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Data Release for The sensitivity of ecosystem service models to choices of input data and spatial resolution

The sensitivity of ecosystem service models to choices of input data and spatial resolution

Dates

Publication Date
Time Period
2017

Citation

Bagstad, K.J., Cohen, Erika, Ancona, Z.H., McNulty, S.G., and Sun, Ge, 2018, Data Release for The sensitivity of ecosystem service models to choices of input data and spatial resolution: U.S. Geological Survey data release, https://doi.org/10.5066/F7CR5S92.

Summary

Although ecosystem service (ES) modeling has progressed rapidly in the last 10-15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study we apply inter- and intra-model comparisons to address these questions at national and provincial scales in Rwanda. We compare results of (1) carbon, annual, and seasonal water yield using InVEST and WASSI models, and the above plus the InVEST sediment regulation model using (2) 30- and 300 m resolution data and (3) three different input land cover datasets. For the inter-model comparison, we found the two models to give diverging [...]

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Attached Files

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Appendix Input Data Tables.zip 6.53 KB
InVEST CCI 2010 300m Data.zip 8.32 MB
InVEST Globeland 300m Data.zip 7.47 MB
InVEST SERVIR 2010 300m Data.zip 7.53 MB
WASSI Data.zip 6.53 MB
InVEST Globeland 2010 30m Data.zip 689.35 MB
Metadata_Sensitivity_Model_Choice_2_26_18.xml
Original FGDC Metadata

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31.38 KB

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Purpose

While ES research has grown substantially in the last 10-15 years, assessments of how data and model choices influence estimates of ES are relatively fewer and newer. This issue is particularly important when ES assessments are conducted in developing countries, which may have limited data availability and modeling expertise. At least four types of data and model variability exist. In the paper, we address the first three of these modeling and data questions using a quantitative example from Rwanda.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/F7CR5S92

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