Farm and socio-economic characteristics of smallholder milk producers and their influence on technology adoption in Central Mexico

In order to identify the factors influencing adoption of technologies promoted by government to small-scale dairy farmers in the highlands of central Mexico, a field survey was conducted. A total of 115 farmers were grouped through cluster analysis (CA) and divided into three wealth status categories (high, medium and low) using wealth ranking. Chi-square analysis was used to examine the association of wealth status with technology adoption. Four groups of farms were differentiated in terms of farms’ dimensions, farmers’ education, sources of incomes, wealth status, management of herd, monetary support by government and technological availability. Statistical differences (p < 0.05) were observed in the milk yield per herd per year among groups. Government organizations (GO) participated little in the promotion of the 17 technologies identified, six of which focused on crop or forage production and 11 of which were related to animal husbandry. Relatives and other farmers played an important role in knowledge diffusion and technology adoption. Although wealth status had a significant association (p < 0.05) with adoption, other factors including importance of the technology to farmers, usefulness and productive benefits of innovations together with farmers’ knowledge of them, were important. It is concluded that the analysis of the information per group and wealth status was useful to identify suitable crop or forage related and animal husbandry technologies per group and wealth status of farmers. Therefore the characterizations of farmers could provide a useful starting point for the design and delivery of more appropriate and effective extension.

A green profession? A global survey of RICS members and their engagement with the sustainability agenda

Purpose – This study seeks to provide a review of the background and context to the engagement of RICS members with the sustainability agenda, and to examine the extent to which the surveying profession uses relevant information, tools and techniques to achieve the key objectives of sustainable development (or sustainability). Design/methodology/approach – The paper analyses results from a major international online survey of 4,600 RICS respondent members, supported by 31 structured telephone interviews. Findings – The results suggest that, although sustainability is highly relevant to RICS members’ work, a lack of knowledge and expertise is making it more difficult for sustainability tools and other information to be used effectively. Research limitations/implications – The survey is based on a substantial number of responses which are broadly representative of the global RICS population. A key implication is that “laggard” faculties include the disciplines of commercial property and valuation. Practical implications – The research suggests that key stakeholders must work together to provide better information, guidance and education and training to “hardwire” the sustainability agenda across RICS faculties. Originality/value – This is the first truly global survey of its kind and focuses particularly on those faculties that play a major role in property investment and finance (i.e. valuation and commercial property), comparing their position with that of other faculties in an international context.

A global assessment of the effects of climate policy on the impacts of climate change

This study presents the first global-scale multi-sectoral regional assessment of the magnitude and uncertainty in the impacts of climate change avoided by emissions policies. The analysis suggests that the most stringent emissions policy considered here – which gives a 50% chance of remaining below a 2oC temperature rise target - reduces impacts by 20-65% by 2100 relative to a ‘business-as-usual’ pathway (A1B) which reaches 4oC, and can delay impacts by several decades. Effects vary between sector and region, and there are few noticeable effects of mitigation policy by 2030. The impacts avoided by 2100 are more strongly influenced by the date and level at which emissions peak than the rate of decline of emissions, with an earlier and lower emissions peak avoiding more impacts. The estimated proportion of impacts avoided at the global scale is relatively robust despite uncertainty in the spatial pattern of climate change, but the absolute amount of avoided impacts is considerably more variable and therefore uncertain.

Global warming potentials and radiative efficiencies of halocarbons and related compounds: a comprehensive review

In the mid-1970s it was recognized that, as well as being substances that deplete stratospheric ozone, chlorofluorocarbons (CFCs) were strong greenhouse gases that could have substantial impacts on radiative forcing of climate change. Around a decade later, this group of radiatively active compounds was expanded to include a large number of replacements for ozone-depleting substances such as chlorocarbons, hydrochlorocarbons, hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), bromofluorocarbons, and bromochlorofluorocarbons. This paper systematically reviews the published literature concerning the radiative efficiencies (REs) of CFCs, bromofluorocarbons and bromochlorofluorocarbons (halons), HCFCs, HFCs, PFCs, SF6, NF3, and related halogen containing compounds. In addition we provide a comprehensive and self-consistent set of new calculations of REs and global warming potentials (GWPs) for these compounds, mostly employing atmospheric lifetimes taken from the available literature. We also present Global Temperature change Potentials (GTPs) for selected gases. Infrared absorption spectra used in the RE calculations were taken from databases and individual studies, and from experimental and ab initio computational studies. Evaluations of REs and GWPs are presented for more than 200 compounds. Our calculations yield REs significantly (> 5%) different from those in the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) for 49 compounds. We present new RE values for more than 100 gases which were not included in AR4. A widely-used simple method to calculate REs and GWPs from absorption spectra and atmospheric lifetimes is assessed and updated. This is the most comprehensive review of the radiative efficiencies and global warming potentials of halogenated compounds performed to date.

