, Volume 22, Issue 7, pp 1085–1100 | Cite as

Can nutrients mask community responses to insecticide mixtures?

  • Alexa C. Alexander
  • Ana T. Luis
  • Joseph M. Culp
  • Donald J. Baird
  • Allan J. Cessna


The ecological effect of simultaneous exposure to two nutrient gradients, three insecticides and different predator intensities was investigated over a 3-week period in 80 outdoor, artificial streams using field-collected benthic invertebrates. The experimental design consisted of a 2 × 5 factorial structure with two nutrient levels (oligotrophic or mesotrophic) and five concentrations of the ternary insecticide mixture consisting of the insecticides (chlorpyrifos, dimethoate and imidacloprid). Equivalent toxic unit doses were summed to create a ternary insecticide dose (e.g., 0.1 + 0.1 + 0.1 = 0.3 TU) resulting in a range of ternary insecticide mixture toxicity (i.e., control groundwater, 0.3, 0.6, 0.9 and 1.2 TU). Two genera of insect predators, Gomphus spp. (Odonata) and Agnetina spp. (Plecoptera) were also added into each replicate stream, at densities and sizes comparable to those found at our collection site, to evaluate how the contribution of predators may change in nutrient limited (oligotrophic) versus amended (mesotrophic) systems. We describe a causal mechanism whereby the combined action of nutrients and insecticides reshaped aquatic community structure by interacting through multiple pathways. Specifically, mesotrophic conditions reduced the toxic effects of ternary insecticide mixtures for aquatic insects which, in some cases, appeared to increase abundance of aquatic insects. However, higher levels of insecticides in mesotrophic streams negated this effect and were even more toxic; for example, to aquatic insect grazers than the same insecticide doses in oligotrophic treatment levels. Effects of predators were only significant in oligotrophic streams. Evidence is provided as to how nutrient and contaminant interactions can greatly complicate the assessment of community level responses to insecticide mixtures due to direct and indirect effects of the resulting changes in the density of different genera and functional feeding groups within a community.


Nutrient masking Ternary insecticide mixtures Field collected benthic macroinvertebrate community Artificial streams Structural-equation model (SEM) 



We thank Bob Brua for his thoughtful review of an early draft of the manuscript. Jon Bailey at NHRC (Saskatoon) who conducted the chemical analyses. Also, Dave Hryn provided invaluable technical expertise and assistance in conducting the experiment. The authors declare that they have no conflict of interest. This work was supported in part by the Pesticide Science Fund awarded to Culp, Baird, Cessna and Alexander and an NSERC (PGS-D3 #362641) to ACA.


