Steven Broekx

A review of Bayesian belief networks in ecosystem service modelling

A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops. BBNs are increasingly used to analyse, predict and value ecosystem services (ESS).Most BBN applications in ESS modelling target only a single service.Numerous advantages of BBNs in ESS modelling are demonstrated in current applications.Model drawbacks are absence of feedback loops and obligatory variable discretization.Spatially explicit modelling and modelling of ESS bundles are future opportunities.

Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen

A modelling approach is presented that determines the most cost-effective set of reduction measures to reach an in-stream concentration target. The framework is based on the coupling of two models: the hydrological water quality model SWAT and an economic optimization model (Environmental Costing Model, ECM). SWAT is used to determine the relationship between the modelled in-stream concentration at the river basin outlet and the associated emission reduction. The ECM is used to set up marginal abatement cost curves for nutrients and oxygen demanding substances. Results for nitrogen are presented for the Grote Nete river basin in Belgium for the year 2006. Results show that the good status for total nitrogen can be reached in the study area. The most cost-effective measures are more productive dairy cattle, implementing basic measures as defined in the WFD, winter cover crops, improved efficiency of WWTP, enhanced fodder efficiency for pigs, further treatment of industrial waste water and tuned fertilization.

An ecosystem service approach to support integrated pond management: A case study using Bayesian belief networks – Highlighting opportunities and risks

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.

A GIS plug-in for Bayesian belief networks

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty. Spatial heterogeneity of ES delivery requires spatially explicit accounting methods.Limited availability of primary data promotes the use of knowledge-based BBN models.The proposed GIS BBN plug-in offers a standardized approach to model ES delivery.Diverse probabilistic output maps can be produced to support decision making.The preferred type of output map depends mainly on end-user requirements.

Sustainability appraisal tools for soil and groundwater remediation: how is the choice of remediation alternative influenced by different sets of sustainability indicators and tool structures?

The state-of-the-science in sustainability assessment of soil and groundwater remediation is evaluated with the application of four decision support systems (DSSs) to a large-scale brownfield revitalization case study. The DSSs were used to perform sustainability appraisals of four technically feasible remediation alternatives proposed for the site. The first stage of the review compares the scope of each tools sustainability indicators, how these indicators are measured and how the tools differ in terms of standardization and weighting procedures. The second stage of the review compares the outputs from the tools and determines the key factors that result in differing results between tools. The evaluation of indicator sets and tool structures explains why the tools generate differing results. Not all crucial impact areas, as identified by sustainable remediation forums, are thoroughly considered by the tools, particularly with regard to the social and economic aspects of sustainability. Variations in boundary conditions defined between technologies, produce distorted environmental impact results, especially when in-situ and ex-situ technologies are compared. The review draws attention to the need for end users to be aware of which aspects of sustainability are considered, how the aspects are measured and how all aspects are ultimately balanced in the evaluation of potential remediation strategies. Existing tools can be improved by considering different technologies within the same boundary conditions and by expanding indicator sets to include indicators deemed to be relevant by remediation forums.

Nitrogen Source Apportionment for the Catchment, Estuary, and Adjacent Coastal Waters of the River Scheldt

Using the systems approach framework (SAF), a coupled model suite was developed for simulating land-use decision making in response to nutrient abatement costs and water and nutrient fluxes in the hydrological network of the Scheldt River, and nutrient fluxes in the estuary and adjacent coastal sea. The purpose was to assess the efficiency of different long- term water quality improvement measures in current and future climate and societal settings, targeting nitrogen (N) load reduction. The spatial-dynamic model suite consists of two dynamically linked modules: PCRaster is used for the drainage network and is combined with ExtendSim modules for farming decision making and estuarine N dispersal. Model predictions of annual mean flow and total N concentrations compared well with data available for river and estuary (r² ≥ 0.83). Source apportionment was carried out to societal sectors and administrative regions; both households and agriculture are the major sources of N, with the regions of Flanders and Wallonia contributing most. Load reductions by different measures implemented in the model were comparable (~75% remaining after 30 yr), but costs differed greatly. Increasing domestic sewage connectivity was more effective, at comparatively low cost (47% remaining). The two climate scenarios did not lead to major differences in load compared with the business-as-usual scenario (~88% remaining). Thus, this spatially explicit model of water flow and N fluxes in the Scheldt catchment can be used to compare different long-term policy options for N load reduction to river, estuary, and receiving sea in terms of their effectiveness, cost, and optimal location of implementation.

