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Landscape-Level Phenology of a Threatened Butterfly: A GIS-Based Modeling Approach

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ABSTRACT

Phenology of organismal development varies between growing seasons according to the weather and also varies within growing seasons across topoclimatic gradients. Combining these factors is necessary to predict landscape-level patterns of phenology and their consequences for population dynamics. We developed a model on a Geographic Information System (GIS) that predicts phenology of adult emergence of the threatened Bay checkerspot butterfly across complex terrain under variable weather. Physiological time was modeled by accumulated slope-specific direct insolation. Insolation sums through growing seasons were calculated for each cell of a digital terrain model (skipping over cloudy days) until a threshold for adult emergence was reached. Emergence times of adult butterflies for a given year were then mapped out across a 100-ha area. To generate predicted emergence curves for the population in a given year, these maps ofemergence times were then modified by incorporating microdistributions of postdiapause larvae. Different larval microdistributions changed both the magnitude and shape of emergence curves under the same yearly weather and could change mean population-wide emergence dates by 11 days. Reproductive success in this butterfly is strongly dependent on the timing of adult emergence, and these models provide insights into the effects of weather, topography, and population history on population dynamics. Because adult emergence phenology is often a key component of reproductive success for insects, understanding the components of phenological variation in space and time in complex terrain may provide insights into population dynamics for management of pests and conservation of rare species.

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Received 2 December 1997; accepted 24 March 1998.

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Weiss, S., Weiss, A. Landscape-Level Phenology of a Threatened Butterfly: A GIS-Based Modeling Approach. Ecosystems 1, 299–309 (1998). https://doi.org/10.1007/s100219900023

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  • DOI: https://doi.org/10.1007/s100219900023

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