New biological model to manage the impact of climate warming on maize corn borers
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- Maiorano, A., Cerrani, I., Fumagalli, D. et al. Agron. Sustain. Dev. (2014) 34: 609. doi:10.1007/s13593-013-0185-2
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Climate change can modify the development of insect pests and their impact on crops. The study of future impacts on maize remains relatively unexplored. Here we modeled the distribution and development of the maize borer Sesamia nonagrioides Lef. in Europe using a 25 × 25 km grid. We studied the pest potential winter survival, distribution, and phenological development at three time horizons, 2000, 2030, and 2050, using the A1B scenario of the international panel on climate change (IPCC). A new model based on the lethal dose exposure concept was developed to simulate winter survival. Two approaches for the simulation of winter survival were compared: the first using air temperature only as weather input, named AirMS; the second taking into account the fraction of larvae overwintering in the soil, therefore considering also soil temperature, named SoilAirMS. The survival model was linked to a phenological model to simulate the potential development. Results show that soil temperature is an essential input for correctly simulating S. nonagrioides distribution. The SoilAirMS approach showed the best agreement (+537 grid cells), compared to the AirMS approach (−2,039 grid cells). Nevertheless, the AirMS approach allowed identifying areas where the agronomic practice suggested for controlling S. nonagrioides should be considered ineffective. This practice consists in uprooting and exposing the stubble on the soils surface for exposing larvae to winter cold. The projections to 2030 and 2050 suggested an overall slight increase of more suitable conditions for the S. nonagrioides in almost all the areas where it develops under the baseline. In these areas, S. nonagrioides could become a new insect pest with a potential strong impact on maize. This is the first attempt to provide extensive estimates on the effects of climate change on S. nonagrioides distribution, development, and on possible management changes.
KeywordsProcess-based modelsSpatialized simulationsInsect pestWinter survival modelPhenological modelClimate changePotential distributionSesamia nonagrioides
The Mediterranean corn borer develops through four main stages: egg, larvae, pupae, and adult, and it overwinters as a diapausing larva in maize stalks and roots (Gillyboeuf et al. 1994). Photoperiod has been reported as the crucial factor for the termination of diapause (Fantinou et al. 2002). Mediterranean corn borer diapause termination starts when photoperiod ≥12 h and larvae pupate after around 48 days. Temperature is also important as it was reported to be synergistic in enhancing diapause development (Fantinou et al. 2002).
Different management strategies have been suggested for the control of the Mediterranean corn borer populations. They include agronomic measures like the uprooting and exposing the stubble on the soil surface for exposing the diapausing larvae to the winter cold temperatures, mating disruption techniques, transgenic maize expressing Bacillus thuringiensis Berliner, and chemical control (Gillyboeuf et al. 1994; Albajes et al. 2002; Farinós et al. 2011). Furthermore, diapause induction can be influenced by maize cycle with consequences on population levels (Eizaguirre et al. 2007).
Insects are poikilotherms (i.e., body temperature varies along with that of the environmental temperature), hence their development, geographic distribution, and population density are strongly influenced by temperature. As a consequence, a warming climate has the potential to significantly modify the actual distribution and development of insects, including agricultural insect pests, with unknown consequences in agricultural systems (Gutierrez et al. 2010). Insect pest simulation models allow the estimation of the potential effects of a warming climate on insects based on their known physiological responses to specific weather factors (Régnière 2009). This can be helpful for estimating the impact of such changes also on management strategies and techniques.
To analyze the role of temperature in the potential distribution and development of the Mediterranean corn borer in Europe
To consider the potential impact on agro-management under current and near future climate scenario.
2 Materials and methods
The work was carried out in five phases: (1) the current distribution of the Mediterranean corn borer in Europe was estimated using data and information from different sources, (2) an original winter survival model was developed based on the Mediterranean corn borer cold tolerance, (3) a phenological model was calibrated for the Mediterranean corn borer, (4) the models were applied in spatialized simulation runs in Europe, and (5) a method for mapping the Mediterranean corn borer distribution was defined.