Recent advances in global electric circuit coupling between the space environment and the troposphere

The global atmospheric electric circuit is driven by thunderstorms and electrified rain/shower clouds and is also influenced by energetic charged particles from space. The global circuit maintains the ionosphere as an equipotential at∼+250 kV with respect to the good conducting Earth (both land and oceans). Its “load” is the fair weather atmosphere and semi-fair weather atmosphere at large distances from the disturbed weather “generator” regions. The main solar-terrestrial (or space weather) influence on the global circuit arises from spatially and temporally varying fluxes of galactic cosmic rays (GCRs) and energetic electrons precipitating from the magnetosphere. All components of the circuit exhibit much variability in both space and time. Global circuit variations between solar maximum and solar minimum are considered together with Forbush decrease and solar flare effects. The variability in ion concentration and vertical current flow are considered in terms of radiative effects in the troposphere, through infra-red absorption, and cloud effects, in particular possible cloud microphysical effects from charging at layer cloud edges. The paper identifies future research areas in relation to Task Group 4 of the Climate and Weather of the Sun-Earth System (CAWSES-II) programme.

Knowledge Interfaces and Practices of Negotiation: Cases from a Women's Group in Bolivia and an Oil Refinery in Wales

This chapter examines encounters between international institutions that frame their objectives through a global policy language, and people whose lives are the focus for change heralded by these institutions. It explores how a global policy language, which seeks consensus and equality, can be at odds with local understandings, conflict and intentions.

TRY: a global database of plant traits

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

The GODAE high resolution sea surface temperature pilot project

Sea surface temperature (SST) measurements are required by operational ocean and atmospheric forecasting systems to constrain modeled upper ocean circulation and thermal structure. The Global Ocean Data Assimilation Experiment (GODAE) High Resolution SST Pilot Project (GHRSST-PP) was initiated to address these needs by coordinating the provision of accurate, high-resolution, SST products for the global domain. The pilot project is now complete, but activities continue within the Group for High Resolution SST (GHRSST). The pilot project focused on harmonizing diverse satellite and in situ data streams that were indexed, processed, quality controlled, analyzed, and documented within a Regional/Global Task Sharing (R/GTS) framework implemented in an internationally distributed manner. Data with meaningful error estimates developed within GHRSST are provided by services within R/GTS. Currently, several terabytes of data are processed at international centers daily, creating more than 25 gigabytes of product. Ensemble SST analyses together with anomaly SST outputs are generated each day, providing confidence in SST analyses via diagnostic outputs. Diagnostic data sets are generated and Web interfaces are provided to monitor the quality of observation and analysis products. GHRSST research and development projects continue to tackle problems of instrument calibration, algorithm development, diurnal variability, skin temperature deviation, and validation/verification of GHRSST products. GHRSST also works closely with applications and users, providing a forum for discussion and feedback between SST users and producers on a regular basis. All data within the GHRSST R/GTS framework are freely available. This paper reviews the progress of GHRSST-PP, highlighting achievements that have been fundamental to the success of the pilot project.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Global estimate of aerosol direct radiative forcing from satellite measurements

Atmospheric aerosols cause scattering and absorption of incoming solar radiation. Additional anthropogenic aerosols released into the atmosphere thus exert a direct radiative forcing on the climate system1. The degree of present-day aerosol forcing is estimated from global models that incorporate a representation of the aerosol cycles1–3. Although the models are compared and validated against observations, these estimates remain uncertain. Previous satellite measurements of the direct effect of aerosols contained limited information about aerosol type, and were confined to oceans only4,5. Here we use state-of-the-art satellitebased measurements of aerosols6–8 and surface wind speed9 to estimate the clear-sky direct radiative forcing for 2002, incorporating measurements over land and ocean. We use a Monte Carlo approach to account for uncertainties in aerosol measurements and in the algorithm used. Probability density functions obtained for the direct radiative forcing at the top of the atmosphere give a clear-sky, global, annual average of 21.9Wm22 with standard deviation, 60.3Wm22. These results suggest that present-day direct radiative forcing is stronger than present model estimates, implying future atmospheric warming greater than is presently predicted, as aerosol emissions continue to decline10.

