What is Meant by “95% of Species”? An Argument for the Inclusion of Rapid Tolerance Testing

Kefford, Ben J.; Palmer, Carolyn G.; Jooste, Sebastian; Warne, Michael St. J.; Nugegoda, Dayanthi

doi:10.1080/10807030500257770

Cited by 63 publications

(66 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With increasing numbers of new and untested chemical compounds reaching the environment, there is an urgent need for more rapid ecotoxicology approaches than the traditional singlespecies tolerance tests (5,6). The application of high-throughput sequencing and qPCR technologies used in this study evaluated the sensitivity of more than 1,700 species, across 266 families, from 39 separate phyla.…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

“…The confidence surrounding five to 10 model organisms accurately representing the sensitivity of an ecosystem is also questionable (5,6). Further, the selection criterion of model organisms has resulted in a bias toward temperate and Northern Hemisphere species, to the exclusion of rare and often sensitive species (6). In the Antarctic and subantarctic regions, traditional toxicology indicator species, such as earthworms and large invertebrates, are sparse or nonexistent, further compounding the uncertainty surrounding the application of traditional tolerance testing "model" organisms.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Bacterial Targets as Potential Indicators of Diesel Fuel Toxicity in Subantarctic Soils

Dorst

Siciliano

Winsley

et al. 2014

Appl Environ Microbiol

View full text Add to dashboard Cite

cAppropriate remediation targets or universal guidelines for polar regions do not currently exist, and a comprehensive understanding of the effects of diesel fuel on the natural microbial populations in polar and subpolar soils is lacking. Our aim was to investigate the response of the bacterial community to diesel fuel and to evaluate if these responses have the potential to be used as indicators of soil toxicity thresholds. We set up short-and long-exposure tests across a soil organic carbon gradient. Utilizing broad and targeted community indices, as well as functional genes involved in the nitrogen cycle, we investigated the bacterial community structure and its potential functioning in response to special Antarctic blend (SAB) diesel fuel. We found the primary effect of diesel fuel toxicity was a reduction in species richness, evenness, and phylogenetic diversity, with the resulting community heavily dominated by a few species, principally Pseudomonas. The decline in richness and phylogenetic diversity was linked to disruption of the nitrogen cycle, with species and functional genes involved in nitrification significantly reduced. Of the 11 targets we evaluated, we found the bacterial amoA gene indicative of potential ammonium oxidation, the most suitable indicator of toxicity. Dose-response modeling for this target generated an average effective concentration responsible for 20% change (EC 20 ) of 155 mg kg ؊1 , which is consistent with previous Macquarie Island ecotoxicology assays. Unlike traditional single-species tolerance testing, bacterial targets allowed us to simultaneously evaluate more than 1,700 species from 39 phyla, inclusive of rare, sensitive, and functionally relevant portions of the community.

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Bacterial Targets as Potential Indicators of Diesel Fuel Toxicity in Subantarctic Soils

Dorst

Siciliano

Winsley

et al. 2014

Appl Environ Microbiol

View full text Add to dashboard Cite

show abstract

“…However Kefford et al (2005) have argued that it is more appropriate to use data for more species which may be derived using less precise techniques. The use of estimates of toxicity data generated using models, such as that proposed in this study, to derive WQGs is consistent with the use of species sensitivity distributions and the argument of Kefford et al (2005). In addition, estimates of toxicities generated by QSARs, are currently used to derive WQGs (e.g.…”

Section: Introductionmentioning

confidence: 98%

Simultaneous prediction of toxicity of multiple chemicals to multiple species using multi‐dimensional functional relationships

2008

Self Cite

View full text Add to dashboard Cite

SUMMARYA theoretical model is developed for the estimation of the toxicity of a large number of chemicals to a group of species for which the log-toxicity values have strong linear relationships. The model is a multi-dimensional functional relationship (FR) that allows for many missing values. It depends on an unobserved variate (denoted by j in the text), with a value for each chemical; for each species, the expectations of the log-toxicity values are each linearly related to j. There are worthwhile gains in multi-dimensional over the two-dimensional FRs hitherto used. The model is applied to data on the toxicity of 51 chemicals to 10 species. It allows for species to have unequal variance about their expectations. There is good prediction of log-toxicity from measurements on other species where only 30% of the combinations were measured even when the taxa are not closely related. Among the uses for this technique are (i) to predict toxicity for combinations of species and chemicals that have not been measured, (ii) to suggest a suitable range of concentrations for a new bioassay, (iii) identifying specificity, that is, chemicals that have a different relative toxicity for a particular species.

show abstract

“…The sample of species in the SSD is an unbiased sample of the communities for which conclusions will be drawn [4]. This assumption would appear to be rarely met in the conventional use of SSDs [6]. The number of species with sensitivity data included in the SSD is adequate [4].…”

Section: Introductionmentioning

confidence: 99%

A similarity‐index–based method to estimate chemical concentration limits protective for ecological communities

Kefford

Schäfer

Liess

et al. 2010

Enviro Toxic and Chemistry

Self Cite

View full text Add to dashboard Cite

A new method is presented to determine retrospectively proportional changes of species composition in a community at risk from particular concentrations of chemical stressors. The method makes estimates with some similarities to those claimed by species sensitivity distributions (SSDs) but is based on species presence/absence field data and requires assumptions that are more likely to be met. The method uses Jaccard's index (JI), the proportion of species in common to two samples. At a similar level of contamination, the occurrence of species is usually highly variable, and thus JI values between individual pairs of samples can be low. However, by pooling samples with a similar contamination level, an increasingly complete set of species present at this level of contamination is gained. Our method involves calculating JI between randomly selected groups of samples (pooled sample sets) with similar and different levels of contamination. It then relates changes in JI to the difference in contamination and produces estimates of the proportional change in species between preselected categories of contamination. The application of the method is illustrated by using data on riverine freshwater macroinvertebrates exposed to salinity in southeastern Australia; pesticide runoff potential in the Aller River Catchment, Germany; and metal pollution (principle Cu) in the Clark Fork River Catchment, Montana, USA.

show abstract

What is Meant by “95% of Species”? An Argument for the Inclusion of Rapid Tolerance Testing

Cited by 63 publications

References 57 publications

Bacterial Targets as Potential Indicators of Diesel Fuel Toxicity in Subantarctic Soils

Bacterial Targets as Potential Indicators of Diesel Fuel Toxicity in Subantarctic Soils

Simultaneous prediction of toxicity of multiple chemicals to multiple species using multi‐dimensional functional relationships

A similarity‐index–based method to estimate chemical concentration limits protective for ecological communities

Contact Info

Product

Resources

About