Editor's evaluation: Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission
Year: 2021
Type: peer-review
Abstract: Article Figures and data Abstract Editor's evaluation eLife digest Introduction Materials and methods Results Discussion Data availability References Decision letter Author response Article and author information Metrics Abstract Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission. Editor's evaluation This careful meta-analysis evaluates consumptive and non-consumptive effects of aquatic predators across multiple mosquito species, drawing from laboratory and semi-field studies. The authors find an important role for larval size in moderating consumption, significant non-consumptive impacts of predators on survival and body size, and variable effects of predators on oviposition behavior. These results therefore highlight multiple mechanisms by which aquatic predators might affect disease transmission. https://doi.org/10.7554/eLife.71503.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest Mosquitoes are often referred to as the deadliest animals on earth because some species spread malaria, West Nile virus or other dangerous diseases when they bite humans and other animals. Adult mosquitoes fly to streams, ponds and other freshwater environments to lay their eggs. When the eggs hatch, the young mosquitoes live in the water until they are ready to grow wings and transform into adults. In the water, the young mosquitoes are particularly vulnerable to being eaten by dragonfly larvae, fish and other predators. When adult females are choosing where to lay their eggs, they can use their sense of smell to detect these predators and attempt to avoid them. Along with eating the mosquitoes, the predators may also reduce mosquito populations in other ways. For example, predators can disrupt feeding among young mosquitoes, which may affect the time that it takes for them to grow into adults or the size of their bodies once they reach the adult stage. Although the impacts of different predators have been tested separately in multiple settings, the overall effects of predators on the ability of mosquitoes to spread diseases to humans remain unclear. To address this question, Russell, Herzog et al. used an approach called meta-analysis on data from previous studies. The analysis found that along with increasing the death rates of mosquitoes, the presence of predators also leads to a reduction in the body size of those mosquitoes that survive, causing them to have shorter lifespans and fewer offspring. Russell, Herzog et al. found that one type of mosquito known as Culex – which carries West Nile virus – avoided laying its eggs near predators. During droughts, increased predation in streams, ponds and other aquatic environments may lead adult female Culex mosquitoes to lay their eggs closer to residential areas with fewer predators. Russell, Herzog et al. propose that this may be one reason why outbreaks of West Nile virus in humans are more likely to occur during droughts. In the future, these findings may help researchers to predict outbreaks of West Nile virus, malaria and other diseases carried by mosquitoes more accurately. Furthermore, the work of Russell, Herzog et al. provides examples of mosquito predators that could be used as biocontrol agents to decrease numbers of mosquitoes in certain regions. Introduction While it is well known that predation reduces vector populations through consumptive effects, non-consumptive effects of predators can also greatly impact prey demographics (Preisser et al., 2005). Mosquitoes are vectors of a variety of debilitating and deadly diseases, including malaria, lymphatic filariasis, and arboviruses, such as chikungunya, Zika, and dengue (Weaver and Reisen, 2010; WORLD HEALTH ORGANIZATION, 2020). Consequently, there is motivation from a public health perspective to better understand the different drivers of variation in mosquito traits that can ultimately impact vector population growth and disease transmission. In addition, recent work has suggested that incorporation of vector trait variation into disease models can improve the reliability of their predictions (Cator et al., 2020). In this study, systematic review and meta-analysis methods are used to synthesize a clearer understanding of the consumptive and non-consumptive effects of predators on mosquito traits, including survival, oviposition, development, and size. Mosquito insecticide resistance is recognized as a growing problem (Hancock et al., 2018; Hemingway and Ranson, 2000; Liu, 2015) leading some to suggest that control efforts should rely more heavily on 'non-insecticide based strategies' (Benelli et al., 2016). The consumptive effects of predators on mosquitoes have previously been harnessed for biocontrol purposes. Past biocontrol efforts have used predators such as cyclopoid copepods (Kay et al., 2002; Marten, 1990; Russell et al., 1996; Veronesi