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A tale of two metrics: the EPA Risk Quotient Approach versus the delay in Population Growth Index for determination of pesticide risk to aquatic species

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Abstract

The potential risk that two closely related insecticides, spinetoram and spinosad, posed to three Cladoceran species, Ceriodaphnia dubia, Daphnia pulex, and D. magna was determined using two approaches, the USEPA Risk Quotient method and the Delay in Population Growth Index (DPGI). Results of the RQ method showed that spinetoram posed a risk to all three species, but spinosad posed a risk only to C. dubia. The DPGI analysis showed that exposure to spinetoram resulted in populations of all three species being delayed ≥ 3 generation times. Exposure to the LC50 and the lower 95% CL resulted in delayed populations while exposure to the upper 95% CL concentration of spinetoram resulted in no recovery of any of the three species over the course of the modeling exercise (88 d). Exposure to the lower and upper 95% Cl and the LC50 of spinosad resulted in C. dubia populations being delayed ≥ 3 generations. D. pulex populations were not negatively affected after exposure to spinosad. D. magna populations were delayed ≥ 3 generations, but only after exposure to the upper 95% Cl of spinosad. These results illustrate that although the EPA risk quotient method indicated that spinetoram posed a risk to all three species and that spinosad only posed a risk to C. dubia, the DPGI showed that D. magna would be negatively affected by spinosad and none of the three species would reach a predetermined number of individuals after exposure to the upper 95% CL of spinetoram. Because the DPGI uses the 95% Cl as well as the LC50 in its calculation and produces a measure of population growth it provides more detailed information in terms of the potential risk of pesticides to populations than the RQ method.

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All data and models are available upon request to the authors

References

  • Akçakaya HR (2005) RAMAS metapop: viability analysis for stage-structured metapopulations (version 5.0). Applied Biomathematics, Setauket, New York, NY

    Google Scholar 

  • Banks J, Stark JD (1998) What is ecotoxicology? An ad-hoc grab bag or an interdisciplinary science? Integr Biol 5:195–204

    Article  Google Scholar 

  • Banks JE, Stark JD (2009) Ecotoxicology: life history data and population models. Ecotoxicology Research Developments. In: Santos, EB (ed) Ecotoxicology Research Developments. Nova Science Publishers, Hauppauge, New York

  • Banks JE, Dick LK, Banks HT, Stark JD (2008) Time-varying disturbance parameters in ecology: an alternative to matrix models. Ecol Model 210:155–160

    Article  Google Scholar 

  • Banks JE, Ackleh A, Stark JD (2010) The use of surrogate species in risk assessment: using life history data to safeguard against false negatives. Risk Anal 30:175–182

    Article  Google Scholar 

  • Banks JE, Stark JD, Vargas RI, Ackleh A (2011) Parasitoids and ecological risk assessment: can toxicity data developed for one species be used to protect an entire guild? Biol Control 59:336–339

    Article  Google Scholar 

  • Banks JE, Stark JD, Vargas RI, Ackleh AS (2014) Deconstructing the surrogate species concept: a life history approach to the protection of ecosystem services. Ecol Appl 24:770–778

    Article  Google Scholar 

  • Banks J, Vargas R, Ackleh A, Stark JD (2017) Sublethal effects in pest management: a surrogate species perspective on fruit fly control. Insects 8:78. https://doi.org/10.3390/insects8030078

    Article  Google Scholar 

  • Banks J, Ackleh A, Veprauskas A, Stark JD (2019) The trouble with surrogates in risk assessment: a daphniid case study. Ecotoxicology 28:62–68

    Article  CAS  Google Scholar 

  • Barnthouse LW (2009) Quantifying population recovery rates for ecological risk assessment. Environ Toxicol Chem 23:500–508

    Article  Google Scholar 

  • Bhat VS, Meek ME, Valcke M, English C, Boobis A, Brown R (2017) Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; increasing utility and facilitating regulatory acceptance. Crit Rev Toxicol 47(9):733–753. https://doi.org/10.1080/10408444.2017.1303818

    Article  CAS  Google Scholar 

  • Billoir E, Pery ARR, Charles S (2008) Integrating the toxic and sublethal effects of toxic compounds into the population dynamics of Daphnia magna:Acombination of the DEBtox and matrix population models. Ecol Model 203:204–214

    Article  CAS  Google Scholar 

  • Baveco JMH, Norman S, Roessink I, Galic N, Van den Brink PJ (2014) Comparing population recovery after insecticide exposure for four aquatic invertebrate species using models of different complexity. Environ Toxicol Chem 33:1517–28

    Article  CAS  Google Scholar 

  • Dalkvist T, Topping CJ, Forbes VE (2009) Population-level impacts of pesticide-induced chronic effects on individuals depend more on ecology than toxicology. Ecotoxicol Environ Saf 72(6):1663–1672

    Article  CAS  Google Scholar 

  • Deardorff A, Stark JD (2009) Acute toxicity and hazard assessment of Spinosad and R-11 to three Cladoceran species and Coho salmon. Bull Environ Contam Toxicol 82:549–553

    Article  CAS  Google Scholar 

  • EPA (2007) Environmental Protection Agency 40 CFR Part 180 [EPA–HQ–OPP–2007–0876; FRL–8149–9] Spinetoram; Pesticide Tolerance. https://www.govinfo.gov/content/pkg/FR-2007-10-10/pdf/E7-19947.pdf

