Carry-Over Effects Across Metamorphosis of a Pesticide on Female

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Carry-over effects across metamorphosis of a pesticide on female lifetime fitness strongly depend on egg hatching phenology: a longitudinal study under seminatural conditions Nedim Tüzün, and Robby Stoks Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04399 • Publication Date (Web): 07 Nov 2017 Downloaded from http://pubs.acs.org on November 12, 2017

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Environmental Science & Technology

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Carry-over effects across metamorphosis of a pesticide on female lifetime fitness strongly

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depend on egg hatching phenology: a longitudinal study under seminatural conditions

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Nedim Tüzün* and Robby Stoks

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Evolutionary Stress Ecology and Ecotoxicology, University of Leuven, Deberiotstraat 32, B-

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3000 Leuven, Belgium

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Corresponding author: [email protected]

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Abstract art


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Abstract

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Current ecological risk assessment of pesticides fails to protect aquatic biodiversity. For the first

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time, we tested two potential reasons for this failure with regard to carry-over effects across

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metamorphosis: their dependence on hatching period, and the lack of studies quantifying adult

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fitness under seminatural conditions. Using the damselfly Coenagrion puella sampled from six

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populations, we designed an outdoor longitudinal one-year study starting from the egg stage. We

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exposed the aquatic larvae to the pesticide esfenvalerate (0.11 µg/L) during the initial microcosm

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part. Next, we monitored the lifetime fitness of the terrestrial adults in an insectary. Exposure to

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the pesticide negatively impacted not only larval traits, but also drastically reduced lifetime

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mating success of adult females. The impact of this post-metamorphic effect of the pesticide on

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the population level was three times more important than the effects in the larval stage.

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Importantly, this carry-over effect was only present in females that hatched early in the season,

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and was not mediated by metamorphic traits (age and mass at emergence). We provide proof-of-

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principle under seminatural conditions for two potential pitfalls that need to be considered when

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improving risk assessment: carry-over effects on adult fitness can (i) be much more important

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than effects during the larval stage and may not be captured by metamorphic traits, and (ii) be

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strongly modulated by egg hatching dates.

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Introduction

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Improving ecological risk assessment of pesticides is a major challenge as it currently fails to

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protect aquatic biodiversity.1,2 One possible reason for this failure is that pollutant effects may

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persist after metamorphosis in the many animals with a complex life cycle.3,4 The fate of a



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pollutant-exposed population heavily depends on lifetime fitness values of its individuals, and

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cannot be accurately judged by pre-adult traits.5 Studies of pollutant effects across

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metamorphosis, however, rarely explicitly quantified adult fitness components (but see ref 4).

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Instead, they focused on metamorphic traits such as age and mass at metamorphosis which do

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not accurately predict the effects of larval stressors on adult fitness.6–8

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Another major factor limiting risk assessment is that studies on carry-over effects of

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pesticides are mostly limited to one population sampled at one moment in time. As a result, the

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widespread temporal variation in egg hatching dates within populations6,9 is neglected in

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ecotoxicology. The time constraints imposed on late-hatching larvae can, however, strongly

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modify carry-over effects of ecological stressors.6,9–11 This is usually assumed to be a result of

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reallocation of resources due to the accelerated growth and development imposed by time

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constraints.

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To advance our insights in pesticide-induced carry-over effects, we carried out a

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longitudinal one-year study starting from the egg stage where we exposed the aquatic larvae of a

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damselfly to a pesticide pulse and studied not only effects during the larval stage and at

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metamorphosis, but also explicitly quantified fitness after metamorphosis in the terrestrial adult

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stage. To specifically assess the importance of within-season temporal variation modulating

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carry-over effects, we exposed in each of the six sampled populations two cohorts that differed

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ca. 40 days in their natural hatching period. Given that effects of pesticides are ideally measured

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under conditions as natural as possible,12 and to obtain realistic estimates of fitness (cfr. ref 13),

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we integrated an outdoor microcosm part for the larval stage with a large outdoor insectary part

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for the adult stage. As pesticide, we chose the pyrethroid insecticide esfenvalerate, one of the

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most widely applied pyrethroids14,15 that can cause carry-over effects in damselflies.16,17 We 4 ACS Paragon Plus Environment

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applied three pulses (with three-day intervals) of esfenvalerate with a concentration of 0.11 µg/L.