2.1 Current distribution records
Germany: South West (ENDURE 2010)
Spain: Andalucia, Aragon, Asturias, Castilla-LaMancha, Catalunia, Extremadura, Galicia, Navarra (Delgado de Torres 1929; Albajes et al. 2002; Novillo et al. 2003; Leniaud et al. 2006; Velasco et al. 2007)
The other areas where the presence of the Mediterranean corn borer has been reported were identified through the following secondary sources of information: the Global Biodiversity Information Facility (www.gbif.org), the Carnet du Lépidoptériste Français (CLF, http://www.lepinet.fr), the initiative Plantwise by CABI (http://www.plantwise.org), and the Pan-European Species directories Infrastructure (http://www.eu-nomen.eu/). These secondary sources of information give information about the presence or not of the insect at the country level, with the exception of the CLF website giving information at a regional level for France. The current distribution records were used to define the Mediterranean corn borer plausible distribution map. Given that the distribution records were not homogeneously distributed in Europe, the mapping of the observed distribution was done as follows: the records from the scientific and technical literature listed above and from the CLF website were arbitrarily mapped at NUTS 2 level (i.e., European Nomenclature of territorial units for statistics—http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/introduction), and the records from other sources were mapped at the country level.
2.2 Winter survival model
The winter survival model is based on the dose/response concept used in toxicology to determine the toxicity, for instance, of pesticides. This is usually done by testing the binomial response (i.e., death/no death) of an organism to a chemical under various concentrations (i.e., “doses”) and then comparing the concentrations at which there is a response (Vincent 2013). The lethal dose (LD) indicates the dose (exposure) that kills a defined threshold percentage of the population. The thresholds that are usually used to compare the dose effects are 50 % (LD50), 75 % (LD75), or 90 % (LD90) of insect pest population killed by the chemical.
the air and/or soil temperature is the “chemical”;
the time of exposure (hours) is the “dose”, and the expression “lethal time” (LT) was used instead of “lethal dose”;
90 % of insect population mortality (LT90) is the reference threshold used to estimate the effect of time exposure.
Example A: sample temperatures: −2, −2, −4, −4, −3 °C. The exposure to −2 °C is 5 h, the one to −3 °C is 3 h, and the one to −4 °C is 2 h;
Example B: sample temperatures: −2, −2, −4, −2, −3 °C. The exposure to −2 °C is again 5 h, while the exposure to 4 and 3 °C is just 1 h. The exposure to −3 °C is not 2 h because the sequence of temperatures ≤3 °C is interrupted by 1 h at −2 °C.
The data source used for the development of the survival model consisted of data about mortality (%) of diapausing cold-acclimated larvae of Mediterranean corn borer following exposure to cold temperatures (reference temperature values −15, −10.8, −4, −2, and 0 °C) and different time of exposure (from 2 to 64 h) obtained by Gillyboeuf et al. (1994) and Andreadis et al. (2011). Data from Gillyboeuf et al. (1994) showed that at 0 °C there was almost no mortality difference between the different time exposures. Since these data showed that a relationship between temperature, time of exposure, and mortality was evident at temperatures ≤−2 °C, this temperature was fixed as a threshold for calculating mortality, while the average mortality at 0 °C was used in the model as total intrinsic diapausing larvae mortality (Mint). According to Andreadis et al. (2011), at 10.8 °C the 90 % of the population dies in 2 h, and at −15 °C no individual can survive after even a short time exposure (5 min). Since 5 min is a very short time exposure, we assumed that at −15 °C the 90 % of the population dies in around 0.9 × 5 min that is 3.6 min. Probit analysis (Finney 1971) was performed for estimating the LT90 at −4 and −2 °C. Probit analysis is usually used in toxicology to analyze dose–response or binomial response experiments. The response is always binomial (e.g., death/no death) and the relationship between the response and the various concentrations is sigmoidal. Probit analysis acts as a transformation from sigmoid to linear (using a cumulative normal probability distribution) and then runs a regression on the relationship (Vincent 2013). Following results of probit analysis, a thermal death time curve (TDTC) representing LT90 at any temperature ≤−2 °C was developed using two linear models (see “Survival and phenological development modeling” section).
