Title Date1 WAVES © 2014 Wealth Accounting and the Valuation of Ecosystem Services Biophysical modeling of ecosystem services: Module 2C: Lookup Table Models WAVES Training Module

Title Date2 WAVES © 2014 Lookup table types and methodological tradeoffs

Title Date3 WAVES © 2014 Types of lookup tables 1.Binary lookup tables 2.Qualitative lookup tables 3.Aggregated statistics lookup tables 4.Multiple layer lookup tables 5.Causal relationships 6.Spatial interpolation 7.Environmental regression models Schröter, M., et al. In press. Lessons learned for spatial modeling of ecosystem services in support of ecosystem accounting. Forthcoming in: Ecosystem Services.

Title Date4 WAVES © 2014 Methods for mapping ecosystem services Schröter et al. in press

Title Date5 WAVES © 2014 Dangers of oversimplified lookup tables “…land cover based proxies provide a poor fit to primary data… correlations between ecosystem services change depending on whether primary or proxy data are used for the analysis.” Eigenbrod, F., et al The impact of proxy- based methods on mapping the distribution of ecosystem services. J. Applied Ecology 47:

Title Date6 WAVES © 2014 Types of lookup tables Land coverBinary lookup table (1 = presence, 0 = absence) Qualitative lookup table (expert rankings, 0-5) Aggregated statistics lookup table (T C/ha) Open water000 Deciduous forest Evergreen forest Mixed forest Cultivated crops112.2 Woody wetlands Herbaceous wetlands Hypothetical lookup table for vegetation carbon storage

Title Date7 WAVES © 2014 Types of lookup tables Land cover & rainfallMultiple layer lookup table (T C/ha) Open water0 Deciduous forest – high annual rainfall63.1 Deciduous forest – low annual rainfall52.0 Mixed forest – high annual rainfall50.6 Mixed forest – low annual rainfall45.3 Cultivated crops – high annual rainfall1.6 Cultivated crops – low annual rainfall2.5 Herbaceous wetland – high annual rainfall 7.8 Herbaceous wetland – low annual rainfall 4.2 Hypothetical lookup table for vegetation carbon storage; Requires input GIS data for land cover and rainfall

Title Date8 WAVES © 2014 Land cover typologies: Complexity and lookup tables U.S. GAP Analysis program land cover (82 land cover classes) U.S. National Land Cover Dataset, state of Colorado (16 land cover classes)

Title Date9 WAVES © 2014 Land cover typologies: Complexity and lookup tables Few classes: Potential to oversimplify within-class differences (e.g., between deciduous forest vs. beech-maple forests and oak-hickory forests) OR Many classes: Data may not exist to distinguish between service provision when there are many land cover classes (e.g., closed beech-maple forest on well-drained soils in a cold temperate climate)

Title Date10 WAVES © 2014 Land cover typologies: Complexity and lookup tables NLCD land cover Vegetation carbon Soil carbonWoody debris carbon Open water Deciduous forest Evergreen forest Mixed forest Cultivated crops Woody wetlands Herbaceous wetlands GAP land coverVegetation carbonSoil carbon Rocky Mountain aspen forest & woodland Southern Rocky Mountain pinon-juniper woodland Colorado Plateau pinon- juniper woodland Rocky Mountain ponderosa pine woodland n = 16 classes n = 82 classes

Title Date11 WAVES © 2014 Lookup tables and monetary valuation of ecosystem services

Title Date12 WAVES © 2014 Global studies “For the entire biosphere, the value… is estimated to be in the range of US $16-54 trillion per year… Global gross national product total is around US $18 trillion per year.”

Title Date13 WAVES © 2014 Global studies “the estimate for the total global ecosystem services in 2011 is $125 trillion/yr... Global estimates expressed in monetary accounting units, such as this, are useful to highlight the magnitude of eco-services, but have no specific decision-making context.”

Title Date14 WAVES © 2014 Regional studies “These tabulations show an estimated ESV flow of $2.98 billion for the California sample counties, $22.6 million for Maury Island, and $6.98 billion for Massachusetts.”

Title Date15 WAVES © 2014 Regional studies “The total value of ecosystem services in Shenzhen was million Yuan in 1996, million Yuan in 2000, and million Yuan in 2004 respectively, with a decrease of million Yuan from 1996 to 2004 mainly due to the decreasing areas of woodland, wetland, and water body.” Tianhong et al. (2010)

Title Date16 WAVES © 2014 Service-specific studies “loss of bats in North America could lead to agricultural losses estimated at more than $3.7 billion/year.”

Title Date17 WAVES © 2014 Service-specific studies Solution: design a transfer function to account for spatial context. This is moving toward valuation, and will be covered in more detail elsewhere. (Wiederholt et al. in review)

Title Date18 WAVES © 2014 Problems with using lookup tables for valuation Typically heavily caveated; objective often to “raise awareness” of ES with a “big number” More harm than good if numbers can’t be trusted? See Bockstael et al. 2000, Plummer 2009

Title Date19 WAVES © 2014 Problems with using lookup tables for valuation Overgeneralization of biome types (forest ≠ forest ≠ forest) Beneficiaries ignored (even simple proxies, e.g., population density) Several economic fallacies, especially conflation of marginal & total values See Bockstael et al. 2000, Plummer 2009

Title Date20 WAVES © 2014 Exercise 4: Building lookup table models 1.Your instructor will provide a GIS layer of land cover for your region of interest. 2.In small groups of 3-4, one (or more) group(s) will review an article assigned to your group that includes information that could be used to build a lookup table. Use the information in that article to build the lookup table. 3.A second (or more) group(s) will develop a qualitative (expert opinion-based) lookup table. As a group, you will rank each land cover type from 1-5 based on its ability to generate the service of interest. 4.The instructor will use the “reclassify” or “join” tool in a GIS software to generate an ecosystem service map. 5.All groups present their results to the full group. Discuss the pros and cons of the quantitative vs. expert approach. How replicable were the results - would a decision maker arrive at a different decision by using one map over the other?