Temperature as a predictor of survival of the pine processionary moth in the Italian Alps

Agricultural and Forest Entomology - Tập 9 Số 1 - Trang 65-72 - 2007
Emiliano Buffo1, Andrea Battisti1, Michael Stastny1, Stig Larsson1
1§ Department of Environmental Agronomy–Entomology, University of Padova, Via Università 16a, 35020 Legnaro, Italy, * Department of Ecology and Evolutionary Biology, Cornell University, Corson Hall, Ithaca, NY 14853-2701, U.S.A. and † Department of Entomology, Swedish University of Agricultural Sciences, PO Box 7044, S-750 07 Uppsala, Sweden

Tóm tắt

Abstract

1 The pine processionary moth Thaumetopoea pityocampa is expanding its geographical range in Europe, as a consequence of enhanced winter survival under a warmer climate. A combination of daytime nest temperatures and night air temperatures determines the number of hours larvae are able to feed (hours above realized feeding threshold, RFT).

2 We tested the RFT‐based model for survival across multiple areas of the insect’s range in the Italian Alps over a 2‐year period. In a series of translocation experiments using natural temperature gradients as spatial analogues for global warming, we transferred colonies of T. pityocampa larvae to sites within zones of historical distribution, recent distribution, and outside the present range. The sites included traditional (Pinus nigra, Pinus sylvestris) as well as novel (Pinus mugo, Pinus uncinata, Pinus cembra) hosts.

3 Survival during precold (August to November), cold (December to February) and postcold (March to May) periods were analysed against climatic variables (temperature and rainfall) and predictors developed by the model.

4 Host species did not significantly affect final survival, with the exception of slower larval development, and resulting lower cold tolerance, on P. cembra than on P. mugo at the same site.

5 Across all the sites and hosts, final survival of colonies depended on the number of feeding hours during the cold period (RFT), which explained 82% of the variance in a regression model. We recommend using RFT, or its surrogate daily mean minimum temperature when nest temperature is not available, in predictive models of range expansion of T. pityocampa under climate change scenarios.

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