The method involves measuring the shoot height distribution of the Phragmites australis population. Shoot height is transformed to shoot dryweight by means of an empirical model. Summing the converted dry weight of all the shoots gives an approximation of the yield

Kauppi, P.E.

Puttonen, P.

Selkäinaho, J.

Helsingin yliopiston digitaalinen arkisto

Ann. Bot. Fennici 20: 5l-55, 1983A method for estimating above-ground biomassin Phragmites standsPEKKA KAUPPI, JORMA SELKAINAHO ANd PASI PUTTONENINTRODUCTIONEstimates of biomass made by the harvestingmethod are affected by spatial variation in twophases of the work. Firstly, the plots seldomcover the whole study area and a risk is involved'' in generalizing from the plots to the whole area.\'If the ptots have been properly sited, however,the variation within the area can be quantified bystudying the variation of the yietd estimatesbetween the plots.Secondly, variation can occur within a plotand this affects the estimate when the dry-matterbiomass is not measured directly but approxi-mated from a regression. Regression models arenot only species-specific, but also specific foreach stand. In addition. alternative regressionscan be used within a stand, which all have theirown special advantages and drawbacks.In studies on the common reed (Phragmitesaustalis (Cav.)'kin. ex Steudel), the parametergenerally estimated is the dry weight of theKauppi ,  P. ,  Selkeinaho, J. ,  & Puttonen, P.  1983: A method for  est imat ing above-groundbiomass in Phragmires tands.  -  Ann. Bot .  Fennic i  20:51-55.  Hels inki .  ISSN 0003-1847A stratified sampling method is presented for €stimating the above-Sround biomassof reedbeds- The m€thod involves measuring the shoot height distribution of thepopulation. Shoot height is transformed to shoot dryweight by m€ans of an empiricalmodel. Summing the converted dry weight of all the shoots gives an approximation ofthe y ie ld.The meihod appeared to give mor€ accurate results than did an earlier method inwhich the average shoot dry weight given by a random sample is multiplied by standdensity. The greater accuracy of the pres€nt method was particu larly evident when smallsamples were used, consisting of 3-20 shools.Key words: biomass, sampling method. PrrdglrirerP. Kauppi. Inrcmational Institute for Ap?lied Sfstems Anal)sit. A- 2361 Loxenburg,Austria: J. Selkdinaho, Lab- Contrcl and SFtems Enginearing, Dept. Proftss Engineerin{,Universitl of Oulu, SF-90570 Oulu 57, l'inland; P. Puttonen, Dett. Farm Forestt.Universitv of Helsitlki. SF- 00710 Helsinki 71, Fintandstanding crop, This has sometimes beencalculated directly by determining the dry weightof all the shoots on the plot (Bjitrk 1967,K6rp'ti& K6rp6ti 1971, Dykyjova et al. 1973, Ho 1979).Unlike methods using sampling within the plot,this approach excludes errors due to within-plotvariation. Some authors, however, have used asample to calculate the average shoot dry weightand multiplied this value by the reedbed density(Mochnacka-Lawacz 1974, Mason & Bryant1975, Toivonen & Lappalainen 1980). Theresulting estimate may be impaired by sample-dependent vadation, and this is also the casewhen "wet weight" is measured in situ and asample is taken to determine the dry mattercontent.Here we present a method which also includessampling within the plot, but is intended todiminish the effect of sample-dependent variationby using a technique which is not sensitive loanomalies in the shoot size distribution of thesamole.52 Pekka Kauppi et al.MATERIAL, METHODS AND RESULTSThe method was applied to a pure stand ofPhragmites australis growing in southern Finland(61"23', 24"24'). Four permanent 2 x 2 m sampleplots were set out at random in the stand on 24April 1978, when ice still covered the lake. Thestand was situated in the central part of a largereedbed. The remnants of the previous year'sshoots were removed from the sample plots at thesame time.The annual yield of above-ground biomasswas measured on 2 and 3 August 