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Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

Tratalos, Jamie A., Cheke, Robert A. ORCID: 0000-0002-7437-1934, Healey, Richard G. and Stenseth, Nils Chr. (2010) Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data. Climate Research, 43 (3). pp. 229-239. ISSN 0936-577X (Print), 1616-1572 (Online) (doi:10.3354/cr00930)

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Abstract

Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and resulted in more realistic forecasts. Using a square-root transformation for the locust data improved the fit. The models were only partially successful when accounting for the dramatic changes in abundance which may occur during locust upsurges and declines, in some cases successfully predicting these phenomena but underestimating their severity. Better fitting models were also produced when rainfall data were added to models of an equivalent series for desert locust hoppers (nymphs) that incorporated lagged data for locust swarms as independent variables, representing parent generations. The results are discussed in relation to predicting likely changes in desert locust dynamics with reference to potential effects of climate change.

Item Type: Article
Additional Information: [1] Citation: Tratalos JA, Cheke RA, Healey RG, Stenseth NC (2010) Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data. Clim Res 43:229-239. [2] This article is marked as an Open Access article. Inter-Research Science Center makes the archives of its journals available as a service to the scientific community. All articles published 5 years ago or more may be accessed freely.
Uncontrolled Keywords: Schistocerca gregaria, time series, population dynamics, endogenous, rainfall
Subjects: Q Science > QL Zoology
S Agriculture > S Agriculture (General)
Faculty / Department / Research Group: Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science
Related URLs:
Last Modified: 05 May 2016 14:54
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/4038

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