Anticiper les impacts des changements climatiques sur les écosystèmes terrestres, notamment sur le cycle du carbone, nécessite la compréhension et la quantification du fonctionnement photosynthétique des végétaux et leurs réponses aux contraintes abiotiques. Suivre l’évolution des propriétés spectrales des couverts végétaux par la télédétection permet d’avoir accès à leur fonctionnement à des échelles spatiales et temporelles variées. Plusieurs indicateurs optiques ont été développés afin d’accéder à la structure, la biochimie et le fonctionnement écophysiologique des végétaux. Le PRI (photochemical reflectance index), déterminé à partir de la réflectance mesurée dans des bandes étroites à 531 nm et 570 nm, est un proxy de l’efficacité de la plante à utiliser la lumière (LUE, light use efficiency) et plus particulièrement du cycle des xanthophylles, utilisé par la plante pour dissiper l’énergie lumineuse excédentaire sous forme de chaleur. Cependant son usage à l’échelle du couvert végétal, ou à plus larges échelles temporelles et spatiales, entraine l’implication de nombreuses sources de variabilités qui masquent la sensibilité du PRI au fonctionnement photosynthétique, particulièrement les variations biochimiques et phénologiques. L’objectif de ce travail est de mieux comprendre les facteurs qui jouent sur la variabilité du PRI à l’échelle de la feuille et du couvert, afin de caractériser ses réponses aux variations abiotiques de l’environnement et de démêler la composante phénologique de la composante physiologique du PRI. Des études ont été menées en conditions contrôlées, semi-naturelles et naturelles, sur des jeunes arbres et en forêt adulte, soumis à différentes contraintes abiotiques. L’analyse des courbes de réponse du PRI aux variations de lumière incidente utilisée pour la photosynthèse (PAR, photosynthetically active radiation) permet d’isoler 3 paramètres. Le PARsat, la valeur de PAR pour laquelle le PRI sature, le PRI₀, la valeur du PRI à une intensité lumineuse faible (mesurée) ou nulle (estimée) et le ∆PRI, l’amplitude de variation entre le PRI₀ et la valeur de PRI maximum. En période de végétation, la variabilité du PARsat est principalement contrôlée par la disponibilité en eau pour la plante. La variabilité du PARsat est aussi impactée par la concentration d’ozone atmosphérique. En période de débourrement et de sénescence, la variabilité du contenu en chlorophylle régit la valeur du PARsat. Ce paramètre explique la variabilité physiologique du PRI et varie en fonction du facteur limitant la photosynthèse. La variabilité du PRI₀ a été expliquée par la variabilité du contenu biochimique des feuilles en réponse au cycle saisonnier de la chlorophylle et à sa variabilité en conditions de stress. A l’échelle de la canopée, la variabilité de la structure du couvert s’ajoute à la variabilité biochimique du PRI₀. Le PRI₀, en temps que composante phénologique de la variabilité du PRI, peut être utilisé pour corriger le PRI afin de lui soustraire la variabilité structurale et obtenir un PRIc fortement corrélé à la LUE. A l’échelle de la canopée, il a été montré que le PRI est principalement représentatif de la strate supérieure du couvert. Le ∆PRI n’a montré aucune variation intra et inter-journalière, suggérant que le PRI répond non pas au contenu en xanthophylle des plantes, mais à un ratio maintenu constant. Ces résultats mettent en évidence l’importance d’isoler les différentes sources de variabilité du PRI avant de l’utiliser comme proxy du fonctionnement photosynthétique des écosystèmes terrestres. / Anticipating impacts of climate change on terrestrial ecosystems, particularly on the carbon cycle, requires the understanding and the quantification of the plant photosynthetic functioning and of their responses to abiotic factors. Tracking variations of spectral properties of plants using remote sensing allows the access of plant functioning at various spatial and temporal scales. Several optical indices have been developed to assess plant canopy structure, biochemistry and ecophysiological functioning. The PRI (photochemical reflectance index), determined from reflectances measured in narrow bands at 531 nm and 570 nm, may be used as a proxy of light use efficiency (LUE) at leaf and canopy scales, and more particularly of the xanthophyll cycle used by plants to dissipate the excess light energy as heat. However the use of PRI at the canopy scale and at large temporal and spatial scales faces several difficulties related to the involvement of different sources of variability that blur PRI sensitivity to photosynthetic functioning. These sources of PRI variability are particularly linked to spatial and temporal variations of