The importance of uncertainties in scenario analyses – A study on future ecosystem service delivery in Flanders

Land use is rapidly changing and is significantly affecting ecosystem service delivery all around the world. The socio-economic context and political choices largely determine land use change. This land use change, driven by socio-economic pressures, will impact diverse elements of the environment including, for example, air quality, soil properties, water infiltration and food and wood production, impacts that can be linked to the provisioning of ecosystem services. To gain more insight into the effects of alternative socio-economic developments on ecosystem service delivery, land use change models are being coupled to ecosystem service delivery models to perform scenario analyses. Although the uncertainty of the results of these kind of scenario analyses are generally far from negligible, studies rarely take them into account. In this study, a cellular automaton land use change model is coupled to Bayesian belief network ecosystem service delivery models to facilitate the study of error propagation in scenario analysis. The proposed approach is applied to model the impact of alternative socio-economic developments on ecosystem service delivery in Flanders, Belgium and to assess the impact of land use allocation uncertainty on the uncertainty associated to future ecosystem service delivery. Results suggest that taking into account uncertainties may have an effect on policy recommendations that come out of the scenario analysis. However, in this study, uncertainties in the applied ecosystem service models were dominant, reducing the importance of accounting for land use allocation uncertainty.

Impact of Perceived Importance of Ecosystem Services and Stated Financial Constraints on Willingness to Pay for Riparian Meadow Restoration in Flanders (Belgium)

The strategic importance of ecosystem service valuation as an operational basis for policy decisions on natural restoration has been increasingly recognized in order to align the provision of ecosystem services with the expectation of human society. The contingent valuation method (CVM) is widely used to quantify various ecosystem services. However, two areas of concern arise: (1) whether people value specific functional ecosystem services and overlook some intrinsic aspects of natural restoration, and (2) whether people understand the temporal dimension of ecosystem services and payment schedules given in the contingent scenarios. Using a peri-urban riparian meadow restoration project in Flanders, Belgium as a case, we explored the impacts of residents’ perceived importance of various ecosystem services and stated financial constraints on their willingness-to-pay for the proposed restoration project employing the CVM. The results indicated that people tended to value all the benefits of riparian ecosystem restoration concurrently, although they accorded different importances to each individual category of ecosystem services. A longer payment scheme can help the respondents to think more about the flow of ecosystem services into future generations. A weak temporal embedding effect can be detected, which might be attributed to respondents’ concern about current financial constraints, rather than financial bindings associated with their income and perceived future financial constraints. This demonstrates the multidimensionality of respondents’ financial concerns in CV. This study sheds light on refining future CV studies, especially with regard to public expectation of ecosystem services and the temporal dimension of ecosystem services and payment schedules.

Integration of the subsurface and the surface sectors for a more holistic approach for sustainable redevelopment of urban brownfields

This paper presents a holistic approach to sustainable urban brownfield redevelopment where specific focus is put on the integration of a multitude of subsurface qualities in the early phases of the urban redevelopment process, i.e. in the initiative and plan phases. Achieving sustainability in brownfield redevelopment projects may be constrained by a failure of engagement between two key expert constituencies: urban planners/designers and subsurface engineers, leading to missed opportunities and unintended outcomes in the plan realisation phase. A more integrated approach delivers greater benefits. Three case studies in the Netherlands, Belgium and Sweden were used to test different sustainability assessment instruments in terms of the possibility for knowledge exchange between the subsurface and the surface sectors and in terms of cooperative learning among experts and stakeholders. Based on the lessons learned from the case studies, a generic decision process framework is suggested that supports holistic decision making. The suggested framework focuses on stakeholder involvement, communication, knowledge exchange and learning and provides an inventory of instruments that can support these processes.

Ecosystem Services and Their Monetary Value

Abstract This chapter introduces the concept of monetary valuation of ecosystem services (ES) and lists the available methods. It discusses what exactly can be valued and the possible use of economic valuation in valuing ecosystem services. Examples of valuation exercises in Belgium are given. We conclude that monetary valuation is promising to value the impact of small changes in ecosystem services on human welfare. The different methods used to value these changes all have advantages and disadvantages. Although some relevant issues concerning the methods themselves remain, the most important issue is to determine how to make practical use of the available data in policy decisions. Guidance is needed on how the data should be used for value transfer.