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ATTACHMENTS TO THE 10-YEAR PLAN LETTER [B] Reason replaces emotion Wisconsin's original CWD plan was created in an emotional atmosphere of uncertainty-driven fear. The chaos and panic that ensued encouraged a rush into a poorly thought out public policy. The result was a preemptive policy based on a worst-case scenario. By trying to act assertive in order to not look weak, the DNR lost credibility with key stakeholders, and the effort soon went south. Its overreaching strategy (herd eradication) and stumbling from one unpopular tactic to another (summer shoots, seasons extending seven months, bounties, sharpshooting) in apparent confusion resulted in a massive waste of resources and squandering of good will. To make matters worse, policy justification was often stated in terms of serving issues, interests and agendas (commercial forestry, TB, agriculture, ecology, deer-vehicle accidents, baiting and feeding, and forced herd reduction) having nothing directly to do with CWD as a wildlife disease. Things are very different today. We now know the worst-case scenario was sold in overly dramatic terms. Anxiety has faded. This time around everyone can be more rational. Policy should focus like a laser on CWD and not carry the burden of other agendas. The DNR has a chance for a do-over in an atmosphere of calm. But there also is a much heightened wariness and skepticism on the part of the public. People are in no mood to accept measures that are not compelling this time around. There is likely to be serious blowback if they feel their license fees and tax dollars are being used to perpetuate a needlessly destructive future policy that ignores the reality on the ground. The backlash could have grave consequences for Wisconsin deer management. [C] Hard data bias The DNR relies heavily on population and environmental measures. Their databases include such things as the estimated acres of deer range, the estimated size of the deer herd, DMU herd targets, the number of deer seen in aerial surveys, the number of deer killed, the number of CWD cases found, and disease prevalence. These hard data are then used as input to computer models and, eventually, to craft deer management policy. The result too often is faulty policy rationalization because the data are often not as concrete or absolute as their quantitative nature suggests. One problem is that each of these hard numbers has a back story based on the definition of what is being counted or measured. A different definition yields different data. For instance, the herd estimate is based on a debatable sex-age-kill formula. DMU herd goals are made up by weighing biological potential factors and human tolerance for deer. Winter aerial surveys are based on a best-guess "sightability" multiplier, and relate deer seen by land section to summer (not winter) range estimates. Deer range is a composite measure of summer habitat quantity, while winter habitat quality and quantity (neither yet determined by the DNR) are the biological keys to deer survival. CWD cases are reported by section of kill, although the infected deer may be a transient that lived most of its life at some distant location. Disease prevalence is the proportion of positive animals in a population, although fawns (representing nearly half of the herd) are no longer tested as they once were. To complicate matters further, data access and collection rules have changed over time, often making year-to-year comparisons guesswork. So what do the hard numbers actually mean? Very little, unless properly qualified and, unfortunately, these qualifications are difficult to incorporate into quantitative analysis. When reported without qualification they become ready tools of distortion to serve a particular end. A second problem is that the reliance on counts and simple measurements can easily miss the more important intangibles that matter most when dealing with issues as complex as CWD. Take agency sharpshooting as an example. The DNR defends the unpopular practice by saying it is effective in getting more deer killed. They cite the kill numbers as if such bean counting was the end of the matter. What they miss is the big picture. How many deer were not killed because landowners and hunters were trying to offset the uncertain sharpshooting kill? Of course, this "deer-saved" number is an intangible (soft data), and cannot be easily determined. The extended winter season is a similar example. The DNR is quick to say it got "X" deer killed in "Y" year. Of course, they do not report how many deer landowners and hunters did not kill (soft data) in an attempt to compensate. Another intangible. A third problem is that the DNR depends on survey data. Manipulative social science is, in our opinion, one of the most offensive aspects used to support this plan. The agency is quick to report that "X" percent of those who returned a survey endorsed option "Y" posed in the survey. What they often fail to report is the non-representative nature of the sample population. But more seriously, they are often reporting results from open-ended and leading questions. As an example, the DNR has defended past policy by saying the people of Wisconsin have clearly said they wanted the DNR to "eradicate CWD from the state, or to stop CWD in the south." The survey questions always suggested that CWD eradication was possible, although it had never been achieved elsewhere. The questions were not qualified with such phrases as "at what cost" or "at all costs." Thus, they did not specify under what extreme conditions and expense these actions would need to take place. Nor did any of the multiple surveys ask the essential question: If CWD is found near where you live or hunt, do you want current CWD rules applied for miles around for decades to come? Clearly, it would be misleading to accept these data at face value. |