1978. Shootsgrowing in the plots were cut off individually atthe point where they protruded from the lakebottom, which at that time was lying above thewater level. The height of each shoot wasmeasured with an accuracy of five centimettes.The total number of shoots was I 066, and theiraverage density 66 shoots . m-' . The distributionofthe shoots in height classes is shown in Fig. la.In the prescnt method the weight determinationsare facilitated by converting shoot height toshoot dry weight. Shoot height can be measuredir Jittt, but determination ofthe shoot dry matterrequires additional laboratory work.The relationship between shoot dry weight, w,and shoot height, h, was formulated as follows:w : a ' h '  ( l )where a and b are empirical parametem.The model (l)enables the height ofevery shootin the sample (shown in Fig. la) to betransformed into shoot dry weight. The final goal- a value for the standing crop in agiven area -is achieved by summing the dry weights ofall theshoots.A subsample of 49 shoots (Fig. lb) was takenin order to estimate param€ters aand tr ofEq. (l).Th€ shoots were dried to constant weight at105'C. When height was €xpressed in metres anddry w€ight in grams, the parameters wereestimated to be: a = 0.949 and b = 3.27 (Fig.2).These values were obtained by computeriteration without linearizing the height to weightrelationship, which would lead to biased values(Baskerville 1972, Wiant & Harner 1979).Approximation of the biomass. T (g . mr).over the four sample plots was performed asfollows:ANN. BOT. FENNICI 20 (1983)1.50Shoot2.OO 2.50height (m)Shoot height (m)Fig../- Shoot height distribution of sample (a) and subsample(b).where A is the area in square metres, i.e., 16 m'.fte ave rage yield appeared Io be | 170 g . m-?.the figures for the individual sample plots being1030,  I  l l 0 ,  1290 and 1250 g  .  mr .AN EVALUATION OF THE METHODEquation (2) was considered to be a suitablemethod forestimating the standing cropfrom thepresent data. The value yielded by the equationwas used as a cliterion in comparisons with somealternative methods.Since measuring the dry weight of reed shoots90809 7 0o.e 60€ u ob 4 0ll8 3 0az 2 0ltoo.cat,o 4o ^.Ct .)= 2z1103.OOI 1066T :  _ :A i rThe subsample49 shoots0.949 . hi327 (2)ANN. BOT. FENNTCT 20 0983)Shoot height (m)F,,9. .'' R€lationship t'etween shoot height and shoot dryweight in the subsample.is laborious, we examined whether a subsampleofonly l0 shoots was large enough for estimationof the parameters in Eq. (l). A random sample ofl0 shoots was taken for this purpose from theoriginal subsample of 49 shoots. Parameters aand b of Eq. (1) were estimated and then insertedin Eq. (2) to approximate the biomass, T,n. Thenew estimate was then compared with thecriterion (Trn) in order to determine the errorpercentage, ero:Estimating abole-grcund biomass 53tested in a similar way. A random sample of l0shoots was taken from the original subsample of49 shoots. The mean weight of these shoots wascalculated and then multiplied by the reedbeddensity, 66 shoots . m-2. The biomass estimate,r,n, was again compared with To, in order toobtain a value for the error percentage, ero:(4)30CDs.99 z ooogo2520s 1 5ooq l o(D(Eo5(3), - -  :  l l l { l  .I 4,1The biomass approximation, T,o, and conse-quently the error percentage, e,o, vary with thesample. Therefore the procedure of Eq. (3) wasrepeated four times with independent randomsamples. The average figure for these fourcomputations, Ero, was obtained to estimate themean deviation of the yield approximation whenl0 sample shoots are used instead of 49. Thevalue of 6ro in our material was 4 Vo.The average-weight-xdensity method wasThe mean deviation ?,0, of the value r,o whencompared with Tae was calculated from thevalues obtained with four independent samples.iro was 12 Vo.The effect ofsubsample size on the accuracy ofthe yield estimate was studied in more detail forboth of the methods. In addition to the abovecalculation with samples of l0 shoots, theestimates for the error percentages 6 and € werecomputed using random samples of 3, 5, 15, 20,25. 