A Multiple Imputation Strategy for Eddy Covariance Data

Half-hourly time series of net ecosystem exchange (NEE) of CO2, latent heat flux (LE) and sensible heat flux (H) measured through the micro-meteorological eddy covariance (EC) technique are noisy and show a high percentage of missing data. By using EC measurements that are part of the FLUXNET2015 dataset, we evaluate the performance of a multiple imputation (MI) strategy based on an efficient computational strategy introduced in Honaker and King (2010), combining the classic Expectation-Maximization (EM) algorithm with a bootstrap approach, in order to take draws from a suitable approximation of posterior distribution of model parameters. Armed with these instruments, we are able to introduce three new multiple imputation models, characterized by an increasing level of complexity, and built on top of multivariate normality assumption: 1) MLR, which imputes EC missing values using a static multiple linear regression of observed values of suitable input variables; 2) ADL, which enriches with dynamic properties the static specification of MLR, by considering an autoregressive distributed lag specification; 3) PADL, which adds further complexity by embedding the ADL model in a panel-data perspective. Under several artificial gap scenarios, we show that PADL has a better ability in modeling the complex dynamics of ecosystem fluxes and reconstructing missing data points, thus providing unbiased imputations and preserving the original sampling distribution. The added flexibility arising from the time series cross section structure of PADL warrants improved performances, outperforming those of other imputation methods, as well as of the marginal distribution sampling algorithm (MDS), a widely used gap- filling approach introduced by Reichstein et al. (2005), especially in the case of nighttime flux data. It is expected that the strategy proposed in this paper will become useful in creating multiple imputations for a variety of EC datasets, providing valid inferences for a broad range of scientific estimands (such as annual budgets)

Potential of ALOS2 and NDVI to estimate forest above-ground biomass, and comparison with lidar-derived estimates

Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data) together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California) and Asiago (Alps). While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66). In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon density, satellite data with lower cost and broad coverage can be as effective as lidar

Experimental validation of footprint models for eddy covariance CO2 flux measurements above grassland by means of natural and artificial tracers

Footprint models, which simulate source area for scalar fluxes, are fundamental tools for a correct interpretation of micromoeteorological flux measurements and ecosystem exchange inferred from such data. Over the last two decades models of varying complexity have been developed, but all of them suffer from a significant lack of experimental validation. In this study two different experimental tests have been conducted with the aim of offering validation: a manipulation of the vegetation cover and an artificial tracer emission. In the first case the extension of the flux source has been changed progressively by successive cuts of vegetation, while in the second case by varying the distance of a tracer emission line respect to the measurement point. Results have been used to validate two analytical and a numerical footprint models. The experimental data show a good agreement with footprint models and indicate a limited extension of the flux source area, with approximately 75% of the sources confined within a range of 10-20 times the effective measurement height, i.e. the measurement height above the zero plane displacement. Another interesting result was the strong dependence on the surface roughness of both experimental estimates and numerical simulations of footprint. The effect of surface roughness on experimental results and models outputs was comparable to the effect of atmospheric stability. This indicates that surface roughness and turbulence conditions may play a significant role in source area location, in particular above inhomogeneous surfaces with change in roughness, as in the case of the manipulation experiment. Consequently a careful site specific quantification of these parameters seems to be fundamental to obtain realistic footprint estimates and significantly improve eddy covariance flux interpretation at complex sites.Peer reviewe

Ideas and perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries

Carbon (C) and greenhouse gas (GHG) research has traditionally required data collection and analysis using advanced and often expensive instruments, complex and proprietary software, and highly specialized research technicians. Partly as a result, relatively little C and GHG research has been conducted in resource-constrained developing countries. At the same time, these are often the same countries and regions in which climate change impacts will likely be strongest and in which major science uncertainties are centered, given the importance of dryland and tropical systems to the global C cycle. Increasingly, scientific communities have adopted appropriate technology and approach (AT&A) for C and GHG research, which focuses on low-cost and low-technology instruments, open-source software and data, and participatory and networking-based research approaches. Adopting AT&A can mean acquiring data with fewer technical constraints and lower economic burden and is thus a strategy for enhancing C and GHG research in developing countries. However, AT&A can have higher uncertainties; these can often be mitigated by carefully designing experiments, providing clear protocols for data collection, and monitoring and validating the quality of obtained data. For implementing this approach in developing countries, it is first necessary to recognize the scientific and moral importance of AT&A. At the same time, new AT&A techniques should be identified and further developed. All these processes should be promoted in collaboration with local researchers and through training local staff and encouraged for wide use and further innovation in developing countries

Introduction

Le rôle de l’économie privée dans la promotion du développement, que ce soit au Sud ou à l’Est, jouit d’une reconnaissance croissante tant parmi les acteurs du développement au Nord que chez leurs partenaires du Sud. Parallèlement, les organisations internationales (Banque mondiale, institutions de l’ONU) et les agences nationales de développement attachent de plus en plus d’importance à la promotion du secteur privé. Comment les entreprises privées, surtout les petites et moyennes entreprise..

