View of Modelling growth and nitrogen balance of barley under ambient and future conditions

Modelling growth ^and nitrogen ^{balance of} barley under ambient and future conditions

Jouko Kleemola1

Department of^PlantProduction, P.O. Box27,FIN-00014 Universityof^{Helsinki, Finland} Tuomo Karvonen

Laboratory of^Hydrologyand Water Resources Engineering, UniversityofTechnology, ^Espoo,Finland

According to currentscenarios,atmosphericC0₂-concentration ([C0₂^])and average air temperature will rise in the future. The predicted longer growingseason ⁱⁿFinland would imply that more pro- ductive cultivars andeven newcropspeciescould be grown.Moreover, higher [C0₂^] is alsolikelyto increasedrymatterproduction of crops. This study analyzed thegrowthofspring barley⁽Hordeum vulgäre^L.)under ambientandsuggestedfutureconditions,and its response toNfertilization. Model simulations of soil temperature and ofsnow accumulation and melting werealso studied. The cali-

brationand validation results showed that the modelperformedwell insimulatingsnow dynamics, soil temperature, thegrowthofbarley,and the response of cropgrowthtoNfertilization under present conditions.According to the simulation runs,ifacultivar wasadapted tothelength of the growing period,the increaseindry^matterproduction was23% inalow estimate scenario of climate change, and56% inahigh estimate scenario under ahighlevel ofnitrogenfertilization. The simulation study showed that the shootdry weightincreasedby 43%,onaverage, underhigh N fertilization(150-200 kg N/ha), but byless (20%) underalow level ofN (25-50 kg N/ha) when the conditions undera central scenario for the year2050were^comparedwith the presentones.

Key words: C0₂concentration,climatechange,crop modelling,Hordeumvulgäre L.

‘Currentaddress: KemiraAgro, EspooResearchCentre, P.O. Box 44,FIN-02271 Espoo,Finland

Introduction

According to current scenarios, atmospheric C0₂-concentration([C0₂^])and average airtem- perature will rise in the future. Carter (1992)stat-

ed thatan increase of I,O°C in airtemperature may result in^a 10-day extension in the length of the growing seasonin Finland. The longer grow- ing _seasonwill enable spring cerealstobesown earlier.This, inturn,would meanthatmorepro- ductive cultivars and even new cropspecies

©Agricultural and Food ScienceinFinland Manuscript receivedFebruary 1996

Kleemola, J. ^&Karvonen, T: Modelling growth

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could be grown (Carter 1992).Moreover, in ad- dition^tothe increase in crop productivity caused by alonger growing period, higher [C0₂^] is like-

ly to increase net photosynthesis, and thus the dry _matter production of crops, in the future (Kimball 1983, Cure and Acock 1986).

A research group in the Department of Plant Productionatthe University of Helsinki has been developing _a crop model which ^canbe used to estimate the effect of changes in airtemperature and [C0

2^] on the development and growth of spring barley⁽Hordeum vulgäreL.).Inaddition, the model simulates moisture, N and tempera- ture dynamics in soil, and _snow accumulation and melting. After validating themodel, using data collected under present conditions, it can be used to estimate the impacts of climate changeon agricultural production. For example, the previous version of the model used in the present study has been applied over a 10 x 10 km grid across Finland in a study on climate change reported by Carteretal.(1996).

A recent study by Kleemola et al. (1995) showed thataprevious version of the modelwas capable of simulating the growth of spring bar- ley cultivated in heavy clay soil under ambient conditions. Their study also included test data collected in a greenhouse where the C0₂ was enriched above the ambient level. The model performed satisfactorily with these data^too.The same field datawere used in the^present study, in which the model wasconstructed differently from that used by Kleemola^etal.(1995). In this study, the model simulations of soiltemperature, the dynamics ofsnow cover, and the response of barley ^to N fertilization are compared with data collected underpresent conditions. More- over,the simulated effect ofincreases in airtem- perature and [C0

