Description: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Description: Tropical forests store 40–50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1–164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.

Description: This document defines and prioritises the key objectives of dissemination of REFLECT and details the steps to be taken during the project’s lifetime in order to achieve maximum impact and reach relevant audiences. It also sets the framework to facilitate communication among Consortium members, and between the Consortium and stakeholders or the general public.

Description: This document corresponds to Deliverable D6.2 of the ongoing Horizon 2020 project REFLECT and is part of the Work Package 6. The deliverable “Stakeholder matrix” aims to define the approach for engaging stakeholders and involving them into the project in the most efficient way in order to achieve quality final results and successful implementation of the project final product. The document defines the main groups of the potential stakeholders and provides general guidelines on how to categorise them, how to establish the first contact and how to engage them.

Description: The basic website of the REFLECT project was launched at the end of March 2020, three months after the project’s start. The website was conceived to support the launch of the project, providing a project overview and information about the partners involved. The final version of the website delivered in June 2020 includes more detailed information about the project’s objectives, approach, dissemination material and links to the project’s social media channels. This document describes the website elements. These elements can (and will) evolve with time, to ensure the best possible interaction with users during the project lifetime.

Description: In this work we present the observational study of propagation of blobs (Sheeley et al., 1997) in which detection in the white-light data is favored during solar minimum activity. Therefore, the minimum of the solar cycle 24 was particularly an optimal occasion to perform an observational analysis of the detection of blobs. As blobs are considered to be tracers in white-light data of the slow solar wind, the importance of the study of their propagation has two aims: (1) to known more about their kinematic behavior and (2) to inquire about the local morphology of the solar magnetic field of their origin. The selected periods of observation have permitted the identification of around 100 blob-like structures detected by LASCO and SECCHI coronagraphs on board SOHO and STEREO, respectively. The inferring location of their origin in the inner solar corona was performed by the tridimensional Potential Field Source Surface (PFSS) developed by De Rosa (2003). The results of this study support previous findings that track down the origin of the slow and intermediate solar wind to neighboring regions of helmet streamers and pseudostreamers (Panasenco and Velli, 2016; Riley and Luhmann, 2012, and references therein). In addition, the kinematic of the 3D trajectories of blobs have been used to explore the 'drag-force' model (Borgazzi et al., 2009) which explains the stretching behavior of faster and slower blobs. Finally in this study, we propose a "new" estimation of the Sun-mass-loss taking into account also the blobs mass along an 11-years solar cycle.

Description: Progressive hydrothermal alteration and mineral precipitation can modify the physical properties and mechanical behavior of the affected rocks, increasing the probabilities of phreatic or hydrothermal explosive eruptions. In this work we focus on the study of rock alteration and hydrothermal system of Deception Island, which is one of the most active volcanoes in Antarctica. A characterization of the pre-caldera and syn-caldera rock alterations has been done as a starting point for the understanding of the past and present hydrothermal system in the island. The alteration processes that have affected pre-caldera deposits are related to low temperature (〈200 oC) fluids, with pervasive palagonitisation and precipitation of smectite and zeolite. In some samples carbonate has also been detected. This alteration is consistent with rocks located at the first 500-600 meters depth of the pre-caldera shield volcano, in which the upper part of the sequence was affected by low-temperature acidic hydrothermal fluids that would have caused the dissolution of some phenocrysts and the consequent precipitation of magnesite. An extended palagonitisation characterize the syn-caldera deposits, but smectite and zeolite have also been identified. This is consistent with syn-depositional and meteoric alteration. Therefore, in the studied samples there is no evidence of persistent hydrothermal alteration that could be related to the current hydrothermal system. This work is part of the CSIC Interdisciplinary Thematic Platform (PTI) Polar zone Observatory (PTI-POLARCSIC) activities. This research was partially funded by the MINECO VOLCLIMA (CGL2015-72629-EXP) and HYDROCAL (PID2020-114876GB-I00) MCIN/AEI/10.13039/501100011033 research projects. This research is also supported by the PREDOCS-UB grant.

Description: Deception Island is the most active volcano in the South Shetland Islands with more than 20 explosive eruptions registered over the past centuries. The latest event (1970) was severely violent with a volcanic explosivity index (VEI) of 3. The column height reached 10 km, the estimated bulk eruptive volume was 〉 0.1 km3 and tephra fallout was reported as far as in King George Island (〉 150 km distance). In this work, we perform a compositional and textural analysis of the 1970 tephra layers found at Livingston Island’s glaciers. Results obtained are compared to the in situ pyroclastic deposits of the active vents during the eruption. The objective is to establish a correlation between the eruptive phases occurred during the 1970 event and the physicochemical features observed in the tephra deposits. This will be used the onset of future studies of tephra layers found in glaciers and marine/lacustrine sediment cores outside the island, improving our capacity to reconstruct the eruptive dynamics of past eruptions. This is fundamental to: (i) determine the size and explosiveness of past eruptions; (ii) assess the extent of their related hazards; (iii) complete the eruptive record; and (iv) consequently, perform accurate hazard assessments at the island. This work is part of the CSIC Interdisciplinary Thematic Platform (PTI) Polar zone Observatory (PTI-POLARCSIC) activities. This research was partially funded by the MINECO VOLCLIMA (CGL2015-72629-EXP) and HYDROCAL (PID2020-114876GB-I00) MCIN/AEI/10.13039/501100011033 research projects. Sampling was founded by CICYT (ANT91-1270, ANT93-0852 and ANT96-0734).