Hazard/Risk Assessment

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1 Environmental Toxicology and Chemistry, Vol. 16, No. 5, pp , SETAC Printed in the USA /97 $ Hazard/Risk Assessment COMPARISON OF TWO POPULATION-LEVEL ECOTOXICOLOGICAL ENDPOINTS: THE INTRINSIC (r m ) AND INSTANTANEOUS (r i ) RATES OF INCREASE WILLIAM K. WALTHALL and JOHN D. STARK Washington State University, Puyallup Research and Extension Center, Puyallup, Washington 98371, USA (Received 26 March 1996; Accepted 18 September 1996) Abstract The instantaneous rate of increase (r i ) was compared to the intrinsic rate of increase (r m ) as an alternative populationlevel ecotoxicological endpoint. The terrestrial arthropod Acyrthosiphon pisum Harris, the pea aphid, was used as the model species and the new nicotinergic insecticide, imidacloprid, as the xenobiotic. In the first experiment, r m was generated each day from a life table for A. pisum neonates exposed to nontreated (control) potted broad bean, Vicia faba L. (variety Banner), and compared to determine the earliest r m which was not significantly different from the final r m. The r m for neonates introduced to nontreated plants was significantly different on days 6 and 7 but not significantly different between 8 to 40 d postintroduction. A second experiment examined the change in r i over time for neonates introduced at birth to nontreated broad bean and censused at 8, 11, 13, 15, 17, 19, and 21 d postintroduction. The r i for neonate populations introduced to nontreated broad bean peaked on days 11 and 19. The r i on nontreated beans was significantly different (p 0.05) from r m on days 8 and 15 but not significantly different at 11, 13, 17, 19, and 21 d. A third experiment was conducted comparing r m and r i following 11 d exposure to a range of imidacloprid concentrations applied to broad bean. There was a high correlation (r 0.91, n 21, p 0.01) between r i and r m 11 d after the start of the study, suggesting that r i can be used as a predictive measure in place of r m. There was a negative relationship, y x (r , n 21), between r i and exposure to imidacloprid-treated broad bean, suggesting that simple regressions may be utilized as tools in the assessment of xenobiotics on population growth rates. Keywords Ecotoxicology Populations Life tables Intrinsic growth rate Instantaneous growth rate INTRODUCTION The integration of population-level endpoints in the assessment of xenobiotic compounds has been promoted as more ecologically relevant than individual-level endpoints [1 9]. The National Research Council, in its report by the Committee to Review Methods in Ecotoxicology [10], emphasized that the assessment of toxicological effect needs to be evaluated beyond the traditional, individual-level endpoints and the potential effects of xenobiotics at the population, community, and ecosystem level should be considered [6]. Despite this support, individual assessment endpoints still dominate the ecotoxicology literature, primarily with measurements of acute mortality and short-term individual fecundity [8]. The assumption is that individual-level endpoints can be extrapolated to higher-order systems such as populations, communities, or ecosystems. However, the assessment of ecological risk based solely on individual endpoints may mask certain critical sublethal effects on a population. Bechmann [8] suggested that certain chemicals may affect demographic parameters far below the traditional concentration response curve, resulting in population decline and extinction at levels previously assessed to have no effect using individual endpoints. This hypothesis was supported by Walton et al. [11], who found that 96-h acute toxicity tests were insensitive for determining the effect of acidic water on populations of Daphnia pulex. Thus, greater emphasis should be placed on measuring population-level effects of xenobiotics. Population-level endpoints, as alternative measures of toxicity, have been criticized for lacking the sensitivity of individual endpoints (e.g., mortality, survivorship, or fecundity) * To whom correspondence may be addressed. [12,13]. Sensitivity, however, may not be the best criterion in selecting endpoints to monitor toxicological stress. While population endpoints may not always be the most sensitive measure of toxicity, they may be more realistic and ecologically relevant measures of toxic response. Life tables have been used as a method for generating population-level endpoints, such as the intrinsic rate of increase (r m ), as measures of toxicological stress [1,3,4,8,9,11 21]. Using schedules of survivorship