2^]on the growth of barley are also reported. The future conditionsare those suggested in scenarios developed for the Finn- ish Research Programme on Climatic Change (SILMU) (Carter etal. 1995, Carter 1996).Sim- ulationswere conducted for three policy-orient- ed scenarios of SILMU representing low, cen- tral, and high levels of change in climate and [CO,] by the year 2050. The respective climate

changes are: for annual precipitation +1.5%, +6.0% and +9.0%, and formean annualtemper- ature +O.6°C, +2.4°C and +3.6°C relativetothe present-day. For details of seasonal changes, see Carter (1996). The corresponding [C0₂^]scenar- ios are 456 ppm, 523 ppm and 555 ppm, com- pared^to apresent-day concentration assumedto be 350 ppm.

The mode

Crop growth

The present crop model is based on the potato model described by Karvonen and Kleemola (1995) and the barley model described by Kl- eemolaetal. (1995). The crop developmentstage (D_vs⁾is driven by the average dailytemperature, the basetemperature,and by thetemperature sum required to complete each phase (Kleemola 1991).D_vsis0.0 atemergence, 0.5 atanthesis, and 1.0at maturity. The model calculates crop production based on latitude, Julian day, daily globalradiation,precipitation, andmeanairtem- perature. The original crop modelwas slightly modified: the method presented by Teittinenet al. (1994) was used _to determine the partition- ing of drymatterbetween shoot organs. At ^first, their model calculates the increase in shoot dry weight. Then, using the _new shoot dry weight and the relative ^amount of each shoot organ, determinedas afunction of developmentstage, a new value for the dry weight of each plantor- gan is calculated. The partitioning of dry^matter betweenroots and shoots, however, is calculat- ed accordingtovanKeulen and Seligman (1987).

The computation of the maximumnetphotosyn- thetic capacity ofa leaf(P_m,kg C0

2 /ha leaf /h) wasalso^modified, P_mis computedas a function of[C0₂^] inside the stomatal cavity (C):

Pm ^- x,*ln(C)I ^' r -x,2 (1)

This relationship was fittedto data adapted from Kemppi (1992),and the following param- eter values were ^obtained;

x,=30.513

x₂=l 19.91. Cis determinedas afunction ofat-

mospheric [COJ ^{using a constant ratio of0.6} (C,/[CO2]).

formulated for each layer ^(Karvonen and Varis 1992).

Soil^water

Water movement in soil is modelled using a modification of the DRAINMOD -model (Sk-

äggs 1978, Skäggs^etal. 1991).The model cal- culates the depth of the ground^water table and water movement in soil using a method based on soil^waterbalance. The input variables of the system areprecipitation and the capillary rise of water in the soil profile, and the output varia- bles arepotential and actual evapotranspiration (ET _o| and ETac|), deep seepage and _water flow- ing via drainage pipes. The water submodelre- quires_a soilwaterretentioncurveand thesatu- rated hydraulic conductivity of the soilas an in- put, and calculateswater movementbetween soil layers, the depth of the groundwaterlevel,drain- age flow,and soil moisture_contentin each layer as output variables. The thickness of the layer used was 10cm in all the soil models. The esti- mates for ET_otandETm|are used for computing the effect ofwater stress on photosynthesis.

Soil nitrogen

Mineralization and the application of fertilizers increase theamount of mineral^Nin soil and the uptake by plants, leaching, and denitrification decrease it in the^present model. Soil processes involved in the Nbalance, i.e., mineralization, dissolution offertilizers, nitrification and deni- trification, are modelled using first orderreac- tion kinetics, i.e., the reactions are linearly re- latedtothe amountof substrate. This approach is commonly used in modelling soil nitrogen dynamics(deWilligen 1991).Themovementof water-soluble N through soil occurs both by molecular diffusion and bymass transportin the soil-water phase. In thecurrentmodel,diffusion processes are neglected and only convective transport is considered. Convective transportis a function of the soil-water flux betweentwo layers, calculated by the soil water submodel, and the mineral nitrogen concentration of these layers. An ordinary differential equation _was