et al., 2015) and mosquitofish (Pyke, 2008, Seale, 1917) to target the mosquito's aquatic larval stage. The strength of the consumptive effects of these predators on mosquitoes can be influenced by multiple factors, including predator-prey size ratio and temperature. Predator-prey body size ratios tend to be higher in freshwater habitats than other types of habitats (Brose et al., 2006), and attack rate tends to increase with temperature (Kalinoski and DeLong, 2016; Dam and Peterson, 1988), although other studies suggest a unimodal response to temperature (Uiterwaal and Delong, 2020; Englund et al., 2011). Predators can also have non-consumptive effects on prey (Peacor and Werner, 2001), and these effects are thought to be more pronounced in aquatic ecosystems than in terrestrial ecosystems (Preisser et al., 2005). Non-consumptive effects of predators are the result of the prey initiating anti-predator behavioral and/or physiological trait changes that can aid in predator avoidance (Hermann and Landis, 2017; Lima and Dill, 1990). Such plasticity in certain prey traits may also result in energetic costs (Lima, 1998). Predator detection is key for these trait changes to occur and can be mediated by chemical, tactile, and visual cues (Hermann and Thaler, 2014). In mosquitoes, exposure to predators is known to affect a variety of traits including behavior, size, development, and survival (Arav and Blaustein, 2006; Bond et al., 2005; Roberts, 2012; Roux et al., 2015, Zuharah et al., 2013). Experimental observations of predator effects on mosquito size and development are inconsistent and results sometimes vary by mosquito sex. For example, exposure to predation was found to increase the size of Culex pipiens mosquitoes (Alcalay et al., 2018) but decrease the size of Culiseta longiareolata (Stav et al., 2005). In addition, female Aedes triseriatus exhibited shorter development times when exposed to predation at high nutrient availability (Ower and Juliano, 2019), but male C. longiareolata had longer development times in the presence of predators (Stav et al., 2005). In some cases, a shared evolutionary history between predator and prey organisms can strengthen the non-consumptive effects of predators on mosquitoes (Buchanan et al., 2017; Sih, 1986). This investigation assesses the consumptive and non-consumptive effects of predators on mosquito traits and describes how these effects could impact disease transmission. The roles of vector genus, predator family, mosquito larval instar (an indicator of prey size), and temperature are also examined as potential moderators of predator effects. Non-consumptive effects of predators are expected to cause a smaller reduction in mosquito survival than consumptive effects because, in practice, measures of consumptive effects always include both consumptive and non-consumptive effects. Based on previous findings, larger predators are more likely to consumptively reduce mosquito survival (Kumar et al., 2008). In addition, Aedes mosquito larvae may be more vulnerable to consumption than other genera because of the high degree of motility observed in this genus (Dieng et al., 2003; Marten and Reid, 2007; Soumare and Cilek, 2011). The oviposition response to predation is expected to be weakest among Aedes species that oviposit above the water line, due in part to their delayed-hatching eggs (Vonesh and Blaustein, 2010). Predation is predicted to reduce mosquito size and lengthen development time, consistent with the reduced growth response observed in other insect systems (Hermann and Landis, 2017). Certain non-consumptive effects of predation, particularly oviposition site selection and decreased vector size, are likely to play important roles in the dynamics of mosquito-borne disease. Materials and methods Literature screening Request a detailed protocol A systematic search was conducted for studies on predation of mosquitoes that were published between 1970 and July 1, 2019 using both PubMed and Web of Science search engines, according to the PRISMA protocol (Moher et al., 2009). Mosquito vectors of the Anopheles and Aedes genera were specifically highlighted in our search terms because these genera contain the vector species that transmit malaria, yellow fever, and dengue – the three most deadly mosquito-borne diseases worldwide (Hill et al., 2005). Searches included 18 combinations of three vector predation terms (mosquito predat*, Anopheles predat*, Aedes predat*) and six trait terms (survival, mortality, development, fecundity, dispers*, host preference). Abstracts from the 1136 studies were each screened by two different co-authors, using the 'metagear' package in R (Lajeunesse, 2016, R Development Core Team, 2020). If either screener thought the study had information relevant to predation of mosquitoes, or both screeners thought the abstract was ambiguous, the study was read in full. This resulted in 306 studies that were fully