Martin Drechsler

RANKING METAPOPULATION EXTINCTION RISK: FROM PATTERNS IN DATA TO CONSERVATION MANAGEMENT DECISIONS

Viability analyses of large metapopulations are often hampered by difficulties in the parameter estimation. This leads to high uncertainty in parameter values and model outputs and complicates the formulation of clear recommendations for conservation management. We present a comprehensive procedure that is able to process spatiotemporal patterns of metapopulation occupancy to rank management scenarios. The first step of the procedure involves the formulation of the stochastic metapopulation model and the estimation of parameter values with a Bayesian approach, using a Markov chain Monte Carlo algorithm. In the second step, the model is used to predict the effects of different management actions, taking into account the uncertainty in the parameter estimates. Finally, in the third step, decision analysis is used to evaluate and aggregate the results of the previous step into a simple rank order of management scenarios. The procedure was applied to a metapopulation of the Glanville fritillary, Melitaea cinxia. Although the amount of available occupancy data was considerable, the uncertainty in the estimated model parameter values was so large that a precise estimate of the extinction risk of the metapopulation could not be made. However, the procedure was able to produce a rank order of management scenarios that was extraordinarily robust to the uncertainty. Application of the procedure to two other case studies revealed that, even though robust rankings cannot always be obtained, the results of the procedure are helpful in assessing the degree of uncertainty in the ranking and pointing to those factors most responsible for the lack of robustness. The results of this paper demonstrate very clearly, by way of example, both the limitations and the possibilities of model-based metapopulation viability analysis.

An ecological-economic modelling procedure to design compensation payments for the efficient spatio-temporal allocation of species protection measures

Abstract Using an interdisciplinary approach, we present an ecological-economic modelling procedure to design compensation payments for species protection. We develop our procedure on the example of White Stork protection in a spatio-temporally structured landscape generated by human land use. The proposed procedure is able to solve complex allocation problems such as the spatio-temporal allocation of a budget among more than two areas with spatially differing species-specific cost and benefit functions of any shapes. Furthermore, the procedure delivers the efficient compensation payments not only qualitatively but quantitatively, and is hence relevant to the implementation of species protection policies.

Model-based Conservation Decision Aiding in the Presence of Goal Conflicts and Uncertainty

Goal conflicts and uncertainty are two major problems in decision-making for conservation and species protection. Conflicts can often be found between ecological goals on the one hand and socio-economic goals on the other, but also among different ecological goals. They can be formally analysed by methods of multi-criteria analysis. As the solution of a multi-criteria decision problem usually depends on the weights put on the individual criteria (objectives), sensitivity and robustness analyses are necessary to understand the decision problem, concentrate on the essential aspects, and support actual decision processes fully. Uncertainty in the decision problem is often caused by scarcity of information needed to predict the consequences of management actions. The so-called outranking concept proved very useful in the consideration of such uncertainty. Based on a simple fictitious case study the paper demonstrates how multi-criteria decision analysis (in particular the PROMETHEE outranking method) in combination with population model analysis can assist in conservation biological decision-making.

Trade-offs between local and regional scale management of metapopulations

A model analysis of the extinction of metapopulations is presented, based on a general model which explicitly considers essential population dynamical factors, such as environmental fluctuations and dispersal of individuals. The model is used to evaluate the influences of three plausible management options on the viability of a metapopulation. These are the increase of the capacity and the number of patches and the improvement of their connectivity. We find that the effects of these management options depend on the specific environmental conditions, such as environmental variability and the patch capacities. We generate a set of scenarios which cover a wide range of different environmental situations. For each scenario the influences of the management options are evaluated. The results are used to compare local management of subpopulations with the establishment of a habitat network.

Smart spatial incentives for market-based conservation

Abstract Market-based instruments such as payments, auctions or tradable permits have been proposed as flexible and cost-effective instruments for biodiversity conservation on private lands. Trading the service of conservation requires one to define a metric that determines the extent to which a conserved site adds to the regional conservation objective. Yet, while markets for conservation are widely discussed and increasingly applied, little research has been conducted on explicitly accounting for spatial ecological processes in the trading. In this paper, we use a coupled ecological–economic simulation model to examine how spatial connectivity may be considered in the financial incentives created by a market-based conservation scheme. Land use decisions, driven by changing conservation costs and the conservation market, are simulated by an agent-based model of land users. On top of that, a metapopulation model evaluates the conservational success of the market. We find that optimal spatial incentives for agents correlate with species characteristics such as the dispersal distance, but they also depend on the spatio-temporal distribution of conservation costs. We conclude that a combined analysis of ecological and socio-economic conditions should be applied when designing market instruments to protect biodiversity.

