The incentive gap: LULUCF and the Kyoto mechanism before and after Durban

To-date, forest resource-based carbon accounting in land use, land use change and forestry (LULUCF) under the United Nations Framework Convention on Climate Change (UNFCCC), Kyoto Protocol (KP), European Union (EU) and national level emission reduction schemes considers only a fraction of its potential and fails to adequately mobilize the LULUCF sector for the successful stabilization of atmospheric greenhouse gas (GHG) concentrations. Recent modifications at the 2011 COP17 meetings in Durban have partially addressed this basic problem, but leave room for improvement. The presence of an Incentive Gap (IG) continues to justify reform of the LULUCF carbon accounting framework. Frequently neglected in the climate change mitigation and adaptation literature, carbon accounting practices ultimately define the nuts and bolts of what counts and which resources (forest, forest-based or other) are favored and utilized. For Annex I countries in the Kyoto Mechanism, the Incentive Gap under forest management (FM) is significantly large: some 75% or more of potential forestry-based carbon sequestration is not effectively incentivized or mobilized for climate change mitigation and adaptation (Ellison etal. 2011a). In this paper, we expand our analysis of the Incentive Gap to incorporate the changes agreed in Durban and encompass both a wider set of countries and a larger set of omitted carbon pools. For Annex I countries, based on the first 2years of experience in the first Commitment Period (CP1) we estimate the IG in FM at approximately 88%. Though significantly reduced in CP2, the IG remains a problem. Thus our measure of missed opportunities under the Kyoto and UNFCCC framework - despite the changes in Durban - remains important. With the exception perhaps of increased energy efficiency, few sinks or sources of reduced emissions can be mobilized as effectively and efficiently as forests. Thus, we wonder at the sheer magnitude of this underutilized resource

Assessment of Forest Biomass and Carbon Stocks at Stand Level Using Site-Specific Primary Data to Support Forest Management

To quantify and map woody biomass (WB) and forest carbon (C) stocks, several models were developed. They differ in terms of scale of application, details related to the input data required and outputs provided. Local Authorities, such as Mountain Communities, can be supported in sustainable forest planning and management by providing specific models in which the reference unit is the same as the one reported in the Forest Management Plans (FMP), i.e. the forest stand. In the Lombardy Region (Northern Italy), a few studies were performed to assess WB and forest C stocks, and they were generally based on data coming from regional\u2014or national\u2014forest inventories and remote sensing, without taking into account data collected in the FMPs. For this study, the first version of the stand-level model \u201cWOody biomass and Carbon ASsessment\u201d (WOCAS) for WB and C stocks calculation was improved into a second version (WOCAS v2) and preliminary results about its first application to 2019 forest stands of Valle Camonica District (Lombardy Region) are presented. Since the model WOCAS uses the growing stock as the main driver for the calculation, it can be applied in any other forest area where the same input data are available

Dealing with locally-driven degradation: A quick start option under REDD+

The paper reviews a number of challenges associated with reducing degradation and its related emissions through national approaches to REDD+ under UNFCCC policy. It proposes that in many countries, it may in the short run be easier to deal with the kinds of degradation that result from locally driven community over-exploitation of forest for livelihoods, than from selective logging or fire control. Such degradation is low-level, but chronic, and is experienced over very large forest areas. Community forest management programmes tend to result not only in reduced degradation, but also in forest enhancement; moreover they are often popular, and do not require major political shifts. In principle these approaches therefore offer a quick start option for REDD+. Developing reference emissions levels for low-level locally driven degradation is difficult however given that stock losses and gains are too small to be identified and measured using remote sensing, and that in most countries there is little or no forest inventory data available. We therefore propose that forest management initiatives at the local level, such as those promoted by community forest management programmes, should monitor, and be credited for, only the net increase in carbon stock over the implementation period, as assessed by ground level surveys at the start and end of the period. This would also resolve the problem of nesting (ensuring that all credits are accounted for against the national reference emission level), since communities and others at the local level would be rewarded only for increased sequestration, while the national reference emission level would deal only with reductions in emissions from deforestation and degradation

Quantifying the effectiveness of climate change mitigation through forest plantations and carbon sequestration with an integrated land-use model

<p>Abstract</p> <p>Background</p> <p>Carbon plantations are introduced in climate change policy as an option to slow the build-up of atmospheric carbon dioxide (CO₂) concentrations. Here we present a methodology to evaluate the potential effectiveness of carbon plantations. The methodology explicitly considers future long-term land-use change around the world and all relevant carbon (C) fluxes, including all natural fluxes. Both issues have generally been ignored in earlier studies.</p> <p>Results</p> <p>Two different baseline scenarios up to 2100 indicate that uncertainties in future land-use change lead to a near 100% difference in estimates of carbon sequestration potentials. Moreover, social, economic and institutional barriers preventing carbon plantations in natural vegetation areas decrease the physical potential by 75–80% or more.</p> <p>Nevertheless, carbon plantations can still considerably contribute to slowing the increase in the atmospheric CO₂concentration but only in the long term. The most conservative set of assumptions lowers the increase of the atmospheric CO₂concentration in 2100 by a 27 ppm and compensates for 5–7% of the total energy-related CO₂emissions. The net sequestration up to 2020 is limited, given the short-term increased need for agricultural land in most regions and the long period needed to compensate for emissions through the establishment of the plantations. The potential is highest in the tropics, despite projections that most of the agricultural expansion will be in these regions. Plantations in high latitudes as Northern Europe and Northern Russia should only be established if the objective to sequester carbon is combined with other activities.</p> <p>Conclusion</p> <p>Carbon sequestration in plantations can play an important role in mitigating the build-up of atmospheric CO₂. The actual magnitude depends on natural and management factors, social barriers, and the time frame considered. In addition, there are a number of ancillary benefits for local communities and the environment. Carbon plantations are, however, particularly effective in the long term. Furthermore, plantations do not offer the ultimate solution towards stabilizing CO₂concentrations but should be part of a broader package of options with clear energy emission reduction measures.</p

