ANALYSIS AND IMPLEMENTATION
Adaptive Management of Leopard in South Africa
Through a scientific partnership with Panthera, SANBI (and provincial conservation authorities) will be assessing the consequences of a range of management strategies and presenting the results in a way that lays bare the trade-offs in performance across a range of management objectives - this approach is known as Monitoring Strategy Evaluation, or MSE. MSE is a simulation technique based on modelling each part of the adaptive management cycle (Figure 1). It was developed more than 20 years ago to consider the implications of alternative management strategies for the robust management of natural resources, such as fish stocks. In contrast to some previous approaches to assess resource management, MSE does not seek to proscribe an optimal strategy or decision. Instead, MSE seeks to provide the decision maker (i.e., SANBI) with the information on which to base a rational decision, given their own objectives, preferences, and attitudes to risk.
Through a scientific partnership with Panthera, SANBI (and provincial conservation authorities) will be assessing the consequences of a range of management strategies and presenting the results in a way that lays bare the trade-offs in performance across a range of management objectives - this approach is known as Monitoring Strategy Evaluation, or MSE. MSE is a simulation technique based on modelling each part of the adaptive management cycle (Figure 1). It was developed more than 20 years ago to consider the implications of alternative management strategies for the robust management of natural resources, such as fish stocks. In contrast to some previous approaches to assess resource management, MSE does not seek to proscribe an optimal strategy or decision. Instead, MSE seeks to provide the decision maker (i.e., SANBI) with the information on which to base a rational decision, given their own objectives, preferences, and attitudes to risk.
Figure 1. The adaptive management cycle
The MSE method has been used by the International Whaling Commission (e.g. IWC 1992, Kirkwood 1997) and Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) (de la Mare 1996) and has been adopted as a standard fisheries tool in a number of countries including: South Africa (Punt and Butterworth 1995, Cochrane et al 1998, Butterworth et al 1998), Europe (Horwood 1994, as of Butterworth and Punt 1999), New Zealand (Starr et al. 1997) and Australia (Punt and Smith 1999). The strength of the MSE approach is that instead of using a single model to find an optimal solution, multiple candidate models are put forward to evaluate alternate hypotheses. By modelling each step of the formal adaptive-management approach the consequences of alternate scenarios can be evaluated across the models. The other core strength of the MSE process is that it is consultative - both managers and stakeholders can have input into the candidate models and management scenarios. As the MSE approach demands clear objectives to do the evaluations against, the method forces participants to be transparent about their objectives and to specify performance indicators that are in the context of what people are interested in.
The power of MSE has yet to be fully realised, and used, in terrestrial conservation. The management of natural resources is a complex process, which is driven by interactions between the dynamics of the natural system, the behaviour and decision-making of stakeholders (e.g., SANBI, hunters, farmers, conservationists, and politicians), and uncertainty at various levels of the management process and well as the natural system. Fixed harvest quotas are prone to failure, often due to their inability to respond to system dynamics and uncertainty. However, research on lion (Panthera leo) demonstrates that MSE can be a very useful and game-changing management tool (Edwards et al. 2014). For additional reading, download the paper below:
The power of MSE has yet to be fully realised, and used, in terrestrial conservation. The management of natural resources is a complex process, which is driven by interactions between the dynamics of the natural system, the behaviour and decision-making of stakeholders (e.g., SANBI, hunters, farmers, conservationists, and politicians), and uncertainty at various levels of the management process and well as the natural system. Fixed harvest quotas are prone to failure, often due to their inability to respond to system dynamics and uncertainty. However, research on lion (Panthera leo) demonstrates that MSE can be a very useful and game-changing management tool (Edwards et al. 2014). For additional reading, download the paper below:
| Edwards et al. (2014) Data-poor management of African lion hunting using a relative index of abundance |
How Does Monitoring Strategy Evaluation Actually Work?
The MSE approach is based on a set of models about the population dynamics of a species (e.g., leopard). These model sets are know as the 'Resource Operating Model' (Figure 2). The resource operating model aims at capturing the key processes in leopard population dynamics given the best ecological knowledge available. The resource operating model is considered a 'minimum realistic model'.
The next MSE phase is to simulate the process of monitoring leopard, which results in simulated measurements such as the number of individuals, distribution, sex ratios, etc. Monitoring is always imperfect because we cannot detect all individuals, particularly across large spatial scales such as Limpopo Province. This monitoring component is represented by the 'Observation Model', and it accounts for error and bias.