biochemical and phenological canopy properties. The aim of these studies is to better understand the factors affecting PRI variability at leaf and canopy scales, to assess the strength of the relationships between PRI and vegetation responses to environmental abiotic constraints and disentangling the phenological component from the physiological component of PRI. Studies were conducted under controlled, semi-natural and natural conditions, on young trees and a mature deciduous forest subjected to various abiotic constraints. The analysis of PRI responses to the variations of photosynthetically active radiation (PAR) allowed isolating three parameters. The PARsat, the PAR value at the PRI saturation; the PRI₀, the value of PRI at dim light (measured) or in darkness (estimated) and the ΔPRI, the range of PRI variations between the PRI₀ and the maximum value of PRI. During the leaf growing season, PARsat variability is mainly controlled by the availability of water content for the plant. The PARsat variability is also impacted by the atmospheric ozone concentration. During the phenological phases of budburst and the senescence, the variability of the leaf chlorophyll content governs PARsat values. This parameter describes the physiological variability of PRI and varies depending on the limiting factor for photosynthesis. The PRI₀ variability has been explained by the dynamic of the biochemical content of the leaves linked to the seasonal variations of chlorophyll content and to abiotic stress conditions. At canopy scale, the structural variability is added to the biochemical variability of PRI₀. The PRI₀, as the phenological component of PRI variability, can be used to correct PRI, removing its structural variability to obtain a PRIc strongly correlated to LUE. At canopy scale, it was shown that the PRI is mostly representative of the upper layer of the canopy. The ΔPRI showed no variation within and between days, suggesting that the PRI does not respond to the plant xanthophyll content but rather to a ratio maintained constant. These results highlight the importance of isolating the different sources of PRI variability before its use as a proxy of the photosynthetic functioning of terrestrial ecosystems.

L’anticipation des effets des changements climatiques nécessite une bonne compréhension dufonctionnement carboné des écosystèmes continentaux. L’une des principales contraintes liées àl’étude de ces écosystèmes est la forte variabilité à la fois spatiale et temporelle de leurs flux decarbone et de leurs réponses aux contraintes abiotiques. L’usage de méthodes de télédétectionoptiques pourrait permettre de suivre de façon spatialisée le fonctionnement des couverts végétaux.Ce travail vise à évaluer le potentiel de méthodes de télédétection pour décrire la structure et lefonctionnement de couverts végétaux à des échelles spatiales et temporelles variées. Pour ce faire,les relations entre indices optiques et phénomènes biologiques ont été étudiées en suivant unedémarche de transfert d’échelle, des échelles les plus fines aux plus larges. Il a été montré que le PRI(Photochemical Reflectance Index), utilisé en tant qu’indicateur du LUE (Light Use Efficiency), est parnature un signal composite qui reflète principalement la régulation du rendement de laphotosynthèse sur des échelles de temps fines, et la structure et composition biochimique ducouvert à l’échelle de la saison. L’analyse de courbes de réponse du PRI au PAR (PhotosyntheticallyActive Radiation) a permis de déconvoluer ces deux sources de variabilité, via l’introduction duconcept de PRI0 ou PRI d’une feuille idéalement adaptée à l’obscurité. Ce PRI0, capturant la variabilitédu PRI indépendante du LUE, a pu être mesuré à l’échelle de la feuille, et estimé à l’échelle de jeunescouverts végétaux et de la parcelle. Cette variabilité a pu être expliquée à l’échelle de la feuille et dejeunes couverts végétaux par les variations du contenu en pigment des feuilles. A l’échelle depeuplements adultes et de l’année, elle résulte cependant d’effets combinés de la compositionbiochimique et de la structure des couverts qui n’ont pu être séparés. Ces effets sont susceptiblesaux échelles larges de masquer en bonne partie, voire de biaiser la relation entre PRI et LUE. Il a enoutre été montré que la représentativité du PRI est limitée aux strates supérieures des canopées etdépend de la structure du couvert et du climat lumineux, ce qui peut limiter son intérêt en tantqu’estimateur du LUE à l’échelle de l’écosystème. Ces résultats soulignent la nécessité de prendre encompte la structure et la composition biochimique des couverts végétaux dans le cadre d’uneutilisation du PRI en tant que proxy du LUE de