Comparable temperature-dependent predatory impacts of two invasive crayfish, Pontastacus leptodactylus and Pacifastacus leniusculus

doi:10.21203/rs.3.rs-8038263/v1

Narrow-clawed crayfish (Pontastacus leptodactylus) are an emergent invasive species, with limited data regarding their potential ecological impacts. Predicting ecological impact in current and future climate conditions is essential to inform policy and management actions. Therefore, we determined temperature-dependent predation of P. leptodactylus compared to the well-studied Signal crayfish (Pacifastacus leniusculus) on native prey Gammarus pulex, along a seasonal gradient (9℃, 12℃, 17℃, and 22℃) using functional response. Both species exerted strong predatory impact on G. pulex at all temperatures, however, when field abundance was considered P. leptodactylus have a higher relative impact driven by higher field abundance for our sampled populations. P. leptodactylus relative impact potential will increase with temperature up to ~ 17℃ and was exacerbated when prey (G. pulex) response to temperature change was incorporated, due to decreased prey abundance at higher temperatures. Our findings indicate P. leptodactylus overlooked potential as a damaging invader, both currently and in the future, and highlight the importance of considering resource and consumer response to changing climate in impact assessments. We recommend that stakeholders consider renewed management appraisals for populations of P. leptodactylus to reduce spread and population size to minimise ecological harm.

Context-dependent impact

Functional response

Impact Assessment

Prey Response

Temperature-dependence

Freshwaters are ecologically, economically and socially important, providing a wide array of ecosystem services and economic value to humans (Vári et al. 2022) and supporting a disproportionately high diversity for their area (Strayer and Dudgeon 2010); 9.5% of all animal species and 1% of vascular plants known worldwide (Balian et al. 2008). However, freshwater biodiversity is declining faster than terrestrial and marine realms (Darwall et al. 2018; Tickner et al. 2020) as a result of multiple threats including invasive non-native species, climate-change, over-exploitation, destruction/alteration of habitat and pollution (Strayer and Dudgeon 2010; Reid et al. 2019; Tickner et al. 2020). Invasive species are a major driver of biodiversity loss worldwide (Bellard et al. 2016; Doherty et al. 2016; Blackburn et al. 2019; IPBES 2019), particularly within freshwaters (Sala et al. 2000; Cox and Lima 2006) which are typically heavily invaded (Strayer 2010). This is due to the wide range of introduction sources: aquaculture, ornamental trade, and ballast water release, and relatively low barriers to dispersal within freshwaters (Padilla and Williams 2004; Moorhouse and Macdonald 2015; Faria et al. 2025).

Crayfish are particularly damaging freshwater invaders (Mathers et al. 2020b; O’Hea Miller et al. 2024) which alter aquatic community structure through reduction of benthic fish, salmonid fry and macro-invertebrate abundance (Edmonds et al. 2011; Holdich et al. 2014; Galib 2020). This causes long term changes in macro-invertebrate community functional properties and composition (Mathers et al. 2020b). Frustratingly, invasive species impacts are typically observed after invasions are successful (Crooks 2005; Strayer et al. 2006), and eradication of established invasive crayfish remains challenging (Peay 2001; Gherardi et al. 2011; Simberloff 2021). Thus, to reduce future invasive impact, an emphasis should be on pre-emptively identifying potential new damaging invaders and implementing proactive policy to prevent invasions (Strayer 2010).

The Narrow-clawed crayfish (Pontastacus leptodactylus), native to the Ponto-Caspian region and widely introduced in Central Europe through the aquaculture pathway, is data deficient in terms of impact assessment compared to widely distributed invasive species like the Signal crayfish Pacifastacus leniusculus or Red swamp crayfish Procambarus clarkii (Holdich et al., 2008; Twardochleb et al. 2013). Concerningly, non-native P. leptodactylus have been shown to have greater impact on gatherer and shredder invertebrates then P. leniusculus (Jackson et al. 2014). This could be exacerbated by climate change and associated temperature increases, which can increase abundance or feeding rates of invasive species (Cuthbert and Briski 2021; Teesalu et al. 2025). Furthermore, based on current P. leptodactylus distribution and predicted suitable invasion range there is potential for range expansion into northern Europe in 2050 (Hodson et al. 2024). Consequently, temperature-dependent impact assessments are essential to evidence gather for future management of this potential emergent threat (Bradley et al. 2023). These impact assessments must also consider temperature-dependent prey response, given asymmetry in predator and prey responses to temperature can alter impact (Öhlund et al. 2015; Pintanel et al. 2021; Meehan and Lindo 2023) for a more holistic, accurate impact assessment (Dickey et al. 2020; South et al. 2022).

Comparative Functional response (FR), which captures density dependent consumption by an invader and compares it to other species, is a commonly used impact assessment (Dick et al. 2017; Faria et al. 2025). It holds that, invasive species have greater per-capita consumptive effects on resources than natives, and that greater impact is associated with greater per-capita effects (Ricciardi et al. 2013; Dick et al. 2014). Attack rate and handling parameters derived from the FR can be used to calculate the Functional Response Ratio (FRR), a composite impact metric that is consistently higher in invaders than natives (Cuthbert et al. 2019). This can be combined with observed abundances of invaders in different contexts, to give a Relative Impact Potential, which provides a field contextualised impact assessment with greater predictive power (Laverty et al. 2017; Dickey et al. 2020). The RIP metric can also incorporate contextual prey abundance (RIPq) to explore whether resource response changes, offset or exacerbate ecological impact (South et al. 2022).

