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Modeling temperature-dependent survival with small datasets: insights from tropical mountain agricultural pests

Published online by Cambridge University Press:  01 March 2013

Verónica Crespo-Pérez ,
Olivier Dangles ,
Jacques Régnière  and
Isabelle Chuine
Verónica Crespo-Pérez*
Affiliation:
IRD, UR 072, Diversité, Ecologie et Evolution des Insectes Tropicaux, Laboratoire Evolution, Génomes et Spéciation, UPR 9034, CNRS, 91198 Gif-sur – Yvette Cedex, France Université Paris-Sud 11, 91405 Orsay Cedex, France Laboratorio de Entomología, Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Católica del Ecuador, 12 de Octubre, 1076 y Roca, Quito, Ecuador Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, 1919 route de Mende, 34293 Montpellier cedex 5, France
Olivier Dangles
Affiliation:
IRD, UR 072, Diversité, Ecologie et Evolution des Insectes Tropicaux, Laboratoire Evolution, Génomes et Spéciation, UPR 9034, CNRS, 91198 Gif-sur – Yvette Cedex, France Université Paris-Sud 11, 91405 Orsay Cedex, France Laboratorio de Entomología, Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Católica del Ecuador, 12 de Octubre, 1076 y Roca, Quito, Ecuador
Jacques Régnière
Affiliation:
Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, PO Box 10380 Stn. Ste Foy, Quebec, QC, CanadaG1V 4C7
Isabelle Chuine
Affiliation:
Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, 1919 route de Mende, 34293 Montpellier cedex 5, France
*
*Author for correspondence Phone: (593) 22991700, ext. 1294; Fax: (593) 22991687 E-mail: mvcrespo@puce.edu.ec
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Abstract

Many regions are increasingly threatened by agricultural pests but suffer from a lack of data that hampers the development of adequate population dynamics models that could contribute to pest management strategies. Here, we present a new model relating pest survival to temperature and compare its performance with two published models. We were particularly interested in their ability to simulate the deleterious effect of extreme temperatures even when adjusted to datasets that did not include extreme temperature conditions. We adjusted the models to survival data of three species of potato tuber moth (PTM), some major pests in the Tropical Andes. To evaluate model performance, we considered both goodness-of-fit and robustness. The latter consisted in evaluating their ability to predict the actual altitudinal limits of the species in the Ecuadorian Andes. We found that even though our model did not always provide the best fit to data, it predicted extreme temperature mortality and altitudinal limits accurately and better than the other two models. Our study shows that the ability to accurately represent the physiological limits of species is important to provide robust predictions of invasive pests' potential distribution, particularly in places where temperatures approach lethal extremes. The value of our model lies in its ability to simulate accurate thermal tolerance curves even with small datasets, which is useful in places where adequate pest management is urgent but data are scarce.

Keywords

Agricultural pestsPhthorimaea operculellapotato tuber mothSymmetrischema tangoliasTecia solanivoratemperature-related survival
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 103 , Issue 3 , June 2013 , pp. 336 - 343
Copyright
Copyright © Cambridge University Press 2013

