Sensitivity of ecosystem net primary productivity models to remotely sensed leaf area index in a montane forest environment

xii, 181 leaves : ill. ; 28 cm.Net primary productivity (NPP) is a key ecological parameter that is important in estimating carbon stocks in large forested areas. NPP is estimated using models of which leaf area index (LAI) is a key input. This research computes a variety of ground-based and remote sensing LAI estimation approaches and examines the impact of these estimates on modeled NPP. A relative comparison of ground-based LAI estimates from optical and allometric techniques showed that the integrated LAI-2000 and TRAC method was preferred. Spectral mixture analysis (SMA), accounting for subpixel influences on reflectance, outperformed vegetation indices in LAI prediction from remote sensing. LAI was shown to be the most important variable in modeled NPP in the Kananaskis, Alberta region compared to soil water content (SWC) and climate inputs. The variability in LAI and NPP estimates were not proportional, from which a threshold was suggested where first LAI is limiting than water availability

Puistute takseertunnuste hindamine aerolidari mõõtmisandmete põhjal hemiboreaalsetes metsades

A Thesis for applying for the degree of Doctor of Philosophy in Forestry.Forest management and planning requires up-to-date data, which commonly is acquired using field experts and ground measurements. Nowadays, more and more of data about forest stands is measured using remotely sensing methods. Most common methods include aerial photography and laser scanning from airplanes, also spectral measurements from satellites or even drone images and applications. This doctoral thesis focuses on developing applications and methods for utilising the airborne laser scanning (ALS) data that is freely available for the whole Estonia. The ALS measurements are carried out by the Estonian Land Board on a routine basis twice a year – in spring and summer. The first variable that was studied in this thesis was forest height. Based on the thesis, the most reliable method for forest height assessment was using the ALS point-cloud 80th height percentile (HP80). The small circular plot (radius of 15…30 m) and stand based studies showed high correlations with the field-measured forest heights and with great confidence it can be said, that ALS-based forest height estimations are close or even with higher accuracy, than field inspected. The second studied variable was standing wood volume. The ALS-based methods and models that were developed throughout this thesis used the idea, that standing wood volume is based on forest height and density. For this the HP80 and a threshold-based point count ratio was used (canopy cover - CC). ALS-based CC (CCALS) estimates were studied and compared with digital hemispherical photo based measurements. The results showed similar errors as were shown in other similar studies, with around 10-15% root mean square error (RMSE). The strongest correlation was shown using all echoes above a 1.3 metre threshold. Combining the CCALS and HP80 showed standing wood volume estimates with a similar error as we would receive from field measurements (<20%). The freely available multitemporal ALS data showed promising results for forest height growth monitoring and detecting small-scale disturbances. CCALS was shown to have strong predictive value, when compared with a four year difference in thinned and unthinned stands. The nation-wide ALS data can also be combined with forest height predictions from satellites, providing a faster update compared to the ALS data. Promising results were shown using the interferometric synthetic aperture radar (InSAR). Stand species maps generated using self-learning algorithms and satellite based spectral data can be used for developing species specific models of standing wood volume prediction. By combining these different datasets we can construct a nation-wide forest resource to help make better decisions for forest management and targeting fieldwork.Metsades majandamisotsuste langetamiseks ja metsamajanduslike tööde planeerimiseks on metsaomanikel vaja andmeid. Harjumuspäraselt on andmete kogumiseks tehtud metsas maapealseid mõõtmisi. Viimastel aastakümnetel on metsade inventeerimiseks üha enam aga kasutatud mittekontaktseid mõõtmisi - lennukitelt tehtavad