Item talk:Q243937
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Comparing approaches to spatially explicit ecosystem service modeling: a case study from the San Pedro River, Arizona", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70048482", "url": "https://pubs.usgs.gov/publication/70048482" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70048482 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1016/j.ecoser.2013.07.007", "url": "https://doi.org/10.1016/j.ecoser.2013.07.007" } ], "journal": { "@type": "Periodical", "name": "Ecosystem Services", "volumeNumber": "5", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Ecosystem Services" } ], "datePublished": "2013", "dateModified": "2014-01-14", "abstract": "Although the number of ecosystem service modeling tools has grown in recent years, quantitative comparative studies of these tools have been lacking. In this study, we applied two leading open-source, spatially explicit ecosystem services modeling tools \u2013 Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) \u2013 to the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. We modeled locally important services that both modeling systems could address \u2013 carbon, water, and scenic viewsheds. We then applied managerially relevant scenarios for urban growth and mesquite management to quantify ecosystem service changes. InVEST and ARIES use different modeling approaches and ecosystem services metrics; for carbon, metrics were more similar and results were more easily comparable than for viewsheds or water. However, findings demonstrate similar gains and losses of ecosystem services and conclusions when comparing effects across our scenarios. Results were more closely aligned for landscape-scale urban-growth scenarios and more divergent for a site-scale mesquite-management scenario. 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