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References

Angilletta, M.J. (2009) Thermal Adaptation: A Theoretical and Empirical Synthesis. New York, Oxford University Press Inc.CrossRefGoogle Scholar
Bentz, B.J., Logan, J.A. & Amman, G.D. (1991) Temperature-dependent development of the mountain pine-beetle (Coleoptera, Scolytidae) and simulation of its phenology. Canadian Entomologist 123, 1083–1094.CrossRefGoogle Scholar
Bonato, O., Lurette, A., Vidal, C. & Fargues, J. (2007) Modelling temperature-dependent bionomics of Bemisia tabaci (Q-biotype). Physiological Entomology 32, 50–55.Google Scholar
Burnham, K.P. & Anderson, D.R. (2004) Multimodel inference – understanding AIC and BIC in model selection. Sociological Methods and Research 33, 261–304.CrossRefGoogle Scholar
Dangles, O., Carpio, C., Barragan, A.R., Zeddam, J.L. & Silvain, J.F. (2008) Temperature as a key driver of ecological sorting among invasive pest species in the tropical Andes. Ecological Applications 18, 1795–1809.CrossRefGoogle ScholarPubMed
Dangles, O., Carpio, C., Villares, M., Yumisaca, F., Liger, B., Rebaudo, F. & Silvain, J.F. (2010) Community-based participatory research helps farmers and scientists to manage invasive pests in the Ecuadorian Andes. AMBIO 39, 325–335.Google Scholar
Deutsch, C.A., Tewksbury, J.J., Huey, R.B., Sheldon, K.S., Ghalambor, C.K., Haak, D.C. & Martin, P.R. (2008) Impacts of climate warming on terrestrial ectotherms across latitude. Proceedings of the National Academy of Sciences of the USA 105, 6668–6672.CrossRefGoogle ScholarPubMed
Duyck, P.F., David, P. & Quilici, S. (2006) Climatic niche partitioning following successive invasions by fruit flies in La Reunion. Journal of Animal Ecology 75, 518–526.Google Scholar
Geurts, K., Mwatawala, M. & De Meyer, M. (2012) Indigenous and invasive fruit fly diversity along an altitudinal transect in Eastern Central Tanzania. Journal of Insect Science 12, 1–18. Available online: insectscience.org/12.12.CrossRefGoogle ScholarPubMed
Gilbert, E., Powell, J.A., Logan, J.A. & Bentz, B.J. (2004) Comparison of three models predicting developmental milestones given environmental and individual variation. Bulletin of Mathematical Biology 66, 1821–1850.Google Scholar
Gilchrist, G.W. (1995) Specialists and generalists in changing environments 0.1. Fitness landscapes of thermal sensitivity. American Naturalist 146, 252–270.Google Scholar
Gondard, P. & Mazurek, H. (2001) 30 años de reforma agraria y colonización en el Ecuador (1964–1994): dinámicas espaciales. pp. 15–40 in Gondard, P. & León, J.B. (Eds) Dinámicas Territoriales: Ecuador, Bolivia, Perú, Venezuela. Quito, Estudio de Geografía.Google Scholar
Hodkinson, I.D. (2005) Terrestrial insects along elevation gradients: species and community responses to altitude. Biological Reviews 80, 489–513.Google Scholar
Isard, S.A., Gage, S.H., Comtois, P. & Russo, J.M. (2005) Principles of the atmospheric pathway for invasive species applied to soybean rust. Bioscience 55, 851–861.CrossRefGoogle Scholar
Jaramillo, J., Chabi-Olaye, A., Kamonjo, C., Jaramillo, A., Vega, F.E., Poehling, H.M. & Borgemeister, C. (2009) Thermal tolerance of the coffee berry borer Hypothenemus hampei: predictions of climate change impact on a tropical insect pest. PLoS ONE 4, e6487.CrossRefGoogle ScholarPubMed
Liger, B. (2010) Elaboración de Mapas predictivos de riesgo de infestación de tres especies de polillas de la papa (Lepidoptera: Gelechiidae). Licenciatura dissertation, PUCE, Quito.Google Scholar
Logan, J.A., Régnière, J., Gray, D.R. & Munson, A.S. (2007) Risk assessment in the face of a changing environment: gypsy moth and climate change in Utah. Ecological Applications 17, 101–117.CrossRefGoogle ScholarPubMed
Luo, Y.Q., Ogle, K., Tucker, C., Fei, S.F., Gao, C., LaDeau, S., Clark, J.S. & Schimel, D.S. (2011) Ecological forecasting and data assimilation in a data-rich era. Ecological Applications 21, 1429–1442.Google Scholar
Ma, Z.S. (1997) Demography and survival analysis of Russian wheat aphid populations. PhD dissertation, University of Idaho.Google Scholar
Ma, Z.S. & Bechinski, E.J. (2008) Developmental and phenological modeling of Russian wheat aphid (Hemiptera:Aphididae). Annals of the Entomological Society of America 101, 351–361.CrossRefGoogle Scholar
Niño, L. (2004) Revisión sobre la Polilla de la Papa Tecia solanivora en Centro y Suramérica. Suplemento Revista Latinoamericana de la Papa 18 pp.Google Scholar
Nyssen, J., Poesen, J. & Deckers, J. (2009) Land degradation and soil and water conservation in tropical highlands. Soil and Tillage Research 103, 197–202.CrossRefGoogle Scholar