reviewed to determine if any predation data could be extracted (Figure 1). Figure 1 Download asset Open asset Flowchart demonstrating the literature search, screening process, data exclusions, and the resulting seven different vector trait data subsets. Study exclusion criteria Request a detailed protocol Data were extracted from studies that collected data on non-consumptive and/or consumptive effects of predators on mosquitoes. Studies were required to have a mean, error measurement, and at least two replicates for both control and predator treatments. The control treatment was required to have all the same conditions as the predator treatment, such as prey density and type of water, without the predators. Studies that were not published in English and studies that did not differentiate between predators of multiple families were excluded. Studies were also excluded if oviposition by free-flying female mosquitoes could have interfered with observing the consumptive effects of predators on vector survival. The final database comprised data extracted from 60 studies (Supplementary file 1). The data included observations from laboratory experiments, as well as semi-field experiments, in which mesocosms of different treatments were observed in outdoor settings. Data extraction Request a detailed protocol Variables related to the publication, the vector, the predator, and the effect size (Table 1) were extracted from each study. Data from tables and text were recorded as they were published, and data from figures were extracted using WebPlotDigitizer (Rohatgi, 2020). Error measurements that were not originally presented as standard deviations were converted to standard deviations prior to the effect size calculation. Table 1 Variables extracted from included studies. VariableDescriptionPublication data:TitleFull study titleJournalName of journal that published the studyYearYear of publicationStudy environmentEnvironment where the experiment took place: lab or semi-fieldVector data:Order, Family, Genus, SpeciesTaxonomic identificationTraitOutcome that was measured (e.g. survival, development, etc.)StageLife stage: egg, larva, pupa, or adultLarval instarEarly (1st and 2nd instars), late (3rd and 4th instars), both, or NA (eggs, pupae, or adults)SexMale or femalePredator data:Phylum, Class, Order, Family, Genus, SpeciesTaxonomic identificationStarvedWhether the predator was starved: yes or noTime starvedAmount of time that the predator was starved (in minutes)Predation effectConsumptive or non-consumptiveEffect size data:UnitsUnits of extracted dataControl meanAverage of the outcome measured among the controlsControl standard deviationStandard deviation of the outcome measured in the controlsControl number of replicatesNumber of control replicatesPredation meanAverage of the outcome measured in the predator treatmentPredation standard deviationStandard deviation of the outcome measured in the predator treatmentPredation number of replicatesNumber of predation replicatesExperiment IDAlphabetic assignment to mark observations sharing a control group or representing the same prey individuals as originating from the same experimentAdditional data:Experiment time (days)Duration of the experiment in daysData sourceGraph or textNumber of predatorsNumber of predators with access to prey, or 'cue' if there are no predators with direct access to preyNumber of prey (vectors)Number of mosquito prey that are exposed to predationArena volume (mL)Volume of the arena where prey encounter predatorsTime exposed to predator(s)Amount of time (in days) when the predator has direct access to the mosquito preyTemperature (°C)Temperature during the predation interactionType of predator cuePredator cues, or cues from both predator(s) and dying conspecifics; NA for observations with a consumptive predation effect Data exclusions Request a detailed protocol A PRISMA plot of literature inclusion and exclusion is provided in Figure 1. Observations where insecticide was used were excluded because insecticides are known to interfere with consumptive and non-consumptive effects of predators (Delnat et al., 2019; Janssens and Stoks, 2012). In addition, observations from experiments with mosquito prey of two or more species were excluded because it was not possible to account for effects from apparent competition or prey-switching. Observations of vector fecundity, vector competence, behavioral traits other than oviposition, as well as observations where the vector trait was marked as 'other' were not analyzed because each of these traits were only recorded from three or fewer studies. Due to protandry, the earlier emergence of males to maximize their reproductive success, mosquitoes respond to sex-specific selective forces that influence their development time and body size (Kleckner et al., 1995). Under low resource conditions, female mosquitoes are likely to maximize body mass by extending their development