Diurnal and Seasonal Variations in Chlorophyll Fluorescence Associated with Photosynthesis at Leaf and Canopy Scales

There is a critical need for sensitive remote sensing approaches to monitor the parameters governing photosynthesis, at the temporal scales relevant to their natural dynamics. The photochemical reflectance index (PRI) and chlorophyll fluorescence (F) offer a strong potential for monitoring photosynthesis at local, regional, and global scales, however the relationships between photosynthesis and solar induced F (SIF) on diurnal and seasonal scales are not fully understood. This study examines how the fine spatial and temporal scale SIF observations relate to leaf level chlorophyll fluorescence metrics (i.e., PSII yield, YII and electron transport rate, ETR), canopy gross primary productivity (GPP), and PRI. The results contribute to enhancing the understanding of how SIF can be used to monitor canopy photosynthesis. This effort captured the seasonal and diurnal variation in GPP, reflectance, F, and SIF in the O2A (SIFA) and O2B (SIFB) atmospheric bands for corn (Zea mays L.) at a study site in Greenbelt, MD. Positive linear relationships of SIF to canopy GPP and to leaf ETR were documented, corroborating published reports. Our findings demonstrate that canopy SIF metrics are able to capture the dynamics in photosynthesis at both leaf and canopy levels, and show that the relationship between GPP and SIF metrics differs depending on the light conditions (i.e., above or below saturation level for photosynthesis). The sum of SIFA and SIFB (SIFA+B), as well as the SIFA+B yield, captured the dynamics in GPP and light use efficiency, suggesting the importance of including SIFB in monitoring photosynthetic function. Further efforts are required to determine if these findings will scale successfully to airborne and satellite levels, and to document the effects of data uncertainties on the scaling

Remote sensing of red and far-red sun-induced chlorophyll fluorescence to estimate gross primary productivity and plant stress in sugar beet

Ohne den Prozess der Photosynthese wäre das Leben auf der Erde, so wie wir es kennen, nicht möglich. Die Quantifizierung des Photosynthese-Prozesses und die Darstellung seiner räumlichen und zeitlichen Adaptierung ist eine der zentralen Herausforderungen in der terrestrischen Umweltforschung. Von Pflanzen absorbiertes Licht kann für den Photosynthese Prozess genutzt, oder aber auch in Form von Wärme (nichtphotochemisches Quenching, NPQ) oder als Fluoreszenz abgegeben werden. Jüngste Fortschritte in der Sensorentechnik ermöglichen es nun, die von der Vegetation emittierte, sonneninduzierte Chlorophyll Fluoreszenz (F) mit Fernerkundungsmethoden zu erfassen. Aufgrund der direkten physikalischen Verbindung zwischen Fluoreszenz und Photosynthese eröffnen sich dadurch neue Möglichkeiten, die Photosynthese-Leistung (normalerweise beschrieben als brutto Primärproduktion, GPP) räumlich und zeitlich zu quantifizieren und Pflanzenstress zu bestimmen. In dieser Dissertation wurden neuartigen boden- (SIF-Sys) und flugzeuggestützte (HyPlant) gestützten Messsysteme genutzt, um die zeitlichen und räumlichen Beziehungen zwischen F, dem photochemischen Reflexionsindex (PRI – als Indikator für NPQ) und der Lichtnutzungseffizienz (LUE) unter wechselnden Umweltbedingungen zu analysieren. Dabei hat sich gezeigt, dass die Kombination aus roter und fern-roter Fluoreszenz Effizienz (F687yield und F760yield) und dem PRI 65% der täglichen und 89% der saisonalen Variabilität der LUE von Zuckerrübe erklärt. Zusätzlich wurden flugzeuggestützte Messungen genutzt, um die räumliche und zeitliche Variabilität von F760yield, F680yield, dem Verhältnis zwischen roter und fern-roter Fluoreszenz (Fratio) und dem sogenannten verbesserten Vegetationsindex (EVI) innerhalb eines Flugstreifens und eines Tages zu bestimmen. Die Ergebnisse zeigen in Abhängigkeit zur Wasserverfügbarkeit eine hohe Variabilität von F760yield und Fratio im Laufe eines Tages und hinsichtlich der Feldfruchtart. Dies deutet darauf hin, dass Fluoreszenz-Produkte sensitiv auf Pflanzenstress reagieren. Die oben beschriebenen Ergebnisse wurden genutzt, um ein empirisches GPP Modell zu entwickeln, das auf F760yield, F687yield und PRI basiert. Die Ergebnisse wurden anschließend mit GPP-Werten, die aus Eddy Kovarianz Messungen (GPPEC) abgeleitet wurden, validiert und mit den Ergebnissen dreier derzeitig genutzten Modellen verglichen, die auf Fluoreszenz und Reflexion basieren. Die Ergebnisse zeigen, dass das neuentwickelte Modell, welches auf Fyield und PRI Informationen basiert, die Tages- und saisonale Variabilität von GPP am besten bestimmt. Die Anwendung der Modelle auf räumlich aufgelöste Daten zeigt, dass generell fluoreszenzbasierte Modelle die räumliche Variabilität von GPP besser erfassen als das Modell, welches allein auf Reflexionsindizes basiert. Abschließend wird der Entwurf für ein Modell vorgeschlagen, welches, basierend auf der photosynthetischen Energiebilanz, den PRI und die absolute Fluoreszenz (Ftot) nutzt, um GPP in einer stärkeren prozessorientierten weise zu bestimmen. Zusammengefasst stellt diese Arbeit heraus, dass sonneninduzierte Fluoreszenz die Abschätzung von GPP verbessert, wobei insbesondere die Kombination aus F und PRI die vielversprechendsten Ergebnisse liefert. Zusätzlich wird gezeigt, dass das Verhältnis von roter zu fern-roter Fluoreszenz sowie Fyield ein großes Potenzial haben, um stressbedingte raum-zeitlichen Pflanzenanpassungsstrategien abzubilden