Soil temperature

Soil temperature is calculated using the model described by Karvonen(1988).Thepresent mod- el, however, unlike the approach used by Kar- vonen(1988), calculates heat transfer separate- ly from mass(water) transfer in soil. The soil temperature model determines the heat transfer in soilonthe basis of thermal conductivity and the heat capacity of each soil layer. Moreover, a soil-specific relationship between unfrozenwa- ter contentand negative soiltemperature is need- ed _to take into _account the influence of latent heat during freezing/melting periods. The mod- eloutputs aresoil temperatureand the distribu- tion oftotalwater contentinto unfrozen and fro- zen fractions in each layer. Frost depth is de- rived from soiltemperature,i.e. the depth where the soiltemperature equals O.O°C.

Snow dynamics

The snow model _was detailed by Karvonen (1988). He combined the models presented by Kuusisto (1984), and by Jansson and Halldin (1980). The model includes submodels for de- termining the form of precipitation (snow or water), the melting of snow driven by air tem- perature, depth and density ofsnow cover,and the^amountof free waterand ice insnow.

Calculation

of

The sowing day was given _{as an} input under present conditions, while under future warmer conditions,itcanbe expected that sowing would be earlier. Using data from Jokioinen (see be- low), the dependence of the sowing day on weatherwas analysed. It was observed that the sum of precipitation between the date when the five-day moving average of airtemperatureris- es above 5°C (D

b^, Julian day) and the sowing date explained 90% of the variation in sowing dates duringasix-year period. Basedon this in- formation, wedeveloped a simple modeltode-

Kleemola, J.^&Karvonen, T: Modelling growth

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termine the sowing day under future conditions.

The model calculates an index, initialized_at 0 when the moving average ofair temperatureris- esabove5°C,and reaching 1atsowing. The in- dex is increased by a parameter related to D_b (0.000523*D_b^),and decreased byaprecipitation parameter (P, mm /d), in case it is raining (0.1517*P).

Calibration and validation of ^{the model}

Experimental data

Two sets of datawere employed in the calibra- tion and validation of the model. The firstsetof data, comprising measurementsof crop growth response tonitrogen fertilization, wascollected

at Viikki Experimental Farm, the University of Helsinki (60°10'N, ^25°00'E) during the period

1986-87. These experiments were detailed by Kiltilä(1988),andareonly briefly outlined here.

The meteorological data needed for running the crop model(daily globalradiation, precipitation, and mean air temperature) wererecorded 10 km from the farm at Kaisaniemi, a meteorological station of the Finnish Meteorological Institute (FMI).The soiltypein the experimentwassandy and muddy clay in 1986, and sandy and silty muddy clay in 1987. Both soil types were rich in organicmatter (6-12%by weight). The spring barley cultivar, Agneta, was supplied with 10, 50, 90 or 120 kg N,40 kg P and 62 kg K /ha at sowing. Above ground crop dry weight (kg/ha) wasrecordedatthe yellow ripeness stage(mois- ture content of grains about 35%). For model- ling purposes, the saturated soil conductivity valueswereassumedtobe the_{same as}those used for data from Jokioinen (60°49'N, 23°30'E), adapted from Aura(1990). The waterretention curve wasadapted from Andersson and Wiklert (1972), according tothe soil classification giv- en by Kiltilä(1988).

The secondsetof data was used to analyse

the performance of the model in simulating year toyear variationsin crop growth,snowdynam- ics and soiltemperature. Furthermore, these data were also used as abaseline when conducting a sensitivity analysis for the model. The datawere collectedatthe Agricultural Research Centre in Jokioinen, as a part of a joint Nordic project during the period 1982-1987^(Ilolaetal. 1988).

The meteorologicaldata, as wellassoiltemper- ature and snowdepth, wererecorded atJokioi- nen, aFMI site close tothe experimental field.