Thus, we used comparative FR experiments to calculate impact and relative impact potential of P. leptodactylus and P. leniusculus preying on Gammarus pulex across four temperatures (9°C, 12°C, 17°C and 22°C ). Comparison with P. leniusculus contextualises P. leptodactylus impact relative to a well-studied destructive invader. Gammarus pulex were used as prey as they are ubiquitous, omnivorous keystone species which alter nutrient cycling through leaf shredding and structuring of macro-invertebrate assemblages (Kelly et al. 2002; Navel et al. 2010). We predicted greatest impact (through Functional Response Ratio and Relative Impact Potential) of P. leptodactylus at 22°C, as this was the temperature closest to their reported thermal optima: 20–25℃ (Kir et al. 2025). We also predicted that incorporating prey response would exacerbate RIP at higher temperatures, as G. pulex are a cold adapted species (Foucreau et al. 2014).

2.1. Animal Collection

Live P. leptodactylus were collected from Boshaw Whams Reservoir, West Yorkshire (N 53.547557 º, S -1.77340º), and P. leniusculus were collected from Settrington Beck, North Yorkshire (N 54.12001º, S -0.71992º) using trappy traps (Dimensions: 500 x 200 mm, diamond shaped mesh size: 30 x 20 mm) baited with cat or dog food. Traps were set overnight and retrieved in the morning (~ 18 h soak time). Gammarus pulex were collected using dip nets from Meanwood Beck, Leeds (N 53.83073˚, S -1.576˚) for use as prey.

2.2. Animal Maintenance

Crayfish were maintained in a controlled temperature laboratory in single sex, species specific holding tanks (internally 605 x 370 x 200mm; Stocking Density: 10–16) in ~ 30 L of continuously aerated dechlorinated water held at 9.2 ± 1.0°C. Shelter was provided using PVC pipes, crayfish were fed ad libitum with dried sycamore leaves and wheatgerm pellets, and water was changed weekly to maintain water quality. Gammarus pulex were held in the same environmental conditions, in a clear plastic holding tank (450 x 300 x 300mm) with glass beads as substrate and maintained on sycamore leaves.

2.3. Experiments

Experimental arenas were plastic tanks (internally L605 x W370 x H200mm) containing 24 L of continuously aerated dechlorinated water and no shelters, to avoid confounding FR results (per. South et al. 2019). Crayfish were randomly selected, sexed, patted dry and measured for mass (g) and carapace length (mm). Animals were size matched where possible, however, due to morphometric differences between species this was not always feasible, therefore a Kendall’s Tau correlation on mass and proportion was carried out, determining no significant correlations (SI1). No crayfish which had missing chelae or appendages, or which had recently moulted were used. Crayfish were then placed in experimental arenas without food for 24 hours, standardising hunger levels and acclimating crayfish to the arenas. Prey (live G. pulex, total length: 0.5–1.5 mm) were supplied at six densities; 2, 6, 10, 20, 40 and 50 at four temperatures (n = 6 per density per temperature per species). Crayfish were allowed to feed for three hours in the dark before being removed and remaining live prey counted. Controls consisted of prey being supplied at a density of 50 without a crayfish at each temperature (n = 3 per temperature).

Crayfish were reused to limit animal use, however, were not used for the same treatment and not within 3 days of a previous experiment. Crayfish were marked to identify them with a small amount of non-toxic nail varnish which had no impact on behaviour.

2.4. Temperature treatments

FR experiments detailed above were carried out at four temperatures in a controlled environment room: 9.2℃, 12℃, 17℃, and 22℃ ± 1.0℃. An incubator was used to acclimate the crayfish to the higher temperature at a rate of 1℃ an hour and then acclimated at temperature for at least one week before experimentation.

2.5. Statistical Analysis

All analyses and modelling were carried out in R 4.2.1 (R Core Team, 2022).

2.5.1. Functional Response

Functional response type was modelled using the R package ‘frair’ (v.0.5.100; Pritchard 2017) per Pritchard et al. (2017) (frair_test and frair_fit). This uses a binomial logistic regression to determine if the proportion of prey consumed decreases with increasing density. A significantly negative first order term indicates a Type II functional response. Alternately, if a significantly positive first order term and negative second order term is obtained it indicates a Type III functional response (Juliano 1998). Functional responses were modelled using maximum likelihood estimation (MLE, v.1.0.25.1; Bolker 2023) and Rogers' (1972) Random Predator Equation to account for prey depletion:

$$\:{\:N}_{e}=\:{N}_{0}(1-\text{e}\text{x}\text{p}(a\left({N}_{E}h-T\right))$$

1

In which, N_E represents the number of prey eaten, N₀ is the initial density of prey, a is the attack parameter, h is the handling parameter and T is the total time available.

Where models could not be fitted to a categorical functional response (P. leniusculus at 9°C), a flexible model was fitted (Real 1977; Vucic-Pestic et al. 2010b; Pritchard et al. 2017). This models a variation of Rogers' random predator equation (Eq. 1) but includes a scaling exponent (q) which is bounded from 0–1 where a categorical Type II functional responses q = 0 and in a Type III q = 1 (Eq. 2). Two-term binomial logistic regressions were used to find the most suitable starting parameters for q. This resulted in a flexible model with q fixed at 0.2.

$$\:{N}_{e}=\:{N}_{0}\left(1-\text{e}\text{x}\text{p}\left(b{N}_{0}^{q}\left({N}_{E}h-T\right)\right)\right)\:$$

2

In which, N_E is the number of prey consumed, N₀ is the initial prey density, b is the search coefficient, h is handling time, q is the scaling coefficient and T is the total time available. Suitability of each non-categorical model was compared to its categorical analogue with Akaike information criterion (AIC).

Both categorical and flexible models were fitted to the data using the Lambert W function (Bolker 2008). The data were non-parametrically bootstrapped (frair::frair_boot; n = 2000) creating 95% confidence intervals around the mean functional response curve for each treatment. This allows phenomenological assessment of population level differences where overlapping confidence intervals indicates lack of statistical difference between functional response curves.

2.5.2. Functional Response Ratio

Data were also non-parametrically bootstrapped (frair:: frair_boot; n = 30) and had 95% outliers removed, to mechanistically compare the Functional Response Ratio (FRR) (a/h or for flexible models b/h) allowing for a composite comparison of both a and h (Cuthbert et al. 2019). Data were over-dispersed so a generalised linear model (GLM) with a quasi-poisson error distribution was used to determine the effects of species and temperature on the FRR. The model was fitted with full interaction terms and simplified step wise. The R package “car” (v3.11; Fox and Weisberg, 2019) was used to interpret the model using a Type II or III sum of squares.

2.5.3. Relative Impact Potential (RIP)

FRR mean and SE generated from bootstrapping (frair:: frair_boot; n = 30) were also used in calculating RIP as in Dick et al., (2017) whereby:

$$\:RIP=\:\frac{FR\:X}{FR\:Y}\times\:\:\frac{AB\:X}{AB\:Y}\:$$

3

In which, FR refers to functional response or an equivalent impact metric, and AB refers to numerical response. FR X and AB X refer to the impact and abundance of population X, FR Y and AB Y refer to the same for population Y. Catch per unit effort (CPUE) for each species, the mean number of individuals caught per trap, was used as a numerical response abundance proxy. CPUE was based on catch data of the sampled P. leptodactylus (Harwood et al. 2025)d leniusculus populations across different temperatures, and temperature treatments were matched to the closest temperature with recorded CPUE (SI2). RIP was calculated for intraspecific comparisons between temperature treatments, and inter-species comparison within temperature treatments. Each species-temperature treatment combination RIP was visualised using a biplot, allowing for assessment of all combinations impact relative to each other. Pacifastacus leniusculus at 9℃ were not included in RIP analysis due to non-significant handling times which produce unreliable maximum feeding estimates and FRRs.

2.5.4. RIPq

RIPq was calculated as in South et al., (2022) accounting for prey abundance changes with temperature using a resource reproductive qualifier (RRQ) based on the average number of eggs per ovigerous females at different temperatures as observed by Hynes (1955), whereby:

$$\:RRQ=1/\frac{Reproductive\:Output\:at\:higher\:temperature}{Reproductive\:Output\:at\:lower\:temperature}$$

4

$$\:RIPq=RIP\times\:RRQ$$

5

Where egg number did not match one of the temperature treatments used, and average was taken between the closest relevant temperatures. The highest temperature observed by Hynes (1955) was 15.3℃, so this was used for both 17 and 22℃ (SI3).

Differences in RIP and RIPq were visualised across temperature comparisons of 12 to 9℃, 17 to 12℃, and 17 to 9℃. These temperatures were selected based on predicted median temperature increases of 1.2℃ in 2041-60, and 1.4℃ in 2080–2099 for RCP 2.6 (Lowe et al. 2018). 17℃ was included to visualise changes in relative impact in more extreme climate scenarios (RCP 8.5) with median temperature increases of 1.8℃ or 3.9℃ in 2041-60 or 2080-99 respectively (Lowe et al. 2018).

Control prey survival was >99% so prey mortality in the experimental groups was attributed to predation.

3.1. Functional Response Types

Using frair::frair_test did not identify a significant categorical Type II or III response for P. leniusculus at 9℃. Diagnostic two-term logistic regressions indicated that categorical Type III functional response models were inappropriate for this treatment (Table 1). Thus, it was modelled as a flexible type with the scaling exponent (q) fixed at 0.2, indicating a response between Type II and III. A significant Type II response was found for all the other treatments (Table 1).

3.2. FR curves under temperature

3.2.1. Between species

At 12°C and 17°C P. leniusculus functional response curves diverge from P. leptodactylus curves, possessing significantly different curves at low densities (ca. densities 0 – 15, and 15 – 20 respectively) driven by a higher attack parameter, indicated by curve steepness (Table 1; Figure 1B and C). At 9 and 22℃ P. leniusculus and P. leptodactylus had comparable functional responses indicated by overlapping confidence intervals (Table 1; Figure 1A and D). For P. leniusculus at 9℃ the FR curve does not plateau as foraging saturation did not occur, producing an unreliable and non-significant handling time. Consequently, the resulting maximum feeding estimate and functional response ratio (FRR) are not derived for P. leniusculus at 9℃. P. leptodactylus had similar-to-shorter handling time but conversely slower attack rates then P. leniusculus (Table 1, Figure 2).

3.2.2. Within species

Functional response curves had broadly overlapped confidence intervals for P. leptodactylus compared between temperature across all densities, whereas for P. leniusculus curves broadly overlapped at prey densities above 20 across all temperatures (SI4).

3.3. FRR

3.3.1. Between species

The interaction between temperature and species significantly affected FRR values (Table 2). As temperatures increased from 12℃ to 17℃ to 22℃ in P. leptodactylus FRR decreases, whereas for P. leniusculus FRR dips at 17℃, but remains relatively similar at 12℃ and 22℃ (Figure 3). Across all temperatures, P. leptodactylus have a significantly lower FRR then P. leniusculus (z = 11.517, p = <0.0001). Please see SI5 for mechanistic comparisons of attack rate and handling times.