Do daily and seasonal trends in leaf solar induced fluorescence reflect changes in photosynthesis, growth or light exposure?

Solar induced chlorophyll fluorescence (SIF) emissions of photosynthetically active plants retrieved from space-borne observations have been used to improve models of global primary productivity. However, the relationship between SIF and photosynthesis in diurnal and seasonal cycles is still not fully understood, especially at large spatial scales, where direct measurements of photosynthesis are unfeasible. Motivated by up-scaling potential, this study examined the diurnal and seasonal relationship between SIF and photosynthetic parameters measured at the level of individual leaves. We monitored SIF in two plant species, avocado (Persea Americana) and orange jasmine (Murraya paniculatta), throughout 18 diurnal cycles during the Southern Hemisphere spring, summer and autumn, and compared them with simultaneous measurements of photosynthetic yields, and leaf and global irradiances. Results showed that at seasonal time scales SIF is principally correlated with changes in leaf irradiance, electron transport rates (ETR) and constitutive heat dissipation (YNO; p \u3c 0.001). Multiple regression models of correlations between photosynthetic parameters and SIF at diurnal time scales identified leaf irradiance as the principle predictor of SIF (p \u3c 0.001). Previous studies have identified correlations between photosynthetic yields, ETR and SIF at larger spatial scales, where heterogeneous canopy architecture and landscape spatial patterns influence the spectral and photosynthetic measurements. Although this study found a significant correlation between leaf-measured YNO and SIF, future dedicated up-scaling experiments are required to elucidate if these observations are also found at larger spatial scales

Progress in Remote Sensing of Photosynthetic Activity over the Amazon Basin

Although quantifying the massive exchange of carbon that takes place over the Amazon Basin remains a challenge, progress is being made as the remote sensing community moves from using traditional, reflectance-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to the more functional Photochemical Reflectance Index (PRI). This new index, together with satellite-derived estimates of canopy light interception and Sun-Induced Fluorescence (SIF), provide improved estimates of Gross Primary Production (GPP). This paper traces the development of these new approaches, compares the results of their analyses from multiple years of data acquired across the Amazon Basin and suggests further improvements in instrument design, data acquisition and processing. We demonstrated that our estimates of PRI are in generally good agreement with eddy-flux tower measurements of photosynthetic light use efficiency (epsilon) at four sites in the Amazon Basin: r(exp 2) values ranged from 0.37 to 0.51 for northern flux sites and to 0.78for southern flux sites. This is a significant advance over previous approaches seeking to establish a link between global-scale photosynthetic activity and remotely-sensed data. When combined with measurements of Sun-Induced Fluorescence (SIF), PRI provides realistic estimates of seasonal variation in photosynthesis over the Amazon that relate well to the wet and dry seasons. We anticipate that our findings will steer the development of improved approaches to estimate photosynthetic activity over the tropics

Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis

Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis. A lawn carpet was sprayed with different doses of the herbicide Dicuran. Canopy-level measurements of gross primary productivity indicated dosage-dependent inhibition of photosynthesis by the herbicide. Dosage-dependent changes in normalized F were also detected. After spraying, we first observed a rapid increase in normalized F and in the Photochemical Reflectance Index, possibly due to the blockage of electron transport by Dicuran and the resultant impairment of xanthophyll-mediated non-photochemical quenching. This initial increase was followed by a gradual decrease in both signals, which coincided with a decline in pigment-related reflectance indices. In parallel, we also detected a canopy temperature increase after the treatment. These results demonstrate the potential of using F coupled with relevant reflectance indices to estimate stress-induced changes in canopy photosynthesis

Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.Peer reviewe

Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence

Quantifying global photosynthesis remains a challenge due to a lack of accurate remote sensing proxies. Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of photosynthetic activity across various spatial scales. However, a global and spatially challenging estimate of terrestrial gross primary production (GPP) based on satellite SIF remains unresolved due to the confounding effects of species-specific physical and physiological traits and external factors, such as canopy structure or photosynthetic pathway (C-3 or C-4). Here we analyze an ensemble of far-red SIF data from OCO-2 satellite and ground observations at multiple sites, using the spectral invariant theory to reduce the effects of canopy structure and to retrieve a structure-corrected total canopy SIF emission (SIFtotal). We find that the relationships between observed canopy-leaving SIF and ecosystem GPP vary significantly among biomes. In contrast, the relationships between SIFtotal and GPP converge around two unique models, one for C-3 and one for C-4 plants. We show that the two single empirical models can be used to globally scale satellite SIF observations to terrestrial GPP. We obtain an independent estimate of global terrestrial GPP of 129.56 +/- 6.54 PgC/year for the 2015-2017 period, which is consistent with the state-of-the-art data- and process-oriented models. The new GPP product shows improved sensitivity to previously undetected 'hotspots' of productivity, being able to resolve the double-peak in GPP due to rotational cropping systems. We suggest that the direct scheme to estimate GPP presented here, which is based on satellite SIF, may open up new possibilities to resolve the dynamics of global terrestrial GPP across space and time.Peer reviewe