2.3 Phenological model
Following information found in literature (Fantinou et al. 2002), the phenological model was started (i.e., biofix) after that scotophase (dark phase of photoperiod) was <12 h. The scotophase was estimated using the SolarRadiation model component (http://agsys.cra-cin.it/tools/) with latitude and day of year as input.
2.4 Climate scenarios
A dataset of weather data on scenarios of future climate, suitable for use with biophysical models, has recently become available from the European Commission JRC, derived from the ENSEMBLE scenarios, and covering Europe with a grid of 25 × 25 km (Donatelli et al. 2012). A maize crop mask based upon the same grid was used to limit the study to the areas where maize is currently cultivated in Europe. The maize crop mask is the one used at the European Commission JRC for scenarios studies (e.g., AVEMAC Project, Donatelli et al. 2012). One realizations of the Intergovernmental Panel on Climate Change (IPCC) was used as the input of the analysis. This was based upon the emission scenario A1B (i.e., scenario of a more integrated world with a balanced emphasis on all energy sources) from the runs of the global circulation model ECHAM5-R3, bias-corrected and downscaled from the original ENSEMBLES data set by the HIRHAM5 RCM regional climate model to a 25-km grid resolution (Dosio and Paruolo 2011). The winter survival and phenological simulations were performed referring to the time horizons 2030 and 2050 in comparison to the baseline of 2000 on a sample of 10 synthetic years for each time horizon. The aim was to estimate potential distribution and development in the future temperature regime compared to current (baseline—2000) conditions.
2.5 Potential environmental suitability and geographic distribution
For each implemented modeling solutions (AirMS and AirSoilMS), the Mediterranean corn borer potential environmental suitability was estimated according to winter survival and phenological development. For each grid, a simulated year was considered suitable to Mediterranean corn borer population development if the population survived to winter conditions (see “Winter survival model” section) and if the survived population was able to develop at least one generation (see “Phenological model” section). Finally, the potential environmental suitability of each grid was estimated according to a minimum threshold of number of suitable years out of the 10 simulated for each grid. Different potential environmental suitability were evaluated according to the different minimum threshold considered (from 1 to 10), where threshold = 1 meaning Mediterranean corn borer population surviving in areas characterized by persisting adverse years and able to develop in infrequent favorable years (1 in this case), and threshold = 10 meaning Mediterranean corn borer population surviving and developing only in areas where optimal conditions for survival and development appear every years. The application of this method to a grid (25 × 25 km) covering Europe (coastal regions of Turkey included) gave as a result 10 potential geographical distribution (one for each threshold) of the Mediterranean corn borer. The obtained potential distributions were checked by comparing them to the observed distribution (see “Current distribution records” section).
2.6 Model implementation and software technology
3 Results and discussion
3.1 Current distribution records
3.2 Survival and phenological development modeling
The thermal death time curve (Fig. 3a) is characterized by a point of strong discontinuity at −4 °C: this temperature has been reported to be starting point of freezing of extra-cellular ice nucleating agents (INA) present in insect species classified as freeze tolerant, like the Mediterranean corn borer (Bale and Hayward 2010; Andreadis et al. 2011): the presence of INA gives the insect the ability to adapt to sub-zero temperatures, but the formation of ice causes damaging deformation to cells (Mazur 1984).
The total number of days required to complete one generation at the optimum temperature resulted equals to 40 days which means a relative growth rate of 0.025 day−1. Following optimization, the optimal values for the Eq. 4 parameters were as follows: Tmin = 7.7, Topt = 30.7, Tmax = 40 (fixed value), and c = 1.9.
