The author of the blog post criticizing Loss et al. (2013) on the Vox Felina website (Wolf 2013, Online Resource 2) is widely viewed in the feral cat advocacy community as an expert on the science of cat impacts and management (BFAS 2013). His writings generally criticize any scientific publication that shows adverse impacts from feral cats or questions the effectiveness of TNR as a management approach, starting with Longcore et al. (2009) and continuing to the present. Wolf, in many recent posts and presentations (e.g., Wolf 2017), has focused extensively on criticizing Loss et al. (2013) without acknowledging any information that would undermine his critiques. In addition, Wolf’s presentations at scientific conferences have included little new material beyond the original blog post. Wolf and other advocates for TNR-only policies have frequently repeated his claims in policy discussions as if they had undisputed merit (CODC 2015). We here respond to these criticisms because they have contributed substantially to shaping the public and policy discourse regarding cat impacts and management.

Criticism: cat predation estimates are unrealistic given the total number of U.S. birds

Wolf has repeatedly claimed that Loss et al.’s (2013) annual estimates of cat predation on birds (1.4–4.0 billion) are not credible because the total estimated breeding population of North American (U.S. and Canada) land birds is 4.9 billion. He credits this estimate to Arnold and Zink (2011), but it was originally generated in Blancher et al. (2007) with data from the North American Breeding Bird Survey (NABBS). As noted in Blancher et al. (2007), 4.9 billion is “likely a conservative total, however, as densities from Breeding Bird Censuses suggest the total could be 2–3 times higher in some regions” (Rosenberg and Blancher 2005). Moreover, these population estimates only include adult birds at the onset of the breeding season, not young-of-the-year birds that hatch after surveys are conducted. An unknown but undoubtedly enormous number of these hatch-year birds do not survive to be counted in the following survey period, and many of these nestlings and fledglings are depredated by cats (Balogh et al. 2011; Stracey 2011). Furthermore, the Blancher et al. (2007) land bird estimates exclude other taxa (waterfowl, shorebirds, waterbirds, and secretive marshbirds), the adults of which—and certainly their nestlings and fledglings—would perhaps triple or quadruple an estimate of the total number of birds available. Other sources suggest roughly 10 billion birds are present in the contiguous U.S. in the pre-breeding season and 20 billion are present in the fall season (USFWS 2002), and even these estimates ignore hatch-year birds that perish during summer, the period when cat predation generally peaks. The Loss et al. (2013) predation estimates are thus reasonable given that the cumulative number of U.S. birds alive and susceptible to predation over an entire calendar year is far greater than 4.9 billion.

Criticism: cat predation does not necessarily lead to population-level impacts

Wolf claims that Loss et al. (2013) fails to acknowledge that predation does not always cause population-level impacts; he further claims such impacts are unlikely because cats tend to prey on “the young, the old, the weak, or unhealthy” that would have died anyway (Wolf 2013). Notably, Loss et al. (2013) never had the objective of assessing population impacts, yet they did state that such impacts are likely for some species in some mainland locations, a conclusion that has since been supported by multiple studies from around the world (Loss and Marra 2017). Because some of these studies existed in 2013 (Crooks and Soulé 1999; van Heezik et al. 2010; Balogh et al. 2011), Wolf’s criticism ignored evidence suggesting such impacts were likely.

Wolf’s evidence in support of cats preying mainly on weak and unhealthy individuals is also unsupported by scientific evidence. Neither of the studies he cited that assessed bird body condition (Møller and Erritzøe 2000; Baker et al. 2008) provides evidence that the birds killed would have lower fitness or survival, and one of the studies explicitly warns against such a conclusion (Baker et al. 2008). Further, a crude assessment of body condition to determine if birds would have died without cat predation overlooks the substantial challenges and complexity of determining whether mortality is additive or compensatory at the population level (Loss and Marra 2017). Finally, a population-level focus reflects a philosophy that ignores the individual welfare and suffering of the animals that cats injure and kill. This philosophy is in contradiction to the narrative used to justify no-kill policies, which focuses on concerns about individual cat welfare (Longcore et al. 2009).