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As study species we chose the damselfly Coenagrion puella which is common in Europe,18 and

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known to react to time constraints by accelerating growth and development rates.19

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Materials and methods

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Study species and populations

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To capture regional variation in life history, we sampled damselflies from six populations,

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situated in both urban and more natural settings in Flanders, Belgium (Appendix S1). We

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collected eggs from each of the six populations in each of two periods, 13 – 22 June (“early

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period”), and 23 – 31 July 2014 (“late period”), matching the peak and the end of the flight

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season in Flanders, respectively. This resulted in two cohorts differing ca. 40 days in egg

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hatching time. Given the average lifespan of adult C. puella is ca. 20 days20 (see also Results),

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the two collected cohorts derived from parents that do not overlap in flight period. We collected

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eggs from 5-10 mated females from each pond in each period. Eggs from the early and late

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periods hatched during 4 – 12 July and 16 – 19 August 2014, respectively. To increase survival,

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we reared the larvae in laboratory conditions for the first three weeks. Larvae were kept per

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female together in plastic containers filled with 1.5 L of dechlorinated tap water in a

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temperature-controlled room at 20 °C with a photoperiod of 14:10 h light:dark. Larvae were fed

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Artemia nauplii ad libitum five days a week.

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General experimental procedure

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Following the three weeks period in the laboratory, the longitudinal one-year study consisted of

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two integrated outdoor parts. In the first, outdoor microcosm part, we set up a full factorial

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experiment consisting of 2 hatching periods (early and late) × 2 pesticide treatments (control and 5 ACS Paragon Plus Environment


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0.2 µg/L esfenvalerate). This part ran from summer 2014 until spring 2015 (with a short indoor

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part to avoid winter freezing; see below). The pesticide application was carried out in May 2015,

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which is within the main application period of agricultural pesticides in the study region.21

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During this period all animals were still in the larval stage. As in nature, all larvae were

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simultaneously exposed to the pesticide irrespective of their egg hatching date the previous

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summer. In the second, outdoor insectary part, adults that emerged from the microcosms were

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placed in a single outdoor insectary where we monitored adult life-history traits and lifetime

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mating success. This part ran from late spring to summer 2015.

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Outdoor microcosm part

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Each of the four hatching period × pesticide treatment combinations was replicated in twelve

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microcosms, giving a total of 48 microcosms. The set of twelve replicated microcosms per

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treatment combination consisted each time of two microcosms of each of the six populations.

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Hence, each microcosm contained larvae from a single population. Microcrosms were 10 L

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polypropylene containers filled with 3 L dechlorinated tap water and 3 L of water from an

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adjacent pond (filtered through a 500 µm mesh). Microcosms were placed at an outdoor

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experimental area in Heverlee, Belgium.

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To allow the development of Daphnia and protozoan populations (food resource for the

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small damselfly larvae), the microcosms were set up ca. two weeks prior to the introduction of

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the larvae. We inoculated each container with ca. 300 D. magna. In addition, we added grass to

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stimulate growth of protozoa. We covered each container with a net to prevent predators entering

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and adult damselflies escaping.


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We introduced 30 C. puella larvae in each container (in total 1,440 larvae), corresponding

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to typical field densities of coenagrionid damselfly larvae.22 We introduced the larvae of each

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period when ca. three weeks old (26-27 July 2014 for the early period and 6-7 September 2014

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for the late period), thereby maintaining the ca. 40 day difference in hatching dates of the two

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cohorts. Throughout the outdoor microcosm experiment, we provided larvae with ad libitum

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food by adding weekly ca. 300 D. magna obtained from outdoor stock tanks. We reduced the

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feeding frequency to biweekly during periods when temperatures dropped below 10 °C, as larval

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growth of the study species ceases at these temperatures.23 To prevent freezing, we moved the

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microcosms to an unheated indoor facility for 45 days during 27 December 2014 – 12 February

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2015, when outdoor temperatures dropped below 0 °C. Daily mean water temperatures when

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placed inside were ca. 4.3 °C (see also Fig. S2 in Appendix S2). Afterwards, microcosms were

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placed again outside.