Eddy covariance flux errors due to random and systematic timing errors during data acquisition

Modern eddy covariance (EC) systems collect high-frequency data (10–20 Hz) via digital outputs of instruments. This is an important evolution with respect to the traditional and widely used mixed analog/digital systems, as fully digital systems help overcome the traditional limitations of transmission reliability, data quality, and completeness of the datasets. However, fully digital acquisition introduces a new problem for guaranteeing data synchronicity when the clocks of the involved devices themselves cannot be synchronized, which is often the case with instruments providing data via serial or Ethernet connectivity in a streaming mode. In this paper, we suggest that, when assembling EC systems “inhouse”, aspects related to timing issues need to be carefully considered to avoid significant flux biases. By means of a simulation study, we found that, in most cases, random timing errors can safely be neglected, as they do not impact fluxes significantly. At the same time, systematic timing errors potentially arising in asynchronous systems can effectively act as filters leading to significant flux underestimations, as large as 10 %, by means of attenuation of high-frequency flux contributions. We characterized the transfer function of such “filters” as a function of the error magnitude and found cutoff frequencies as low as 1 Hz, implying that synchronization errors can dominate high-frequency attenuations in open- and enclosed-path EC systems. In most cases, such timing errors neither be detected nor characterized a posteriori. Therefore, it is important to test the ability of traditional and prospective EC data logging systems to assure the required synchronicity and propose a procedure to implement such a test relying on readily available equipment

Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

To answer new scientific and ecological questions and monitor multiple forest changes, a fine scale characterization of these ecosystems is needed, and could imply the mapping of specific species, of detailed forest types, and of functional composition. This characterization can be now provided by the novel Earth Observation tools. This study aims to contribute to understanding the innovation in forest and ecological research that can be brought in by advanced remote sensing instruments, and proposes the guild mapping approach as a tool to efficiently monitor the varied tropical forest resources. We evaluated, in tropical Ghanaian forests, the ability of airborne hyperspectral and simulated multispectral Sentinel-2 data, and derived vegetation indices and textures, to: distinguish between two different forest types; to discriminate among selected dominant species; and to separate trees species grouped according to their functional guilds: Pioneer, Non Pioneer Light Demanding, and Shade Bearer. We then produced guild classification maps for each area using hyperspectral data. Our results showed that with both hyperspectral and simulated Sentinel-2 data these discrimination tasks can be successfully accomplished. Results also stressed the importance of texture features, especially if using the lower spectral and spatial Sentinel-2 resolution data, and highlighted the important role of the new Sentinel-2 data for ecological monitoring. Classification results showed a statistically significant improvement in overall accuracy using Support Vector Machine, over Maximum Likelihood approach. We proposed the functional guilds mapping as an innovative approach to: (i) monitor compositional changes, especially with respect to the effects of global climate change on forests, and particularly in the tropical biome where the occurrence of hundreds of species prevents mapping activities at species level; (ii) support large-scale forest inventories. The imminent Sentinel-2 data could serve to open the road for the development of new concepts and methods in forestry and ecological research

Assessment of full carbon budget of Italy: the CarbIUS project

Regional carbon balances, funded, for the Italian side, by the Italian Ministry of Environment in the context of a bilateral agreement to develop scientific collaborations in Global Change Research between Italy and USA signed in 2001. The two regions selected are Italy and Oregon-California; there are many similarities between these two regions (climate, vegetation, topography, population pressure, etc.) but, on other hand, there are also interesting contrasts in societal aspects like demography, land-use history and emissions. The main CarbIUS objectives are 1) the identification of spatial and temporal variability of carbon sources and sinks and the relative contribution of the different anthropogenic and biogenic components, 2) the impact of land use changes and human population dynamics on the carbon balance, 3) the quantification of the effects of climate and natural disturbances on the terrestrial carbon stocks and fluxes and 4) the application of new methodologies to investigate carbon metabolism at the plot, ecosystem and regional scale. In this paper will be presented the methodologies that we are using to assess the contribution of the different components to the full carbon budget, like carbon stocks and fluxes, disturbances (harvesting, wild forest fires and forest pathology), CH4 and NO2 fluxes and anthropogenic emissions. All these information will be input in a Data Assimilation System and the results will be validated using sub-regional airborne measurements of carbon fluxes