and fecundity, the r m can be calculated by solving for the equation 1 lme rmx x x (1) where x is the age of the cohort, l x is the proportion of individuals surviving to age x, m x is the number of females produced per female of age x, and r m is the intrinsic rate of increase for the population. The intrinsic rate of increase measures the ability of a population to increase exponentially in an unlimited environment. The application of r m in the assessment of xenobiotics is more ecologically relevant than traditional LC50 measurements because it integrates age-specific survivorship and fecundity into a single parameter [3]. Despite the high ecological relevance of the r m endpoint in ecotoxicological studies, it has been applied less widely than mortality-based, standard toxicity tests. This is due in part to the time, labor, and expense associated with generating the schedules of survivorship and fecundity necessary to generate the measurement. The assessment of xenobiotics based on population endpoints may not become feasible until research can be performed cheaply and quickly. What is needed is a population measure that integrates both survivorship and fecundity as r m does, yet is not as time 1068

2 Population-level ecotoxicological endpoints Environ. Toxicol. Chem. 16, and labor intensive. One such measure may be the instantaneous rate of increase. The instantaneous rate of increase, or r i, measures the ability of a population to increase exponentially over time [22] ln N t N 0 r (2) i t where N t is the final number of animals, N 0 is the initial number of animals introduced, and t is the change in time (number of days the experiment was run). Solving for r i yields a rate of population increase or decline similar to that obtained by the intrinsic rate of increase (r m ). Positive values of r i indicate a growing population, r i 0 indicates a stable population, and a negative r i value indicates a population in decline and headed toward extinction. The r i is calculated from the number of individuals in a starting and ending population (Eqn. 2) without the detailed schedules of survivorship and fecundity required for calculating r m. By substituting r i in place of r m to generate population growth data, it may be possible to establish laboratory procedures that integrate together ecological and toxicological theory, yet provide a cheaper, more accurate alternative that better represents the impact of a chemical within an ecosystem. Hall [22] previously used the r i endpoint to monitor the birth and death rates for a natural population of Daphnia galeata mentodae in a Michigan lake. Frazer [23], Kareiva and Sahakian [24], and Zeng et al. [25] also used r i measurements to monitor communities of terrestrial arthropods. The r i endpoint, however, has not been widely applied as an endpoint in ecotoxicological studies. The only author who has previously applied r i in an ecotoxicological study was Marshall [26], who used it to monitor the effects of chronic cadmium stress on the population dynamics of D. g. mentodae. The purpose of this study was to test the hypothesis that r i could be applied as a substitute for r m as a population endpoint measurement in toxicity studies. Model comparison for this study was conducted using the pea aphid, Acyrthosiphon pisum Harris. The pea aphid was chosen as the test organism because of its well-documented life history, its significance as a food source for many beneficial species, its relatively short life span, parthenogenetic reproduction (all individuals are females), and high reproductive rate, which simplifies toxicological assessment. Imidacloprid was used because it is a new insecticide that may eventually be widely used in agriculture and thus may have an impact on various ecosystems. In the first experiment, the r m was calculated for each day after the start of the experiment using schedules of survivorship and fecundity for A. pisum neonates exposed to untreated potted broad bean, Vicia faba L. (variety Banner), and the results were statistically compared to determine the earliest r m that was not significantly different from the final r m of the life table experiment. A second experiment was performed to determine how r i changed over time for neonates reared on untreated broad bean. Using the results of this experiment, two methods for predicting the minimum time required for test termination were compared. One method was to create a curvefit equation for r i over time and determine the relative extrema for the function. The second method was to compare statistically the r i values over time