30 and 35 shoots. The values for € and E werecalculated using identical sets ofrandom samples.The results are shown in Fis. 3.t..-e- {obLNumber of shoots in the subsampleFig. 3. Error percentages when two different methods areused to estimate biomass, shown as a function of the size ofthe sampl€. Th€ percentages for the new method are shownby the solid line (e) and those for the average-weilht-x-density method by the broken line (;).10T,o - To,e r o :  I U U  'Tc,)504030201054 Pekka Karypi et al.Multipllng the average dry weight of rhewhole subsample shown in Fig. lb (17.05 g) bythe reedbed density (66.05 shoots . m-2) gave a 370 lower €stimate ofthe biomass than did the newmethod with the same subsample (Fig.3). Thedifference was chiefly due to the difference inshoot size distribution between the sample andthe subsample.DISCUSSIONThe present method is based on stratifiedsampling. It involves description of the shootheight distribution of the population. Themeasurement work is not too time-consuming.since two persons can easily measure 100-200shoots an hour,The description of the shoot height distributionis useful not only for approximation ofthe yieldbut also as a basis for more detailed ecologicalcomparisons. Besides varying in density, standsdiffer in shoot length and in shoot sizedistribution. The present method makes itpossible to quantify these differences.The problem ofsample-dependent vadation inthe biomass estimate for a plot is, of course,compl€tely avoided by determining the dryweight directly. When this method is used,however, the size ofthe sample may be restrictedby limited space in drying ovens, and relatedconstraints. The idea of using stratified samplingin studies of plant biomass production is notnew. It has been applied in forest inventories fordecades (cf. Miilter 1902), and a method whichcorresponds to ours has been used by Ross andUlasova (1966) in studies on maize (quoted inOndok l97l).Our results show that the average enor wassmaller with the present method than with theaverage-weight-x-density method (Fig. 3). Thegreater reliability ofthe new method was evidentthroughout the range ofsample sizes studied, butparticularly with small samples of 3-20 shoots.The results shown in Fig. 3 are sensitive to thedata sets. In our material the sample (1066) andsubsample (49) differ in their distributions byshoot height (Fig. l), the curve for the subsamplebeing platykurtic. Such a subsample is moresuitable for fitting the regression of Eq. (l) but isunfavourable for the dry-weight-x-densitymethod in the comparison shown in Fig. 3.However, another factor acts in the oppositeANN, BOT, FENNICI 20 (1983)way; i.e., it favours the dry-weight-x-densitymethod in the comparison. When the presentmethod is applied, the subsample shoots arenever chosen at random. The shoots in a randomsubsample may be very similar in size, which isunsuitable for fitting the regression curve of Eq.(l). Hence, the estimated mean deviations forthebiomass estimates (Fig.3) depend on the datasets in different ways, but the difference inaccuracy between the two methods is most likelyto be a general one.The shape chosen for Eq. (l) appears to beuseful in studies of the relationships betweenshoot height, shoot weight and stand density(Yoda et al. 1963, see also Gorham 19?9). Theweight of a plant is generally proportional to thecube of a linear dimension of the plant (in ourcase the height). The exponent obtained (3.27) is ..