shared by Ireland and the Highland area of Scotland.
It is the migration of these haplotypes westward during the first
millennium that make the Scottish to Irish migration in the 1700s so difficult
to isolate genetically. Specifically
Sykes writes, “There is a basic
similarity between Irish and Pictish Y Chromosomes which, incidentally, makes
it almost impossible to detect any genetic effect of the Ulster Plantations.”
5. OGAP4 is particularly
intriguing. It is ubiquitous across all
areas of Scotland and exceptionally strong in
Grampian, Tayside, and Strathclyde. If we
discount the Irish influx in Argyll and the Hebrides, it is also among the strongest
haplotypes present in these regions. It would not be too much of a stretch to
label OGAP4 the quintessential Scottish haplotype and the single closest
identifier to whatever is considered the indigenous Scottish population. Sykes and Oppenheimer both write that the
Picts were as close as anything to the indigenous population of Scotland. Sykes states on page 217,
6. OGAP6 is prominent in Argyll and
the Hebrides.
It is also probable that OGAP6 is what Sykes was referring to when on
page 209 of his book he writes, “The
Argyll Y Chromosomes were much more like their Hebridean counterparts than
those in the Highlands … Argyll Y chromosomes are in between the Irish and the
Pictish values… Argyll has a low gene-sharing score with Grampian, even after
the Norse component has been subtracted.”
The first part of this statement can be observed by looking at the
affinities for OGAP6. The second part of
the statement further reinforces the notion that OGAP4 represents Pictishness
since the OGAP6 (Argyll) is a connection of OGAP4 to the Irish constellation in
Figure 3.
7. OGAP9 and OGAP11 both show an
affinity for both the Northern Isles and the Borders regions. This affinity is distinctive, but the author
is unqualified to venture a theory that might explain this geographic
discontinuity.
8. OGAP13 and OGAP17 both show a
clear affinity for Northern England.
9. OGAP14, OGAP16, and OGAP20 all
show a common regional affinity. Though
their presence in Tayside is very slightly higher than in Central England, the author believes that they
are probably better categorized as English rather than Scottish. It is theorized that this signature probably
migrated northward along the east coast of England, but the author is at a loss as
to why there isn’t a greater presence of these haplotypes in the Borders, Northumbria, and Northern England.
Perhaps more historically astute researchers might provide a theory.
10. OGAP7 seems to be most prevalent
in Southern
England. OGAP12 has a stronger presence on the Borders
area, but similar to the comment above, it is speculated that this may have
been a northward migration but again the author can’t explain the apparent
geographical jump.
11. The core haplotypes for the full British Isles are OGAP1, OGAP2, and OGAP3. By their nature these haplotypes are
considered oldest and progenitors of the British R1b lines. This means that these haplotypes by their
very nature should be, and are, much diffused.
OGAP1 has a slight predisposition to Scotland and has its greatest
concentration in Wales. OGAP2 has a slight affinity for Ireland, and OGAP3 has a slight affinity
for Southern
England. It is unclear if much more can be said about
these haplotypes but with them one might see the original immigrants to the
Isles and their possible paths along the western and eastern coasts.
12. Wales is interesting. Sykes on page 239 makes the statement that Wales has the lowest diversity of R1b
variety than anywhere else in the Isles.
However this analysis shows that Wales has no predominant haplotype and
a relatively even distribution of other haplotypes used in this analysis.
13. Like Wales, the Isle of Man is at a similar crossroads. However, rather than the diversity of Wales, the Isle of Man shows a strong presence of three
haplotypes. Looking at the geographic
context of Figure 4, it can be seen that the Isle of Man was populated by OGAP10 eastward
from Ireland and westward by OGAP13 from
northern England and OGAP16 from central England.
Summary
Through the analysis of Sykes’
OGAP data, this study has provided a means linking DNA results to haplotypes
and conclusions in Sykes’ book, “Blood of the Isles.” The study has confirmed Sykes’ interpretation
of the data, and hopefully, provided a means for other researchers to further
validate and extend his work. The study
both confirmed some subclades identified by Sykes as well as identified some
new subclades worthy of further research.
Key subclades that the study posits and which are defined by Sykes
include those of the Picts and the Dal Riada Celts.
Picts –
It is asserted that OGAP4 best represents the Pictish ancestry of Scotland.
While there is no fundamental genetic difference between the Picts and
the Celts, i.e., both being R1b, they are both from the same mixture of Iberian
and European Mesolithic ancestry that forms the Pictish/Celtic substructure of
the Isles.