aerofotosid, laserskaneerimist, satelliitidelt tehtavaid kiirgusmõõtmisi või viimastel aastatel ka droonidelt tehtud pilte. Antud doktoritöö on võtnud fookusesse aerolaserskaneerimise (ALS) andmete põhjal Eesti metsadesse sobilike rakenduste väljatöötamise. ALS mõõtmisi teeb Eesti Maa-amet rutiinsete lendude käigus kaks korda aastas, nii kevadel kui ka suvel. Aastast 2008 alustatud mõõtmiste tulemusel on Eesti üks väheseid riike maailmas, kus on vabalt kasutada mitmekordselt kogu riiki kattev ALS andmestik. Doktoritöö tulemusel töötati välja metsa kõrguse hindamiseks sobilikud meetodid, kasutades selleks punktipilvede kõrgusprotsentiile. Tugevamaid seoseid metsas proovitükkidel mõõdetud kõrgustega näitas punktipilve 80-protsentiil (HP80) ja uuringute põhjal võib väita, et metsa kõrguse määramine suvistelt aerolidari andmetelt on ligilähedane täpsustele, mida saadakse metsas kohapeal mõõtes. Teine oluline tunnus, mida metsade majandamise planeerimisel silmas peetakse, on kasvava metsa tagavara. Teadustöö põhjal töötati välja mudelite kujud ja metoodika, mille abil prognoositud tagavara oli sarnase veapiiriga, mis on lubatud metsas hinnanguid tegevatele taksaatoritele (<20%). Väljatöötatud ALS-põhine mudeli kuju järgib loogikat, et metsa tagavara on otseselt seotud mõõdetud kõrguse ja metsa tihedusega. Tihenduse hindamiseks aerolidari andmetelt kasutatakse nivoopõhist punktide suhtearvu ehk nn katvushinnangut (CCALS). Katvushinnangu täpsuse valideerimiseks ja tihedas metsas sobiva prognoosimeetodi väljatöötamiseks tehti välimõõtmisi kasutades poolsfäärikaameraid. Poolsfääripiltide põhjal tehtud valideerimise tulemused andsid sarnaseid veahinnanguid, mida on ka varasemates teadusuuringutes esitletud (RMSE = 10…15%). Kahe sarnasest fenoloogilisest perioodist ALS andmestiku lahutamisel uuriti ka muutuste tuvastamise võimalikkust. Uuringud andsid paljulubavaid tulemusi metsade kõrguskasvu hindamiseks ja CCALS osutus ka oluliseks tunnuseks väiksemate häiringute, nagu näiteks harvendusraie, tuvastamiseks. Kogu riiki katva ALS andmestiku kombineerimisel erinevate satelliitandmetega või näiteks spektraalsete mõõtmiste põhjal tehtud puistu liigiliste koosseisu kaartidega on võimalik antud töös välja pakutud meetodite abil anda igal aastal kogu Eesti metsaressursside ülevaade. Samuti on võimalik koostada vaid kaugseirevahendeid ja proovitükkidel lähendatud mudeleid kasutades eraldiste põhised takseerkirjeldused, mida siis taksaatorid saavad näiteks kasutada oma välitööde kavandamisel.  Publication of this thesis is supported by the Estonian University of Life Sciences

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

Environmental factors influencing the Douglas fir invasion of Nothofagus forest

Douglas fir (Pseudotsuga menziesii) was introduced to New Zealand in 1859 for timber, and in the last few decades has been recognised as an invasive species, particularly into grassland. However, its potential to invade native forests is still poorly understood. I investigated the invasion of Douglas fir into mountain beech (Nothofagus solandri var. cliffortioides) forest, particularly the factors limiting the spread, at Cora Lynn, near Arthur’s Pass. Adjacent to the beech forest is an 80 ha Douglas fir and Corsican pine (Pinus nigra) plantation, whose invasive potential started to raise concerns in the late 1980s. The study was divided into three parts. The first consisted of resampling plots established on the site in 1989 to count Douglas fir seedlings spreading into Nothofagus. In the second part, I investigated the factors limiting the establishment of Douglas fir seedlings in the beech forest. To do this I established 400 points in the native forest, and at each point I assessed the light environment (via hemispherical photography), measured altitude, and distance to the nearest seedling. Lastly, I conducted a root competition and fertiliser-addition experiment to investigate the factors limiting the growth of the Douglas fir seedlings. I selected 544 naturally regenerating seedlings (30 to 70 cm tall) in the beech forest, and applied one of four treatments: fertiliser addition, root trenching, fertiliser addition plus root trenching, and control. Light environment and altitude at each seedling were measured. The mean density of seedlings in the plots has increased 13-fold since the first measurement in 1989, from 11,267 seedlings/ha to 150,333 