[{"key":"dc.contributor.author","value":"Sun, Jiejie","language":null},{"key":"dc.date.accessioned","value":"2026-04-16T16:26:32Z","language":null},{"key":"dc.date.available","value":"2026-04-16T16:26:32Z","language":null},{"key":"dc.date.issued","value":"2026","language":"en"},{"key":"dc.identifier.uri","value":"http:\/\/hdl.handle.net\/2429\/94115","language":null},{"key":"dc.description.abstract","value":"Greenhouse CO\u2082 enrichment has been widely applied in commercial production and investigated in numerous experiments worldwide, yet findings vary across dispersed studies, and its yield benefits have not been systematically quantified and interpreted at the global scale. This dissertation quantifies the greenhouse CO\u2082 fertilization effect, explains variation across crop functional types and harvested organs, and identifies where CO\u2082 enrichment is most effective under current and future climates. In Chapter 2, I compiled a global dataset of greenhouse experiments (454 observations from 147 studies) and applied meta-analysis using log response ratios (lnRR) to estimate yield gains and benchmark greenhouse CO\u2082 enrichment against Free-Air CO\u2082 Enrichment (FACE). Across comparable CO\u2082 increments of 115\u2013300 ppm (ppm, parts per million by volume (\u03bcmol mol\u207b\u00b9)), greenhouse CO\u2082 enrichment increases yields by ~28% on average and delivers ~1.4 times larger response than FACE. Dose-response analyses suggest that yield gains peak at CO\u2082 concentration increment of 800\u20131,200 ppm. Chapter 3 identifies differences in responses among crops with harvestable organs, showing that below-ground crops (roots and tubers) exhibit roughly double the yield response of above-ground crops, which may be attributed to stronger sink capacity and carbon storage of below-ground crops. In Chapter 4, I evaluate climatic and soil controls on enrichment performance and train Random Forest models (R\u00b2 around 0.7) using CMIP6 GCM ensemble to map global suitability and project changes under SSP126 and SSP585. The maps suggest a poleward shift in suitability for greenhouse CO\u2082 enrichment under future scenarios. Overall, this thesis integrates meta-analysis, greenhouse\u2013FACE benchmarking, yield-CO\u2082 response surfaces, and machine-learning suitability mapping to provide evidence-based guidance for climate-smart greenhouse CO\u2082 enrichment under ongoing climate change.","language":"en"},{"key":"dc.language.iso","value":"eng","language":"en"},{"key":"dc.publisher","value":"University of British Columbia","language":"en"},{"key":"dc.rights","value":"Attribution-NonCommercial-NoDerivatives 4.0 International","language":"*"},{"key":"dc.rights.uri","value":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/","language":"*"},{"key":"dc.title","value":"Quantifying global crop yield responses to greenhouse CO\u2082 enrichment : synthesis, optimization, and climate resilience","language":"en"},{"key":"dc.type","value":"Text","language":"en"},{"key":"dc.degree.name","value":"Doctor of Philosophy - PhD","language":"en"},{"key":"dc.degree.discipline","value":"Forestry","language":"en"},{"key":"dc.degree.grantor","value":"University of British Columbia","language":"en"},{"key":"dc.contributor.supervisor","value":"Wang, Tongli (Forest geneticist)","language":null},{"key":"dc.date.graduation","value":"2026-05","language":"en"},{"key":"dc.type.text","value":"Thesis\/Dissertation","language":"en"},{"key":"dc.description.affiliation","value":"Forestry & Environmental Stewardship, Faculty of","language":"en"},{"key":"dc.degree.campus","value":"UBCV","language":"en"},{"key":"dc.description.scholarlevel","value":"Graduate","language":"en"}]