Toward a protocol for quantifying the greenhouse gas balance and identifying mitigation options in smallholder farming systems

Globally, agriculture is directly responsible for 14% of annual greenhouse gas (GHG) emissions and induces an additional 17% through land use change, mostly in developing countries (Vermeulen et al 2012). Agricultural intensification and expansion in these regions is expected to catalyze the most significant relative increases in agricultural GHG emissions over the next decade (Smith et al 2008, Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa and Asia are predominately managed by smallholders, with 80% of land holdings smaller than ten hectares (FAO 2012). One can therefore posit that smallholder farming significantly impacts the GHG balance of these regions today and will continue to do so in the near future. However, our understanding of the effect smallholder farming has on the Earth's climate system is remarkably limited. Data quantifying existing and reduced GHG emissions and removals of smallholder production systems are available for only a handful of crops, livestock, and agroecosystems (Herrero et al 2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteen studies of nitrous oxide emissions from soils have taken place in sub-Saharan Africa, leaving the rate of emissions virtually undocumented. Due to a scarcity of data on GHG sources and sinks, most developing countries currently quantify agricultural emissions and reductions using IPCC Tier 1 emissions factors. However, current Tier 1 emissions factors are either calibrated to data primarily derived from developed countries, where agricultural production conditions are dissimilar to that in which the majority of smallholders operate, or from data that are sparse or of mixed quality in developing countries (IPCC 2006). For the most part, there are insufficient emissions data characterizing smallholder agriculture to evaluate the level of accuracy or inaccuracy of current emissions estimates. Consequentially, there is no reliable information on the agricultural GHG budgets for developing economies. This dearth of information constrains the capacity to transition to low-carbon agricultural development, opportunities for smallholders to capitalize on carbon markets, and the negotiating position of developing countries in global climate policy discourse. Concerns over the poor state of information, in terms of data availability and representation, have fueled appeals for new approaches to quantifying GHG emissions and removals from smallholder agriculture, for both existing conditions and mitigation interventions (Berry and Ryan 2013, Olander et al 2013). Considering the dependence of quantification approaches on data and the current data deficit for smallholder systems, it is clear that in situ measurements must be a core part of initial and future strategies to improve GHG inventories and develop mitigation measures for smallholder agriculture. Once more data are available, especially for farming systems of high priority (e.g., those identified through global and regional rankings of emission hotspots or mitigation leverage points), better cumulative estimates and targeted actions will become possible. Greenhouse gas measurements in agriculture are expensive, time consuming, and error prone. These challenges are exacerbated by the heterogeneity of smallholder systems and landscapes and the diversity of methods used. Concerns over methodological rigor, measurement costs, and the diversity of approaches, coupled with the demand for robust information suggest it is germane for the scientific community to establish standards of measurements—'a protocol'—for quantifying GHG emissions from smallholder agriculture. A standard protocol for use by scientists and development organizations will help generate consistent, comparable, and reliable data on emissions baselines and allow rigorous comparisons of mitigation options. Besides enhancing data utility, a protocol serves as a benchmark for non-experts to easily assess data quality. Obviously many such protocols already exist (e.g., GraceNet, Parkin and Venterea 2010). None, however, account for the diversity and complexity of smallholder agriculture, quantify emissions and removals from crops, livestock, and biomass together to calculate the net balance, or are adapted for the research environment of developing countries; conditions that warrant developing specific methods. Here we summarize an approach being developed by the Consultative Group on International Agricultural Research's (CGIAR) Climate Change, Agriculture, and Food Security Program (CCAFS) and partners. The CGIAR-CCAFS smallholder GHG quantification protocol aims to improve quantification of baseline emission levels and support mitigation decisions. The protocol introduces five novel quantification elements relevant for smallholder agriculture (figure 1). First, it stresses the systematic collection of 'activity data' to describe the type, distribution, and extent of land management activities in landscapes cultivated by smallholder. Second, it advocates an informed sampling approach that concentrates measurement activities on emission hotspots and leverage points to capture heterogeneity and account for the diversity and complexity of farming activities. Third, it quantifies emissions at multiple spatial scales, whole-farm and landscape, to provide information targeted to household and communities decisions. Fourth, it encourages GHG research to document farm productivity and economics in addition to emissions, in recognition of the importance of agriculture to livelihoods. Fifth, it develops cost-differentiated measurement solutions that optimize the relationships among scale, cost, and accuracy. Each of the five innovations is further described in the main article

A Categorical Equivalence between Generalized Holonomy Maps on a Connected Manifold and Principal Connections on Bundles over that Manifold

A classic result in the foundations of Yang-Mills theory, due to J. W. Barrett ["Holonomy and Path Structures in General Relativity and Yang-Mills Theory." Int. J. Th. Phys. 30(9), (1991)], establishes that given a "generalized" holonomy map from the space of piece-wise smooth, closed curves based at some point of a manifold to a Lie group, there exists a principal bundle with that group as structure group and a principal connection on that bundle such that the holonomy map corresponds to the holonomies of that connection. Barrett also provided one sense in which this "recovery theorem" yields a unique bundle, up to isomorphism. Here we show that something stronger is true: with an appropriate definition of isomorphism between generalized holonomy maps, there is an equivalence of categories between the category whose objects are generalized holonomy maps on a smooth, connected manifold and whose arrows are holonomy isomorphisms, and the category whose objects are principal connections on principal bundles over a smooth, connected manifold. This result clarifies, and somewhat improves upon, the sense of "unique recovery" in Barrett's theorems; it also makes precise a sense in which there is no loss of structure involved in moving from a principal bundle formulation of Yang-Mills theory to a holonomy, or "loop", formulation.Comment: 20 page