seedlings/ha in 2016. There is a widespread Douglas fir invasion of the mountain beech forest in progress – in only a single point out of 400 did I fail to find a seedling within a 10-m radius. Altitude had the strongest effect on the distance to the nearest seedling, with lower seedling density at higher altitudes. Although distance to the nearest seedling decreased with light, the seedlings were not restricted to light-wells or canopy gaps as generally presumed, but present throughout the native forest. Light had the strongest effect on seedling growth. At the experimental seedlings, light ranged from 3.01 to 10.29 mol m-2 d-1, that is 8.12% and 27.8% respectively of full sunlight. Altitude had a negative effect on seedling growth. Nutrient availability was second to light as a growth limiting factor. Fertiliser addition had the largest effect on seedling growth across treatments, increasing it 18.3% above that of the control. Root trenching had a small negative effect on growth, while fertilizer plus trenching had a positive effect, but still smaller than expected. I have demonstrated that Douglas fir is well able to invade Nothofagus forest, albeit slowly, and that the spread was affected by a complex relationship between light, nutrients, root competition, distance to the seed source, and altitude. In New Zealand, poor control of conifer invasions into grasslands and shrublands in the past has led to large environmental and economic impacts. The potential negative effects of the Douglas fir spread into native forest could be minimized by early control. I hope that my work will contribute to a better understanding of the Douglas fir’s invasive potential, as well as draw attention to the need for managing the spread in progress

Trooppisten alkuperäismetsien monitorointi Taita Hillsin alueella digitaalisen ilmakuva-aineiston avulla

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955-2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.Metsien väheneminen ja niiden laadun heikkeneminen on maailmanlaajuisesti tunnustettu ongelma. Metsien pirstoutuminen vaikuttaa biodiversiteettiin ja ekosysteemien hyvinvointiin myös Keniassa. Tämä tutkimus keskittyy kahden trooppisen alkuperäisvuoristometsän tutkimiseen Taita Hillsin alueella Kaakkois-Keniassa. Tutkimus on osa Helsingin yliopiston maantieteen laitoksen TAITA-projektia. Tutkimusmetsiä, Ngangaoa ja Chawiaa tutkitaan kaukokartoitus- ja paikkatietomenetelmien avulla. Tutkimuksen pääaineiston muodostavat mustavalkoiset ilmakuvat vuodelta 1955 ja digitaaliset oikeaväri-ilmakuvat vuodelta 2004. Näistä ilmakuvista muodostetaan ilmakuvamosaiikit tutkimusalueilta. Alueiden maanpeite luokitellaan kolmella metodilla: visuaalisella tulkinnalla, pikselipohjaisella ohjatulla luokituksella sekä objekti-orientoidulla ohjatulla luokituksella. Metsäpinta-alan muutosta vuosina 1955-2004 tutkitaan visuaalisten luokitusten perusteella käyttämällä paikkatietomenetelmiä. Tutkimusmetsien kuntoa arvioidaan lehtipinta-alaindeksin ja latvuksen sulkeituneisuuden avulla. Nämä parametrit saadaan käyttämällä hemisfäärisiä valokuvia. Lisäksi tutkimuksessa käytetään metsien kuntoa arvioivaa aiemmin kerättyä tutkimustietoa. Latvusparametreja verrataan digitaali-ilmakuvamosaiikeilta saatuihin tekstuurisiin parametreihin. Yhteenvetona voidaan sanoa, että metsäalueiden luokitus oikeaväri-ilmakuvia käyttämällä ei ole helppoa, vaikka itse digitaali-ilmakuvista tehdyt mosaiikit olisivat erittäin tarkkoja. Parhaat luokitustulokset saavutetaan edelleen visuaalisella tulkinnalla, sillä pikselipohjainen ja objekti-orientoitu ohjattu luokitus eivät saavuta tarpeeksi hyvää luotettavuutta. Tutkimusalueiden maanpeitteen muutostulkinnan mukaan alkuperäismetsän osuus on vähentynyt sekä Ngangaossa että Chawiassa 1955-2004. Ngangaossa metsän kokonaisala on kuitenkin lisääntynyt lähinnä eksoottisten puulajien istutusten vuoksi. Molempien tutkimusalueiden maanpeite on huomattavasti pirstoutuneempaa vuonna 2004 kuin vuonna 1955. Vaikka metsäala on pienentynyt, tutkimusmetsien tulevaisuus näyttää paremmalta kuin aiemmin. Tämä johtuu lähinnä kasvavasta metsien arvostuksesta

Influence of sky conditions on carbon dioxide uptake by forests