3.3.2. Within species

Temperature altered P. leptodactylus FRR (x² = 37.20, df = 3 p = <0.01), where FRR was significantly lower at 9℃ compared to the other temperatures but there were no differences between FRR at 12-17℃ and 17-22℃ (Figure 3A, Table 3). Temperature also significantly impacted P. leniusculus FRR (x² = 10.29, df = 2 p = <0.01), where FRR was highest at 12℃ and lowest at 17℃ with significantly higher FRR at 12 compared to 17°C (Figure 3B, Table 3). Please see SI5 for mechanistic comparisons of attack rate and handling times.

3.4. Relative Impact Potential (RIP)

3.4.1. FRR RIP

Using the Functional Response Ratio (FRR) for RIP the highest relative impact on G. pulex is at 17℃ for P. leptodactylus and 12℃ for P. leniusculus. This is driven by high CPUE for P. leptodactylus and high FRR for P. leniusculus at the respective temperatures (Figure 4A). P. leptodactylus at 9℃ have the lowest relative impact driven by the lowest FRR and a low CPUE (SI6 for RIP values).

3.4.2. RIPq

Incorporating the resource reproductive qualifier into RIP increased RIP metric score across all temperature comparisons except from 22 to 17℃ where the RRQ was 1 because the same average egg number per females was used (SI3, Figure 4B, SI6 for all temperature

We combined FR experiments to compare the predatory impact of both Pontastacus leptodactylus and Pacifastacus leniusculus under four different temperature conditions: 9, 12, 17 and 22℃. P. leptodactylus and P. leniusculus both show similar Type II functional response across all temperatures, excepting P. leniusculus at 9℃. P. leptodactylus and P. leniusculus impact, based on FRR, varied significantly with temperature and was greatest at 12℃, contrary to our predictions. Across both species, P. leptodactylus had the greatest relative impact potential at 17℃. This was exacerbated when prey response to temperature change was incorporated.

Impact was comparable between P. leptodactylus and P. leniusculus at all temperatures as indicated by broadly overlapping Type II FR curves (Bollache et al. 2007; Alexander et al. 2014). Furthermore, at 12 and 17℃ FRR values of P. leptodactylus are similar or greater than mean FRR benchmark values for invaders with known high ecological impact (83.36) reported by (Cuthbert et al. 2019). Consequently, P. leptodactylus will likely be an impactful invader, over-predating G. pulex and destabilising broader freshwater systems and communities in a similar fashion to P. leniusculus (Dunoyer et al. 2014; Galib 2020; Mathers et al. 2020b). Whilst, our study was simplistic, based on arenas without structural complexity, which can tend to Type II FR’s (Vucic-Pestic et al. 2010a), we consider impact relative to a known damaging invader, thus similar results can be viewed as a proxy for high impact. Ultimately, significantly lower FRR in P. leptodactylus compared to P. leniusculus does suggest that per capita, P. leptodactylus would have lower predatory impacts on G. pulex than P. leniusculus. This is driven by P. leniusculus attack rate being almost twice as high as P. leptodactylus in all temperature conditions.

When incorporating field abundance for our sampled populations, P. leptodactylus have a greater relative impact potential then P. leniusculus due to higher abundance. P. leptodactylus’ higher abundance is surprising given P. leniusculus are typically more fecund (Chybowski 2013; Cìlbìz 2020) but likely reflects that P. leptodactylus were only sampled from lentic environments in which they had high abundance (Harwood et al. 2025)d leniusculus from lotic, which may drive the abundance difference. For example, P. leniusculus are less likely to establish in high-flow lotic environments, which may reduce our sampled populations abundance (Mathers et al. 2020a). This emphasises how contexts like hydrological regime influence impact and must be considered when making impact predictions, particularly when transferring knowledge across species or locations.

For P. leptodactylus, our results provide evidence of a population specific thermal optima of ~ 12–17℃; lower than the optima of 20–25℃ observed in Turkey (Kir et al. 2025). This adds to the body of evidence for observations of population specific functional responses for freshwater invaders like Faxonius limosus, Faxonius rusticus and Pseudorasbora parva (Boets et al. 2019; Grimm et al. 2020; Chicatun et al. 2024) and suggests if possible impact assessments be carried out at the population, not species level. Our lower optima likely reflect temperatures at Boshaw Whams reservoir, Yorkshire, which ranged from 0.7–19℃ (Harwood et al. 2025). The greater impact at 12–17℃ is consistent with previous research finding highest FRs at intermediate temperatures (Uiterwaal and DeLong 2020). Consequently, large temperature increases above 17℃ may reduce the ecological impact of P. leptodactylus within West Yorkshire particularly given gamete production is impaired from 19℃ which may simultaneously reduce abundance (Farhadi and Harlıoglu 2018).

As well as consumer response to different contexts like temperature, prey response should also be incorporated into impact assessments for more accurate impact predictions (Kumschick et al. 2015; Urban et al. 2016; South et al. 2022). British or cold-adapted Gammarus pulex populations show reduced reproductive functioning from 10–20℃, and reductions in survival from 15–30℃ (Welton and Clarke 1980; Foucreau et al. 2014). Coupled with the high thermal tolerance of P. leptodactylus (Kir et al. 2025) this suggests a predator-prey asymmetry in thermal responses, which may alter impact (Öhlund et al. 2015; Pintanel et al. 2021; Meehan and Lindo 2023). Considering consumer and prey abundance our RIPq results reflect that reduced reproductive output of G. pulex at higher temperatures will exacerbates P. leptodactylus impact. Nonetheless, thermal asymmetry can also occur in differing levels of fitness, metabolism, growth rates and drive observed patterns. For example, as temperatures increases from 5–15℃, G. pulex show an increase in motility (Vellinger et al. 2012). The significant decrease in FRR, from 12–17℃ for P. leniusculus, is driven by reduced attack rate. Perhaps increased motility of G. pulex at temperatures close to 15℃ may reduce opportunity to attack or successful attacks, which are computed by FR analyses as the same entity, producing the observed reduction in impact. Consequently, for accurate impact assessments, it is imperative we consider a variety of prey responses to the observed context alongside predator response.

