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Spatial Interrelationships between Wheat Phenology, Thermal Time, and Terrain Attributes

Author:
McMaster, Gregory S., Green, Timothy R., Erskine, Robert H., Edmunds, Debora A., Ascough, James C.
Source:
Agronomy journal 2012 v.104 no.4 pp. 1110-1121
ISSN:
0002-1962
Subject:
Triticum aestivum, air temperature, ambient temperature, developmental stages, landscape position, landscapes, models, phenology, soil air, winter wheat, Colorado
Abstract:
Spatial variation of winter wheat (L.) phenology across complex terrain has received little attention despite its importance for assessing overall crop status and making key precision management decisions. Temperature is the environmental factor explaining the greatest variation in phenology, and temperature varies across a landscape. Our primary hypothesis was that variability in thermal time (TT) by landscape position could explain the phenological variation, with a secondary hypothesis that spatial patterns of TT and phenology were related to terrain attributes. Four years of phenology and soil and air temperature data were collected from a 100-ha field in northeast Colorado. Five developmental stages were monitored at 10 landscape sites each year. Terrain attributes were computed using 5-m-grid land surface elevation data. Spatial differences in reaching developmental stages across sites varied from 2 to 12 d within a year. Up to 96% of the phenological variation among years was explained when using a general TT model pooling all data. Refining the TT model, however, by using either air or soil TT at specific sites partially supported the primary hypothesis only for the relatively wetter 2004–2005 and 2006–2007 years (regression relationships explained up to 72% of the variation). Similarly, terrain attributes occasionally explained spatial patterns of phenology in the two wetter years, and attributes with the highest explanatory power varied among years and developmental stages. Further research is needed to better understand the controlling environmental factors and predict spatial patterns of wheat phenology for precision management using terrain attributes.
Agid:
311228