Assessing the risks and uncertainties of regional crop potential under a changing climate in Finland Timothy R. Carter 1, Riitta A. Saarikko' and Kai J. Niemi Agricultural Research Centre of Finland, 'Office address: Finnish Meteorological Institute, Box 503, FIN-00101 Helsinki, Finland Results are presented of a modelling study to estimate the regional suitability and potential produc- tivity of selected crops in Finland under a changing climate. Model simulations were conducted across a regular 10 km grid over Finland for various cultivars of the following crops: spring wheat, barley, oats, potato and maize, and for two nematode pests and a fungal disease of potato. Models were run for both the present-day (1961-1990) climate and scenarios of future climate. Results are presented as maps. The main findings of the study are: (1) A warming of the climate induces shifts in the northern limit of cereal suitability of some 100-150 km per °C. (2) Changes in climate and carbon dioxide concentration by 2050 are estimated to enhance average grain yields of present-day barley cultivars in all regions. (3) Under projected warming, the potential distribution of nematode species expands northwards and additional generations of some species are likely. The risk of late blight occurrence increases in all regions. (4) By 2050 grain maize could be cultivatedreliably in favoura- ble regions of southern Finland, and satisfactory yields obtained. (5) Uncertainties surround all esti- mates, including uncertainties in projections of future climate, model errors and assumptions and observational errors. Key words: suitability, crop yield, spring cereals, maize, potato, late blight, nematodes, 2050 scenario ntroduction It has been demonstrated in numerous studies that global climate change can have significant impacts on crop production in different parts of the world (e.g. Parry 1990,Rosenzweig and Par- ry 1994, Reilly et al. 1996). In Finland too, re- search suggests that increasing temperature and higher concentrations of carbon dioxide in the atmosphere can lengthen the growing season and enhance the productive potential of field crops (e.g. Kettunen et al. 1988, Hakala and Mela 1996, Kleemola and Karvonen 1996). These conclu- sions are largely based on two sources of infor- mation: (i) experiments with plants grown un- der controlled conditions and (ii) simulations with mathematical crop growth models. Such findings tend to be .site specific, and usually fail adequately to describe geographical variations © Agricultural and Food Science in Finland Manuscript received February 1996 329 Vol. 5 (1996): 329-350. AGRICULTURAL AND FOOD SCIENCE IN FINLAND https://www.c-info.fi/en/info/?token=QPNWj-yEyq0TvhJ8.ELtMDgFWYMLEgu5Rf_W1CQ.9WfqnIrRKiksF_sfMo8QWxJIVa2WgBgYLPwxBqOn2BqdWJGrlIdIEA8jIK_RSpJhTOkzXzTUz-OY5h3BnRnuf24PfgmlM0hqtv71j1k_1mM4ISCR_O2kJL9DLN6mZzML9U0fxySlBPKHgNvC84vk1MsRSUT9S4F8E3McepBQ0BG6_0WM5-3bH038h3LtDvw_J66L9aL-wbxdS29pLgpcOt4l9nKO933fI60il4dY-DbQUQYu9l4zSH2rnERH9lj0EaJNlyRIybgVva_E_DTIMAQ9dTldFrZEVFIjLRr1D3qCESEYu35eY36ussPX in crop response. However, knowledge about possible changes in the regional pattern of crop potential may be of great value to agricultural decision makers. Several previous climate change studies in Europe have focused on changes in crop suita- bility, using simple models to delimit regions in which future agroclimatic conditions would be appropriate for successful crop cultivation. Stud- ies have been reported of wheat (Kenny et al. 1993, Brignall et al. 1994, Bindi et al. 1993), maize (Carter et al. 1991a, Kenny and Harrison 1992a, Brignall et al. 1994); sunflower and soy- bean (Carter et al. 1991b), grapevine (Kenny and Harrison 1992b) and cauliflower (Kenny et al. 1993). Fewer studies have attempted to estimate regional crop productivity using mechanistic crop growth models. Some model site yields and attempt to scale up to the surrounding region or country using qualitative criteria (e.g. Wolf 1993, Wolf and van Diepen 1995; and, in a global study, Rosenzweig and Iglesias 1994) or using objec- tive interpolation and extrapolation (e.g. Wil- liams et al. 1988 in Canada; Rötter and van Di- epen 1994,Davies et al. 1993). A small number have run simple crop growth models over a reg- ular grid, using interpolated long-term mean cli- matological data as input (e.g. Leemans and Solomon 1993 at global scale, Jones and Carter 1993, Harrison et al. 1995). To our knowledge, no grid-based modelling studies have yet con- sidered both the mean and the interannual varia- bility of regional crop response to a changing climate. Variability of crop potential can be as important as the mean because it is a measure of the risk and reliability of crop production (Mearns et al. 1992,Semenov and Porter 1995). In this paper, we present results ofa study to estimate the regional suitability and potential productivity of selected crops in Finland under a changing climate. We demonstrate, for the first time, the application of crop models over a reg- ulargrid to evaluate changes not only in the mean but also the variability of regional crop poten- tial. In addition, we provide an illustration of the changing pattern of damage potential from pests and diseases. Some of the major uncertainties of the approach are quantified and a number of future research needs identified. Methods Geographical analysis system The approach adopted in the study employs a national-scale geographical analysis system in conjunction with crop-climate models (Carter and Saarikko 1996). The models, which range from simple agroclimatic indices to complex crop growth simulation models, are run using data organised in a network of 3827 grid boxes at 10 x 10 km resolution across Finland. Environmental data at this resolution have been obtained forclimate, land cover and topog- raphy, but gridded soils data for Finland are not available. Regional agricultural data on cropped area and yields were also obtained to map the current production pattern and to validate the indices and models. A geographical information system, IDRISI, is used to combine the data and display the results. Climatological data are for the baseline pe- riod 1961-1990, the standard reference used in the Finnish Research Programme on Climate Change (SILMU). Station data for each year of the period and for 30-year means have been in- terpolated to the 10km grid by a kriging method (Henttonen 1991) at the Finnish Meteorological Institute (FMI). The data include monthly pre- cipitation and monthly means of maximum, min- imum and mean temperature and global solar radiation. Observed values of