Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

DYNAMIC SIMULATION MODEL OF CENTRAL AMERICAN LOCUST SCHISTOCERCA PICEIFRONS (ORTHOPTERA: ACRIDIDAE)

M. I. Hernández-Zul, J. A. Quijano-Carranza, R. Yáñez-López, R. V. Ocampo-Velázquez, I. Torres-Pacheco, R. G. Guevara-González and A. E. Castro-Ramírez
The Florida Entomologist
Vol. 96, No. 4 (December, 2013), pp. 1274-1283
Stable URL: http://www.jstor.org/stable/23609163
Page Count: 10
  • Read Online (Free)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
DYNAMIC SIMULATION MODEL OF CENTRAL AMERICAN LOCUST SCHISTOCERCA PICEIFRONS (ORTHOPTERA: ACRIDIDAE)
Preview not available

Abstract

Locusts, large gregarious and migratory grasshoppers, are pests of economic importance in several regions of the world because of the severe damage they can cause to crops. The Central American locust, Schistocerca piceifrons is the most important locust species in the Americas, and it is distributed in zones of Mexico, Central and South America. In Mexico, despite the efforts to survey and monitor S. piceifrons (Walker) populations, outbreaks are still difficult to predict and prevent, and high economic and ecological costs are incurred in controlling them. The purpose of this study was to build a dynamic model of locust growth and development as a function of environmental conditions in order to identify suitable conditions for the high reproduction rates of this insect. This information can be used to assist in locust management. A modular approach and numerical integration techniques were applied in model building. The main inputs of the model were daily rainfall and temperature data, and physical soil properties such as texture and depth. The model estimates the growth of non-cultivated grass in breeding zones and oviposition rates as a function of soil moisture. The development rates of the different locust stages are calculated as a function of temperature. The model satisfactorily represents S. piceifrons behaviour, and generates 2 generations per yr, the first in summer and the second in winter. In locations with suboptimal temperatures the second generation does not complete development until the next year. A good agreement was found between model outputs and field data from Yucatan, Mexico for 2008 to 2010. Based on these results the model is proposed for use as a tool to support S. piceifrons monitoring by the National Locust Control Program. Langosta, el nombre común dado a los chapulines gregarios y migratorios son considerados como plaga de importancia económica en el mundo debido a los daños que causa a los cultivos. La langosta centroamericana Schistocerca piceifrons (Walker) es la más importante en el continente americano y se encuentra distribuida en zonas de México, Centro y Sudamérica. En México, a pesar de los esfuerzos de seguimiento y control de las poblaciones de Schistocerca piceifrons, los brotes de este insecto siguen siendo difíciles de predecir y prevenir ocasionando altos costos económicos y ecológicos para controlarlos. El objetivo de este estudio fue construir un modelo dinámico del crecimiento y desarrollo de la langosta en función de las condiciones ambientales con el fin de identificar las condiciones adecuadas para altas tasas de reproducción y darle soporte al manejo de la langosta. Un enfoque modular y métodos de integración numérica fueron utilizadas en la construcción del modelo. Las principales entradas del modelo son datos diarios de temperatura y precipitación y propiedades físicas del suelo como la textura y la profundidad. Las tasas de desarrollo de las diferentes etapas de la langosta son calculadas en función de la temperatura. Se encontró una buena concordancia con las salidas del modelo y los datos de campo del 2008 al 2010 en el estado de Yucatán, México. Con base en estos resultados, el modelo se propone como una herramienta de apoyo a la Campaña Nacional de Langosta para el monitoreo de S. piceifrons.

Page Thumbnails

  • Thumbnail: Page 
1274
    1274
  • Thumbnail: Page 
1275
    1275
  • Thumbnail: Page 
1276
    1276
  • Thumbnail: Page 
1277
    1277
  • Thumbnail: Page 
1278
    1278
  • Thumbnail: Page 
1279
    1279
  • Thumbnail: Page 
1280
    1280
  • Thumbnail: Page 
1281
    1281
  • Thumbnail: Page 
1282
    1282
  • Thumbnail: Page 
1283
    1283