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Starting 4 May 2015, we applied three pesticide pulses to half of the microcosms, with

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three days between pulses. This simulates spring pesticide applications and the associated run-off

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in nearby surface waters.24 The nominal esfenvalerate concentration of 0.2 µg/L induces

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mortality and reduces growth rate in another Coenagrion damselfly.16 Although this

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concentration exceeds the predicted environmental concentrations (e.g. 0.06 µg/L for a realistic

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scenario25), it falls within the range of esfenvalerate concentrations detected in natural water

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bodies, e.g. in Denmark (up to 0.66 µg/L, ref 26) and the USA (up to 0.8 µg/L, refs 27–29).

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Moreover, regulatory surface water models, even when simulating most realistic scenarios,

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strongly underpredict measured field concentrations; especially for hydrophobic insecticides

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such as esfenvalerate.30 Importantly, our main aim was to test for a proof-of-principle for carry-

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over effects of pesticides and their dependence on the hatching period, rather than fine tuning the



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specific risk assessment of esfenvalerate. We initially prepared a 2 × 105 µg/L stock solution by

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dissolving 1 mg esfenvalerate powder (purity >99%, Sigma-Aldrich) in 5 mL absolute ethanol.

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This stock solution was further diluted with filtered pond water (mesh size: 500 µm) to obtain a

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spraying solution with a concentration of 24 µg/L. Fifty millilitre of this spraying solution was

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gently poured over the surface of the microcosms to obtain the nominal esfenvalerate

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concentrations of 0.2 µg/L. For the control treatment, we added 50 mL of ethanol dissolved in

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filtered pond water with a concentration of 24 µL/L ethanol, i.e. the ethanol concentration of the

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esfenvalerate treatment, to the microcosms. Growth and behavior of damselfly larvae are not

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affected by ethanol concentrations up to 5 × 103 µL/L (Lizanne Janssens, unpublished data). The

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esfenvalerate concentration in the containers 20 min after application was 0.11 µg/L, whereas

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after three days, just before the next pulse, the concentration was below the detection limit (
3 standard deviations from the

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mean), and was excluded from all analyses. For the analysis of post-exposure survival, we

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identified one microcosm from the late period - control treatment combination as an outlier (>3

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standard deviations from the mean) and excluded this microcosm from all analyses. To

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strengthen the interpretation of key results (see Results Lifetime mating success), we additionally

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calculated effect sizes estimated as Hedges’ d with 95% confidence intervals.38

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Path analyses



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We used structural equation modeling (SEM39) to test whether any potential effect of the

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pesticide treatment on LMS was operating directly, or was indirectly mediated via the

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metamorphic traits (age and mass at emergence). We specifically applied the path analysis

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approach, which is a SEM method that deals explicitly with observed variables. Our data

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included a non-normally distributed response variable (i.e. Poisson-distributed LMS), and was

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hierarchically structured (i.e. nested random effects). Therefore, we applied the piecewise SEM

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(or ‘generalized multilevel path analysis’) approach, which allows translating a path diagram into

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a set of GLMMs.40,41

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To specifically evaluate the role of direct and indirect effects of the pesticide, we built

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three candidate models: (1) the pesticide affects fitness only directly; (2) the pesticide affects

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fitness only indirectly via the metamorphic traits; and (3) the pesticide affects fitness both

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directly and indirectly (Fig. 1). As the pesticide effect on LMS was modulated by period (see

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results of GLMMs), we ran separate path models for early and late females with the pesticide

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treatment as the predictor variable. All models included paths going from age and mass at

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emergence to LMS. Further, to correct for potential density-mediated effects, we included paths

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going from larval density per microcosm to age and mass at emergence (results not shown). As

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the effects on LMS remained when the weather variables were removed from the GLMMs (data

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not shown), we did not include them in the path analysis. We included correlated errors between

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age and mass at emergence to capture the potential trade-off between both variables. The error

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structure and random effects of the GLMMs used to build the path models were identical to the

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ones used in the mean analyses (see above). For all path models, the categorical variable

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‘pesticide treatment’ was binary coded: control = 0, pesticide = 1. Hence, a negative path going


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from pesticide treatment to LMS, for example, should be interpreted as decreased LMS for

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pesticide-exposed females.

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We selected the most parsimonious among the three candidate path models using the

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AICc (Akaike Information Criterion, corrected for small sample size) implemented for path

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models.42 For this, we calculated and compared ∆AICc scores and relative support for each

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model (AICc weights), where lower AICc scores and higher AICc weights indicate better

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models.43 The overall fit of path models was evaluated with Shipley’s test of d-separation,40

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which tests for missing paths in the model. Using the combined significance of these unrealized

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paths, a Fisher’s C statistic is calculated and compared to a χ2 distribution to reject (P < 0.05) or

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accept (P > 0.05) the model.

