Landuyt Dries, Lemmens Pieter, D'hondt Rob, Broekx Steven, Liekens Inge, De Bie Tom, Declerck Steven A J, De Meester Luc, Goethals Peter L M
Unit Environmental Modelling-RMA, Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium; Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University, Jozef Plateaustraat 22, B-9000 Ghent, Belgium.
Laboratory of Aquatic Ecology, Evolutionary Biology and Conservation, KU Leuven, Charles Deberiotstraat 32, B-3000 Leuven, Belgium.
J Environ Manage. 2014 Dec 1;145:79-87. doi: 10.1016/j.jenvman.2014.06.015. Epub 2014 Jul 5.
Freshwater ponds deliver a broad range of ecosystem services (ESS). Taking into account this broad range of services to attain cost-effective ESS delivery is an important challenge facing integrated pond management. To assess the strengths and weaknesses of an ESS approach to support decisions in integrated pond management, we applied it on a small case study in Flanders, Belgium. A Bayesian belief network model was developed to assess ESS delivery under three alternative pond management scenarios: intensive fish farming (IFF), extensive fish farming (EFF) and nature conservation management (NCM). A probabilistic cost-benefit analysis was performed that includes both costs associated with pond management practices and benefits associated with ESS delivery. Whether or not a particular ESS is included in the analysis affects the identification of the most preferable management scenario by the model. Assessing the delivery of a more complete set of ecosystem services tends to shift the results away from intensive management to more biodiversity-oriented management scenarios. The proposed methodology illustrates the potential of Bayesian belief networks. BBNs facilitate knowledge integration and their modular nature encourages future model expansion to more encompassing sets of services. Yet, we also illustrate the key weaknesses of such exercises, being that the choice whether or not to include a particular ecosystem service may determine the suggested optimal management practice.
淡水池塘提供广泛的生态系统服务（ESS）。考虑到这些广泛的服务以实现具有成本效益的ESS供给，是综合池塘管理面临的一项重要挑战。为了评估ESS方法在支持综合池塘管理决策方面的优缺点，我们在比利时弗拉芒地区的一个小型案例研究中应用了该方法。开发了一个贝叶斯信念网络模型，以评估在三种替代池塘管理情景下的ESS供给：集约化养鱼（IFF）、粗放式养鱼（EFF）和自然保护管理（NCM）。进行了概率成本效益分析，其中包括与池塘管理实践相关的成本以及与ESS供给相关的效益。分析中是否包含特定的ESS会影响模型对最优选管理情景的识别。评估更完整的生态系统服务供给往往会使结果从集约化管理转向更注重生物多样性的管理情景。所提出的方法说明了贝叶斯信念网络的潜力。贝叶斯信念网络有助于知识整合，其模块化性质鼓励未来将模型扩展到更全面的服务集。然而，我们也说明了此类做法的关键弱点，即是否纳入特定生态系统服务的选择可能会决定建议的最优管理实践。