Monitoring and modelling landscape dynamics

International audienceChanges in land cover and land use are among the most pervasive and important sources of recent alterations of the Earth's land surface.This special issue also presents new directions in modelling landscape dynamics. Agent-based models have primarily been used to simulate local land use and land cover changes processes with a focus on decision making (Le 2008; Matthews et al. 2007; Parker et al. 2003; Bousquet and Le Page 2001)

Contributions of nitrogen deposition and forest regrowth to terrestrial carbon uptake

<p>Abstract</p> <p>Background</p> <p>The amount of reactive nitrogen deposited on land has doubled globally and become at least five-times higher in Europe, Eastern United States, and South East Asia since 1860 mostly because of increases in fertilizer production and fossil fuel burning. Because vegetation growth in the Northern Hemisphere is typically nitrogen-limited, increased nitrogen deposition could have an attenuating effect on rising atmospheric CO₂by stimulating the vegetation productivity and accumulation of carbon in biomass.</p> <p>Results</p> <p>This study shows that elevated nitrogen deposition would not significantly enhance land carbon uptake unless we consider its effects on re-growing forests. Our results suggest that nitrogen enriched land ecosystems sequestered 0.62–2.33 PgC in the 1980s and 0.75–2.21 PgC in the 1990s depending on the proportion and age of re-growing forests. During these two decades land ecosystems are estimated to have absorbed 13–41% of carbon emitted by fossil fuel burning.</p> <p>Conclusion</p> <p>Although land ecosystems and especially forests with lifted nitrogen limitations have the potential to decelerate the rise of CO₂concentrations in the atmosphere, the effect is only significant over a limited period of time. The carbon uptake associated with forest re-growth and amplified by high nitrogen deposition will decrease as soon as the forests reach maturity. Therefore, assessments relying on carbon stored on land from enhanced atmospheric nitrogen deposition to balance fossil fuel emissions may be inaccurate.</p

Forest carbon sequestration:the impact of forest management

In this chapter, we describe alternative ways in which forests and forestry can help to mítigate climate change, along with the potential impact of these activities. The three carbon storage compartments should be considered inall impact estimates. Carbon content in living biomass is easily estimated via species-specific equations or by applying factors to oven-dry biomass weights (e.g.,lbañez et al.,2002, Herrero et al.,2011,Castaño and Bravo, 2012).Litter carbon content has been analysed in many studies on primary forest productivity, though information regarding the influence of forest management on litter carbon content is less abundant (Blanco et al., 2006). In the last decade,efforts have been made to assess soil carbon in forests, but studies on the effect of forest management on soils show discrepancies (Lindner and Karjalainen,2007).Hoover (2011), for example,found no difference in forest floor carbon stocks among stands subjected to partial or complete harvest treatments in the United States.Instituto Universitario de Gestión Forestal Sostenibl

Orientation-dependent backbone-only residue pair scoring functions for fixed backbone protein design

<p>Abstract</p> <p>Background</p> <p>Empirical scoring functions have proven useful in protein structure modeling. Most such scoring functions depend on protein side chain conformations. However, backbone-only scoring functions do not require computationally intensive structure optimization and so are well suited to protein design, which requires fast score evaluation. Furthermore, scoring functions that account for the distinctive relative position and orientation preferences of residue pairs are expected to be more accurate than those that depend only on the separation distance.</p> <p>Results</p> <p>Residue pair scoring functions for fixed backbone protein design were derived using only backbone geometry. Unlike previous studies that used spherical harmonics to fit 2D angular distributions, Gaussian Mixture Models were used to fit the full 3D (position only) and 6D (position and orientation) distributions of residue pairs. The performance of the 1D (residue separation only), 3D, and 6D scoring functions were compared by their ability to identify correct threading solutions for a non-redundant benchmark set of protein backbone structures. The threading accuracy was found to steadily increase with increasing dimension, with the 6D scoring function achieving the highest accuracy. Furthermore, the 3D and 6D scoring functions were shown to outperform side chain-dependent empirical potentials from three other studies. Next, two computational methods that take advantage of the speed and pairwise form of these new backbone-only scoring functions were investigated. The first is a procedure that exploits available sequence data by averaging scores over threading solutions for homologs. This was evaluated by applying it to the challenging problem of identifying interacting transmembrane alpha-helices and found to further improve prediction accuracy. The second is a protein design method for determining the optimal sequence for a backbone structure by applying Belief Propagation optimization using the 6D scoring functions. The sensitivity of this method to backbone structure perturbations was compared with that of fixed-backbone all-atom modeling by determining the similarities between optimal sequences for two different backbone structures within the same protein family. The results showed that the design method using 6D scoring functions was more robust to small variations in backbone structure than the all-atom design method.</p> <p>Conclusions</p> <p>Backbone-only residue pair scoring functions that account for all six relative degrees of freedom are the most accurate and including the scores of homologs further improves the accuracy in threading applications. The 6D scoring function outperformed several side chain-dependent potentials while avoiding time-consuming and error prone side chain structure prediction. These scoring functions are particularly useful as an initial filter in protein design problems before applying all-atom modeling.</p