REVIEWS OF RECENT SCANDINAVIAN WOLF PVAS (LISTED CHRONOLOGICALLY) We are very impressed by the quality and sincerity of efforts by scientists to apply the

very best ecological and genetic knowledge to the question of concrete management guidelines for Scandinavian wolves. The literature on this topic is both broad and deep.

In the interest of brevity, we will focus on the four key viability analyses conducted since 2011. The purpose of these four efforts was to consolidate, critique, and update the previous PVA-related efforts prior to 2011 (eg Nilsson 2004, Liberg 2006, Bull et al. 2009, Liberg et al. 2009, Forslund 2010).

14 HANSEN et al. 2011: This was a conceptual report, not technically a PVA. In its conclusions, the report places inbreeding and genetic health as the highest priority for managing wolves in Sweden, and implies that these problems are at crisis levels so that actions to drastically

decrease inbreeding should be implemented as soon as possible. Specifically, the report argues for reduction of the inbreeding coefficient to 0.1 over the next 20 years. To achieve these low inbreeding coefficients would require, the authors state very high levels of connectivity of about 5-10 effective immigrants per generation (when the Scandinavian population is 240

individuals), translating to 10-20 actual wolves per generation or 2 to 4 per year. The report also argues for large population sizes for Favorable Conservation Status, consisting of 3,000 to 5,000 individuals in the greater Scandinavia/Finland/Karelia-Kola metapopulation, with a ‘starting point’ recommendation of 700 for the Swedish part of the metapopulation (page 111).

None of these thresholds are unreasonable for small populations faced with imminent extinction due to inbreeding depression. However, nothing in this report (or others we have seen) provide convincing evidence that such extinction due to inbreeding depression is in fact imminent for Scandinavian wolves. Also, as stated above in the conceptual review, no body of evidence provides general support for the stated genetic criteria of inbreeding coefficient

needing to be 0.1 or less, or for the stated population sizes or gene flow requirements. Likewise, because of the complex interactions between population growth rate, nature of genetic load, rate of inbreeding, effects of individual vital rates on population growth, and so on, it is not necessarily the case that “an overall inbreeding coefficient of 0.3 must be considered very high, and should be taken very seriously” (p. 114).

Finally, Hansen et al. 2011 encourages the use of artificial translocation, including from captive wolves. We are much less sanguine about such actions, and would urge careful consideration of the potential negative effects of artificial translocations due to outbreeding depression, disease, breakup of pack structure, and other issues. As will be emphasized below, lower connectivity levels with ‘natural’ movements should be preferred over very high gene flow levels with manually translocated individuals.

CHAPRON et al. (2012): This is what has been called a ‘demographic only’ PVA,

acknowledging that it does not account for genetic factors. Under a very short deadline (1 month), the authors quite heroically developed a time series count-based approach, and two demographically explicit approaches: one simple generalized birth-death model without age structure, and an individual-based model incorporating pack structure. In all cases population growth was considered exponential up to a ceiling, which was considered the putative ‘MVP’.

Because the intrinsic growth rate of wolves as a species is quite high among vertebrates, it is not surprising that Chapron et al. 2012 found a high probability of persistence for even very small populations of 100 or so total individuals, even in the face of occasional severe mortality events (‘catastrophes’ or ‘disasters’). The authors properly emphasized that these results are relevant only with the current estimates of vital rates; that is, the results would not apply if vital rates were substantially reduced in the future by stressors such as human harvest or inbreeding depression.

15 LIBERG AND SAND 2012 This analysis was commissioned as a complement to the purely demographic PVA of Chapron et al. (2012, above). It is noted that the short time frame

prevented this from being a formal PVA, but rather simply an exploration of tradeoffs between gene flow and levels of inbreeding based on studies to date and general concepts. The review is thorough and results are reasonable and in accord with the general concepts discussed above: Moderate levels of gene flow (eg 2—3 wolves per generation, or about 1 wolf every other year) will hold inbreeding coefficient to the vicinity of 0.2, the equilibrial level expected from OMPG. BRUFORD (2015): The purpose of this PVA was to provide an updated and comprehensive examination of the effects of effective immigrants into a hypothetical Swedish wolf population whose size ranges from 170 to > 417. The author uses Vortex with modifications to attempt to improve the modeling of effects of immigrants on genetic variation. The Vortex software has traditionally assumed the supplemented individuals (immigrants) are genetically unique, with no similarity between source and recipient populations. Of course, this is counter to reality, where immigrants from neighboring subpopulaitons would be genetically similar to those in Sweden. Uncorrected, this assumption would be expected to overestimate the genetic benefit of supplementation, because the genetically distinct immigrants will artificially decrease

inbreeding and therefore inbreeding depression. Working with Bob Lacy (developer of Vortex) the author developed two customized approaches, each of which (in different ways) accounted for similarities between extant Swedish wolves and putative immigrants from Finland and Karelia.

The author (and reviewers) openly discusses some limitations, oddities and unexpected outcomes in the modeling results, at the level of both genetic and demographic trajectories. Some of these may have arisen from complex interactions that could not be interpreted or explored in the short time the author had to prepare the PVA. For example, as noted above, both the carrying capacity and the density dependence function (eg ceiling vs logistic vs Allee) can have profound effects on outcomes of PVA projections. The density dependence function used in all models was exponential growth up to a hard ‘ceiling’, where abundance was truncated. This function could give very different results from other density dependent functions that might have been used. Other curious results that may indicate structural problems with the model were raised by reviewers of the report.

Despite the oddities in performance of the simulations, the conclusions from the Bruford report were roughly consistent with expectations from general theory and previous work. When gene flow was absent or low (eg < one effective migrant per generation), heterozygosity was lost and the inbreeding coefficient continued to accumulate, with the potential for

inbreeding depression to add its negative effects to the extinction vortex. However, when gene flow levels were at or above 1 effective migrant / generation, the inbreeding coefficient

remained more or less constant. In the end, this PVA was not able to provide much more specific guidelines than those that could be derived from the general concepts discussed above: an overall metapopulation of effective populations size of 500 with a moderate level of gene flow into the Sweden subpopulation (1 or more effective immigrants per generation), should be sufficient for FRP status.

16 OVERVIEW OF SCIENCE-BASED CRITERIA