time, whereas males tend to minimize their development time at the expense of lower body mass (Kleckner et al., 1995). Observations of mosquito development time and body size in our database that were not sex-specific were excluded so that these vector traits could be analyzed while controlling for sex. In addition, among the observations of development time and body size, some predator means did not necessarily represent an evenly weighted average of the replicates. For example, if a total of 20 mosquitoes from three different predator replicates survived to adulthood, the mean development time and size of those 20 individuals may have been reported. To represent an evenly weighted average of the replicates, it is necessary to first calculate summary statistics among multiple individuals that emerge from the same replicate, and then report the average of the replicate-specific means. Observations that might have been influenced by uneven representation of replicates were excluded to prevent pseudo-replication from altering later meta-analyses. For consumptive observations where life stage-specific survival was reported after more than 10 days of predator exposure, only data on survival marked by adult emergence were included for analysis. Effects observed among immature vector stages after such a long period of predator exposure were not analyzed because they could have resulted from a combination of non-consumptive effects on development, and consumptive effects on survival. Development time observations that were reported as the inverse of development time (units of days–1) were excluded because although their means could be converted to units of days, their standard deviations could not be converted to match units of days. In cases where multiple body sections of the same mosquitoes were measured to produce multiple size observations, only the wing measurement was included in the analysis to prevent pseudo-replication. Observations in which both the control and the predator treatments had standard deviations of zero were excluded because the meta-analysis methods did not support non-positive sampling variances. Exclusions and data substitutions for predator treatment means of zero Request a detailed protocol One study that was included in our database reported egg survival data as the hatch rate of field collected Culex pervigilans rafts (Zuharah et al., 2013). However, mosquitoes have been shown to lay eggs independent of mating (O'Meara, 1979), and hatch rates of zero have previously been observed in rafts laid by Culex females that were held separately from males (Su and Mulla, 1997). Thus, hatch rates of zero were excluded from further analysis because these values may represent unfertilized egg rafts, rather than a strong impact of predators on survival. Twenty of the 187 consumptive survival observations had a predation mean of zero, and each of these zeros resulted from experiments that began with a specified number of live larvae. Consumptive survival zeros were each replaced with 0.5% of the starting number of mosquito prey to avoid undefined effect sizes. In addition, there was one zero out of the 36 oviposition predation means; this value had units of 'number of egg rafts laid' and was replaced with 0.5 rafts. Similar methods for replacing zero values in the treatment mean with small non-zero values have previously been employed (Thapa et al., 2018). The final analysis dataset included seven subsets: consumptive effects on survival, non-consumptive effects on survival, oviposition, development (female and male), and size (female and male). The data included 187 observations from 34 studies of consumptive survival, 24 observations from seven studies of non-consumptive survival, 36 observations from 12 studies of oviposition, 14 observations from seven studies of female development, 14 observations from seven studies of male development, 27 observations from 10 studies of female size, and 18 observations from nine studies of male size (Figure 1). These observations covered seven different classes of predator families (Figure 2). Figure 2 Download asset Open asset Mosquito predator classes (bold font) and families (italicized font) included in the database and the vector traits that they may influence (in parentheses); predator images not to scale, and placed randomly with respect to the different mosquito life stages. Image sources: phylopic.org (CC BY 3.0 or public domain): Actinopterygii (creator: Milton Tan), Arachnida (creators: Sidney Frederic Harmer & Arthur Everett Shipley, vectorized by Maxime Dahirel), Branchiopoda (creator: Africa Gomez), and Insecta (creator: Marie Russell). BioRender.com: Amphibia, Hexanauplia, and Malacostraca class silhouettes; mosquito larval instars, pupa, and blood-feeding adult. Trishna Desai: mosquito egg raft. Data analysis Measuring effect sizes and heterogeneity Request a detailed protocol All analyses were conducted