an inventory of guadua (guadua angustifolia) bamboo in the coffee region of colombia.pdf

8/18/2019 An inventory of Guadua (Guadua angustifolia) bamboo in the Coffee Region of Colombia.pdf

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O R I G I N A L P A P E R

Christoph Kleinn David Morales-Hidalgo

An inventory of Guadua (Guadua angustifolia ) bamboo in the Coffee

Region of Colombia

Received: 28 February 2005/ Accepted: 17 February 2006/ Published online: 20 April 2006 Springer-Verlag 2006

Abstract Management of renewable natural resourcesand the corresponding policy formulation should befounded on reliable data and information. This refersboth to information on the resource itself and to infor-

mation on the market situation. In this paper, we presentmethodology and major results of an inventory of theGuadua resources, in a study area of about 1 million hawithin the Coffee Region of Colombia. This inventoryproduced for the first time sample-based statistical esti-mations of the Guadua area and growing stock. In thestudy area, land cover of Guadua patches was estimatedto be 3.9% or about 40,000 ha (minimum patch area0.3 ha). This is higher than figures published earlier.Estimation for mean number of standing culms (includ-ing shoots and dry culms) per hectare was 6,940 with amean diameter at breast height of 10.8 cm, apparentcommercial volume of 654 m3/ha, commercial wood

volume of 304 m3

/ha, oven-dry biomass of 311 ton/ha,and total carbon stock of 156 ton/ha. While the low-intensity sampling approach worked well and may serveas an example for similar studies, we identified a numberof issues for further research, particularly in what refersto as the basic mensurational models for Guadua volumeand biomass estimation from inventories.

Keywords Sampling Æ Renewable natural resources ÆForest inventory

Introduction

The management of renewable natural resources and theformulation of the corresponding policies and conser-

vation strategies should be founded on reliable data andinformation. The information need refers to the resourceitself and to the market to which the resource eventuallygoes. Inventories provide an important part of the nat-

ural resource information.Guadua (Guadua angustifolia Kunth) is a bamboo

species native to the tropical regions in Central andSouth America. It grows in natural stands, predomi-nantly along rivers either as pure stands or as mixed withtrees. More and more, Guadua stands are also estab-lished artificially on lands that had been previously un-der other use like pasture or coffee. Typical for naturalGuadua stands in the Coffee Region of Colombia is thatthey are relatively small and irregular in shape, thusforming a highly fragmented pattern.

Guadua culms have been traditionally used for manypurposes, such as construction and handicraft. It is as-

sumed that the utilization of Guadua as a naturalrenewable raw material can be enhanced and eventuallyturned into an economic alternative for farmers, par-ticularly in the Coffee Region of Colombia. Much re-search has, therefore, been initiated in the past years onGuadua, focused particularly on utilization aspects.Now, more and more projects also deal with the natural‘‘production process’’, i.e. the identification of suitablesilvicultural practices, of suitable sites and with thedevelopment of management models (Camargo 2004,2006; Camargo et al. 2003; Garcı ´a 2004).

As baseline information, data on area and status of the Guadua stands are required for many of those pro-

jects. In this paper, we present methods and major re-sults of a Guadua inventory that had been carried out inthe year 2002 in the Coffee Region of Colombia with theobjective of producing statistical estimations and of developing an inventory protocol for further applica-tions. We adapted statistical sampling methods widelyused in forest inventory where much research has beendone on sampling and response design optimization(Schreuder et al. 1993). Among the assets of statisticalsampling for resources inventories is that point estima-tions can be accompanied by interval estimations, i.e.

Communicated by Hans Pretzsch

C. Kleinn (&) Æ D. Morales-HidalgoInstitute of Forest Management, Georg-August-Universita ¨ tGo ¨ ttingen, Bu ¨ sgenweg 5, 37077 Gottingen, GermanyE-mail: [email protected].: +49-551-393472Fax: +49-551-399787Present address: E-mail: [email protected]

Eur J Forest Res (2006) 125: 361–368DOI 10.1007/s10342-006-0129-3


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the precision of the estimations can be quantified. This,together with the definition of a clear protocol, adds tothe general credibility of the results.

