10.5061/DRYAD.6QG398D1
Jump, Alistair S.
University of Stirling
Rico, Laura
Autonomous University of Barcelona
Coll, Marta
Autonomous University of Barcelona
PeƱuelas, Josep
Autonomous University of Barcelona
Data from: Wide variation in spatial genetic structure between natural
populations of the European beech (Fagus sylvatica) and its implications
for SGS comparability
Dryad
dataset
2012
molecular ecology
spatial genetic structure
European beech
present
Fagus sylvatica
2012-01-10T19:44:38Z
2012-01-10T19:44:38Z
en
https://doi.org/10.1038/hdy.2012.1
427703 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Identification and quantification of spatial genetic structure (SGS)
within populations remains a central element of understanding population
structure at the local scale. Understanding such structure can inform on
aspects of the species' biology, such as establishment patterns and
gene dispersal distance, in addition to sampling design for genetic
resource management and conservation. However, recent work has identified
that variation in factors such as sampling methodology, population
characteristics, and marker system can all lead to significant variation
in SGS estimates. Consequently, the extent to which estimates of SGS can
be relied upon to inform on the biology of a species or differentiate
between experimental treatments is open to doubt. Following on from a
recent report of unusually extensive SGS when assessed using amplified
fragment length polymorphisms (AFLP) in the tree Fagus sylvatica, we
explored whether this marker system led to similarly high estimates of SGS
extent in other apparently similar populations of this species. In the
three populations assessed, SGS extent was even stronger than this
previously reported maximum, extending up to 360 m, an increase of up to
800% in comparison with the generally accepted maximum of 30 - 40 m based
on the literature. Within this species, wide variation in SGS estimates
exists, whether quantified as SGS intensity, extent, or the Sp parameter.
Consequently, we argue that greater standardisation should be applied in
sample design and SGS estimation and highlight five steps that can be
taken to maximize the comparability between SGS estimates.
JUMP AFLP Data_ DryadAFLP data derived from natural populations of the
European beech, Fagus sylvatica in the Pyrenees and Montseny Mountains in
northeast Spain
North east Spain