Matches in SemOpenAlex for { <https://semopenalex.org/work/W2029349871> ?p ?o ?g. }
- W2029349871 endingPage "166" @default.
- W2029349871 startingPage "154" @default.
- W2029349871 abstract "Many benthic quality indices rely on categorising impacts by assigning species to ecological-groups (EGs) that reflect their tolerance to pollution. This is usually based on best professional judgement (BPJ) by experts with access to relevant ecological and taxonomic information. However, international applicability of such indices is restricted in areas where the species taxonomy, biology and response to pollution are poorly understood. In this study we describe an approach that enables objective allocation of EGs in situations where species information is limited. This approach utilised BPJ to categorise the environmental condition of benthic habitats around fish farms in New Zealand in relation to defined enrichment stages (ESs). Quantile regression was then used to model distributions of select taxa. The experts assigned ES scores from 1 to 7, for stations that ranged from relatively natural to excessively enriched (i.e. near-azoic), respectively, with judgements based on a suite of quantitative and qualitative indicators of enrichment, but without reference to detailed species information. The individual BPJ estimates were highly correlated, with minimal bias, indicating good agreement among the experts. Forty key indicator taxa were identified and quantile regression models based on ES (derived as a continuous explanatory variable) were fitted for 34. Abundances of the same taxa were also modelled in response to a more traditional enrichment indicator (organic content, %OM) for comparison with the BPJ technique. The regression approach characterised enrichment responses and objectively identified both the upper and lower tolerance limits of a range of taxa according to their ES and %OM. The models discriminated a number of key indicator taxa, including several that were responsive to low-level changes in ES, but not necessarily %OM. There was reasonable agreement (59%) between EGs derived using the regression approach and those defined using the AMBI database (one of the most commonly applied benthic quality indices). Moreover, the regression method allowed the classification of 10 additional taxa for which our ecological understanding was limited. A key outcome of this study was the acknowledgement that EG characterisations for species need to be regionally validated, no matter how well defined they might appear to be. The combined BPJ/regression analysis approach described provides a valid means of both assigning and validating EG classifications, which will be particularly useful in situations where the taxa are poorly defined, and will enable existing biotic indices to be more broadly applied and interpreted." @default.
- W2029349871 created "2016-06-24" @default.
- W2029349871 creator A5016819817 @default.
- W2029349871 creator A5033777778 @default.
- W2029349871 creator A5078948029 @default.
- W2029349871 date "2012-01-01" @default.
- W2029349871 modified "2023-09-25" @default.
- W2029349871 title "Combining best professional judgement and quantile regression splines to improve characterisation of macrofaunal responses to enrichment" @default.
- W2029349871 cites W1610990140 @default.
- W2029349871 cites W177113258 @default.
- W2029349871 cites W1968381280 @default.
- W2029349871 cites W1969896322 @default.
- W2029349871 cites W1970739592 @default.
- W2029349871 cites W1979725290 @default.
- W2029349871 cites W1982449013 @default.
- W2029349871 cites W1986264309 @default.
- W2029349871 cites W1987212411 @default.
- W2029349871 cites W1989933010 @default.
- W2029349871 cites W1990144679 @default.
- W2029349871 cites W1990227458 @default.
- W2029349871 cites W2014759029 @default.
- W2029349871 cites W2015852146 @default.
- W2029349871 cites W2016466591 @default.
- W2029349871 cites W2016694454 @default.
- W2029349871 cites W2026179425 @default.
- W2029349871 cites W2027977527 @default.
- W2029349871 cites W2041072954 @default.
- W2029349871 cites W2042409053 @default.
- W2029349871 cites W2043363073 @default.
- W2029349871 cites W2046010400 @default.
- W2029349871 cites W2047076594 @default.
- W2029349871 cites W2047816526 @default.
- W2029349871 cites W2051474297 @default.
- W2029349871 cites W2061883894 @default.
- W2029349871 cites W2063151329 @default.
- W2029349871 cites W2064335136 @default.
- W2029349871 cites W2068571426 @default.
- W2029349871 cites W2071693131 @default.
- W2029349871 cites W2072109079 @default.
- W2029349871 cites W2073212459 @default.
- W2029349871 cites W2082000634 @default.
- W2029349871 cites W2084273283 @default.
- W2029349871 cites W2085810503 @default.
- W2029349871 cites W2091937157 @default.
- W2029349871 cites W2096904991 @default.
- W2029349871 cites W2108106320 @default.
- W2029349871 cites W2110876005 @default.
- W2029349871 cites W2111738734 @default.
- W2029349871 cites W2122805096 @default.
- W2029349871 cites W2127242366 @default.
- W2029349871 cites W2131727130 @default.
- W2029349871 cites W2142568711 @default.
- W2029349871 cites W2154300018 @default.
- W2029349871 cites W2157863650 @default.
- W2029349871 cites W2160899588 @default.
- W2029349871 cites W2162484055 @default.
- W2029349871 cites W2162510013 @default.
- W2029349871 cites W2165828331 @default.
- W2029349871 cites W2167239677 @default.
- W2029349871 cites W2172776214 @default.
- W2029349871 cites W2484991121 @default.
- W2029349871 doi "https://doi.org/10.1016/j.ecolind.2011.03.022" @default.
- W2029349871 hasPublicationYear "2012" @default.
- W2029349871 type Work @default.
- W2029349871 sameAs 2029349871 @default.
- W2029349871 citedByCount "42" @default.
- W2029349871 countsByYear W20293498712012 @default.
- W2029349871 countsByYear W20293498712013 @default.
- W2029349871 countsByYear W20293498712014 @default.
- W2029349871 countsByYear W20293498712015 @default.
- W2029349871 countsByYear W20293498712016 @default.
- W2029349871 countsByYear W20293498712018 @default.
- W2029349871 countsByYear W20293498712019 @default.
- W2029349871 countsByYear W20293498712020 @default.
- W2029349871 countsByYear W20293498712021 @default.
- W2029349871 countsByYear W20293498712022 @default.
- W2029349871 countsByYear W20293498712023 @default.
- W2029349871 crossrefType "journal-article" @default.
- W2029349871 hasAuthorship W2029349871A5016819817 @default.
- W2029349871 hasAuthorship W2029349871A5033777778 @default.
- W2029349871 hasAuthorship W2029349871A5078948029 @default.
- W2029349871 hasConcept C105795698 @default.
- W2029349871 hasConcept C159985019 @default.
- W2029349871 hasConcept C17744445 @default.
- W2029349871 hasConcept C185933670 @default.
- W2029349871 hasConcept C18903297 @default.
- W2029349871 hasConcept C192562407 @default.
- W2029349871 hasConcept C199539241 @default.
- W2029349871 hasConcept C204323151 @default.
- W2029349871 hasConcept C2776548248 @default.
- W2029349871 hasConcept C33923547 @default.
- W2029349871 hasConcept C63817138 @default.
- W2029349871 hasConcept C71640776 @default.
- W2029349871 hasConcept C83042747 @default.
- W2029349871 hasConcept C86803240 @default.
- W2029349871 hasConceptScore W2029349871C105795698 @default.
- W2029349871 hasConceptScore W2029349871C159985019 @default.
- W2029349871 hasConceptScore W2029349871C17744445 @default.