One of the major impediments for forest inventory isthe cost involved, and this was no different in the Gu-adua inventory project described, in which the inventorywas to provide input data for a research project underlimited resources. Some research, particularly for forestinventories of larger areas, is currently done on low-intensity sampling (e.g. Thuresson 2002; Kleinn et al.2005), an approach that has also been applied in thisstudy.

Study area

The study area is located in the central mountain rangeof the Andes, in the Coffee Region of Colombia, andextends over parts of the Departments of Valle delCauca, Quindio, Risaralda and Caldas (see also Fig. 2),the UTM grid coordinates being (zone 18) 1064421,922515 and 1195757, 1122579. The area was selected

such that it covered an altitudinal range between 900and 2,000 m, where there are favourable growing con-ditions for Guadua. The total area was 1,029,525 ha.

Coffee had been the major crop in that region; pas-tures and plantain being other agricultural land uses.Mean annual precipitation is 2,750 mm with two majorrainy seasons (April to June and August to November),and mean annual temperature is around 21C. Accord-ing to the life zoning proposed by Holdridge et al. (1971)the study area belongs to the following life zones:tropical humid forest, tropical very humid forest, trop-ical dry forest and premontane tropical humid forest.

For sampling studies, the sampling frame needs to be

defined from which sample selection takes place. Here,the sampling frame is defined by all Guadua patches inthe study region with a minimum patch area of 0.3 ha.This threshold value was defined in discussion withColombian experts, who stated that smaller patches areless attractive for commercial harvesting.

Methods

Commonly, two basic elements of information are re-quired in large area natural resources inventories: (1) theestimation of area and (2) the estimation of character-

istics of the resource per unit of area.Estimation of the total area of the very irregular and

fragmented patches of Guadua is a challenge. Because of the fragmentation, the small size of the patches and thetopography, medium resolution satellite imagery of about 15–30 m appeared to be problematic and was nottaken into consideration. For economic reasons, highresolution satellite imagery could not be used, so thatwe resorted to readily available aerial photographstaken between 1990 and 1995. While photographs of 7–12 years old are critical for many inventory studies,

here it appeared justified as experts confirm that con-siderable changes have not taken place during that timeperiod. To check this statement, verification observa-tions were taken and used for calibration of the aerialphoto-based area estimation.

From the interpretation of the aerial photographs,the projected area of Guadua culms was estimated. Thisarea, however, needed to be reduced to correct for theslop-over of culms at the Guadua stand boundary (seeFig. 1). The width of this strip along the stand bound-ary, which is under the vertical projection of the culmsbut where there are no culms growing was measuredduring the inventory at many points at the standboundaries. The corrected area is then what we call theeffective area.

Sampling was done by systematic sampling, wheresample size was determined by the available budget. Ona randomly located 10 km · 10 km grid in North–Southorientation (see Fig. 2), 103 sample points fell into thestudy area. For each point, the most recent aerial pho-tograph was searched in the Instituto Geogra ´ ficoAgustı ´n Codazzi (IGAC, Bogota ´ ), the central point of

which was closest to the sampling point. Eventually,suitable aerial photographs could be found for 89 sam-pling points. The remaining 14 sample points weretreated as non-response.

On each photograph a sample plot was installed suchthat the area in the field was 3 km · 3 km. This airphoto plot was located at the centre of the photographto reduce geometric distortions as much as possible. Forcost reasons and the lack of appropriate digital elevationmodels, distortion-free orthophotos could not be pro-duced. The prints were scanned in 600 dpi resolution sothat an interpretation on screen was possible.

Because of its peculiar texture in the aerial photo-

graphs and their typical fragmented shape, it was not amajor problem to distinguish and identify Guaduastands. Within the aerial photo plots, all Guadua pat-ches were delineated.

Field verification was done for 21 randomly selectedsample areas out of the total of 89; the corresponding 21aerial photo plots were geo-referenced for this exercise.Following this verification, some new patches needed tobe included and some eliminated from the maps gener-ated for the aerial photo sample plots. This field verifi-cation recorded both interpretation errors and realchanges that have occurred between taking the aerialphotographs and the inventory—where we assume that

interpretation errors were at a minimum because of thespecific and relatively easily identifiable texture of Gu-adua stands. A calibration factor was calculated fromthis verification exercise to calibrate the final area esti-mate.