Sky conditions play an important role in the Earth’s climate system, altering the solar radiation reaching the Earth’s surface and determining the fraction of incoming direct and diffuse radiation. Sky conditions dictate the radiation distribution inside plant canopies and also the carbon dioxide uptake by forests during the growing season. On the long term these diffuse conditions may have a positive influence on forest growth in Northern Britain during the last 50 years. We compared the quantity (amount) and quality (spectral distribution) of direct and diffuse radiation above, inside and below a forest stand under sunny, cloudy and overcast conditions in a thinned Sitka spruce [Picea sitchensis (Bong.) Carr.] forest (28 years, with an leaf area index (LAI) of around 5 m2m-2). Similar radiation properties (sky conditions) were used for analysis of light response and canopy conductance measurements in the same and also in a different spruce forest of the same species (33 years, LAI of around 7 m2 m-2) over the growing season 2008 in order to compare canopy activity under these conditions. In order to integrate short-term and longterm studies, we were looking at how far these conditions are influencing forest growth over several decades. To do so, we used freshly cut tree discs of Sitka spruce from a felled forest (planting year 1953) in southern Scotland and solar direct and diffuse radiation along with other meteorological data from the nearest meteorological station. Our analysis show that the amount and quality of solar radiation is distributed differently inside forest stands under various sky conditions, leading to an enhanced carbon dioxide uptake and canopy stomatal activity under diffuse cloudy and overcast conditions. Furthermore we demonstrated which factors have influenced diffuse radiation distribution over the past 50 years and how these are correlated with forest growth in southern Scotland

Evolutionary Dynamics of Rapid, Microgeographic Adaptation in an Amphibian Metapopulation

Wild organisms can rapidly adapt to changing environments, even at fine spatial scales. This fact prompts hope that contemporary local adaptation may buffer some of the negative anthropogenic impacts to ecosystems. However, there are limits to the pace of adaptation. Understanding the adaptive potential—and limitations—of individual species at fine-resolution is an important task if we hope to accurately predict the repercussions of future climate and landscape change on biodiversity. My dissertation takes advantage of an uncommonly long-observed and closely-studied system to paint a comprehensive picture of evolution over time in association with shifts in ecological contexts. In this dissertation, I show evidence of rapid, microgeographic evolution in response to climate within a metapopulation of wood frogs (Rana sylvatica). Critically, I show that populations separated by tens to hundreds of meters—well within the dispersal ability of the species—exhibited considerable shifts in development rates over a period of two decades, or roughly 6-9 generations. Using historical climate data and new methods of assessing landscape change, I show that these changes were mainly a response to warming climates. The ecological contexts experienced by the metapopulation are associated with the evolution of physiological rates. Specifically, I show that climate change seems to have caused a counter-intuitive delay in spring breeding phenology while drought and warming later in the larval development period correspond with a shift toward earlier metamorphosis. The picture that emerges is of a contracting developmental window, which is expected to select for faster intrinsic development rates. Superimposed on the metapopulation-wide shift to faster development was a pattern of counter-gradient variation reflecting a similar pattern seen two decades prior. Furthermore, I empirically demonstrate a trade-off between faster development and a swimming performance trait that strongly contributes to fitness. This trade-off helps to explain why intrinsic development rates vary spatially with pond temperatures, but in the opposite direction of the relationship with temperature over time. Though the evidence for rapid adaptation to climate change presented in this dissertation reveals that evolution can buffer populations from extinction, it also entreats caution. There is a clear trend of demographic decline among wood frog populations that experienced greater magnitudes of environmental change. In fact, the three populations that suffered local extinctions over the 20-year course of observations inhabited ponds characterized by the greatest change in temperature or canopy

