Agriculture for Developing Nations

Bray, Francesca

doi:10.1038/scientificamerican0794-30

Cited by 33 publications

(7 citation statements)

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“…The answer to this is facilitated by the fine-scale and detailed soils research and agricultural undertaken in the Belize River area published in the 1970s (Jenkin et al 1976;Birchall and Jenkin 1979). This agricultural assessment was undertaken within the context of a development scheme promoted by the United Kingdom and consistent with the United States for emerging economies since the last half of the twentieth century (Boserup 1965;Bray 1994;see also Fukuoka 1978;Mollison 1988;Nash 2007).…”

Section: Discussionmentioning

confidence: 99%

Modeling Settlement Patterns of the Late Classic Maya Civilization with Bayesian Methods and Geographic Information Systems

Ford

Clarke

Raines³

2009

Annals of the Association of American Geographers

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The ancient Maya occupied tropical lowland Mesoamerica and farmed successfully to support an elaborate settlement pattern that developed over many centuries. There has been debate as to the foundation of the settlement patterns. We show that Maya settlement locations were strongly influenced by environmental factors, primarily topographic slope, soil fertility, and soil drainage properties. Maps of these characteristics were created at the local scale and combined using Bayesian weights-of-evidence methods to develop probabilistic maps of settlement distributions based on the known, but incomplete, distribution of Maya archaeological sites, both domestic and monumental. The predictive model was validated with independently collected point-sampled field data for both presence and absence, predicting 82 percent of undiscovered Maya sites and 94 percent of site absence. This information should be of use in conservation planning for the region, which is under threat from contemporary agricultural expansion. Key Words: Maya settlement, predictive modeling, weights-of-evidence.Los antiguos mayas ocuparon las tierras bajas tropicales de Mesoamérica y produjeron una agricultura tan exitosa como para sostener un elaborado patrón de poblamiento, desarrollado a lo largo de varios siglos. Se ha presentado debate en lo que concierne a la fundación de los patrones de aquel asentamiento. Nosotros mostramos que las locaciones de los asentamientos maya fueron fuertemente influidas por factores ambientales, en especial la pendiente topográfica, la fertilidad del suelo y las propiedades del drenaje de los suelos. Para representar estas características, se crearon mapas a escala local, combinándolos con el uso de métodos bayesianos de peso-de-evidencia a fin de desarrollar mapas probabilísticos de la distribución de los asentamientos. Se tomó en cuenta la conocida aunque incompleta distribución de los sitios arqueológicos maya, tanto domésticos como monumentales. El modelo predictivo fue validado con datos de campo independientemente obtenidos en puntos de muestreo para presencia y ausencia, pronosticando el 82 por ciento de sitios maya sin descubrir y el 94 por ciento de ausencia de sitio. Esta información debería ser utilizada para planificar la conservación de la región, que se halla bajo la amenaza contemporánea de la expansión agrícola. Palabras clave: asentamientos mayas, modelación predictiva, peso-de-evidencia.

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Section: Discussionmentioning

confidence: 99%

Modeling Settlement Patterns of the Late Classic Maya Civilization with Bayesian Methods and Geographic Information Systems

Ford

Clarke

Raines³

2009

Annals of the Association of American Geographers

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“…This advantage would be reinforced as large farmers bought out smaller ones until their holdings were large enough to replace labor with machinery-which would further enhance their advantage. This substitution, in concert with a growing class of landless laborers, would reduce agricultural wages (e.g., Johnston and Cownie 1969, Wharton 1969, Falcon 1970, Cleaver 1972, Shiv a 1991, Bray 1994. Hayami and Ruttan ( 1985) claim that these predictions have not been borne out.…”

Section: Equity Between Households and Food Productionmentioning

confidence: 99%

Socioeconomic Equity, Sustainability, and Earth's Carrying Capacity

Daily¹,

Ehrlich²

1996

Ecological Applications

137

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We examine the relationship between socioeconomic equity in opportunity and sustainability, as reflected in patterns of food production and fertility. Our analysis spans various levels of social organization, from within the household (gender‐ and age‐related equity) to relations among households (of different material wealth), among regions (particularly rural vs. urban), and among nations (rich and poor). Our preliminary results in this complex area suggest that increasing equality of opportunity at each of these levels can help to increase food production and to lower fertility rates, through varied mechanisms. Working toward such equity constitutes a no regrets strategy for transitioning to a sustainable society and increasing Earth's carrying capacity for human beings, as measures to reduce the growing disparity between rich and poor have merit on ethical grounds alone. An important caveat, however, is that equity in consumer lifestyles within and between nations cannot be achieved globally by leveling up to consumption from the bottom. Runaway consumption in rich countries must be curbed as part of an effort to reduce the scale of human enterprise to below carrying capacity while still permitting needed development among the poor.

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“…In a social impact assessment of the Green Revolution, Bowonder (1979) found an uneven distribution of benefits and consequencespoor farmers were made poorer and rich farmers richer. Numerous researchers before and since then have come to the same conclusions regarding the impacts of the introduction of high-yielding varieties on different socioeconomic classes of agriculturists (see, for example, Bray, 1994;Cleaver, 1972;Griffin, 1974;Hewitt de Alcántara, 1976;Shiva, 1991;Wright, 1990). These impacts on small farmers include employment changes, debt, loss of land, marginalization, social changes, regional economic disparity, dependency for inputs and credits, unrest, and migration (Barrow, 1997).…”

Section: The Green Revolution and The New Biotechnologiesmentioning

confidence: 99%

Bringing Social Analysis Into a Multilateral Environmental Agreement: Social Impact Assessment and the Biosafety Protocol

Stabinsky

2000

The Journal of Environment & Development

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Negotiations under the UN Convention on Biological Diversity have recently concluded on a protocol governing the safe handling, transport, and use of living modified organisms (LMOs)—the Cartagena Protocol on Biosafety. One of the most contentious issues in these negotiations was the inclusion of socioeconomic considerations in the evaluation for import of an LMO. Many countries wanted the protocol to include provisions that enable an import ban or other trade-related measure to be taken if negative socioeconomic impacts are predicted that would have downstream consequences for the conservation and/or sustainable use of biological diversity. Other countries, principally the United States, believed such measures would run counter to national obligations under the World Trade Organization (WTO) agreements. The author considers the rationale for inclusion of socioeconomic considerations in evaluation of LMOs for import and evaluates the arguments that such provisions would not be WTO legal.

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Agriculture for Developing Nations

Cited by 33 publications

References 0 publications

Modeling Settlement Patterns of the Late Classic Maya Civilization with Bayesian Methods and Geographic Information Systems

Modeling Settlement Patterns of the Late Classic Maya Civilization with Bayesian Methods and Geographic Information Systems

Socioeconomic Equity, Sustainability, and Earth's Carrying Capacity

Bringing Social Analysis Into a Multilateral Environmental Agreement: Social Impact Assessment and the Biosafety Protocol

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