IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v457y2021ics0304380021002374.html
   My bibliography  Save this article

Forecasting impacts of biological control under future climates: mechanistic modelling of an aphid pest and a parasitic wasp

Author

Listed:
  • Barton, Madeleine
  • Parry, Hazel
  • Ward, Samantha
  • Hoffmann, Ary A.
  • Umina, Paul A.
  • van Helden, Maarten
  • Macfadyen, Sarina

Abstract

Climate change impacts agricultural pests in complicated ways, and accounting for these responses should form an integral part of pest management programmes. Process-based models are often used in agriculture to forecast population dynamics of pests within a growing season, however these are often constrained to assessing the impacts of temperature in isolation of other factors. These models are therefore unable to fully explore species’ responses to climate change, which may be driven by multiple abiotic and biological stressors. Here, we build a mechanistic model of a globally distributed agricultural aphid pest (Myzus persicae (Sulzer)), and an associated parasitic wasp (Diaeretiella rapae (M'Intosh)) that is known to biologically control the aphid. We simulate temporal dynamics of the crop with a well-established canola growing degree-day model (APSIM) and incorporate the impacts of temperature and rainfall on insect survival. The model was parameterised with laboratory-measured datasets from around the globe, and we have calibrated and validated the model to Australian broadacre cropping systems using regional observation records. We then ran the validated models with future temperature and rainfall scenarios to reveal that suppression of aphid populations by the wasp is enhanced under stressful abiotic conditions, which are predicted to occur more frequently in the future. The process-based modelling approach affords valuable and novel insights into physiological traits that influence population dynamics of both species and highlights gaps in our current understanding of the system. In the future, farmers could have greater confidence in the bio-control potential of D. rapae under different conditions, and be in a position to adjust their M. persicae management programmes accordingly. This is the first model to explore the interaction of these two cosmopolitan species in the field, which is applicable across broad geographic regions, while also providing insights as to how both species could be better managed on a local scale.