3.3 Potential distribution under actual and future scenarios
Results coming from the SoilAirMS approach are more interesting because they take into account also soil temperature. Hence, it is a closer-to-reality representation of the Mediterranean corn borer winter survival system. Considering this approach, when the threshold is set equal to 3 years, the potential distribution of the 2000 scenario is largely overestimated and spread to areas where the Mediterranean corn borer has never been reported including Southern England, Belgium, the Netherlands, Central, Northern and Western Germany, Northern and Eastern France, Serbia, and Bulgaria (AE = 1,808). The potential distribution is progressively reduced with the increase of the threshold. These results are in agreement with the reported high sensitivity of Mediterranean corn borer population to thermal stresses (Gillyboeuf et al. 1994). If compared to the observed distribution, the better agreement of higher thresholds indicates that even in areas where years with unfavorable survival conditions occur just occasionally, the Mediterranean corn borer populations could be seriously affected and future development compromised. The best agreement with the observed distribution was observed when the threshold was equal to 10 years out of 10 simulated (data not shown). Nevertheless, a lower threshold was preferred that is taking into account that the Mediterranean corn borer population could survive to few occasional unfavorable years. It must be noticed that in this work each run of simulation was independent from the others, that is, the 10 years were treated independently and not as a time series, meaning that possible cumulative effects of consecutive positive (or negative when choosing lower thresholds) years on the Mediterranean corn borer population were not considered. Furthermore, the area covered by distributions obtained using slightly lower thresholds than the 10-year threshold (e.g., 8 or 9), was just slightly higher than the 10 threshold one. Considering the intrinsic spatial distortions included in the use of a 25 × 25 km grid (Donatelli et al. 2012), it was considered reasonable using a threshold slightly lower than 10. Therefore, it was decided to use a threshold of 8 for this study that is considering that Mediterranean corn borer population can survive to two unfavorable years out of 10. When the threshold is set equal to 8, the estimated potential distribution appears very close to the observed one (AE = 537) with the exception of Southern England and Benelux (not included in the observed distribution). Results of simulations seem to indicate that in the Balkans the Mediterranean corn borer is distributed only in the coastal regions. From the literature search, it was only possible to determine the presence of the insect at the national level, but not its distribution at finer level. It must be pointed out that this work focuses on the potential distribution based on temperature, which is the main abiotic factor influencing insect distribution and development. Other biotic or abiotic factors were not taken into account. These factors might include a high percentage of larval population whose development is anticipated compared to the diapause induction signal of the critical photoperiod, and that consequently continue development exposing eggs to later winter temperatures (Eizaguirre and Fantinou 2012), sowing date that influence maize phenology, and the percentage of diapausing larvae (Eizaguirre et al. 2007), parasitoids (Alexandri and Tsitsipis 1990), and viruses of the Baculoviruses group reported to be endemic in the northern population of the Mediterranean corn borer (Gillyboeuf et al. 1994). This is the possible reason why the estimated potential distribution is projected as spread to some areas (Southern England and Benelux) where the Mediterranean corn borer has never been reported.
For what concerns the estimated increase in potential geographical distribution due to climate change, the potential geographical range is expected to increase according to the SoilAirMS approach including vast areas of Central and Eastern France, Belgium, The Netherlands, and Western and Northern Germany. A slight increase is also expected in the Balkans and in mainland Turkey. Since no presence of the insect is expected by the AirMS approach in these areas during the same time frame, it can be argued that uprooting and exposing the stubble on the soils surface could be a sufficient strategy to control the Mediterranean corn borer in the future in these areas of new distribution.
The main increase is expected between 2000 and 2030 (70 % of total increase between 2000 and 2050) while between 2030 and 2050 the increase is much less marked (30 % of total increase between 2000 and 2050). The noticeable lower increase between 2030 and 2050 seems to indicate that even under rising temperature conditions, there could be a geographical limit to the expansion of the Mediterranean corn borer driven by its physiological sensitivity to temperature that could hamper the expansion of this pest, at least in the farthest time horizon considered.