radiation were supplemented with values derived from obser- vations of cloudiness and sunshine duration. In addition, daily data were obtained from FMI for various climatic variables at individual meteorological stations in Finland. These data were used for model validation. An alternative source of daily climatological time series (for precipitation, mean temperature and cloudiness) was a stochastic weather generator, CLIGEN 330 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et ai: Assessing regional crop potential under a changing climate in Finland (Posch 1992, 1994, Carter et al. 1995). The pa- rameters of CLIGEN were derived for all mete- orological stations reporting daily data in Fin- land during the period 1961-1990. Daily time series can be generated for any point in Finland, by interpolation of the station parameters. Daily solar radiation values are derived from cloudi- ness amounts using empirical relationships es- tablished from site data. Model testing and application to the grid The models are described in the next section. Each model was subjected to conventional sen- sitivity testing, in order to evaluate possible sources of model uncertainty. Where possible, model outputs were validated against observa- tions from experimental sites, variety trials, pest and disease observation networks and regional statistical sources. Particular attention was paid to the performance and applicability of models across the full range ofenvironmental conditions currently found in Finland, to justify applying the models to the grid. Moreover, models were also tested for climatic conditions outside the range experienced in Finland, to assess their applicability for simulating effects of climate change. The approach used to conduct model simu- lations over the 10km grid varied between mod- els. All models operate on a daily time step, but their input datarequirements vary widely. Most of the models of crop and pest/disease develop- ment are based on measures of accumulated tem- perature, which can be evaluated to an accepta- ble accuracy using daily temperatures interpo- lated from mean monthly temperatures. Howev- er, several models are highly sensitive to the within-month daily variability of climate, espe- cially precipitation. For these models, realistic daily data were required at each grid box. Where soil parameters were required, in the absence of gridded soil data the parameters of generic soil types were defined, and models were run for each soil type across the entire grid. Simulating a changed climate Climate changes were simulatedby altering the baseline climatological data according to the SILMU climatic scenarios (Carter et al. 1995, Carter 1996). The basic scenario employed in all model simulations is SILMU policy scenario 1 (central “best guess”) for 2050. However, some model runs have also been conducted for the range ofscenario uncertainty, using SILMU pol- icy scenarios 2 (low) and 3 (high), and for time horizons of 2020 and 2100. These scenarios specify seasonal changes which are uniform over the whole ofFinland. In addition, several runs have also explored variants of scenario 1, using the SILMU scientific scenarios la, lb and Ic. These specify the regional pattern of change on a monthly basis, based on estimates from differ- ent global climate models. All SILMU climatic scenarios are accompanied by consistent scenar- ios of carbon dioxide concentration, which are required as inputs to some yield models (Carter 1996). In the simulationsreported here, the baseline climate at a future date has been adjusted ac- cording to each scenario by applying the same changes to all years of the baseline period. This approach treats the future climate as ifit were in equilibrium. In reality, of course, the future cli- mate is unlikely to be in equilibrium, but will be changing continually. However, exploratory crop model simulations indicate that removing the trendfrom the scenario climate does not signif- icantly alter the crop response. Models Five different models or sets ofmodels have been employed in the study. They are described briefly here, but all are documented in detail elsewhere. Their selection should not imply that they are any more appropriate for this application than other models - it merely indicates that a model was available for this study, and sufficient data 331 Voi 5 (1996): 329-350. AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et al: Assessing regional crop potential under a changing climate in Finland could be obtained for model testing. Other mod- els will be applied to the grid at a later date. Cereal development models Phenological models have been constructed to estimate the growing time and phasic develop- ment of spring-sown cereal cultivars (Saarikko and Carter 1996). Relationships were examined between environmental factors (temperature, precipitation and photoperiod) and phenological observations after sowing (heading and yellow ripening) at experimental stations in Finland during the period 1970-1990. Temperature alone was found to explain the course of phenological development, and a linear relationship was es- tablished between daily mean air temperature and daily development rate for all phases and cultivars (Figure 1). Models were constructed for three cultivars of wheat ( Triticum aestivum), of barley (Hordeum vulgare) and of oats (Arena saliva) for the phases sowing to heading, head- ing to yellow ripening and the entire phase sow- ing to yellow ripening. In order to apply the model to the grid, the beginning and end of a “favourable growing pe- riod” need to be defined. Sowing of spring cere- als was assumed to take place on the day when smoothed daily mean temperature exceeds B°C, based on sowing date information from the ex- perimental sites. The end of the favourable grow- ing period is defined by the date on which mean daily temperature falls below 12°C. This date approximately corresponds to the 25% probabil- ity of first autumn frost occurrence in Finland as computed by Solantie (1987). When estimating crop development across the Finnish grid, smoothed daily mean air tem- peratures were obtained from monthly means using the Brooks sine curve interpolation meth- od (Brooks 1943). The development ofeach cul- tivar was computed for individual years during the 30 year baseline period and during 30 year periods corresponding to a range ofSILMU sce- narios. Barley yield simulation model Barley is grown widely in Finland, accounting for about 20% of the cultivated area in 1993 (Agricultural Information Centre 1994). Barley yields have been simulated using a process-based