Suggested Citation

  • Barton, Madeleine & Parry, Hazel & Ward, Samantha & Hoffmann, Ary A. & Umina, Paul A. & van Helden, Maarten & Macfadyen, Sarina, 2021. "Forecasting impacts of biological control under future climates: mechanistic modelling of an aphid pest and a parasitic wasp," Ecological Modelling, Elsevier, vol. 457(C).
    • Handle: RePEc:eee:ecomod:v:457:y:2021:i:c:s0304380021002374
    DOI: 10.1016/j.ecolmodel.2021.109679
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380021002374
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2021.109679?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Barton, Madeleine G. & Terblanche, John S. & Sinclair, Brent J., 2019. "Incorporating temperature and precipitation extremes into process-based models of African lepidoptera changes the predicted distribution under climate change," Ecological Modelling, Elsevier, vol. 394(C), pages 53-65.
    2. Kennedy, Marc C. & Anderson, Clive W. & Conti, Stefano & O’Hagan, Anthony, 2006. "Case studies in Gaussian process modelling of computer codes," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1301-1309.
    3. Bahlai, Christine A. & Weiss, Ross M. & Hallett, Rebecca H., 2013. "A mechanistic model for a tritrophic interaction involving soybean aphid, its host plants, and multiple natural enemies," Ecological Modelling, Elsevier, vol. 254(C), pages 54-70.
    4. Camille Parmesan & Gary Yohe, 2003. "A globally coherent fingerprint of climate change impacts across natural systems," Nature, Nature, vol. 421(6918), pages 37-42, January.
    5. Bennie, Jonathan & Huntley, Brian & Wiltshire, Andrew & Hill, Mark O. & Baxter, Robert, 2008. "Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland," Ecological Modelling, Elsevier, vol. 216(1), pages 47-59.
    6. Michael E. Dillon & George Wang & Raymond B. Huey, 2010. "Global metabolic impacts of recent climate warming," Nature, Nature, vol. 467(7316), pages 704-706, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lee Yit Leng & Osumanu Haruna Ahmed & Mohamadu Boyie Jalloh & Azwan Awang & Norawanis Abdul Razak & Adiza Alhassan Musah & Syahirah Shahlehi, 2023. "Brief Review: Climate Change and Its Impact on Mango Pests and Diseases," Journal of Agriculture and Crops, Academic Research Publishing Group, vol. 9(3), pages 391-399, 07-2023.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Richard Tol, 2011. "Regulating knowledge monopolies: the case of the IPCC," Climatic Change, Springer, vol. 108(4), pages 827-839, October.
    2. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    3. Anne Goodenough & Adam Hart, 2013. "Correlates of vulnerability to climate-induced distribution changes in European avifauna: habitat, migration and endemism," Climatic Change, Springer, vol. 118(3), pages 659-669, June.
    4. Francesca Pilotto & Ingolf Kühn & Rita Adrian & Renate Alber & Audrey Alignier & Christopher Andrews & Jaana Bäck & Luc Barbaro & Deborah Beaumont & Natalie Beenaerts & Sue Benham & David S. Boukal & , 2020. "Meta-analysis of multidecadal biodiversity trends in Europe," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    5. Wesley R. Brooks & Stephen C. Newbold, 2013. "Ecosystem damages in integrated assessment models of climate change," NCEE Working Paper Series 201302, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Mar 2013.
    6. Barton, Madeleine G. & Terblanche, John S. & Sinclair, Brent J., 2019. "Incorporating temperature and precipitation extremes into process-based models of African lepidoptera changes the predicted distribution under climate change," Ecological Modelling, Elsevier, vol. 394(C), pages 53-65.
    7. Hao Wang & Guohua Liu & Zongshan Li & Xin Ye & Bojie Fu & Yihe Lü, 2017. "Analysis of the Driving Forces in Vegetation Variation in the Grain for Green Program Region, China," Sustainability, MDPI, vol. 9(10), pages 1-14, October.
    8. Guoming Du & Tongbing Guo & Chen Ma, 2022. "Effects of Topographic Factors on Cultivated-Land Ridge Orientation in the Black Soil Region of Songnen Plain," Land, MDPI, vol. 11(9), pages 1-13, September.
    9. Fabina, Nicholas S. & Abbott, Karen C. & Gilman, R.Tucker, 2010. "Sensitivity of plant–pollinator–herbivore communities to changes in phenology," Ecological Modelling, Elsevier, vol. 221(3), pages 453-458.
    10. Xiumei Wang & Jianjun Dong & Taogetao Baoyin & Yuhai Bao, 2019. "Estimation and Climate Factor Contribution of Aboveground Biomass in Inner Mongolia’s Typical/Desert Steppes," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    11. Anna Yusa & Peter Berry & June J.Cheng & Nicholas Ogden & Barrie Bonsal & Ronald Stewart & Ruth Waldick, 2015. "Climate Change, Drought and Human Health in Canada," IJERPH, MDPI, vol. 12(7), pages 1-54, July.
    12. Portalier, S.M.J. & Candau, J.-N. & Lutscher, F., 2024. "Larval mortality from phenological mismatch can affect outbreak frequency and severity of a boreal forest defoliator," Ecological Modelling, Elsevier, vol. 493(C).
    13. Isaac Corro Ramos & Maureen P. M. H. Rutten-van Mölken & Maiwenn J. Al, 2013. "The Role of Value-of-Information Analysis in a Health Care Research Priority Setting," Medical Decision Making, , vol. 33(4), pages 472-489, May.
    14. A. Ogden & J. Innes, 2008. "Climate change adaptation and regional forest planning in southern Yukon, Canada," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 13(8), pages 833-861, October.
    15. Ye, Qing & Yang, Xiaoguang & Dai, Shuwei & Chen, Guangsheng & Li, Yong & Zhang, Caixia, 2015. "Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China," Agricultural Water Management, Elsevier, vol. 159(C), pages 35-44.
    16. Petropoulos, G. & Wooster, M.J. & Carlson, T.N. & Kennedy, M.C. & Scholze, M., 2009. "A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation," Ecological Modelling, Elsevier, vol. 220(19), pages 2427-2440.
    17. Brandt, Laura A. & Benscoter, Allison M. & Harvey, Rebecca & Speroterra, Carolina & Bucklin, David & Romañach, Stephanie S. & Watling, James I. & Mazzotti, Frank J., 2017. "Comparison of climate envelope models developed using expert-selected variables versus statistical selection," Ecological Modelling, Elsevier, vol. 345(C), pages 10-20.
    18. Prem B. Parajuli & Priyantha Jayakody & Ying Ouyang, 2018. "Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 985-996, February.
    19. Fullman, Timothy J. & Bunting, Erin L. & Kiker, Gregory A. & Southworth, Jane, 2017. "Predicting shifts in large herbivore distributions under climate change and management using a spatially-explicit ecosystem model," Ecological Modelling, Elsevier, vol. 352(C), pages 1-18.
    20. -, 2018. "Climate Change in Central America: Potential Impacts and Public Policy Options," Sede Subregional de la CEPAL en México (Estudios e Investigaciones) 39150, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:457:y:2021:i:c:s0304380021002374. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.