{"query_echo":{"q":"","filters":{"geography":["Argentinean Pampa Region"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'Argentinean Pampa Region' for facet 'geography' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Argentinean+Pampa+Region","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"iai-000045","url":"https://climateinsightsdirectory.org/document/iai-000045","title":"Agricultural impact on soil organic carbon content: testing the IPCC carbon accounting method for evaluations at county scale","publisher":{"name":"Inter-American Institute for Global Change Research","organization":"inter-american-institute-for-global-change-research"},"document_type":"research paper","language":"en","date_published":"2025-01-17","source_url":"https://iai.int/es/pub_acad/agricultural-impact-on-soil-organic-carbon-content-testing-the-ipcc-carbon-accounting-method-for-evaluations-at-county-scale/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study tests the IPCC's carbon accounting methods for soil organic carbon (SOC) in the Argentinean Pampa Region, finding that a developed Tier 2 (T2) method using the RothC model significantly outperforms the Tier 1 (T1) method. While T1 showed poor performance at both sub-region and county scales, the T2 method demonstrated strong accuracy at the sub-region scale (R2 = 0.85) and improved accuracy at the county scale (R2 = 0.73) when excluding the Flooding Pampa region. The T2 method identified the highest average SOC losses in Central Pampa (35%), Southern Pampa – Eastern (28%), and Rolling Pampa (26%).","ai_generated":true,"unit":"iai-000045#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Tier 1 (T1) IPCC carbon accounting method performed poorly at both sub-region and county spatial scales, whereas the developed Tier 2 (T2) method, based on the RothC model, provided a significant improvement in estimation accuracy.","ai_generated":true,"unit":"iai-000045#insight-1","date_modified":"2026-10-23"},{"text":"The T2 method's performance varied by scale: it was very accurate at the sub-region scale (R2 = 0.85), but showed a poorer fit at the county scale (R2 = 0.46). However, excluding the Flooding Pampa sub-region due to poor input and validation data increased the county-scale R2 to 0.73.","ai_generated":true,"unit":"iai-000045#insight-2","date_modified":"2026-10-23"},{"text":"Using the T2 method to estimate land use change impacts, the highest average soil organic carbon (SOC) losses were found in Central Pampa (35%), Southern Pampa – Eastern (28%), and Rolling Pampa (26%).","ai_generated":true,"unit":"iai-000045#insight-3","date_modified":"2026-10-23"}],"climate_tags":["carbon accounting","greenhouse gas emissions","land-use change"],"geography_discussed":["Central Pampa","Southern Pampa – Eastern","Rolling Pampa","Flooding Pampa"],"frame_perspective":[],"analysis_type":["comparative analysis","model validation"]}]}