Effective monitoring for biodiversity conservation

Abstract

Monitoring of biodiversity is expensive and can detract resources for managing biodiversity. Given limited resources for conservation, it is not only important to assess the choices we make for managing biodiversity but also those for monitoring biodiversity. This entails considering the benefits and costs of alternative monitoring strategies, and selecting the ones that best inform and improve management decisions. However, understanding which aspects of an ecosystem to monitor (e.g. which species, threat, or indicator) to make effective management decisions is a challenging task. This is especially true when we are faced with large uncertainties, such as those regarding the drivers of change when species are impacted by multiple threats. Although optimal monitoring approaches for conservation decision-making under limited resources have gained popularity over the last decade, similar approaches for monitoring and indicator selection to inform the management of multiple threats for biodiversity have received relatively little attention. In this thesis, I contribute to the theory and tools for selecting monitoring strategies and indicators to improve management decisions, with a focus on multi-species, multi-threat systems. The four objectives of my thesis are: (1) to review current approaches for selecting indicator species for biodiversity management; (2) to assess the value of monitoring species for managing multiple threats; (3) to assess the relative influence of uncertainty and expected benefits of management on monitoring decisions for multiple threats; and (4) to develop a simple indicator selection tool based on a return on investment framework for managing multi-species, multi-threat systems. The thesis starts with a systematic review of the conservation literature, in chapter two, to assess the extent to which the selection of indicator species for biodiversity management explicitly considers management objectives and the management outcomes of monitoring. I find that most indicator selection studies focus on improving the monitoring efficiency rather than the management effectiveness, potentially leading to ineffective indicators. Recommendations are provided to improve indicator selection for management decision-making. I also propose a decision framework for selecting indicator species and identify decision-analytic approaches to evaluate alternative monitoring choices that are further developed in the remainder of the thesis. In chapter three, I use value of information analysis to investigate how monitoring alternative species subject to multiple threats improves our ability to inform the management of these threats. Specifically, I compare the effectiveness of passive monitoring (monitoring species without experimentation) with experimental monitoring (monitoring with experimentation to learn about threats). My results show that monitoring species alone is unlikely to provide useful information for threat management when there is uncertainty about the effect of multiple threats. Instead, an experimental design to learn about how species respond to threats in the system provides much higher benefits for management in terms of conservation outcomes. In chapter four I again use value of information analysis to establish the benefit of monitoring to resolve uncertainty about the effectiveness of management on two different threats. Here, look at the effect of uncertainty versus the relative expected effectiveness of each management action on the value of monitoring to inform management. I find that decisions regarding whether managers should implement monitoring to inform management of the threats depend on the difference in the expected benefit of managing each threat, and the uncertainty in the benefit of managing the threat. In cases where monitoring is found to be beneficial, monitoring the action with the greater uncertainty always provides higher benefit. In chapter five, I propose a relatively simple indicator selection tool for real-world conservation decision-making, compared to the value of information approach. Here, I evaluate the cost-effectiveness of alternative indicators for informing management decisions. The approach incorporates six key factors that include monitoring efficiency, management outcomes and economic constraints. I find that that indicator selection based on the cost-effectiveness approach improves threat management decisions when resources are limited, leading to better conservation outcomes. Because this framework accounts for multiple criteria, it improves on common approaches whereby indicators are often selected based only on whether they are sensitive to change, or cheap to monitor. This thesis makes original contributions to the field of optimal monitoring to manage multi-species, multi-threat systems. It develops the underlying theory for relatively complex systems where there is a wide range of possible monitoring options, and proposes decision-analytic approaches to evaluate alternative monitoring choices. Through the use of case studies, I illustrate different scenarios of decision making that vary in context, to demonstrate the real world applicability for the proposed approaches. In doing so, this thesis addresses the repeated calls for monitoring to be better suited for informing policy and decisions on management actions for biodiversity conservation.