Effects of climate change and CO2 increase on potential agricultural production in Southern Québec, Canada

Abstract

ABSTRACT:We assessed the effect of greenhouse gas-induced climate change, as well as the direct fertilization effect of CO 2 , on crop yields in Québec, Canada. Our methodology coupled the transient diagnostics of 2 Atmosphere-Ocean General Circulation Models (CGCM1 and HadCM3) to the DSSAT 3.5 crop simulation system to simulate current and future (2040-2069) crop yields for spring wheat, maize, soybean and potato grown in 8 agricultural regions of Québec. For the future (2040-2069), we predict significant yield increases for soybean, lesser increases for wheat, no significant change for maize, and yield decreases for potato. These yields, especially for soybean, are further increased when incorporating the CO 2 fertilization effect, but vary according to the crop, climate scenario and agricultural region. Similar trends have been found in comparable agricultural regions in the Northeastern USA and in Southern Finland. These results are useful for designing appropriate crop and farm management adaptation strategies in response to future climate change.KEY WORDS: Climate change · CO 2 increase · Canada · Crop yields Resale or republication not permitted without written consent of the publisherClim Res 34: [105][106][107][108][109][110][111][112][113][114][115][116][117] 2007 GCMs (general circulation models) CGCM1 and HadCM3, as well as data from the crop model DSSAT 3.5 (Brassard 2003). METHODS AND DATAThis study uses the coupled climate scenario-crop model approach in which present and future climate conditions, generated by the selected climate models, following different CO 2 and other GHG emission scenarios, are integrated as inputs into the different crop models so as to simulate crop growth, development and production. All model variables, other than weather (e.g. soil, cultivar and management), are held constant between present and future crop yield simulations. Present and future crop yields are then compared to evaluate the impacts of GHG-induced climate change on agriculture. The A-OGCM climate models used in this study are the coupled CGCM1 of the Canadian Centre for Climate Modeling and Analysis (CCCma) and the HadCM3 of the British Hadley Centre. The CGCM1 model is forced by the IS92a emission scenario, whilst the HadCM3 model is forced by both the SRES A2 and B2 emission scenarios (Houghton et al. 2001). The selection of the A-OGCMs was based on their relevance to Canadian conditions and their ability to provide daily climate diagnostics at a relatively fine scale. The crop models used were those of the Decision Support System for Agrotechnology Transfer (DSSAT) version 3.5, namely CERES, CROPGRO and SUBSTOR, suitable for use under Canadian conditions (Mahdian & Gallichand 1997).This study was conducted in 8 of the 13 agricultural regions of the province of Québec, Canada (Fig. 1). These regions are those of the Régie des Assurances Agricoles du Québec (RAAQ 2001a). The choice of study region was based on the importance of the cultivated acreages and the desire to have as complete a representat...

Modelling soybean yield responses to seeding date under projected climate change scenarios

“…Seeding date was often fixed to the same date as the baseline in climate change impact studies using crop models (Bao et al 2015a;Bao et al 2015b;Brassard and Singh 2007;Wolf 2002b). Thus it is not surprising that the growing period reported in those studies would be shortened under the warmer future climate.…”

“…Many crop models have simulated soybean growth under expected climate change scenarios, such as SOYBEANW (Wolf 2002b), Agro-IBIS (Twine et al 2013), GLICIM (Haskett et al 1997), EPIC (Phillips et al 1996), and CROPGRO (Bao et al 2015a;Bao et al 2015b;Brassard and Singh 2007;Wolf 2002b). In these studies, soybean yields under climate change scenarios were often simulated with similar seeding dates to the baseline conditions.…”

“…This model was originally developed as CROPGRO for simulating soybean growth and development with a daily time step (Boote et al 1998). The CSM-CROPGRO-Soybean model has been impact studies, such as in southeastern USA (Bao et al 2015b;Carbone et al 2003), southern Québec in Canada (Brassard and Singh 2007), India (Mall et al 2004), and France (Wolf 2002a). …”

A conceptual framework for multi-regional climate change assessments for international market systems with long-term investments

“…Although at first glance this step may appear relatively straightforward, the experience of past impact assessments suggests otherwise. Some earlier assessments were able to take advantage of previously-developed processbased models; for example, the Decision Support System for Agrotechnology Transfer (DSSAT) model ensemble (Jones et al 2003) has been used in a number of assessments for agriculture ranging from agronomic productivity (e.g., Tsvetsinskaya et al 2003;Brassard and Singh 2007) to crop management (e.g., Eitzinger et al 2003) to soil fertility (e.g., Gijsman et al 2002). Process-based models offer a theoretical advantage in climate change assessments as they allow simulation over a wide range of conditions, even potentially including those outside the range used in the original model development.…”

Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies

“…The DSSAT Cropping System Model (CSM-DSSAT) has been widely evaluated with experimental data from different soils around the world [see, for example, Tsuji et al (2002)] and it has been used in a wide range of applications, such as assessing climate change impacts on crop growth and production (Rosenzweig and Iglesias 1998;Brassard and Singh 2007) and predicting soil nitrogen (N) availability and leaching (Beckie et al 1995;Snapp and Fortuna 2003). Thus, it was used in this study to simulate spring wheat (Triticum aestivum L.) yields on different soils across the Canadian prairies.…”