Pet cat personality linked to owner‐reported predation frequency

Abstract The domestic cat, Felis catus, is one of the most popular and widespread domestic animals. Because domestic cats can reach high population densities and retain at least some tendency to hunt, their overall impact on wildlife can be severe. Domestic cats have highly variable predation rates depending on the availability of prey in their environment, their owners' practices, and individual cat characteristics. Among these characteristics, cat personality has recently been hypothesized to be an important factor contributing to variations in the hunting activity of cats. In this study, we surveyed 2508 cat owners living in France about their cats' personalities, using the Feline Five personality framework, and the frequency with which cats bring home prey. Personality traits were analyzed using factor analysis and related to predation frequency using cumulative logit models. For both birds and small mammals, cats with high levels of extraversion or low levels of neuroticism had significantly higher frequencies of prey return. Owners whose cats had low levels of agreeableness or high levels of dominance reported a significantly lower frequency of bird return. Personality differences therefore seem to contribute to the high variability in predation rates among domestic cats. We also found that the owner‐reported prey return frequencies were significantly higher for cats spending more time outdoors, for non‐pedigree cats, and for owners living in rural or suburban areas as opposed to urban areas. By contrast, we did not detect an effect of cat sex or age on their reported prey return rates.


| INTRODUC TI ON
The domestic cat, Felis catus, is currently one of the most common carnivores in the world (O'Brien & Johnson, 2007). Cats are generalist predators introduced by humans globally, and their potential impact on wildlife is the subject of growing international interest and concern (Crowley et al., 2020a;Loss & Marra, 2017). They hunt many types of prey, including invertebrates and vertebrates, mainly mammals, birds, and reptiles (e.g., Barratt, 1997;Castañeda et al., 2019Castañeda et al., , 2020. The ecological impacts of cats have been shown to be particularly severe on island ecosystems, where island vertebrates have never coexisted with such introduced mammalian carnivores, and cats are a major driver of extinctions of insular endemic birds, mammals, and reptiles (Bonnaud et al., 2012;Doherty et al., 2016;Medina et al., 2011;Palmas et al., 2017). On continents, cats have been estimated to be responsible for high vertebrate mortality (e.g., Blancher, 2013;Loss et al., 2013;Murphy et al., 2019), although the extent to which their predation represents a form of compensatory or additive mortality is currently under debate (Loss & Marra, 2017), as they consume the most abundant prey and rarely the most vulnerable or declining species.
The majority of research to date has focused on the behavior and impacts of feral cats (see the review of Loss et al., 2022), which are dependent on the abundance and availability of natural prey species.
However, most pet cats that are fed by their owners retain some tendency to hunt (Thomas et al., 2012;Tschanz et al., 2011), and as they can reach very high population densities in areas where humans are also numerous (Baker et al., 2005;Sims et al., 2008), their overall impact can be severe. Several studies have shown that pet cats have highly variable predation rates (Loyd et al., 2013;Tschanz et al., 2011).
For example, Baker et al. (2008) and Thomas et al. (2012), respectively, showed in the cities of Bristol and Reading, UK, that approximately 60% of pet cats did not return prey home in the study period, highlighting the importance of identifying the factors that determine the predation rates of individual cats. Cecchetti, Crowley, Goodwin, and McDonald (2021) recently reviewed the drivers of hunting behavior in domestic cats. For the authors, whereas general cat hunting is mainly driven by evolutionary constraints and the associated physiological and nutritional requirements, the causes of variation in hunting behaviors among pet cats mainly relate to prey availability in the environment and the owners' practices. These practices include the level of outdoor access given to their cats, the amount and quality of the food provided, and the amount of time spent playing with the cat .
Variations in hunting activity have also been linked to the individual characteristics of cats such as their sex, age, and body size (Kays & DeWan, 2004;Moseby et al., 2015), although a number of studies have failed to find an association with these factors (Cordonnier et al., 2022;Loyd et al., 2013;Tschanz et al., 2011;Woods et al., 2003). Recently, Cecchetti et al. (2021a) hypothesized that personality could be a significant factor contributing to variations in hunting activity between cats. Over the past few decades, it has been recognized that in numerous animal taxa ranging from invertebrates to vertebrates, individuals show different behavioral tendencies that are consistent over time and across ecological contexts, a phenomenon commonly known as animal personalities (Réale et al., 2007(Réale et al., , 2010Wolf & Weissing, 2012). For example, boldness, aggressiveness, or sociability are commonly studied animal personality traits (Réale et al., 2007). Personality traits are frequently correlated: for example, animals that are bolder in risky situations also have a tendency to be more aggressive toward conspecifics, resulting in what is known as "behavioral syndromes" (Sih et al., 2004). Animal personalities have substantial consequences for numerous ecological processes (Brehm et al., 2019;Spiegel et al., 2017;Wolf & Weissing, 2012). Regarding predator-prey interactions, several studies have shown that individual differences in predator behavior can influence hunting (Pettorelli et al., 2011). For example, in several predator fish species, bolder individuals have a markedly higher predation rate compared with shyer ones (Ioannou et al., 2008;Rhoades et al., 2019). In their review of the drivers of hunting behavior in domestic cats, Cecchetti et al. (2021a) speculated that cats with certain personality traits, particularly those with high levels of boldness and extraversion, could potentially be more motivated to hunt wild prey. To our knowledge, this hypothesis has never been investigated.
Currently, the assessment of personality traits in domestic cats is most often based on surveys of people familiar with the animals, usually their owners (Bradshaw, 2016;Wedl et al., 2011), as this is both a reliable and time-efficient method (Bennett et al., 2017).
These studies (reviewed in Gartner & Weiss, 2013;Vitale Shreve & Udell, 2015;Mikkola et al., 2021) usually produced between one and seven personality factors, with the three most common factors being the personality traits of sociable, dominant, and curious, albeit with varying names. In this study, we used the Feline Five personality model of Litchfield et al. (2017), which consists of five personality dimensions in domestic cats: neuroticism, extraversion, dominance, impulsiveness, and agreeableness (see further details in the 'Section 2').
In this study, our primary objective is to determine whether the personality traits of pet cats are related to their hunting activity. To this end, we surveyed a large sample of cat owners living in France and estimated the personality traits of their cats using the Feline Five personality model of Litchfield et al. (2017) as well as the frequency of birds and mammals returned home by the cats as reported by their owners. We expected that cats with "low neuroticism (boldness, leading to travelling, exploring) or high extraversion (curiosity, leading to boredom), would potentially be more interested in hunting wild prey" , To control for potential confounding factors, we also included questions about variables previously shown to influence pet cat predation: type of environment around the home, time spent outdoors, individual characteristics, and breed (Castañeda et al., 2019(Castañeda et al., , 2020Cordonnier et al., 2022;Kauhala et al., 2015;Lepczyk et al., 2004;Robertson, 1998;Salonen et al., 2019).

| Questionnaire design and dissemination
A questionnaire was developed to collect information on French pet cats regarding their personality (five personality traits model) and the frequency with which their owners observed them bringing home birds and small mammals (ranging from never to very often, defined as once a week or more). To control for potential confounding factors, additional information was gathered on other characteristics of the cats (sex, age, and breed) and their living conditions (type of dwelling, type of the area around the dwelling, amount of time spent outdoors). The questionnaire was hosted online on the Google Form platform.
Households in France with at least one pet cat were targeted through postings on social media. We asked respondents with multiple cats to focus on one particular cat, the one they wanted. The survey was anonymous, and no personal information was collected from the respondents. In the introduction part of the survey, respondents indicated their consent to participate in the study. The study complied with the legal requirements in France: as no personal information was collected, ethics approval was not mandatory, as was confirmed by the Research Ethics Committee of Paris-Saclay (Polethis, report from January 4, 2021).
The questionnaire consisted of four sections (Appendix S1).
The first section focused on the cat characteristics: sex (female, male, unknown), age (<1 years, 1-2 years, 2-10 years, over 10 years, unknown), breed (Bengal, Birman, British Shorthair, Chartreux, Maine Coon, Persian, Ragdoll, Savannah, Sphynx, Siamese, Turkish Angora, non-pedigree, European, other, unknown). Note that in France "European" means "non-pedigree." We offered the two options, because some owners might have been more familiar with one word than the other. The second section focused on the living conditions of the cat: type of housing (apartment without balcony, apartment with balcony, subdivision house, individual house), type of environment (urban, suburban, or  The third section involved assessing the personality traits. Litchfield et al. (2017) determined that the personality profiles of cats are organized around five factors that represent traits related to neuroticism, extraversion, agreeableness, dominance, and impulsivity. Each factor can be evaluated using a list of adjectives that have varying correlations with the trait in question. In our questionnaire, to ensure short response times and thus high completion rates (e.g., Plowman et al., 2013), we selected 15 of the 52 adjectives used in the original study of Litchfield et al. (2017). For each of the five personality traits, we selected three adjectives based on two criteria. First, we selected adjectives with unequivocal translations in French to avoid ambiguity for the respondents. Second, we used the factor scores of Litchfield et al. (2017) for each adjective to select those with a high correlation with the relevant personality trait and a low correlation with the four others in order to facilitate the interpretation of the results. For example, the adjective affectionate was selected, because it is readily translatable in French and has a high correlation with the personality trait of agreeableness and a low correlation with the four other personality traits. In English, we chose the following 15 adjectives. For neuroticism we chose: shy, calm (negative loading), and fearful of other cats; for extraversion: smart, vigilant, and persevering; for agreeableness: affectionate, friendly to people, and solitary (negative loading); for dominance: bullying, dominant, and aggressive to other cats; and for impulsiveness: impulsive, predictable (negative loading), and distractible.
Each of these 15 adjectives was presented to the owners who could choose between strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree.
The final section of the questionnaire focused on the prey returned home as observed by the owners and included the reported frequency of return of birds and small mammals (daily, 1-6 times per week, 2-3 times per month, 1-3 times per trimester, 1-3 times per year, never). At the end of the survey, we added an optional openended question to give the owners the opportunity to add any comments that they wished to share about their cat and to communicate any insights that may have been overlooked in the survey (Harland & Holey, 2011).
The social network Facebook®was chosen as a channel to disseminate the questionnaire. This network has a large number of user groups dedicated to cats, which made it possible to conduct a large-scale study. The questionnaire was distributed in 23 Frenchspeaking groups from February 9, 2021, to March 14, 2021, which allowed us to collect a total of 3217 responses. The dataset was deposited in the Mendeley repository (https://data.mende ley.com/ datas ets/ht5p5 pg7b7/ 1; DOI: 10.17632/ht5p5pg7b7.1).

| Data treatment and statistical analyses
All analyses were conducted using R v.4.2 (http://www.R-proje ct.org). For all statistical tests, the level of significance was set at p < .05.

| Factor analysis of personality structure
To ensure that the personality traits of the cats were reliably described by the owners, we removed from the analyses the surveys indicating that the owners did not spend any time with their cat (n = 10) and those with comments that prevented their use to study the personality traits (e.g., respondent not the cat owner, recently adopted cat, cat with a major health issue; n = 21). Like all animal species, cats go through different stages of development, and in juveniles, personality and predatory behavior are not yet stable (Lowe & Bradshaw, 2001). Following Litchfield et al. (2017), we conservatively excluded cats aged under 1 year (n = 614) from the dataset.
Finally, the responses with missing data in the set of personality adjectives were also removed (n = 64). The final dataset included 2508 responses.
We performed exploratory factor analysis on the personality variables (15 adjectives evaluated by the owners) to first determine the number of personality traits to be extracted and then estimate the values of each trait for each cat (Hutcheson & Sofroniou, 1999). We initially ensured that the data were suitable for factor analysis using Bartlett's test of sphericity, which was significant (p < .01), and the Kaiser-Meyer-Olkin (KMO) criterion, which had an overall value of 0.722 (depending on the authors of the statistical tests, a value above 0.5 or 0.6 is considered to mean that the sampling is adequate). Both indicators thus show that the data were suitable for factor analysis (Hutcheson & Sofroniou, 1999;Kaiser, 1974). To determine the number of factors -here, personality traits -to extract, we used the empirical Kaiser criterion (see Braeken & Van Assen, 2017 for details) and parallel analysis with principal component analysis (PCA) (comparing the eigenvalues obtained to those generated from a Monte-Carlo simulated matrix), which indicated that four factors should be retained. We therefore choose to retain four factors, and used maximum likelihood factor analysis to extract them from the 15 adjectives. We obliquely rotated these factors (i.e., correlations between them were allowed), because personality traits are frequently correlated, as shown by the existence of personality syndromes. As in previous studies (e.g., Weiss et al., 2015), to interpret the factors, we defined salient loadings as those equal to

| Breed and personality
We tested the link between breed and personality traits by computing the Euclidian distance between personality profiles for each pair of cats to produce a resemblance matrix from which we conducted a nonparametric (permutational) analysis of variance (permanova; package vegan; Oksanen et al., 2007) using 999 permutations to test whether personality profiles differed according to breed. We then performed discriminant analysis using a non-parametric version of Pillai's test to evaluate the significance of the eigenvalues (package ade4; Dray & Dufour, 2007). To ensure to have enough statistical power, we removed five breeds with <60 individuals (Chartreux, n = 28; Savanah, n = 20; Sphinx, n = 57, Siamese, n = 49, Turkish Angora, n = 21), leading to a dataset of 2162 responses. We regrouped the "Non-pedigree" and "European" cats under the "Nonpedigree" label, as both terms are used to describe the same type of cat in France (the European Short Hair breed exists but is extremely rare in France).

| Factors influencing owner-reported frequency of prey brought home
To run the subsequent analyses regarding predation, additional responses were excluded from the previously described dataset: cats living in apartments with minimal outdoor access as well as cats living in houses but without daily outdoor access (n = 1217), owners of four or more cats (Cordonnier et al., 2022) who would supposedly have difficulty determining which cat brought home which prey (n = 188), incomplete responses (n = 2), and cats belonging to the Bengal breed (n = 36) because when the survey was posted on a Bengal cat Facebook group, several people suggested in the comments that participants give false answers to questions relating to predation. The final dataset included 719 responses. Since the response variables for reported predation frequencies were ordered (0: never, 1: 1-5 times a year, 2: 5-10 times a year, 3: 1-3 times a month; 4: once a week or more), two cumulative logit models (CLMs) were adjusted (McCullagh, 1980) (Christensen, 2015). For both models, we used a stepwise selection by sequential replacement to identify the subset of variables in the dataset resulting in the best performing model with the lowest prediction error (Hegyi & Laczi, 2015;Venables & Ripley, 2013). Wald tests were performed on the predictor variables. The quality of the model estimates was monitored using Pearson residuals (package sure ;Greenwell et al., 2018). For the qualitative variables, post hoc tests (including a Holm correction) were performed using a self-designed contrast matrix (package lsmeans; Lenth & Hervé, 2015).

| Factor analysis of personality structure
We performed exploratory factor analysis on the 15 cat personality items selected from the list of Litchfield et al. (2017). We obtained four factors which explained 30.9%, 28.6%, 23.8%, and 16.7% of the variance, respectively (Table 1a). The value of the correlations between them was relatively small, ranging from −0.01 to 0.30 (Table 1b). Table 1a and Figure 1 show the loadings of these four extracted factors for the 15 cat personality items. As he four personality dimensions were very similar to those extracted by Litchfield et al. (2017), we kept the same names: extraversion, dominance, neuroticism, and agreeableness. However, we did not find their fifth factor, impulsiveness, which was expected to be associated with the adjectives impulsive, predictable, and distractible.
In our dataset, the impulsive adjective was strongly loaded on the Dominance factor, whereas predictable and distractible were moderately loaded on the Agreeableness factor (Table 1a).

| Breed and personality
We confirmed that personality is influenced by breed (permanova;  Figure S1).

| Personality structure and breed differences
We Even when we tried performing exploratory factor analysis with five factors, the additional factor did not correspond to impulsiveness (Table S2). The impulsiveness factor was expected to emerge from the adjectives impulsive, predictable (negative loading), and distractible.
However, in our dataset, impulsive was strongly loaded on the dominance factor, whereas predictable and distractible were moderately loaded on the agreeableness factor (Table 1a). Litchfield et al. (2017) analyzed survey data from New Zealand and Australian owners. When the two data sets were examined separately in the initial analysis, the scree plot of both datasets supported retaining only four factors as in the case of our dataset. Furthermore, in this initial separate analysis of the two data sets, the impulsive adjective was strongly and positively loaded on the impulsivity factor in the Australian data set but negatively in the New Zealand data set. It is therefore possible that cat impulsivity is perceived differently in different countries.  Figure S1). These breeds were previously shown to be closely related genetically (Lipinski et al., 2008) and to have low levels of activity and aggression (Salonen et al., 2019).

| Factors influencing owner-reported frequency of prey brought home
It was previously shown that domestic cats have highly variable predation rates: some cats frequently bring prey home, while a significant proportion rarely does so (Baker et al., 2008;Kauhala et al., 2015;Thomas et al., 2012;Tschanz et al., 2011). Given the high local ecological impact of pet cat predation, understanding the causes of this variation could potentially help identify ways of mitigating this impact. Variations in hunting behavior among pet cats are related to three main factors: (1) the availability of prey in the environment (e.g., Barratt, 1997;Bonnaud et al., 2009); (2) the practices of owners, who can influence the cats' access to prey by regulating their outdoor access and using deterrents and can affect the cats' motivation to hunt by providing a suitable diet or enriching the environment (Cecchetti et al., 2021b); and (3) the intrinsic characteristics of the cats themselves, which modulate their reactions to the previous factors. In this study, we focused on the effect of cat characteristics (personality traits in addition to sex, age, and breed) and included several factors related to the cats' environment (see 'Section 2'), which were expected to play an important role.
Regarding the relationship between the individual characteristics and the reported predation rate of cats, we observed a significant effect of breed in addition to the four personality traits studied here.
By contrast, age and sex did not seem to play a significant role, as also observed by Cordonnier et al. (2022). Note, however, that we excluded cats younger than 1 year from the analyses, while their sexed and desexed status was not recorded. The main finding of this study is that cat personality has a major influence on the owner-reported frequency of birds and small mammals brought home, which, to our knowledge, has not previously been observed. For both birds and that cats with low levels of neuroticism or high levels of extraversion hunt wild prey more frequently. Additionally, we observed that cats with low levels of agreeableness (here, friendliness to people) and high levels of dominance had higher frequencies of bringing home birds but not small mammals.
The personality of cats can potentially influence their predation activity at several different levels. First, it can modulate the time that cats choose to spend outside. For example, cats with high neuroticism could be more fearful of going outdoors than other cats, or friendly cats with high agreeableness could be more motivated to stay inside with their owners. Lowe and Bradshaw (2001) thus showed that "staying indoors" is an important element of the behavioral styles recognizable in young domestic cats. Second, personality can also influence the time that the owners allow to their cats to spend outdoors (Tan et al., 2021) Marmet et al., 2012;Schirmer et al., 2019;Wauters et al., 2021). Finally, cats with personality traits such as high levels of intelligence and perseverance could be more successful hunters. Our data set does not allow us to disentangle these four possibilities. However, a survey with a larger sample, particularly a larger sample of free-ranging cats, would make it possible to determine whether the observed effect of personality traits on the frequency of prey brought home is primarily mediated by the time spent outdoors or by a greater motivation or hunting efficiency once outdoors.
Regarding the cats' environment, we found that rural or suburban settings as opposed to an urban environment and a high abundance of vegetation around the home were associated with higher frequencies of prey brought home as reported by the owners. As expected, we also found that cats who spent a greater amount of time outdoors had higher reported frequencies of prey brought home (though cats without outdoor access were excluded from this analysis). Because pet cats usually remain close to their home (~100 m radius in average; Kays et al., 2020) and are opportunistic hunters, their predation should reflect the fauna found in immediate proximity to their home (Barratt, 1997;Castañeda et al., 2019Castañeda et al., , 2020. Several studies on free-ranging pet cats found significant differences between rural and urban areas in terms of the amount and composition of prey brought home, probably reflecting differences in local prey availability induced by differences in land use (Kauhala et al., 2015;Krauze-Gryz et al., 2017;Piontek et al., 2021). In our study, predation analysis was conducted on cats with outdoor access ranging from <1 h per day to free-ranging cats. This has the advantage of being more representative of the pet cat population as a whole because not all pet cats are free ranging. However, because owners living in urban settings are much more likely to limit their cat's time spent outdoors, often due to their fear of road traffic accidents (Foreman-Worsley et al., 2021), this means that the effects of urban and rural environments as well as the time spent outdoors are difficult to separate in our data set.

| Limitations
In this study, we used online convenience sampling to survey cat owners about their animals' personality traits as well as the frequency of prey brought home. This methodology allowed us to gather a large sample, although it also has several limitations. First, we contacted respondents through social media by disseminating the questionnaire in user groups dedicated to cats. However, the sociodemographic characteristics of these social media users probably differ from those of the general population, for example, in terms of age and education level (Mellon & Prosser, 2017). Furthermore, it is likely that the participants in the cat-dedicated groups present differences in terms of their relationship to their cat (high interest in particular) compared with cat owners who do not frequent such groups. It is therefore likely that the respondents do not constitute a representative sample of French cat owners. In addition, we estimated cat predatory activity using a semi-quantitative measure of how often they bring prey home, as observed by their owners.
Although cat predation rates are frequently estimated by the prey brought home method (e.g., Krauze-Gryz et al., 2017;Lepczyk et al., 2004;Tschanz et al., 2011;Woods et al., 2003) However, in this study, we were interested in determining which personality factors contributed to the variations in predation rates between cats as opposed to the absolute amount of prey captured by the animals. These limitations are therefore not supposed to impact the results of the present research.

| CON CLUS ION
The major influence of cat personality on the frequency of birds and small mammals brought home could potentially help mitigate predation by domestic cats. Pet cat predation rates are strongly associated with the amount of time spent outdoors, although other factors are also important (Cecchetti, Crowley, Goodwin, & McDonald, 2021; (Crowley et al., 2020b) also recently observed that the majority of surveyed owners "valued outdoor access for cats and opposed confinement to prevent hunting." Taking into account the personality of the cats having an outdoor access, for instance by promoting the adoption of cats (or breeds) that are by temperament less likely to hunt (cats with low extraversion and dominance, but high neuroticism and high agreeableness), could therefore potentially allow owners to reduce the impact of their cats on wildlife in places where there are strong biodiversity preservation issues.

O PEN R E S E A RCH BA D G E S
This article has earned an Open Data badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://data.mendeley.com/ datasets/ht5p5pg7b7/1.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are openly avail-