with r m to determine the earliest day in which there was no significant difference between the two endpoints. A third study was conducted comparing r m and r i following an 11-d exposure to a range of toxicant concentrations applied to broad bean. Day 11 was chosen as the point of termination because it was the earliest day in which there was no significant difference (p 0.05) between the r m and r i endpoints. A correlation coefficient was calculated to determine the relationship between the two endpoints, r m and r i, for populations exposed over the same range of concentrations. Regression analysis was performed to compare the relationship between r i and increasing concentrations of the toxicant. MATERIALS AND METHODS Test organisms and chemicals Pea aphids, A. pisum, were obtained from laboratory colonies maintained at the Washington State University Research and Extension Center, Puyallup, Washington, USA. Colonies were reared on potted broad bean, V. faba L. (variety Banner), in free-standing environmental chambers set at C, 50 5% RH, and a photoperiod of 16 h 8 h light dark regimen. The insecticide imidacloprid, formulated at 240 FS (240 g active ingredient per liter [240 g a.i./l]) was provided by Miles, Inc., Kansas City, Missouri, USA. r m vs. r i on untreated plants A life table study was conducted with neonate pea aphids to determine the changes in r m over time. Broad bean plants were reared in circular pots (15 cm diameter) until they were approximately 25 cm in height, at which time they were thinned to five plants per pot. Four pots were sprayed with deionized, distilled water only. After plants were dry, 10 apterous A. pisum adults were placed individually into clip cages and fastened to the underside of randomly selected leaves in each pot (n 40). Twenty-four hours later, all aphids were removed from each clip cage except for one neonate, thus ensuring exposure to the plant from birth. Mortality and reproduction were recorded at 24-h intervals throughout the life span of each aphid. A life table was constructed [27] from the daily schedules of survivorship and fecundity, and the intrinsic rate of increase, r m, was calculated using Equation 1. To determine the change in r i over time, 21 pots of broad bean were greenhouse-reared at a density of 8 to 10 plants per pot (15 cm diameter 12.5 cm high). When plants reached 25 cm in height, pots were thinned to six plants, and each plant was attached to a 40- to 50-cm wooden stake with a plastic twist-tie. Twenty-four hours prior to A. pisum introduction, all plants were transported to an environmental growth chamber set as previously described. On the day of aphid introduction, all pots were taken from the growth chamber, the wooden stakes were removed, and Mylar sleeves (14 cm diameter 43 cm high) were placed over the top of each pot. Batches of 10 neonates ( 16 h old) were transferred onto plants inside the sleeve using a fine camel-hair paint brush. The Mylar sleeves were then covered with a nylon mesh screen held in place by a circular piece of rigid plastic sawed from the top of a plant pot. Neonates were allowed to migrate and reproduce freely on their new host. Following neonate introduction, all 21 pots were returned to the growth chamber. Populations were censused at 8, 11, 13, 15, 17, 19, and 21 d postintroduction. At each time interval, three pots were randomly removed from the growth chamber and the total A. pisum population was censused in each pot. The instantaneous rate of increase was calculated for the censused population in each pot using Equation 2.

3 1070 Environ. Toxicol. Chem. 16, 1997 W.K. Walthall and J.D. Stark r m vs. r i on treated plants A life table study was conducted to determine the chronic toxicity of imidacloprid on individuals exposed from birth. Insecticide concentrations were chosen from a previously obtained concentration response curve. Broad bean plants were reared in circular pots (15 cm diameter) until they were approximately 25 cm in height, at which time they were thinned to five plants per pot and sprayed with one of nine concentrations (1.25, 1.0, 0.6, 0.4, 0.25, 0.15, 0.1, 0.07, and 0 [control] mg a.i./l) of imidacloprid solution in deionized, distilled water using a Thomas atomizer attached to an Emerson air pump set at 100 kpa. Four replicates were treated for each concentration. After plants were dry, 10 apterous A. pisum adults were placed into individual clip cages using the previously described method. Twenty-four hours later, all aphids were removed except for one neonate, thus ensuring continuous exposure from birth. Mortality and