crop growth model, CropWatN, developed at the Department of Plant Production, University of Helsinki (Karvonen and Kleemola 1995). The model calculates crop growth and development on a daily basis as a function of global radia- tion, mean air temperature and precipitation. Simulations can be conducted either for poten- tial production or for soil water and nitrogen lim- ited production. The direct effects of increasing atmospheric C0 2 concentration on plant photo- synthesis are also computed. The main features of the model are described by Kleemola and Karvonen (1996), the only differencebeing a less detailed soil temperature scheme in the version used here than in their updated model. The model was calibrated using detailed ob- servations of climate, soils and the growth and development of barley (cv. Porno) from experi- ments at Jokioinen during 1982-1987 (Ilola et al. 1988). Values of more than 30 parameters were required, and many of these were site spe- Fig. 1. Relationship between mean development rate (day' 1) and mean temperature (°C) in spring wheat (cv. Ruso) for the phase sowing to yellow ripening. Broken lines are 95% confidence limits. (Data source: Official variety trials, Ag- ricultural Research Centre of Finland) 332 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. cific, since they related to soil properties. A pri- or sensitivity analysis indicated that modelled yields could be highly sensitive to parameter values relating to the movement of water in the soil. To test whether the model could be applied to other conditions in Finland, data on phenolo- gy, fertilizer application, soil type and yields were obtained for official variety trials at four experimental stations in different parts of Fin- land during the period 1970-1990. Since meas- ured soil characteristics were not available, pa- rameter values for the fine sand, sand loam and silty clay types reported from the sites were es- timated based on published material (J. Kleemo- la, personal communication). The model was run using weather data from each site. A comparison of simulated against observed grain yields at the four sites is given in Figure 2, classified by soil type. There is a positive rela- tionship between the two (r = 0.48) although the scatter is quite large. Some of the discrepancies between the modelled and observed values are clearly systematic and related to soil type. This is not surprising, given that the precise nature of the soils at each site was not known. These re- sults were encouraging enough, however, to jus- tify applying the model at national scale. In order to apply the model to the grid, two soil types were selected, representing a range of water holding characteristics: a heavy clay type, using the measured parameters from Jokioinen, and the fine sand type, using the same parame- ter estimates used in the validation exercise. Parameters for crop phenology were those re- ported for the Porno cultivar by Saarikko and Carter (1996). Daily temperature and radiation data were obtained from monthly data using the Brooks interpolation technique (Brooks 1943). The ef- fect of using smoothed temperature and radia- tion data was evaluated in an earlier sensitivity analysis, and found to produce an overestimate of final yield compared with using observed dai- ly values of about 19%. This is to be expected since daily extremes of temperature and radia- tion, which inhibit growth, are not represented in the smoothed data. Gridded monthly precipitation was allocat- ed between days according to the frequency dis- tribution of precipitation observed at Jokioinen during 1961-1990. Given the high sensitivity of the modelled yield to soil water, this technique produced the most realistic precipitation distri- bution of several methods tested. Model runs were conducted for the 30 indi- vidual years of the 1961-1990 baseline and for a 30-year scenario climate representing 2050, us- ing SILMU scenario 1. The model was run at all grid boxes for unstressed (potential) conditions and for rainfed conditions on both soil types. Simulations were run for scenario temperature and precipitation changes alone, for elevated C02 concentration (523 ppm) alone, and for these two conditions combined. Maize yield simulation model Maize (Zea mays) is a tropical crop occasional- ly grown for silage and sweet corn in Finland. Trials conducted in the 1970 s in southern Fin- land suggested that with very early hybrid vari- eties a mature grain yield could be harvested twice in ten years, good quality silage material obtained six years in ten and a satisfactory crop eight years in ten (Pulli et al. 1979).Later work, at European scale, indicated that climatic warm- Fig. 2. Simulated vs observed grain yield in barley for three soil types at tour sites in selected years during 1970-1990. Modelled phenology is fixed at observed dates (Data source: Official variety trials.Agricultural Research Centre of Fin- land) 333 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et al.: Assessing regional crop potential under a changing climate in Finland ing of 3-4°C would have the potential to shift the northern limit for economic yields of grain maize from northern Germany and central Po- land, where it lies today, into southern Finland (Carter etal. 1991a, Kenny and Harrison 1992a). The CERES-Maize model (Jones and Kiniry 1986) has been adopted in this study. It has been used in a number of previous climate change studies in different parts of the world (e.g. Rosen- zweig and Iglesias 1994). Like CropWatN, CERES-Maize attempts to simulate the main processes of crop development and growth. It requires daily minimum and maximum temper- ature, global radiation and precipitation as in- puts. A key requirement for running the model is the selection of parameters characterising the crop phenology and yield capacity. These were estimated for a short-season hybrid, based on information given by Pulli et al. (1979). Model simulations with the CERES-Maize model were exploratory, and the only runs con- ducted to date have been for potential yields. They are thus independent of soil type and as- sume no water or nutrient stress. Gridded data on monthly climate were converted to daily val- ues in the same way as for the barley model. Sim- ulations were conducted for each year of the 1961-1990 baseline climate and for the climate estimated for 2050 under SILMU scenario I. Effects of C02 increase on crop growth were not modelled. Nematode models Simple models of two pests of potato (Solanum tuberosum) have been applied to the grid. One, the potato cyst nematode, is a