Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters.

Stauber, JL; Gadd, J; Price, GAV; Evans, A; Holland, A; Albert, A; Batley, GE; Binet, MT; Golding, LA; Hickey, C; Harford, A; Jolley, D; Koppel, D; McKnight, KS; Morais, LG; Ryan, A; Thompson, K; Van Genderen, E; Van Dam, RA; Warne, MSJ

Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters.

Stauber, JL Gadd, J Price, GAV Evans, A Holland, A Albert, A Batley, GE Binet, MT Golding, LA Hickey, C Harford, A Jolley, D Koppel, D McKnight, KS Morais, LG Ryan, A Thompson, K Van Genderen, E Van Dam, RA Warne, MSJ

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Publisher:: WILEY
Publication Type:: Journal Article
Citation:: Environ Toxicol Chem, 2023, 42, (12), pp. 2614-2629
Issue Date:: 2023-12

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Field	Value	Language
dc.contributor.author	Stauber, JL
dc.contributor.author	Gadd, J
dc.contributor.author	Price, GAV
dc.contributor.author	Evans, A
dc.contributor.author	Holland, A
dc.contributor.author	Albert, A
dc.contributor.author	Batley, GE
dc.contributor.author	Binet, MT
dc.contributor.author	Golding, LA
dc.contributor.author	Hickey, C
dc.contributor.author	Harford, A
dc.contributor.author	Jolley, D
dc.contributor.author	Koppel, D
dc.contributor.author	McKnight, KS
dc.contributor.author	Morais, LG
dc.contributor.author	Ryan, A
dc.contributor.author	Thompson, K
dc.contributor.author	Van Genderen, E
dc.contributor.author	Van Dam, RA
dc.contributor.author	Warne, MSJ
dc.date.accessioned	2024-01-31T05:20:15Z
dc.date.available	2023-07-16
dc.date.available	2024-01-31T05:20:15Z
dc.date.issued	2023-12
dc.identifier.citation	Environ Toxicol Chem, 2023, 42, (12), pp. 2614-2629
dc.identifier.issn	0730-7268
dc.identifier.issn	1552-8618
dc.identifier.uri	http://hdl.handle.net/10453/175137
dc.description.abstract	Bioavailability models, for example, multiple linear regressions (MLRs) of water quality parameters, are increasingly being used to develop bioavailability-based water quality criteria for metals. However, models developed for the Northern Hemisphere cannot be adopted for Australia and New Zealand without first validating them against local species and local water chemistry characteristics. We investigated the applicability of zinc chronic bioavailability models to predict toxicity in a range of uncontaminated natural waters in Australia and New Zealand. Water chemistry data were compiled to guide a selection of waters with different zinc toxicity-modifying factors. Predicted toxicities using several bioavailability models were compared with observed chronic toxicities for the green alga Raphidocelis subcapitata and the native cladocerans Ceriodaphnia cf. dubia and Daphnia thomsoni. The most sensitive species to zinc in five New Zealand freshwaters was R. subcapitata (72-h growth rate), with toxicity ameliorated by high dissolved organic carbon (DOC) or low pH, and hardness having a minimal influence. Zinc toxicity to D. thomsoni (reproduction) was ameliorated by both high DOC and hardness in these same waters. No single trophic level-specific effect concentration, 10% (EC10) MLR was the best predictor of chronic toxicity to the cladocerans, and MLRs based on EC10 values both over- and under-predicted zinc toxicity. The EC50 MLRs better predicted toxicities to both the Australian and New Zealand cladocerans to within a factor of 2 of the observed toxicities in most waters. These findings suggest that existing MLRs may be useful for normalizing local ecotoxicity data to derive water quality criteria for Australia and New Zealand. The final choice of models will depend on their predictive ability, level of protection, and ease of use. Environ Toxicol Chem 2023;42:2614-2629. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	WILEY
dc.relation.ispartof	Environ Toxicol Chem
dc.relation.isbasedon	10.1002/etc.5722
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	03 Chemical Sciences, 05 Environmental Sciences, 06 Biological Sciences
dc.subject.classification	Environmental Sciences
dc.subject.classification	31 Biological sciences
dc.subject.classification	34 Chemical sciences
dc.subject.classification	41 Environmental sciences
dc.subject.mesh	Animals
dc.subject.mesh	Linear Models
dc.subject.mesh	New Zealand
dc.subject.mesh	Hydrogen-Ion Concentration
dc.subject.mesh	Australia
dc.subject.mesh	Cladocera
dc.subject.mesh	Organic Chemicals
dc.subject.mesh	Zinc
dc.subject.mesh	Fresh Water
dc.subject.mesh	Water Pollutants, Chemical
dc.subject.mesh	Animals
dc.subject.mesh	Cladocera
dc.subject.mesh	Zinc
dc.subject.mesh	Organic Chemicals
dc.subject.mesh	Water Pollutants, Chemical
dc.subject.mesh	Linear Models
dc.subject.mesh	Fresh Water
dc.subject.mesh	Hydrogen-Ion Concentration
dc.subject.mesh	Australia
dc.subject.mesh	New Zealand
dc.subject.mesh	Animals
dc.subject.mesh	Linear Models
dc.subject.mesh	New Zealand
dc.subject.mesh	Hydrogen-Ion Concentration
dc.subject.mesh	Australia
dc.subject.mesh	Cladocera
dc.subject.mesh	Organic Chemicals
dc.subject.mesh	Zinc
dc.subject.mesh	Fresh Water
dc.subject.mesh	Water Pollutants, Chemical
dc.title	Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters.
dc.type	Journal Article
utslib.citation.volume	42
utslib.location.activity	United States
utslib.for	03 Chemical Sciences
utslib.for	05 Environmental Sciences
utslib.for	06 Biological Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-31T05:20:13Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	42
utslib.citation.issue	12

Abstract:

Bioavailability models, for example, multiple linear regressions (MLRs) of water quality parameters, are increasingly being used to develop bioavailability-based water quality criteria for metals. However, models developed for the Northern Hemisphere cannot be adopted for Australia and New Zealand without first validating them against local species and local water chemistry characteristics. We investigated the applicability of zinc chronic bioavailability models to predict toxicity in a range of uncontaminated natural waters in Australia and New Zealand. Water chemistry data were compiled to guide a selection of waters with different zinc toxicity-modifying factors. Predicted toxicities using several bioavailability models were compared with observed chronic toxicities for the green alga Raphidocelis subcapitata and the native cladocerans Ceriodaphnia cf. dubia and Daphnia thomsoni. The most sensitive species to zinc in five New Zealand freshwaters was R. subcapitata (72-h growth rate), with toxicity ameliorated by high dissolved organic carbon (DOC) or low pH, and hardness having a minimal influence. Zinc toxicity to D. thomsoni (reproduction) was ameliorated by both high DOC and hardness in these same waters. No single trophic level-specific effect concentration, 10% (EC10) MLR was the best predictor of chronic toxicity to the cladocerans, and MLRs based on EC10 values both over- and under-predicted zinc toxicity. The EC50 MLRs better predicted toxicities to both the Australian and New Zealand cladocerans to within a factor of 2 of the observed toxicities in most waters. These findings suggest that existing MLRs may be useful for normalizing local ecotoxicity data to derive water quality criteria for Australia and New Zealand. The final choice of models will depend on their predictive ability, level of protection, and ease of use. Environ Toxicol Chem 2023;42:2614-2629. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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http://hdl.handle.net/10453/175137