Page 56 - A bird’s-eye view of recreation - Rogier Pouwels

A bird's-eye view of recreation
This chapter illustrates how models can be part of the framework presented in Fig. 1. Local knowledge and monitoring data increase the quality and credibility of the results from the models. Stakeholder involvement is important not only at the start (scoping / goal setting) and at the end (evaluation) of the planning process (Bentrup 2001), but also during the spatial analysis of scenarios (Johnson & Campbell 1999). Since citizens participating in planning processes will not support what they do not understand (Theobald et al. 2000), decision support tools for choosing common and measurable goals need to be easily understood. The effectiveness of conservation management is thought to be closely linked to adaptive management processes that empower stakeholders, rather than by “ever-more precise techniques for prioritizing elements of nature” (Knight et al. 2006).
The results of the simulation models are useful in communication with stakeholders. Managers can show clearly what the effects of different scenarios are for attainment of both habitat goals and recreation goals. In an iterative and reflective process, indicators for nature and recreational quality can be compared across scenarios. Communicative action among participating stakeholder groups allows eventual construction of a consensus policy on recreational access. Managers of three large dune areas in and around the case study area put effort in the further development of MASOOR (Jochem et al. 2007). This was mainly because the model showed its usefulness in communication with stakeholders. See Jochem et al. (2007) for a discussion on this issue.
Euler stated: “Give me five parameters and I will draw you an elephant; six, and I will have him wave his trunk”. This quotation (in Mollison 1986) illustrates the pitfalls of model parameterization and calibration and is often used as a criticism of using models. However spatial models may be the only objective tools for scenario studies. Translating scenario studies into model parameters can simulate effects of, for example, changes in land-use. While the exact quantitative model outcomes sometimes have high levels of uncertainty, when used for comparing scenarios the results are more robust (Verboom and Wamelink 2005). For example, in applying the NTM model, Schouwenberg et al. (2000) illustrate that the model output had a large uncertainty for a single prediction, but when scenarios were compared the uncertainty was much smaller. The best alternative predicted by the model is likely to be the best one in real life (Verboom and Wamelink 2005). It is in the comparative evaluation of scenarios that integrated use of models such as MASOOR and METAPHOR may have its greatest utility. Managers faced with the task of accurately estimating outcomes of specific scenarios may find use of the models more problematic.
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