While Pacifastacus lenuisculus is considered to be a pervasive threat to native species through predation and pathogen transfer, Pontastacus leptodactylus has been overlooked for management interventions. Nonetheless, P. leptodactylus is predicted to be an ecologically damaging invasive species now, and in the near future, whose relative impact potential will increase with temperature up to ~ 17℃. When incorporating prey response to temperature, into our predictions, we find an even greater relative impact, emphasising the threat of P. leptodactylus and highlighting the importance of including prey-response in impact assessments. Additionally, P. leptodactylus potential suitable range, currently and in the future, gives room for expansion from the current invasive distribution (Hodson et al. 2024). Therefore, we recommend that stakeholders consider renewed management appraisals for populations of P. leptodactylus to reduce spread and population size to minimise ecological harm.

Conflict of interest

The authors declare no conflict of interest

Author contributions

Conceptualisation: JS, JH Formal Analysis: JH, Investigation: JH, KC, MH, EC, A-JN, Methodology: JH, KC, JS, Supervision: MH, JS, Writing – Original Draft: JH, Writing – Review & Editing: JH, JS

Acknowledgements

We thank students of Biology, English and History from the University of Leeds who were roped into trapping crayfish and retrieving Gammarus. JH would also like to thank Isobel Richards for her support throughout the process. JS acknowledges funding from UKRI Future Leaders Fellowship [Grant/Award Number: MR/X035662/1].

Data Availability

Data and associated metadata will be available on Figshare upon acceptance.

Alexander ME, Dick JTA, Weyl OLF, et al (2014) Existing and emerging high impact invasive species are characterized by higher functional responses than natives. Biol Lett 10:20130946. https://doi.org/10.1098/rsbl.2013.0946

Balian E, Segers H, Lévêque C, Martens K (2008) The Freshwater Animal Diversity Assessment: An overview of the results. Hydrobiologia 595:627–637. https://doi.org/10.1007/s10750-007-9246-3

Bellard C, Cassey P, Blackburn TM (2016) Alien species as a driver of recent extinctions. Biol Lett 12:20150623. https://doi.org/10.1098/rsbl.2015.0623

Blackburn TM, Bellard C, Ricciardi A (2019) Alien versus native species as drivers of recent extinctions. Front Ecol Environ 17:203–207. https://doi.org/10.1002/fee.2020

Boets P, Laverty C, Fukuda S, et al (2019) Intra- and intercontinental variation in the functional responses of a high impact alien invasive fish. Biol Invasions 21:1751–1762. https://doi.org/10.1007/s10530-019-01932-y

Bolker B, R Development Core Team (2023) _bbmle: Tools for General Maximum Likelihood Estimation_. R package version 1.0.25.1, <https://CRAN.R-project.org/package=bbmle>.

Bolker B (2008) Ecological Models and Data in R. Princeton University Press

Bollache L, Dick JTA, Farnsworth KD, Montgomery WI (2007) Comparison of the functional responses of invasive and native amphipods. Biol Lett 4:166–169. https://doi.org/10.1098/rsbl.2007.0554

Bradley BA, Beaury EM, Fusco EJ, Lopez BE (2023) Invasive Species Policy Must Embrace a Changing Climate. BioScience 73:124–133. https://doi.org/10.1093/biosci/biac097

Chicatun V, Sheppard NLM, Ricciardi A (2024) Intraspecific variation in the functional response of an invasive crayfish under different temperatures. Can J Zool 102:746–758. https://doi.org/10.1139/cjz-2024-0006

Chybowski Ł (2013) Absolute fecundity of two populations of signal crayfish, Pacifastacus leniusculus (Dana). Fish Aquat Life 21:357–362. https://doi.org/10.2478/aopf-2013-0036

Cìlbìz M (2020) Pleopodal fecundity of narrow-clawed crayfish (Pontastacus leptodactylus Eschscholtz, 1823). Invertebr Reprod Dev 64:208–218. https://doi.org/10.1080/07924259.2020.1762771

Cox JG, Lima SL (2006) Naiveté and an aquatic–terrestrial dichotomy in the effects of introduced predators. Trends Ecol Evol 21:674–680. https://doi.org/10.1016/j.tree.2006.07.011

Crooks JA (2005) Lag times and exotic species: The ecology and management of biological invasions in slow-motion1. Écoscience 12:316–329. https://doi.org/10.2980/i1195-6860-12-3-316.1

Cuthbert RN, Briski E (2021) Temperature, not salinity, drives impact of an emerging invasive species. Sci Total Environ 780:146640. https://doi.org/10.1016/j.scitotenv.2021.146640

Cuthbert RN, Dickey JWE, Coughlan NE, et al (2019) The Functional Response Ratio (FRR): advancing comparative metrics for predicting the ecological impacts of invasive alien species. Biol Invasions. https://doi.org/10.1007/s10530-019-02002-z