--lsomewhat higher than the expected one (3.0),which may indicate light competition. However,the difference is apparently mainly due to thesimultaneous estimation of parameters a and b.If the 6 value was fixed at 3.0 and the a value wasallowed to adjust, the fit of the curve would bealmost as good as the one in Fig. 2.In practical applications of this method theselection ofthe subsample would deserve specialattention. A random subsample would makecalculation easy, but might not give the optimalcompromise between accuracy on the one handand labour consumption on the other. Instead oflooking for a generally valid sampling procedure,selection should be tailored to the studyobjectives. Ifthe shape ofthe height-weight curveis of interest, then it would be worthwhile toincrease the selection probability of rare sizeclasses, If, in turn, biomass approximation is theonly goal, then the largest shoots are the mostimportant and one should increase the probability -oftheir being selected. This could be done with aprocedure where selection probability isproportional to, e.g., the cube of the shootheight.As computed above, the error percentages eand E do not take into account all sources oferrorin the course of the sampling procedure. Forexample, the estimate given by the wholesubsample, Tae, is not a real measurement ofthebiomass on the plots. However, the fit of thecurve in Fig. 2 seems fair and the slope of thefunction € in Fig. 3 suggests that increasing thenumber of shoots in the subsample would notincrease the accuracy by morc than l-2 Vo.ANN. BOT. FENNTCI 20 (1983)The sample plots were not sited in the stand soas to study the standing crop outside the plots.To obtain a generalization for the whole reedbed,the location of the plots should follow standardstatistical methods. The reedbed border limitsshould first be defined, and a sufficient numberof plots placed according to a predeterminedschedule (systematically or at random). This isnot too laboriouswhen small plots are used (-lm' ).Estimati g abow-ground biomass 55With such material the confidence limits for thebiomass approximation are easy to determine.ACKNOWLEDGEMENTSWe thank Dr. Pekka Kilkki, Mr. Juha Lappi, Dr. Juhan Rossand Dr- Heikki Toivonen for criticism of the manuscript. Thestudy was supported by the Energy Department of theMinistry of Trade and Industry.REFERENCESBaskerville, G. L. 1972: Use of logarithmic regrcssion in theest imat ion ofplant  b iomass.  -  Can. J.  For.  Res.2:49-53Biitrk, S. 1967: Ecological investigations of Phragmites. communis. - Folia Limnol. Scand. 14: 1-248.- Dykyjova, D., Hejni, S. & Kvet, J. 1973r Proposal forinternational comparative investigations of productionby stands of reed (Phragmites communis) - Foliaceobot. Phytotax. 8: 435-,92.Gorham, E. 1979: Shoot height, weight and standing croP inrelation to density of monospecific plant stands. -Nature 279:  148-150.Ho, Y. B. 1979: Shoot development and production studies ofPhragmites austialis (Cav.) Trin. ex Steudel in Scoltishlochs. - Hydrobiologia 64t 215-222.K6rpdti, I. & K:irpeti, v. 1971: Methodological problems ofthe research on the production of the primaryphytobiomass of Lake Balaton. - Hidrobiologia 12:155-158.Mason, C. F. & Bryant, R. J. 1975: Production, nutrientcontent  and decomposr i t ion of  Phlagmi ler  communj.Tr in.  and Typha angust i fo l ia L.  -  J-  Ecol .63:  ? l  95.Mochnacka-Lawacz, H. 1974: S€asonal changes of Phmgmitescommunis Trin. Part L Growth, morphom€trics, densityand biomass.  -  Pol .  Arch.  Hydrobiol .  2 l :  355-368.Miiller, U. 1902: L€hrbuch det Holzmesskunde. - PaulParey, Berlin.Ondok, J. D. l97l: Indirect estimation of primary valuesused in growth analysis.  -  In:  Sest6k,2. ,  Catski ,  J .  &Jarvis, P. G. (eds.), Plant photosynthetic production, pP.392-411. Manual of methods. - Junk, The Hague.Toivonen, H. & Lappalainen, T. 1980: Ecology andproduction of aquatic macrophytes in the oligotrophic,mesohumjc lake Suomunjervi, eastern Finland. - Ann.Bot. Fennici l?: 69-85.wiant, H. V. & Harner, E. J. 19?9: Percent bias and standarderror  in logar i thmic regression.  -  Forest  Sci .25:167-168.Yoda, K., Kira, T., Ogawa, H. & Hozumi, H. 1963: Self-thinning in overcrowded pure stands under cultivated andnatural conditions. - J. Biol. Osaka Cy. Univ. 14:101-t29.Received 20.VI.1982

A method for estimating above-ground biomass in Phragmites stands

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