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Undamaged cotton plants yield more if their neighbour is damaged: implications for pest management

Published online by Cambridge University Press:  10 February 2009

L.J. Wilson ,
T.T. Lei ,
V.O. Sadras ,
L.T. Wilson  and
S.C. Heimoana
L.J. Wilson*
Affiliation:
CSIRO Division of Plant Industry and Cotton Catchment Communities CRC, Locked Bag 59, Narrabri, New South Wales, Australia, 2390
T.T. Lei
Affiliation:
CSIRO Division of Plant Industry and Cotton Catchment Communities CRC, Locked Bag 59, Narrabri, New South Wales, Australia, 2390 Ryukoku University, Faculty of Science and Technology, Department of Environmental Solutions, Japan
V.O. Sadras
Affiliation:
CSIRO Division of Plant Industry and Cotton Catchment Communities CRC, Locked Bag 59, Narrabri, New South Wales, Australia, 2390 South Australian Research and Development Institute – School of Agriculture, Food and Wine, The University of Adelaide, GPO Box 397, Adelaide, South Australia, 5001
L.T. Wilson
Affiliation:
Texas A & M University, Beaumont Agricultural Centre, 1509 Aggie Drive, Beaumont, TX 77713, USA
S.C. Heimoana
Affiliation:
CSIRO Division of Plant Industry and Cotton Catchment Communities CRC, Locked Bag 59, Narrabri, New South Wales, Australia, 2390
*
*Author for correspondence Fax: 61-2-67931186 E-mail: [email protected]
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Abstract

Understanding the compensatory responses of crops to pest damage is important in developing pest thresholds. Compensation for pest damage in crops can occur at the plant level, where the architecture, growth dynamics and allocation patterns of damaged plants are altered, allowing them to recover or, at the crop level, where differential damage between plants may alter plant-to-plant interactions. We investigated growth and yield of cotton (Gossypium hirsutum L.) following non-uniform manual defoliation of seedlings. This partially replicates real pest damage and is valuable in understanding crop-level responses to damage because it can be inflicted precisely. Damage distributions included damaging 0, 25, 50, 75 or 100% of the plants. Damage intensity for the damaged plants was varied by removing 100 or 75% of each true leaf when plants had two, four and six true leaves. At the crop level, yield loss increased as the proportion of plants damaged and intensity of damage per damaged plant increased. Neighbour interactions occurred; undamaged plants with damaged neighbours grew larger and yielded better than undamaged plants with undamaged neighbours, while the converse applied for damaged plants with undamaged neighbours. Neighbour interactions were influenced by the intensity of damage and were stronger when 100% of the leaf area was removed than when 75% was removed. At the crop level, when compared with yield estimates based on yield of plants from uniformly damaged or undamaged plots, these interactions resulted in higher yield than expected (+8%). This suggests that damage distribution may have to be considered in studies where artificial or real pest damage is inflicted uniformly on plants.

Keywords

compensationthresholdintegrated pest managementcropsherbivory
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 99 , Issue 5 , October 2009 , pp. 467 - 478
Copyright
Copyright © 2009 Cambridge University Press

