Hydrobiologia

Howard, Alan

doi: 10.1023/A:1003099009095pmid: N/A

Ferguson, A.

doi: 10.1023/A:1003004406291pmid: N/A

Blooms and scums of blue-green algae (cyanobacteria)have occurred throughout the world for many years andare only one of many problems associated withover-enrichment by nutrients of fresh and marinewaters. Although much studied and written about,eutrophication poses complex and difficult managementproblems. The role of modelling as an aid to thecontrol of blue green algae is discussed.

Reynolds, C.; Irish, A.

doi: 10.1023/A:1003020823129pmid: N/A

Supposing the ability to elect in situspecies-specific replication rates of phytoplankton tobe an essential step towards the development of soundecological models of phytoplankton populations inlakes and reservoirs, we promote the case for takingmaximum specific growth rates under ideal cultureconditions as base, rather than derivations ofspecific growth rate assembled from models ofphotosynthetic carbon fixation and nutrient uptake. Itis argued that these yield capacities for growth butcan greatly exaggerate in-situ replication rates. Theuse of published regressions of robust properties oforganismic assembly is recommended and some relevantmodel algorithms are outlined.

Harris, G.

doi: 10.1023/A:1003072907200pmid: N/A

This paper sets out a conceptual framework formodelling events in aquatic ecosystems as coupledprocesses in catchments, water columns and sediments.This theoretical framework is developed using ideasfrom the behaviour of complex adaptive systems. I showthat it is possible to use similar models for eachsubsystem and that there are analogous processes ineach, differing only in scale. In this framework thephytoplankton appear as ’system canaries‘. Nuisancealgal blooms appear as a result of perturbations tothe system biogeochemistry at a range of scales.Macrophytes are identified as important components ofthe coupled catchment, water, sediment system.Thinking of models of algal blooms as coupled sets ofcatchment, water column and sediment models focusesattention on the flows of materials between thesubsystems. Such flows of dissolved and particulateorganic and inorganic nutrients (carbon, nitrogen andphosphorus) are rarely fully quantified. The balanceof particulate and dissolved organic nutrient loads(including detritus) is an important parameter whichdetermines events in aquatic ecosystems. This balanceis affected by a number of anthropogenic changesincluding land use, trophic state and flow regulation.Scaling of temporal and spatial patterns and processesin catchments, water columns and sediments will needto be further studied if this model framework is to bedeveloped.

Steel, J.

doi: 10.1023/A:1003025026764pmid: N/A

Major aspects of algal modelling are defined.Prediction and explanation are suggested as mainobjectives. Examples of the development and use ofshort-term prediction and more general explanatoryalgal models for reservoirs are given. It is concludedthat good prediction and explanation are not likely tobe simultaneously achievable. Possible means ofassessing the capabilities of ecosystem models andmodelling are considered. Some suggestions as to howthe present situation may be coped with, and improved,are proposed.

Whitehead, P.; Howard, A.; Arulmani, C.

doi: 10.1023/A:1003089310834pmid: N/A

Algae present considerable problems for river qualitymanagers and water suppliers and methods to predicttheir behaviour, growth and transport can assist inoperational management. Alternative techniques existfor predicting algal response and three approacheshave been compared and applied to data from six sitesalong the River Thames. These techniques include timeseries analysis, dynamic mass balance and growthequations and neural network approaches. It is shownthat neural network techniques offer a new approachrequiring less intuitive knowledge but predictivecapability is not improved greatly compared to otherapproaches. Neural networks enable models to bedeveloped along all six reaches of the RiverThames.

Recknagel, Friedrich

doi: 10.1023/A:1003041427672pmid: N/A

Predictive potential of deductive and inductivephytoplankton models are compared regarding theirusefulness for forecasting and control of harmfulalgal blooms. While applications of deductive modelsstill seem to be restricted by lack of knowledge, ad hocinductive models sometimes prove to bestraightforward and useful. The inductive neuralnetwork model ANNA is documented by means of anapplication to Lake Kasumigaura, Japan. ANNA wasvalidated for five blue-green algae species wherepredictive accuracy has improved with increased eventand time resolution of training data. A scenarioanalysis on species succession has demonstrated thepotential of ANNA for hypothesis testing. Finally,implications for use of ANNA for operational algalbloom control are discussed.

Kneale, Pauline; Howard, Alan

doi: 10.1023/A:1003093411743pmid: N/A

Data on cyanobacteria (blue-green algae) are generallycollected on a reactive basis, frequently in responseto bloom events. Such data presents a biased andincomplete snapshot of water quality. This paper looksat two typical data sets for UK waters showing thatwhile statistics may be used to describe the data theyare of limited use in forecasting. Suggestions ofappropriate tests for small and sparse data sets aremade.

Walsby, A.

doi: 10.1023/A:1003045528581pmid: N/A

Detailed descriptions have been made of theunder-water light field based on continuousmeasurements of surface photon irradiance,calculations of losses by surface reflection andmeasurements of the vertical light attenuation. Thesemeasurements have been combined with measurements ofthe vertical distribution of phytoplankton chlorophylland the photosynthesis/irradiance curve to produce ameasurement of the daily integral of photosynthesis bynumerical integration using a PC spreadsheet; theaccuracy of the integrations is evaluated. The resultshave been compared with models that assume a uniformvertical distribution of phytoplankton. Suchassumptions produced underestimates of the dailyintegral of photosynthesis by 50–109% for apopulation of Aphanizomenon flos-aquae inthe Baltic Sea owing to the overestimate ofrespiratory losses. Buoyant cyanobacterial populationsfloat up during brief episodes of calm; this increasesthe insolation they receive and their resultantphotosynthetic activity may increase several times.These advantages of buoyancy, provided by gasvesicles, are a major factor in determining thesuccess of waterbloom-forming cyanobacteria. A modelis produced of the relationship between the mean depthof the Aphanizomenon phytoplankton populationand the daily integral of photosynthesis at differentinsolations; this may provide the basis forimprovement of models applicable to otherphytoplankton populations. The integration spreadsheetis available athttp://www.bio.bris.ac.uk/research/walsby/integral.htm.

Schubert, H.; Forster, R.

doi: 10.1023/A:1003097512651pmid: N/A

The accumulation of phytoplankton biomass, which oftenoccurs when water bodies receive enhanced inputs ofinorganic nutrients, causes large changes in theavailability and spectral composition of underwaterlight. Quantitative descriptions of the variations inlight available to phytoplankton are a prerequisitefor modelling of aquatic primary productivity. As anexample of the range of natural variation inirradiance, the main spectral, spatial and temporalchanges in underwater light, which occur in a shalloweutrophic estuary in response both to increasingchlorophyll concentration and to wind-induced verticalmixing, are described. Additionally, phytoplanktonwere shown to exhibit changes in photosyntheticphysiology which were triggered by changes in thequantity and spectra of light. The characteristics andkinetics of these responses are presented anddiscussed in relation to their impact on modelling ofprimary productivity.