Recognizing and realizing the potential of organic agriculture in Kenya

Formal organic agriculture in Kenya dates back to the early eighties when the first pioneer organic training institutions were established. During the same period, a few horticultural companies started growing organic vegetables for export. Initial efforts to promote organic agriculture in Kenya were made by rural development non-governmental organizations (NGOs), faith based organizations and community based organizations (CBOs). They seek to help rural farmers in addressing the issue of declining agricultural productivity (especially the degradation of soils and natural resource base), high poverty incidences, food insecurity and low incomes which pre-vented farmers from assessing high costs inputs. Currently Kenya has five major players in organic agriculture namely Kitale-based Manor House Agricultural Center, Baraka College in Molo, the Sustainable Agriculture Community Development Pro-gram in Thika, the Kenya Institute of Organic Farming (KIOF), a training center on the outskirts Kenya’s capital Nairobi, and the Association for Better Land Husbandry (ABLH), headquartered in Nairobi. The organic sector is relatively small; however, it is growing very fast, led mainly by NGOs and private sector (companies growing organic produce for export). Exports of organic products have been taking place for the last two decades, mainly with vegetables and fruits produced on large scale farms. Over the years exports have developed beyond vegetables and fruits to include other prod-ucts such as essential oils, dried herbs and spices as well as products for the cos-metic and pharmaceutical industries which are more often produced by smallholders. Currently, there are five international certifiers operating in Kenya, namely: the Soil Association (SA), EcoCert International; IMO (Institute for Market Ecology); USDA’s (United States Department of Agriculture) National Organic Programme (NOP) and Bio Suisse

Using the Twentieth Century Reanalysis to assess climate variability for the European wind industry

We characterise the long-term variability of European near-surface wind speeds using 142 years of data from the Twentieth Century Reanalysis (20CR), and consider the potential of such long-baseline climate data sets for wind energy applications. The low resolution of the 20CR would severely restrict its use on its own for wind farm site-screening. We therefore perform a simple statistical calibration to link it to the higher-resolution ERA-Interim data set (ERAI), such that the adjusted 20CR data has the same wind speed distribution at each location as ERAI during their common period. Using this corrected 20CR data set, wind speeds and variability are characterised in terms of the long-term mean, standard deviation, and corresponding trends. Many regions of interest show extremely weak trends on century timescales, but contain large multidecadal variability. Since reanalyses such as ERAI are often used to provide the background climatology for wind farm site assessments, but contain only a few decades of data, our results can be used as a way of incorporating decadal-scale wind climate variability into such studies, allowing investment risks for wind farms to be reduced.Comment: 18 pages, plus 4 page supplementary information included here as Appendix D. This is the authors' corrected version, matching the content of the version accepted by Theoretical and Applied Climatolog

Characterization of smallholder farmers and agricultural credit institutions in Rwanda

The significance of access to agricultural credit in perpetuating agricultural productivity is unquestionable, because it is a means to achieving optimal productivity. The minimization of any barriers to agricultural credit access should, thus, be a global priority. One of the most significant and current barriers to agricultural credit access is information asymmetry which results into mutual distrust between lending institutions and  borrowers in this case the smallholder farmers. To address information asymmetry, both the lending institutions and borrowers need to have definitive descriptive information about either party. Without the profiling of institutions and potential borrowers, an information gap persists, thereby increasing mutual distrust. This study addresses that gap, in the context of Rwanda by characterizing smallholder farmers and agricultural credit institutions. A cross-sectional survey design was used in this study with smallholder farmers and staff in agricultural credit institutions in the Eastern, Western, and Central provinces of Rwanda as the units of analysis. A multistage sampling procedure was used, with stratified sampling of administrative levels spanning from province (stage 1) to districts (stage 2) and sectors (stage 3), followed by a simple random sampling of cells per sector, and the convenience sample of households. Staff in the financial institutions were purposively sampled. The data collected was analyzed using principal component analysis and cluster analysis with the K-means statistic (SPSS version 25). The largest cluster of smallholder farmers has the following characteristics:  household size of 1 to 5 people, farmers with education, owning arable land not exceeding a hectare, with more than five years of farming experience, earning from other off-farm activities, with no dependents under five years of age, and renting less than an acre of land. As for agricultural credit institutions, the largest cluster has following compositions: have mechanisms or measures established for managing loan defaults with the  majority using refinancing, rescheduling, and collateral release, with variable loan payback options, and provide targeted agricultural credit to farmers such as agricultural input premium. The research findings are particularly pertinent for maize- and rice-growing farmers, and how to reduce the information gap and the implications of broadening access to credit to smallholder farmers were discussed. This study emphasizes the need for characterization for both parties to be better informed about the characteristics and dynamics of each other, all in a bid to lessen asymmetric information and thus improve access to credit