troublesome pest at the present-day. The other, the Columbia root- knot nematode, could represent a serious threat in the future (Tiilikkala et al. 1995). The potato cyst nematode {Globodera rosto- chiensis), is the most noxious pest in present- day Finnish potato production. This parasite is restricted in its range by temperature to south- ern and central Finland (Tiilikkala 1991). Its absence from northern Finland is a valuable as- set for the production of high quality seed pota- toes. The northern limitof the nematode approx- imately coincides with an effective temperature sum (ETS) of 800 day-degrees above a base tem- perature of 5°C, cumulated during the period with air temperatures exceeding 9°C (Tiilikka- la, personal communication). The Columbiaroot-knot nematode (Meloido- gyne chitwoodi), is a newly discovered nema- tode pest in Europe (Tiilikkala et al. 1995). It has a wide host range and is well adapted to low temperatures. The nematode is a serious pest of potato in the Pacific Northwest of the USA, but has only recently been discovered in Europe, in the Netherlands. M. Chitwoodi can overwinter as eggs and juveniles. This pest, unlike G. ros- tochiensis, can produce multiple generations, the number dependent upon the soil temperature. An extra generation, especially late in the season, will result in a tremendous increase in popula- tion densities. The model used here is again based on effec- tive temperature sum above a base temperature of 5°C, but cumulated in this case during the period with air temperatures exceeding 5°C. The approximate day-degree requirements for differ- ent generations have been defined in a pest risk assessment by Tiilikkala et al. (1995). Both nematode indices have been computed across the Finnish grid, using daily temperatures interpolated from the monthly means (as de- scribed above) for each of the 30 years of the baseline climate and for the baseline values adjust- ed according to a number of SILMU scenarios. Potato late blight model Potato late blight (Phytophthora infestans) is a damaging fungal pathogen that grows in the leaves and stems of the potato plant. It progres- sively kills the tissues and reduces the effective photosynthetic area of the plant. As a result, lit- tle assimilate is passed to the tubers and yield is reduced. The spores are dispersed by rain, and can initiate new infections on leaves or, if washed into the soil, on the developing tubers. 334 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. The onset of late blight has been closely monitored in recent years at seven sites in Fin- land, as part of a Nordic observation network established in 1992. Results from this monitor- ing network have been used to develop a simple index of blight onset based on a daily tempera- ture sum cumulated on wet days (Kaukoranta 1996). This index has been coupled to a tuber growth model simplified from the more detailed model of MacKerron and Waister (1985). The model computes potential daily tuber growth based on radiation and temperature, assuming that water and nutrients are not limiting. The coupled model is first run through to harvest to compute the potential tuber yield assuming no blight symptoms. Subsequently, the model is run again, this time calculating the date of onset of blight symptoms, whereupon the leaf area index is reduced to zero over a two week period, thus curtailing tuber growth. The difference between the accumulated tuber growth from the date of first symptoms until harvest and the blight-af- fected tuber growth represents the potential tu- ber loss due to the disease. More details of the site validation of this model for Finnish condi- tions are given by Kaukoranta (1996). A key requirement in applying the model to the grid was for daily temperature and precipi- tation data, to define the onset of blight. Realis- tic daily values could not be obtained by inter- polating the gridded mean monthly values, so instead the stochastic weather generator, CLI- GEN, was used to produce daily climatic time series. To test the validity of using CLIGEN, the model was first tested for individual meteoro- logical stations in Finland to compare results based on the stochastically generated weather with those based on observed weather during 1961-1990. The analysis revealed that the weath- ergenerator underestimates the inter-annual var- iability ofclimate on a seasonal basis because it fails to replicate accurately the persistence of weather events such as warm spells and droughts. As a result, while the mean of modelled tuber loss was similar in both cases, the variance based on generated weather was lower than that simu- lated for the observed conditions. Thus, results from the grid should be interpreted as conserva- tive estimates of tuber loss - the actual variabil- ity of losses is likely to be greater than depicted. The parameters of CLIGEN were interpolat- ed to each grid box location, and 30-year time series of baseline and scenario climate were gen- erated for all boxes across the grid. All three SILMU policy scenarios were simulated for 2020, 2050 and 2100. Results Given the numerous models applied to the grid system, and the multiplicity of scenarios exam- ined, it is only possible in this paper to provide a short synthesis of the major results obtained. More detailed findings are published elsewhere (e.g. Carter and Saarikko 1995, 1996). At the outset, it should be stressed that the mapped results obtained in this study are pre- liminary and are designed to be illustrative. The maps depict patterns of crop potential that are climatically determined, and do not account for factors such as the local soils, land cover and terrain. Over large regions these factors would preclude crop production altogether. Methods of identifying and excluding such regions from analysis are currently being addressed. Regional suitability of spring cereals Three aspects of the regional suitability for ce- reals under changing climate are summarised in this section: changes in crop risk and reliability, shifts in patterns of suitability and changes in rates of phenological development. Uncertain- ties associated with all of these are considered in a later section. Changes in crop risk and reliability. As cli- mate warms, so the probability of modelled crops reaching the yellow ripening stage increases. In 335 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. etai: Assessing regional crop potential under a changing climate in Finland Fig. 3. (a) Actual cultivated area of spring wheat in 1990 as a percentage of total arable (source: Finnish Board ofAgricul- ture); (b and c) estimated probability ofsuccessful ripening (percent) for cv. Ruso under the baseline, 1961-1990climate (b) and SILMU scenario 1 (best guess) by 2050 (c). 