{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/121531"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/121531","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Multi-scale Remote Assessment of Phenology of Photosynthesis and Productivity of Northern Forests","abstract":"Northern trees undergo seasonal regulation of photosynthetic activity in response to environmental conditions. Remote sensing provides a powerful tool to assess photosynthetic phenology at the global scale. However, traditional “greenness” based vegetation indices, like the normalized difference vegetation index (NDVI) which is sensitive to chlorophyll content, are often limited in monitoring the phenology of evergreen conifers due to the retention of green foliage year-round. Therefore, the main goal of my thesis is to evaluate the ability of carotenoid sensitive vegetation indices, photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI), for monitoring the phenology of photosynthesis in evergreen conifers and deciduous trees. This study was conducted at two long-term carbon monitoring forest stands at the Turkey Point Observatory in Ontario, Canada, representing an evergreen forest and a mixed deciduous forest. First, I characterized the energy partitioning of photochemical and photoprotective processes and photosynthetic pigment composition in eastern white pine, red maple and white oak to understand the photosynthetic mechanisms reflected by NDVI, PRI and CCI at the leaf-scale. In deciduous trees, NDVI adequately reflected seasonal variation of photosynthetic activity and pigments. In pine, NDVI was unable to represent phenology. In contrast, PRI and CCI reflected seasonal variation in carotenoid pigments to represent photosynthetic phenology in both deciduous and evergreen trees. I then further evaluated NDVI, PRI and CCI as proxies of photosynthetic parameters at the canopy-scale and validated using leaf-scale measurements. NDVI and PRI were confirmed to be good indicators of the fraction of absorbed photosynthetically active radiation (ƒAPAR) and photosynthetic efficiency (ɛ), respectively. CCI was revealed to be a good indicator of both photosynthesis and ɛ. Finally, I parameterized a light-use efficiency (LUE) model with PRI and CCI as proxies of ɛ and compared model performance with a meteorological-based LUE model and a land surface model. The PRI- and CCI-LUE models demonstrated improved performance for reflecting the timing of phenology of GPP. Together, these results show that PRI and CCI reflect seasonal variation of carotenoid pigments and photoprotection in both evergreen and deciduous trees and are good proxies of photosynthetic activity for parameterizing LUE models to improve the monitoring of photosynthetic phenology.","abstract_html":"Northern trees undergo seasonal regulation of photosynthetic activity in response to environmental conditions. Remote sensing provides a powerful tool to assess photosynthetic phenology at the global scale. However, traditional “greenness” based vegetation indices, like the normalized difference vegetation index (NDVI) which is sensitive to chlorophyll content, are often limited in monitoring the phenology of evergreen conifers due to the retention of green foliage year-round. Therefore, the main goal of my thesis is to evaluate the ability of carotenoid sensitive vegetation indices, photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI), for monitoring the phenology of photosynthesis in evergreen conifers and deciduous trees. This study was conducted at two long-term carbon monitoring forest stands at the Turkey Point Observatory in Ontario, Canada, representing an evergreen forest and a mixed deciduous forest. First, I characterized the energy partitioning of photochemical and photoprotective processes and photosynthetic pigment composition in eastern white pine, red maple and white oak to understand the photosynthetic mechanisms reflected by NDVI, PRI and CCI at the leaf-scale. In deciduous trees, NDVI adequately reflected seasonal variation of photosynthetic activity and pigments. In pine, NDVI was unable to represent phenology. In contrast, PRI and CCI reflected seasonal variation in carotenoid pigments to represent photosynthetic phenology in both deciduous and evergreen trees. I then further evaluated NDVI, PRI and CCI as proxies of photosynthetic parameters at the canopy-scale and validated using leaf-scale measurements. NDVI and PRI were confirmed to be good indicators of the fraction of absorbed photosynthetically active radiation (ƒAPAR) and photosynthetic efficiency (ɛ), respectively. CCI was revealed to be a good indicator of both photosynthesis and ɛ. Finally, I parameterized a light-use efficiency (LUE) model with PRI and CCI as proxies of ɛ and compared model performance with a meteorological-based LUE model and a land surface model. The PRI- and CCI-LUE models demonstrated improved performance for reflecting the timing of phenology of GPP. Together, these results show that PRI and CCI reflect seasonal variation of carotenoid pigments and photoprotection in both evergreen and deciduous trees and are good proxies of photosynthetic activity for parameterizing LUE models to improve the monitoring of photosynthetic phenology.","abstract_has_math":false,"creators":["Wong, Christopher Yet San"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Ecology and Evolutionary Biology","school":null,"contributors":[],"advisors":["Ensminger, Ingo"],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-06","date_published":"2020-06","updated_at":"2026-07-27T21:28:18Z","subjects":["Carotenoids","Chlorophyll fluorescence","Deciduous forest","Evergreen forest","Photosynthesis","Spectral reflectance"],"languages":[],"rights":["Attribution-NonCommercial-NoDerivatives 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/121531","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Ensminger, Ingo"]},{"key":"dc:contributor.department","label":"Department","values":["Ecology and Evolutionary Biology"]},{"key":"dc:creator","label":"Author","values":["Wong, Christopher Yet San"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-06"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-06-22T04:11:30Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-06-22T04:11:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2020-06"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Carotenoids","Chlorophyll fluorescence","Deciduous forest","Evergreen forest","Photosynthesis","Spectral reflectance"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution-NonCommercial-NoDerivatives 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/121531"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Northern trees undergo seasonal regulation of photosynthetic activity in response to environmental conditions. Remote sensing provides a powerful tool to assess photosynthetic phenology at the global scale. However, traditional “greenness” based vegetation indices, like the normalized difference vegetation index (NDVI) which is sensitive to chlorophyll content, are often limited in monitoring the phenology of evergreen conifers due to the retention of green foliage year-round. Therefore, the main goal of my thesis is to evaluate the ability of carotenoid sensitive vegetation indices, photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI), for monitoring the phenology of photosynthesis in evergreen conifers and deciduous trees. This study was conducted at two long-term carbon monitoring forest stands at the Turkey Point Observatory in Ontario, Canada, representing an evergreen forest and a mixed deciduous forest. First, I characterized the energy partitioning of photochemical and photoprotective processes and photosynthetic pigment composition in eastern white pine, red maple and white oak to understand the photosynthetic mechanisms reflected by NDVI, PRI and CCI at the leaf-scale. In deciduous trees, NDVI adequately reflected seasonal variation of photosynthetic activity and pigments. In pine, NDVI was unable to represent phenology. In contrast, PRI and CCI reflected seasonal variation in carotenoid pigments to represent photosynthetic phenology in both deciduous and evergreen trees. I then further evaluated NDVI, PRI and CCI as proxies of photosynthetic parameters at the canopy-scale and validated using leaf-scale measurements. NDVI and PRI were confirmed to be good indicators of the fraction of absorbed photosynthetically active radiation (ƒAPAR) and photosynthetic efficiency (ɛ), respectively. CCI was revealed to be a good indicator of both photosynthesis and ɛ. Finally, I parameterized a light-use efficiency (LUE) model with PRI and CCI as proxies of ɛ and compared model performance with a meteorological-based LUE model and a land surface model. The PRI- and CCI-LUE models demonstrated improved performance for reflecting the timing of phenology of GPP. Together, these results show that PRI and CCI reflect seasonal variation of carotenoid pigments and photoprotection in both evergreen and deciduous trees and are good proxies of photosynthetic activity for parameterizing LUE models to improve the monitoring of photosynthetic phenology."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Multi-scale Remote Assessment of Phenology of Photosynthesis and Productivity of Northern Forests"]}]}],"canonical_facts":{"dc:contributor.advisor":["Ensminger, Ingo"],"dc:contributor.department":["Ecology and Evolutionary Biology"],"dc:creator":["Wong, Christopher Yet San"],"dc:date":["2020-06"],"dc:date.accessioned":["2022-06-22T04:11:30Z"],"dc:date.available":["2022-06-22T04:11:30Z"],"dc:date.issued":["2020-06"],"dc:description.abstract":["Northern trees undergo seasonal regulation of photosynthetic activity in response to environmental conditions. Remote sensing provides a powerful tool to assess photosynthetic phenology at the global scale. However, traditional “greenness” based vegetation indices, like the normalized difference vegetation index (NDVI) which is sensitive to chlorophyll content, are often limited in monitoring the phenology of evergreen conifers due to the retention of green foliage year-round. Therefore, the main goal of my thesis is to evaluate the ability of carotenoid sensitive vegetation indices, photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI), for monitoring the phenology of photosynthesis in evergreen conifers and deciduous trees. This study was conducted at two long-term carbon monitoring forest stands at the Turkey Point Observatory in Ontario, Canada, representing an evergreen forest and a mixed deciduous forest. First, I characterized the energy partitioning of photochemical and photoprotective processes and photosynthetic pigment composition in eastern white pine, red maple and white oak to understand the photosynthetic mechanisms reflected by NDVI, PRI and CCI at the leaf-scale. In deciduous trees, NDVI adequately reflected seasonal variation of photosynthetic activity and pigments. In pine, NDVI was unable to represent phenology. In contrast, PRI and CCI reflected seasonal variation in carotenoid pigments to represent photosynthetic phenology in both deciduous and evergreen trees. I then further evaluated NDVI, PRI and CCI as proxies of photosynthetic parameters at the canopy-scale and validated using leaf-scale measurements. NDVI and PRI were confirmed to be good indicators of the fraction of absorbed photosynthetically active radiation (ƒAPAR) and photosynthetic efficiency (ɛ), respectively. CCI was revealed to be a good indicator of both photosynthesis and ɛ. Finally, I parameterized a light-use efficiency (LUE) model with PRI and CCI as proxies of ɛ and compared model performance with a meteorological-based LUE model and a land surface model. The PRI- and CCI-LUE models demonstrated improved performance for reflecting the timing of phenology of GPP. Together, these results show that PRI and CCI reflect seasonal variation of carotenoid pigments and photoprotection in both evergreen and deciduous trees and are good proxies of photosynthetic activity for parameterizing LUE models to improve the monitoring of photosynthetic phenology."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/121531"],"dc:rights":["Attribution-NonCommercial-NoDerivatives 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:subject":["Carotenoids","Chlorophyll fluorescence","Deciduous forest","Evergreen forest","Photosynthesis","Spectral reflectance"],"dc:title":["Multi-scale Remote Assessment of Phenology of Photosynthesis and Productivity of Northern Forests"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:18Z"}