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Method: Ecological Classification of Rivers using Macrophytes [Ecological Classification of Rivers using Macrophytes]

1. General information

1.01 GIG: Central-Baltic
Relevant intercalibration types: n.a.
1.02 Category: Rivers
1.03 BQE: Macrophytes
1.04 Country: United Kingdom
1.05 Specification: none
1.06 Method name: Ecological Classification of Rivers using Macrophytes
1.07 Original name: Ecological Classification of Rivers using Macrophytes
1.08 Status: Method is/will be used in First RBMP (2009), Second RBMP (2015)
1.09 Detected pressure(s):
Eutrophication, Hydromorphological degradation Specification of pressure-impact-relationship:
The relationship of all metrics with pressure (SRP, total oxidised nitrogen [TON], NH4, % intensive land cover) were investigated using 6600 macrophyte surveys of almost 1000 UK rivers. The nutrient metric (RMNI) was the most significantly related to nutrient pressure (Correlation of RMNI to SRP r2 = 0.475, correlation to TON r2 = 0.582), diversity metrics were only significantly related to nutrients in high alkalinity rivers, but were related to other BQEs (Invertebrates p<0.001). Filamentous algal cover was significantly related to nutrient pressure (p<0.05).
Pressure-impact-relationship:
Yes, with quantitative data (e.g. against range of sites reflecting continuous gradient of pressure).
1.10 Internet reference:
http://www.wfduk.org/bio_assessment/bio_assessment/river%20macrophytes%20nw
1.11 Pertinent literature of mandatory character:
Water Framework Directive- United Kingdom Technical, 2009. UKTAG river assessment methodsmacrophyte and phyronbenthos macrophytes river leafpacs. Version 2.
http://www.wfduk.org/bio_assessment/bio_assessment/river%20macrophytes%20nw
Willby, N.J., J. Pitt & G.L. Phillips, 2010. The ecological classification of UK rivers using aquatic macrophytes. Enviroment Agency Science Report.
1.12 Scientific literature: n.a.
1.13 Method developed by: Nigel Willby
Email of developer: n.j.willby@stir.ac.uk
Institute of developer: University of Stirling
1.14 Method reported by: Damien Hicks, Imelda O?Neill, Geoff Phillips
Email of person reporting the method:
Damien.Hicks@sepa.org.uk, imelda.oneill@doeni.gov.uk, Geoff.phillips@environment-agency.gov.uk
Email of institute reporting the method:
Scottish Environment Protection Agency, Northern Ireland Environment Agency, Environment Agency(England & Wales)
1.15 Comments: none

2. Data acquisition

Field sampling/surveying

2.01 Sampling/Survey guidelines:
Willby, N.J., J. Pitt & G.L. Phillips, 2010. The ecological classification of UK rivers using aquatic macrophyte. Enviroment Agency Science Report.
2.02 Short description:
At the 100 m stretch surveyors record presence and abundance of macrophytes in permanently submerged parts of the channel or within the saturated zone at the margins or the lower part of the inundation zone.
2.03 Method to select the sampling/survey site or area: Expert knowledge
2.04 Sampling/survey device: Grapnel
Other macrophyte sampling device: bathyscope
Any other sampling device: bathyscope
2.05 Specification: none
2.06 Sampled/surveyed habitat:
Sampled habitat: All available habitats per site (Multi-habitat)
2.07 Sampled/surveyed zones in areas with tidal influence: not relevant
2.08 Sampling/survey month(s): June - September
2.09 Number of sampling/survey occasions (in time) to classify site or area:
Dependent on confidence required: recommended 1 year of the 6-year RBMP reporting period
2.10 Number of spatial replicates per sampling/survey occasion to classify site or area:
Dependent on confidence required: recommended 3 sites per water body. 2 sites per water body can achieve 95% confidence of being worse than Good if the class is at the middle point of moderate. For the 1st RBMP 1-3 sites per water body have been used in different parts of the UK depending on available resources.
2.11 Total sampled/surveyed area or volume or total sampling duration to classify site or area:
Surveyed area is 100 m. Between one and three 100 m stretches are surveyed and mean EQR for each 100 m stretch is determined for river waterbody.

Sample processing

2.12 Minimum size of organisms sampled and processed: Macroalgal filaments
2.13 Sample treatment:
Organisms of the complete sample are identified.
2.14 Level of taxonomical identification:
Level: Genus, Species/species groups
Specification of level of determination: Most macroalgae to genus level only
2.15 Record of abundance:
Determination of abundance: Abundance classes
Abundance is related to: n.a.
Unit of the record of abundance:
Rank 1-9 Species Cover Value: C1 <0.1% C2 0.1 to 1% C3 1 to 2.5% C4 2.5 to 5% C5 5 to 10% C6 10 to 25% C7 25 to 50% C8 50 to 75% C9 >75%
Other record of abundance: cover
2.16 Quantification of biomass: n.a.
2.17 Other biological data: none
2.18 Special cases, exceptions, additions:
Non-wadable rivers are surveyed by 5m wide sections on each side of the river
2.19 Comments: none