336 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. cereals, the importance of reaching this stage depends on the final use of the crop. For exam- ple, reliable attainment of full maturity is more important on farms where good quality cereal production represents a major source of income, than on farms where it merely supplements oth- er activities. The estimated regional probability of ripen- ing for an early-maturing spring wheat cultivar (cv. Ruso) is shown in Figure 3b for the base- line climate. As might be expected, the reliabil- ity of wheat cropping is greatest in the warmer south of Finland and declines northwards. This map can be compared to the actual pattern of cultivation for all spring wheat varieties in 1990 (Figure 3a), which is representative of the aver- age present-day distribution. The northernmost cultivation areas are approximately coincident with the 60% probability limit, while the zone of most intensive cultivation (>lO% of total ar- able area) coincides with a reliability well in excess of 80%. For barley and oats, the corre- sponding probabilities are lower, probably re- flecting the lower dependence on ripening for these crops. Figure 3c illustrates the corresponding prob- ability zones mapped for the climate in 2050 under SILMU scenario 1 (mean annual warm- ing of 2.4°C). Here, the zone of high (>80%) reliability extends into central Finland and there is approximately an even chance of successful ripening in southern Lapland. Shifts in the pattern of suitability. We have adopted the 80% probability level to define the limit of suitability for all cereal species in our subsequent analyses, assuming that farmers would be willing to accept a crop "failure" in 2 years out of 10. Shifts in suitability for each crop have been mapped for 2020, 2050 and 2100 un- der SILMU scenario 1, relative to the baseline. This is illustrated for barley (cv. Porno) in Fig- ure 4. The geographical extent of these shifts is summarised in Table 1 for acultivarofeach crop. The shifts can also be interpreted as rates, which are shown as averages at the bottom of Table 1. These imply that under the best guess SILMU scenario the northern limit of reliable cereal cul- tivation in Finland would shift northwards by, on average, about 45-60 km per decade up to 2100. Changes in the rate of phenological devel- opment. Higher temperatures increase the rate of phenological development ofcereal crops (cf. Figure I) so that plants can complete a given phase in a shorter period. Figure 4 demonstrates how the phase heading to yellow ripening in barley (cv. Porno) progressively shortens as the climate warms under SILMU scenario 1. The duration of this phase is of particular interest, as it contains the grain filling period. A marked foreshortening of the phase would be expected to reduce grain yields, an effect confirmed in simulations with the barley growth model, CropWatN (see below). Table I. Estimated shifts in the northern limit ofsuitability relative to thebaseline for cereal cultivars under SILMU scenario 1 (best guess) by 2020,2050 and 2100, and the mean rate of shift up to 2100 (km/decade). Shifts under SILMU Spring wheat Spring barley Oats scenario 1 (cv. Ruso) (cv. Aira) (cv. Veli) 24°E 29°E 24°E 29°E 24°E 29°E 2020 (km) 150 150 90 290 130 280 2050 (km) 270 460 230 340 280 500 2100 (km) 550 640 490 620 550 630 Mean rate to 2100 (km/decade) 50 58 45 56 50 57 337 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et ai: Assessing regional crop potential under a changing climate in Finland Fig. 4. Simulated change in duration of the phase heading to yellow ripening in barley (cv. Pomo) relative to the 1961-1990 baseline for SILMU scenario 1 (best-guess) by (a) 2020, (b) 2050 and (c) 2100. Units are days and areas of expanded suitability are also shown. 338 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. Changes in regional cereal yields: the case of barley The results presented in this section are for bar- ley. However, given the similarities of growth habit between spring-sown barley, wheat and oats in Finland, the regional pattern of response to climate change shown here can be regarded as broadly indicative of responses for all three cereals - only the specific location and details of changes differ. Simulations with the CropWatN model used the phenological development model for barley (cv. Porno) mapped above and similar methods to compute sowing and harvest dates. Here, the modelled estimates of dry matter yield within the zones of suitability (i.e. 80% reliability) are reported for both stressed and unstressed crops. Estimates of the 30-year mean potential grain yield for the baseline period are about twice those reported from agricultural districts in annual sta- tistical yearbooks, which is not surprising given that nutrients and water were unlimiting in these runs. Simulated baseline yields for a fine sand soil were close to the potential values, an unre- alistic result which is probably attributable to inappropriate selection of soil parameters as de- scribed earlier. In contrast, the mean yields esti- mated for a heavy clay soil (Figure sa), includ- ing water limitations and assuming an annual nitrogen fertilizer application of 100 kg/ha, are much closer in magnitude to those reported op- erationally in Finland. Note, however, that since a uniform heavy clay soil is assumed over the whole country, the regional pattern of modelled yields cannot be compared with the actual yields, on a range of soils, reported from different parts of the country. The pattern depicted indicates the highest yields in east-central Finland, declining to the north, mainly as a function of low tem- perature, and towards the western coast, where the mean growing season soil water deficit is greatest. To compare the relative effects of increasing C02 concentration and of changing climate ac- cording to SILMU scenario I by 2050, both were analysed separately and then in combination. Figure 5b shows the modelled mean yield for temperature and precipitation changes alone. Climate change alone has a negative effect on the yield of the Porno barley cultivar over the whole of southern Finland (compare with Fig- ure sa). This is primarily due to the shortening of the grain filling phase under the increased tem- peratures (cf. Figure 4), although increased pre- cipitation (by 6% in the summer months under this scenario) serves to modify this effect. Fur- ther north, however, the higher