Soil temperature was measured once a week at the depths of 20, 50 and 100cm. Snow depth was recorded daily, but five-day intervals ^were used in this study. The soil type in the experi- mental fieldwas classified asheavy clay, with 63% of the topsoil particles ^<0.002 mm. ^In the model, the soil was treated_as twolayers: 1) 0- 30cm asthe_topsoil and 2) below 30cmdepth as the bottom soil. A spring barley cultivar.

Porno, was grown throughout the experiment.

The crop was fertilized with80-100 kg ^N,35- 40 kg P, and40-65 kg K /ha each year. Above- ground crop dry matter was monitored weekly, and thesemeasurementswereused in validating the crop model. The waterretentioncurve was adapted from Andersson and Wiklert (1972), according tothe physical characteristics of the

soil reported by Ilolaetal. (1988).

Model simulationswerecarriedouton a ^year- ly basis for the data of^Viikki,asthe experiments wereconducted in different fields. For Jokioin- en,the modelwas runcontinuously from 1 Jan- uary 1982 until 31 December 1987, and the ini- tial values for the soil statevariablesweregiven only once, _at the beginning of the simulation period. The crop variables were initialized at sowing each year.

Crop response to nitrogen

fertilization

The data collectedatViikki Experimental Farm in 1987 were used for calibrating the response of the crop^tonitrogen fertilization, and the data from 1986wereused for validating the nitrogen response. The base temperatures used in deter- mining ^the development ^rate of the crops were adapted from Saarikko et al. (1993). The tern-

perature sum requirements of the crops for the periods between emergence and heading, and between heading and yellow ripeness were ad- justed using the data from the year 1987. The parameter determining the lower limit of the range in which the leaf Ncontent(g N/ leaf m 2) does not limit the photosynthesiswas also cali- brated using 1987 data. The values for the other parameters of the model were taken from Kl- eemolaetal.(1995),and Kleemola^etal.(1996), who also gavea description for those parame- ters. Figure la indicates that the calibrationwas successful,despiteasmall overestimation of the crop dry weight atthe lowest N ^treatment.The weather conditions in the year 1986werequite different from those of the year 1987: the^aver- agetemperature was 14.8°C in May-July^(12.5°C in 1987)and the totalprecipitation was 147 mm (170 mm in 1987). However, the model per- formed satisfactorily in 1986,^too (Fig. lb),

though in contrast to 1987, the crop dry weight wasslightly underestimatedatthe lowest nitro- gen level.Figure 1 also indicates that both the observed and simulated optimal nitrogen fertili- zationlevel, i.e. the nitrogen fertilization level at which additional nitrogen does not increase growth, was lower in 1986 than in 1987, pre- sumably because ofwaterdeficiency.

Crop growth

The _same setofparameters as in the nitrogen data above were used when running the model for the second_setof data collectedatJokioinen, 1982-87.However, as the cultivar _was differ- ent, theparametersdetermining thetemperature sumrequirements of the cropwerechanged. The values were taken from Saarikko ^etal. (1993).

The model performed well compared toobser- vations in simulating the shoot dry weight(DW) at Jokioinen. The coefficient of determination (r²)for all the samples taken during the growing periods in 1982-87was0.90. The coefficient of variationwas8.5 and 8.6% for the measured and the simulated shoot DW atmaturity, respective- ly. As anexample. Fig. 2a shows the time-course of the measured and the simulated shoot dry weight for theyear 1983, when the weathercon-

ditions were close to the optimum for crop growth. Figure 2bpresents data for 1984, when the soil moisture was inexcess and was report- ed asrestricting crop growth (Ilola^etal. 1988).

However, the simulated response of crop growth tothisexcesssoil moisture was greaterthan the one observed. Figure 2b shows that the simula- tion was erroneous during _a two-week period after the day number 175; during the^restof the growing period the simulated growth_{rate was}

close to that observed.

Soil temperature

We compared the simulation results of the soil

temperature model with the data of the years 1982-84, collectedatJokioinen. As thetemper- aturewas measured weekly the data comprised

156 observations ateach depth. The modelac- Fig. 1.The response of simulated and measured cropgrowth toNfertilizationin^(a) 1987and (b) 1986.The model^was calibratedusingdata from 1987.

Kleemola^, J. ^&Karvonen, T: Modelling growth

of

counted for 95, 96 and 97% of the variation be-

tweenthe measured and the simulated soil_tem- peratures,pooled for all three years,_atthe depths of20, 50 and 100cm,respectively. At each depth, the variation in the simulated valueswassmall- erthan in the measured ones. The time-course of the soiltemperature atthe depth of 20cmis shown in Fig. 3 for the years 1982(a) and 1983 (b).The model performed satisfactorily through- outeach year,exceptin the spring, when the sim- ulated soiltemperature rose more rapidly than the measuredone in both years. Moreover, the model overestimated the soiltemperaturein win- ter1983. This may have been caused by the fact that the soil water model tendsto overestimate the soil moisture content of the_top soil layers.

The simulated soil probably had more water to freeze than the actualsoil,and for the_sameavail- able energy proportionally less^waterfroze than actually happenedsothat the simulated soiltem-

peratureremained higher than the measuredone.

Anotherreason for the overestimation may have been that the depth of thesnow cover wassmall in 1983(see later) and the model may have _ex- aggerated the heat flux through the thin snow coverinto the soil.

Snow depth

The appearance and disappearance ofsnow cover was modelled satisfactorily. The simulation of snowdepth _wasnotas good (Fig.4). The model was able to explain 81% of the variation in the measured snow depth during the winters 1982- 84 (pooled for all three years). The simulated valueswere generally slightly higher than those measured. An accurate estimation of the depth (and density) of_snowis essential for simulating the soil temperature successfully in the winter and the spring. There exists aclear relation be- tween the snow depth and the soiltemperature during the winter (Figs 3,4): the thicker the_snow cover the higher the soil temperature.

Results

Sensitivity analysis

The sensitivity of the model_outputstochanges in variables suggestedtobe affected by climate change, were analysed. The sensitivity analysis wasconducted in ordertoaid in making conclu- sions about the results given by the model for the weather conditions in 2050. The baseline weather usedwas the 1982-87 data from Jokio- inen, and the nitrogen fertilizationrate was as- sumed_tobe 200 kg/ha. Model runs were con- ducted for thelow,central and high scenarios of SILMU. One variable(airtemperature,precipi- tation and[C0₂])atatimewasadjusted accord- ing toeach scenario. The results of the sensitiv- ity analysis arepresented in Table 1. Table 1 shows that the effect of C0₂on cropgrowthwas bigger than that of the other variables according

to the model.^The year to year variation was slightly decreased when compared to ambient Fig. 2.The time-course of simulated and measured shoot

dry weight atJokioinenin^(a) 1983and (b) 1984.

Fig. 3. The time-course ofsimulated and measured soil temperature at the depth of20cm in^(a) 1982and (b) 1983.

Kleemola, J.^&Karvonen, T:Modelling growth

of

conditions. The increase in precipitation had lit- tle affecton cropgrowth. Neitherwasthe varia- tion between years affected. However, the in- crease in precipitation clearly increased the amount of drainagewater in theautumnand the spring (resultsnotshown). Higher air tempera- ture decreased shoot dry weight and increased the variation between years. The decrease in

shootdry weightresulted, inpart,from acceler-

Table I.Sensitivity analysisof the model:the response ^of simulated shoot dry weight (relative to the present) of present-day barley cultivar to thechanges inair tempera- ture,precipitationand [C0₂^]. Oneweather variable was increasedintimeaccordingtoSILMUlow,central andhigh scenario. Weather data collected at Jokioinenduring the period 1982-87^wasused^abaseline. Coefficient of varia- tion (CV,^%)between years showninparenthes; CVwas 9.20%for the baseline period.

Scenario

Weather variable Low Central High Precipitation ^{100(9.17) 101(9.04)} 101(9.11) Temperature 98(9.90) 92.0(12.6) 87.5(14.1)

(COJ ^{120(7.93) 129(7.36) 133(7.16)}

ated development under highertemperatures and a consequent shortening in the length of the growing period. Higher temperatures also in- creased the potential evapotranspiration, lead- ingtoadecrease in shoot dry weight in dry years.

