STRIVE - Environmental Protection Agency

in lakes from assemblage III, and their presence
in surface water samples probably reflects water
column mixing concomitant to climatic conditions
characterised by regimes of wind and precipitations. It
is also possible that those taxa reflect the near-shore
sampling strategy which was applied to the survey.
Data ordination in a planar projection showed the first
component to be positively correlated with lake surface
temperature, enabling the discrimination of the three
lake assemblages across the temperature gradient. The
first component was therefore interpreted in this study
as a general indicator of seasonality and meteorological
conditions.
Shifts in climatic conditions, in particular those that result
in physical mixing processes, can impact significantly
upon the structuring of phytoplankton communities
(Reynolds et al. 1983, Spigel & Imberger 1987,
Huissman et al. 2004). It has been predicted that the
outcome of competition for light in a well-mixed water
column depends on the individual critical light intensities
of the organisms, which can differ considerably between
species (Huissman & Weissing 1994, Huisman & Hulot
2005). In particular, studies in Lake Nieuwe Meer, The
Netherlands, confirmed that turbulent mixing could
shift the competitive balance – hence, phytoplankton
community composition – between buoyant
cyanobacteria and sinking diatoms (Huisman et al.
2004). Despite the lack of measurements of wind stress
and vertical turbulent diffusivities in the present study, it
can be hypothesised, based on the evolution of surface
water temperature, Secchi depth and meteorological
conditions that a similar shift occurred at the end of July,
which lasted throughout August. The phytoplankton
community structure in Ireland changed toward lower
chlorophyll-a levels and the dominance of diatoms over
this period.
The relationship between community complexity and
primary productivity is important for trophic interactions
within the aquatic food chain, and greater phytoplankton
diversity has been observed in lakes of low productivity
(Leibold 1999, Dodson et al. 2000). In this study,
phytoplankton richness was significantly lower in zone I
(and cluster B), which contained the greatest proportions
of mesotrophic and eutrophic lakes in the sampled
population. Niche differentiation can be reduced in wellmixed
environments with low spatial heterogeneity, and
N. Touzet (2008-FS-EH-3-S5)
55
is accompanied by lower diversity in the water column
(Jäger et al. 2008). Since sampling within each cluster
of river catchment was spread over a 15-week period
encompassing a range of weather conditions, it is likely
that the lower richness observed in the lakes sampled
from zone I originates from the interactions of multiple
factors rather than meteorological effects only.
4.5 Environmental Fingerprinting:
Molecular Assessment of
Communities
Advances in molecular biology have enabled the study of
microbial communities in multiple environments based
on the variability between species in the nucleotide
sequences of a number of genes. Molecular ecology
has strongly benefited from the adaptation of genetic
fingerprinting techniques to unravel the wide diversity
in microbial communities. The generalisation of the
use of PCR and sequencing to genetically characterise
isolates of globally distributed taxa has also permitted
the resolution of some taxonomic ambiguities.
The summer variation in lacustrian cyanobacterial
diversity was investigated using 16S rDNA DGGE
fingerprinting across a region of Ireland containing
multiple river catchments during 2009. Even
though nested PCR-DGGE is a powerful molecular
fingerprinting method for detecting low copy number
genes or specific hierarchical taxonomic groups in
microbial communities, it has usually been described as
unsuitable for quantitative assessments, as the degree
of proportionality between initial template amounts and
resulting amplicon concentration can be lost through the
amplifications cycles (Farrelly et al. 1995, Muylaert et al.
2002, Zwart et al. 2005). The abundances of amplicons
may also not reflect those of all target genes due to
differences in primer binding, elongation efficiency or
initial proportions of target DNA in template samples
(Raeymaekers 1995, Suzuki & Giovannoni 1996). Those
aspects have been examined while coupling the nested
approach with quantitative PCR, in which the number of
amplifications cycles in the secondary PCR did affect
the reliability of the quantification. Park and Crowley
(2010) also demonstrated that the number of first-round
PCR cycles was essential to limit the bias associated
with nested PCR-DGGE, recommending less than 20
cycles for amplifying low copy number sequences and