3. Data evaluation

Evaluation

3.01 List of biological metrics:
River Macrophyte Nutrient Index; River Macrophyte Hydraulic Index, Functional Group Diversity, Number of Taxa, Filamentous Algal Cover
3.02 Does the metric selection differ between types of water bodies: n.a.
3.03 Combination rule for multi-metrics: Weighted average metric scores, Worst metric score
Other rules:
Worst diversity metric, worst nutrient and hydraulic index are combined with each other and algal metric using weighted average depending on location of water body on natural fertility gradient
3.04 From which biological data are the metrics calculated:
List of biological metrics: Data from single spatial replicate

Reference conditions

3.05 Scope of reference conditions: Site-specific
3.06 Key source(s) to derive reference conditions:
Scope of reference conditions:
Existing near-natural reference sites, Modelling (extrapolating model results)
Other reference source:
Cover of highly sensitive and sensitive taxa. Taxa defined using modelled (CCA) relationships with pressure, subsequently verified and adjusted by comparing regression of metric scores of these indicative taxa groups against a morpho edaphic index to ensure that UK data used to select groups were drawn from a full gradient of pressure.
3.07 Reference site characterisation:
Number of sites: C400 surveys (mixture of historic and contemporary surveys)
Geographical coverage:
Surveys from whole of UK (England, Wales, Scotland & Northern Ireland)
Location of sites: Available on request
Data time period: Surveys selected from data set covering 1976-2003C10
Criteria:
Sites selected by iterative application of biological and physicochemical criteria. <15% total cover of pressure tolerant taxa, highly pressure sensitive specie present, cover of highly tolerant species <10% total cover, number of aquatic taxa and functional groups > 25th percentile of type specific richness, total hydrophyte cover & mean cover score per species within type and method specific 10-90th percentile range. No individual taxa with cover score > 6 (10-25%), no established invasive alien or translocated species, dominant acid tolerant taxa <50% cover, filamentous green algae < 2.5% absolute cover and <20% relative cover. Mean annual concentration of N-NH4 < 0.05-0.1mg/l, SRP < 20-40 µ, N-NO3g/l <2-4 mg/l depending on type, River Habitat Survey Class 1 or 2, No resectioning of reaches, flows within 10% of naturalised flow, impacted land cover <20% of catchment area.
3.08 Reference community description:
Macrophyte community dominated by highly sensitive taxa, tolerant taxa are strongly subordinate and highly tolerant taxa occur only as transients and are never established.
Typical macrophyte mediated functions (habitat support, bed and bank stabilisation, biogeochemical cycling, aesthetics) are intact.
3.09 Results expressed as EQR: Yes

Boundary setting

3.10 Setting of ecological status boundaries:
High-good boundary derived from metric variability at near-natural reference sites
Using paired metrics that respond in different ways to the influence of the pressure
Other boundary setting:
Approach to boundary setting is set out in:
Phillips et al., 2003. The assessment of ecological quality of lakes in the Great Britain Ecoregion: an update on thinking and a possible approach for phytoplankton. TeemaNord 2003, 547: 35-39.
3.11 Boundary setting procedure:
The relative positions of High-Good and Poor-Bad boundaries are effectively symmetrical with sensitive species overwhelmingly dominant at one and tolerant species overwhelmingly dominant at the other.
Using the same standard error from logistic regressions, a ratio of sensitive:tolerant species of 85:15 is used as the High-Good boundary, since this represents the upper error when tolerant species are predicted to be absent. These ratios are reversed at the Poor-Bad boundary with 15% sensitive species representing the lower error when sensitive species are predicted to be absent.
3.12 "Good status" community:
Sensitive taxa dominate, highly sensitive taxa are scarcer and account for about half the contribution of sensitive taxa. Tolerant taxa are present, but remain subordinate. Highly tolerant taxa, if present are rare.
Macrophyte functions at high status all remain intact, undesirable disturbances are rare and macrophyte cover is stable over time.

Uncertainty

3.13 Consideration of uncertainty: Yes
Specification of uncertainty consideration:
If the modelled relationship between observed mean EQR and EQR SD, taking into account sampling, temporal and spatial sources of variation is accepted as the best available estimate of the error associated with a given EQR. We can combine this with information on class boundaries and therefore predict the confidence with which a site can be assigned to a given class. This approach effectively assumes that the errors associated with a given EQR are normally distributed about that mean with a distribution equivalent to the modelled EQR SD. Given this information one can assess the impact of different survey frequencies on confidence of class. The procedure for calculating confidence of class is outlined by Ellis (2006). The risk of face-value misclassification (i.e. of assigning a site to the wrong class) is then computed as the sum of confidences of membership of all classes except for the observed class. The risk of misclassification will always be at least 50% for an EQR that lies exactly on a class boundary but will fall to a minimum moving towards the middle of that class. It should be noted that this approach differs slightly from that trialled previously using the STARBUGS software (Clarke, 2005). In STARBUGS the EQR SD is considered constant and confidence of class is based on the result of multiple simulations in which a random error derived from the distribution defined by the SD is added to each observed EQR. The probability that a site belongs to a specific class is based on the statistical distribution of these simulated values.
3.14 Comments:
Further information on variability can be found in Environment Agency report SC070051/SR4 Davey & Garrow (2010) Variability components for macrophyte communities in rivers.

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