Crop growth responses under scenarios

of

matechange

Afewtestruns were madetodetermine the ef- fect of the suggested changes in [COJ, airtem- perature and precipitation on cropgrowth. The baseline weather usedwasthe 1982-87 data from Jokioinen. Under the central scenario of SILMU for 2050, the simulationruns suggested that the average shootDW of barley would increase by 23% ifa present-day barley cultivar, such as Pornowasused and the N fertilization level was 100kg /ha^{(Table 2).}The interannual variability of the shoot DW increased slightly, in accord- ance with_an increase in the variability of the length of the growing period. However, if the cultivarwas changed toonerequiring a higher temperature sum for maturing, the increase in shoot DW was 35 ^%and the coefficient of vari- ation decreased.

Fig.4,The time-course of simulated and measuredsnowdepth duringthe winters of1982and 1982-83.

The modelwas^{also used}toestimate the crop response under the low andhigh climate change scenarios of SILMU (Table 2).The “new” crop cultivar was assumed to be adapted to the changedconditions, so that the sowing daywas assumedtochange accordingtotheclimate,and the development rate was adjusted so that the

harvest dateswere closeto those observed un- der ambient conditions. Again, the model sug- gested clear increases in crop growth: by 23%

under the low scenario and by 56% under the high scenario of SILMU assumingahigh N fer- tilization^rate, 200 kg /ha (Table 1).

Some simulation runs were also conducted Fig. 5.The simulated response of cropgrowth to Nfertilization under observed conditions,and under conditions adjustedaccordingtothe central scenario of SILMU with increased CO, -concentration and air temperature by 2050, for (a)afavourable year (1983) and (b) adryyear (1986). Arrows indicate the N

fertilization levelrequired for^amaximum yield.

Table2,Average simulated increase^(%)inshootdry weight ofapresent-day anda newbarleycultivar when shootdry weightobtained under conditionsin2050was^comparedto

oneobtained under present conditions. Weather data col- lected at Jokioinenduringtheperiod 1982-87were used asthe baseline.

central low high

scenario scenario scenario Nfertilization presentcv. new cv. new cv. new cv.

100kgN/ha 23 35

200kgN/ha 25 43 23 56

in orderto analyse the effect of climate change on the optimal rate of N fertilization. Figure 5 shows the simulated crop response when weath- er data from two different years were used as baseline conditions. The growing conditions were very favourable in 1983, whereas in 1986 they weremuch drier. According to the simula- tions,enhanced crop growth requires additional nitrogen. Under present-day conditions,when the growing conditions _aregood shoot DW contin- ues toincrease with increasing nitrogen fertili- zation up toa level of 125 kg N/ ha (Fig. sa).

However, if soil moisture deficiency restricts growth, the optimum N fertilizationrateis found atmuch lower levels (Fig. ^sb).The effect of the scenario changes in climate is to increase the level atwhich this “saturation effect” of nitro- gen occurs, under both favourable and drought conditions. The effect is reinforced in simula- tions withanadapted cultivar (Figure 5).

Discussion

The model performed well at simulating vari- ous components of the soil-plant atmosphere systemfor which measurementswere available for comparison. This indicates that the simula- tion results given in the^present paper^arecredi- ble for the kind of weather and soil types used in this research. However, morevalidation stud-

ies arerequired since this is the first time the model has been applied in itspresent configura- tion. For example, experimentson onlytwosoil types were considered, and measurements of crop responses under enriched [C0₂^] were not used.Moreover, dataon the soil N content and soil moisture were ^not available.