l’écosystème. / In order to assess the effect of global warming, a good understanding of carbon functioning ofterrestrial ecosystems is needed. The study of terrestrial ecosystem carbon fluxes and responses toabiotic stress remain challenging due to their high spatial and temporal variability. The use of remotesensing may help us to describe those sources of variability. The aim of this work is to assess thepotential of remote sensing as a way to describe canopy structure and functioning over a broadrange of temporal and spatial scales. The relationships between optical indices and biologicalphenomenon were investigated over a range of increasing scales. The PRI (PhotochemicalReflectance Index), used as a proxy of the LUE (Light Use Efficiency) was shown to be a compositesignal, mainly impacted by the regulation of the LUE at short time scales, and by canopy structureand pigment content at seasonal scale. The analysis of PRI response to PAR (PhotosyntheticallyActive Radiation) allowed us to deconvolve those two sources of variability thanks to theintroduction of the PRI0 defined as the PRI of ideally dark adapted leaves. The PRI0 was shown toefficiently describe the LUE unrelated PRI variability, and could be measured at leaf scale, andestimated at the leaf, canopy and stand scales. This variability could be explained by changes in leafpigment content over the growing season at leaf and canopy scales. At the stand scale and over theyear, this LUE independent PRI variability resulted from combined effects of canopy structure andpigment content, which could not be separated. These effects may result in biased or masked PRIversus LUE relationships at larges scales. Moreover, it was shown that the in-situ PRI measurementsmainly responded to the LUE of sunlit leaves, depending on canopy structure and sky conditions. Thismay considerably hamper the use of the PRI as a proxy of the whole ecosystem LUE. These resultsillustrate the need to take canopy structure and pigment content into account while using the PRI asa proxy of the ecosystem LUE.

There are considerable expenditures by government and private forest industry to enhance the growth of forests and reduce time required for crop rotation. The effectiveness of some of these treatments is dependent on site productivity. In addition, as responsible stewards of the forest resource and habitat, it is important that the state of forests are actively monitored, especially in the face of a changing climate and increased rates of disturbance. This dissertation reports on the development of a method for estimating and mapping forest productivity. The Shawnigan Lake thinning and fertilization forest installation, established in 1971 by CFS, was selected as the study site largely for its rich mensuration history. Square treatment plots were 0.04ha in area and included two thinning levels (1/3 & 2/3 of the basal area), two fertilization treatments (224kg & 448kg N/ha) with repeated fertilizations and macronutrient experiments (S, P) and control plots. A sample of plots was selected for high precision ground based lidar reference surveys. In September of 2012 a multi-sensor airborne survey of SLP was conducted that collected high-density lidar (up to ~70pnts/m2) and VNIR imaging spectroscopy. A thorough empirical radiometric calibration was conducted in addition to a spatial calibration at the Victoria International Airport. A combination of area based height percentile, point density ratios and statistical moments with individual lidar tree metrics including height distribution and proximity metrics were generated. Topographic metrics were also generated from the lidar ground classified point cloud. A library of spectral indices was computed from the imaging spectrometer data, with an emphasis on those indices known to be associated with vegetation health. These metrics were summarized to the plot level for a coarse scale regression analysis. A control survey and ground based lidar was used to facilitate an individual tree based fine scale of analysis, where reference data could unambiguously be matched to airborne collected data through the projected positions. Regression analysis was conducted applying the best subset regression with exhaustive feature selection search criteria and included a critical evaluation of the resulting selected features. Models were investigated considering the data source and in combination, that is, lidar metrics were considered independent of spectroscopy as well as the converse, and lidar metrics in combination with spectral metrics. The contribution of this study is the revelation that existing area based point cloud metrics are highly correlated, potentially noisy and