근접 표면 원격 센싱 시스템들을 이용한 지속적 식물 계절 및 태양 유도 엽록소 형광물질 관측

학위논문(박사) -- 서울대학교대학원 : 환경대학원 협동과정 조경학, 2022.2. 류영렬.Monitoring phenology, physiological and structural changes in vegetation is essential to understand feedbacks of vegetation between terrestrial ecosystems and the atmosphere by influencing the albedo, carbon flux, water flux and energy. To this end, normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) from satellite remote sensing have been widely used. However, there are still limitations in satellite remote sensing as 1) satellite imagery could not capture fine-scale spatial resolution of SIF signals, 2) satellite products are strongly influenced by condition of the atmosphere (e.g. clouds), thus it is challenging to know physiological and structural changes in vegetation on cloudy days and 3) satellite imagery captured a mixed signal from over- and understory, thus it is difficult to study the difference between overstory and understory phenology separately. Therefore, in order to more accurately understand the signals observed from the satellite, further studies using near-surface remote sensing system to collect ground-based observed data are needed. The main purpose of this dissertation is continuous observation of vegetation phenology and SIF using near-surface remote sensing system. To achieve the main goal, I set three chapters as 1) developing low-cost filter-based near-surface remote sensing system to monitor SIF continuously, 2) monitoring SIF in a temperate evergreen needleleaf forest continuously, and 3) understanding the relationships between phenology from in-situ multi-layer canopies and satellite products. In Chapter 2, I developed the filter-based smart surface sensing system (4S-SIF) to overcome the technical challenges of monitoring SIF in the field as well as to decrease sensor cost for more comprehensive spatial sampling. I verified the satisfactory spectral performance of the bandpass filters and confirmed that digital numbers (DN) from 4S-SIF exhibited linear relationships with the DN from the hyperspectral spectroradiometer in each band (R2 > 0.99). In addition, we confirmed that 4S-SIF shows relatively low variation of dark current value at various temperatures. Furthermore, the SIF signal from 4S-SIF represents a strong linear relationship with QEpro-SIF either changing the physiological mechanisms of the plant using DCMU (3-(3, 4-dichlorophenyl)-1, 1-dimethyurea) treatment. I believe that 4S-SIF will be a useful tool for collecting in-situ data across multiple spatial and temporal scales. Satellite-based SIF provides us with new opportunities to understand the physiological and structural dynamics of vegetation from canopy to global scales. However, the relationships between SIF and gross primary productivity (GPP) are not fully understood, which is mainly due to the challenges of decoupling structural and physiological factors that control the relationships. In Chapter 3, I reported the results of continuous observations of canopy-level SIF, GPP, absorbed photosynthetically active radiation (APAR), and chlorophyll: carotenoid index (CCI) in a temperate evergreen needleleaf forest. To understand the mechanisms underlying the relationship between GPP and SIF, I investigated the relationships of light use efficiency (LUE_p), chlorophyll fluorescence yield (Φ_F), and the fraction of emitted