Organic certification, export market access and the impacts of policy: Bayesian estimation of avocado smallholder “times-to-organic certification” in Michoacán Mexico

This study analyzes organic adoption decisions using a rich set of time-to-organic durations collected from avocado small-holders in Michoacán Mexico. We derive robust, intrasample predictions about the profiles of entry and exit within the conventional-versus-organic complex and we explore the sensitivity of these predictions to choice of functional form. The dynamic nature of the sample allows us to make retrospective predictions and we establish, precisely, the profile of organic entry had the respondents been availed optimal amounts of adoption-restraining resources. A fundamental problem in the dynamic adoption literature, hitherto unrecognized, is discussed and consequent extensions are suggested.

Typification of four North American club-chollas: the names of four Engelmannian species from Mexico and Southwestern United States

The names Opuntia bulbispina, O. clavata, O. emoryi and O. grahamii, originally proposed by George Engelmann between 1848 and 1856, are reviewed and typified after new findings of previously unknown voucher specimens. Original materials collected by some of the collaborators employed by Engelmann during the Mexican Boundary Survey were discovered in a loan from the Torrey Herbarium at the New York Botanical Garden (NY). Many of the materials include fragments of stems and fruits, and others include only sectioned flowers and some seeds. Particularly good descriptions of the species here concerned were published in Engelmann’s “Synopsis of the Cactaceae” in 1857, and exceptional illustrations were produced by Paulus Roetter and printed in “Cactaceae of the Boundary” in 1859. The problems surrounding some previous typifications of these names range from typification of joint lectotypes to illegitimate typifications of illustrations when original material was known to exist. The materials selected for typification were collected by the Mexican Boundary Survey and are lodged at the herbaria of the Missouri Botanical Garden (MO) and the New York Botanical Garden (NY); some are illustrations published by Engelmann.

Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on smallholder adoption in developing countries

There have been limited recent advances in understanding of what influences uptake of innovations despite the current international focus on smallholder agriculture as a means of achieving food security and rural development. This paper provides a rigorous study of factors influencing adoption by smallholders in central Mexico and builds on findings to identify a broad approach to significantly improve research on and understanding of factors influencing adoption by smallholders in developing countries. Small-scale dairy systems play an important role in providing income, employment and nutrition in the highlands of central Mexico. A wide variety of practices and technologies have been promoted by the government public services to increase milk production and economic efficiency, but there have been very low levels of uptake of most innovations, with the exception of improving grassland through introduction of grass varieties together with management practices. A detailed study was conducted with 80 farmers who are already engaged with the use of this innovation to better understand the process of adoption and identify socioeconomic and farm variables, cognitive (beliefs), and social–psychological (social norms) factors associated with farmers' use of improved grassland. The Theory of Reasoned Action (TRA) was used as a theoretical framework and Spearman Rank Order correlation was conducted to analyse the data. Most farmers (92.5%) revealed strong intention to continue to use improved grassland (which requires active management and investment of resources) for the next 12 months; whereas 7.5% of farmers were undecided and showed weak intention, which was associated with farmers whose main income was from non-farm activities as well as with farmers who had only recently started using improved grassland. Despite farmers' experience of using improved grassland (mean of 18 years) farmers' intentions to continue to adopt it was influenced almost as much by salient referents (mainly male relatives) as by their own attitudes. The hitherto unnoticed longevity of the role social referents play in adoption decisions is an important finding and has implications for further research and for the design of extension approaches. The study demonstrates the value and importance of using TRA or TPB approaches to understand social cognitive (beliefs) and social–psychological (social norms) factors in the study of adoption. However, other factors influencing adoption processes need to be included to provide fuller understanding. An approach that would enable this, and the development of more generalisable findings than from location specific case studies, and contribute to broader conceptualisation, is proposed.

Generation and analysis of the 2005 land cover map for Mexico using 250m MODIS data

Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada, the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover.