Algae as Bioindicators - Freshwater Algae: Identification, Enumeration and Use as Bioindicators - page 109

Union Water Framework Directive (WFD; European
Union, 2000) have required the need to assess cur-
rent water status in relation to some baseline state
in the past. This baseline state (referred to as 'ref-
erence conditions') defines an earlier situation when
there was no significant anthropogenic influence on
the water body. In the United Kingdom, this refer-
ence baseline is generally set at about 1850, prior
to the modern era of industrialisation and agricul-
tural intensification. Having defined the reference
conditions, contemporary analyses can then be used
to make a comparative assessment of human influ-
ences on lake biology, hydromorphology and water
chemistry. For a particular water body, the absence of
long-term contemporary data means that reference
conditions have to be assessed on a retrospective
basis, including the use of palaeolimnology - the
study of the lake sediment record. The use of lake
sediments to generate a historical record only gives
reliable results under optimal conditions of optimal
algal preservation (see below) and if the sediments
are undisturbed by wind, bottom-feeding fish and
invertebrates.

Diatom bioindicators within sediments

Within lake sediments, diatoms have been particu-
larly useful as bioindicators (Section 1.10) of past
lake acidification (Battarbee et al ., 1999), point
sources of eutrophication (Anderson et al ., 1990)
and total phosphorus concentration (Hall and Smol,
1999). The widespread use of lake sediment diatoms
for reconstruction of past water quality is supported
by the European Diatom Database Initiative (EDDI).
This is a web-based information system designed to
enhance the application of diatom analysis to prob-
lems of surface water acidification, eutrophication
and climate change. The EDDI has been produced
by combining and harmonising data from a series of
smaller datasets from around Europe and includes a
diatom slide archive, electronic images of diatoms,
new training sets for environmental reconstruction
(see below) and applications software for manipulat-
ing data. In addition to the EDDI, other databases are
also available - including a large-scale database for
benthic diatoms (Gosselain et al ., 2005).
Diatoms within sediments are chemically cleaned
to reveal frustule structure (Section 2.5.2), identi-
fied and species counts expressed as percentage total.
Numerous examples of cleaned diatom images from
lake sediments are shown in Chapter 4. As with fos-
sil chrysophytes (Section 1.9), subsequent analysis
of diatom species counts to provide information on
waterqualitycaninvolvetheuseoftransferfunctions,
species assemblages and may be part of a multi-proxy
approach. The data obtained, coupled with radiomet-
ric dating of sediment cores, provide information on
times and rates of change and help in setting targets
for specific restoration procedures to be carried out.

Lake sediments - algal accumulation
and preservation

Continuous sedimentation of phytoplankton from the
surface waters (photic zone) of lakes leads to the
build-up of sediment, with the accumulation of both
planktonic and benthic algal remains at the bot-
tom of the water column. In a highly productive
lake such as Rostherne Mere, UK (Fig. 3.5), the
wet sedimentation rate in the deepest parts of the
water body has been estimated at 20 mm year −1
(Prartano and Wolff, 1998), with subsequent com-
pression as further sedimentation and decomposi-
tion occur. Decomposition of algal remains leads to
the loss of most organic biomass, and algal iden-
tification is largely based on the relatively resis-
tant inorganic (siliceous) components of diatoms
and chrysophytes (Section 1.9). Optimal preserva-
tion of this cell wall material requires anaerobic con-
ditions, and sediment samples are best taken from
central deep parts of the lake rather than from shal-
low regions such as the littoral zone (Livingstone,
1984).

Transfer functions These are mathematical
models that allow contemporary data to be applied to
fossil diatom assemblages for the quantitative recon-
struction of (otherwise unknown) past water quality.
Various studies (Bennion et al ., 2004; Taylor et al .,
2006; Bennion and Battarbee, 2007) have used this
approach, which involves

Generation of a predictive equation (transfer func-
tion) from a large number of lakes, in each
case relating the dataset of modern surface-
sediment diatom samples to lake water quality data