temperatures are beneficial for this variety of barley, enhancing yields and shifting the northern limit of reliabil- ity some 300 km northwards. The yield response to elevated CO, (523 ppm) alone, assuming no change in the climate, is positive (less than 1 t/ha) with little variation across the country (not shown here). The com- bined effects of increased CO, and climate change are shown in Figure sc. Yield responses are positive across the whole country, with the beneficial effect of increasing CO, slightly out- weighing the negative effect of higher tempera- tures in southern Finland. The pattern of chang- es for both the potential and fine sand simula- tions are very similar to those for clay, but the magnitude of changes is proportionally greater since crops experience little or no water and nu- trient stress in these simulations. Estimates of the inter-annual variation of yields were also obtained. The standard devia- tion of modelled annual yields on heavy clay under the present-day climateranges from about 1 t/ha in the south of Finland to approximately 2 t/ha at the northern limit ofreliability. This de- creases under the 2050 scenario over much of southern and central Finland and increases slight- ly in the extreme south as well as in some north- ern regions which were unsuitable under the baseline climate. Changes in pest and disease risk of potato Potato cultivation in Finland extends north of the Arctic Circle, but yields are constrained by the short growing season as well as occasional drought during the period of growth. Potato sel- 339 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. etai: Assessing regional crop potential under a changing climate in Finland Fig. 5. Modelled grain yield of barley (cv. Pomo) on a heavy clay soil (t/ha) under (a) the baseline climate, 1961-1990, (b) SILMU scenario 1 (best guess) by 2050 for climate (temperature and precipitation) change only, and (c) SILMU scenario 1 for climate and CO, changes combined. 340 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. dom reaches physiological maturity anywhere in Finland under the present-day climate, its growth usually curtailed in the autumn by frost or sur- plus soil water. Results from the coupled late blight/potential tuber growth model indicate that for the warming by 2050 under SILMU scenario 1 (central), the crop would reliably reach full maturity in the south ofFinland before low tem- peratures became a risk for harvesting. For this reason, in spite of an earlier sowing date, the growing period would actually shorten by about 10 days for present-day cultivars of potato. In contrast, the growing period would extend by 3 4 weeks in the north of the country. Under this scenario, potential dry matter tuber yields in- crease by some 3-4 t/ha (about 20-30%) in southern Finland and by more than 5 t/ha in some central and northern areas, where little growth is possible under the baseline climate. Howev- er, soil moisture and C02 effects still need to be incorporated in the model before a more realis- tic pattern of response can be obtained. While the prospects for potato yields appear favourable under a warming, the potential for pest and disease damage of the crop also increas- es. Under SILMU scenario 1 (2050), the north- ern limit of the potato cyst nematode (the medi- an limit during the 30 years simulated) extends on average by about 250 km northwards from its location under the baseline climate, occupy- ing many of the areas of current seed production in Lapland (Figure 6). Under SILMU scenarios 2 and 3 (low and high), northward shifts by 2050 average about 50 km and 400 km, respectively. The effect of future warming on the poten- tial development of the Columbian root-knot nematode, were it to be introduced in Finland, is no less significant. The model results suggest that under the baseline climate this species would be capable of producing one full generation and hatching a second over much of southern and central Finland (Figure 7a). In warmer years such as 1975 and 1988, it could complete a second generation and hatch a third in the most favour- Fig. 6. Potential distribution of the potato cyst nematode (Globodera rostochiensis) based on temperature (median limit) under the baseline climate, 1961-1990, and its extension by 2050 under three alternative future climates: SILMU low, central (best guess) and high policy scenarios. 341 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. etai: Assessing regional crop potential under a changing climate in Finland able regions. Under the scenario I warming by 2050, the nematode would be capable in an av- erage year of producing two full generations and hatching a third in southern Finland (Figure 7b), with the possibility in warmer years of complet- ing a third and hatching a fourth generation at a few locations. The damage implications of such changes are self-evident. Finally, the results of the simulations of po- tato late blight also indicate an increased risk of occurrence and damage potential for unprotect- ed crops. Figure 8a shows the estimated tuber loss under the baseline climate. This is greatest in the south ofFinland, where yields are highest and where blight symptoms, and hence losses, are estimated to occur in most or all years (not shown). Losses are negligible north of the Arc- tic Circle. Under SILMU scenario 1 for 2050, the date of onset of blight symptoms is earlier than for the baseline by some 20 days in the south and 30 days in the north. In the absence of crop pro- tection, losses would occur in every year over all of central and southern Finland, and the an- nual risk of blight is greater than 50% over most of the remainder of the country. Average tuber losses increase over the whole country relative to the baseline, with the greatest increase in loss Fig. 7. Potential number of generations of the Columbia root-knot nematode (Meloidogyne chitwoodi) based on temperature under: (a) the baseline climate 1961-1990 and (b) SILMU scenario 1 (best guess) by 2050. 