in R version 4.0.2 (R Development Core Team, 2020). For each subset of trait data (Figure 1), the ratio of means (ROM) measure of effect size was calculated using the 'escalc' function from the 'metafor' package; this effect measure is equal to a log-transformed fraction, where predation mean is the numerator and control mean is the denominator (Viechtbauer, 2010). Random effects models, using the 'rma.uni' function, were run with the ROM effect sizes as response variables; each model had a normal error distribution and a restricted maximum likelihood (REML) estimator for τ2, the variance of the distribution of true effect sizes (Viechtbauer, 2010). Although these random effects models could not account for multiple random effects or moderators, they provided overall estimates of the ROM effect sizes and estimates of the I2 statistics. Each I2 the of total variation across studies due to heterogeneity et al., If the I2 was equal to or than the heterogeneity was to be high et al., and high heterogeneity has previously further of moderators et al., 2017). Request a detailed protocol was by and with standard error as the and 2010). If the showed significant of based on plot the and was used to how the predation effect size might after values from studies and and 2010). The and has previously been for the of related to in and and the two and and that were originally and and the estimator was used in this study because it is more for smaller and moderators Request a detailed protocol Data that had high observations from at least 10 and no of according to results were analyzed further using effects models with the function (Viechtbauer, 2010; et al., 2020). All effects models had normal error for τ2, and for two random effect size and experiment study such as predator family, vector genus, larval instar to prey size), and were tested each data subset to determine if they the observed heterogeneity in ROM effect sizes. For moderators, the of the effects model was an analysis of variance referred to as the of to if any of the categories had an effect size different than For data with observations from 10 to only one was tested at a time to account for size For with observations from a higher number of studies or to two moderators were tested at and between moderators was also The small was used to effects models and to the model of each data in than two were and Results Random effects models Each data subset (Figure 1) had an I2 of than high heterogeneity et al., Random effects model results showed that predators consumptively decreased mosquito survival with an effect size of and reduced survival with a smaller effect size of In addition, predators reduced oviposition behavior with an effect size of and mosquito body size was reduced by predators in both males and the female effect size was and the male effect size was was not a significant non-consumptive effect of predators on either male or female development the female effect size was and the male effect size was The results showed that the non-consumptive survival both development time and and the female size subset exhibited plot of The and studies in the non-consumptive survival subset and the female size but the did not any studies in either of the development time subsets. studies were to be from the non-consumptive survival and for values from studies resulted in a in the predation effect size from to studies were to be from the female size and for values from these studies the predation effect size from to in effect size estimates due to the and were and did not cause any of the observed effects of predators to or effects models The consumptive survival and oviposition data the criteria of high observations from at least 10 and no of these data were tested for moderators using effects Predator families that decreased mosquito survival included and (Figure genera that significant in survival due to consumptive effects of predators included and (Figure all 187 consumptive survival observations from 34 the model according to was when an between predator and vector genus was included in the model (Table 2). However, among the larval consumptive survival observations from an between larval instar (an indicator of prey and predator had a on model than an between vector genus and predator (Figure Table did not affect the heterogeneity of consumptive survival either as a or a The oviposition model according to was when vector genus was as a (Table The mean oviposition effect size was not significantly different than zero for or but for Culex mosquitoes, oviposition was significantly decreased by predator (Figure Table 2 effects models of consumptive effects from predators on mosquito survival, to dataset of effect sizes 187 from 34 and by information of of vector vector Table
Source: eLife
Author: Sarah E Cobey
Institution: University of Chicago
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
OpenAlex ID: W4205112425