For the estimation of Guadua stand characteristics, atwo-stage sampling design was used, using the base gridof 10 km · 10 km. From the 89 aerial photo plots—-which were considered a set of primary plots—a sub-sample of 13 was randomly selected for field sampling.Within each of these 13 selected primary plots, 10 sec-

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ondary plots of 10 m · 10 m were randomly chosen.For this second-stage sampling, the mapped Guaduastands were used as a sampling frame, i.e. all field plotswere located completely in Guadua stands as illustratedin Fig. 2b. Primary plots without Guadua (delineatedcover 0%) were not field sampled. For each primaryunit, more than ten secondary plot locations were pre-pared by random selection in the office. If, in the field, aplot did not fall into a Guadua stand (because of changes of land use since taking the aerial photographs),the field crews omitted that plot and searched the next

plot in the list, until a total of ten plots was completed.In each secondary sampling unit all Guadua culmswere diameter measured. Diameter was defined as thediameter at the middle of the internode located at abreast height of 1.3 m. This definition—and not anabsolute height value—was used to avoid having thediameter measurement at a node. Development stageand health status of each culm were also observed. Somebasic site attributes were recorded (such as elevation,aspect, slope, distance to water bodies) and variables onmanagement [such as origin of the stand (planted ornatural), silvicultural treatments and harvesting inten-sity]. To adjust the area estimated from aerial photo-

graphs to the effective area, for each secondary unit closeto a stand boundary, two distance measurements weretaken from border culms to the point where the crownprojection hits the ground. Details of the protocol andthe definitions used are in D. Morales and C. Kleinn(unpublished data).

Interest was also in variables that cannot directly beobserved, such as apparent volume (i.e. the total culmvolume including the hollow parts), wood volume (thevolume of the woody walls of the culms), oven-drybiomass, and carbon content. We distinguished here

commercial and total volume, and define the commercialvolume as the volume of the culm sections of matureGuadua that is typically extracted for utilization in theCoffee Region of Colombia. Total volume refers to thetotal culm volume from the ground to the top.

For these attributes, models needed to be applied thatpredict the attributes of interest from variables measuredin the inventory such as number of culms and diameterat breast height. However, for estimation of volume andbiomass of Guadua in Colombia, there is still a lack of suitable models. We used and compared two ap-

proaches:Approach 1: the official approach in Colombia,commonly applied in practice, assumes that the com-mercial parts of ten culms correspond to 1 m3 of apparent commercial volume (Ministerio del Ambiente2002). Obviously, this approach implies assumptionsabout the average length of the commercial culm andabout the average diameter. However, Garcı ´a (2004)finds for his data sets that ten culms yield 1.3 m3 of apparent volume, i.e. 30% more!

Approach 2: if we assume that the commercial part of the Guadua culms resembles a cylinder, then we maycalculate apparent commercial volume va (m

3) from

culm diameter d c (cm) and commercial culm length l c(m) by the basic geometric formula for the volume of acylinder

va ¼p

4

d c

100

2lc

Commercial culm length is not measured for eachculm, and needs to be defined or modelled. While thenorms which are applied in Colombia use a standardlength of 16 m (Ministerio del Ambiente 2002), we ap-

Fig. 1 Illustration of theconcept of effective area. Left: aGuadua stand boundary wherethe projection of ‘‘crowns’’extends into the adjacentagricultural field; the highlyirregular crown projectionrequires smoothing whendelineation is done in aerialphotographs. Right: illustrationof the difference between

crown-projected area andeffective area of a Guaduapatch; the outer bold line is thesmoothed delineation of crownprojection; the inner line is theestimated area where culmsactually grow. Here, threelarger tree crowns are visiblewithin the Guadua area

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plied here the model given in Arbela ´ ez (1996), whichgives the total culm length l c (m) as a function of culmperimeter pc at breast height by a simple conversionfactor of 0.56: lc ¼ 0:56 p c ¼ 0:56pd c This value fortotal length is then reduced to commercial length by a

factor of 0.7, which we derived from Garcia (2004).Inserting this length model in the above formula forcylinder volume and combining the constants yield asimple model for apparent commercial volume per culm:va ¼ 9:6722 10