342 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. occurring in central Finland, where the increas- es in potential yield are estimated to be largest (Figure 8b). The estimated increase in loss due to late blight is similar in magnitude and may even exceed the simulated increase in tuberyield over much of central and southern Finland, but yield gains outweigh losses in the north. Changes in the potential for cultivating new crops: the case of maize All of the above model simulations pertain to crop varieties that are cultivated at the present- day in Finland. One important conclusion is that as the climate changes, these varieties will be- come progressively maladapted to the new en- vironment. An obvious farming response is to substitute these with different varieties or even with new species that can properly exploit the changed conditions. One candidate as a substi- tute crop for a warmer climate is maize, and the model simulations with CERES-Maize were in- tended to assess the potential for this crop under the changed conditions. The results of these simulations are summa- rised in Figure 9. Even in the most favourable areas of the country, a measurable (non-zero) Fig. 8. Simulated potential tuber loss in potato (t/ha) due to late blight (Phytophthora infeshms) under: (a) baseline climate, 1961-1990and (b) SILMU scenario I (best guess) by 2050. 343 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et al: Assessing regional crop potential under a changing climate in Finland grain yield can only be expected in about 6 years in 10 (Figure 9a). Over most of the country, dur- ing most years, the crop would not even reach the grain filling stage of development. 30-year average baseline yields for an unstressed crop are estimated to be about 2 t/ha at isolated loca- tions in southern Finland, although in favoura- ble years yields as high as 7 t/ha are simulated. Except for these rare instances, however, it is unlikely that the grain yield would be of a suffi- cient quality for any use other than green fodder or silage. Under the temperature changes given by SIL MU scenario 1 by 2050, the probability of ob- taining a non-zero grain yield is estimated to have increased to 100% in southern Finland, and measurable yields could be obtained in over 50% of years as far north as Oulu (Figure 9b). The mean level of potential maize yields estimated under this scenario exceeds 7 t/ha in the most favourable areas (10 t/ha in warm years), with yields averaging 4 t/ha or more over a sizable part of southern Finland. The effects of increas- ing CO, concentrations on crop photosynthesis, which are not modelled here, are likely to be much lower for a crop like maize, with a C 4 pho- Fig. 9. Simulated probability (percent) of obtaining measurable (non-zero) grain yield of maize under: (a) baseline climate 1961-1990and (b) SILMU scenario I (best guess) by 2050. 344 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. tosynthetic pathway, than for C 3 crops like bar- ley and potato (e.g. see Reilly et al. 1996). C02 and water stress effects will be investigated in further work with the model. Quantifying the uncertainties We have presented results from a diverse set of models and for a range ofclimatic scenarios. The results are preliminary, and all are subject to uncertainties. In an attempt to quantify some of these uncertainties, four sources of uncertainty have been identified and compared using the development model for spring wheat (cv. Ruso) described earlier: cultivar type, model error, glo- bal scenario assumptions, and regional scenario differences. Cultivar type. The response of a given crop species to climate varies widely among differ- ent cultivars of that crop, a diversity that forms the whole basis of plant breeding. The differenc- es in response of two cultivars of wheat (Ruso and Kadett), chosen to represent the range of growth traits in Finnish cultivars, are shown in Figure 10a. Though this is not strictly a measure of uncertainty, it does indicate what range of re- sponses are implied when generalising the be- haviour of individual crop species. Model errors. The quantification of model errors and uncertainties is perhaps the single most difficult and time consuming task in mod- el testing. However, the importance of such ex- ercises cannot be overstated, as the credibility of the results depends upon a good knowledge of model accuracy. Here we use as a simple example the phono- logical models for cereals described above. The uncertainty of the linear relationship between temperature and development rate is delimited as 95% confidence limits around the regression line in Figure 1 (dashed lines). These confidence limits can be expressed geographically as uncer- tainties in the limits of suitability (Figure 10b). Compared to the differences between cultivars (Figure 10a), this source of uncertainty appears fairly modest. However, if the uncertainty of any single point plotted in Figure 1 were to be eval- uated, the plotted and mapped range of uncer- tainty would be much greater. Wider uncertain- ty ranges than shown in Figure 10b would also be expected for results from the other models described in this paper, were they to be evaluated. Global scenario assumptions. By far the greatest source of uncertainty in the estimates of future crop potential shown here is attributa- ble to the range of SILMU temperature scenari- os. This range accounts for uncertainties at the global level of both greenhouse gas emissions into the atmosphere and the mean climate re- sponse to changing atmospheric composition (Carter 1996). The magnitude of the uncertainty range is illustrated in Figure 10c, which shows the shift in suitability of spring wheat (cv. Ruso) by 2050 for each of the SILMU policy scenarios (low, central and high). The range of estimates varies from a low estimate averaging about 100 km under scenario 2, to a high estimate of about 550 km under scenario 3.Similar results are also obtained for the other cereal crops. Regional scenario differences. The SILMU policy scenarios only express the uncertainties at global level. There are further uncertainties to consider at a regional level, some of which are represented in the SILMU scientific scenar- ios. These are based on alternative regional pat- terns of temperature change specified by gener- al circulation models (Carter 1996). The effect of this source of uncertainty on crop suitability is shown in Figure lOd. Differences in the limits of suitability under alternative regional climate predictions appear to be of the same order of magnitude as corresponding differences assum- ing alternative crop cultivars (Figure 10a). Discussion The major findings of this study can be summa- rised as follows: 1) A warming of the climate is estimated to induce shifts in the northern limit of cereal cul- 345 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Carter, T. R. et al: Assessing regional crop potential under a changing climate inFinland Fig. 10. Range in estimates of suitability for spring wheat (cv. Ruso) attributable to: (a) cultivar type (Ruso and Kadett under the baseline climate), (b) uncertainty of the development model (baseline climate), (c) uncertainties in projections of global climate change (extension under the SILMU low, central and high policy scenarios by 2050) and (d) uncertainties in projections of regional climate change(extension under the SILMU scientific scenarios - GFDL, UKTRand MPI by 2050). For explanation see text. SILMU scenarios are described in Carter (1996). 