The Mass Profile and Accretion History of Cold Dark Matter Halos

We use the Millennium Simulation series to study the relation between the accretion history (MAH) and mass profile of cold dark matter halos. We find that the mean density within the scale radius, r_{-2} (where the halo density profile has isothermal slope), is directly proportional to the critical density of the Universe at the time when the main progenitor's virial mass equals the mass enclosed within r_{-2}. Scaled to these characteristic values of mass and density, the mean MAH, expressed in terms of the critical density of the Universe, M(\rho_{crit}(z)), resembles that of the enclosed density profile, M(), at z=0. Both follow closely the NFW profile, suggesting that the similarity of halo mass profiles originates from the mass-independence of halo MAHs. Support for this interpretation is provided by outlier halos whose accretion histories deviate from the NFW shape; their mass profiles show correlated deviations from NFW and are better approximated by Einasto profiles. Fitting both M() and M(\rho_{crit}) with either NFW or Einasto profiles yield concentration and shape parameters that are correlated, confirming and extending earlier work linking the concentration of a halo with its accretion history. These correlations also confirm that halo structure is insensitive to initial conditions: only halos whose accretion histories differ greatly from the NFW shape show noticeable deviations from NFW in their mass profiles. As a result, the NFW profile provides acceptable fits to hot dark matter halos, which do not form hierarchically, and for fluctuation power spectra other than CDM. Our findings, however, predict a subtle but systematic dependence of mass profile shape on accretion history which, if confirmed, would provide strong support for the link between accretion history and halo structure we propose here.Comment: 12 pages, 8 figures, MNRAS 432 1103L (2013

Intrinsic galaxy shapes and alignments I: Measuring and modelling COSMOS intrinsic galaxy ellipticities

The statistical properties of the ellipticities of galaxy images depend on how galaxies form and evolve, and therefore constrain models of galaxy morphology, which are key to the removal of the intrinsic alignment contamination of cosmological weak lensing surveys, as well as to the calibration of weak lensing shape measurements. We construct such models based on the halo properties of the Millennium Simulation and confront them with a sample of 90,000 galaxies from the COSMOS Survey, covering three decades in luminosity and redshifts out to z=2. The ellipticity measurements are corrected for effects of point spread function smearing, spurious image distortions, and measurement noise. Dividing galaxies into early, late, and irregular types, we find that early-type galaxies have up to a factor of two lower intrinsic ellipticity dispersion than late-type galaxies. None of the samples shows evidence for redshift evolution, while the ellipticity dispersion for late-type galaxies scales strongly with absolute magnitude at the bright end. The simulation-based models reproduce the main characteristics of the intrinsic ellipticity distributions although which model fares best depends on the selection criteria of the galaxy sample. We observe fewer close-to-circular late-type galaxy images in COSMOS than expected for a sample of randomly oriented circular thick disks and discuss possible explanations for this deficit.Comment: 18 pages, 8 figures; updated simulations and galaxy sample definition, more galaxy samples analysed; matches version published in MNRA