sensitive to variations in point density, resulting in unstable feature selection and coefficients in model building. The approach offered as an alternative is the gridded lidar treetops method, which is evidently lacking within the literature and which this study overwhelmingly advocates. Additionally, the breadth and diversity of metrics assessed, the size and quality of the reference data applied, and the fine spatial scale of analysis are unique within the research area. This study also contributes to the knowledge base, in that, productivity can be estimated by remote sensing technologies. The use of gridded generalizations of the individual tree approach reduced estimation errors for both structural and productivity attributes. At the plot-level, crown structure and crown health features best estimated productivity. This study emphasizes the dangers of empirical modeling; at the even-aged SLP installation, growth is strongly tied to structure and the extrapolation to other sites is expected to provide biased values. It is my perspective that physical lidar structural models of the dominant and co-dominant crown classes be used to augment spatially explicit tree and stand growth models. In addition, direct measures should be obtained by multi-temporal lidar surveys or as an alternative photogrammetric point clouds after an initial lidar survey to quantify growth and aid in calibrating growth models. / Graduate

Northern Canadian peatlands contain vast deposits of carbon. It is with growing urgency that we seek a better understanding of their assimilative capacity. Assimilative capacity and peat accumulation in raised bogs are linked to primary productivity of resident Sphagnum species. Understanding moisture-mediated photosynthesis of Sphagnum spp. is central to understanding peat production rates. The relationship between depth to water table fluctuation and spectral reflectance of Sphagnum moss was investigated using multispectral imaging at a recovering raised bog on the southwest coast of British Columbia, Canada. Burns Bog is a temperate oceanic ombrotrophic bog. Three ecohydrological indicator species of moss were chosen for monitoring: S. capillifolium, S. papillosum, and S. cuspidatum. Three spectral vegetation indices (SVIs) were used to characterize Sphagnum productivity: the normalized difference vegetation index 660, the chlorophyll index, and the photochemical reflectance index. In terms of spectral sensitivity and the appropriateness of SVIs to species and field setting, we found better performance for the normalized difference vegetation index 660 in the discrimination of moisture mediated species-specific reflectance signals. The role that spatiotemporal scale and spectral mixing can have on reflectance signal fidelity was tested. We were specifically interested in the relationship between changes in the local water table and Sphagnum reflectance response, and whether shifting between close spatial scales can affect the statistical strength of this relationship. We found a loss of statistical significance when shifting from the species-specific cm2 scale to the spectrally mixed dm2 scale. This spatiospectral uncoupling of the moisture mediated reflectance signal has implications for the accuracy and reliability of upscaling from plot based measurements. In terms of species-specific moisture mediated reflectance signals, we were able to effectively discriminate between the three indicator species of Sphagnum along the hummock-to-hollow gradient. We were also able to confirm Sphagnum productivity and growth outside of the vascular growing season, establishing clear patterns of reflectance correlated with changes in the local moisture regime. The strongest relationships for moisture mediated Sphagnum productivity were found in the hummock forming species S. capillifolium. Each indicator Sphagnum spp. of peat has distinct functional traits adapted to its preferred position along the ecohydrological gradient. We also discovered moisture mediated and species-specific reflectance phenologies. These phenospectral characteristics of Sphagnum can inform future monitoring work, including the creation of a regionally specific phenospectral library. It’s recommended that further close scale multispectral monitoring be carried out incorporating more species of moss, as well as invasive and upland species of concern. Pervasive vascular reflectance bias in remote sensing products has implications for the reliability of peatland modelling. Avoiding vascular bias, targeted spectral monitoring of Sphagnum indicator species provides a more reliable measure for the modelling of peatland productivity and carbon assimilation estimates. / Graduate