Dynamic group communication for large-scale parallel data mining

Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

The global effect of follicle-stimulating hormone and tumour necrosis factor α on gene expression in cultured bovine ovarian granulosa cells

Background Oocytes mature in ovarian follicles surrounded by granulosa cells. During follicle growth, granulosa cells replicate and secrete hormones, particularly steroids close to ovulation. However, most follicles cease growing and undergo atresia or regression instead of ovulating. To investigate the effects of stimulatory (follicle-stimulating hormone; FSH) and inhibitory (tumour necrosis factor alpha; TNFα) factors on the granulosa cell transcriptome, bovine ovaries were obtained from a local abattoir and pools of granulosa cells were cultured in vitro for six days under defined serum-free conditions with treatments present on days 3–6. Initially dose–response experiments (n = 4) were performed to determine the optimal concentrations of FSH (0.33 ng/ml) and TNFα (10 ng/ml) to be used for the microarray experiments. For array experiments cells were cultured under control conditions, with FSH, with TNFα, or with FSH plus TNFα (n = 4 per group) and RNA was harvested for microarray analyses. Results Statistical analysis showed primary clustering of the arrays into two groups, control/FSH and TNFα/TNFα plus FSH. The effect of TNFα on gene expression dominated that of FSH, with substantially more genes differentially regulated, and the pathways and genes regulated by TNFα being similar to those of FSH plus TNFα treatment. TNFα treatment reduced the endocrine activity of granulosa cells with reductions in expression of FST, INHA, INBA and AMH. The top-ranked canonical pathways and GO biological terms for the TNFα treatments included antigen presentation, inflammatory response and other pathways indicative of innate immune function and fibrosis. The two most significant networks also reflect this, containing molecules which are present in the canonical pathways of hepatic fibrosis/hepatic stellate cell activation and transforming growth factor β signalling, and these were up regulated. Upstream regulator analyses also predicted TNF, interferons γ and β1 and interleukin 1β. Conclusions In vitro, the transcriptome of granulosa cells responded minimally to FSH compared with the response to TNFα. The response to TNFα indicated an active process akin to tissue remodelling as would occur upon atresia. Additionally there was reduction in endocrine function and induction of an inflammatory response to TNFα that displays features similar to immune cells.

Efficient group communication for large-scale parallel clustering

Global communication requirements and load imbalance of some parallel data mining algorithms are the major obstacles to exploit the computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication cost in iterative parallel data mining algorithms. In particular, the analysis focuses on one of the most influential and popular data mining methods, the k-means algorithm for cluster analysis. The straightforward parallel formulation of the k-means algorithm requires a global reduction operation at each iteration step, which hinders its scalability. This work studies a different parallel formulation of the algorithm where the requirement of global communication can be relaxed while still providing the exact solution of the centralised k-means algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real world distributed applications or can be induced by means of multi-dimensional binary search trees. The approach can also be extended to accommodate an approximation error which allows a further reduction of the communication costs.

Operating models for a multi-polar world: balancing global integration and local responsiveness

Purpose – Multinationals have always needed an operating model that works – an effective plan for executing their most important activities at the right levels of their organization, whether globally, regionally or locally. The choices involved in these decisions have never been obvious, since international firms have consistently faced trade‐offs between tailoring approaches for diverse local markets and leveraging their global scale. This paper seeks a more in‐depth understanding of how successful firms manage the global‐local trade‐off in a multipolar world. Design methodology/approach – This paper utilizes a case study approach based on in‐depth senior executive interviews at several telecommunications companies including Tata Communications. The interviews probed the operating models of the companies we studied, focusing on their approaches to organization structure, management processes, management technologies (including information technology (IT)) and people/talent. Findings – Successful companies balance global‐local trade‐offs by taking a flexible and tailored approach toward their operating‐model decisions. The paper finds that successful companies, including Tata Communications, which is profiled in‐depth, are breaking up the global‐local conundrum into a set of more manageable strategic problems – what the authors call “pressure points” – which they identify by assessing their most important activities and capabilities and determining the global and local challenges associated with them. They then design a different operating model solution for each pressure point, and repeat this process as new strategic developments emerge. By doing so they not only enhance their agility, but they also continually calibrate that crucial balance between global efficiency and local responsiveness. Originality/value – This paper takes a unique approach to operating model design, finding that an operating model is better viewed as several distinct solutions to specific “pressure points” rather than a single and inflexible model that addresses all challenges equally. Now more than ever, developing the right operating model is at the top of multinational executives' priorities, and an area of increasing concern; the international business arena has changed drastically, requiring thoughtfulness and flexibility instead of standard formulas for operating internationally. Old adages like “think global and act local” no longer provide the universal guidance they once seemed to.