According ^to the simulation results climate change will clearly enhance crop growth under northern conditions. The increase in the dry matterproduction, as aresult ofa longer grow- ing period and higher [C0₂^], is not likelyto be counteracted either by the increased develop- ment rate of crops, and the shortened grain fill- ing period, _orby the increased potential eva- potranspiration inducing water deficiency _con- ditions for crops. It was observed that the in- crease in yields is also dependent on the crop- ping methods employed. As shown in Table 1, the increase in temperaturedecreases shoot dry weight by decreasing the length of the growing period. This effect ismorethan^counterbalanced by the positive effect of the increase in [C0

2^]

(Table 2). A further increase in yields will be obtained, for example, ifnew cultivars, witha longer growing period _are used. Moreover, the nutrient requirements of crops will also increase if the growth is enhanced.

The results of this study refertospring-sown crops. Some of theaspects and trends may hold for winter crops, ^too.The higher^[C0₂^] will in- creasethe photosynthesis of winter crops in Fin- land.However, the cropsystemforautumn-sown crops is morecomplex than for the spring-sown crops. ^It is likely that the frequency of warm periods in the wintertime,during which the_snow disappears, will increase under a changed cli-

mate, as indicated by our model (results not shown). This, in ^turn, may affect the suscepti- bility of cropstowinter damage. Inaddition,the refreezing of the melted water can also _cause damage. On the otherhand,the total duration of snow coverwill probably decrease, which will be beneficial for overwintering crops. The short- er the winter period, the smaller the storage of assimilates crops havetoaccumulate in theau- tumn to survive. Biochemical reactions require Kleemola, J. ^&Karvonen, T: Modelling growth

of

some energy during the winter period too, and asassimilation is^notpossible in the winter due to low temperatures and probable snow cover, the plants have toaccumulate some assimilates prior^to overwintering. It is difficultto design field experiments for studying these problems, asthe heating of field plots would be very diffi- cult in the winter without disturbing other

prevailing conditions. A partial solution would be to analyse the exisiting dataonoverwinter- ing during warm winters under ambient condi- tions.

Acknowledgements.This studywasfinancedbythe Acad- emy ofFinlandas apart of the Finnish ResearchProgramme onClimaticChange(SILMU).

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SELOSTUS

Ohran kasvun ja typpidynamiikan mallintaminen nykyisissä ja tulevaisuuden olosuhteissa

JoukoKleemola jaTuomo Karvonen HelsinginyliopistojaTeknillinen korkeakoulu

Tutkimuksessaanalysoitiinohran kasvuaja typpilan- noituksen vaikutusta siihen kokeellisten aineistojen jamatemaattisen mallin avulla. Mallin toimivuutta testattiin nykyisissäoloissakerätyillä aineistoilla, ja malliakäytettiin ennustamaan ilmastonmuutoksen vaikutusta ohran kasvuun. Samalla analysoitiinmal- linkykyä simuloidamaanlämpötilaa sekä lumen ker- tymistä jasulamista. Kalibrointi- jatestaustulokset osoittivat, että käytetty malli simuloi hyvin ohran kasvua ja typpilannoituksen vaikutusta siihen sekä maanlämpötilaa jalumenkertymistä jasulamista ny- kyisissä oloissa. Ohran fytomassa nykytasoonverrat- tunaoli hitaan ilmastonmuutoksen oloissa23^%suu-

rempi janopean ilmastonmuutoksen oloissa 56 ^% suurempi, jos viljelijän oletettiin vaihtavan lajiketta kasvukauden pituuden mukaanja käyttävänkorkeaa typpilannoitustasoa. Keskinopean muutosennusteen mukaan ohranfytomassa lisääntyi korkeaa typpilan- noitustasoa(200 kg N /ha) käytettäessä suhteellises- tienemmänkuin alhaistatyppilannoitustasoa⁽¹⁰⁰kg N/ha) käytettäessä. Mallin antamien tulosten perus- teella ohran kasvun lisääntymiseen vaikuttaa eniten kohoavahiilidioksidipitoisuus. Lämpötilankohoami- nen sen sijaanalentaajonkin verrantuotantopotenti- aalia,jos viljelyyn ei oteta uusialajikkeita, jotkavaa- tivatsuuremman lämpösummantuleentumiseensa.

Kleemola, J.^&Karvonen, T: Modelling growth

of