The importance of economic costs in the development of guidelines for spatial conservation management

The paper analyses the efficient spatial allocation of subsidies for biodiversity-enhancing land use. For this purpose a spatial allocation model for two different regions is developed which allows guidelines to be derived on how to achieve the highest possible ecological benefit within a given budget provided to support biodiversity-enhancing forms of land use. In contrast to other conservation biological models, our model includes more realistic economic assumptions. The difference from economic models dealing with the efficient spatial allocation of environmental goods is that the benefit function of our model is based on ecological theory. Therefore, our results differ from those obtained in monodisciplinary studies. In particular, with increasing marginal costs a more even allocation of resources becomes optimal.

Modelling the persistence of an apparently immortal Banksia species after fire and land clearing

Abstract A stage-based model was developed for the population dynamics of Banksia goodii , a rare long-lived shrub in Western Australia. While few seeds are produced, death of adults due to senescence or fire has yet to be observed. A sensitivity analysis showed that population growth is close to zero as long as post-fire mortality and recruitment are within their usual low bounds. To remain viable, the size of a population remnant should exceed about 80 individuals. If fires occur at random intervals, an average of one fire in 10–15 years is optimal. Regular fires should have inter-fire periods of 15–20 years. Loss of adult plants due to human activities, such as land clearing, will increase mortality beyond its natural bounds and cannot be compensated for, due to the low fecundity of this species. Hand sowing after a fire may raise establishment by orders of magnitude and achieve a permanent population increase within the first year. Conservation authorities should target the sensitive factors through active management at the recruitment stage and by ensuring that no further loss of mature plants takes place through land clearance. ©

Combining population viability analysis with decision analysis

Management of endangered species requires methods to assess the effects of strategies, providing a basis for deciding on a best course of action. An important component of assessment is population viability analysis (PVA). The latter may be formally implemented through decision analysis (DA). These methods are most useful for conservation when used in conjunction. In this paper we outline the objectives and the potential of both frameworks and their overlaps. Both are particularly helpful when dealing with uncertainty. A major problem for conservation decision-making is the interpretation of observations and scientific measurements. This paper considers probabilistic and non-probabilistic approaches to assessment and decision-making and recommends appropriate contexts for alternative approaches.

Multicriteria analysis under uncertainty with IANUS - method and empirical results

Integrated assessment of decisions under uncertainty for sustainable development (IANUS) is a method for aiding public decisionmaking that supports efforts towards sustainable development and has a wide range of applications. We introduce the main features of IANUS and illustrate the method by using the results of a case study in the Torgau region (eastern Germany) with conflicts over economic development and groundwater protection in the Elbe River basin. IANUS structures the decision process into four steps: scenario derivation, criteria selection, modelling, and evaluation. Its overall aim is to support the finding of policy solutions in a participatory setting and to extract the information needed for a sound, responsible decision in a clear, transparent manner. The method is designed for use in conflict situations where environmental and socioeconomic effects need to be considered and so an interdisciplinary approach is required. Special emphasis is placed on a broad perception and consideration of uncertainty. Three types of uncertainty are explicitly taken into account by IANUS: development uncertainty (uncertainty about the social, economic and other developments that affect the consequences of decision), model uncertainty (uncertainty associated with the prediction of the effects of decisions), and weight uncertainty (uncertainty about the appropriate weighting of the criteria). The backbone of IANUS is a multicriteria method with the ability to process uncertain information. In the case study the multicriteria method PROMETHEE is used. As PROMETHEE in its basic versions is not able to process uncertain information an extension of this method is developed here and described in detail. One methodological lesson to be learned from the experience of the case study reads that the design of the participation process must be planned and executed carefully to prevent important stakeholders backing out of the participatory evaluation process—as happened with the decisionmakers in the Torgau case study.

Uncertainty in population dynamics and its consequences for the management of the orange-bellied parrot Neophema chrysogaster

Abstract The population dynamics of a rare and dispersed species like the Orange-bellied Parrot Neophema chrysogaster include many uncertainties, especially concerning mortality. Taking these uncertainties into account we evaluated several options for management of the Orange-bellied Parrot habitat. Options were ranked by their effects on the viability of the population. There was considerable variability in the resulting rank orders. A few general features appeared to be rather stable with respect to all forms of uncertainty considered. It was found that survival of birds during the winter season was more important than their reproductive success in summer and qualitative features of the habitat, such as the composition of vegetation, were more important than quantitative features such as the habitat size.