  • Federal Register (2005) Spinosad; notice of filing a pesticide petition to establish a tolerance for a certain pesticide chemical in or on food. Volume 70, Number 138. [Notices] [pp 41730–41735] From the Federal Register Online via GPO Access [wais.access.gpo.gov] [DOCID:fr20jy05–67]

  • Forbes VE, Calow P (2002) Population growth rate as a basis for ecological risk assessment of toxic chemicals. Philos Trans Biol Sci 357:1299–1306

    Article  Google Scholar 

  • Forbes VE, Calow P, Grimm V, Hayashi TI, Jager T, Katholm A, Palmqvist A, Pastorok R, Salvito D, Sibly R, Spromberg J, Stark JD, Stillman RA (2011) Adding value to ecological risk assessment with population modelling. Human Ecol Risk Assess 17:287–299.

    Article  CAS  Google Scholar 

  • Galm U, Sparks TC (2016) Natural product derived insecticides: discovery and development of spinetoram. J Ind Microbiol Biotechnol 43:185–193

    Article  CAS  Google Scholar 

  • Grimm V, Ashauer R, Forbes V, Hommen U, Preuss TG, Schmidt A, Van den Brink PJ, Wogram J, Thorbek P (2009) CREAM: a European project on mechanistic effect models for ecological risk assessment of chemicals. Environ Sci Pollut Res 16:614–617

    Article  Google Scholar 

  • Knillmann S, Stampfli NC, Noskov YA et al. (2012) Interspecific competition delays recovery of Daphnia spp. populations from pesticide stress. Ecotoxicology 21:1039–1049

    Article  CAS  Google Scholar 

  • Price PS, Keenan RE, Schwab B (1999) Defining the interindividual (intraspecies) uncertainty factor. Hum Ecol Risk Assess 5(5):1023–1033. https://doi.org/10.1080/10807039991289310

    Article  Google Scholar 

  • Sibly RM (1999) Efficient experimental designs for studying stress and population density in animal populations. Ecol Appl 9:496–503

    Article  Google Scholar 

  • Stark JD, Banks JE (2001) “Selective pesticides”: are they less hazardous to the environment? BioScience 51:980–982

    Article  Google Scholar 

  • Stark JD, Banks JE (2003) Population-level effects of pesticides and other toxicants on arthropods. Annu Rev Entomol 48:505–19

    Article  CAS  Google Scholar 

  • Stark JD, Banks JE, Vargas RI (2004) How risky is risk assessment? the role that life history strategies play in susceptibility of species to stress. Proc Natl Acad Sci USA 101:732–736

    Article  CAS  Google Scholar 

  • Stark JD, Vargas RI, Banks JE (2015) Incorporating variability in point estimates in risk assessment: bridging the gap between LC50 and population endpoints. Environ Toxicol Chem 34:1683–1688

    Article  CAS  Google Scholar 

  • Stark JD, Banks JE (2016) Developing demographic toxicity data: optimizing effort for predicting population outcomes in ecotoxicology. PeerJ 4:e2067. https://doi.org/10.7717/peerj.2067

    Article  Google Scholar 

  • Stark JD, Banks JE (2019) Comparative toxicity of the semi-natural insecticide Spinetoram (Delegate™) to three Cladoceran species. Biopestic Int 15:1–4

    Google Scholar 

  • USEPA (2004) Overview of the ecological risk assessment process in the Office of Pesticide Programs, U.S. Environmental Protection Agency: Endangered and Threatened Species Effects Determinations. https://www3.epa.gov/pesticides/endanger/consultation/ecorisk-overview.pdf

  • USEPA (2009) Office of Prevention, Pesticides and Toxic Substances (7505P) Spinetoram Pesticide Fact Sheet 2009. USEPA, Washington, DC

  • Van den Brink PJ (2013) Assessing aquatic population and community-level risks of pesticides. Environ Toxicol Chem 32:972–973. https://doi.org/10.1002/etc.2210

    Article  CAS  Google Scholar 

  • Wennergren U, Stark JD (2000) Modeling long-term effects of pesticides on populations: beyond just counting dead animals. Ecol Appl 10:295–302

    Article  Google Scholar 

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Acknowledgements

We thank Oriki and Grace Jack for help with carrying out the toxicity studies and collecting data.

Funding

Funding for this project was provided by Washington State University and California State University as partial salary and benefits for the authors

Author contributions

Both authors contributed equally to the development of this study, gathering of data, statistical analysis of the data and writing of the manuscript.

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Authors and Affiliations

  1. Ecotoxicology Program, Department of Entomology, Washington State University, Research and Extension Center, Puyallup, WA, 98371, USA

    John D. Stark

  2. California State University, Monterey Bay 100 Campus Center, Seaside, CA, 93955, USA

    John E. Banks

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  1. John D. Stark
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  2. John E. Banks
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Correspondence to John D. Stark.

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Stark, J.D., Banks, J.E. A tale of two metrics: the EPA Risk Quotient Approach versus the delay in Population Growth Index for determination of pesticide risk to aquatic species. Ecotoxicology 30, 1922–1928 (2021). https://doi.org/10.1007/s10646-021-02462-x

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