Importance of Population Structure at the Time of Toxicant Exposure

Stark, John D.; Banken, Julie A. O.

doi:10.1006/eesa.1998.1760

Cited by 83 publications

(65 citation statements)

References 18 publications

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“…The sublethal effects on population growth rate after exposure to insecticides are highly influenced by the starting population structure. Because different insect stages/ages may present different susceptibilities to toxicants, it is essential to consider this factor to estimate the population susceptibility [52].…”

Section: Demographic Studies For the Assessment Of Insecticide Subletmentioning

confidence: 99%

The Sublethal Effects of Insecticides in Insects

França¹,

Brêda²,

Barbosa³

et al. 2017

Biological Control of Pest and Vector Insects

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Studies related to the effect of insecticides on insect pests and nontarget organisms, such as natural enemies, are traditionally accessed by the estimative of lethal effects, through mortality data. Due to the limitations of the traditional methods, recent studies in the past three decades are assessing the sublethal effects of insecticides upon several important biological traits of insect pests and natural enemies. Besides mortality, the sublethal dose/concentrations of an insecticide can affect insect biology, physiology, behavior and demographic parameters. In this chapter, many sublethal effects of insecticides were addressed for several chemical groups, such as botanical insecticides, carbamate, diamide, insect growth regulators, neonicotinoid, organochlorides, organophosphates, pyrethroid and others. An accurate assessment of these effects is crucial to acquire knowledge on the overall insecticide efficacy in the management of pest insect populations, as well as on their selectivity toward nontarget organisms.

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Section: Demographic Studies For the Assessment Of Insecticide Subletmentioning

confidence: 99%

The Sublethal Effects of Insecticides in Insects

França¹,

Brêda²,

Barbosa³

et al. 2017

Biological Control of Pest and Vector Insects

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“…However, this design is not appropriate for determining the mechanistic bases of toxicant-density effects that link individual performance to population dynamics. Starting conditions, such as whether the population is initiated with juveniles, adults, or with a stable age distribution will also influence population development and need to be considered carefully (Stark and Banken 1999). Decisions about sampling frequency and protocol (i.e., harvesting entire replicates or subsampling replicates repeatedly over time) will also have to be made on a case-by-case basis.…”

Section: The Importance Of Experimental Designmentioning

confidence: 99%

Toxicant Impacts on Density-Limited Populations: A Critical Review of Theory, Practice, and Results

Forbes

Sibly

Calow

2001

Ecological Applications

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Abstract. Most natural populations experience some density dependence, and longterm average rates of population growth are likely to be close to zero (i.e., steady state). An essential question, therefore, is how and to what extent do density-dependent effects influence the responses of populations to toxicant impacts? Here we consider three general types of interaction between density dependence and toxicant effects: additive, less than additive, and more than additive. If we know enough about the life-history dynamics of an organism and how its life-history traits are affected by density and toxicant exposure, we should be able to use life-history models to predict responses of populations living under density-dependent control to chemical exposure. However, because the number of factors influencing the outcome is large, we demonstrate that simple, general, a priori predictions are not feasible. A review of the literature confirms that a variety of interactions has been observed in experimental systems. It is essential that experiments are designed so that the interactions of interest can be determined. We review these critically. Experimental designs that are appropriate for exploring density-toxicant interactions on individual physiological performance may be unable to detect potential compensatory interactions at the population level. Designs most likely to simulate the dynamics of field populations will be unable to determine the mechanistic bases underlying population-level impacts. To facilitate an ecologically correct interpretation of density-toxicant interactions, it is therefore essential that the limitations of the chosen experimental designs be recognized and made explicit.

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“…The most common population-level measure of toxicity is its effect on the popula-tion growth rate (PGR), which can be expressed as the continuous growth rate r per unit time, or by the discrete multiplicative rate, λ, where λ = e r (Hansen et al, 1999;Stark and Danken, 1999;Forbes et al, 2000;Kuhn et al, 2000;Stark and Vargas, 2003;Stark, 2005). Forbes and Calow (1999) concluded that the PGR is a better response variable than individual-level endpoints, such as condition factor or fecundity, since r explicitly integrates individual-level responses to contaminants at the population level.…”

Section: Approaches To Quantifying Toxicity In Aquatic Organismsmentioning

confidence: 99%

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

Gledhill

Kirk

2011

Ecological Modelling

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MODELING EFFECTS OF TOXIN EXPOSURE IN FISH ON LONG-TERM POPULATION SIZE, WITH AN APPLICATION TO SELENIUM TOXICITY IN BLUEGILL (LEPOMIS MACROCHIRUS)Michelle Gledhill A primary goal in ecotoxicology is the prediction of population-level effects of contaminant exposure based on individual-level response. Assessment of toxicity at the population level has predominately focused on the population growth rate (PGR), but the PGR may not be a relevant toxicological endpoint for populations at equilibrium. Equilibrium population size may be a more meaningful endpoint than the PGR because a population with smaller equilibrium (i.e., long-term mean) size is more susceptible to the negative effects of environmental variability. I address the ecotoxicology individual-to-population extrapolation problem with modeling. I developed and analyzed a general model applicable to many freshwater fish species that includes density-dependent juvenile survival and additional juvenile mortality due to toxicity exposure, and I quantified its effect on equilibrium population size as a means of assessing toxicity. I then used selenium toxicity in bluegill sunfish as an example to assess the effects of environmental stochasticity on toxicity response with simulation modeling. Individual-level effects are typically greater than population-level effects until the individual effect is large, due to compensatory density-dependent relationships. These effects are sensitive to the recruitment potential of a population, in particular the low-density first-year survival rate S b . Assuming high S b could result in underestimating effects of population-level toxicity. The equilibrium size depends directly on S b , the reproductive potential, the toxin concentration at which mean mortality is 50% (LC 50 ), and iii the rate at which individual mortality increases with increasing toxin concentration. More experimental data are needed to decrease the uncertainty in estimating these parameters.Effects of environmental variability resulted in simulated extinctions at much lower toxin concentrations than predicted deterministically. iv ACKNOWLEDGEMENTS

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Importance of Population Structure at the Time of Toxicant Exposure

Cited by 83 publications

References 18 publications

The Sublethal Effects of Insecticides in Insects

The Sublethal Effects of Insecticides in Insects

Toxicant Impacts on Density-Limited Populations: A Critical Review of Theory, Practice, and Results

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

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