Evaluating the relationship between SIF and GPP under climate extremes

2021 ◽  
Author(s):  
Sebastian Wieneke ◽  
Ana Bastos ◽  
Manuela Balzarolo ◽  
José Miguel Barrios ◽  
Ivan Janssens
Keyword(s):  
Large Scale ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Climate Extremes ◽  
Vegetation Stress ◽  
Linear Relationships ◽  
Forest Sites ◽  
Good Proxy ◽  
The Relationship

<p>Sun Induced Chlorophyll Fluorescence (SIF) is considered as a good proxy for photosynthesis given its closer link to the photosynthetic light reactions compared to remote sensing vegetation indices typically used for ecosystem productivity modelling (eg. NDVI). Satellite-based SIF shows significant linear relationships with gross primary production (GPP) from in-situ measurements across sites, biomes and seasons. While SIF can be considered a good proxy for large scale spatial and seasonal variability in GPP, much of the SIF-GPP co-variance can be explained by their common dependence on the absorbed photosynthetically active radiation. Whether SIF can be an equally good proxy for interannual variability in GPP especially during periods of vegetation stress (drought/heat) is, so far, not clear.</p><p>In this study, we evaluate the relationship between satellite-based SIF and in-situ GPP measurements during vegetation stress periods (drought/heat), compared to non-stress periods. GPP is obtained from eddy-covariance measurements from a set of forest sites pre-filtered to ensure homonegeous footprints. SIF is obtained from GOME-2 covering the period 2007-2018. Because of scale mismatch between each site’s footprint (in the order of hundred meters) and the spatial resolution of GOME-2 (ca. 50km), we additionally use SIF from the downscale product from Duveiller et al. 2020 (ca. 5km) and the more recent dataset from TROPOMI (ca. 7 x 3.5 km), covering only the last year of the study period.</p><p>We develop a classification of stress periods that is based on both the occurrence of drought/heat extreme events and the presence of photosynthetic downregulation. We then evaluate the relationship between SIF and GPP and their yields, for different plant functional types and at site-level. We evaluate how these relationships vary depending on environmental conditions and in particular for “stress” versus “non-stress” days.</p><p>Duveiller, G., Filipponi, F., Walther, S., Köhler, P., Frankenberg, C., Guanter, L., and Cescatti, A.: A spatially downscaled sun-induced fluorescence global product for enhanced monitoring of vegetation productivity, Earth Syst. Sci. Data, 12, 1101–1116, https://doi.org/10.5194/essd-12-1101-2020, 2020.</p>

scholarly journals Lack of an association between gallstone disease and bilirubin levels with risk of colorectal cancer: a Mendelian randomisation analysis

2021 ◽  
Author(s):  
Richard Culliford ◽  
Alex J. Cornish ◽  
Philip J. Law ◽  
Susan M. Farrington ◽  
Kimmo Palin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Causal Effect ◽  
Gallstone Disease ◽  
Epidemiological Studies ◽  
Mendelian Randomisation ◽  
Linear Relationships ◽  
Potential Risk Factors ◽  
The Relationship ◽  
Circulating Levels

Abstract Background Epidemiological studies of the relationship between gallstone disease and circulating levels of bilirubin with risk of developing colorectal cancer (CRC) have been inconsistent. To address possible confounding and reverse causation, we examine the relationship between these potential risk factors and CRC using Mendelian randomisation (MR). Methods We used two-sample MR to examine the relationship between genetic liability to gallstone disease and circulating levels of bilirubin with CRC in 26,397 patients and 41,481 controls. We calculated the odds ratio per genetically predicted SD unit increase in log bilirubin levels (ORSD) for CRC and tested for a non-zero causal effect of gallstones on CRC. Sensitivity analysis was applied to identify violations of estimator assumptions. Results No association between either gallstone disease (P value = 0.60) or circulating levels of bilirubin (ORSD = 1.00, 95% confidence interval (CI) = 0.96–1.03, P value = 0.90) with CRC was shown. Conclusions Despite the large scale of this study, we found no evidence for a causal relationship between either circulating levels of bilirubin or gallstone disease with risk of developing CRC. While the magnitude of effect suggested by some observational studies can confidently be excluded, we cannot exclude the possibility of smaller effect sizes and non-linear relationships.