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All analyses were performed using R version 3.3.2.44 We used the ‘lme4’45 and ‘nlme’46

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packages for GLMMs, the ‘car’ package47 for testing fixed effects with Wald- χ2, the

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‘piecewiseSEM’ package41 for conducting path analyses, the ‘MuMIn’ package48 to calculate

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AICc weights, and the ‘effsize’ package49 to estimate Hedges’ d. We report standardized

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coefficients for the path models. Mass at emergence and lifespan were log-transformed to meet

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model assumptions.

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Results and discussion

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Below we report effects of pesticide exposure and hatching period on life-history traits. For full

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details of the statistical analyses, including results for covariates, see Appendix S4.

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Larval life history and metamorphic traits



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Larval survival prior to pesticide exposure was ca. 79% and independent of hatching period.

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During the pesticide exposure period, survival was reduced from ca. 89% (of the 79% pre-

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exposure survival) in the control group to ca. 81% in the pesticide-exposed group (χ12 = 11.60, P

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= 0.001, Fig. 2a). Hatching period (χ12 = 2.87, P = 0.090) and its interaction with pesticide

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treatment (χ12 = 0.43, P = 0.514) did not influence survival during the pesticide exposure period.

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Pesticide exposure reduced larval growth (χ12 = 21.15, P < 0.001, Fig. 2b). Larvae from the late

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period (‘late larvae’) had faster growth rates during the exposure period than larvae from the

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early period (‘early larvae’) (χ12 = 6.73, P = 0.009, Fig. 2b), and this did not depend on the

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pesticide treatment (pesticide × period: χ12 = 0.11, P = 0.739). Pesticide exposure negatively

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affected post-exposure survival (χ12 = 8.37, P = 0.004, Fig. 2c). Likewise, late larvae had a lower

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survival during the post-exposure period than early larvae (χ12 = 12.22, P < 0.001, Fig. 2c). The

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interaction of pesticide treatment and hatching period did not influence post-exposure survival

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(χ12 = 1.55, P = 0.212).

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Age at emergence strongly differed between individuals of the two hatching periods (χ12

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= 172.25, P < 0.001), with late females developing ca. 28 days faster compared early females

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(Fig. 3a). Pesticide exposure (χ12 = 1.17, P = 0.279) and its interaction with hatching period (χ12 =

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0.34, P = 0.560) did not influence age at emergence. Damselflies from the pesticide treatment

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and late hatching group emerged with a slightly lower mass compared to the control and early

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group, respectively, yet these effects were marginally non-significant (pesticide treatment: χ12 =

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3.43, P = 0.064; hatching period: χ12 = 3.12, P = 0.077, Fig. 3b). The interaction of pesticide

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treatment and hatching period did not influence mass at emergence (χ12 = 0.27, P = 0.600).

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As expected, the chosen dose of esfenvalerate reduced survival both during and after the exposure period. This matches studies at similar esfenvalerate concentrations in aquatic 14 ACS Paragon Plus Environment

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insects,14,50–52 including damselflies.16,17 Likewise, the pesticide reduced the growth rate,

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possibly due to energy re-allocation to detoxification.52

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As predicted by life history theory on time constraints,53,54 late-hatched larvae developed

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and grew faster than early-hatched larvae. There is ample empirical support for this pattern from

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a wide range of taxa,55 particularly from studies with anurans11,56 and damselflies.57,58 This

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accelerated life history decreased post-exposure survival. Similarly, survival until emergence

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was lower in late compared to early larvae in the damselfly Lestes sponsa,59 and may reflect the

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trade-off between growth and survival.60

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Lifetime mating success

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Of the adults released in the insectary, 68 of the 248 females mated at least once. Pesticide

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exposure and hatching period did not affect lifespan (see Appendix S5). While the main effects

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of pesticide (χ12 = 0.15, P = 0.707) and period (χ12 = 0.05, P = 0.819) were not significant, female

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LMS was modulated by a significant pesticide × period interaction (χ12 = 4.38, P = 0.036, Fig.

