Harmonized Methods for Assessing Carbon Sequestration in European Forests

The MASCAREF (Study under EEC 2152/2003 Forest Focus regulation on developing harmonized methods for assessing carbon sequestration in European forests) project was conducted by a consortium of 10 European institutions coordinated by IFER ¿ Institute of Forest Ecosystem Research, Czech Republic. The overall objective of this project was to contribute to the development of a monitoring scheme for carbon sequestration in forests of the European Union (EU). Specifically, the project aimed at i) strengthening and harmonizing the existing national systems to better meet the requirements of international monitoring and reporting of greenhouse-gas (GHG) emissions and sinks and ii) improving the comparability, transparency and accuracy of the GHG inventory reports of the Land use, land-use change and forestry (LULUCF) sector of the EU Member States, as implemented in the EC Monitoring Mechanism. This project represents a step towards addressing the challenges of GHG inventories and the reporting under the United Nations Framework Convention on Climate Change (UNFCCC) and its Kyoto protocol related to forest land and forest activities. Reflecting the heterogeneity in land use, natural conditions and monitoring data availability, there is a wide variety in greenhouse gas reporting practices within the European Community, which becomes clearly apparent from an overview of the current GHG reporting practices prepared by MASCAREF. The particular tasks of the project were based on available data from regional, national and EU-wide projects and relevant activities that took place over the last decade. The project elaboration was conducted within several major tasks, followed by selected regional case-studies. Firstly, the currently available data and methodological approaches to estimate carbon stock and carbon stock change for emission inventories were analyzed. Secondly, the project conducted an analysis of ICP Forests health monitoring and Forest Focus programs. Similarly, it assessed the potential of utilizing data from the European National Forest Inventories for the purpose of emission inventory under UNFCCC and the Kyoto protocol. Related to this, the JRC AFOLUDATA website on biomass functions and conversion/expansion factors http://afoludata.jrc.ec.europa.eu/index.php/public_area/home) was complemented by adding new factors from the European member states. Also, the methodologies to aggregate the forest carbon stock data based on the National Forest Inventory plots to a 10x10 km grid were explored. Finally, several of the above tasks were elaborated and/or applied in case studies in the selected regions of Europe. The MASCAREF project fulfilled its main objectives and its results should facilitate a further development of monitoring schemes for carbon stock change assessment in forests of the European member states, hopefully leading to an improved GHG reportingJRC.DDG.H.2-Climate chang

LULUCF MRV - Analysis and proposals for enhancing Monitoring, Reporting and Verification of greenhouse gases from Land Use, Land Use Change and Forestry in the EU

Land use land use change and forestry sector (LULUCF) is a greenhouse gas inventory (GHG) sector that covers anthropogenic emissions and removals from terrestrial carbon stocks living biomass dead organic matter and soil organic carbon following six main land use categories, Forest land, Cropland, Grassland, Wetlands, Settlements and Other land. According to the United Nation Framework Contract on Climate Change (UNFCCC) all Parties shall report periodically an update inventory of anthropogenic emissions and removals of GHG using comparable methodologies provided by the Intergovernmental Panel on Climate Change (IPCC). Additional requirements exist for reporting and accounting emissions/removals from related direct-human induced activities under the Kyoto Protocol (KP), because its accounting quantities are counted towards an international commitment reduction target. International negotiations have resulted in recent years in the adoption of new rules (e.g. mandatory accounting of Forest management) for the second commitment period of the KP (CP2: 2013-2020). Furthermore, Decision 529/2013/EU, going beyond the international negotiation, added the mandatory accounting of Cropland management and Grassland management. All these changes pose new challenges that MS will need to face from 2015 (i.e. for starting to report during CP2). This report describes the actions undertaken in the context of the Administrative Arrangement “LULUCF MRV” (Monitoring, Reporting, Verification) with DG CLIMA, trough a sequence of tasks (described in detailed in the Annexes). The aim of the AA is to support MS in improving the quality and comparability of LULUCF reporting during CP2, in line with IPCC methods and the new rules at UNFCCC and EU level.JRC.H.3-Forest Resources and Climat