The various facets of digital repeat photography fully exploited with the phenopix R package

2020 ◽  
Author(s):  
Gianluca Filippa ◽  
Edoardo Cremonese ◽  
Marta Galvagno ◽  
Mirco Migliavacca
Keyword(s):  
Land Surface ◽  
Gross Primary Production ◽  
Rapid Development ◽  
Vegetation Indices ◽  
Region Of Interest ◽  
Climate Extremes ◽  
R Package ◽  
Seasonal Development ◽  
Special Focus ◽  
The Impact

<p>Flux towers are more and more often equipped with digital cameras (aka phenocams) widely used to track canopy greenness. Phenocam-derived vegetation indices can capture land surface phenology but also seasonality in gross primary production (GPP) estimated from eddy covariance (EC) measurements. In addition, phenocams can be used to track seasonal development of different species or individuals within the same image scene, and evaluate spatial variability within the footprint of EC measurements. Further, phenocams were recently used to quantify disturbance such as late frost, fires, storms etc. in forested ecosystems and the impact of climate extremes on ecosystem functioning. With the recent rapid development of phenocameras, the need for up-to-date, efficient, open-source software is also increasing tremendously. The phenopix R package was developed for this purpose. In this contribution, we will provide an overview of the software capabilities, with a special focus on how EC measurements can benefit from phenocam data streams.</p><p>The steps of a basic processing workflow will be illustrated, including drawing a region of interest (ROI) on an image; extracting red, green and blue digital numbers from a seasonal series of images; depicting greenness index trajectories; fitting a curve to the seasonal trajectories; extracting relevant phenological thresholds (phenophases); characterizing phenophase uncertainties. A focus will be made on recent software developments, including the calculation of camera-derived NDVI and other infrared-based indices, and the handling of shifts in the field of view of the phenocameras.</p>

scholarly journals Testing the relationship between the solar radiation dose and surface DMS concentrations using high resolution in situ data

2009 ◽  
Vol 6 (2) ◽  
pp. 3063-3085
Author(s):  
C. J. Miles ◽  
T. G. Bell ◽  
T. M. Lenton
Keyword(s):  
Radiation Dose ◽  
Solar Radiation ◽  
Mixed Layer Depth ◽  
Light Attenuation ◽  
Climate Feedback ◽  
Solar Ultraviolet Radiation ◽  
In Situ Data ◽  
Linear Relationships ◽  
The Relationship

Abstract. We tested the recently proposed, strong positive relationship between dimethylsulphide (DMS) concentrations and the solar radiation dose (SRD) received into the surface ocean. We utilised in situ daily data sampled concurrently with DMS concentrations from the Atlantic Meridional Transect (AMT) programme for the component variables of the SRD; mixed layer depth (MLD), surface insolation (I0) and a light attenuation coefficient (k), to calculate SRDin situ. We find a significant correlation (ρ=0.53) but the slope of the relationship is approximately half that previously proposed. The correlation is improved (ρ=0.76) by replacing the in situ data with an estimated I0 (which assumes a constant 50% removal of the top of atmosphere value; 0.5×TOA), a MLD climatology and a fixed value for k following a previously described methodology. Equally significant, but non-linear relationships are also found between DMS and both in situ MLD (ρ=0.73) and the estimated I0 (ρ=0.76) alone. The DMS data shows an interesting relationship to an approximated UV attenuation depth profile. Using a cloud adjusted, satellite climatology of surface UVA irradiance to calculate a UV radiation dose (UVRD) provides an equivalent correlation (ρ=0.73) to DMS. With this data, MLD appears the dominant control upon DMS concentrations and remains a useful shorthand to prediction without fully resolving the biological processes involved. However, the implied relationship between incident solar/ultraviolet radiation dose and sea surface DMS concentrations (modulated by MLD) is critical for closing a climate feedback loop.

scholarly journals Ability of RCM/GCM couples to represent the relationship of large scale circulation to climate extremes over the Mediterranean region

2011 ◽  
Vol 46 (3) ◽  
pp. 197-209 ◽  
Author(s):  
HA Flocas ◽  
M Hatzaki ◽  
K Tolika ◽  
C Anagnostopoulou ◽  
E Kostopoulou ◽  
...  
Keyword(s):  
Mediterranean Region ◽  
Large Scale ◽  
Climate Extremes ◽  
Large Scale Circulation ◽  
The Mediterranean ◽  
Relationship Of ◽  
The Relationship

In situ examination of the relationship between various vegetation indices and canopy phenology in an evergreen coniferous forest, Japan

2012 ◽  
Vol 33 (19) ◽  
pp. 6202-6214 ◽  
Author(s):  
Shin Nagai ◽  
Taku M. Saitoh ◽  
Hideki Kobayashi ◽  
Mitsunori Ishihara ◽  
Rikie Suzuki ◽  
...  
Keyword(s):  
Vegetation Indices ◽  
Coniferous Forest ◽  
The Relationship ◽  
In Situ Examination

scholarly journals Estimation of cloud condensation nuclei concentration from aerosol optical quantities: influential factors and uncertainties

