A diagnostic modelling framework to construct indices of biotic integrity: A case study of fish in the Zeeschelde estuary (Belgium)

Transitional and coastal waters ecological status assessment: advances and challenges resulting from implementing the European Water Framework Directive

“…Modelling and BPJ can be used in setting reference conditions when adequate information is missing. However, although there are attempts at modelling the community structure of some BQEs (Valesini et al, 2010;Quataert et al, 2011), none of these are suitable in decision-support systems. This leaves BPJ as the most practical tool for setting reference conditions.…”

The Evaluation of Water Quality and Investigation of Benthic Macroinvertebrates in Stone-Horse River of Dongjiang (China)

“…The diversity of the benthic macroinvertebrates can be used to evaluate the ecological health of the river comprehensively [1] . It also can show the pollution sitiation in a certain extent [2] . But there are affects on the results, such as the habitat condition, the weather, the pollution status (kinds and concentrations of pollutants, the time) in each point.…”

A technical guide to develop a statistically valid fish-based index in compliance with the water framework directive: an evaluation for Turkish freshwaters

“…There are several approaches for scoring the selected metrics (Blocksom 2003). The reference sites have a key role in scoring; reference sites with minimum disturbance can be used to determine optimal scores (Quataert et al 2011;Mostafavi et al 2015). If the reference conditions are not available, preclassification systems can be used (e.g., Fame manual 2004; Quataert et al 2011).…”

“…Thus, if the preclassification of the sampling locations will be done using this system, a slight adjustment is needed. Although, the preclassification is not an accurate system for habitat status assignment, it is accepted as a useful procedure to rank the sampling locations and develop an index (Quataert et al 2011). The habitat assignment and EQR classification should match considering a one class divergence as acceptable errors (Type I or II error; see Breine et al 2010).…”