Blockchain-driven customer order management

Purpose The purpose of this paper is to investigate the effects of Blockchain on the customer order management process and operations. There is limited understanding of the use and benefits of Blockchain on supply chains, and less so at processes level. To date, there is no research on the effects of Blockchain in the customer order management process. Design/methodology/approach A twofold method is followed. First, a Blockchain is programmed and implemented in a large international firm. Second, a series of simulations are built based on three scenarios: current with no-Blockchain, 1-year and 5-year Blockchain use. Findings Blockchain improves the efficiency of the process: it reduces the number of operations, reduces the average time of orders in the system, reduces workload, shows traceability of orders and improves visibility to various supply chain participants. Research limitations/implications The research is based on a single in-depth case that has the scope to be tested in other contexts in future. Practical implications This is the first study that demonstrates with real data from an industrial firm the effects of Blockchain on the efficiency gains, reduction on the number of operations and human-processing savings. A detailed description of the Blockchain implementation is provided. Furthermore, this research shows a list of the resources and capabilities needed for building and maintaining a Blockchain in the context of supply chains. Originality/value This is the first study that demonstrates with real data from an industrial firm the effects of Blockchain on the efficiency gains, the reduction in the number of operations and human-processing savings. A detailed description of the Blockchain implementation is provided. This paper contributes to the resource-based view of the firm, by demonstrating two new competitive valuable capabilities and a new dynamic capability that organisations develop when implementing and using Blockchain in a supply–demand process. It also contributes to the information processing theory by highlighting the analytics capabilities required to sustain Blockchain-related operations. </jats:sec

Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations

We investigated the effects of forest management on the carbon (C) dynamics in Romanian forest soils, using two model simulations: CBM-CFS3 and Yasso15. Default parametrization of the models and harmonized litterfall simulated by CBM provided satisfactory results when compared to observed data from National Forest Inventory (NFI). We explored a stratification approach to investigate the improvement of soil C prediction. For stratification on forest types only, the NRMSE (i.e., normalized RMSE of simulated vs. NFI) was approximately 26%, for both models; the NRMSE values reduced to 13% when stratification was done based on climate only. Assuming the continuation of the current forest management practices for a period of 50 years, both models simulated a very small C sink during simulation period (0.05 MgC ha(-1) yr(-1)). Yet, a change towards extensive forest management practices would yield a constant, minor accumulation of soil C, while more intensive practices would yield a constant, minor loss of soil C. For the maximum wood supply scenario (entire volume increment is removed by silvicultural interventions during the simulated period) Yasso15 resulted in larger emissions (-0.3 MgC ha(-1) yr(-1)) than CBM (-0.1 MgC ha(-1) yr(-1)). Under 'no interventions' scenario, both models simulated a stable accumulation of C which was, nevertheless, larger in Yasso15 (0.35 MgC ha(-1) yr(-1)) compared to CBM-CSF (0.18 MgC ha(-1) yr(-1)). The simulation of C stock change showed a strong "start-up" effect during the first decade of the simulation, for both models, explained by the difference in litterfall applied to each scenario compared to the spinoff scenario. Stratification at regional scale based on climate and forest types, represented a reasonable spatial stratification, that improved the prediction of soil C stock and stock change.Peer reviewe

Organic carbon concentrations and stocks in Romanian mineral forest soils

Estimating soils organic carbon stock and its change in time isan actual concern for scientists and climate change policy makers. Thepresent article firstly focus on determination of C stocks in Romania on forest soil types, as well as development of the spatial distribution mapping using a Geographic Information System (GIS) and also the secondly on the quantification of uncertainty associated with currently available data on C concentration on forest soils geometrical layers. Determination of C stock was done based on forest management plans database created over 2000-2006. Unlike original database, the data for this study was harmonized on following depths: 0-10 cm, 10-20 cm, 20-40 cm, and > 40 cm. Then, the obtained values were grouped by soil types, resulting average values for the main forest soils from Romania. A soil area weighted average value of 137 t/ha is calculated for Romania, in the range of estimationsfor other European geographic and climatic areas. The soils that have the largest amount of organic carbon are andosols, vertisols, entic and haplic podzols, whereas the ones that have the smallest values of organic carbon are solonetz and solonchaks. Although current assessment relies on very large number of samples from the forest management planning database, the variability of C concentration remains very large, ~40-50% for coefficient the variation and ~100% of the average, when defining the range of 95% of entire soil population, rather showing the variability than uncertainty of the average estimated. Best fit for C concentration on geometric layersin any forest soil is asymmetric, associated with log-normal distributions