SIF photons escaping from the canopy (f_esc) separately. I found a strongly non-linear relationship between GPP and SIF at diurnal and seasonal time scales (R2 = 0.91 with a hyperbolic regression function, daily). GPP saturated with APAR, while SIF did not. In addition, there were differential responses of LUE_p and Φ_F to air temperature. While LUE_p reached saturation at high air temperatures, Φ_F did not saturate. I also found that the canopy-level chlorophyll: carotenoid index was strongly correlated to canopy-level Φ_F (R2 = 0.84) implying that Φ_F could be more closely related to pigment pool changes rather than LUE_p. In addition, I found that the f_esc contributed to a stronger SIF-GPP relationship by partially capturing the response of LUE_p to diffuse light. These findings can help refine physiological and structural links between canopy-level SIF and GPP in evergreen needleleaf forests. We do not fully understand what satellite NDVI derived leaf-out and full leaf dates actually observe because deciduous broadleaf forest consists of multi-layer canopies typically and mixed-signal from multi-layer canopies could affect satellite observation. Ultimately, we have the following question: What phenology do we actually see from space compared to ground observations on multi-layer canopy phenology? In Chapter 4, I reported the results of 8 years of continuous observations of multi-layer phenology and climate variables in a deciduous broadleaf forest, South Korea. Multi-channel spectrometers installed above and below overstory canopy allowed us to monitor over- and understory canopy phenology separately, continuously. I evaluated the widely used phenology detection methods, curvature change rate and threshold with NDVI observed above top of the canopy and compared leaf-out and full leaf dates from both methods to in-situ observed multi-layer phenology. First, I found that NDVI from the above canopy had a strong linear relationship with satellites NDVI (R2=0.95 for MODIS products and R2= 0.85 for Landsat8). Second, leaf-out dates extracted by the curvature change rate method and 10% threshold were well matched with understory leaf-out dates. Third, the full-leaf dates extracted by the curvature change rate method and 90% threshold were similar to overstory full-leaf dates. Furthermore, I found that overstory leaf-out dates were closely correlated to accumulated growing degree days (AGDD) while understory leaf-out dates were related to AGDD and also sensitive to the number of chill days (NCD). These results suggest that satellite-based leaf-out and full leaf dates represent understory and overstory signals in the deciduous forest site, which requires caution when using satellite-based phenology data into future prediction as overstory and understory canopy show different sensitivities to AGDD and NCD.식물 계절 및 식생의 생리학적, 구조적인 변화를 지속적으로 모니터링 하는 것은 육상생태계와 대기권 사이의 에너지, 탄소 순환 등의 피드백을 이해하는데 필수적이다. 이를 관측하기 위하여 위성에서 관측된 정규화 식생 지수 (NDVI) 태양 유도 엽록소 형광물질 (SIF)는 대중적으로 사용되고 있다. 그러나, 우주 위성 기반의 자료는 다음과 같은 한계점들이 존재한다. 1) 아직까지 고해상도의 위성 기반 SIF 자료는 없고, 2) 위성 자료들은 대기의 질 (예, 구름)에 영향을 받아, 흐린 날의 식생의 생리학적, 구조적 변화를 탐지하기 힘들다. 또한, 3) 위성 이미지는 상부 식생과 하부 식생이 혼합되어 섞인 신호를 탐지하기 때문에, 각 층의 식물 계절을 각각 연구하기에 어려움이 있다. 그러므로, 위성에서 탐지한 신호를 평가하고, 식생의 생리학적, 구조적 변화를 보다 정확히 이해하기 위해서는 근접 표면 원격 센싱 시스템을 이용한 실측 자료 기반의 연구들이 요구된다. 