Measuring and predicting conservation conflicts: creating an inter-disciplinary horizon scanning tool
Conflicts between wildlife conservation and other human livelihoods are numerous, widespread and detrimental to both biodiversity and human well-being (Redpath et al. 2013). Yet, as conservationists, we have a very poor track record of measuring and predicting them.
This poor track record may arise because conflicts in conservation are complex and often involve many different stakeholders (Marshall et al. 2007). Conflicts are defined by a combination of ecological, social, cultural, economic and historical characteristics, which may vary considerably from one case study to the next (Dickman & Hazzah 2016). Much of the literature relating to conservation conflicts (including “human-wildlife” conflicts) focuses on specific case studies or species, serving to highlight the distinctive character of each situation, but not commonalities between them. Moreover, there is a lack of consistency in how conflicts are measured, including which aspects are considered, what indicators are used, and how conflict levels are scaled. These challenges were highlighted during a workshop on Conservation Conflicts held at the University of Stirling, Scotland, in March 2017.
One could argue that such challenges also apply to the study of armed conflicts. Yet, analyses and predictions of armed conflict are more widespread in the literature, and supported by extensive datasets and multinomial models (Burnley et al. 2008, Wimmer et al. 2009, Hegre et al. 2013). Frameworks such as the “Curve of Conflict” (Lund 2009) or the ViEWS project (Colaresi et al. 2016; Hegre et al. 2016) facilitate the comparison and forecasting of conflicts, something that is sorely needed when considering conservation conflicts (although see Madden & McQuinn 2014).
At ICN 2018
The overall aim of this workshop will be to develop a general framework with which to measure and predict conservation conflict levels. We will try to think of conflicts in a general sense, aiming to highlight aspects that can be generalised across individual case studies. More specifically, we will explore the following questions:
- What are the fundamental characteristics of conservation conflicts?
- How can we measure these characteristics?
- Do any frameworks enabling integration of these characteristics currently exist in the conservation literature?
- Can we use tools and frameworks developed in the context of armed conflicts (e.g. extensive databases, models) to predict future conservation conflicts and inform potential courses of action?
The output of this workshop will be a collaboratively written scientific paper summarising the key characteristics of conflicts and how these could be measured. We will also aim to present a framework that unifies the different characteristics, potentially applying it to a selected case study.
Redpath, S. M., Young, J., Evely, A., Adams, W. M., Sutherland, W. J., Whitehouse, A., Amar, A., Lambert, R. A., Linnell, J. D., Watt, A., & Gutierrez, R. J. (2013). Understanding and managing conservation conflicts. Trends in Ecology & Evolution, 28(2), 100-109.
Marshall, K., White, R., & Fischer, A. (2007). Conflicts between humans over wildlife management: on the diversity of stakeholder attitudes and implications for conflict management. Biodiversity and Conservation, 16(11), 3129-3146.
Dickman, A. J., & Hazzah, L. (2016). Money, myths and man-eaters: complexities of human–wildlife conflict. In Problematic Wildlife (pp. 339-356). Springer International Publishing.
Burnley, C., Buda, D., & Kayitakire, F. (2008). Quantifying the Risk of Armed Conflict at Country Level—A Way Forward. 3 Treaty Monitoring Based on Geographic Information Systems and Remote Sensing, 38.
Wimmer, A., Cederman, L. E., & Min, B. (2009). Ethnic politics and armed conflict: A configurational analysis of a new global data set. American Sociological Review, 74(2), 316-337.
Hegre, H., Karlsen, J., Nygård, H. M., Strand, H., & Urdal, H. (2013). Predicting armed conflict, 2010–2050. International Studies Quarterly, 57(2), 250-270.
Lund, M. S. (2009). Conflict prevention: Theory in pursuit of policy and practice (pp. 287-308). London: Sage.
Colaresi, M., Hegre, H., & Nordkvelle, J. (2016). Early ViEWS: a prototype for a political Violence Early-Warning System. Paper presented to the American Political Science Association annual meeting 2016, Philadelphia. Accessible online: http://www.pcr.uu.se/digitalAssets/653/c_653796-l_1-k_earlyviewsapsa2016.pdf
Hegre, H., Buhaug, H., Calvin, K.V., Nordkvelle, J., Waldhoff, S.T., & Gilmore, E. (2016). Forecasting civil conflict along shared socioeconomic pathways. Environmental Research Letters, 11 (5), 054002
Madden, F., & McQuinn, B. (2014). Conservation’s blind spot: the case for conflict transformation in wildlife conservation. Biological Conservation, 178, 97-106.