Assessing uncertainties of in situ FAPAR measurements across different forest ecosystems

Carbon balances are important for understanding global climate change. Assessing such balances on a local scale depends on accurate measurements of material flows to calculate the productivity of the ecosystem. The productivity of the Earth's biosphere, in turn, depends on the ability of plants to absorb sunlight and assimilate biomass. Over the past decades, numerous Earth observation missions from satellites have created new opportunities to derive so-called “essential climate variables” (ECVs), including important variables of the terrestrial biosphere, that can be used to assess the productivity of our Earth's system. One of these ECVs is the “fraction of absorbed photosynthetically active radiation” (FAPAR) which is needed to calculate the global carbon balance. FAPAR relates the available photosynthetically active radiation (PAR) in the wavelength range between 400 and 700 nm to the absorption of plants and thus quantifies the status and temporal development of vegetation. In order to ensure accurate datasets of global FAPAR, the UN/WMO institution “Global Climate Observing System” (GCOS) declared an accuracy target of 10% (or 0.05) as acceptable for FAPAR products. Since current satellite derived FAPAR products still fail to meet this accuracy target, especially in forest ecosystems, in situ FAPAR measurements are needed to validate FAPAR products and improve them in the future. However, it is known that in situ FAPAR measurements can be affected by significant systematic as well as statistical errors (i.e., “bias”) depending on the choice of measurement method and prevailing environmental conditions. So far, uncertainties of in situ FAPAR have been reproduced theoretically in simulations with radiation transfer models (RTMs), but the findings have been validated neither in field experiments nor in different forest ecosystems. However, an uncertainty assessment of FAPAR in field experiments is essential to develop practicable measurement protocols. This work investigates the accuracy of in situ FAPAR measurements and sources of uncertainties based on multi-year, 10-minute PAR measurements with wireless sensor networks (WSNs) at three sites on three continents to represent different forest ecosystems: a mixed spruce forest at the site “Graswang” in Southern Germany, a boreal deciduous forest at the site “Peace River” in Northern Alberta, Canada and a tropical dry forest (TDF) at the site “Santa Rosa”, Costa Rica. The main statements of the research results achieved in this thesis are briefly summarized below: Uncertainties of instantaneous FAPAR in forest ecosystems can be assessed with Wireless Sensor Networks and additional meteorological and phenological observations. In this thesis, two methods for a FAPAR bias assessment have been developed. First, for assessing the bias of the so-called two-flux FAPAR estimate, the difference between FAPAR acquired under diffuse light conditions and two-flux FAPAR acquired during clear-sky conditions can be investigated. Therefore, measurements of incoming and transmitted PAR are required to calculate the two-flux FAPAR estimate as well as observations of the ratio of diffuse-to-total incident radiation. Second, to assess the bias of not only the two- but also the three-flux FAPAR estimate, four-flux FAPAR observations must be carried out, i.e. measurements of top-of-canopy (TOC) PAR albedo and PAR albedo of the forest background. Then, to quantify the bias of the two and three-flux estimate, the difference with the four-flux estimate can be calculated. Main sources of uncertainty of in situ FAPAR measurements are high solar zenith angle, occurrence of colored leaves and increased wind speed. At all sites, FAPAR observations exhibited considerable seasonal variability due to the phenological development of the forests (Graswang: 0.89 to 0.99 ±0.02; Peace River: 0.55 to 0.87 ±0.03; Santa Rosa: 0.45 to 0.97 ±0.06). Under certain environmental conditions, FAPAR was affected by systemic errors, i.e. bias that go beyond phenologically explainable fluctuations. The in situ observations confirmed a significant overestimation of FAPAR by up to 0.06 at solar zenith