본 학위논문의 주 목적은 근접 표면 원격 센싱 시스템을 이용하여 식물 계절 및 SIF를 현장에서 지속적으로 실측하고, 위성 영상 기반의 연구가 갖고 있는 한계점 및 궁금증들을 해결 및 보완하는 것이다. 이 목적을 달성하기 위하여, 아래와 같은 세가지 Chapter: 1) SIF를 관측하기 위한 필터 기반의 저렴한 근접 표면 센싱 시스템 개발, 2)온대 침엽수림에서의 연속적인 SIF 관측, 3)위성 기반의 식물 계절과 실측한 다층 식생의 식물 계절 비교로 구성하고, 이를 진행하였다. SIF는 식생의 구조적, 생리학적 변화를 이해하고, 추정하는 인자로 사용될 수 있어, SIF를 현장에서 관측하기 위한 다양한 근접 표면 원격 센싱 시스템들이 최근 제시되어 오고 있다. 그러나, 아직까지 SIF를 관측하기 위한 상업적으로 유통되는 관측 시스템은 현저히 부족하며, 분광계의 구조적 특성상 현장에서 관측 시스템을 보정 및 관리하기가 어려워 높은 질의 SIF를 취득하는 것은 매우 도전 적인 분야이다. 본 학위 논문의 Chapter 2에서는 SIF를 현장에서 보다 손쉽게 관측하기 위한 필터 기반의 근접 표면 센싱 시스템(Smart Surface Sensing System, 4S-SIF)을 개발하였다. 센서는 대역 필터들과 포토다이오드가 결합되어 있으며, 서보 모터를 사용하여 대역 필터 및 관측 방향을 자동적으로 변경함으로써, 한 개의 포토다이오드가 3개의 파장 범위(757, 760, 770 nm)의 빛 및 태양으로부터 입사되는 광량과 식생으로 반사/방출된 광량을 관측할 수 있도록 고안되었다. 포토다이오드로부터 인식된 디지털 수치 값은 상업적으로 판매되는 초고해상도 분광계(QE Pro, Ocean Insight)와 뚜렷한 선형 관계를 보이는 것을 확인하였다 (R2 > 0.99). 추가적으로, 4S-SIF에서 관측된 SIF와 초고해상도 분광계를 이용하여 추출한 SIF가 선형적인 관계를 이루는 것을 확인하였다. 식생의 생리학적 변화를 일으키는 화학 물질인 DCMU(3-(3, 4-dichlorophenyl)-1, 1-dimethyurea)을 처리했음에도 불구하고, 산출된 SIF들은 선형 관계를 보였다. 본 센서는 기존 시스템들에 비해 사용하기 쉽고 간단하며, 저렴하기 때문에 다양한 시공간적 스케일의 SIF를 관측할 수 있다는 장점이 있다. 위성 기반의 SIF를 이용하여 총일차생산성(gross primary productivity, GPP)을 추정하는 연구는 최근 탄소 순환 연구 분야에서 각광받고 있는 연구 주제이다. 그러나, SIF와 GPP의 관계는 여전히 많은 불확실성을 지니고 있는데, 이는 SIF-GPP 관계를 조절하는 식생의 구조적 및 생리학적 요인을 따로 분리하여 고찰한 연구들이 부족하기 때문이다. 본 학위 논문의 Chapter 3에서는 지속적으로 SIF, GPP, 흡수된 광합성유효복사량 (absorbed photosynthetically active radiation, APAR), 그리고 클로로필과 카로티노이드의 비율 인자 (chlorophyll: carotenoid index, CCI)를 온대침엽수림에서 연속적으로 관측하였다. SIF-GPP 관계의 구체적인 메커니즘 관계를 밝히기 위하여, 광 이용효율 (light use efficiency, LUE_p), 엽록소 형광 수득률 (chlorophyll fluorescence yield, Φ_F) 그리고 SIF 광자가 군락으로부터 방출되는 비율 (escape fraction, f_esc)을 각각 도출하고 탐구하였다. SIF와 GPP의 관계는 뚜렷한 비 선형적인 관계를 보이는 것을 확인했으며(R2 = 0.91 with a hyperbolic regression function, daily), 일주기 단위에서 SIF는 APAR에 대해 선형적이었지만 GPP는 APAR에 대해 뚜렷한 포화 관계를 보이는 것을 확인하였다. 추가적으로 LUE_p 와 Φ_F 가 대기 온도에 따라 반응하는 정도가 다른 것을 확인하였다. LUE_p는 높은 온도에서 포화 되었지만, Φ_F는 포화 패턴을 확인할 수 없었다. 또한, 군락 수준에서의 CCI와 Φ_F가 뚜렷한 상관 관계를 보였다(R2 = 0.84). 이는 Φ_F가 엽록소 색소에 영향을 LUE_p에 비해 더 강한 관계가 있을 수 있음을 시사한다. 마지막으로, f_esc가 태양광의 산란된 정도에 따라 반응을 하여, Φ_F와 LUE_p의 강한 상관 관계를 형성하는데 기여하는 것을 확인하였다. 이러한 발견은 온대 침엽수림에서 군락 수준의 SIF-GPP관계를 생리학적 및 구조적 측면에서 이해하고 규명하는데 큰 도움이 될 것이다. 식물 계절은 식생이 철을 따라 주기적으로 나타내는 변화를 관측하는 반응이다. 식물 계절은 육상생태계와 대기권 사이의 물질 순환을 이해하는데 매우 중요하다. 위성 기반의 NDVI는 식물 계절을 탐지하고 연구하는데 가장 대중적으로 사용된다. 그러나, 활엽수림에서의 위성 NDVI 기반의 개엽 시기 및 성숙 시기가 실제 어느 시점을 탐지하는지는 불분명하다. 실제 활엽수림은 다층 식생 구조의 삼차원으로 이루어져 있는 반면, 위성 영상은 다층 식생의 신호가 섞여 있는 이차원의 결과물이기 때문이다. 따라서, 위성 NDVI 기반의 식물 계절이 다층 식생 구조를 이루고 있는 활엽수림에서 실제 현장 관측과 비교하였을 때 어느 시점을 탐지하는지에 대한 궁금증이 남는다. 본 학위 논문의 Chapter 4에서는 지속적으로 8년 동안 활엽수림내의 다층 식생의 식물 계절을 근접 표면 원격 센싱 시스템을 이용하여 관측하고, 위성 NDVI 기반의 식물 계절과 비교하였다. 다채널 분광계를 상부 식생의 위와 아래에 설치함으로써, 상부 식생과 하부 식생의 식물 계절을 각각 연속적으로 관측하였다. 식물 계절을 탐지하기 위하여 가장 많이 사용되는 방법인 1) 역치를 이용하는 방법과 2) 이계도함수를 이용하는 방법을 사용하여 개엽 시기 및 성숙 시기를 계산하고 이를 다층 식생의 식물 계절과 비교하였다. 본 연구 결과, 첫번째로, 군락의 상층부에서 실측한 NDVI와 위성 기반의 NDVI가 강한 선형 관계를 보이는 것을 확인했다 (R2=0.95 는 MODIS 영상들 및 R2= 0.85 는 Landsat8). 두번째로, 이계도함수 방법과 10%의 역치 값을 이용한 방법이 비슷한 개엽 시기를 추정하는 것을 확인하였으며, 하부 식생의 개엽 시기와 비슷한 시기임을 확인하였다. 세번째로, 이계도함수 방법과 90%의 역치 값을 이용한 방법이 비슷한 성숙 시기를 산출하였으며, 이는 상부 식생의 성숙 시기와 비슷하였다. 추가적으로 상부 식생의 개엽 시기와 하부 식생의 개엽 시기가 온도와 반응하는 정도가 뚜렷하게 차이가 나는 것을 확인할 수 있었다. 상부 식생의 개엽 시기는 적산 생장 온도 일수 (AGDD)와 강한 상관성을 보였고, 하부 식생의 개엽 시기는 AGDD와 연관성을 갖고 있을 뿐만 아니라 추위 일수(NCD)에도 민감하게 반응하는 것을 확인하였다. 