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Wild Animal Suffering is Intractable

Abstract

Most people believe that suffering is intrinsically bad. In conjunction with facts about our world and plausible moral principles, this yields a pro tanto obligation to reduce suffering. This is the intuitive starting point for the moral argument in favor of interventions to prevent wild animal suffering (WAS). If we accept the moral principle that we ought, pro tanto, to reduce the suffering of all sentient creatures, and we recognize the prevalence of suffering in the wild, then we seem committed to the existence of such a pro tanto obligation. Of course, competing values such as the aesthetic, scientific or moral values of species, biodiversity, naturalness or wildness, might be relevant to the all-things-considered case for or against intervention. Still, many argue that, even if we were to give some weight to such values, no plausible theory could resist the conclusion that WAS is overridingly important. This article is concerned with large-scale interventions to prevent WAS and their tractability and the deep epistemic problem they raise. We concede that suffering gives us a reason to prevent it where it occurs, but we argue that the nature of ecosystems leaves us with no reason to predict that interventions would reduce, rather than exacerbate, suffering. We consider two interventions, based on gene editing technology, proposed as holding promise to prevent WAS; raise epistemic concerns about them; discuss their potential moral costs; and conclude by proposing a way forward: to justify interventions to prevent WAS, we need to develop models that predict the effects of interventions on biodiversity, ecosystem functioning, and animals’ well-being.

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Notes

  1. Dawkins (1995), Horta (2010) and Tomasik (2015). Also see an overview at http://www.animal-ethics.org/population-dynamics-animal-suffering/ (accessed January 18, 2017).

  2. The prevalence claim might be subject to disagreement or epistemic uncertainty, regarding the scope as well as the intensity of negative experience across species. We set the question aside for the argument’s sake.

  3. For instance, Nussbaum (2006) advocates an “intelligent, respectful paternalism” (p. 370) and “the gradual supplanting of the natural by the just” (p. 400), and argues that, given our pervasive interference with natural processes and the cruelty inherent in nature, we have positive duties to ensure the flourishing of all creatures with “capabilities”; Sapontzis (1987, Ch. 13) argues that our commonsense principles commit us to accept that, in some circumstances, we have positive duties to rescue “the rabbit from the fox”; Johannsen (2017) (see below) also argues from non-utilitarian premises.

  4. For instance, Liz Ashford (2003) has argued that Scanlonian contractualism can be very demanding and commit well-off agents to stringent obligations to make significant sacrifices for the global poor. However, Hills (2010) has argued that utilitarianism is uniquely demanding when it comes to WAS, a problem that contractualism has an easier job avoiding.

  5. Text in parentheses added.

  6. The r/K-selection paradigm was introduced by MacArthur and Wilson (1967) and gained traction in the 1970s. Its predictive power and empirical adequacy have since been subject to controversy (see e.g., Reznick et al. 2002). We do not take a stance on this. We treat the distinction as a rough heuristic meant to capture the evolution of different life histories and reproduction strategies.

  7. ‘CRISPR’ is an acronym for Clustered Regularly Interspaced Short Palindromic Repeats, a naturally occurring feature of certain bacterial genetic codes that functions as a sort of immune defense system against invading viruses. CRISPRs, which contain the genetic code of past invading viruses, are used to help identify and destroy those viruses when they return. The CRISPR/Cas9 technology is based on this remarkable feature of bacteria. It acts as a cutting tool—the Cas9 enzyme is guided to a target DNA sequence and then “cuts it”, either shutting off or activating the targeted gene.

  8. For more on the complexity of SES’s, see our “Climate Change” section below.

  9. See Gruen (2011, 185–187) for examples of the “havoc” that our interventions often wreak, e.g., adjudicating between in conflicts between native and non-native species; and Jamieson (2008, Ch. 6).

  10. See for instance Lashley et al. (2018) on the complex ecological consequences of a recent experimental massive culling of feral pigs.

  11. Management may not always involve promoting resilience, because resilience is not necessarily desirable (Walker et al. 2004). When a system is in an undesirable regime, good management may require overcoming resilience to reach a new regime. Of course, the question of what regimes are “desirable” is up for debate. To make our point here we only need it to be true that the regime state of an ecosystem has significant bearing on the well-being of the ecosystem’s members.

  12. That is, the higher the number of individuals and species, the lower the variance in response, eventually approximating the mean response predicted by theoretical models of the system.

  13. If Ng (see fn. 30 below) and Tomasik are right that suffering is largely prevalent in nature in part because of r-strategists, then interventions that accidentally cause e.g., species extinction or habitat loss would tend to decrease total suffering by reducing the number of r-strategists. We have argued against this view because (1) we cannot reliably predict that ecological damage will not have other major impacts and (2), as we argue below, additional considerations tip the scale against taking such risks. The threshold of acceptable risk, of course, depends on the relative importance of these different considerations, including one’s confidence in the disvalue of the existence of r-strategists. We also note that this strategy relies on the assumption that these are necessarily lives not worth living. We thank Kyle Johannsen for pressing us on this point.