3.4 Potential phenological development under actual and future scenarios
Results are shown in terms of absolute differences between the average potential number of generations estimated for the baseline and 2030, and between 2030 and 2050 scenarios using the SoilAirMS. The projections suggest an overall slight increase (+0.2 to +0.4 generations) of more suitable conditions for the Mediterranean corn borer in almost all the areas where it develops under the baseline, the main increase being observed between baseline and 2030. Even if the simulated development under future scenarios suggests a slight acceleration of the Mediterranean corn borer development (+0.2 to +0.4 generations corresponds to an acceleration of the development of 8 to 16 days at the end of the season), this acceleration could lead to a different phenological relationship with its main host (maize) with consequences on the insect pest management strategies (Eizaguirre et al. 2007), and to a different phenological relationship with the critical photoperiod inducing diapause at the end of summer with consequences on survival and on the population levels of the Mediterranean corn borer (Gillyboeuf et al. 1994). Most of the increase >0.6 generations is detectable in areas where an increase in potential distribution is expected due to the absence of development during baseline. These areas that are not suitable to the Mediterranean corn borer development under current climate could be interested by a significant invasion of the Mediterranean corn borer if winter conditions change. The Mediterranean corn borer could potentially develop up to two generations in France and Germany, and up to almost three in the Balkans and in mainland Turkey becoming a new insect pest in these regions with effects especially on maize productions.
The Mediterranean corn borer is one of the most important pests of maize in Europe. The estimation of the potential impact of climate change on its spread and development can help in evaluating risks of invasions to new areas and changes in the agronomic measures used for its control.
This is the first study about the potential survival, distribution, and phenological development of this insect pest under current and future climate considering overwinter survival in crop roots. Potential survival was simulated using an original approach based on the concept of dose exposure and taking into account the important role played by soil temperatures.
Results showed that there is a close correlation between soil temperature and the Mediterranean corn borer distribution. Even if most of the larvae overwinter above the soil surface, the Mediterranean corn borer potential distribution was much better explained when soil temperature was taken into account (SoilAirMS approach). On the contrary, the modeling approach without soil temperature as input (AirMS) largely underestimated the insect distribution compared to the observed one. Nevertheless, the AirMS approach was also useful as it allowed identifying areas where the Mediterranean corn borer winter survival is assured even without the soil thermal buffer. In these areas, overwintering larvae can survive on the soil surface and the agronomic strategy usually suggested for S. nonagrioides control would not be effective. This practice consists in uprooting and exposing the stubble on the soils surface for exposing larvae to winter cold.
Potential distribution under future scenarios close to present allowed identifying areas of future potential invasion by the Mediterranean corn borer. Simulation results suggested that in these areas the rising of winter soil temperatures could create the potential conditions for the onset of this insect pest. In these regions, the Mediterranean corn borer could become an important pest as the temperatures during the development season could allow the development of up to three generations. In these areas, exposing the root to air temperature could be a very effective measure.
For what that concern changes in phenological development under future climate scenarios, they could be very limited and might not lead to changes in the number of observed generations in the areas where this insect is spread under current conditions. Nevertheless, these small changes could change the phenological relationships between the Mediterranean corn borer and maize, and between the Mediterranean corn borer and the critical photoperiod inducing diapause at the end of summer. These changes might have effects on population levels.
Further simulation studies are needed (1) to evaluate the impact of the new phenological relationships with the critical photoperiod at the end of summer, (2) using other different climate projections in order to evaluate the Mediterranean corn borer distribution and development estimation uncertainty, and (3) to understand how the phenological relationships between the insect and its main host could change under a warming climate. This can be done coupling MIMYCS.Borers to maize crop development simulations. Thanks to the implementation technology used for developing the modeling approaches presented in this paper, such studies and improvements can be easily performed.
This research was supported by a Marie Curie Intra European Fellowship within the 7th European Community Framework Programme and partially supported by the project AgroScenari of the Italian Ministry of Agricultural, Food and Forestry Policies. Thanks to Raúl López Lozano (EC-JRC) for his help with some mapping-related issues.