reproduction were recorded at 24-h intervals throughout the life span of each aphid. The r m for populations exposed to each concentration were generated from the daily schedules of survivorship and fecundity. To determine the relationship between toxicant concentration and r i, pots of broad bean were sprayed with one of eight concentrations of imidacloprid (1.0, 0.8, 0.6, 0.4, 0.25, 0.15, 0.1, and 0.07 mg a.i./l); control plants were sprayed with deionized, distilled water only. Three replicates were used for each concentration (27 pots total). After plants were dry, a Mylar sleeve was placed over each pot and 10 neonates ( 16 h old) were introduced onto plants inside the Mylar sleeve using a fine camel-hair paint brush. Each pot was covered with nylon mesh and placed into an environmental chamber set as previously described. Aphid populations were allowed to move freely on their new host and all pots were left undisturbed for 11 d with the exception of necessary watering. At 11 d postspray all 27 pots were removed from the environmental chamber and the total aphid population in each pot was censused. The 11-d instantaneous rate of increase for each population was calculated using Equation 2. Data analysis Mean daily r m values were generated from life tables. Significant differences in the day-to-day r m values were determined using one-way analysis of variance (ANOVA) on ranks; mean separation was determined using the Student Newman Keuls method. Significant differences among the r i s for populations introduced to nontreated plants and censused over time were determined using one-way analysis of variance (ANOVA); mean separation was performed using the Student Newman Keuls method. A curve fit was generated using the r i values calculated from the censused population using the SigmaPlot graphing software package [28]. The order of the equation used was determined by iteration using the SigmaPlot software package [28] as the lowest-order equation to fit the data. Differences between the mean daily r m and mean r i values for populations introduced to untreated plants were compared on days 8, 11, 13, 15, 17, 19, and 21 with a t test (p 0.05). The relationship between increasing imidacloprid concentrations and decline in the instantaneous rate of increase (r i ) was investigated using a linear regression model. The correlation between r m and r i following an 11-d exposure to identical imidacloprid concentrations was found using the Pearson product moment correlation. Statistical analyses of all data sets were performed using the SigmaStat statistical package [29]. Fig. 1. Comparison between the mean ( SEM) daily intrinsic (r m ) and instantaneous (r i ) rates of increase over time for A. pisum introduced to untreated broad bean at birth. The r m and r i were significantly different (p 0.05, t test) on days 8 and 15 (*) but were not different on all other days. RESULTS Mean daily r m values for populations reared on untreated broad bean from birth increased rapidly following the onset of reproduction on day 6 until it peaked at on day 12. After day 12, the r m declined and stabilized at The r m on days 6 and 7 were significantly different (p 0.05) from all subsequent days, but there was no significant difference in r m from day 8 until the end of the study (day 40) (Fig. 1). The mean ( SEM) r i for populations censused from untreated plants over time was significantly different (p 0.05) on days 8 and 15 but was not significantly different on days 11, 13, 17, 19, and 21 (Fig. 1). Comparing the two population endpoints on the days in which the sampling dates overlapped, there was a significant difference (p 0.05) between r i and r m on days 8 and 15. There was no significant difference between the two endpoints on days 11, 13, 17, 19, and 21 (Table 1). Figure 2 is a curve fit of r i values over time for the censused populations. The peaks, or relative extrema, of this function represent the mean maximum rate of growth for these populations. In this study, the formation of a peak on day 11 sug- Table 1. Comparison between the intrinsic (r m ) and instantaneous (r i ) rates of increase for neonate A. pisum introduced to untreated broad bean at birth a Day Intrinsic rate of increase (r m ) mean ( SEM) 0.26 ( 0.05) A 0.33 ( 0.03) A 0.33 ( 0.03) A 0.32 ( 0.02) A 0.32 ( 0.02) A 0.31 ( 0.02) A 0.30 ( 0.02) A Instantaneous rate of increase (r i ) mean ( SEM) 0.13 ( 0.03) B 0.29 ( 0.02) A 0.26 ( 0.04) A 0.24 ( 0.01) A 0.30 ( 0.01) A 0.30 ( 0.01) A 0.28 ( 0.01) A a Means within rows followed by the same letter are not significantly different (p 0.05) using t test.