Dal Riada Celts – When considered in a narrow genetic sense, the Gaels of Ireland, as
identified by the DNA signature of OGAP8, are as close as any group to being
considered the root line and forbearers of Celts of today. When present in Scotland, it is suggested that OGAP8
represents the signature of the Dal Riada Celts. However, more generally, it should be clearly
noted that the term Celtic has taken on a near mystical meaning and now more
commonly refers to cultural, linguistic and regional patterns that have
superseded any genetic definition. Sykes
says it best when he states. “Overall,
the genetic structure of the Isles is stubbornly Celtic, if we by that mean
descent from people who were here before the Romans and who spoke the Celtic
language. We are an ancient people
…genetically rooted in the Celtic past.
The Irish, the Welsh, and the Scots know this, but the English sometimes
think otherwise.”
Several interesting clusters were
identified that show geographic affinities but discontinuities. Scotish clusters OGAP9 and OGAP11 have a strong
presence in the Borders as well as the Northern Isles. English clusters OGAP14, OGAP16, and OGAP20
show a predisposition to both Central England as well as Tayside. These and other geographic affinities warrant
further research.
Electronic Database Information
Capelli, C. et al. 2003 Data Set: http://freepages.genealogy.rootsweb.com/~gallgaedhil/Capelli.htm
Oxford Genetic Atlas Project (OGAP) Data
Set:
http://www.bloodoftheisles.net/results.html
John
McEwan’s R1b Haplotypes:
http://www.geocities.com/mcewanjc/p3modal.htm
Whit Athey’s
Haplogroup Predictor:
http://www.hprg.com/hapest5/
Athey TW (2006) Haplogroup prediction from Y-STR values using
a Bayesian allele-frequency approach. J
Genetic Genealogy, 2:34-39.
McEwan J (2007) Phase 3 analysis: Ysearch 37 STR modal
summary and analysis tables (web site).
Oppenheimer S (2006) The Origins of the British - A Genetic
Detective Story, Constable and Robinson, London (ISBN 1-84529-158-1). Published in the U.S. by Carroll and Graf, New York.
Sykes B (2006) Blood of the Isles: Exploring The Genetic
Roots of Our Tribal History. Bantam
Books. Published in the U.S. as Saxons, Vikings, and Celts:
The Genetic Roots of Britain and Ireland, by W. W. Norton, New York.
Appendix A – OGAP
Haplotypes
The 1625 data points that comprise
the R1b data set include 291 separate haplotypes. However, 50% of the data can be accounted for
with only 10 haplotypes; 60% by 20 haplotypes; and 68% by 30 haplotypes. In addition, haplotypes beyond the top 30
have only single-digit frequencies compared to the most frequent – the Atlantic
Modal Haplotype (AMH), which occurs 262 times in the data.
Below are the top 50 haplotypes in
order of descending frequency. These are
number OGAP1 through OGAP55 for reference in this study and represent all
haplotypes that occur more than 5 times.
The distribution of these haplotypes in Sykes’ OGAP data and in YSearch
(www.ysearch.org) as of December 2006) is
shown on the right hand side of the chart.
Also, a mapping of John McEwan’s
(2007) R1b subclades is shown on the left hand side of the chart. The letters designating the McEwan group
refer to the groups described in Appendix B that were assigned when McEwan
individual haplotypes were grouped together to reflect the much smaller number
of markers in the OGAP data.
Appendix B –
McEwan’s R1b Haplotypes Reduced
By mining YSearch and collecting
similar 37-marker haplotypes into clusters, McEwan (2007) has identified a
large number of R1b “types” that comprise the world-wide scope of this
data. It is interesting to consider how
the Sykes OGAP data relates to McEwan’s haplotypes. However to compare the data, McEwan’s modal
haplotypes had to be collapsed into smaller groups to reflect the smaller
number of markers in the OGAP haplotypes (Refer to Appendix A).
The following is the reduction of
the McEwan haplotypes to 10-marker haplotypes.
In each case, letter designations have been included here for the
purpose of mapping the full set of McEwan haplotypes (designated R1bSTR##) to
the reduced set used in this analysis (Letter Groups). While this exercise
necessitates the loss of considerable resolution in the McEwan haplotypes, the
exercise is included here to provide traceability to the analysis included in
Appendix A.
In the case of academic researchers,
many keep tight control of their data.
It is hoped that in the future that scientific journal editors will
require the submission of supporting data, which they might even hold for a
period of time even after publication of analytic articles. Such submissions would ensure that important
research is fully documented even if it is years later when the article is no
longer at the forefront of everyone’s mind.
Address for
correspondence: [email protected]