Darwall W, Bremerich V, De Wever A, et al (2018) The Alliance for Freshwater Life: A global call to unite efforts for freshwater biodiversity science and conservation. Aquat Conserv Mar Freshw Ecosyst 28:1015–1022. https://doi.org/10.1002/aqc.2958

Dick JTA, Alexander ME, Jeschke JM, et al (2014) Advancing impact prediction and hypothesis testing in invasion ecology using a comparative functional response approach. Biol Invasions 16:735–753. https://doi.org/10.1007/s10530-013-0550-8

Dick JTA, Laverty C, Lennon JJ, et al (2017) Invader Relative Impact Potential: a new metric to understand and predict the ecological impacts of existing, emerging and future invasive alien species. J Appl Ecol 54:1259–1267. https://doi.org/10.1111/1365-2664.12849

Dickey JWE, Cuthbert RN, South J, et al (2020) On the RIP: using Relative Impact Potential to assess the ecological impacts of invasive alien species. NeoBiota 55:27–60. https://doi.org/10.3897/neobiota.55.49547

Doherty TS, Glen AS, Nimmo DG, et al (2016) Invasive predators and global biodiversity loss. Proc Natl Acad Sci 113:11261–11265. https://doi.org/10.1073/pnas.1602480113

Dunoyer L, Dijoux L, Bollache L, Lagrue C (2014) Effects of crayfish on leaf litter breakdown and shredder prey: are native and introduced species functionally redundant? Biol Invasions 16:1545–1555. https://doi.org/10.1007/s10530-013-0590-0

Edmonds NJ, Riley WD, Maxwell DL (2011) Predation by Pacifastacus leniusculus on the intra-gravel embryos and emerging fry of Salmo salar. Fish Manag Ecol 18:521–524. https://doi.org/10.1111/j.1365-2400.2011.00797.x

Faria L, Cuthbert R, Dickey J, et al (2025) Non-native species have higher consumption rates than their native counterparts. Biol Rev Camb Philos Soc. https://doi.org/10.1111/brv.13179

Foucreau N, Cottin D, Piscart C, Hervant F (2014) Physiological and metabolic responses to rising temperature in Gammarus pulex (Crustacea) populations living under continental or Mediterranean climates. Comp Biochem Physiol A Mol Integr Physiol 168:69–75. https://doi.org/10.1016/j.cbpa.2013.11.006

Fox J, Weisberg S (2019) _An R Companion to Applied Regression_, Third edition. Sage, Thousand Oaks CA. <https://www.john-fox.ca/Companion/>.

Galib S (2020) THE ECOLOGICAL IMPACTS OF SIGNAL CRAYFISH IN UPLAND STREAM ECOSYSTEMS. Doctoral, Durham University

Gherardi F, Aquiloni L, Diéguez-Uribeondo J, Tricarico E (2011) Managing invasive crayfish: is there a hope? Aquat Sci 73:185–200. https://doi.org/10.1007/s00027-011-0181-z

Grimm J, Dick JTA, Verreycken H, et al (2020) Context-dependent differences in the functional responses of conspecific native and non-native crayfishes. In: NeoBiota. pp 71–88

Harwood M, Stebbing PD, Dunn AM, et al (2025) Rapid assessment of population dynamics and monitoring methods for invasive narrow clawed crayfish Pontastacus leptodactylus in a freshwater reservoir. Knowl Manag Aquat Ecosyst 22. https://doi.org/10.1051/kmae/2025017

Hodson J, South J, Cancellario T, Guareschi S (2024) Multi-method distribution modelling of an invasive crayfish (Pontastacus leptodactylus) at Eurasian scale. Hydrobiologia. https://doi.org/10.1007/s10750-024-05641-z

Holdich DM, James J, Jackson C, Peay S (2014) The North American signal crayfish, with particular reference to its success as an invasive species in Great Britain. Ethol Ecol Evol 26:232–262. https://doi.org/10.1080/03949370.2014.903380

Holdich DM, Reynolds J, Souty-Grosset C, Sibley P (2008) A review of the ever increasing threat to European crayfish from non-indigenous crayfish species. Knowl Manag Aquat Ecosyst. http://dx.doi.org/101051/kmae/2009025 11:

Hynes HBN (1955) The Reproductive Cycle of Some British Freshwater Gammaridae. J Anim Ecol 24:352–387. https://doi.org/10.2307/1718

IPBES (2019) Summary for policymakers of the global assessment report on biodiversity and ecosystem services. Zenodo

Jackson MC, Jones T, Milligan M, et al (2014) Niche differentiation among invasive crayfish and their impacts on ecosystem structure and functioning. Freshw Biol 59:1123–1135. https://doi.org/10.1111/fwb.12333

Juliano SA (1998) Nonlinear Curve Fitting: Predation and Functional Response Curves. In: Design and Analysis of Ecological Experiments. Chapman and Hall/CRC

Kelly DW, Dick JTA, Montgomery WI (2002) The functional role of Gammarus(Crustacea, Amphipoda): shredders, predators, or both? Hydrobiologia 485:199–203. https://doi.org/10.1023/A:1021370405349

Kir M, Ege ÇINAR İ, Can SUNAR M, Topuz M (2025) Acclimation, thermal tolerance and aerobic metabolism of narrow-clawed crayfish, Pontastacus leptodactylus (Eschscholtz, 1823). J Therm Biol 104045. https://doi.org/10.1016/j.jtherbio.2025.104045

Kumschick S, Gaertner M, Vilà M, et al (2015) Ecological Impacts of Alien Species: Quantification, Scope, Caveats, and Recommendations. BioScience 65:55–63. https://doi.org/10.1093/biosci/biu193

