ntegrated, dynamic, spatially explicit computer modelling isincreasingly being used as a tool to address the complexity ofinteractions that lead to ecosystem services production

If we are tosucceed at moving beyond the current model of ‘growth at allcosts’ to embrace the idea of a ‘wellbeing economy’, we need a dif-ferent approach to data collection and modelling that is adaptable,evolutionary, and integrated (Fioramonti, 2017a)

e need modelling to synthesize and quantify our understand-ing of ES and to understand dynamic, non-linear, spatially explicittrade-offs as part of the larger social-ecological systems(Fioramonti, 2017b).

ractical applicationsare still limited. Limiting factors include: (1) inconsistentapproaches to ecosystem service modelling, assessment and valu-ation; (2) the expense of applying sophisticated enough methodsto adequately answer the questions; (3) the lack of appropriateinstitutional frameworks; and (4) mistrust or misunderstandingof the science

A few years ago, DowChemical established a $10 million collaboration with The NatureConservatory (TNC) to tally up the ecosystem costs and benefitsof every business decision (Walsh, 2011; Molnar andKubiszewski, 2012). Such collaboration will provide a significantaddition to ecosystem services valuation knowledge andtechniques.Another example is TruCos

Systems of payment for ecosystem services (PES) and commonasset trusts can be effective elements in these institutions (Sattlerand Matzdorf, 2013).

But recognizing the importance of information does not obviatethe limitations of human perception-centered valuation

the anal-ysis shows that the total value of ecosystem services is consider-able and ranges between 490 $/ha/year for the total bundle ofecosystem services that can potentially be provided by an ‘average’hectare of open oceans to almost 350,000 $/ha/year for the poten-tial services of an ‘average’ hectare of coral reefs.

tated preference methods rely on individuals’ responses tohypothetical scenarios involving ecosystem services and includecontingent valuation and structured choice experiments(Fioramonti, 2014). Contingent valuation

Other revealedpreference methods include replacement costs or hedonic or sha-dow pricing, which infer ecosystem service values from closelylinked, parallel markets, like real estate.

hree types of value for ESand NC, based on the three sub-goals for sustainable wellbeing firstarticulated byDaly (1992)as (1) sustainable scale; (2) fair distribu-tion; and (3) efficient allocation. Conventional economic ‘willingness-to-pay” approaches are focused on the third of these goalsusing current individual preferences. But valuation with respectto the fairness and sustainability goals need very differentapproaches that are more in line with community or societalpreferences and whole system sustainability issues

group dimensions on the valuator side and incorpo-rate the dynamics of natural capital and ecosystem services at mul-tiple geographical and temporal scales

identifying and mappingand modeling the properties

Our point is that this perspective is itself an implicit valuation. Itis simply arguing that nature is more valuable than any possiblealternative. While in many cases this may be true, society hasmade decisions that imply it is not always the case (Russell-Smith et al., 2015). Every time we build homes, schools, and hospi-tals, which are essential for human wellbeing, we appropriateecosystems and impact our natural capital. Thus, being more expli-cit about the value of ES and NC can help society make better deci-sions in the many cases in which trade-offs exist

Habitat Servicesor refugia service (as it was called inCostanza, 1997)tohighlight the importance of ecosystems to provide habitatfor migratory species (e.g., as nurseries) and gene-pool ‘‘pro-tectors” (e.g., natural habitats allowing natural selection pro-cesses to maintain the vitality of the gene pool)

Modeling the dynamics of the integrated earth system and the value of global ecosystem services using the GUMBO modelAuthor links open overlay panelRoelofBoumansa1RobertCostanzaa1JoshuaFarleya1