angles above 60° and by up to 0.05 under the occurrence of colored leaves of deciduous trees. The results confirm theoretical findings from radiation transfer simulations, which could now for the first time be quantified under field conditions. As a new finding, the influence of wind speed could be shown, which was particularly evident at the boreal location with a significant bias of FAPAR values at wind speeds above 5 ms-1. The uncertainties of the two-flux FAPAR estimate are acceptable under typical summer conditions. Three-flux or four-flux FAPAR measurements do not necessarily increase the accuracy of the estimate. The highest average relative bias of different FAPAR estimates were 2.1% in Graswang, 8.4% in Peace River and -4.5% in Santa Rosa. Thus, the GCOS accuracy threshold of 10% set by the GCOS was generally not exceeded. The two-flux FAPAR estimate was only found to be biased during high wind speeds, as changes in the TOC PAR albedo are not considered in two-flux FAPAR measurements. Under typical summer conditions, i.e. low wind speed, small solar zenith angle and green leaves, two-flux FAPAR measurements can be recommended for the validation of satellite-based FAPAR products. Based on the results obtained, it must be emphasized that the three-flux FAPAR estimate, which has often been preferred in previous studies, is not necessarily more accurate, which was particularly evident in the tropical location. The discrepancies between ground measurements and the current Sentinel-2 FAPAR product still largely exceed the GCOS target accuracy at the respective study sites, even when considering uncertainties of FAPAR ground measurements. It was found that the Sentinel-2 (S2) FAPAR product systematically underestimated the ground observations at all three study sites (i.e. negative values for the mean relative bias in percent). The highest agreement was observed at the boreal site Peace River with a mean relative deviation of -13% (R²=0.67). At Graswang and Santa Rosa, the mean relative deviations were -20% (R²=0.68) and -25% (R²=0.26), respectively. It was argued that these high discrepancies resulted from both the generic nature of the algorithm and the higher ecosystem complexity of the sites Graswang and Santa Rosa. It was also found that the temporal aggregation method of FAPAR ground data should be well considered for comparison with the S2 FAPAR product, which refers to daily averages, as overestimation of FAPAR during high solar zenith angles could distort validation results. However, considering uncertainties of ground measurements, the S2 FAPAR product met the GCOS accuracy requirements only at the boreal study site. Overall, it has been shown that the S2 FAPAR product is already well suited to assess the temporal variability of FAPAR, but due to the low accuracy of the absolute values, the possibilities to feed global production efficiency models and evaluate global carbon balances are currently limited. The accuracy of satellite derived FAPAR depends on the complexity of the observed forest ecosystem. The highest agreement between satellite derived FAPAR product and ground measurements, both in terms of absolute values and spatial variability, was achieved at the boreal site, where the complexity of the ecosystem is lowest considering forest structure variables and species richness. These results have been elaborated and presented in three publications that are at the center of this cumulative thesis. In sum, this work closes a knowledge gap by displaying the interplay of different environmental conditions on the accuracy of situ FAPAR measurements. Since the uncertainties of FAPAR are now quantifiable under field conditions, they should also be considered in future validation studies. In this context, the practical recommendations for the implementation of ground observations given in this thesis can be used to prepare sampling protocols, which are urgently needed to validate and improve global satellite derived FAPAR observations in the future.Projektionen zukünftiger Kohlenstoffbilanzen sind wichtig für das Verständnis des globalen Klimawandels und sind auf genaue Messungen von Stoffflüssen zur Berechnung der Produktivität des Erdökosystems angewiesen. Die Produktivität der Biosphäre unserer Erde wiederum ist abhängig von der Eigenschaft von Pflanzen, Sonnenlicht zu absorbieren und Biomasse zu