Management of the Diamondback Moth and Other Crucifer Insect ...

EIFigure 4. Annual EI values (pink lines) for Oxford, England from 1853 to date. Also shown are the years in which“outbreaks” have been recorded (red bars) as well as light trap data at Rothamsted (blue lines) expressed asproportion of total catch.phenology in Japan, southern China and in north andsouth India agree with published notions of when thespecies is a “problem” (see previous DBM workshopproceedings). There is nothing particularly special aboutthe species biology and ecology at specific locationsthroughout its range; all these predictions are basedusing a single set of parameters and site specific climatedata.Estimates of long term abundanceAs in Zalucki and Furlong (2008) we use the CLIMEXparameter set for DBM to generate a long series ofsuitability estimates for locations based on climaterecords. We used the British Isles as a case study partlybecause data is available and partly because outbreaks ofDBM that occur most likely migrate from elsewhere.The years in which outbreaks were recorded in theBritish Isles were taken from the summaries in Chu(1986). Outbreaks of DBM in the British Isles arebelieved to be driven by migration from elsewhere inEurope, most likely the low-countries (Chapman et al.2002) and parts of southern Scandinavia and Estonia(Shaw and Hurst 1969).Using a long series of weather data from Oxford(maximum and minimum temperatures and rainfall from1853 to 2010) we generated yearly EI values and markedthe known outbreak years, as well as light trap data forone site in recent years (Fig 4). The EI are low(generally less than 20) suggesting that the species is atthe edge of its range in this region. Outbreaks are notassociated with positive EI years but are most likely theresult of migration, as argued elsewhere (see Zalucki andFurlong 2008). Note that EI has become moreconsistently positive in recent years and we can start toexpect persistent populations and greater DBM pestproblems in the UK. This may well represent the effectsof global warming (see Sutherst et al. 2011).For Hangzhou, China, we analyzed a discontinuous setof light trap data for DBM from 1976-1979, 1983, and1986-1990. Abundance varies a great deal with very lowcatches in 1983 and 1986 and very high catches in 1977and 1987 (Fig 5). We used the difference (change) inCLIMEX GI indices from one week to the next (Gi+1-Gi) as an estimate of population growth rate. Using thedate of first capture of moths in the light trap record andthe growth rate estimates from five weeks earlier (i-5)we generated predicted population changes for each yearof record (Fig 5). There is a close fit between thesepredicted values and actual population data; in generalour crude model “predicts” population peaks, orindicates that there could have been a peak (at least as faras climate suitability was concerned) but that it failed tomaterialize. Is this the effect of planting, insecticides etcat a landscape level? The exceptions are the two peakyears. We wonder if the late autumn peaks do notrepresent migration from elsewhere, presumablynorthern China?The CLIMEX approach to population modelling is verybroad and crude. Insects have discrete generations withknown temperature-mediated development times.Different stages have very different susceptibilities toextreme climate variables of temperature and rainfall.These stages may or may not be available in thepopulation when the events occur. CLIMEX in a senseassumes they are available. We have consequently12 AVRDC - The World Vegetable Center