4 Population-level ecotoxicological endpoints Environ. Toxicol. Chem. 16, Fig. 2. Curve fit of the instantaneous (r i ) rate of increase over time for A. pisum introduced to untreated broad bean. gests that this is the earliest time interval necessary for these populations to reach their maximum rate of increase under the described conditions. The r i and r m for populations exposed to insecticide-treated plants for 11 d from birth declined in a concentration-dependent manner (Table 2). The r i and r m for neonate populations exposed to the same concentrations of imidacloprid were highly correlated (r , n 21, p 0.01) following exposure for 11 d (Fig. 3). There was a negative relationship (y x, r , n 21) between mean r i values and increasing imidacloprid concentration (Fig. 4). DISCUSSION Endpoints such as r m and r i are important measures of xenobiotic response because they integrate several critical factors of population response into a single variable [3,19]. However, population-level endpoints will not be popularized in ecotoxicological research until the time and expense required in generating the necessary data can be reduced. One method for determining the minimum test time was suggested by Daniels and Allan [19], who used regression analysis to determine the Fig. 3. Correlation (r 0.91, n 21, p 0.01) between the intrinsic (r m ) and instantaneous (r i ) rates of increase for A. pisum exposed to identical concentrations of imidacloprid for 11 d. time necessary to generate homogeneity in daily growth rates and the final r m. Their analysis suggested that r m values for D. pulex populations exposed to the pesticide dieldrin for 21 d yielded the same growth rates as populations exposed over the 55-d life table. The fact that Daniels and Allan [19] were able to show equalities in growth rate for dieldrin-exposed D. pulex populations does not imply that similar results can be obtained for D. pulex populations exposed to other chemicals over the same time period. Homogeneity of growth rates in a life table experiment is probably chemical specific, especially for compounds that affect reproduction. Thus the results obtained by Daniels and Allan [19] may not be applicable to other compounds. If population-level endpoints are supposed to find the contaminant levels that will inhibit population growth from the levels seen in control populations, it would be easier and of greater significance to determine the earliest point in which Table 2. Comparison between the intrinsic (r m ) and instantaneous (r i ) rates of increase for neonate A. pisum following 11 d exposure to imidacloprid-treated broad bean plants Concentration (mg/l) Intrinsic rate of increase (r m ) Instantaneous rate of increase (r i ) mean ( SEM) Control a c 0.31 ( 0.01) 0.28 ( 0.03) 0.29 ( 0.00) 0.27 ( 0.01) 0.22 ( 0.01) 0.15 ( 0.04) 0.06 ( 0.01) 0.01 b c a Concentration not tested in the life table study. b Only one population was available for calculating r i. c All populations died before reproducing. Fig. 4. Relationship (y x, r , n 21) between increasing imidacloprid concentration and the instantaneous (r i ) rates of increase for neonate A. pisum exposed to treated broad bean for 11 d.

5 1072 Environ. Toxicol. Chem. 16, 1997 W.K. Walthall and J.D. Stark an untreated population reaches its maximum rate of increase and test chemicals up to this point. One of the concerns about utilizing r i as an endpoint is the maximum time in which an experiment could be performed. In toxicological studies using microcosms or confined systems, it may be possible for species with high reproductive rates to approach their carrying capacity for the system prior to test termination. As a population approaches its growth limit, the r i will decline in response to density-dependent negative feedback. Natural suppression of population growth will affect endpoint assessment in a toxicological study if growth rates in control populations become suppressed while toxicant-exposed populations are allowed sufficient time to recover. Thus the dose response relationship becomes inverted as control populations decline and toxicant-exposed populations begin to increase due to declining toxicant concentrations and an abundance of available resources. This problem can be solved by minimizing the duration of the test to the period in which r i is maximized in control populations. This assessment should be determined prior to toxicity testing. The minimum time required for this study was estimated using two separate methods: by determining the earliest time in which r i was not statistically different than r m and by defining the relative maxima for the generated curve fit equation. The first method used to determine the minimum time for the r i study was to determine the earliest time in which the r m was not significantly different from the r m for the entire life table experiment. For A. pisum populations, the 8-d r m on nontreated plants did not differ significantly from the r m at the end of the study. However, the daily r m continued to increase until peaking at 12 d postintroduction. Despite the fact that the daily r m does not change significantly for neonate A. pisum on untreated plants after 8 d, the r i was significantly lower than r m on this day. Populations censused for r i on