Research Article |
Corresponding author: Larissa Faria ( lari.f92@gmail.com ) Academic editor: Jaimie T.A. Dick
© 2023 Larissa Faria, Jean R. S. Vitule, Julian D. Olden.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Faria L, Vitule JRS, Olden JD (2023) Predation risk by largemouth bass modulates feeding functional responses of native and non-native crayfish. NeoBiota 87: 191-212. https://doi.org/10.3897/neobiota.87.108457
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Context-dependency is prevalent in nature, challenging our understanding and prediction of the potential ecological impacts of non-native species (NNS). The presence of a top predator, for example, can modify the foraging behaviour of an intermediate consumer, by means of non-consumptive effects. This raises the question of whether the fear of predation might modulate consumption rates of NNS, thus shaping the magnitude of ecological impacts. Here, we quantified the functional feeding responses of three non-native crayfish species – red swamp crayfish Procambarus clarkii, rusty crayfish Faxonius rusticus and virile crayfish Faxonius virilis – compared to the native analogue signal crayfish Pacifastacus leniusculus, considering the predation risk imposed by a top fish predator, the globally invasive largemouth bass Micropterus salmoides. We applied the comparative functional response (FR) approach using snails as prey and exposing crayfish to water containing predator and dietary chemical cues or not. All crayfish species presented a destabilising Type II FR, regardless of the presence of chemical cues. Predation risk resulted in significantly longer handling times or lower attack rates in non-native crayfish; however, no significant differences were observed in signal crayfish. We estimated per capita impacts for each species using the functional response ratio (FRR; attack rate divided by handling time). The FRR metric was lower for all crayfish species when exposed to predation risk. Rusty crayfish demonstrated the highest FRR in the absence of chemical cues, followed by signal crayfish, virile crayfish and red swamp crayfish. By contrast, the FRR of signal crayfish was nearly twice that of rusty crayfish and virile crayfish and ten times greater than red swamp crayfish when chemical cues were present. The latter result agrees with the well-recognised ecological impacts of signal crayfish throughout its globally-introduced range. This study demonstrates the importance of considering the non-consumptive effects of predators when quantifying the ecological impacts of intermediate non-native consumers on prey. The direction and magnitude of the modulating effects of predators have clear implications for our understanding of NNS impacts and the prioritisation of management actions.
ecology of fear, decapods, higher-order predator, kairomones, trait-mediated indirect effects
Non-native species (NNS) are a primary driver of environmental change, with negative impacts on individuals to entire ecosystems and severely disrupting important services provided by nature (
Quantifying per capita effects of NNS remains central to most frameworks evaluating their ecological impacts (
The fundamental ecological concept of functional responses (FR) – resource use as a function of availability – provides a measurable estimate of the per capita effect of a consumer on a given resource (
The comparative FR approach enables the evaluation of per capita effects in different contexts, allowing more realistic and practical impact assessments (
Trait-mediated indirect effects are particularly prominent in freshwater ecosystems, likely due to the effective transmission of visual and chemical cues indicating predator presence (
Despite the strong effects of non-consumptive effects in shaping communities, they are relatively underexplored compared to consumptive effects in the context of quantifying NNS impacts. Applying the comparative FR approach, we aim to test whether the non-consumptive effects of a top predator, the non-native largemouth bass, mediate the consumptive impacts of three non-native crayfish species (Procambarus clarkii, Faxonius virilis and F. rusticus) and a native analogue (Pacifastacus leniusculus) preying on snails. We hypothesise that non-consumptive effects of a top predator will reduce consumption rates of all crayfish species, but to a lesser extent for non-native crayfish with a shorter evolutionary history with the predator. The differential response to predation risk imposed by the largemouth bass may explain the expected higher per capita effects of non-native consumers compared to native analogue species.
Our study system is a three-level food chain composed by a non-native top predator, the largemouth bass, an intermediate consumer represented by non-native or native crayfish (Table
Crayfish species examined in this study, including scientific and common names, history of introduction in the Pacific Northwest region, sampled populations (coordinates) and carapace length (CL) and mass, presented as the mean (SD), of the individuals used in the experiments.
The geographic context of the study is the Pacific Northwest region of the US, where all species were sourced (Table
Largemouth bass were collected using electrofishing from Lake Washington, WA (47.6469, -122.2991) in October 2022. A total of 33 fish were captured and transported to the lab facility at the University of Washington, where they were maintained in a circular tank of approximately 800 l without shelter (hereafter stimulus tank), aerated and continuously filled with water from Lake Washington, in an open circulation system (mean total length = 194 mm, SD = 53). Fish were acclimatised to the stimulus tank for two weeks before the beginning of the trials.
