Spatial patterns of tree yield explained by endogenous forces through a correspondence between the Ising model and ecology.

Spatial patterning of periodic dynamics is a dramatic and ubiquitous ecological phenomenon arising in systems ranging from diseases to plants to mammals. The degree to which spatial correlations in cyclic dynamics are the result of endogenous factors related to local dynamics vs. exogenous forcing has been one of the central questions in ecology for nearly a century. With the goal of obtaining a robust explanation for correlations over space and time in dynamics that would apply to many systems, we base our analysis on the Ising model of statistical physics, which provides a fundamental mechanism of spatial patterning. We show, using 5 y of data on over 6,500 trees in a pistachio orchard, that annual nut production, in different years, exhibits both large-scale synchrony and self-similar, power-law decaying correlations consistent with the Ising model near criticality. Our approach demonstrates the possibility that short-range interactions can lead to long-range correlations over space and time of cyclic dynamics even in the presence of large environmental variability. We propose that root grafting could be the common mechanism leading to positive short-range interactions that explains the ubiquity of masting, correlated seed production over space through time, by trees

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

Limits of agricultural greenhouse gas calculators to predict soil N2O and CH4 fluxes in tropical agriculture

Acknowledgements This work was undertaken as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), which is a strategic partnership of CGIAR and Future Earth. This research was carried out with funding by the European Union (EU) and with technical support from the International Fund for Agricultural Development (IFAD). The UN FAO Mitigation of Climate Change in Agriculture (MICCA) Programme funded data collection in Kenya and Tanzania. The views expressed in the document cannot be taken to reflect the official opinions of CGIAR, Future Earth, or donors. We thank Louis Bockel of the UN FAO Agricultural Development Economics Division (ESA) for his comments on an earlier draft of the manuscript.Peer reviewedPublisher PD

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

Number of Common Sites Visited by N Random Walkers

We compute analytically the mean number of common sites, W_N(t), visited by N independent random walkers each of length t and all starting at the origin at t=0 in d dimensions. We show that in the (N-d) plane, there are three distinct regimes for the asymptotic large t growth of W_N(t). These three regimes are separated by two critical lines d=2 and d=d_c(N)=2N/(N-1) in the (N-d) plane. For d<2, W_N(t)\sim t^{d/2} for large t (the N dependence is only in the prefactor). For 2<d<d_c(N), W_N(t)\sim t^{\nu} where the exponent \nu= N-d(N-1)/2 varies with N and d. For d>d_c(N), W_N(t) approaches a constant as t\to \infty. Exactly at the critical dimensions there are logaritmic corrections: for d=2, we get W_N(t)\sim t/[\ln t]^N, while for d=d_c(N), W_N(t)\sim \ln t for large t. Our analytical predictions are verified in numerical simulations.Comment: 5 pages, 3 .eps figures include

Acceptability of temporary suspension of visiting during norovirus outbreaks:investigating patient, visitor and public opinion

Background Noroviruses are a leading cause of outbreaks globally and the most common cause of service disruption due to ward closures. Temporary suspension of visiting (TSV) is increasingly a recommended public health measure to reduce exposure, transmission and impact during norovirus outbreaks; however, preventing patient–visitor contact may contravene the ethos of person-centred care, and public acceptability of this measure is not known. Aim To investigate the acceptability of TSV during norovirus outbreaks from the perspectives of patients, visitors and the wider public. Methods Cross-sectional survey of patients (N = 153), visitors (N = 175) and the public (N = 224) in three diverse areas in Scotland. Health Belief Model constructs were applied to understand ratings of acceptability of TSV during norovirus outbreaks, and to determine associations between these levels and various predictor variables. Findings The majority (84.6%) of respondents indicated that the possible benefits of TSV are greater than the possible disadvantages. Conversely, the majority (70%) of respondents disagreed that TSV ‘is wrong as it ignores people's rights to have contact with family and friends’. The majority (81.6%) of respondents agreed that TSV would be more acceptable if exceptions were made for seriously ill or dying patients. Correlational analysis demonstrated that overall acceptability was positively related to perceived severity (r = 0.65), identified benefits (r = 0.54) and implementing additional communication strategies (r = 0.60); acceptability was negatively related to potential barriers (r = −0.49). Conclusions There is greater service user and public support for the use of TSV than concerns around impinging upon patients' rights to have visitors. TSV should be considered as an acceptable infection control measure that could be implemented consistently during norovirus outbreaks