Blog originally posted in November 2013 at Stirling Conservation Science
As conservationists, we endeavour providing increasingly better solutions for conservation issues, based on reliable information and robust understanding of the dynamics of the systems under consideration. However, despite our efforts in collecting data and learning about our study systems, increasing predictability and improving conservation implementation, conservation is both uncertain and dynamic. Uncertainty is very common in natural resource management and conservation; decisions may be affected by, for example, stochastic environmental variation, limited ability to observe wildlife and a lack of understanding about functional responses. So should we just give up and throw a coin when making decisions? On the contrary: we should investigate multiple types of uncertainty and their potential implications so that we can support better decisions. And that’s exactly what I did during my recently finished doctoral studies.
As conservationists, we endeavour providing increasingly better solutions for conservation issues, based on reliable information and robust understanding of the dynamics of the systems under consideration. However, despite our efforts in collecting data and learning about our study systems, increasing predictability and improving conservation implementation, conservation is both uncertain and dynamic. Uncertainty is very common in natural resource management and conservation; decisions may be affected by, for example, stochastic environmental variation, limited ability to observe wildlife and a lack of understanding about functional responses. So should we just give up and throw a coin when making decisions? On the contrary: we should investigate multiple types of uncertainty and their potential implications so that we can support better decisions. And that’s exactly what I did during my recently finished doctoral studies.
Using the conservation of harvested ungulate species in the Serengeti, Tanzania, as a case study, I was fortunate to spend a few years studying one of the most famous protected areas in the world. Despite many conservation interventions over the last decades, the challenges to the sustainability of the Serengeti have never been greater since the national park was formed in 1951. For example, although bushmeat hunting has been illegal for decades and anti-poaching enforcement has been one of the main activities of the national park since its creation, illegal hunting by local communities has remained a notoriously difficult (and potentially escalating) issue to address.
Poachers’ camp in the Serengeti. © FZS (Frankfurt Zoological Society)
This case study represented a unique opportunity to explore the challenges of managing social-ecological systems, giving special attention to the issues of observation and implementation uncertainty. When I started my PhD, a few issues came up several times when reading the available literature and meeting several people working in the study area. On the one hand, the illegal and sensitive nature of poaching made its quantification a particularly difficult task. On the other hand, given its immense area (around 25 000km2) and abundant wildlife, detecting trends (and knowing how many animals there are) had several difficulties. Moreover, science and conservation plans were often poorly translated into action and conservation outcomes. How could I contribute to help managers making decisions about this complex system under such varied uncertainty?
Acknowledging the social-ecological nature of the system, I took a multidisciplinary approach and combined a number of tools such as matrix population models, semi-structured interviews and social network analysis. For example, I employed simulation modelling to investigate how wildlife abundance estimates are affected by multiple types of uncertainty and investigated which factors should be prioritized in order to increase survey accuracy and precision (see our paper). Then, I explored trade-offs between different types of error when monitoring changes in population abundance and explored how these interactions vary depending on budgetary, observational and ecological conditions. I also investigated the potential of specialized questioning techniques developed in the social sciences for studying non-compliant and sensitive harvest behaviour; I used the unmatched-count technique (UCT) and identified socio-demographic characteristics of noncompliant households to assess prevalence of illegal hunting in the Serengeti (see our paper). Finally, I investigated the challenges and potential barriers to successful conservation implementation, obtaining insights into the constraints and opportunities for fulfilling stakeholder aspirations for the system, and developed social network models to describe the interactions between different actor types.
Uncertainty is often used as an excuse for inaction and for decision makers to question the overall usefulness of science. My work contributes to better understanding the role and implications of different sources and types of uncertainty for the management of social-ecological systems and provides information for more robust decision-making in the Serengeti. Given that uncertainty has important implications for management decisions, relationships between stakeholders and conservation outcomes, innovative approaches that deal with uncertainty are much needed. Instead of allowing uncertainty to be used as a political weapon, we must improve the way we communicate, deal with and minimize uncertainty, allowing decision-makers and stakeholders to carefully consider alternative options and their risks.
For anyone interested in knowing more about the management of social-ecological systems under uncertainty, here’s my PhD thesis.
Acknowledging the social-ecological nature of the system, I took a multidisciplinary approach and combined a number of tools such as matrix population models, semi-structured interviews and social network analysis. For example, I employed simulation modelling to investigate how wildlife abundance estimates are affected by multiple types of uncertainty and investigated which factors should be prioritized in order to increase survey accuracy and precision (see our paper). Then, I explored trade-offs between different types of error when monitoring changes in population abundance and explored how these interactions vary depending on budgetary, observational and ecological conditions. I also investigated the potential of specialized questioning techniques developed in the social sciences for studying non-compliant and sensitive harvest behaviour; I used the unmatched-count technique (UCT) and identified socio-demographic characteristics of noncompliant households to assess prevalence of illegal hunting in the Serengeti (see our paper). Finally, I investigated the challenges and potential barriers to successful conservation implementation, obtaining insights into the constraints and opportunities for fulfilling stakeholder aspirations for the system, and developed social network models to describe the interactions between different actor types.
Uncertainty is often used as an excuse for inaction and for decision makers to question the overall usefulness of science. My work contributes to better understanding the role and implications of different sources and types of uncertainty for the management of social-ecological systems and provides information for more robust decision-making in the Serengeti. Given that uncertainty has important implications for management decisions, relationships between stakeholders and conservation outcomes, innovative approaches that deal with uncertainty are much needed. Instead of allowing uncertainty to be used as a political weapon, we must improve the way we communicate, deal with and minimize uncertainty, allowing decision-makers and stakeholders to carefully consider alternative options and their risks.
For anyone interested in knowing more about the management of social-ecological systems under uncertainty, here’s my PhD thesis.
RSS Feed
