Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping

Growing demand of resources increases pressure on ecosystem services (ES) and biodiversity. Monetary valuation of ES is frequently seen as a decision-support tool by providing explicit values for unconsidered, non-market goods and services. Here we present global value transfer functions by using a meta-analytic framework for the synthesis of 194 case studies capturing 839 monetary values of ES. For 12 ES the variance of monetary values could be explained with a subset of 93 study- and site-specific variables by utilizing boosted regression trees. This provides the first global quantification of uncertainties and transferability of monetary valuations. Models explain from 18% (water provision) to 44% (food provision) of variance and provide statistically reliable extrapolations for 70% (water provision) to 91% (food provision) of the terrestrial earth surface. Although the application of different valuation methods is a source of uncertainty, we found evidence that assuming homogeneity of ecosystems is a major error in value transfer function models. Food provision is positively correlated with better life domains and variables indicating positive conditions for human well-being. Water provision and recreation service show that weak ownerships affect valuation of other common goods negatively (e.g. non-privately owned forests). Furthermore, we found support for the shifting baseline hypothesis in valuing climate regulation. Ecological conditions and societal vulnerability determine valuation of extreme event prevention. Valuation of habitat services is negatively correlated with indicators characterizing less favorable areas. Our analysis represents a stepping stone to establish a standardized integration of and reporting on uncertainties for reliable and valid benefit transfer as an important component for decision support.


1
Area Spatial extent of the investigation area applied in the case study for each monetary valued ES.
Square kilometer Site scale to continental 1975-2012 [13, 36] 1 Year Publication year of the case study.
Year Site scale to continental 1975-2012 [13, 36] 1 Beneficiary Indication of population that benefits from enjoyment, consumption or use of valued ES.

Unitless index
Site scale to continental 1975-2012 [13, 36] 2 Provider Type of supplier of ES or landowner of service area that is being valued, e.g. private, Non-Governmental Organization, Non-Profit Organization or government.
Unitless index Local to international 1975Local to international -2012 6 ES sub-services Determined ES sub-classes based on the TEEB classification system. The TEEB categories consist of 27 ES, e.g. food provision or climate regulation, which were sub-divided into 74 sub-classes.
ES sub-types Site scale to continental 1975-2012 [13, 36] 6 Value method Classification of techniques used in the case study to value ES in monetary terms.
Type of method Site scale to continental 1975-2012 [13, 36] 6 Value Type The type of monetary "output" value from the case study, determined by the aggregated value of the ES benefits provided in a given state.
Type of value Site scale to continental 1975-2012 [13, 36] 2 Consumer prices A consumer price index is constructed to measure price changes over time for a fixed set of consumer goods and services of constant quantity and characteristics, acquired, used or paid for by households.

Unitless index National level 2007
International Labour Office database provided by ILO. Retrieved 01/07/2015, from: http://laborsta.ilo.org/applv8/data/c7e.html GDP growth Annual percentage growth rate of Gross Domestic Product (GDP) per capita based on constant local currency. GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy (plus any product taxes and minus any subsidies, not included in the value of the products) measured in purchaser's prices. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Loss due to inequality in education The loss in mean years of schooling due to inequality is the difference between two averages -the arithmetic mean which does not account for inequality and the geometric mean which does. The loss, expressed as a percentage, is the relative difference between the two. Market access Accessibility to markets based on measurements of travel time to cities and major maritime ports as proxies for domestic and international markets. It rather accounts for the infrastructure (roads, rivers) and a number of terrain characteristics (slopes, landcover) that impede access to the markets than for the absolute distance. Furthermore a uniform velocity was used to calculate the total travel time. Fertilizer consumption Is the sum of fertilizer consumption of the following types of nutrients: nitrogen (N), phosphate (P 2 0 5 ), potash (K 2 0) and including complex fertilizers (NP, PK, NK and NPK). Distance to Sea Spatial inequality of the distance to sea across artificial pixels (of 2.5 x 2.5 decimal degrees). As a measure of the distance to sea the geodesic distance from the centroid of each pixel to the nearest coastline is estimated. Gini coefficients are calculated across these pixels for each country. The Environmental performance Index (EPI) describes environmental compatibility of a state's policy concerning to human health affected by ecosystem health and human interventions, such as ecosystem protection and resource management. The EPI focused on a core set of environmental outcomes linked to policy goals.

Unitless index
Conservation area reactive Areas that prioritizing high vulnerability of conservation areas in highly irreplaceable regions. These areas are characterized by a high threat that unique biodiversity will soon be lost unless immediate conservation action is taken within them. The indicator is based on an overlay of different conservation approaches, such as species and habitat diversity, species and habitat rarity, ecological functions at risk etc., in order to see whether certain areas are consistently identified as being of high priority.