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3a,b): previous pesticide exposure reduced LMS of early females with ca. 60% (Hedges’ d = -

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0.391, 95% CI: [-0.725, -0.058]), while, if anything, the pesticide seemed to have a positive

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effect on LMS of late females (Hedges’ d = 0.235, 95% CI: [-0.158, 0.627]). This drastic

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negative pesticide effect on female LMS was not mediated via the metamorphic traits (the ‘direct

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paths only’ model was the best supported model, Table S5 in Appendix S6). Indeed, the model

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for early females revealed that the pesticide exposure had a direct negative effect on LMS (as

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indicated by the significant negative path coefficient, Fig. 3c, Table S6). Further, increasing mass

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and age at emergence resulted in a higher LMS. The model for late females confirmed the

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pesticide had no significant effect on their LMS (Fig. 3d, Table S6).



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A key finding was that the negative effects of larval pesticide exposure carried over to the

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adult stage and decreased LMS in early females. This result adds to the mounting evidence of

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carry-over effects and their impact on fitness.61,62 This is in line with effects of esfenvalerate

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often being detected long after the exposure period ends,50,63–65 and being able to bridge

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metamorphosis16,66,67 (but see ref 63). The path analysis indicated that this effect was not

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mediated via pesticide effects on mass or age at emergence. This is in contrast with the

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assumption that reduction in fitness due to exposure to a stressor should be operating by

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affecting these two key metamorphic traits.53,54 Although the mechanisms underlying latent

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effects of pesticides are not fully understood, pesticide-mediated reductions in adult energy

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reserves50,65 may be responsible. We hypothesize this ‘hidden’ carry-over effect on female

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fitness is mediated by negative effects of esfenvalerate on fat and flight muscle mass, two flight-

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related traits that are impaired by this pesticide in damselflies,16,67 thereby reducing the flight

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performance. Similarly, studies documenting negative effects of contaminants on mating

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success, for example in fish,68 birds,69 bed bugs,70 and moths71 suggest impaired reproductive

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behavior as the underlying mechanism. Compared to early females, the LMS of late females did

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not seem to be as strongly influenced by the pesticide; possibly because more vulnerable late

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larvae were already eliminated during metamorphosis (i.e. lower post-exposure survival in the

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late period). The apparent positive effect of the pesticide exposure on late period animals (Fig.

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4b) may be a hormetic response, not uncommon in ecotoxicology,72 operating via a mechanism

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not identified in the present study.

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General implications for risk assessment of pesticides

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Using a powerful longitudinal design that integrated an exposure part in microcosms with the

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monitoring of lifetime fitness in a large outdoor insectary, our study provides the first data on 16 ACS Paragon Plus Environment

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carry-over effects of a pesticide across metamorphosis on adult lifetime fitness under seminatural

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conditions. Although the here used concentration of esfenvalerate (0.11 µg/L) is ca. two times

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higher than the predicted environmental concentration based on worst-case scenarios25,

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regulatory surface water models simulating realistic scenarios strongly underpredict actual

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measured field concentrations; especially for hydrophobic insecticides such as esfenvalerate.30

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This is in agreement with several studies reporting substantially higher (up to 0.8 µg/L)

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esfenvalerate concentrations in natural water bodies.26–29 Nevertheless, our aim was to test under

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seminatural conditions for mechanisms possibly responsible for the failure of current risk

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assessment of pesticides in general (detailed below), rather than fine tuning regulatory limits for

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esfenvalerate.

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Aquatic habitats are usually dominated by insects with complex life cycles, i.e. with

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aquatic larvae metamorphosing into terrestrial adults. Although current water quality standards

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acknowledge latent effects of pesticide exposure,73 they do not explicitly take into account carry-

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over effects across metamorphosis, hence assume that protection of aquatic stages translate to the

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protection of adults. We provide a proof-of-principle that this assumption is not met, and suggest

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that the current guidelines would have erroneously concluded the pesticide effect to be weak if

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looking only at responses at the larval stage (for metals 4,74). Notably, a simple simulation based

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on our results and the general relationships between fitness components and the number of

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offspring that reaches adulthood (based on studies in a natural C. puella population 33,36) revealed

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that when including the carry-over effects, the pesticide treatment is expected to reduce the

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number of offspring reaching maturity by more than three times (see Appendix S7 for details of

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the simulation). Importantly, this simulation shows that the pesticide-induced mortality in the