  1. Alexander AC, Culp JM (2013) Predicting the effects of insecticide mixtures on non-target aquatic communities. In: Trdan S (ed) Insecticides development of safer and more effective technologies. Intech Open Publishers, Rijeka.
  2. Alexander AC, Culp JM, Liber K, Cessna AJ (2007) Effects of insecticide exposure on feeding inhibition in mayflies and oligochaetes. Environ Toxicol Chem 26:1726–1732CrossRefGoogle Scholar
  3. Alexander AC, Heard KS, Culp JM (2008) Emergent body size of mayfly survivors. Fresh Biol 53:171–180Google Scholar
  4. Allan JD (1982) Feeding habits and prey consumption of three Setipalpian stoneflies (Plecoptera) in a mountain stream. Ecology 63(1):26–34CrossRefGoogle Scholar
  5. Allan JD (2004) Landscapes and riverscapes: the influence of land use on stream ecosystems. Ann Rev Ecol Evol Syst 35:257–284CrossRefGoogle Scholar
  6. Baekken T, Aanes KJ (1991) Pesticides in Norwegian agriculture. Their effects on benthic fauna in lotic environments (preliminary results). Int Ver Theor Angew Limnol Verh 24:2277–2281Google Scholar
  7. Biggs BJF (2000) Eutrophication of streams and rivers: dissolved nutrient–chlorophyll relationships for benthic algae. J N Am Benthol Soc 19:17–31CrossRefGoogle Scholar
  8. Campero M, Slos S, Ollevier F, Stoks R (2007) Sublethal pesticide concentrations and predation jointly shape life history: behavioral and physiological mechanisms. Ecol Appl 17:2111–2122CrossRefGoogle Scholar
  9. Cardinale BJ, Bennett DM, Nelson CE, Gross K (2009) Does productivity drive diversity or vice versa? A test of the multivariate productivity-diversity hypothesis in streams. Ecology 90:1227–1241CrossRefGoogle Scholar
  10. Carter JL, Resh VH, Hannaford MJ, Myers MJ (2006) Macroinvertebrates as biotic indicators of environmental quality. In: Hauer FR, Lamberti GA (eds) Methods in stream ecology, 2nd edn. Elsevier, Boston, pp 805–854Google Scholar
  11. Chambers JE, Meek EC, Chambers HW (2010) The metabolism of organophosphorus insecticides. In: Krieger R (ed) Hayes’ handbook of pesticide toxicology, 3rd edn. Academic Press, New York, pp 1399–1407CrossRefGoogle Scholar
  12. Cooper SD, Smith DW, Bence JR (1985) Prey selection by freshwater predators with different foraging strategies. Can J Fish Aquat Sci 42:1720–1732CrossRefGoogle Scholar
  13. Coors A, Decaestecker E, Jansen M, De Meester L (2008) Pesticide exposure strongly enhances parasite virulence in an invertebrate host model. Oikos 117:1840–1846CrossRefGoogle Scholar
  14. Culp JM, Baird DJ (2006) Establishing cause-effect relationships in multi-stressor environments. In: Hauer FR, Lamberti GA (eds) Methods in Stream Ecology, 2nd edn. Elsevier, Boston, pp 835–854Google Scholar
  15. Culp JM, Podemski CL, Cash KJ (2000) Interactive effects of nutrients and contaminants from pulp mill effluents on riverine benthos. J Aquat Ecosyst Stress Recovery 8:67–75CrossRefGoogle Scholar
  16. Culp JM, Cash KJ, Glozier NE, Brua RB (2003) Effects of pulp mill effluent on benthic assemblages in mesocosms along the Saint John River, Canada. Environ Toxicol Chem 22:2916–2925CrossRefGoogle Scholar
  17. Davis JM, Rosemond AD, Eggert SL, Cross WF, Wallace JB (2010) Long-term nutrient enrichment decouples predator and prey production. Proc Natl Acad Sci USA 107:121–126CrossRefGoogle Scholar
  18. Dodds WK, Jones JR, Welch EB (1998) Suggested classification of stream trophic state: distributions of temperate stream types by chlorophyll, total nitrogen, and phosphorus. Water Res 32:1455–1462CrossRefGoogle Scholar
  19. Dunn A (2004) A relative risk ranking of pesticides used in Prince Edward Island. Report EPS-5-AR-04-03. Environment Canada, Dartmouth, p 41Google Scholar
  20. EPA (2009) ECOTOX (ECOTOXicology) database, Version 4. U.S. Environmental Protection Agency, Office of Research and Development (ORD), and the National Health and Environmental Effects Research Laboratory’s (NHEERL’s) Mid-Continent Ecology Division (MED). Accessed 1 June 2009
  21. European Commission (2003) Technical guidance document on risk assessment in support of commission directive 93/67/EEC on risk assessment for new notified substances and commission regulation (EC) No. 1488/94 on risk assessment for existing substancesGoogle Scholar