346 AGRICULTURAL AND FOOD SCIENCE IN FINLAND Vol. 5 (1996): 329-350. tivalion of between 100 and 150 km per °C in- crease in mean annual temperature. Under the best guess SILMU scenario, this translates into a mean northward shift of about 50 km per dec- ade up to 2100. 2) Average grain yields of present-day bar- ley cultivars in 2050 are estimated to be greater than at present over the whole country, with the greatest increases in north-central Finland un- der the best guess SILMU scenario for a combi- nation of changed climate and increased C02 concentration. However, increased temperature alone has a negative effect on yields in southern Finland, due to a shortened grain filling period. 3) The risk of crop damage by pests and dis- eases increases in all regions under a warming of the climate. Northward shifts in the distribu- tion of certain pests could be of a similar mag- nitude and rate as reported above for cereal crops. Additional generations of multivoltine pest species can also be expected. The damage potential of diseases such as potato late blight could increase at a similar rate as the potential increase in yields of the crop host. 4) The opportunities for cultivating new crops in Finland could increase under a warmer cli- mate. Estimates suggest that grain maize could be cultivated reliably by 2050 in many parts of southern Finland under the best guess SILMU scenario. 5) Uncertainties surround all of these esti- mates. The largest uncertainty is that attributa- ble to estimates of future climate, but other un- certainties to consider include model errors and assumptions, observation errors, and alternative modelling methods. The results represent an early attempt at de- picting the regional effects of climate change on Finnish agriculture. Considerable efforts are still required to refine the methods and to improve the models. Future research efforts should con- centrate on the following areas: Further testing and validation of existing models, to establish their credibility when ap- plied in climate change studies. In addition to rigorous sensitivity analyses, this also re- quires the acquisition of validation material from controlled experiments and from re- gions with a warmer climate than in Finland Refining methods of scaling-up from site models to the regional-scale, including im- proving methods of spatial model validation, analysing and depicting uncertainty and testing and applying stochastic weather generators. Improving the realism of crop potential map- ping, by accounting for local features of land cover, soils and topography which may pre- clude arable agriculture altogether. Widening the focus to consider climate change effects on other crop species, includ- ing the major food and non-food crops cur- rently grown and those potentially viable under a changed climate. Models will need to be tested for each crop considered. Considering more aspects of farm-level ad- aptation to changing climate, for example, adjustments in fertilizer application, timing of operations, crop switches and irrigation. The effects of all of these can be simulated with appropriate models. Evaluating the effects of climate change on crop quality. There are many measures of quality, and most can be related to seasonal weather. CO, concentration is also known to affect some aspects of crop quality. Clearly there is much work still to be done if we are to obtain a more comprehensive and ac- curate picture of agricultural potential in Finland under the changing climate of the next century. Acknowledgements. We are grateful to a number of col- leagues for supplying models and advice: Jouko Kleemola of Kemira Oy, Espoo, provided the computer code of CropWatN and much assistance in calibrating the model. Timo Kaukoranta and Kari Tiilikkala of the Crop Protec- tion Department, Agricultural Research Centre ofFinland, Jokioinen, offered thepotato late blight and nematode mod- els, respectively. We also thank Eino Hellsten and Ari Venäläinen of the Finnish Meteorological Institute for set- ting up the interpolation routines for climatological data. This work was funded by the Academy of Finland as part of the Finnish Research Programme on Climate Change (SILMU). 347 AGRICULTURAL AND FOOD SCIENCE IN FINLAND 4 Carter, T. R. etai: Assessing regional crop potential under a changing climate in Finland References Agricultural Information Centre 1994. Agrifacts '94 about Finland. Helsinki. 31 p. Bind!, M., Castellani, M. Marrachi, G. & Miglietta, F. 1993. The ontogenesis of wheat under scenarios of in- creased air temperature in Italy: a simulation study. Eu- ropean Journal of Agronomy 4: 261-280. Brignall, A.P., Favis-Mortlock, D.T., Hossell, J.E. & Rounsevell, M.D.A. 1994. 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Mallien avulla tarkasteltiinerilaisten kevätveh- nä-, ohra-, kaura-, peruna- ja maissilajikkeiden ke- hitystä ja kasvua. Lisäksi selvitettiin perunaruton ja perunan kahden tuhoeläimen, peruna-ankeroisen ja juuren äkämäankeroisen esiintymisriskiä. Tarkastelu tehtiin sekä vertailukauden ilmasto-oloille (1961- 1990)että tulevaisuuden mahdollisille ilmasto-oloille eli skenaarioille, jotka kehitettiin osana Suomalaisen ilmakehänmuutosten tutkimusohjelmaa SILMUa. Tutkimustulokset on esitetty karttoina, joiden tär- keimmät johtopäätökset ovat: (1) Ilmaston lämmetes- sä viljojen viljelysopivuuden pohjoisraja siirtyy noin 100-150 km pohjoisemmaksi jokaista yhden asteen vuosikeskilämpötilan nousua kohti. (2) Ilmastonmuu- toksesta ja ilman hiilidioksidipitoisuuden kohoami- sesta johtuen nykyisin viljeltyjen ohralajikkeiden sa- dot kasvaisivat koko Suomessa vuoteen 2050 men- nessä. (3) Arvioitu ilmaston lämpeneminen siirtää ankeroislajien potentiaalisia esiintymisrajoja pohjoi- seen sekä lisää sukupolvien määrää, joita juuren äkä- mäankeroinen kykenisi vuodessa tuottamaan. Peru- nan viljelyssä myös ruttoepidemioiden riski lisään- tyy- (4) Vuoteen 2050 mennessä maissin viljelvar- muus olisi parantunut niin, että Etelä-Suomen edul- lisimmilla alueilla jyväsadot olisivat tyydyttäviä. (5) Esitetyt arviot kasvintuotantopotentiaalista ovat epä- varmoja, mikä johtuu ilmastoskenaarioista, mallien virheistä ja epätarkkuuksista, oletuksista ja havain- tovirheistä. 350 AGRICULTURAL AND FOOD SCIENCE IN FINLAND