Estimating forest parameters from top of atmosphere multi-angular radiance data using coupled radiative transfer models

ABSTRACT -Traditionally, the estimation of forest parameters using physically-based canopy radiative transfer models (RT

Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests

Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO2 flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO2 fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO2 exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate's temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE

The BMP Antagonist Follistatin-Like 1 Is Required for Skeletal and Lung Organogenesis

Follistatin-like 1 (Fstl1) is a secreted protein of the BMP inhibitor class. During development, expression of Fstl1 is already found in cleavage stage embryos and becomes gradually restricted to mesenchymal elements of most organs during subsequent development. Knock down experiments in chicken and zebrafish demonstrated a role as a BMP antagonist in early development. To investigate the role of Fstl1 during mouse development, a conditional Fstl1 KO allele as well as a Fstl1-GFP reporter mouse were created. KO mice die at birth from respiratory distress and show multiple defects in lung development. Also, skeletal development is affected. Endochondral bone development, limb patterning as well as patterning of the axial skeleton are perturbed in the absence of Fstl1. Taken together, these observations show that Fstl1 is a crucial regulator in BMP signalling during mouse development

The RSPO–LGR4/5–ZNRF3/RNF43 module controls liver zonation and size

LGR4/5 receptors and their cognate RSPO ligands potentiate Wnt/β-catenin signalling and promote proliferation and tissue homeostasis in epithelial stem cell compartments. In the liver, metabolic zonation requires a Wnt/β-catenin signalling gradient, but the instructive mechanism controlling its spatiotemporal regulation is not known. We have now identified the RSPO-LGR4/5-ZNRF3/RNF43 module as a master regulator of Wnt/β-catenin-mediated metabolic liver zonation. Liver-specific LGR4/5 loss of function (LOF) or RSPO blockade disrupted hepatic Wnt/β-catenin signalling and zonation. Conversely, pathway activation in ZNRF3/RNF43 LOF mice or with recombinant RSPO1 protein expanded the hepatic Wnt/β-catenin signalling gradient in a reversible and LGR4/5-dependent manner. Recombinant RSPO1 protein increased liver size and improved liver regeneration, whereas LGR4/5 LOF caused the opposite effects, resulting in hypoplastic livers. Furthermore, we show that LGR4(+) hepatocytes throughout the lobule contribute to liver homeostasis without zonal dominance. Taken together, our results indicate that the RSPO-LGR4/5-ZNRF3/RNF43 module controls metabolic liver zonation and is a hepatic growth/size rheostat during development, homeostasis and regeneration

Quantifying the effect of forest age in annual net forest carbon balance

Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was adominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches

Correction:How the COVID-19 pandemic highlights the necessity of animal research (vol 30, pg R1014, 2020)

(Current Biology 30, R1014–R1018; September 21, 2020) As a result of an author oversight in the originally published version of this article, a number of errors were introduced in the author list and affiliations. First, the middle initials were omitted from the names of several authors. Second, the surname of Dr. van Dam was mistakenly written as “Dam.” Third, the first name of author Bernhard Englitz was misspelled as “Bernard” and the surname of author B.J.A. Pollux was misspelled as “Pullox.” Finally, Dr. Keijer's first name was abbreviated rather than written in full. These errors, as well as various errors in the author affiliations, have now been corrected online

Estimation of plant functional biochemical traits of subalpine and alpine grasslands from airborne images of high spatial and spectral resolution

Abstract of presentation at the 9th Swiss Geoscience Meeting, Zurich 2011, 11-13 November, ETH Hauptgebaude & Department of Earth Sciences, ETH Zurich

Estimation of spruce needle-leaf chlorophyll content based on DART and PARAS canopy reflectance models

Needle-leaf chlorophyll content (Cab) of a Norway spruce stand was estimated from CHRIS-PROBA images using the canopy reflectance simulated by the PROSPECT model coupled with two canopy reflectance models: 1) discrete anisotropic radia- tive transfer model (DART); and 2) PARAS. The DART model uses a detailed description of the forest scene, whereas PARAS is based on the photon recollision probability theory and uses a simplified forest structural description. Subsequently, statisti- cally significant empirical functions between the optical indices ANCB 670 − 720 and ANMB 670 − 720 and the needle-leaf Cab content were established and then applied to CHRIS-PROBA data. The Cab estimating regressions using ANMB 670 − 720 were more robust than using ANCB 670 − 720 since the latter was more sensitive to LAI, especially in case of PARAS. Comparison between Cab esti- mates showed strong linear correlations between PARAS and DART retrievals, with a nearly perfect one-to-one fit when using ANMB 670 − 720 (slope = 1.1, offset = 11 μ g · cm − 2 ). Further com- parison with Cab estimated from an AISA Eagle image of the same stand showed better results for PARAS (RMSE = 2.7 μ g · cm − 2 for ANCB 670 − 720 ;RMSE = 9.5 μ g · cm − 2 for ANMB 670 − 720 )than for DART (RMSE = 7.5 μ g · cm − 2 for ANCB 670 − 720 ;RMSE = 23 μ g · cm − 2 for ANMB 670 − 720 ). Although these results show the potential for simpler models like PARAS in estimating needle-lea

Detecting leaf pulvinar movements on NDVI time series of desert trees: a new approach for water stress detection.

Heliotropic leaf movement or leaf 'solar tracking' occurs for a wide variety of plants, including many desert species and some crops. This has an important effect on the canopy spectral reflectance as measured from satellites. For this reason, monitoring systems based on spectral vegetation indices, such as the normalized difference vegetation index (NDVI), should account for heliotropic movements when evaluating the health condition of such species. In the hyper-arid Atacama Desert, Northern Chile, we studied seasonal and diurnal variations of MODIS and Landsat NDVI time series of plantation stands of the endemic species Prosopis tamarugo Phil., subject to different levels of groundwater depletion. As solar irradiation increased during the day and also during the summer, the paraheliotropic leaves of Tamarugo moved to an erectophile position (parallel to the sun rays) making the NDVI signal to drop. This way, Tamarugo stands with no water stress showed a positive NDVI difference between morning and midday (ΔNDVI mo-mi) and between winter and summer (ΔNDVI W-S). In this paper, we showed that the ΔNDVI mo-mi of Tamarugo stands can be detected using MODIS Terra and Aqua images, and the ΔNDVI W-S using Landsat or MODIS Terra images. Because pulvinar movement is triggered by changes in cell turgor, the effects of water stress caused by groundwater depletion can be assessed and monitored using ΔNDVI mo-mi and ΔNDVI W-S. For an 11-year time series without rainfall events, Landsat ΔNDVI W-S of Tamarugo stands showed a positive linear relationship with cumulative groundwater depletion. We conclude that both ΔNDVI mo-mi and ΔNDVI W-S have potential to detect early water stress of paraheliotropic vegetation