5d 3c In all approaches for commercial volume we excluded

broken culms and shoots.Furthermore,for wood volume, oven-dry biomass,

and carbon content of Guadua culms, there is still aconsiderable lack of models and conversion factors.Therefore, we again used simple geometric approxima-

tions. For wood volume calculation we took the averagewall thickness of Guadua culms of 1.58 cm as reportedfrom measurements at three different culm heights byGarcia (2004) and applied the basic geometric model of a ‘‘tube’’ with outer diameter d c as an approximation.

For this calculation, we used total culm length from themodel given in Arbela ´ ez (1996) and applied eventually aform factor of 0.78 as reported by the same author toaccount for the conical shape of the total culm.

We calculated oven-dry biomass from wood volumewith the values for specific density from Garcia (2004)who reports an average value of 0.67 g/cm3 and a rangefrom 0.36 to 0.813 g/cm3. For conversion of dry biomassto carbon, we used the factor 0.5, an approximationwidely used in forestry when more specific information isnot available (Brown 1997).

Fig. 2 Study area and samplepoint locations. Five provincesin the western part of Colombiaof Caldas, Quindı´o, Risaralda,Tolima and Valle form theCoffee Region of Colombia; thestudy area is completelysituated within the CoffeeRegion (map A and enlargedmap). In sample points withaerial photographs, aerial

photo plots were establishedand all Guadua patchesmapped (map B); within thesepatches, ten secondary plotswere randomly selected peraerial photo plot

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The standard error was calculated for all estimationsfrom the estimators for two-stage sampling. We used theestimator for simple random sampling in both stagesalthough at the first stage we applied systematic sam-pling. As a consequence, our estimations of the standarderror must be seen as conservative estimations, i.e. thetrue standard error is likely to be lower.

Results

Area estimation

Total Guadua stand area, delineated as crown projectedarea and reduced by a calibration factor of 0.96 resultingfrom field verification, was estimated to be 3.9%(SE% = 10.7%), corresponding to an absolute area of about 40,000 ha. Mean patch size was estimated to be2.9 ha (SE% = 4.8%), ranging in the aerial photographsample plots from 0.3 to 43.7 ha. It is interesting to notethat the maximum Guadua patch perimeter observed inthe sample was about 15,000 m for a Guadua patch of

42.3 ha. A square with that perimeter would have anarea of about 1,400 ha! This calculation gives animpression of the high degree of irregularity and frag-mentation of Guadua patches. The patch size distribu-tion, produced from the mapped aerial photograph plots(Fig. 3), shows that this biggest patch of 43.7 ha has thecharacter of an outlier. The vast majority of patch sizesis 2 ha and less.

The effective area is calculated from the mappedprojected area by subtracting a strip at the outer edge of each Guadua patch, where there are no culms. The meanwidth of this strip was estimated 8.6 m from n = 230field measurements with a relative standard error of

SE% = 1.6; see Fig. 1 for illustration. Because of thefragmented and elongated shape of the Guadua patchesthis border strip covers a considerable area; it was esti-mated to be 31.1% of the total projected Guadua stand

area! Effective area is then 2.7%, or, in absolute terms,about 28,000 ha.

Stand characteristics estimated from sample plots

The mean number of culms per hectare was estimated tobe 6,940 (SE% = 6.8%), the breakdown to develop-ment classes is presented in Table 1. The major per-centage of the culms (69%) is mature (commercialculms). The regeneration, represented by the develop-ment classes shoots and young Guadua has a relativelylow share of 22.3%.

The diameter distribution was also estimated and isdepicted in Fig. 4 for each development class. Nearly88.7% of the culms had dbh values between8 and 16 cmand only 3% had larger diameters. This information isof high value to the market, because it is the biggerGuadua which is demanded and used for constructionpurposes (Morales and Kleinn 2004; Garcia and Cam-argo 2004). Mean culm diameter was estimated to be10.8 cm (SE% = 4.2%), the observations ranging from

4 to 20.5 cm, and the mean total culm length estimatedwith the model of Arbela ´ ez (1996) was 19.1 m.