Kinetics of stochastically-gated diffusion-limited reactions and geometry of random walk trajectories

In this paper we study the kinetics of diffusion-limited, pseudo-first-order A + B -> B reactions in situations in which the particles' intrinsic reactivities vary randomly in time. That is, we suppose that the particles are bearing "gates" which interchange randomly and independently of each other between two states - an active state, when the reaction may take place, and a blocked state, when the reaction is completly inhibited. We consider four different models, such that the A particle can be either mobile or immobile, gated or ungated, as well as ungated or gated B particles can be fixed at random positions or move randomly. All models are formulated on a $d$-dimensional regular lattice and we suppose that the mobile species perform independent, homogeneous, discrete-time lattice random walks. The model involving a single, immobile, ungated target A and a concentration of mobile, gated B particles is solved exactly. For the remaining three models we determine exactly, in form of rigorous lower and upper bounds, the large-N asymptotical behavior of the A particle survival probability. We also realize that for all four models studied here such a probalibity can be interpreted as the moment generating function of some functionals of random walk trajectories, such as, e.g., the number of self-intersections, the number of sites visited exactly a given number of times, "residence time" on a random array of lattice sites and etc. Our results thus apply to the asymptotical behavior of the corresponding generating functions which has not been known as yet.Comment: Latex, 45 pages, 5 ps-figures, submitted to PR

Insulin and IGF-1 improve mitochondrial function in a PI-3K/Akt-dependent manner and reduce mitochondrial generation of reactive oxygen species in Huntington’s disease knock-in striatal cells

Akt, protein kinase B; ARE, antioxidant response element; Erk, extracellular signal-regulated kinase; CBP, CREB-binding protein; CREB, cAMP response-element (CRE) binding protein; CDK, cyclin-dependent kinase; DHE, dihydroethidium; Drp1, dynamin-related protein 1 or dynamin 1-like (DNM1L); GCL, glutamate-cysteine ligase; GCLc, glutamate-cysteine catalytic subunit; GPx, glutathione peroxidase; GSH, glutathione, reduced form; GSSG, glutathione oxidized form; IGF-1, Insulin-like growth factor 1; IGF1R, insulin-like growth factor 1 receptor; IR, insulin receptor; IRS, insulin receptor substrate; H2DCFDA, 2′,7′-dichlorodihydrofluorescein diacetate; HKII, hexokinase type II; HD, Huntington’s disease; HO-1, heme oxygenase; Hsp60, heat shock 60 kDa protein 1 (chaperonin); mHtt, mutant huntingtin; mtDNA, mitochondrial DNA; MT-COII, mitochondrial-encoded cytochrome c oxidase II; mTOR, mammalian target of rapamycin; NDUFS3, NADH dehydrogenase (ubiquinone) Fe–S protein 3, 30 kDa (NADH-coenzyme Q reductase); NQO1, NAD(P)H dehydrogenase [quinone] 1; Nrf2, nuclear factor (erythroid-derived 2)-like 2; PI-3K, phosphatidylinositol 3-kinase; PGC-1α, peroxisome proliferator-activated receptor-γ coactivator 1α; ROS, reactive oxygen species; SDHA, succinate dehydrogenase complex, subunit A, flavoprotein (Fp); SOD, superoxide dismutase; Tfam, transcription factor A, mitochondrial; TMRM, tetramethylrhodamine methyl ester; Tom20, translocase of outer mitochondrial membrane 20 homolog (yeast); Tom40, translocase of outer mitochondrial membrane 40 homolog (yeast)

The roots of "Western European societal evolution". A concept of Europe by Jenő Szűcs

Jenő Szűcs wrote his essay entitled Sketch on the three regions of Europe in the early 1980s in Hungary. During these years, a historically well-argued opinion emphasising a substantial difference between Central European and Eastern European societies was warmly received in various circles of the political opposition. In a wider European perspective Szűcs used the old “liberty topos” which claims that the history of Europe is no other than the fulfillment of liberty. In his Sketch, Szűcs does not only concentrate on questions concerning the Middle Ages in Western Europe. Yet it is this stream of thought which brought a new perspective to explaining European history. His picture of the Middle Ages represents well that there is a way to integrate all typical Western motifs of post-war self-definition into a single theory. Mainly, the “liberty motif”, as a sign of “Europeanism” – in the interpretation of Bibó’s concept, Anglo-saxon Marxists and Weber’s social theory –, developed from medieval concepts of state and society and from an analysis of economic and social structures. Szűcs’s historical aspect was a typical intellectual product of the 1980s: this was the time when a few Central European historians started to outline non-Marxist aspects of social theory and categories of modernisation theories, but concealing them with Marxist terminology