2014 ◽  
Vol 14 (1) ◽  
pp. 471-483 ◽  
Author(s):  
Jianjun Liu ◽  
Zhanqing Li
Keyword(s):  
Great Plains ◽  
Large Scale ◽  
Cloud Condensation Nuclei ◽  
Single Scattering ◽  
Influential Factors ◽  
Condensation Nuclei ◽  
Scattering Coefficients ◽  
Forest Sites ◽  
The Relationship ◽  
Aerosol Hygroscopicity

Abstract. Large-scale measurements of cloud condensation nuclei (CCN) are difficult to obtain on a routine basis, whereas aerosol optical quantities are more readily available. This study investigates the relationship between CCN and aerosol optical quantities for some distinct aerosol types using extensive observational data collected at multiple Atmospheric Radiation Measurement (ARM) Climate Research Facility (CRF) sites around the world. The influences of relative humidity (RH), aerosol hygroscopicity (fRH) and single scattering albedo (SSA) on the relationship are analyzed. Better relationships are found between aerosol optical depth (AOD) and CCN at the Southern Great Plains (US), Ganges Valley (India) and Black Forest sites (Germany) than those at the Graciosa Island (the Azores) and Niamey (Niger) sites, where sea salt and dust aerosols dominate, respectively. In general, the correlation between AOD and CCN decreases as the wavelength of the AOD measurement increases, suggesting that AOD at a shorter wavelength is a better proxy for CCN. The correlation is significantly improved if aerosol index (AI) is used together with AOD. The highest correlation exists between CCN and aerosol scattering coefficients (σsp) and scattering AI measured in situ. The CCN–AOD (AI) relationship deteriorates with increasing RH. If RH exceeds 75%, the relationship where AOD is used as a proxy for CCN becomes invalid, whereas a tight σsp–CCN relationship exists for dry particles. Aerosol hygroscopicity has a weak impact on the σsp–CCN relationship. Particles with low SSA are generally associated with higher CCN concentrations, suggesting that SSA affects the relationship between CCN concentration and aerosol optical quantities. It may thus be used as a constraint to reduce uncertainties in the relationship. A significant increase in σsp and decrease in CCN with increasing SSA is observed, leading to a significant decrease in their ratio (CCN / σsp) with increasing SSA. Parameterized relationships are developed for estimating CCN, which account for RH, particle size, and SSA.

scholarly journals Evidence for the organization of chromatin in megabase pair-sized loops arranged along a random walk path in the human G0/G1 interphase nucleus.

1995 ◽  
Vol 130 (6) ◽  
pp. 1239-1249 ◽  
Author(s):  
H Yokota ◽  
G van den Engh ◽  
J E Hearst ◽  
R K Sachs ◽  
B J Trask
Keyword(s):  
Random Walk ◽  
Dna Sequences ◽  
Large Scale ◽  
Loop Model ◽  
Interphase Nuclei ◽  
Attachment Sites ◽  
The Relationship ◽  
Made In ◽  
Random Walk Path

We determined the folding of chromosomes in interphase nuclei by measuring the distance between points on the same chromosome. Over 25,000 measurements were made in G0/G1 nuclei between DNA sequences separated by 0.15-190 megabase pairs (Mbp) on three human chromosomes. The DNA sequences were specifically labeled by fluorescence in situ hybridization. The relationship between mean-square interphase distance and genomic separation has two linear phases, with a transition at approximately 2 Mbp. This biphasic relationship indicates the existence of two organizational levels at scales > 100 kbp. On one level, chromatin appears to be arranged in large loops several Mbp in size. Within each loop, chromatin is randomly folded. On the second level, specific loop-attachment sites are arranged to form a supple, backbonelike structure, which also shows characteristic random walk behavior. This random walk/giant loop model is the simplest model that fully describes the observed large-scale spatial relationships. Additional evidence for large loops comes from measurements among probes in Xq28, where interphase distance increases and then locally decreases with increasing genomic separation.

scholarly journals Agricultural drought monitoring in Tamil Nadu in India using Satellite-based multi vegetation indices

2021 ◽  
Vol 13 (2) ◽  
pp. 414-423
Author(s):  
Kumaraperumal. R. ◽  
Pazhanivelan. S. ◽  
Ragunath. K.P. ◽  
Balaji Kannan ◽  
Prajesh. P.J. ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Spectral Indices ◽  
Vegetation Stress ◽  
Additive Combination ◽  
Combined Indices ◽  
Better Than