assimilieren. Über die letzten Jahrzehnte haben zahlreiche Erdbeobachtungsmissionen von Satelliten neue Möglichkeiten geschaffen, sogenannte „essentielle Klimavariablen“ (ECVs), darunter auch wichtige Variablen der terrestrischen Biosphäre, aus Satellitendaten abzuleiten, mit deren Hilfe man die Produktivität unseres Erdsystems computergestützt berechnen kann. Eine dieser „essenziellen Klimavariablen“ ist der Anteil der absorbierten photosynthetisch aktiven Strahlung (FAPAR) die man zur Berechnung der globalen Kohlenstoffbilanz benötigt. FAPAR bezieht die verfügbare photosynthetisch aktive Strahlung (PAR) im Wellenlängenbereich zwischen 400 und 700 nm auf die Absorption von Pflanzen und quantifiziert somit Status und die zeitliche Entwicklung von Vegetation. Um möglichst präzise Informationen aus dem globalen FAPAR zu gewährleisten, erklärte die UN/WMO-Institution zur globalen Klimabeobachtung, das “Global Climate Observing System“ (GCOS), ein Genauigkeitsziel von 10% (bzw. 0.05) FAPAR-Produkte als akzeptabel. Da aktuell satellitengestützte FAPAR-Produkte dieses Genauigkeitsziel besonders in Waldökosystemen immer noch verfehlen, werden dringen in situ FAPAR-Messungen benötigt, um die FAPAR-Produkte validieren und in Zukunft verbessern zu können. Man weiß jedoch, dass je nach Auswahl des Messsystems und vorherrschenden Umweltbedingungen in situ FAPAR-Messungen mit erheblichen sowohl systematischen als auch statistischen Fehlern beeinflusst sein können. Bisher wurden diese Fehler in Simulationen mit Strahlungstransfermodellen zwar theoretisch nachvollzogen, aber die dadurch abgeleiteten Befunde sind bisher weder in Feldversuchen noch in unterschiedlichen Waldökosystemen validiert worden. Eine Unsicherheitsabschätzung von FAPAR im Feldversuch ist allerdings essenziell, um praxistaugliche Messprotokolle entwickeln zu können. Die vorliegende Arbeit untersucht die Genauigkeit von in situ FAPAR-Messungen und Ursachen von Unsicherheit basierend auf mehrjährigen, 10-minütigen PAR-Messungen mit drahtlosen Sensornetzwerken (WSNs) an drei verschiedenen Waldstandorten auf drei Kontinenten: der Standort „Graswang“ in Süddeutschland mit einem Fichten-Mischwald, der Standort „Peace River“ in Nord-Alberta, Kanada mit einem borealen Laubwald und der Standort „Santa Rosa“, Costa Rica mit einem tropischen Trockenwald. Die Hauptaussagen der in dieser Arbeit erzielten Forschungsergebnisse werden im Folgenden kurz zusammengefasst: Unsicherheiten von FAPAR in Waldökosystemen können mit drahtlosen Sensornetzwerken und zusätzlichen meteorologischen und phänologischen Beobachtungen quantifiziert werden. In dieser Arbeit wurden zwei Methoden für die Bewertung von Unsicherheiten entwickelt. Erstens, um den systematischen Fehler der sogenannten „two-flux“ FAPAR-Messung zu beurteilen, kann die Differenz zwischen FAPAR, das unter diffusen Lichtverhältnissen aufgenommen wurde, und FAPAR, das unter klaren Himmelsbedingungen aufgenommen wurde, untersucht werden. Für diese Methode sind Messungen des einfallenden und transmittierten PAR sowie Beobachtungen des Verhältnisses von diffuser zur gesamten einfallenden Strahlung erforderlich. Zweitens, um den systematischen Fehler nicht nur der „two-flux“ FAPAR-Messung, sondern auch der „three-flux“ FAPAR-Messung zu beurteilen, müssen „four-flux“ FAPAR-Messungen durchgeführt werden, d.h. zusätzlich Messungen der PAR Albedo des Blätterdachs sowie des Waldbodens. Zur Quantifizierung des Fehlers der „two-flux“ und „three-flux“ FAPAR-Messung kann die Differenz zur „four-flux“ FAPAR-Messung herangezogen werden. Die Hauptquellen für die Unsicherheit von in situ FAPAR-Messungen sind ein hoher Sonnenzenitwinkel, Blattfärbung und erhöhte Windgeschwindigkeit. An allen drei Untersuchungsstandorten zeigten die FAPAR-Beobachtungen natürliche saisonale Schwankungen aufgrund der phänologischen Entwicklung der Wälder (Graswang: 0,89 bis 0,99 ±0,02; Peace River: 0,55 bis 0,87 ±0,03; Santa Rosa: 0,45 bis 0,97 ±0,06). Unter bestimmten Umweltbedingungen war FAPAR von systematischen Fehlern, d.h. Verzerrungen betroffen, die über phänologisch erklärbare Schwankungen hinausgehen. So bestätigten die in situ Beobachtungen eine signifikante Überschätzung von FAPAR um bis zu 0,06 bei Sonnenzenitwinkeln von über 60° und um bis zu 0,05 bei Vorkommen gefärbter Blätter der Laubbäume. Die Ergebnisse bestätigen theoretische Erkenntnisse aus