The data used in the observation model are then passed to the 'Management Model', which encompasses the 'harvest control rule' (HCR). The HCR is a set of well-defined rules used for determining management actions in the form of a 'total allowable harvest' (i.e., the total number of leopard than can be removed from the system) or 'total allowable effort' (i.e., the total effort required to successfully remove a leopard from the system). The HCR incorporates factors such as biological components, socio-economic components, stakeholder requirements, spatial and temporal restrictions (e.g., hunting zones), and harvest methods (i.e., hunting techniques). Importantly, the success of management implementation and human-decision making (e.g., hunter compliance to new management interventions) can be incorporated around the HCR. This is an important addition to assessing management strategies, as resource users (e.g., professional hunters or subsistence poachers) may not fully comply to regulations, or individual behavioural dynamics of resource users might affect how a species is harvested. These various HCRs form the 'Harvester Operating Model', which then feeds back to the resource operating model as the model updates to the next time step.
By evaluating a range of HCRs against a set of operating models using multiple performance metrics, MSE enables scientists to give resource managers advice on robust management procedures as well as on the trade-offs involved with each procedure (Bunnefeld et al. 2011). MSEs can evaluate which data and how much of it should be collected and how often monitoring should be carried out to improve management performance. Stakeholders can be involved at various points in the process of proposing and evaluating different HCRs and assessment approaches. There is ample evidence from terrestrial conservation and fisheries that stakeholder involvement throughout the process of resource management is key to compromise between stakeholders, acceptance of the rules and hence the sustainability of resource use (Bunnefeld et al. 2011).
The MSE approach is based on a set of models about the population dynamics of a species (e.g., leopard). These model sets are know as the 'Resource Operating Model' (Figure 2). The resource operating model aims at capturing the key processes in leopard population dynamics given the best ecological knowledge available. The resource operating model is considered a 'minimum realistic model'.
The next MSE phase is to simulate the process of monitoring leopard, which results in simulated measurements such as the number of individuals, distribution, sex ratios, etc. Monitoring is always imperfect because we cannot detect all individuals, particularly across large spatial scales such as Limpopo Province. This monitoring component is represented by the 'Observation Model', and it accounts for error and bias.
The data used in the observation model are then passed to the 'Management Model', which encompasses the 'harvest control rule' (HCR). The HCR is a set of well-defined rules used for determining management actions in the form of a 'total allowable harvest' (i.e., the total number of leopard than can be removed from the system) or 'total allowable effort' (i.e., the total effort required to successfully remove a leopard from the system). The HCR incorporates factors such as biological components, socio-economic components, stakeholder requirements, spatial and temporal restrictions (e.g., hunting zones), and harvest methods (i.e., hunting techniques). Importantly, the success of management implementation and human-decision making (e.g., hunter compliance to new management interventions) can be incorporated around the HCR. This is an important addition to assessing management strategies, as resource users (e.g., professional hunters or subsistence poachers) may not fully comply to regulations, or individual behavioural dynamics of resource users might affect how a species is harvested. These various HCRs form the 'Harvester Operating Model', which then feeds back to the resource operating model as the model updates to the next time step.
By evaluating a range of HCRs against a set of operating models using multiple performance metrics, MSE enables scientists to give resource managers advice on robust management procedures as well as on the trade-offs involved with each procedure (Bunnefeld et al. 2011). MSEs can evaluate which data and how much of it should be collected and how often monitoring should be carried out to improve management performance. Stakeholders can be involved at various points in the process of proposing and evaluating different HCRs and assessment approaches. There is ample evidence from terrestrial conservation and fisheries that stakeholder involvement throughout the process of resource management is key to compromise between stakeholders, acceptance of the rules and hence the sustainability of resource use (Bunnefeld et al. 2011).
Figure 2. Flow diagram for the management strategy evaluation framework. This comprises a resource operating model (simulating the ‘true’ population biology of the species), the observation model to monitor the species (with error) and the management model, using the perceived stock to create and implement the harvest control rules. In the extended model (dotted line) the harvest control rule is fed into an additional harvester model which allows for individual decision-making by harvesters. In this model, the harvester can also be monitored through the observation model (dotted line). Figure and explanation courtesy of Bunnefeld et al. (2011)