Criticism: cat predation estimates have broad uncertainty

Wolf also criticizes the broad uncertainty around the Loss et al. (2013) predation estimates, citing an earlier paper by the same authors (Loss et al. 2012) highlighting limitations of wildlife mortality estimates that are extrapolated from a limited sample of data and do not account for uncertainty. Thus, Wolf attempts to discredit Loss et al. (2013) by claiming their methods do not follow their own recommendations. However, Wolf quotes Loss et al. (2012) out of context; that paper referred to limitations of extrapolating from one or a few small-scale studies without accounting for estimate uncertainty. As described above, Loss et al. (2013) synthesized data from multiple studies and defined data-derived probability distributions for all model parameters, allowing for explicit and transparent accounting for estimate uncertainty. Loss et al. (2013) also conducted a sensitivity analysis to quantify the amount of estimate uncertainty contributed by each parameter. The wide uncertainty around estimates therefore represented the state of the science on cat predation, and the sensitivity analysis highlighted opportunities to refine estimates with further research. Notably, even the lowest bounds of the estimates still amount to an exceptionally high number of birds and mammals killed by cats.

Criticism: the estimate of predation by unowned cats is inflated

Wolf has claimed that the Loss et al. (2013) estimates of predation by unowned cats are inflated for several reasons. For the number of unowned cats (range 30–80 million), Wolf states that no empirically derived estimates existed to inform the distribution range, a limitation Loss et al. (2013) in fact acknowledged. The authors did cite several sources providing non-empirical estimates, and the most commonly cited figure of 60–100 million cats is actually higher than the numbers used by Loss et al. (2013). If one assumes the actual numbers of unowned cats lie at the lower end of the distribution range (30 million cats), then the lower ends of the Loss et al. (2013) predation estimates reflect this possibility. As illustrated by the Loss et al. (2013) sensitivity analysis, this parameter contributed the greatest uncertainty to predation estimates. Wolf might have highlighted the need for research to improve the estimates, but he has provided no evidence that the numbers are lower than those cited by nearly every authority, including the Humane Society of the United States (30–40 million; HSUS 2018).

Wolf also claimed that Loss et al. (2013) was unjustified in assuming 80–100% of unowned cats kill wildlife because the studies cited are only on rural cats, and some urban studies have resulted in few direct observations of predation. Wolf further claimed that many urban cats reduce their hunting frequency because they are fed by humans. Regarding the former claim, the urban studies Wolf cites had no objective of estimating predation (Calhoon and Haspel 1989; Castillo and Clarke 2003), and the anecdotal nature of their observations does not allow conclusions about the proportion of cats that hunt or the frequency of predation events. The latter claim also has limited support in the peer-reviewed literature; indeed, studies show that cats hunt and kill regardless of whether they are fed by humans [Liberg 1984; Barratt 1998; but see Silva-Rodríguez and Sieving (2011)]. Based on the Loss et al. (2013) summary of rural studies, the lowest documented hunting proportion was 90%, yet they included a potential for an 80–100% hunting rate, an approach that was actually more conservative than the literature.

The Vox Felina blog post also criticized the annual predation rates of unowned cats. Wolf claimed that some of the earlier studies Loss et al. (2013) used, particularly those from the 1930s–1950s, overestimate predation because their data collection method (shooting cats along roads and assessing stomach contents) only samples cats that are hunting. This criticism is irrelevant because the predation rate parameters Loss et al. (2013) derived were only meant to reflect hunting cats, and as described above, the study derived a separate parameter to account for cats that do not hunt. Further, although stomach contents analyses do not provide an exact representation of numbers of prey killed, Loss et al. (2013) implemented a transparent and conservative approach to interpreting these data (see methods summary above). Wolf also claims predation estimates are inflated because Loss et al. (2013) used a uniform distribution rather than a skewed distribution. This criticism reflects a fundamental misunderstanding of the methods. Variation in predation among individual cats does tend to be skewed, but the uniform distributions Loss et al. (2013) derived were based on study averages across multiple cats. There is no evidence that among-study variation in average cat predation follows a skewed distribution. Finally, a more recent study using substantially more predation data reported higher rates of predation on birds by individual unowned cats in Australia (Woinarski et al. 2017), suggesting the range used for this parameter by Loss et al. (2013) was likely conservative.

Criticism: the estimate of predation by owned cats is inflated

Wolf also claimed that the estimates of predation by owned cats are inflated for several reasons. For the proportion of pet cats outdoors (range 0.4–0.7), Wolf suggested that two sources Loss et al. (2013) used to generate the distribution range (Marketing and Research Services, Inc. (MRS) 1997; American Bird Conservancy (ABC) 2012) actually referred to the same survey. Although it does appear that the ABC estimate originated from the earlier MRS survey, counting a study twice would have no effect on the parameter values drawn or the resultant predation estimates; Loss et al. (2013) assumed a uniform distribution, and counting a study twice would not change the distribution bounds. Wolf further claimed that Loss et al. (2013) did not distinguish between cats that are outdoors at all times and those that spend at least some time indoors, and that predation estimates are therefore inflated because indoor-outdoor cats probably kill fewer animals than cats that are outdoors at all times. Loss et al. (2013) derived the range of 40–70% of pet cats outdoors from published surveys for which data were unavailable to parse apart the number of hours each cat was allowed outdoors. This criticism therefore relates primarily to the level of detail in the original studies, not to the methods in Loss et al. (2013). Additionally, since studies from which Loss et al. (2013) extracted data included multiple cats that spent varying amounts of time outdoors, they indirectly captured variation in time spent outdoors in the prey return distributions. Finally, even if prey return parameters were overestimated, there would be little overall effect on predation estimates because pet cat predation rates are far lower than those for unowned cats.

Wolf has also claimed in scientific conference presentations (Wolf 2017) that Loss et al. (2013) used inflated values for the proportion of outdoor cats that hunt (range 0.5–0.8). A study published after Loss et al. (2013) offers further insight on this proportion. Loyd et al. (2013) used cat-borne videos to determine that 44% of owned cats hunted during an average monitoring period of 38 h. With a longer monitoring period, this rate would certainly meet and likely exceed the values used by Loss et al. (2013). For prey return rates, Wolf states in the blog post that estimates are biased for the same reasons he claims bias in unowned cat predation rates; however, as described above, this criticism about the skewed nature of predation reflects a misunderstanding of the way Loss et al. (2013) defined distributions for the predation rates.

Wolf also claims that Loss et al. (2013) misapplied the correction factor for prey items not returned to owners from Kays and DeWan (2004) because this value (3.3) was based only on observations of cat hunting success for mammals in summer. Loss et al. (2013) applied this correction factor for all prey taxa and seasons because there is no evidence that the proportion of prey items returned to owners varies taxonomically or seasonally. A more recent study indicates that the Loss et al. (2013) estimate for this correction factor may actually be conservative. Cat-borne videos showed that only 23% of prey items were returned to owners, suggesting a correction factor of 4.3 (Loyd et al. 2013), a value that if used would have increased predation estimates. Wolf was correct in pointing out that Loss et al. (2013) misinterpreted George (1974) when interpreting a correction factor of 2 based on George (1974) stating that 50% of predation events were observed. This percentage actually referred to an observation bias associated with the author’s survey methods, not the prey return behavior of cats. This misinterpretation has frequently been made in the literature (Fitzgerald and Turner 2000), but in the context of Loss et al. (2013), it has no effect on the correction factor distribution or the predation estimates because it is between the other two values used to inform the bounds of the uniform distribution.