Strahlungstransfersimulationen, die nun erstmalig unter Feldbedingungen quantifiziert werden konnten. Als eine neue Erkenntnis konnte der Einfluss der Windgeschwindigkeit gezeigt werden, der sich besonders am borealen Standort mit einer signifikanten Verzerrung der FAPAR-Werte bei Windgeschwindigkeiten über 5 ms-1 äußerte. Die Unsicherheiten der „two-flux“ FAPAR-Messung sind unter typischen Sommerbedingungen akzeptabel. „Three-flux“ oder „four-flux“ FAPAR-Messungen erhöhen nicht unbedingt die Genauigkeit der Abschätzung. Die höchsten durchschnittlichen relativen systematischen Fehler verschiedener Methoden zur FAPAR-Messung betrugen 2,1% in Graswang, 8,4% in Peace River und -4,5% in Santa Rosa. Damit wurde der durch GCOS festgelegte Genauigkeitsschwellenwert von 10% im Allgemeinen nicht überschritten. Die „two-flux“ FAPAR-Messung wurde nur als fehleranfällig bei hohe Windgeschwindigkeiten befunden, da Änderungen der PAR-Albedo des Blätterdachs bei der „two-flux“ FAPAR-Messung nicht berücksichtigt werden. Unter typischen Sommerbedingungen, also geringe Windgeschwindigkeit, kleiner Sonnenzenitwinkel und grüne Blätter, kann die „two-flux“ FAPAR-Messung für die Validierung von satellitengestützten FAPAR-Produkten empfohlen werden. Auf Basis der gewonnenen Ergebnisse muss betont werden, dass die „three-flux“ FAPAR-Messung, die in bisherigen Studien häufig bevorzugt wurde, nicht unbedingt weniger fehlerbehaftet sind, was sich insbesondere am tropischen Standort zeigte. Die Abweichungen zwischen Bodenmessungen und dem aktuellen Sentinel-2 FAPAR-Produkt überschreiten auch unter Berücksichtigung von Unsicherheiten in der Messmethodik immer noch weitgehend die GCOS-Zielgenauigkeit an den jeweiligen Untersuchungsstandorten. So zeigte sich, dass das S2 FAPAR-Produkt die Bodenbeobachtungen an allen drei Studienstandorten systematisch unterschätzte (d.h. negative Werte für die mittlere relative Abweichung in Prozent). Die höchste Übereinstimmung wurde am borealen Standort Peace River mit einer mittleren relativen Abweichung von -13% (R²=0,67) beobachtet. An den Standorten Graswang und Santa Rosa betrugen die mittleren relativen Abweichungen jeweils -20% (R²=0,68) bzw. -25% (R²=0,26). Es wurde argumentiert, dass diese hohen Abweichungen auf eine Kombination sowohl des generisch ausgerichteten Algorithmus als auch der höheren Komplexität beider Ökosysteme zurückgeführt werden können. Es zeigte sich außerdem, dass die zeitlichen Aggregierung der FAPAR-Bodendaten zum Vergleich mit S2 FAPAR-Produkt, das sich auf Tagesmittelwerte bezieht, gut überlegt sein sollte, da die Überschätzung von FAPAR während eines hohen Sonnenzenitwinkels in den Bodendaten die Validierungsergebnisse verzerren kann. Unter Berücksichtigung der Unsicherheiten der Bodendaten erfüllte das S2 FAPAR Produkt jedoch nur am boreale Untersuchungsstandort die Genauigkeitsanforderungen des GCOS. Insgesamt hat sich gezeigt, dass das S2 FAPAR-Produkt bereits gut zur Beurteilung der zeitlichen Variabilität von FAPAR geeignet ist, aber aufgrund der geringen Genauigkeit der absoluten Werte sind die Möglichkeiten, globale Produktionseffizienzmodelle zu speisen und globale Kohlenstoffbilanzen zu bewerten, derzeit begrenzt. Die Genauigkeit von satellitengestützten FAPAR-Produkten ist abhängig von der Komplexität des beobachteten Waldökosystems. Die höchste Übereinstimmung zwischen satellitengestütztem FAPAR und Bodenmessungen, sowohl hinsichtlich der Darstellung von absolutem Werten als auch der räumlichen Variabilität, wurde am borealen Standort erzielt, für den die Komplexität des Ökosystems unter Berücksichtigung von Waldstrukturvariablen und Artenreichtum am geringsten ausfällt. Die dargestellten Ergebnisse wurden in drei Publikationen dieser kumulativen Arbeit erarbeitet. Insgesamt schließt diese Arbeit eine Wissenslücke in der Darstellung des Zusammenspiels verschiedener Umgebungsbedingungen auf die Genauigkeit von situ FAPAR-Messungen. Da die Unsicherheiten von FAPAR nun unter Feldbedingungen quantifizierbar sind, sollten sie in zukünftigen Validierungsstudien auch berücksichtigt werden. In diesem Zusammenhang können die in dieser Arbeit genannten praktische Empfehlungen für die Durchführung von Bodenbeobachtungen zur Erstellung von Messprotokollen herangezogen werden, die dringend erforderlich sind, um globale satellitengestützte FAPAR-Beobachten validieren und zukünftig verbessern zu können