A total of 433 crayfish were sampled using baited traps deployed overnight from lakes in Washington and Oregon States in October 2022 (Table
Native and NNS of crayfish were tested for differences in their predatory rate of snail prey supplied in seven different initial densities (2, 4, 8, 12, 16, 24 and 40 snails) under the presence or absence of waterborne predator and dietary chemical cues (hereafter, predator treatment and control, respectively). Experiments were conducted in a fully-randomised design with respect to crayfish species and initial prey densities assigned to predator treatment and control. Experimental arenas were round opaque tanks (44.5 cm diameter, 42.5 cm height) filled with 10 l of water and no substrate or shelter were provided (Fig.
Experimental setup used in the functional response trials A experimental arena with a signal crayfish and snail prey during a trial B water from the tank containing largemouth bass (left) was pumped to a head tank (upper right) and C distributed to the experimental arenas in the predator treatment (upper-left row) or water was supplied directly from Lake Washington to the control arenas (lower-right row). Blue tanks in the background were stock and starvation tanks where crayfish were kept before being used in trials D the water from both treatments was supplied to each experimental arena via individually controlled hoses.
Fish were starved for a week and then fed every other day a diet of crayfish before and during the experiments. Small individuals of all crayfish species were supplied simultaneously until satiation to enhance the response of crayfish to conspecific dietary cues released by the fish (
There were seven replicates for each combination of crayfish species, initial density of prey and treatment. At least five replicates of each combination were performed in the absence of crayfish to account for any background mortality of prey. Prey survivorship in these replicates was 99.9%, thus all prey deaths during experiments were attributed to crayfish predation. Crayfish were not reused in the experimental trials and replicates where crayfish moulted during the trial or one week after were repeated.
All statistical analyses were carried out in R version 4.1.2 (
Based on these analyses, all FRs were then modelled as Type II. Maximum Likelihood model fitting was used to fit data to the Rogers’ random predator equation (
where Ne is the number of prey consumed, N0 is the initial density of prey, a is the attack rate, h is the handling time and T is the time available for predation in days (i.e. experimental duration). As Ne is obtained experimentally, the estimated FR parameters are attack rate and handling time, representing a measure of successful attacks and the time needed for a predator to handle and ingest a prey item, respectively. The Lambert W function is implemented to solve the fact that Ne appears on both sides of the equation (
To compare FR parameters a and h between predator treatment and control, we used the indicator variables method (
where j is an indicator variable that takes value 0 for control and 1 for predator treatment. The parameters Da and Dh estimate the differences between treatments in the value of the parameters a and h, respectively. If Da and Dh are significantly different from zero, then the estimated FR parameters differ between treatment and control (
Potential differences in the trial’s water temperature amongst species and initial densities of prey were evaluated through Kruskal-Wallis tests, as well as differences in crayfish weight and carapace length (CL) amongst species and initial densities of prey. Water temperature in trials did not vary amongst species (Kruskal–Wallis Χ2(3) = 7.366, p = 0.06) nor in association with the initial densities of prey tested (Kruskal–Wallis Χ2(6) = 11.339, p = 0.08). Crayfish mass and carapace length varied amongst species (Mass: Kruskal–Wallis Χ2(3) = 96.73, p < 0.001; CL: Kruskal–Wallis Χ2(3) = 224.73, p < 0.001). The effect of crayfish size and sex on the proportion of prey consumed was investigated with Spearman’s correlation and Mann-Whitney tests, respectively. Crayfish size (Mass: r = 0.01, p = 0.84; CL: r = -0.08, p = 0.12) and sex (Mann-Whitney U = 14828, p = 0.74) had no relation to the proportion of prey consumed.
All crayfish species presented a destabilising Type II FR towards snail prey, regardless of the presence of chemical cues (Fig.
Functional response estimates of native and non-native crayfish species under predator treatment and control. The 1st order term of the logistic regression (see Methods), the functional response (FR) type, estimated parameters attack rate (a) and handling time (h), the maximum feeding rate (1/hT) and the functional response ratio (FRR). * = significant results.
