DOI: 10.5061/dryad.6d52b
title: Data from: Projecting pest population dynamics under global warming: the combined effect of inter- and intra-annual variations

description: The typical short generation length of insects makes their population
 dynamics highly sensitive not only to mean annual temperatures but also to
 their intra-annual variations. To consider the combined effect of both
 thermal factors under global warming, we propose a modeling framework that
 links general circulation models (GCMs) with a stochastic weather
 generator and population dynamics models to predict species population
 responses to inter- and intra-annual temperature changes. This framework
 was utilized to explore future changes in populations of Bemisia tabaci,
 an invasive insect pest-species that affects multiple agricultural systems
 in the Mediterranean region. We considered three locations representing
 different pest status and climatic conditions: Montpellier (France),
 Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local
 daily temperature realizations representing current and future (mid-21st
 century) climatic conditions under two emission scenarios for the three
 locations. Our simulations predicted a significant increase in the average
 number of annual generations and in population size, and a significant
 lengthening of the growing season in all three locations. A negative
 effect was found only in Seville for the summer season, where future
 temperatures lead to a reduction in population size. High variability in
 population size was observed between years with similar annual mean
 temperatures, suggesting a strong effect of intra-annual temperature
 variation. Critical periods were from late spring to late summer in
 Montpellier and from late winter to early summer in Seville and
 Beit-Jamal. Although our analysis suggested that earlier seasonal activity
 does not necessarily lead to increased populations load unless an
 additional generation is produced, it is highly likely that the insect
 will become a significant pest of open-fields at Mediterranean latitudes
 above 40° during the next 50 years. Our simulations also implied that
 current predictions based on mean temperature anomalies are relatively
 conservative and it is better to apply stochastic tools to resolve complex
 responses to climate change while taking natural variability into account.
 In summary, we propose a modeling framework capable of determining
 distinct intra-annual temperature patterns leading to large or small
 population sizes, for pest risk assessment and management planning of both
 natural and agricultural ecosystems.
description: Montpellier-BCC-CSM1.1-CurrentDownscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Montpellier station France. Current climate scenario.Montpellier-BCC-Current.xlsxMontpellier-BCC-CSM1.1-RCP4.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Montpellier station France. RCP4.5 climate scenarioMontpellier-BCC-RCP4.5.xlsxMontpellier-BCC-CSM1.1-RCP8.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Montpellier station France. RCP8.5 climate scenario.Montpellier-BCC-RCP8.5.xlsxSeville-BCC-CSM1.1-CurrentDownscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Seville station Spain. Current climate scenario.Seville-BCC-Current.xlsxSeville-BCC-CSM1.1-RCP4.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Seville station Spain. RCP4.5 climate scenario.Seville-BCC-RCP4.5.xlsxSeville-BCC-CSM1.1-RCP8.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Seville station Spain. RCP8.5 climate scenario.Seville-BCC-RCP8.5.xlsxBeitJamal-BCC-CSM1.1-CurrentDownscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Beit-Jamal station Israel. Current climate scenario.BeitJamal-BCC-Current.xlsxBeitJamal-BCC-CSM1.1-RCP4.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Beit-Jamal station Israel. RCP4.5 climate scenario.BeitJamal-BCC-RCP4.5.xlsxBeitJamal-BCC-CSM1.1-RCP8.5Downscaled (bias-corrected) daily temperature data (150 simulations for 10 years) based on the BCC-CSM1.1 CMIP5 model. Beit-Jamal station Israel. RCP8.5 climate scenario.BeitJamal-BCC-RCP8.5.xlsxPopulationDynamicData&FunctionsFunctions used in the population dynamics model and the experimental data used to derive their coefficientsModelOutputMean temperature and population dynamic model output (generation number, log population size and growth season length) for each climate model, scenario, station and simulated year.