untreated broad bean showed lower reproduction per individual than in the r m study. This difference in reproduction between the r m and r i on untreated plants may be due to the time at which the neonates were introduced. Neonates in the life table were exposed to the same leaf from birth and were left relatively undisturbed throughout their life cycle. While all neonates were 24 h old, the exact time of birth was not known. The time at which all other aphids in a clip cage were removed was considered the start of the experiment, or rather t 0. In determining r i on untreated plants over time, neonates 16 h old were introduced to new plants and allowed to move freely around the new host. Thus two factors may help account for the apparent difference in short-term reproductive potential of the two populations: the fact that neonates in the r i experiment were unconfined and allowed to roam and the potential 8-h gap in physiological time between two neonate populations. The r m and r i, however, were not significantly different on day 11, suggesting that this is the earliest time in which a comparison between r m and r i could be made. The obvious drawback of statistically comparing r i and r m to determine the minimum time is the requirement that a life table be generated. Life table generation can be both time consuming and expensive, especially if it is performed on control samples in which survivorship and fecundity are uninhibited. For species in which the r m is unknown, the curvefitting process may be an effective substitute in determining the minimum time because of its relative quickness and simplicity. In this study, the curve-fitting method showed that the population reached its maximum rate of increase on day 11. Thus, this method yielded similar results for determining the minimum test time as comparing the r i and r m endpoints statistically. The relationship between r m and r i for populations exposed to identical concentrations on treated broad bean for 11 d was highly correlated and statistically significant. These data validate our hypothesis that r i can be applied as a substitute measure for r m in monitoring population response to toxicant exposure. This suggests the potential application of r i as a shortterm toxicity screen. While the r i endpoint does not provide the detailed demographic information provided by life tables, it appears to have some advantages over the r m because it evaluates real populations with density-dependent feedback mechanisms and it can be generated in less time and expense than the traditional life table method. One problem with life tables and the estimation of r m is that it may not fully consider a toxicant s effect on oogenesis or embryogenesis [3,4]. In certain cases, a toxicant s effect on these developmental stages may not become apparent for several generations following initial exposure; unless life table studies are performed over multiple generations, these developmental effects may pass unnoticed. If these effects are compounded within a population following continuous toxicant exposure, it could severely hinder a population s ability to recover when exposed to multiple environmental stressors. The r i endpoint may be a useful tool for monitoring these types of stress over several generations. Because r i studies tend to be low maintenance, experiments could be carried out over several succeeding generations by rearing toxicant-exposed populations in both control and toxicant-influenced environments. This may be a more practical method for determining safe concentrations at the population or community level. The evaluation of introduced neonate populations to a range of imidacloprid-treated plants yielded a linear relationship between a population s r i value and the concentration to which it was exposed. The integration of toxicant concentration and population growth rates into a linear regression creates a concentration response function for population-level exposure. The ability to generate accurate concentration response functions at the population level may significantly improve the ability to predict the effect of chemicals in an ecosystem. Using linear regression models, it may also be possible to integrate a population s response to more than one environmental stress. Gentile et al. [1] suggested that the toxicological effect of a xenobiotic on population growth rates could be integrated with the effects from other environmental stressors, such as predation, to model the combined effect on a population. Thus, linear regression models improve our ability to monitor and predict responses in situations where populations face multiple environmental stressors. The ability to monitor the effect of multiple stressors on population growth rates will benefit ecotoxicological and environmental assessment programs, which can use this information to model and predict a population response to a combination of biotic and abiotic factors. Such models would be beneficial in providing a more accurate estimate of a toxicant s impact within an ecosystem. Acknowledgement The authors thank Julie Banken and Carla Derie for their assistance in data collection. REFERENCES 1. Gentile, J.H., S.M. Gentile, N.G. Hairston, Jr. and B.K. 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