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Table 5 Linear regressions of eutrophication-sensitive metrics against TP

From: Ecological status assessment of European lakes: a comparison of metrics for phytoplankton, macrophytes, benthic invertebrates and fish

BQE Metric Metric description adj. R 2 GIG or country P N b1 b1* SE b1* Comment
Phytoplankton Chla Chlorophyll a (μg/l) 0.62 All, but mainly NGIG & CBGIG <0.001 1447 0.7078 0.7872 0.0162 Linear regression model using log10 TP and log10 Chla data
  PTI Phytoplankton Trophic Index 0.50 All, but mainly NGIG & CBGIG <0.001 618 1.2471 0.7068 0.0285 Linear regression model using log10 TP data
  FTI Functional Traits Index (mean of SPI and MFGI) 0.49 CB/N/M GIGs <0.001 228 0.0336 0.7002 0.0475 Linear regression model using log10 TP and FTI data
  J Evenness 0.15 N-GIG <0.001 716 −0.1351 −0.3930 0.0344 Linear regression model using log10 TP and evenness data, J′ multiplied by −1 to reverse slope
  Cyano bloom intensity Cyanobacteria biovolume (mg/l) 0.40 All, but mainly NGIG & CBGIG <0.001 1447 1.2165 0.6355 0.0203 Linear regression model using log10 TP and log10 cyano-biovolume data
Macrophytes ICM Intercalibration Common Metric 0.55 CB/N-GIG <0.001 1504 2.2963 0.7401 0.0174 Linear regression model using log10 TP and ICM data
  EI Ellenberg Index of taxonomic composition 0.47 CB/N-GIG <0.001 1504 2.2133 0.6871 0.0188 Linear regression model using log10 TP and Ellenberg data
  C max Maximum growing depth of submerged macrophytes 0.31a Mainly CB/N-GIG + Italy <0.001 478 n.a.a n.a.a n.a.a Linear regression model using log10 TP and C max data
Benthic invertebrates MMI Multimetric Index for intercalibration in CB-GIG 0.36 CB-GIG <0.001 193 −0.3605 −0.6026 0.0577 Linear regression model using log10 TP and MMI data
Fish ELFI European Lake Fish Index (multimetric of BPUE, CPUE and OMNI) 0.13 All GIGs <0.001 444 −0.1161 −0.3587 0.0444 Linear regression model using log10 TP and ELFI
  NLFI Nordic Lake Fish Index (multimetric of BPUE, CPUE and OMNI) 0.46 N-GIG <0.001 155 −0.4148 −0.6797 0.0593 Linear regression model using log10 TP and NLFI
  1. N number of observations (mean values for each water body), b1 regression slope, b1* standardised regression slope (based on z-transformed data), SE b1* standard error of the slope (regression on z-transformed data)
  2. a C max not included in the comparison of regression slopes