Several researchers recently took an extended look at Wisconsin’s 2022 ‘scaled occupancy model’ for estimating wolf counts in the state and concluded that the Wisconsin method systematically overestimates wolf abundance by large margins. This is due to several factors, and perhaps the most concerning part of all is that these over-estimations likely extend to other states using similar counting methods.

New Counting Methods

Despite there already being several proven methods developed by Wolf scientists over the course of many years, Wisconsin and other states have chosen to attempt to cut costs and create a lot more gray area and margin for era for their counts. As Adrian Treves and Francisco J. Santiago-Avila put it in their recent paper titled Estimating wolf abundance with unverified methods, “The new methods sacrifice precision but are believed to retain adequate accuracy and sensitivity to changing conditions for reliable decision-making…We conclude that the Wisconsin method would systematically overestimate wolf abundance by large (but currently incalculable) margins. Because Wisconsin, similar to other states, not only changed to unverified methods but also implemented widespread wolf killing, shortcomings in their estimates of wolf abundance may have far-reaching consequences for population viability and confidence in state wildlife policy.”

The new counting method combines estimates of pack size, ranging pack area, and occupied range. This method is used in Wisconsin, and similarly, counts have been used in Montana and Idaho. Perhaps unsurprisingly, each of these states has also expanded the allowance of wolf hunting and killing over the last several years, and these estimates don’t always do a great job of factoring in all those wolves lost.

Flawed Metrics

The changes to Wolf counting in Wisconsin and similar states are dependent on Wolf populations reaching a number that makes it difficult to take a “census” approach, and instead, take a new approach, called the ‘scaled occupancy model’ (SOM), which attempts to estimate the total number based on several factors. The SOM has three components, each estimated with separate models: an estimate of the area occupied by wolves, an estimate of territory size, and an estimate of pack size.

The problem is that Treves and Santiago-Avila determined that all three components carry levels of uncertainty, that when compounded together, create a wide margin for error for the total count.

Perhaps one of the most telling metrics that shows this flaw is described by the two researchers in the study: “It is important to note here that the data input to the SOM comes from previous years (two winters of snow track surveys and four years of pack-occupied range estimates).” So the data used in the SOM has a range of up to four years, meaning if a wolf pack was seen within the last four years, they got counted in the estimate. In case there was confusion of what that four-year range meant to counters, the Wisconsin Department of Natural Resources included an Addendum that clarified the pack just had to be observed at least one of the previous four years. The biggest flaw in that logic is that a pack could’ve been seen prior to the aggressive wolf hunts and other wolf killings that happened in 2021.

The killings were so brutal, hunters killed 218 wolves in just four days, blowing past their 119-animal quota, and knocking out as much as 30% of the state’s wolf population, and that’s just what was officially reported. That means any one of those wolves could’ve been counted in previous years, and would still count in the most recent count, despite clearly being wiped out since then. As the study puts it, “The SOM was developed and compared to the traditional method entirely under conditions without hunting or killing of suspected predators of domesticated ungulates (Stauffer et al. 2021), raising questions about its sensitivity to population changes caused by legal killing.”

Conclusions

This study brings up some very valid questions about the counting methods employed by Wisconsin and other states using similar methods. We never advocate that wolves should be killed or culled through hunting or other methods, but even if you do think that wolves in these regions are at a sustainable enough number to be periodically hunted, this study calls into question whether we can trust the data being provided by these states about the overall population, and how it might have shifted since legal wolf killing was sanctioned. It’s best that the concerns about the new Wisconsin ‘SOM’ method are brought about now, as a means of informing public policy debate about how best to count and manage these wolf populations in Wisconsin and in Wolf management states across the US.