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy

Carbon implications of forest restitution in post-socialist Romania

The collapse of socialism in 1989 triggered a phase of institutional restructuring in Central and Eastern Europe. Several countries chose to privatize forests or to return them to pre-socialist owners. Here, we assess the implications of forest restitution on the terrestrial The collapse of socialism in 1989 triggered a phase of institutional restructuring in Central and Eastern Europe. Several countries chose to privatize forests or to return them to pre-socialist owners. Here, we assess the implications of forest restitution on the terrestrial carbon balance. New forest owners have strong incentives to immediately clearcut their forests, resulting in increased terrestrial emissions. On the other hand, logging generally decreased after 1989 and forests are expanding on unused or abandoned farmland, both of which may offset increased logging on restituted forests. We mapped changes in forest cover for the entire country of Romania using Landsat satellite images from 1990 to 2010. We use our satellite estimates, together with historic data on logging rates and changes in forest cover, to parameterize a carbon book-keeping model for estimating the terrestrial carbon flux (above and below ground) as a consequence of land use change and forest harvest. High logging rates during socialism resulted in substantial terrestrial carbon emissions and Romania was a net carbon source until the 1980s. After the collapse of the Soviet Union forest harvest rates decreased dramatically, but since restitution laws were implemented they have increased by 60% (from 15 122 ± 5397 ha y − 1 in 2000 to 23 884 ± 11 510 ha y − 1 in 2010), but still remain lower than prior to 1989. Romania currently remains a terrestrial carbon sink, offsetting 7.6% ± 2.5% of anthropogenic carbon emissions. A further increase in logging could result in net emissions from terrestrial ecosystems during the coming decades. However, forest expansion on degraded land and abandoned farmland offers great potential for carbon sequestration. decreased after 1989 and forests are expanding on unused or abandoned farmland, both of which may offset increased logging on restituted forests. We mapped changes in forest cover for the entire country of Romania using Landsat satellite images from 1990 to 2010. We use our satellite estimates, together with historic data on logging rates and changes in forest cover, to parameterize a carbon book-keeping model for estimating the terrestrial carbon flux (above and below ground) as a consequence of land use change and forest harvest. High logging rates during socialism resulted in substantial terrestrial carbon emissions and Romania was a net carbon source until the 1980s. After the collapse of the Soviet Union forest harvest rates decreased dramatically, but since restitution laws were implemented they have increased by 60% (from 15 122 ± 5397 ha y − 1 in 2000 to 23 884 ± 11 510 ha y − 1 in 2010), but still remain lower than prior to 1989. Romania currently remains a terrestrial carbon sink, offsetting 7.6% ± 2.5% of anthropogenic carbon emissions. A further increase in logging could result in net emissions from terrestrial ecosystems during the coming decades. However, forest expansion on degraded land and abandoned farmland offers great potential for carbon sequestration.Peer Reviewe

The Influence of Age, Location and Soil Conditions on the Allometry of Young Norway Spruce (Picea abies L. Karst.) Trees

In this study the influence of tree’s age, location (i.e. latitude and altitude) and soil conditions (i.e. pH, humus content, carbon to nitrogen ratio, cation exchange capacity and percent base saturation) on tree allometry was investigated. The data was collected from 22 Norway spruce (Picea abies L. Karst) plantations located in Eastern Carpathians of Romania, aged between 4 and 15. From each plantation a soil sample and 10 trees were collected for soil chemical properties and biomass measurements, respectively. Root collar diameter (RCD) and height (H) based allometric equations were developed for total tree and vegetative organs of the tree (i.e. stem, branches, needles and roots). Furthermore, the interaction between the standardised residuals of these models and the tested factors was analysed. In order to account for the random effect of the clustered data, the mixed-effect modelling procedure was used. The results have shown no influence of these factors (age, location and soil conditions) on RCD based models, except for branches biomass model which was linked to soil carbon/nitrogen ratio. The H based models, however, were significantly influenced by latitude and soil cation exchange capacity as a consequence of H/RCD ratio change with these factors. The trees were more likely to allocate more to height growth when growing in higher latitudes or on soils with higher values of cation exchange capacity

Site-effects on biomass allometric models for early growth plantations of Norway spruce ( Picea abies (L.) Karst.)

Although it is commonly assumed that biomass allometric models are site specific, evaluations of site-effects are rarely undertaken. In this paper we develop biomass-allometric models to determine site influences. This study is based on data from 240 Norway spruce trees (Picea abies (L.) Karst.), growing in 24 early-growth plantations. A multilevel modelling approach was adopted and intraclass correlation was used to evaluate site effects. Results indicated that biomass allometric models were highly specific to sites and that, depending on the biomass component and the type of predictor adopted, some 33% and 86% of overall model variance could be attributed to forest stand effects. The remaining variance was attributable within stand variability. Stem biomass was the most site-specific biomass component whereas branch biomass was the least influenced by site effects. Diameter at collar height (D) was less site-specific than height (H) in predicting biomass. Using D and H within the same model as distinct predictors, although improving the model fit, increased the model site-specificity. However, when D and H were combined in one predictor expression (i.e. D2H), this reduced model site specificity, despite requiring fewer parameters than other models. This also compensated for undesirable collinearity effects amongst predictor variables. Furthermore, for the sampled diameter range, the site-specificity was mainly driven by biomass allocation pattern (to branches, needles and roots). The considerable between site variability of allometric relationships suggests that consideration of stand effects is essential for the robust prediction of biomass

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q &lt; 0.05). The most strongly upregulated proteins (fold change &gt;1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P &lt; 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.</p