Adult emergence phenology in checkerspot butterflies: the effects of macroclimate, topoclimate, and population history View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1993-11

AUTHORS

Stuart B. Weiss, Dennis D. Murphy, Paul R. Ehrlich, Charles F. Metzler

ABSTRACT

The prediction of adult emergence times in insect populations can be greatly complicated by microclimatic gradients, especially in circumstances where distributions of juveniles along those gradients vary from year to year. To investigate adult emergence patterns in topographically heterogeneous habitats, we built a model of postdiapause development of the Bay checkerspot butterfly, Euphydryas editha bayensis. The model uses slope-specific insolation as the rate-controlling variable, and accounts for both solar exposure of the habitat and cloud cover. Instar-specific larval mass gains per unit of insolation were determined from mark-recapture experiments. A small correction for daily low temperatures was used to calibrate the model to five years of field data on larval mass. The model predicted mean mass of 90% of larval samples within 4 clear days over a 70-120 day growing season. The magnitude of spatial variation in emergence times across habitat slopes is greater than annual variation in emergence times due to yearly weather conditions. Historical variation (yearly shifts in larval distributions across slopes) is an important determinant of mean population emergence dates. All of these factors need to be considered in understanding adult emergence phenology in this butterfly and in other insects inhabiting heterogeneous thermal environments. Such an understanding can be useful in managing insect populations for both pest control and conservation. More... »

PAGES

261-270

References to SciGraph publications

Journal

TITLE

Oecologia

ISSUE

2

VOLUME

96

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00317740

DOI

http://dx.doi.org/10.1007/bf00317740

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022193544

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28313423


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