이러한 결과는 위성 NDVI 기반의 개엽 시기는 하부 식생의 개엽 시기와 연관성이 높고, 성숙 시기는 상부 식생의 성숙 시기와 비슷하다는 것을 의미한다. 또한, 상부 식생과 하부 식생이 온도에 다른 민감성을 갖고 있어, 위성에서 산출된 식물 계절을 이용하여 기후변화를 이해하고자 할 때, 어떤 층의 식생이 위성 영상에 주된 영향을 미치는지 고려해야 한다는 것을 시사한다. 위성은 넓은 지역의 변화를 손쉽게 모니터링할 수 있어 많은 가능성을 갖고 있는 도구이지만, 보다 정확한 위성 관측 값을 이해하기 위해서는 현장에서 관측된 자료를 기반으로 한 검증이 요구된다. 본 학위 논문에서는 1) 근접 표면 센싱 시스템을 개발, 2) 근접 표면 센싱 시스템을 활용한 식생의 생리학적 구조적 변화의 지속적인 관측, 3) 다층 식생 구조에서 관측되는 식물 계절 및 위성에서 추정된 식물 계절의 연관성 평가를 수행하였다. 개발한 근접 표면 센서는 상업 센서들과 비교했을 때, 가격적으로 저렴하고 손 쉽게 사용할 수 있었으며, 성능적으로도 부족함이 없었다. 근접 표면 센싱 시스템을 이용하여 SIF를 온대 침엽수림에서 지속적으로 관측한 결과, 총일차생산성과 SIF는 비선형 관계를 갖는 것을 확인하였다. 이는 많은 선행 연구들에서 발표한 위성 기반의 SIF와 GPP가 선형적인 관계를 보인다는 것과는 다소 상반된 결과이다. 다측 식생의 봄철 식물 계절을 연속적으로 관측하고, 위성 기반의 식물 계절과 비교평가한 연구에서는 위성 기반의 개엽 시기는 하부 식생에 영향을 주로 받고, 성숙 시기는 상부 식생의 시기와 비슷한 것을 확인하였다. 즉, 근접 표면 센싱 시스템을 이용하여 현장에서 실측한 결과는 위성 영상을 활용한 연구들과는 다른 결과를 보일 수도 있으며, 위성 영상을 평가 및 이해하는데 사용될 수 있다. 따라서, 보다 정확한 식생의 구조적, 생리학적 메커니즘을 이해하기 위해서는 근접 표면 센싱을 활용한 현장에서 구축한 자료 기반의 더 많은 연구들이 필요하다는 것을 시사한다.Abstract i Chapter 1. Introduction 2 1. Background 2 2. Purpose 5 Chapter 2. Monitoring SIF using a filter-based near surface remote sensing system 9 1. Introduction 9 2. Instrument desing and technical spefications of the filter-based smart surface sensing system (4S-SIF) 12 2.1. Ultra-narrow band pass filter 14 2.2. Calibration of 4S-SIF 15 2.3. Temperature and humidity response 16 2.4. Evaluate SIF quality from 4S-SIF in the field 17 3. Results 20 4. Discussion 23 Chapter 3. SIF is non-linearly related to canopy photosynthesis in a temperate evergreen needleleaf forest during fall transition 27 1. Introduction 27 2. Methods and Materials 31 2.1. Study site 31 2.2. Leaf-level fluorescence measurement 32 2.3. Canopy-level SIF and spectral reflectance measurement 34 2.4. SIF retrieval 37 2.5. Canopy-level photosynthesis estimates 38 2.6. Meteorological variables and APAR 39 2.7. Statistical analysis 40 3. Results 41 4. Discussion 48 4.1. Non-linear relationships between SIF and GPP 49 4.2. Role of f_esc in SIF-GPP relationship 53 4.3. Implications of non-linear SIF-GPP relationship in temperate ENF 54 5. Conclusion 57 6. Appendix 59 Chapter 4. Monitoring spring phenology of multi-layer canopy in a deciduous broadleaf forest: What signal do satellites actually see in space 65 1. Introduction 65 2. Materials and Methods 69 2.1. Study site 69 2.2. Multi-layer spectral reflectance and transmittance measurement 70 2.3. Phenometrics detection 72 2.4. In-situ multi-layer phenology 74 2.5. Satellite remote sensing data 75 2.6. Meteorological variables 75 3. Results 76 3.1. Seasonal to interannual variations of NDVI, 1-transmittance, and air temperature 76 3.2. Inter-annual variation of leaf-out and full-leaf dates 78 3.3. The relationships between dates calculated according tothreshold and in-situ multi-layer phenology 80 3.4. The relationship between multi-layer phenology, AGDD and NCD 81 4. Discussion 82 4.1. How do satellite-based leaf-out and full-leaf dates differ from in-situ multi-layer phenology 83 4.2. Are the 10 % and 90 % thresholds from satellite-basedNDVI always well matched with the leaf-out and full-leaf dates calculated by the curvature change rate 86 4.3. What are the implications of the difference between satellite-based and multi-layer phenology 87 4.4. Limitations and implications for future studies 89 5. Conclusion 91 6. Appendix 92 Chapter 5. Conclusion 114 Abstract in Korean 115박

Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands?

Ground solar-induced chlorophyll fluorescence (SIF) is important for the mechanistic understanding of the dynamics of vegetation gross primary production (GPP) at fine spatiotemporal scales. However, eddy covariance (EC) observations generally cover larger footprint areas than ground SIF observations (a bare fiber with nadir), and this footprint mismatch between nadir SIF and GPP could complicate the canopy SIF-GPP relationships. Here, we upscaled nadir SIF observations to EC footprint and investigated the change in SIF-GPP relationships after the upscaling in cropland. We included 13 site-years data in our study, with seven site-years corn, four siteyears soybeans, and two site-years miscanthus, all located in the US Corn Belt. All sites’ crop nadir SIF observations collected from the automated FluoSpec2 system (a hemispheric-nadir system) were upscaled to the GPP footprint-based SIF using vegetation indices (VIs) calculated from high spatiotemporal satellite reflectance data. We found that SIF-GPP relationships were not substantially changed after upscaling nadir SIF to GPP footprint at our crop sites planted with corn, soybean, and miscanthus, with R2 change after the upscaling ranging from -0.007 to 0.051 and root mean square error (RMSE) difference from -0.658 to 0.095 umol m-2 s-1 relative to original nadir SIF-GPP relationships across all the site-years. The variation of the SIF-GPP relationship within each species across different site-years was similar between the original nadir SIF and upscaled SIF. Different VIs, EC footprint models, and satellite data led to marginal differences in the SIF-GPP relationships when upscaling nadir SIF to EC footprint. Our study provided a methodological framework to correct this spatial mismatch between ground nadir SIF and GPP observations for croplands and potentially for other ecosystems. Our results also demonstrated that the spatial mismatch between ground nadir SIF and GPP might not significantly affect the SIF-GPP relationship in cropland that are largely homogeneous