LAUSR

Manywildlife populations worldwide are experiencing unprecedented population declines and local extinction due to threats, such as habitat loss and fragmentation, invasive species, pollution, overexploitation, and climate change (Ceballos & Ehrlich 2002; Newbold et al. 2016; Pawluk et al. 2019). To prevent further loss of biodiversity and imminent demise of imperiled species, many countries have enacted legislation, including the Endangered Species Act (ESA) and the Marine Mammal Protection Act (MMPA) in the United States and the Species at Risk Act in Canada. Listing and delisting criteria and recovery planning process under some of these legislations have been criticized for lacking consistency, transparency, objectivity, and scientific justification (Boor 2014; Doak et al. 2015; Neel et al. 2012; Zeigler et al. 2013). To address these concerns, it has been suggested that listing, downlisting, or delisting (hereafter, listing) and recovery planning processes be guided by the results of population viability analyses (PVAs) when data to support such analyses are available (Boor 2014; Doak et al. 2015; Lindenmayer et al. 1993; Lindenmayer et al. 2012; Morris & Doak 2002). Consistent with these recommendations, the use of PVA results in listing and recovery planning has been increasing in recent years. Some examples include the use of PVA results for listing and recovery planning of the West Indian manatee (Trichechus manatus) (https://www.fws.gov/northflorida/manatee/2017% 20Reclass/WIM_Reclass_FR_2017-06657.pdf), the Florida panther (Puma concolor coryi) (https://www.fws.gov/policy/ library/2008/E8-29890.html), the Louisiana black bear (Ursus americanus luteous) (Davidson et al. 2015), and the red wolf (Canis rufus) (https://www.govinfo.gov/content/pkg/FR-2018-0628/pdf/2018-13906.pdf) under the ESA. Although the increased use of PVA in conservation planning processes is encouraging, it has become increasingly clear that many studies are poorly executed, not reproducible, or replicable, lack essential PVA components and that there exists substantial inconsistency across studies in terms of how PVA models are formulated or implemented and how the results are interpreted (Pe’er et al. 2013). These results suggest that not all PVAs are created equal and that an objective framework for assessing PVA quality is necessary to ensure that low-quality PVAs are avoided in conservation-planning and decision-making processes. Hence, we proposed an objective framework composed of 32 questions about essential PVA components based on existing guidelines for assessing PVA quality (Chaudhary & Oli 2020). Commenting on our paper, Lawson et al. (2021) argue that the definition of quality for decisionsupport PVAs should be different from those developed for heuristic purposes. Although we agree with them that decision support is one of many important applications of PVAs, we suggest that their proposal is based on a false dichotomy.