  14. We do not assume that resilience per se is always desirable. Whether it is depends on many natural and social factors. Our claim is that the descriptive concept of resilience captures one way in which altering ecosystems can affect predictability, which is key to overcoming the practical constraint on interventions we started with.

  15. Some K-strategists, the Giant Panda for instance, are inflexible at both the population level and the individual level. The Giant Panda is a threatened species of course, and so it is an exception that proves the rule: flexibility either at the individual level or at the population level is crucial for resilience to disruption. A decrease in flexibility at one level without a corresponding increase in flexibility at the other level can therefore be expected to worsen a species’ prospects for survival in the face of disruption.

  16. The authors stress the importance of long-term studies to evaluate the effects of gene drive use on genetic diversity as part of an “integrated management of environmental and security risks”. For “any population reduced in numbers will have reduced genetic diversity and could be more vulnerable to natural or anthropogenic pressures.” If altered communities became more vulnerable to such pressures, our ability to predict their future states would decrease.

  17. See Naeem et al. (2009, 5) for numerous citations in support of these claims.

  18. Construing ecological systems as SESs also entails that promoting resilience, and therefore managing unpredictability, does not require a hands-off approach but rather an integrated form of management about which we say more later.

  19. In a context of high decision stakes and/or high system uncertainty, the relation between policy and science may be helpfully approached from the standpoint of “Post-Normal Science,” in particular given the conflicting values involved (Funtowicz and Ravetz 1990).

  20. Advocates to reduce WAS are aware of this and now tend to focus their messages on fewer, identifiable victims. See e.g., Animal Ethics: http://www.animal-ethics.org/. Accessed March 1st, 2017.

  21. Tomasik, http://reducing-suffering.org/how-many-wild-animals-are-there/ Accessed March 1st, 2017.

  22. Here Derek Parfit’s non-identity problem (1976, 1984) rears its head, as it does with any policy or action that alters procreative behavior. The core of the problem is how to morally assess actions that both affect the quality of life of future individuals and determine which individuals will come to exist in the future. Here the concern is that, as long as future wild animals have lives worth living, and they would not have existed had we not intervened to prevent WAS, then it is not clear that we can identify a sense in which our intervention harms them. Addressing the non-identity problem, or its many purported solutions, is beyond the scope of this paper.

  23. Key figures in this debate include Rachels (1975), Foot (1967), Thomson (1976) and Bennett (1995). Kagan (1989) provides perhaps the most compelling sustained attack on the doing/allowing distinction.

  24. Thomson (1976, 206).

  25. David Morrow (2014) defends a similar claim in the context of discussing the ethics of geoengineering the global climate system in response to climate change. He argues that, because of the existence of a moral asymmetry between doing and allowing harm, “the bar for establishing [geoengineering’s] potential moral permissibility is higher than some scientists believe.” (124). The moral relevance of the distinction between “a negative duty not to harm” and a “positive duty to assist” also forms the backbone of Clare Palmer’s defense of the “Laissez-faire Intuition”, the intuition that there is no presumptive duty to assist wild animals (2010, 75).

  26. This objection does not apply to calls to refrain from reintroducing predator species to areas where they have been driven to extinction. Reintroducing such species would count as doing harm.

  27. It is easier to damage a complex system than to improve it because the ways in which “[it] could be damaged are indefinitely more numerous than the ways in which it could be improved” (Savulescu and Persson 2012, 51).

  28. Rolston (1989), Katz (2000) and Cafaro (2001). Sandler (2012) summarizes these different accounts of the value of species.

  29. We are appealing, rather loosely, to the account of transformative experience developed by Paul (2014).

  30. Note that one the early proponents of “welfare biology”-based interventions to reduce the suffering of wild species, a recurrent reference in the WAS community (Ng 1995), has recently argued that we should focus on the suffering of domesticated species before dedicating significant resources to WAS (Ng 2016).

  31. We thank Glen Miller for these suggestions.

  32. Also see Nussbaum (2006, 366–370).

  33. We thank Glen Miller for pressing us on this issue.

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Acknowledgements

This article benefitted from fruitful early discussions with Dale Jamieson, detailed comments from Kyle Johannsen, Glen Miller, and two anonymous referees, and feedback from audiences at the Bovay Workshop on Engineering and Animal Ethics at Texas A&M and the CRE/GREA Conference on Animal and Environmental Ethics at McGill University in Montreal. We also thank Clare Palmer and Gary Varner for their encouragement and suggestions.

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Delon, N., Purves, D. Wild Animal Suffering is Intractable. J Agric Environ Ethics 31, 239–260 (2018). https://doi.org/10.1007/s10806-018-9722-y

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Keywords

  • Ecology
  • Welfare
  • Animal suffering
  • Genetic engineering
  • Ecosystem management