Treatment/ Species | 1st order term (p-value) | FR type | a ± SE (p-value) | h ± SE (p-value) | 1/hT | FRR |
---|---|---|---|---|---|---|
Predator | ||||||
Signal crayfish (native) | -0.0617 (> 0.001)* | II | 2.26 ± 0.23 (> 0.001)* | 0.04 ± 0.004 (> 0.001)* | 28.02 | 63.5 |
Red swamp crayfish | -0.0078 (0.29) | I† | 0.25 ± 0.05 (> 0.001)* | 0.04 ± 0.037 (0.271) | 24.81 | 6.1 |
Rusty crayfish | -0.0283 (> 0.001)* | II | 1.16 ± 0.14 (> 0.001)* | 0.03 ± 0.006 (> 0.001)* | 31.37 | 36.3 |
Virile crayfish | -0.0411 (> 0.001)* | II | 1.64 ± 0.23 (> 0.001)* | 0.05 ± 0.006 (> 0.001)* | 19.81 | 32.5 |
Control | ||||||
Signal crayfish (native) | -0.0358 (> 0.001)* | II | 2.08 ± 0.24 (> 0.001)* | 0.03 ± 0.004 (> 0.001)* | 37.53 | 78.2 |
Red swamp crayfish | -0.0142 (0.022)* | II | 0.50 ± 0.08 (> 0.001)* | 0.04 ± 0.015 (0.021)* | 28.59 | 14.3 |
Rusty crayfish | -0.0101 (0.086) | II | 1.14 ± 0.13 (> 0.001)* | 0.01 ± 0.006 (0.061) | 94.99 | 108.0 |
Virile crayfish | -0.0252 (> 0.001)* | II | 1.43 ± 0.15 (> 0.001)* | 0.02 ± 0.005 (> 0.001)* | 47.95 | 68.8 |
Functional responses of native and non-native crayfish feeding on snails under predator treatment and control A native signal crayfish B non-native red swamp crayfish C non-native rusty crayfish and D non-native virile crayfish. Lines represent model fit (solid line: predator treatment, dashed line: control). Points represent mean consumption and error bars represent ± SE per density (filled circles: predator treatment, open circles: control; n = 7 per initial density × treatment combination).
Non-consumptive effects were observed for all non-native crayfish species, except for native signal crayfish (Fig.
Estimated functional response parameters of native and non-native crayfish species under predator treatment and control A handling time parameter h and B attack rate parameter a. Points represent the mean estimate of the model (filled circles: predator treatment, open circles: control) and error bars represent ± SE. *p < 0.1 and **p < 0.05.
Native signal crayfish demonstrated a greater consumption rate when exposed to predation risk compared to non-native crayfish (Fig.
The functional response ratio (FRR) of native and non-native crayfish species under predator treatment and control. The calculated FRR (a/h) is represented as bars (solid bars: predator treatment, shadowed bars: control) and error bars represent propagated standard errors of original estimates of parameters attack rate a and handling time h.
Predators can exert non-consumptive effects on prey that are comparable in magnitude to consumptive effects (
Native signal crayfish was the only study species demonstrating little evidence for the effect of predation risk on the FR magnitude. This outcome is supported by a body of literature suggesting that the response of signal crayfish to predation risk is highly variable and context-dependent (
All crayfish species presented a Type II FR, which is deemed to destabilise resource populations. This result aligns with the known impacts of these species on biomass and abundance of benthic invertebrates, particularly snails (
We found significant differences amongst NNS predatory impacts towards prey. Rusty crayfish and virile crayfish showed consumption rates similar to those of native signal crayfish, whereas red swamp crayfish demonstrated the lowest feeding rate, despite the latter species being considered one of the most impactful invasive crayfish in the world (
Previous studies that investigated TMIEs using the FR approach reported mixed outcomes. Considering simple habitats, the presence of predator cues reduced consumption rates of the amphipod Echinogammarus marinus, an intermediate predator, towards isopod prey (
First, the effect of abiotic contexts, such as habitat complexity and presence of shelter, continues to be a research need. The Type II FR curves reported here align with general expectations from the broader literature (
Second, it would be valuable to evaluate additional biotic contexts, such as alternative resource availability, the presence of intra- and inter-specific competitors and effects of visual predator cues. For instance, prey preference for different resources, such as macrophyte or detritus, could have a significant effect on FRs for omnivorous crayfish (
Ecological impacts of NNS are notoriously challenging to anticipate given a myriad of biotic and abiotic context-dependencies that can affect the organismal performance in nature. The comparative FR approach has been used to incorporate these context-dependencies to predict the impact of NNS, through relative comparisons of per capita effects (
The ecology of fear predicts that the cost of anti-predator behaviour is associated with reduced offspring, thus modulating consumer abundance (
Assistance in the collection of fish provided by the Washington Department of Fish and Wildlife and the collection of crayfish by the Oregon Department of Fish and Wildlife, the Washington Crawfish Company and Dwayne Lamb. We thank Alexandre Bee Amaral, Jon Wittouck and lab-mates in the Freshwater Ecology & Conservation Lab for their help in assembling the mesocosms. We are grateful to Fulbright Brazil, the Fulbright Scholarship Board and the Bureau of the Educational and Cultural Affairs of the United States Department of State for the scholarship granted to LF as part of the Doctoral Dissertation Research Award programme. JRSV was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) – Process Numbers 02367/2018-7 and 303776/2015-3. JDO was supported by the Richard C. and Lois M. Worthington Endowed Professor in Fisheries Management from the School of Aquatic and Fishery Sciences, University of Washington. This study was also supported by Coordenação de Aperfeiçoamento de Pessoal do Nível Superior (CAPES) – Finance Code 001. All experiments were approved by the University of Washington Institutional Animal Care and Use Committee (permit 4172-12).
Data from functional response trials
Data type: xls
Explanation note: Data from functional response trials for each crayfish species under predator treatment and control.