Drought being an insidious hazard, is considered to have one of the most complex phenomenons. The proposed study identifies remote sensing-based indices that could act as a proxy indicator in monitoring agricultural drought over Tamil Nadu's region India. The satellite data products were downloaded from 2000 to 2013 from MODIS, GLDAS – NOAH, and TRMM. The intensity of agricultural drought was studied using indices viz., NDVI, NDWI, NMDI, and NDDI. The satellite-derived spectral indices include raw, scaled, and combined indices. Comparing satellite-derived indices with in-situ rainfall data and 1-month SPI data was performed to identify exceptional drought to no drought conditions for September month. The additive combination of NDDI showed a positive correlation of 0.25 with rainfall and 0.23 with SPI, while the scaled NDDI and raw NDDI were negatively correlated with rainfall and SPI. Similar cases were noticed with raw LST and raw NMDI. Indices viz., LST, NDVI, and NDWI performed well; however, it was clear that NDWI performed better than NDVI while LST was crucial in deciding NDVI coverage over the study area. These results showed that no single index could be put forward to detect agricultural drought accurately; however, an additive combination of indices could be a successful proxy to vegetation stress identification.  

scholarly journals Understanding the Land Surface Phenology and Gross Primary Production of Sugarcane Plantations by Eddy Flux Measurements, MODIS Images, and Data-Driven Models

2020 ◽  
Vol 12 (14) ◽  
pp. 2186
Author(s):  
Fengfei Xin ◽  
Xiangming Xiao ◽  
Osvaldo M.R. Cabral ◽  
Paul M. White ◽  
Haiqiang Guo ◽  
...  
Keyword(s):  
Primary Production ◽  
Seasonal Dynamics ◽  
Land Surface ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Data Driven ◽  
Flux Tower ◽  
The Usa ◽  
The Relationship

Sugarcane (complex hybrids of Saccharum spp., C4 plant) croplands provide cane stalk feedstock for sugar and biofuel (ethanol) production. It is critical for us to analyze the phenology and gross primary production (GPP) of sugarcane croplands, which would help us to better understand and monitor the sugarcane growing condition and the carbon cycle. In this study, we combined the data from two sugarcane EC flux tower sites in Brazil and the USA, images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and data-driven models to study the phenology and GPP of sugarcane croplands. The seasonal dynamics of climate, vegetation indices from MODIS images, and GPP from two sugarcane flux tower sites (GPPEC) reveal the temporal consistency in sugarcane phenology (crop calendar: green-up dates and harvesting dates) as estimated by the vegetation indices and GPPEC data. The Land Surface Water Index (LSWI) is shown to be useful to delineate the phenology of sugarcane croplands. The relationship between the sugarcane GPPEC and the Enhanced Vegetation Index (EVI) is stronger than the relationship between the GPPEC and the Normalized Difference Vegetation Index (NDVI). We ran the Vegetation Photosynthesis Model (VPM), which uses the light use efficiency (LUE) concept and is driven by climate data and MODIS images, to estimate the daily GPP at the two sugarcane sites (GPPVPM). The seasonal dynamics of the GPPVPM and GPPEC at the two sites agreed reasonably well with each other, which indicates that VPM is a powerful tool for estimating the GPP of sugarcane croplands in Brazil and the USA. This study clearly highlights the potential of combining eddy covariance technology, satellite-based remote sensing technology, and data-driven models for better understanding and monitoring the phenology and GPP of sugarcane croplands under different climate and management practices.

scholarly journals Remote Sensing of Vegetation Recovery in Grasslands after the 1988 Fires in Yellowstone National Park

1993 ◽  
Vol 17 ◽  
pp. 130-138
Author(s):  
Eveyln Merrill ◽  
Ronald Marrs
Keyword(s):  
National Park ◽  
Large Scale ◽  
Vegetation Indices ◽  
Electromagnetic Spectrum ◽  
Landsat Data ◽  
Spectral Indices ◽  
Green Vegetation ◽  
Variable Success ◽  
Vegetation Characteristics ◽  
The Relationship

Traditional methods for measurement of vegetative characteristics can be time-consuming and labor-intensive, especially across large areas. Yet such estimates are necessary to investigate the effects of large scale disturbances on ecosystem components and processes. Because foliage of plants differentially absorbs and reflects energy within the electromagnetic spectrum, one alternative for monitoring vegetation is to use remotely sensed spectral data (Tueller 1989). Spectral indices developed from field radiometric and Landsat data have been used successfully to quantify green leaf area, biomass, and total yields in relatively homogeneous fields for agronomic uses (Shibayama and Akiyama 1989}, but have met with variable success in wildland situations (Pearson et al. 1976). Interference from soils (Hardinsky et al. 1984, Huete et al. 1985), weathered litter (Huete and Jackson 1987), and senesced vegetation (Sellers 1985) have diminished the relationship between green vegetation characteristics and various vegetation indices.

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