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References

Baldwin, I.T. (1990) Herbivory simulations in ecological research. Tree 5, 3.Google ScholarPubMed
Baldwin, I.T., Halitschke, R., Paschold, A., von Dahl, C.C. & Preston, C.A. (2006) Volatile signalling in plant-plant interactions: ‘Talking trees’ in the genomics era. Science 311, 812–815.CrossRefGoogle ScholarPubMed
Ballaré, C.L. & Casal, J.J. (2000) Light signals perceived by crop and weed plants. Field Crops Research 67, 149–160.CrossRefGoogle Scholar
Brook, K.D., Hearn, A.B. & Kelly, C.F. (1992a) Response of cotton to damage by insect pests in Australia: compensation for early season fruit damage. Journal of Economic Entomology 85, 1378–1386.CrossRefGoogle Scholar
Brook, K.D., Hearn, A.B. & Kelly, C.F. (1992b) Response of cotton, Gossypium hirsutum L., to damage by insect pests in Australia: manual simulation of damage. Journal of Economic Entomology 85, 1368–1377.CrossRefGoogle Scholar
Chisholm, I.F. & Lewis, T. (1984) A new look at thrips (Thysanoptera) mouthparts, their action and effects of feeding on plant tissue. Bulletin of Entomological Research 74, 663–675.CrossRefGoogle Scholar
Crawley, M. (1983) Herbivory: The Dynamics of Animal-Plant Interactions. 437 pp. Oxford, UK, Blackwell Scientific Publications.Google Scholar
Dent, J. & Blackie, M. (1979) Systems Simulation in Agriculture. 180 pp. London, UK, Applied Science.CrossRefGoogle Scholar
Deutscher, S., Wilson, L. & Mensah, R. (2005) Integrated Pest Management Guidelines for Cotton Production Systems in Australia. 78 pp. Narrabri, New South Wales, Australia, Australian Cotton Cooperative Research Centre.Google Scholar
Fila, G., Bellocchi, G., Acutis, M. & Donatelli, M. (2003) Irene: a software to evaluate model performance. European Journal of Agronomy 18, 369–372.CrossRefGoogle Scholar
Karban, R. (1997) Neighbourhood affects a plant's risk of herbivory and subsequent success. Ecological Entomology 22, 433–439.CrossRefGoogle Scholar
Lei, T.T. & Wilson, L.J. (2004) Recovery of Leaf Area through Accelerated Shoot Ontogeny in Thrips-damaged Cotton Seedlings. Annals of Botany 94, 179–186.CrossRefGoogle ScholarPubMed
Macedo, T.B., Peterson, R.K.D., Dausz, C.L. & Weaver, D.K. (2007) Photosynthetic responses of wheat, Triticum aestivum L., to defoliation patterns of individual leaves. Environmental Entomology 36, 602–608.CrossRefGoogle ScholarPubMed
Niklas, K. (1994) Plant Allometry: The Scaling of Form and Process. 412 pp. Chicago, IL, USA, University of Chicago Press.Google Scholar
Oesterheld, M. & McNaughton, S. (1991) Effects of stress and time for recovery on the amount of compensatory growth after grazing. Oecologia 85, 305–313.CrossRefGoogle ScholarPubMed
Payne, R., Harding, S., Murray, D., Soutar, D., Baird, D., Welham, S., Kane, A., Gilmour, A., Thompson, R., Webster, R. & Wilson, G.T. (2005) The Guide to GenStat® Release 8. Part 2: Statistics. 1009 pp. Payne, R. (Ed.). Oxford, UK, VSN International.Google Scholar
Peterson, R.K.D., Danielson, S.D. & Higley, L.G. (1992) Photosynthetic responses of alfalfa to actual and simulated alfalfa weevil (Coleoptera: Curculionidae) injury. Environmental Entomology 21, 501–507.CrossRefGoogle Scholar
Sadras, V.O. (1995) Compensatory growth in cotton after loss of reproductive organs. Field Crops Research 40, 1–18.CrossRefGoogle Scholar
Sadras, V.O. (1996a) Cotton compensatory growth after loss of reproductive organs as affected by availability of resources and duration of recovery period. Oecologia 106, 432–439.CrossRefGoogle ScholarPubMed
Sadras, V.O. (1996b) Population-level compensation after loss of vegetative buds: interactions among damaged and undamaged cotton neighbours. Oecologia 106, 417–423.CrossRefGoogle ScholarPubMed
Sadras, V.O. (1997) Interference among cotton neighbours after differential reproductive damage. Oecologia 109, 427–432.CrossRefGoogle ScholarPubMed
Sadras, V.O. & Wilson, L.J. (1998) Recovery of cotton crops after early season damage by thrips (Thysanoptera). Crop Science 38, 399–409.CrossRefGoogle Scholar
Salguera-Navas, V., Funderburk, J., Mack, T., Beshear, R. and Olson, S. (1994) Aggregation indices and sample size curves for binomial sampling of flower inhabiting Frankliniella species (Thysanoptera: Thripidae) on tomato. Journal of Economic Entomology 87, 1622–1626.Google Scholar
Snipes, C. & Baskin, C. (1994) Influence of defoliation on cotton yield, seed quality, and fibre properties. Field Crops Research 37, 137–143.CrossRefGoogle Scholar
Taylor, L. (1984) Assessing and interpreting the spatial distributions of insect populations. Annual Review of Entomology 29, 321–357.CrossRefGoogle Scholar
Trumble, J.T., Kolodny-Hirsh, D.M. & Ting, I.P. (1993) Plant compensation for arthropod herbivory. Annual Review of Entomology 38, 93–119.CrossRefGoogle Scholar
Wilson, L.J. (1993) Spider mites (Acari: Tetranychidae) affect yield and fibre quality of cotton. Journal of Economic Entomology 86, 566–585.CrossRefGoogle Scholar
Wilson, L.J., Sadras, V.O., Heimoana, S.C. & Gibb, D. (2003) How to succeed by doing nothing: cotton compensation after simulated early season pest damage. Crop Science 43, 2125–2134.CrossRefGoogle Scholar
Wilson, L.J., Mensah, R.K. & Fitt, G.P. (2004) Implementing IPM in Australian cotton. pp. 97–118in Horowitz, A.R. & Ishaaya, I. (Eds). Novel Approaches to Insect Pest Management in Field and Protected Crops. Berlin, Germany, Springer-Verlag.Google Scholar
Wilson, L.T. & Room, P.M. (1983) Clumping patterns of fruit and arthropods in cotton with implications for binomial sampling. Environmental Entomology 12, 50–54.CrossRefGoogle Scholar