  22. Forbes VE, Calow P (2002) Extrapolation in ecological risk assessment: balancing pragmatism and precaution in chemical controls legislation. Bioscience 52:249–257CrossRefGoogle Scholar
  23. Gilliom RJ (2007) Pesticides in U.S. streams and groundwater. Environ Sci Technol 41:3408–3414CrossRefGoogle Scholar
  24. Goedkoop W, Spann N, Akerblom N (2010) Sublethal and sex-specific cypermethrin effects in toxicity tests with the midge Chironomus riparius Meigen. Ecotoxicology 19:1201–1208CrossRefGoogle Scholar
  25. Grace JB (2006) Structural equation modeling and natural systems. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  26. Grimaldi S, Petroselli A, Serinaldi F (2012) Design hydrograph estimation in small and ungauged watersheds: continuous simulation method versus event-based approach. Hydrol Processes 26:3124–3134CrossRefGoogle Scholar
  27. Hall SR, Shurin JB, Diehl S, Nisbet RM (2007) Food quality, nutrient limitation of secondary production, and the strength of trophic cascades. Oikos 116:1128–1143Google Scholar
  28. Hoffman ER, Fisher S (1994) Comparison of a field and laboratory-derived population of Chironomus riparius (Diptera, Chironomidae) - biochemical and fitness evidence for population divergence. J Econ Entomol 87:320–325Google Scholar
  29. LeBlanc HMK, Culp JM, Baird DJ, Alexander AC, Cessna AJ (2012) Single versus combined lethal effects of three agricultural insecticides on larvae of the freshwater insect Chironomus dilutus. Arch Environ Contam Toxicol 63:378–390CrossRefGoogle Scholar
  30. Luis AT, Alexander AC, de Almeida SFP, da Silva EAF, Culp JM (2013) Benthic diatom communities in streams from zinc mining areas in continental (Canada) and mediterranean climates (Portugal). Water Quality Res J Can 48:180–191Google Scholar
  31. Matsuda K, Shimomura M, Ihara M, Akamatsu M, Sattelle DB (2005) Neonicotinoids show selective and diverse actions on their nicotinic receptor targets: electrophysiology, molecular biology, and receptor modeling studies. Biosci Biotechnol Biochem 69:1442–1452CrossRefGoogle Scholar
  32. McCann K, Hastings A, Huxel GR (1998) Weak trophic interactions and the balance of nature. Nature 395:794–797CrossRefGoogle Scholar
  33. McGrady-Steed J, Morin PJ (2000) Biodiversity, density compensation, and the dynamics of populations and functional groups. Ecology 81:361–373CrossRefGoogle Scholar
  34. Merritt RW, Cummins KW (1996) An introduction to the aquatic insects of North America. Kendall Hunt Pub, DubuqueGoogle Scholar
  35. Mishra SK, Pandey RP, Jain MK, Singh VP (2008) A rain duration and modified AMC-dependent SCS-CN procedure for long duration rainfall-runoff events. Water Resour Manag 22:861–876CrossRefGoogle Scholar
  36. Murphy C, Mutch JP, Reeves D, Clark T, Lavoie S, Rees H, Chow L, Nunn L, Hebb D (2006) Multi-media pesticide monitoring program in Prince Edward Island, New Brunswick and Nova Scotia. An Environment Canada Pesticide Science fund project final project report: 3 year monitoring report program—2003/04 to 2005/06. Environment CanadaGoogle Scholar
  37. Peckarsky BL (1982) Aquatic insect predator-prey relations. Bioscience 32:261–266CrossRefGoogle Scholar
  38. Peckarsky BL, Dodson SI (1980) Do stonefly predators influence benthic distributions in streams? Ecology 61:1275–1282CrossRefGoogle Scholar
  39. Peckarsky BL, Cowan CA, Penton MA, Anderson C (1993) Sublethal consequences of stream-dwelling predatory stoneflies on mayfly growth and fecundity. Ecology 74:1836–1846CrossRefGoogle Scholar
  40. Petersen DG, Sundback K, Larson F, Dahllof I (2009) Pyrene toxicity is affected by the nutrient status of a marine sediment community: implications for risk assessment. Aquat Toxicol 95:37–43CrossRefGoogle Scholar
  41. Pintor LM, Sih A (2011) Scale dependent effects of native prey diversity, prey biomass and natural disturbance on the invasion success of an exotic predator. Biol Invasions 13:1357–1366CrossRefGoogle Scholar
  42. Poff NL, Olden JD, Vieira NKM, Finn DS, Simmons MP, Kondratieff BC (2006) Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships. J N Am Benthol Soc 25:730–755CrossRefGoogle Scholar
  43. Relyea RA, Mills N (2001) Predator-induced stress makes the pesticide carbaryl more deadly to gray tree frog tadpoles (Hyla versicolor). Proc Natl Acad Sci USA 98:2491–2496CrossRefGoogle Scholar
  44. Schulz R (2004) Field studies on exposure, effects, and risk mitigation of aquatic nonpoint-source insecticide pollution: a review. J Environ Qual 33:419–448Google Scholar
  45. Schulz R, Dabrowski JM (2001) Combined effects of predatory fish and sublethal pesticide contamination on the behavior and mortality of mayfly nymphs. Environ Toxicol Chem 20:2537–2543CrossRefGoogle Scholar
  46. Shears NT, Ross PM (2010) Toxic cascades: multiple anthropogenic stressors have complex and unanticipated interactive effects on temperate reefs. Ecol Lett 13:1149–1159CrossRefGoogle Scholar
  47. Shipley B (2000) Cause and correlation in biology: a user’s guide to path analysis, structural equations and causal inference. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  48. Suhling F (1996) Interspecific competition and habitat selection by the riverine dragonfly Onychogomphus uncatus. Fresh Biol 35:209–217CrossRefGoogle Scholar
  49. Tilman D (1996) Biodiversity: population versus ecosystem stability. Ecology 77:350–363CrossRefGoogle Scholar
  50. Townsend CR, Uhlmann SS, Matthaei CD (2008) Individual and combined responses of stream ecosystems to multiple stressors. J Appl Ecol 45:1810–1819CrossRefGoogle Scholar
  51. Traas TP, van de Meent D, Posthuma L, Hamers T, Kater BJ, de Zwart D, Aldenberg T (2002) The potentially affected fraction as a measure of ecological risk (Chapter 16). In: Posthuma L, Suter GW, Traas TP (eds) Species sensitivity distributions in ecotoxicology. CRC Press, Boca Raton, pp 315–344Google Scholar
  52. Traas TP, Janse JH, Van den Brink PJ, Brock TCM, Aldenberg T (2004) A freshwater food web model for the combined effects of nutrients and insecticide stress and subsequent recovery. Environ Toxicol Chem 23:521–529CrossRefGoogle Scholar
  53. Underwood AJ (2002) Experiments in ecology: their logical design and interpretation using analysis of variance. Cambridge University Press, New YorkGoogle Scholar
  54. Usseglio-Polatera P, Bournaud M, Richoux P, Tachet H (2000) Biological and ecological traits of benthic freshwater macroinvertebrates: relationships and definition of groups with similar traits. Fresh Biol 43:175–205CrossRefGoogle Scholar
  55. van Wijngaarden R, Leeuwangh P, Lucassen WGH, Romijn K, Ronday R, van der Velde R, Willigenburg W (1993) Acute toxicity of chlorpyrifos to fish, a newt, and aquatic invertebrates. Bull Environ Contam Toxicol 51:716–723CrossRefGoogle Scholar
  56. Vinebrooke RD, Cottingham KL, Norberg MSJ, Dodson SI, Maberly SC, Sommer U (2004) Impacts of multiple stressors on biodiversity and ecosystem functioning: the role of species co-tolerance. Oikos 104:451–457CrossRefGoogle Scholar
  57. Walde SJ, Davies RW (1984) Invertebrate predation and lotic prey communities: evaluation of in situ enclosure/exclosure experiments. Ecology 65:1206–1213CrossRefGoogle Scholar
  58. Wesner JS (2012) Predator diversity effects cascade across an ecosystem boundary. Oikos 121:53–60CrossRefGoogle Scholar
  59. Westfall MJ, Tennessen KJ (1996) Chapter 12, Odonata. In: Merrit RW, Cummins KW (eds) An introduction to the aquatic insects of North America, 2nd edn. Kendall Hunt, Dubuque, pp 164–211Google Scholar
  60. Wooster D (1994) Predator impacts on stream benthic prey. Oecologia 99:7–15CrossRefGoogle Scholar
  61. Wooster D, Sih A (1995) A review of the drift and activity responses of stream prey to predator presence. Oikos 73:3–8CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Alexa C. Alexander
    • 1
    • 2
  • Ana T. Luis
    • 3
  • Joseph M. Culp
    • 2
    • 4
  • Donald J. Baird
    • 2
    • 4
  • Allan J. Cessna
    • 5
  1. 1.Canada Centre for Inland WatersBurlingtonCanada
  2. 2.Department of Biology at the University of New BrunswickFrederictonCanada
  3. 3.Geosciences DepartmentUniversity of AveiroAveiroPortugal
  4. 4.National Water Research Institute, Environment CanadaFrederictonCanada
  5. 5.National Hydrology Research Centre, Environment CanadaSaskatoonCanada

Personalised recommendations