The introduction of new genetic material into wild populations, using novel biotechnology, has the potential to fortify populations against existential threats, and, controversially, create wild genetically modified populations. The introduction of new genetic variation into populations, which will have an ongoing future in areas of conservation interest, complicates long-held values in conservation science and park management. I discuss and problematize, in light of genetic intervention, what I consider the three core goals of conservation science: biodiversity, ecosystem services, and wilderness. This (...) uneasy relationship, however, does not forgo the use of such interventions. I argue there is a case for the application of this technology within some interpretations of the moral frameworks of wilderness and biodiversity, despite apparent conflict between these values and the technology, and the possibility that this technology's use displays some limitations of the ecosystem services framework. Ultimately, the advent of biotechnology assisted restoration highlights the need for us to reevaluate our ethical concepts of conservation at times of global environmental and technological change. (shrink)

Philosophy and statistics have studied two causal species, deterministic and probabilistic. There's a third species, however, hitherto unanalysed: underdeterministic causal phenomena, which are non-deterministic yet non-probabilistic. Here, I formulate a framework for modelling them. -/- Consider a simple case. If I go out, I may stumble into you but also may miss you. If I don’t go out, we won't meet. I go out. We meet. My going out is a cause of our encounter even if there was no determinate (...) probability of us meeting conditional on my going out. The cause is neither deterministic (it didn't necessitate the effect) nor probabilistic (the relevant conditional probabilities are undefined). Rather, it's underdeterministic: it raises the modal status of the effect from causally impossible to possible. -/- Here, I won't offer a theory of such token causes but develop the prerequisite for any such theory: the underdeterministic framework. The framework is like the deterministic structural-equations framework but with one consequential difference---an equation can return multiple values. This change allows me to define causal possibility and necessity, and corresponding notions of interventionist might- and would-counterfactuals. I also define conditional independence, which obeys the graphoid axioms, and prove that underdeterministic models satisfy the causal Markov condition. The framework can causally model situations that other frameworks cannot: decision-making under bounded uncertainty, games with multiple equilibria, infinite fair lotteries, and any other non-deterministic situation where indeterminacies are essentially non-probabilistic, or where we have a reason not to use probabilities. (shrink)