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larval stage accounted only for ca. 24% of the total impact on the population in the next



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generation, while the rest of the impact was captured by variation in LMS (Appendix S7). These

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delayed effects after metamorphosis could not be predicted by effects on the two key

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metamorphic traits (age and mass at metamorphosis), thereby violating the assumption of life

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history theory that metamorphic traits should predict the effects of stressors on adult fitness.75

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This further complements the few studies reporting that post-metamorphic traits are weak

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predictors of carry-over effects of ecological stressors on adult fitness.6–8 This argues against

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using mass and age at metamorphosis as proxies for effects on adult fitness in ecotoxicological

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studies,76–78 and underscores the importance of identifying the underlying mechanisms of carry-

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over effects.62,79

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We further identified an overlooked, yet important temporal component associated with

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time constraints strongly determining the impact of pesticide exposure. Indeed, the larval

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pesticide exposure affected lifetime fitness only in early-hatched females, and not in the more

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time-stressed late-hatched females. This large impact of hatching phenology is striking because

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pesticide exposure occurred ca. 10 months after egg hatching, thereby simulating the general

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scenario where aquatic insects that hatched in summer are exposed the next spring to pesticide

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pulses. Given the widespread variation in hatching periods in natural populations and the

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associated differences in time constraints,6,9 this is expected to be a general factor that may

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critically affect the consequences of pollutant exposure on adult fitness. Ecotoxicology tests on

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field-collected animals (as frequently done in mesocosm tests) typically ignore the hatching date.

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Hence, the here identified mechanisms may introduce considerable noise when animals differing

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in hatching period are being tested, and may explain differences between toxicological studies;

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even when using animals from the same study population.

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Supporting Information

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Information on study populations (S1), abiotic parameters (S2), and weather variables (S3), full

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details of the statistical analyses (S4), results for lifespan (S5), details of the path analyses (S6),

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explanations for the simulation to estimate pesticide effect at the population level (S7).

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Acknowledgments

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We thank Selina Müller for her dedicated help during the experiment, and Geert Neyens for

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setting up the insectary. Comments from four anonymous reviewers considerably improved our

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manuscript. Financial support came from the Belspo project SPEEDY (IAP- project P7/04) and

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research grants from the KU Leuven (PF/2010/07 and C16/17/002) and the FWO research

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network EVENET.

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References

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589



590

Figure legends

591

Figure 1. Candidate path models used to test whether the effect of a predictor on lifetime mating

592

success (LMS) of the damselfly Coenagrion puella is (a) direct, (b) indirect, or (c) both direct

593

and indirect. The predictor in the models was selected based on linear mixed effect analyses of

594

treatment means (see main text for details). Double-headed arrows are partial correlations

595

between traits.

596

Figure 2. Larval survival (a), growth rate (b), and post-pesticide exposure survival (c) of the

597

damselfly Coenagrion puella as a function of pesticide treatment and hatching period. Growth

598

rate is controlled for initial mass. Note that larval survival during exposure (a) was calculated

599

based on larvae that survived the winter (79%, see Results). Given are least square means ± 1

600

SE.

601

Figure 3. Metamorphic traits (age at emergence (a) and mass at emergence (b)) for the females

602

of the damselfly Coenagrion puella as a function of pesticide treatment and hatching period.

603

Both traits are controlled for larval density in the microcosms. Given are least square means ± 1

604

SE.

605

Figure 4. Lifetime mating success (LMS) as a function of pesticide treatment (a,b) and path

606

diagrams depicting the effects of the pesticide treatment on life-history traits and LMS (c,d) for

607

the females of the damselfly Coenagrion puella. Separately shown are plots and path diagrams

608

for the early hatching period (a,c) and late hatching period (b,d). Given are least square means ±

609

1 SE for the upper plots. Pesticide treatment was significant in the early period (*), but not in the

610

late period (NS). Dashed grey lines indicate non-significant paths, whereas double-headed

611

arrows are partial correlations between traits. Binary coding for pesticide treatment in the path


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612

model: control = 0, pesticide = 1. Standardized path coefficients are given next to the arrows (see

613

Table S6 for details).



614 615

Figure 1.


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616 617

Figure 2.



618 619

Figure 3


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620

621 622

Figure 4


Carry-Over Effects Across Metamorphosis of a Pesticide on Female

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