9b. Future challenges
As pointed out in section 5.4, ecosystem services are produced by a complex and intertwined, difficult to delineate and open system which we call the ecosystem. Although large amounts of empirical data on parts of this system are available, and many of these data have been synthesized in models with varying degrees of applicability and confidence, these results are scattered and integration is essential. This is also the case for estuaries. TIDE has brought together experts, datasets and know-how on four estuaries.
The first task at hand is centralization and linking of this knowledge. Automatically, data gaps will be determined and scientific debates will emerge. These should be used as a guideline to generate hypotheses and perform research to tackle these uncertainties.
Second, functional production models have to be constructed per ecosystem service. This requires integration of coupled existing models and empirical relationships per ES, complemented with scientific expertise to obtain a functional production model per ES. When constructing these production models, the focus will be on intermediate services.
Third, probabilities for all model relationships have to be determined: for empirical data confidence intervals can be used, while for expert data accordance and amount of expert evidence can be assessed. This process is necessary to determine final probabilities of estimates for each service production.
Fourth, ES production models have to be merged. This allows capturing first level trade-offs, determination of tipping points for delivery of (parts of) the ES bundle, and determine the impact of pressures exerted by use/harvest of services.
Last, but by far not least, these results have to be translated in clear estimate of ES production differences
(including the ranges) between given situations or scenarios
. This is essential input for valuation and fully informed decision making.
There is a fundamental difference when a service is expressed in different units. For instance, flood water storage as a storage volume will be very similar throughout the estuary, but the effect
(or the benefit) on flood protection depends on other factors like the local (storm flood) volume of water in the estuary: a same area can have a large benefit upstream, but a very small one at the mouth where the estuarine volume is larger. The same holds for nutrient removal, as a marsh could remove the same amount of nitrogen per hectare upstream or downstream, but the local concentration and load of nitrogen in the estuary will differ, hence the final amount removed. A ‘distance to target’ indicator would be needed for all ES. Moreover, the demand (e.g. number of properties where a flood risk is present) also varies spatially. These spatial relationships are essential to take into account, and the choice of parameters is important in determining the outcomes.
The central idea is that the risk of exceeding local thresholds (water quality, water levels,…) can be reduced as well as realization benefits (reduction of loads, flood protection,…) further down- or upstream or for the estuary in general.
Ecosystem services have to be valued in order to make choices. This value or importance is not easy to determine. As Maris and Bechet (2010) point out, values are contextual, relative to a certain place, a certain time, and a certain group of people is facing a problem and is engaged in collective action. As Costanza (2000) puts it: ‘we humans have to make choices and trade-offs concerning ES and this implies and requires valuation, because any choice between competing alternatives implies that the one chosen was more highly valued.
The use of the economic valuation of ES is well recognized but many ecosystem services are absent from a real market and thus require a non-market valuation: assessing values in the absence of an actual market. One approach is demand-oriented, by measuring the level of willingness-to-pay (e.g., contingent valuation). The other approach is supply/cost-oriented. Third, the embodied energy approach measures energy used directly and indirectly to value ecosystem services. According to Costanza and Folke (1997), the valuation of ecosystem services occurs in three ways: ecological sustainability (S-value), economic efficiency (E-value) and social fairness (F-value). Dendoncker et al (2013) therefore propose a three pillar valuation framework. Valuation can be seen has the final step before decision making: It translates the consequences of maintaining the status quo and opting for each alternative into comparable units of impact on human well-being, now and in the future. it consists of efficiency, sustainability and equity.
Economic valuation uses a broad range of techniques to evaluate efficiency of scenarios. Valuation thus targets changes
in supply of ES, which can be compared between scenarios in order to choose the more efficient one. This comparison occurs on two levels: costs and benefits. Both can be compared “as is” (e.g. number of people protected from flooding, area of marshes with high biodiversity) or translated in monetary terms. This monetary approach is often very eye-opening, but it has to be applied with care and involves many uncertainties.
Adopting a strictly benefit-oriented approach risks an over-concentration on changes in benefits which places underlying ecological assets at risk (Turner, 1999), thereby risking over-exploitation and system change or collapse (e.g. focusing on the fish only and neglect functions as water quality, breeding areas etc. leads to the overexploitation as we know today, Liekens et al 2013). This has to be guarded against by imposing the constraint that ecosystem assets are not run down to unsustainable levels and by valuing bundles of ecosystem services rather than a single service (TEEB, 2010).
Also, the quantification of the risk to reach tipping points is an essential challenge. As Risk = Chance * Damage
, this involves both probabilities derived from research described in section 6.4.1 as valuation of the eventually occurring losses. This gives a pragmatic and measurable interpretation to the intuitive and theoretical concept of carrying capacity and resilience which are key in reaching a sustainable management.
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