Project Details
Description
BECC financed project
Popular science description
This project extends cereal aphid biocontrol models being developed at CEC (SAPES, YC in cooperation with MJ & RB) to consider climate and enable prediction of outbreaks and crop losses under climate change in Sweden, in collaboration with climate-pest (AMJ) and climate-crop modellers (GS). It is a precursor for developing (i) European pest control models and (ii) integration of crop and pest climate models.
Cereal aphids outbreaks occur sporadically, can account for up to 15% yield losses [1, 2], and motivate large-scale insecticide use in Sweden. Outbreak frequency and severity vary spatially depending on climate, management and the relative suitability of the landscape for aphid overwintering and availability of resources for their natural enemies [3,4]. A better quantitative understanding of these relationships will allow us to (i) predict the spatial distribution of outbreak risk and crop losses under future climates and (ii) identify the potential for managing landscapes for reduced outbreak risk & crop losses, without resorting to insecticide.
First we will develop a phenological model linking the latest gridded observed climate data (e.g. E-OBS 1950-present) to aphid population dynamics [5]. Validation will use a Sweden-wide, spatially explicit aphid time series (Sw. Board of Agriculture, SJV, 1997-present). Secondly, we will infer the relationship between landscape composition, aphids, and natural enemies from the deviations between empirical data and the phenological model predictions. To do this we integrate the phenological model with an existing landscape model for aphid biocontrol [4], and a subset of the empirical aphid data in a Hierarchical Bayesian framework. Thirdly, we will predict outbreaks and cereal crop losses in future climates & landscapes using the models above, land-use scenarios developed in SAPES, and future climate data (CORDEX, 1950-2100). We will work with daily temperature and precipitation at a resolution of 25x25 km or finer, use data from several climate model runs in an ensemble approach, and compare different future scenarios (RCP's). Crop losses will account for changes in crop productivity as predicted by crop models (LPJ-Guess).
References
1 Östman et al. 2003. Ecol Econ 45:149-158
2 Larsson 2005. Crop Prot 24:397-405
3 Bommarco et al. 2007. J Appl Ecol 44:1013-1022
4 Jonsson et al. 2014. Meth Ecol Evol (online)
5 Jönsson et al. 2013. Glob Change Biol 19:1043-10
Cereal aphids outbreaks occur sporadically, can account for up to 15% yield losses [1, 2], and motivate large-scale insecticide use in Sweden. Outbreak frequency and severity vary spatially depending on climate, management and the relative suitability of the landscape for aphid overwintering and availability of resources for their natural enemies [3,4]. A better quantitative understanding of these relationships will allow us to (i) predict the spatial distribution of outbreak risk and crop losses under future climates and (ii) identify the potential for managing landscapes for reduced outbreak risk & crop losses, without resorting to insecticide.
First we will develop a phenological model linking the latest gridded observed climate data (e.g. E-OBS 1950-present) to aphid population dynamics [5]. Validation will use a Sweden-wide, spatially explicit aphid time series (Sw. Board of Agriculture, SJV, 1997-present). Secondly, we will infer the relationship between landscape composition, aphids, and natural enemies from the deviations between empirical data and the phenological model predictions. To do this we integrate the phenological model with an existing landscape model for aphid biocontrol [4], and a subset of the empirical aphid data in a Hierarchical Bayesian framework. Thirdly, we will predict outbreaks and cereal crop losses in future climates & landscapes using the models above, land-use scenarios developed in SAPES, and future climate data (CORDEX, 1950-2100). We will work with daily temperature and precipitation at a resolution of 25x25 km or finer, use data from several climate model runs in an ensemble approach, and compare different future scenarios (RCP's). Crop losses will account for changes in crop productivity as predicted by crop models (LPJ-Guess).
References
1 Östman et al. 2003. Ecol Econ 45:149-158
2 Larsson 2005. Crop Prot 24:397-405
3 Bommarco et al. 2007. J Appl Ecol 44:1013-1022
4 Jonsson et al. 2014. Meth Ecol Evol (online)
5 Jönsson et al. 2013. Glob Change Biol 19:1043-10
| Status | Finished |
|---|---|
| Effective start/end date | 2014/06/01 → 2015/12/31 |