Laverty C, Green KD, Dick JTA, et al (2017) Assessing the ecological impacts of invasive species based on their functional responses and abundances. Biol Invasions 19:1653–1665. https://doi.org/10.1007/s10530-017-1378-4

Lowe J, Bernie D, Bett P, et al (2018) UKCP18 Overview report. Met Office Hadley Centre

Mathers KL, White JC, Fornaroli R, Chadd R (2020a) Flow regimes control the establishment of invasive crayfish and alter their effects on lotic macroinvertebrate communities. J Appl Ecol 57:886–902. https://doi.org/10.1111/1365-2664.13584

Mathers KL, White JC, Guareschi S, et al (2020b) Invasive crayfish alter the long-term functional biodiversity of lotic macroinvertebrate communities. Funct Ecol 34:2350–2361. https://doi.org/10.1111/1365-2435.13644

Meehan ML, Lindo Z (2023) Mismatches in thermal performance between ectothermic predators and prey alter interaction strength and top-down control. Oecologia 201:1005–1015. https://doi.org/10.1007/s00442-023-05372-3

Moorhouse TP, Macdonald DW (2015) Are invasives worse in freshwater than terrestrial ecosystems? WIREs Water 2:1–8. https://doi.org/10.1002/wat2.1059

Navel S, Mermillod-Blondin F, Montuelle B, et al (2010) Interactions between fauna and sediment control the breakdown of plant matter in river sediments. Freshw Biol 55:753–766. https://doi.org/10.1111/j.1365-2427.2009.02315.x

O’Hea Miller SB, Davis AR, Wong MYL (2024) The Impacts of Invasive Crayfish and Other Non-Native Species on Native Freshwater Crayfish: A Review. Biology 13:610. https://doi.org/10.3390/biology13080610

Öhlund G, Hedström P, Norman S, et al (2015) Temperature dependence of predation depends on the relative performance of predators and prey. Proc R Soc B Biol Sci 282:20142254. https://doi.org/10.1098/rspb.2014.2254

Padilla DK, Williams SL (2004) Beyond ballast water: aquarium and ornamental trades as sources of invasive species in aquatic ecosystems. Front Ecol Environ 2:131–138. https://doi.org/10.1890/1540-9295(2004)002[0131:BBWAAO]2.0.CO;2

Peay S (2001) Eradication of Alien Crayfish Populations. Environment Agency

Pintanel P, Tejedo M, Salinas-Ivanenko S, et al (2021) Predators like it hot: Thermal mismatch in a predator–prey system across an elevational tropical gradient. J Anim Ecol 90:1985–1995. https://doi.org/10.1111/1365-2656.13516

Pritchard D (2017) _frair: Tools for Functional Response Analysis_. R package version 0.5.100, <https://CRAN.R-project.org/package=frair>.

Pritchard DW, Paterson RA, Bovy HC, Barrios-O’Neill D (2017) frair: an R package for fitting and comparing consumer functional responses. Methods Ecol Evol 8:1528–1534. https://doi.org/10.1111/2041-210X.12784

Real LA (1977) The Kinetics of Functional Response. Am Nat 111:289–300. https://doi.org/10.1086/283161

Reid AJ, Carlson AK, Creed IF, et al (2019) Emerging threats and persistent conservation challenges for freshwater biodiversity. Biol Rev 94:849–873. https://doi.org/10.1111/brv.12480

Ricciardi A, Hoopes M, Marchetti M, Lockwood J (2013) Progress toward understanding the ecological impacts of nonnative species. Ecol Monogr 83:263–282. https://doi.org/10.1890/13-0183.1

Rogers D (1972) Random Search and Insect Population Models. J Anim Ecol 41:369–383. https://doi.org/10.2307/3474

Sala OE, Stuart Chapin F, III, et al (2000) Global Biodiversity Scenarios for the Year 2100. Science 287:1770–1774. https://doi.org/10.1126/science.287.5459.1770

Simberloff D (2021) Maintenance management and eradication of established aquatic invaders. Hydrobiologia 848:2399–2420. https://doi.org/10.1007/s10750-020-04352-5

South J, Dickey JWE, Cuthbert RN, Dick JTA (2022) Combining resource population dynamics into impact assessments of native and invasive species under abiotic change. Ecol Indic 142:109260. https://doi.org/10.1016/j.ecolind.2022.109260

South J, Mccard M, Khosa D, et al (2019) The effect of prey identity and substrate type on the functional response of a globally invasive crayfish. NeoBiota 52:. https://doi.org/10.3897/neobiota.52.39245

Strayer DL (2010) Alien species in fresh waters: ecological effects, interactions with other stressors, and prospects for the future. Freshw Biol 55:152–174. https://doi.org/10.1111/j.1365-2427.2009.02380.x

Strayer DL, Dudgeon D (2010) Freshwater biodiversity conservation: recent progress and future challenges. J North Am Benthol Soc 29:344–358. https://doi.org/10.1899/08-171.1

Strayer DL, Eviner VT, Jeschke JM, Pace ML (2006) Understanding the long-term effects of species invasions. Trends Ecol Evol 21:645–651. https://doi.org/10.1016/j.tree.2006.07.007

Teesalu P, Muuga J-M, Hurt M, et al (2025) Effects of temperature on marbled crayfish (Procambarus virginalis, Lyko 2017) invasion ecology. Hydrobiologia 852:3541–3558. https://doi.org/10.1007/s10750-025-05828-y

Tickner D, Opperman JJ, Abell R, et al (2020) Bending the Curve of Global Freshwater Biodiversity Loss: An Emergency Recovery Plan. BioScience 70:330–342. https://doi.org/10.1093/biosci/biaa002

Uiterwaal SF, DeLong JP (2020) Functional responses are maximized at intermediate temperatures. Ecology 101:e02975. https://doi.org/10.1002/ecy.2975

Urban MC, Bocedi G, Hendry AP, et al (2016) Improving the forecast for biodiversity under climate change. Science 353:aad8466. https://doi.org/10.1126/science.aad8466

Vári Á, Podschun SA, Erős T, et al (2022) Freshwater systems and ecosystem services: Challenges and chances for cross-fertilization of disciplines. Ambio 51:135–151. https://doi.org/10.1007/s13280-021-01556-4

Vellinger C, Felten V, Sornom P, et al (2012) Behavioural and Physiological Responses of Gammarus pulex Exposed to Cadmium and Arsenate at Three Temperatures: Individual and Combined Effects. PLoS ONE 7:e39153. https://doi.org/10.1371/journal.pone.0039153

Vucic-Pestic O, Birkhofer K, Rall BC, et al (2010a) Habitat structure and prey aggregation determine the functional response in a soil predator–prey interaction. Pedobiologia 53:307–312. https://doi.org/10.1016/j.pedobi.2010.02.003

Vucic-Pestic O, Rall BC, Kalinkat G, Brose U (2010b) Allometric functional response model: body masses constrain interaction strengths. J Anim Ecol 79:249–256. https://doi.org/10.1111/j.1365-2656.2009.01622.x

Welton JS, Clarke RT (1980) Laboratory Studies on the Reproduction and Growth of the Amphipod, Gammarus pulex (L.). J Anim Ecol 49:581–592. https://doi.org/10.2307/4265

Table 1 Functional mechanistic parameters (a, b, h, and 1/h) associated significance levels using Rogers’ random predator equation, bias accelerated and corrected 95% confidence intervals (BCa CIs) for a, b and h, scaling co-efficient (q), and the functional response ratio (a/h) for Pontastacus leptodactylus and Pacifastacus leniusculus under different temperature conditions

Species	Temperature (℃)	First order term (p-value)	FR Type	a (p-value)	a 95% BCa CI	h (p-value)	h 95% BCa CI	b (p-value)	B 95% BCa CI	q (p-value)	Maximum feeding estimate/3 hours (1/h)	Functional response ratio (a/h or b/h)
P. leptodactylus	9	-0.02 (<0.0001)	II	1.11 (<0.0001)	0.22-0.61	0.023 (<0.0001)	0-0.15	-	-	-	43.47	48.26
P. leptodactylus	12	-0.03 (<0.0001)	II	1.93 (<0.0001)	1.4-2.8	0.022 (<0.0001)	0.005-0.04	-	-	-	45.45	87.73
P. leptodactylus	17	-0.01 (<0.0001)	II	1.17 (<0.0001)	0.8-1.62	0.015 (<0.0001)	0-0.033	-	-	-	66.66	78
P. leptodactylus	22	-0.05 (<0.0001)	II	2.28 (<0.0001)	1.02-4.19	0.034 (<0.0001)	0.012-0.073	-	-	-	29	67.06
P. leniusculus	9	-0.07 (<0.01)	Non-categorical	-	-	0.000083 (0.99)	-0.39-0.40	0.84 (<0.01)	0.28-2.67	0.030 (0.84)	12,048.19	10,120.48
P. leniusculus	12	-0.12 (<0.0001)	II	4.88 (<0.0001)	3.24-8.26	0.033 (<0.0001)	0.019-0.048	-	-	-	30	147.88
P. leniusculus	17	-0.03 (<0.0001)	II	2.24 (<0.0001)	1.32-3.53	0.020 (<0.0001)	0.004-0.034	-	-	-	50	112
P. leniusculus	22	-0.11 (<0.0001)	II	5.29 (<0.0001)	3.22-9.65	0.037 (<0.0001)	0.022-0.055	-	-	-	27.03	142.97

Table 2 Model terms for all variables from a generalised linear model with a quasi-poisson error distribution used to determine differences in FRR based on species (Pontastacus leptodactylus or Pacifastacus leniusculus), and temperature (12℃, 17℃ and 22℃ interactions, using a Type 3 ANOVA and χ2 to report the effects. 9℃ is not included, as FRR was only available for P. leptodactylus

Model terms	X²	df	p-value
Species	35.096	1	<0.0001
Temperature	13.388	2	<0.0001
Species*Temperature	8.390	2	<0.05

Table 3 Pairwise comparison results from type II sum of squares used to determine significant differences in FRR for Pontastacus leptodactylus and Pacifastacus leniusculus within species at different temperature conditions: 9℃, 12℃, 17℃ and 22℃. 9℃ was not included in comparison for P. leniusculus due to non-significant handling times

Species	Comparison	z	p-value
P. leptodactylus	9℃ - 12℃	-5.68	<0.0001
P. leptodactylus	9℃ - 17℃	-4.376	<0.0001
P. leptodactylus	9℃ - 22℃	-2.796	<0.05
P. leptodactylus	12℃ - 17℃	1.353	0.52
P. leptodactylus	12℃ - 22℃	3.133	<0.01
P. leptodactylus	17℃ - 22℃	1.73	0.30
P. leniusculus	12℃ - 17℃	3.11	<0.01
P. leniusculus	17℃ - 22℃	-2.23	0.06
P. leniusculus	12℃ - 22℃	0.99	0.57

Comparable temperature-dependent predatory impacts of two invasive crayfish, Pontastacus leptodactylus and Pacifastacus leniusculus

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods