We searched JSTOR, Google Scholar, and the Web of Science database (formerly ISI Web of Science) within the Web of Knowledge search engine published by Thomson Reuters to identify studies that document cat predation on birds and mammals. We initially focused this search on US studies, but due to a limited sample of these studies, we expanded the search to include predation research from other temperate regions. We also searched for studies providing estimates of cat population sizes at the scale of the contiguous United States and for US studies that estimate the proportion of owned cats with outdoor access and the proportion of cats that hunt wildlife. The search terms we used included: ‘domestic cat’ in combination with ‘predation,’ ‘prey,’ ‘diet,’ ‘food item’ and ‘mortality’; all previous terms with ‘domestic cat’ replaced by ‘Felis catus,’ ‘feral,’ ‘stray,’ ‘farm,’ ‘free-ranging,’ and ‘pet’; ‘trap-neuter-return colony’; ‘TNR colony’; and ‘cat predation’ in combination with ‘wildlife,’ ‘bird,’ ‘mammal,’ and ‘rodent’. We checked reference lists of articles to identify additional relevant studies. Lead authors of three studies were also contacted to enquire whether they knew of ongoing or completed unpublished studies of cat predation in the United States.
Classification of cat ranging behaviour
We grouped studies based on the ranging behaviour of cats investigated. We defined owned cats to include owned cats in both rural and urban areas that spend at least some time indoors and are also granted outdoor access. We defined un-owned cats to include all un-owned cats that spend all of their time outdoors. The un-owned cat group includes semi-feral cats that are sometimes considered pets (for example, farm/barn cats and strays that are fed by humans but not granted access to habitations), cats in subsidized (including TNR) colonies, and cats that are completely feral (that is, completely independent and rarely interacting with humans). We did not classify cats by landscape type or whether they receive food from humans because the amount of time cats spend outdoors is a major determinant of predation rates33,34 and because predation is independent of whether cats are fed by humans6,34,35.
Study inclusion criteria
Studies were only included if: (1) they clearly reported cat ranging behaviour (that is, a description of whether cats were owned or un-owned and whether they were outdoor cats or indoor-outdoor cats), and (2) the group of cats investigated fit exclusively into one of the two groups we defined above (that is, we excluded studies that lumped owned and un-owned cats in a single predation rate estimate). For some studies, we extracted a portion of data that met these criteria but excluded other data from cats with unknown ranging behaviour. We only included mainland and large island (New Zealand and United Kingdom) predation studies, because cat predation on small islands is often exceptionally high36,37 and focused on colony nesting seabirds38. We excluded studies from outside temperate regions and those with predation rate estimates based on fewer than 10 cats, <1 month of sampling, or on cats that were experimentally manipulated (for example, by fitting them with bells or behaviour altering bibs). We included studies that used cat owners’ records of prey returns, but we excluded those that asked owners to estimate past prey returns because such questionnaires may lead to bias in estimation of predation rates39. (For a list of all included and excluded studies, see Supplementary Table S1).
Data extraction and standardization of predation rates
Most studies report an estimate of cat predation rate (that is, daily, monthly or annual prey killed per cat) or present data that allowed us to calculate this rate. When studies only reported predation rate estimates for all wildlife combined, we calculated separate predation rates by extracting taxa-specific prey counts from tables or figures and multiplying the total predation rate by the proportion of prey items in each taxon. If taxa-specific counts were not provided, we directly contacted authors to obtain this information. For studies that presented low, medium and high estimates or low and high estimates, we used the medium and average values, respectively. For studies that presented more than one predation estimate for cats with similar ranging behaviour (for example, owned cats in rural and urban areas), we calculated the average predation rate.
Nearly all studies of un-owned cats report numbers or frequencies of occurrence of different taxa in stomachs and/or scats. For studies reporting numbers of prey items, we estimated annual predation rates by assuming one stomach or scat sample represented a cat’s average daily prey intake (for example, an average of one prey item per stomach or scat=365 prey per cat per year). This assumption likely resulted in conservative estimates because cats generally digest prey within 12 h (ref.2828) and can produce two or more scats each day29. For studies reporting occurrence frequencies of prey items, we assumed this proportion represented a cat’s average daily prey intake (for example, a 10% bird occurrence rate=0.1 bird per stomach or scat=36.5 birds per cat per year). This assumption results in coarse predation rate estimates, but estimates from this approach are even more conservative than those from the first assumption because many stomachs and scats undoubtedly included more than one bird or mammal.
Predation rate estimates from many studies were based on continuous year-round sampling or multiple sampling occasions covering all seasons. However, seasonal coverage of some studies was incomplete. To generate full-year predation rate estimates in these cases, we adjusted partial-year predation estimates according to the average proportion of prey taken in each month as determined from year-round studies reporting monthly data (birds and mammals8,33, birds only7,40). For partial-year estimates from the northern hemisphere, we offset monthly estimates from southern hemisphere studies by 6 months. The final annual predation rate estimates for all studies are presented in Supplementary Table S1. The year-round studies we used represent different geographical regions (for birds—England, Kansas (US), Australia and New Zealand; for mammals—England and Australia) with varying climates and slightly varying seasonal patterns of predation. For both birds and mammals, averaging across full-year studies resulted in higher proportions of predation in the spring and summer compared with fall and winter, an expected pattern for much of the United States. The reference studies we used, therefore, provide a reasonable baseline for correcting to full-year mortality estimates. This approach greatly improves upon the assumption that mortality is negligible during the period of the year not covered by sampling.
Quantification of annual mortality from cat predation
We estimated wildlife mortality in the contiguous United States by multiplying data-derived probability distributions of predation rates by distributions of estimated cat abundance, following41. Quantification was conducted separately for owned and un-owned cats and for birds and mammals. As there was a relatively small sample of US studies that estimated predation rates (n=14 and 10 for birds and mammals, respectively), we repeated calculations using predation rate distributions that were augmented with predation rates from Europe and all temperate zones. However, we only used studies from the contiguous United States to construct all other probability distributions (listed below).
We estimated mortality using the following model of cat predation:
where npc is the number of owned cats in the contiguous United States, pod is the proportion of owned cats granted outdoor access, pph is the proportion of outdoor owned cats that hunt wildlife, ppr is the annual predation rate by owned cats, cor is a correction factor to account for owned cats not returning all prey to owners, nfc is the number of un-owned cats in the contiguous United States, pfh is the proportion of un-owned cats that hunt wildlife, and fpr is the annual predation rate by un-owned cats. From the probability distribution of each parameter (see Table 1 and Supplementary Methods for details about the specific probability distributions used), we randomly drew one value and used the above formulas to calculate mortality. Random draws were made using distribution functions in Programme R (rnorm and runif commands for normal and uniform distributions, respectively). We conducted 10,000 random draws to estimate a potential range of annual predation on each wildlife taxa. For all analyses, we report median mortality estimates and lower and upper estimates bracketing the central 95% of values.
We used multiple linear regression analysis to assess how much variance in mortality estimates was explained by the probability distribution for each parameter. We treated total mortality estimates as the dependent variable (n=10,000) and we defined a predictor variable for each parameter that consisted of the 10,000 randomly drawn values. We used adjusted R2 values to interpret the percentage of variance explained by each parameter.
1. Vigne JD, Guilaine J, Debue K, Haye L, Gerard P. Early taming of the cat in Cyprus. Science. 2004;304:259.[PubMed]
2. Dobney K, Larson G. Genetics and animal domestication: new windows on an elusive process. Journal of Zoology. 2006;269:261–271.
3. Gupta AK. Origin of agriculture and domestication of plants and animals linked to early Holocene climate amelioration. Current Science. 2004;87:54–59.
4. Zohary D, Hopf M. Domestication of Plants in the Old World. Oxford University Press; Oxford: 2000.
5. Bradshaw JWS, Horsfield GF, Allen JA, Robinson IH. Feral cats: their role in the population dynamics of Felis catus. Applied Animal Behaviour Science. 1999;65:273–283.
6. Clutton-Brock J. A natural history of domesticated mammals. Cambridge University Press; New York: 1999.
7. Beaumont M, et al. Genetic diversity and introgression in the Scottish wildcat. Mol Ecol. 2001;10:319–36.[PubMed]
8. Pierpaoli M, et al. Genetic distinction of wildcat (Felis silvestris) populations in Europe, and hybridization with domestic cats in Hungary. Mol Ecol. 2003;12:2585–98.[PubMed]
9. Randi E, Pierpaoli M, Beaumont M, Ragni B, Sforzi A. Genetic identification of wild and domestic cats (Felis silvestris) and their hybrids using Bayesian clustering methods. Mol Biol Evol. 2001;18:1679–93.[PubMed]
10. Wiseman R, O'Ryan C, Harley EH. Microsatellite analysis reveals that domestic cat (Felis catus) and southern African wild cat (F. lybica) are genetically distinct. Animal Conservation. 2000;3:221–228.
11. CFA . The Cat Fanciers' Association Cat Encyclopedia. Simon & Schuster; New York: 1993.
12. Wastlhuber J. In: History of domestic cats and cat breeds. Pedersen NC, editor. Feline Husbandry, American Veterinary Publications, Inc.; Goleta, CA, USA: 1991. pp. 1–59.
13. Parker HG, et al. Genetic structure of the purebred domestic dog. Science. 2004;304:1160–4.[PubMed]
14. Driscoll CA, et al. The Near Eastern origin of cat domestication. Science. 2007;317:519–23.[PMC free article][PubMed]
15. Menotti-Raymond M, et al. A genetic linkage map of microsatellites in the domestic cat (Felis catus) Genomics. 1999;57:9–23.[PubMed]
16. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155:945–59.[PMC free article][PubMed]
17. Cavalli-Sforza LL, Edwards AW. Phylogenetic analysis. Models and estimation procedures. Am J Hum Genet. 1967;19(Suppl 19):233+.[PMC free article][PubMed]
18. Nei M, Feldman MW. Identity of genes by descent within and between populations under mutation and migration pressures. Theor Popul Biol. 1972;3:460–5.[PubMed]
19. Excoffier L, Smouse PE, Quattro JM. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics. 1992;131:479–91.[PMC free article][PubMed]
20. Piry S, et al. GENECLASS2: a software for genetic assignment and first-generation migrant detection. J Hered. 2004;95:536–9.[PubMed]
21. Malek J. The cat in Ancient Egypt. University of Pennsylvania; Philadelphia: 1993.
22. Rosenberg NA, et al. Genetic structure of human populations. Science. 2002;298:2381–5.[PubMed]
23. Morris D. Cat breeds of the world. Penguin Books; New York: 1999.
24. Morris D. Cat Breeds of the World: A Complete Illustrated Encyclopedia. Viking Penquin; New York: 1999.
25. Sambrook J, Russel DW. Preparation and analysis of eukaryotic genomic DNA, Molecular Cloning: A Laboratory Manual. Cold Spring Harbor Laboratory Press; New York: 2001.
26. Leutenegger CM, et al. Viral infections in free-living populations of the European wildcat. J Wildl Dis. 1999;35:678–86.[PubMed]
27. Menotti-Raymond M, et al. Second-generation integrated genetic linkage/radiation hybrid maps of the domestic cat (Felis catus) J Hered. 2003;94:95–106.[PubMed]
28. Toonen RJ, Hughes S. Increased throughput for fragment analysis on an ABI PRISM 377 automated sequencer using a membrane comb and STRand software. Biotechniques. 2001;31:1320–4.[PubMed]
29. Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F. GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Laboratoire Génome, Populations, Interactions, Université de Montpellier II; Montpellier (France): 2004.
30. Rannala B, Mountain JL. Detecting immigration by using multilocus genotypes. Proc Natl Acad Sci U S A. 1997;94:9197–201.[PMC free article][PubMed]
31. Felsenstein J. PHYLIP - Phylogeny Inference Package (Version 3.2) Cladistics. 1989;5:164–166.
32. Page RD. TreeView: an application to display phylogenetic trees on personal computers. Comput Appl Biosci. 1996;12:357–8.[PubMed]
33. Schneider S, Roessli D, Excoffier L. Arlequin: A software for population genetics data analysis. Genetics and Biometry Lab, Dept. of Anthropology, University of Geneva; 2000.
34. Peakall R, Smouse PE. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes. 2006;6:288–295.[PMC free article][PubMed]
35. Goudet J. Fstat version 1.2: a computer program to calculate Fstatistics. Journal of Heredity. 1995;86:485–486.