Traditional agriculture in transition: examining the impacts of agricultural modernization on smallholder farming in Ghana under the new Green Revolution

Following the renewed effort at achieving a new green revolution for Africa, emphasis has been placed on modernizing smallholder agriculture through the deployment of improved inputs especially mechanized technologies. In Ghana, the government has in the last decade emphasized the provision of subsidized mechanized ploughing services to farmers alongside a rapidly growing private sector tractor service market. While mechanized technology adoption rates have increased rapidly, the deployment of these technologies has been without critical analysis of the impacts on production patterns and local agrarian systems. This paper examines the distributional impacts of agriculture mechanization on cropping patterns and farm sizes of smallholder farmers in northern Ghana using Geographic Information Systems (GIS) techniques, and semi-structured interviews with smallholder farmers (n=60). Specifically, comparative analysis of the field sizes and cropping patterns of participant farmers prior to and after the adoption of mechanized technologies was conducted. In-depth interviews were used to contextualize the experiences of smallholder farmers toward understanding how mechanization may be impacting traditional agriculture. Our findings reveal a mechanization paradox in which farm sizes are expanding, while cropping patterns are shifting away from traditional staple crops (pearl millet and sorghum bicolor) to market-oriented crops (maize, rice and groundnuts). This transition we argue, has adverse implications on the cultural dimension of food security, the organization of social life, and climate change adaptation. We recommend a retooling of the current agricultural policy focus to ensure context sensitivity for a more robust battle against food insecurity.     

Promoting e-mobility in India: challenges,framework, and future roadmap

The purpose of the research is to identify the critical challenges that are impeding the adoption of e-mobility in India. It also aims to give a roadmap how to address these challenges while taking into considerations concerns of all the relevant stakeholders. Based on an in-depth literature review, an exploratory research design is employed to delve deep into various aspects of e-mobility. This is followed by a three-phase Delphi technique to identify and rate the e-mobility challenges in the Indian context. The study successfully identifies four different categories of challenges and proposes integrative framework for e-mobility. Further, the research goes on to lay out the future roadmap for mass adoption of electric vehicles (EVs) in India. The research is novel in terms of presenting a holistic viewpoint on e-mobility in India. Its originality lies in identifying the major inhibitors obstructing EVs adoption in India and then suggesting the roadmap how to overcome these impediments for mass adoption of e-mobility.     

Transition zone in otoliths of orange roughy (Hoplostethus atlanticus) and its relationship to the onset of maturity

A transition zone in the otoliths of orange roughy (Hoplostethus atlanticus) is described where annulus width decreases markedly. For fish sampled at spawning time, the relationship between gonad stage and the presence or absence of a transition zone is consistent with the hypothesis that this zone marks the onset of maturity, if allowance is made for some error in gonad staging and identification of the zone. Another data set from a non-spawning area after the spawning season is not consistent with the hypothesis. However, these latter data are considered less reliable because of the small size of the fish in the sample and difficulties in determining, outside the spawning season, whether a fish has been reproductively active. This hypothesis was used to provide estimates of the median age (30 yr) and length (31 cm) at the onset of maturity for the Chatham Rise, New Zealand population. These estimates are unaffected by the biases associated with the usual ogive method of estimation. Received: 27 June 1997 / Accepted: 1 July 1997     

The Spatiotemporal Pattern of Fires in Northern Taiga Larch Forests of Central Siberia

The periodicity of fires in larch forests of Evenkia and their relationship with landscape elements have been studied. Cross-sections with “burns” in them caused by past fires have been analyzed in 72 test plots; the fire chronology encompassed the period from the 15th to the 20th century. The between-fire intervals (BFIs) have been calculated by two methods: (I) on the basis of burns alone and (II) on the basis of burns and the start of growth of the new generation of larch after the earliest fire. The BFI depends on local orographic features; it is 86 ± 11 (105 ± 12), 61 ± 8 (73 ± 8), 139 ± 17 (138 ± 18), and 68 ± 14 (70 ± 13) years for northeastern slopes, southwestern slopes, bogs, and flatlands, respectively. The mean BFIs calculated by methods I and II are 82 ± 7 and 95 ± 7 years, respectively. The permafrost horizon rises at a mean rate of 0.3 cm per year after a forest fire. It has been shown that the number of fires regularly peaks at periods of 36 and 82 years. There is also a temporal trend in fire frequency: the mean BFI was approximately 100 years in the 19th century and 65 years in the 20th century.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.