Palacios, M., Tenorio, J., Vera, M., Zevallos, F. & Lagnaoui, A. (1998) Population dynamics of the Andean potato tuber moth, Symmetrischema tangolias (Gyen), in three different agro-ecosystems in Peru. CIP – Program Report 153–160.Google Scholar
Perez, C., Nicklin, C., Dangles, O., Vanek, S., Sherwood, S., Halloy, S., Martinez, R., Garret, K. & Forbes, G. (2010) Climate change in the high Andes: implications and adaptation strategies for small scale farmers. International Journal of Environmental, Cultural, Economic and Social Sustainability 6, 78–88.Google Scholar
Perez-Mendoza, J., Weaver, D.K. & Throne, J.E. (2004) Development and survivorship of immature Angoumois grain moth (Lepidoptera : Gelechiidae) on stored corn. Environmental Entomology 33, 807–814.CrossRefGoogle Scholar
Raftery, A.E. (1995) Bayesian model selection in social research. Sociological Methodology 25, 111–163.CrossRefGoogle Scholar
Rebaudo, F., Dangles, O., Lery, X., Lopez-Ferber, M. & Zeddam, J.L. (2006) Biological efficacy of a granulovirus for the control of Tecia solanivora, Povolny (1973). pp. 826–834 in Proceedings of the 8th International Conference on Plant Diseases (Tours, France, 5–6 December, 2006). Alfortville, France, Association Française de Protection des Plantes.Google Scholar
Régnière, J., Powell, J., Bentz, B. & Nealis, V. (2012) Effects of temperature on development, survival and reproduction of insects: experimental design, data analysis and modeling. Journal of Insect Physiology 58, 634–647.Google Scholar
Roux, O. (1993) Population Ecology of Potato Tuber Moth Phthorimaea operculella (Zeller) (Lepidoptera:Gelechiidae) and Design of an Integrated Pest Management Program in Tunisia. Zurich, Doctor of Technical Sciences. Swiss Federal Institute of Technology.Google Scholar
Schoolfield, R.M., Sharpe, P.J.H. & Magnuson, C.E. (1981) Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory. Journal of Theoretical Biology 88, 719–731.Google Scholar
Schwarz, G. (1978) Estimating dimension of a model. Annals of Statistics 6, 461–464.CrossRefGoogle Scholar
Sharpe, P.J.H. & DeMichele, D.W. (1977) Reaction-kinetics of poikilotherm development. Journal of Theoretical Biology 64, 649–670.Google Scholar
Sinclair, B.J., Vernon, P., Jaco Klok, C. & Chown, S.L. (2003) Insects at low temperatures: an ecological perspective. Trends in Ecology & Evolution 18, 257–262.Google Scholar
Sporleder, M., Kroschel, J., Quispe, M.R.G. & Lagnaoui, A. (2004) A temperature-based simulation model for the potato tuberworm, Phthorimaea operculella Zeller (Lepidoptera; gelechiidae). Environmental Entomology 33, 477–486.Google Scholar
Sporleder, M., Kroschel, J., Huber, J. & Lagnaoui, A. (2005) An improved method to determine the biological activity (LC50) of the granulovirus PoGV in its host Phthorimaea operculella . Entomologia Experimentalis et Applicata 116, 191–197.CrossRefGoogle Scholar
Tang, P.A., Wang, J.J., He, Y., Jiang, H.B. & Wang, Z.Y. (2008) Development, survival, and reproduction of the psocid Liposcelis decolor (Psocoptera: Liposcelididae) at constant temperatures. Annals of the Entomological Society of America 101, 1017–1025.Google Scholar
Torres, W., Notz, A. & Valencia, L. (1997) Cliclo de vida y otros aspectos de la biologia de la polilla de la papa Tecia solanivora (Povolny) (Lepidoptera: Gelechiidae) en el estado Tachira, Venezuela. Boletín de Entomología Venezolana 12, 81–94.Google Scholar
van der Have, T.M. (2002) A proximate model for thermal tolerance in ectotherms. Oikos 98, 141–155.Google Scholar
Young, K.R. (2009) Andean land use and biodiversity: humanized landscapes in a time of change. Annals of the Missouri Botanical Garden 96, 492–507.Google Scholar
Supplementary material: File

Crespo-Pérez Supplementary Material

Lists the parameters and their values of the Sharpe and DeMichel equation (modified by Schoolfield et al. 1981) adjusted to development time data of the three immature stages of the three species of potato tuber moth

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Supplementary material: File

Crespo-Pérez Supplementary Material

Lists the parameters and their values of the three survival rate equations adjusted to survival rate data of the three immature stages of the three species of potato tuber moth

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Supplementary material: File

Crespo-Pérez Supplementary Material

Consists on a figure showing the relationship between observed abundance and predicted survival of the three species of potato tuber moth at 50 sites in the Ecuadorian Andes

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