Suchergebnisse

Measuring rates and causes of mortalities is important in animal ecology and management. Observing the fates of known individuals is a common method of estimating life history variables, including mortality patterns. It has long been assumed that data lost when known animals disappear were unbiased. We test and reject this assumption under conditions common to most, if not all, studies using marked animals. We illustrate the bias for 4 endangered wolf populations in the United States by reanalyzing data and assumptions about the known and unknown fates of marked wolves to calculate the degree to which risks of different causes of death were mismeasured. We find that, when using traditional methods, the relative risk of mortality from legal killing measured as a proportion of all known fates was overestimated by 0.05–0.16 and the relative risk of poaching was underestimated by 0.17–0.44. We show that published government estimates are affected by these biases and, importantly, are underestimating the risk of poaching. The underestimates have obscured the magnitude of poaching as the major threat to endangered wolf populations. We offer methods to correct estimates of mortality risk for marked animals of any taxon and describe the conditions under which traditional methods produce more or less bias. We also show how correcting past and future estimates of mortality parameters can address uncertainty about wildlife populations and increase the predictability and sustainability of wildlife management interventions.

Worldwide, unsustainable use of nature threatens many ecosystems and the services they provide for a broad diversity of life, including humans. Yet, governments commonly claim that the best available science supports their policies governing extraction of natural resources. We confront this apparent paradox by assessing the complexity of the intersections among value judgments, fact claims, and scientifically verified facts. Science can only describe how nature works and predict the likely outcomes of our actions, whereas values influence which actions or objectives society ought to pursue. In the context of natural resource management, particularly of fisheries and wildlife, governments typically set population targets or use quotas. Although these are fundamentally value judgments about how much of a resource a group of people can extract, quotas are often justified as numerical guidance derived from abstracted, mathematical, or theoretical models of extraction. We confront such justifications by examining failures in transparency about value judgments, which may accompany unsupported assertions articulated as factual claims. We illustrate this with two examples. Our first case concerns protection and human use of habitats harboring the northern spotted owl (Strix occidentalis caurina), revealing how biologists and policy scholars have argued for divergent roles of scientists within policy debates, and how debates between scientists engaged in policy-relevant research reveal undisclosed value judgments about communication of science beyond its role as a source of description (observation, measurement, analysis, and inference). Our second case concerns protection and use of endangered gray wolves (Canis lupus) and shows how undisclosed value judgments distorted the science behind a government policy. Finally, we draw from the literature of multiple disciplines and wildlife systems to recommend several improvements to the standards of transparency in applied research in natural resource management. These recommendations will help to prevent value-based distortions of science that can result in unsustainable uses and eventual extinctions of populations. We describe methods for communicating about values that avoid commingling factual claims and discuss approaches to communicating science that do not perpetuate the misconception that science alone can dictate policy without consideration of values. Our remedies can improve transparency in both expert and public debate about preserving and using natural resources, and thereby help prevent non-human population declines worldwide.

The social license to operate framework considers how society grants or withholds informal permission for resource extractors to exploit publicly owned resources. We developed a modified model, which we refer to as the social license to hunt (SLH). In it we similarly consider hunters as operators, given that wildlife are legally considered public resources in North America and Europe. We applied the SLH model to examine the controversial hunting of large carnivores, which are frequently killed for trophies. Killing for trophies is widespread, but undertaken by a minority of hunters, and can pose threats to the SLH for trophy‐seeking carnivore hunters and potentially beyond. Societal opposition to large carnivore hunting relates not only to conservation concerns but also to misalignment between killing for trophies and dominant public values and attitudes concerning the treatment of animals. We summarized cases related to the killing of grizzly bears (Ursus arctos), wolves (Canis lupus), and other large carnivores in Canada, the United States, and Europe to illustrate how opposition to large carnivore hunting, now expressed primarily on social media, can exert rapid and significant pressure on policy makers and politicians. Evidence of the potential for transformative change to wildlife management and conservation includes proposed and realized changes to legislation, business practice, and wildlife policy, including the banning of some large carnivore hunts. Given that policy is ultimately shaped by societal values and attitudes, research gaps include developing increased insight into public support of various hunting policies beyond that derived from monitoring of social media and public polling. Informed by increased evidence, the SLH model can provide a conceptual foundation for predicting the likelihood of transient versus enduring changes to wildlife conservation policy and practice for a wide variety of taxa and contexts.

Resource management agencies commonly defend controversial policy by claiming adherence to science-based approaches. For example, proponents and practitioners of the "North American Model of Wildlife Conservation," which guides hunting policy across much of the United States and Canada, assert that science plays a central role in shaping policy. However, what that means is rarely defined. We propose a framework that identifies four fundamental hallmarks of science relevant to natural resource management (measurable objectives, evidence, transparency, and independent review) and test for their presence in hunt management plans created by 62 U.S. state and Canadian provincial and territorial agencies across 667 management systems (species-jurisdictions). We found that most (60%) systems contained fewer than half of the indicator criteria assessed, with more criteria detected in systems that were peer-reviewed, that pertained to "big game," and in jurisdictions at increasing latitudes. These results raise doubt about the purported scientific basis of hunt management across the United States and Canada. Our framework provides guidance for adopting a science-based approach to safeguard not only wildlife but also agencies from potential social, legal, and political conflict.