Rian ˜ o et al. (2002) made the observation, that themean diameter is smaller in stands where the number of culms per hectare is higher (i.e. negative correlationbetween number of culms and mean diameter). For theGuadua stands inventoried in this study, however, wedid not observe that. Here, a correlation coefficient of r = 0.077 was estimated, which was not statisticallysignificantly different from zero (P = 0.3797).

Apparent commercial volume along approach 1 (tenmature culms yield 1 m3) was estimated to be 479 m3/ha(SE% = 6.96%). Following Garcı ´a (2004) (ten culms

yield 1.3 m3) the apparent volume was estimated to be622 m3, the relative standard error being the same(SE% = 6.96%). Analysis along approach 2 (see Ta-ble 2) produces an estimation of total apparent volumeof 654 m3/ha (SE% = 10.99%). In particular for theseestimations of apparent volume, however, it must beemphasized that the relative standard error refersexclusively to sampling. In this case, the model error (i.e.the error caused by the fact that the target variable is notmeasured but modelled) is likely to add another con-siderable error component so that the total error will behigher to an unknown extent.

Total above ground commercial wood volume of

mature Guadua along the simple geometric model of atube with outer diameter d c is estimated to be 304 m

3/ha.Total wood volume of Guadua culms is estimated to be465 m3/h where also young and dry Guadua are in-cluded. From this total wood volume, we obtain anestimation of the above ground dry biomass of 311 ton/ha and the above ground carbon stock of 156 ton/ha.

Additional information was gathered about speciescomposition of the tree component (dbh > 10 cm)associated with the Guadua stands (see also Fig. 1,right). On the cumulative area of all field sample plots

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42

Guadua patch size [ha]

0

50

100

150

200

250

300

350

400

450

F r e q u

e n c y

Fig. 3 Size distribution of Guadua patches

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(1.3 ha), 25 different botanical tree families and 61 treespecies were found with a mean number of 178 trees perhectare (SE% = 9.9%), 5.5 m2 basal area per hectare(SE% = 20.9%) and a wood volume of 78.9 m3/ha(SE% = 24.6%). Most of the tree species (70%) be-longed to species not commercially utilized for timber.

The findings about tree species diversity were similar tothe ones reported by Ospina (2001).

Discussion and conclusions

This Guadua inventory presents for the first time sam-ple-based statistical estimations of Guadua area andgrowing stock in a study area within the Coffee Regionof Colombia.

The crown projected and effective area were esti-mated to be 3.9 and 2.7% (in absolute terms 40,000 and28,000 ha), respectively. Our figures are higher than

other figures published so far: from a preliminary mapcompiled by the autonomous development corporations(Corporaciones Auto ´ nomas Regionales), we determinedthe area of Guadua stands for our study area with acover percent of 0.85% (Bernal 2002). This figure isoutside the 95% confidence interval for the true coverpercent (cc%) from our study, which for the crownprojected area is 3.07% £ cc% £ 4.74% (t = 2). Forthis statistical inference, we needed to consider the figurefrom Bernal (2002) as constant because the standarderror was not known to us.

It is not uncommon in natural resources inventoriesthat results of different studies differ to some degree, as

illustrated, for example in Kleinn et al. (2002) for forestarea figures in Costa Rica. Various causes can be iden-tified, such as different definitions and measurementprocedures, different information sources and differentinventory techniques. A sample-based statistical inven-tory, however, has the advantage that confidence inter-vals can be estimated that provide an idea of theprecision of the estimations and allow comparisons onstatistical grounds. While this adds to the credibility of our results, we cannot state with 100% certainty that ourresults are closer to the true value than other figures.

This Guadua inventory, like most forest inventoriesas well, turned out to be a complex task, with a series of potential sources of errors in all project steps, whichmake the true total error higher than the standard erroralone; the standard error which we specified in this studyfor all point estimations marks the lower limit for this

true total error of estimation. The major potentialsource of error here was probably the fact that the aerialphotographs were not up-to-date and not available forall selected plots. We needed to apply 7–12 years oldphotographs for budgetary reasons. Although expertsconfirm that the changes in Guadua stands during thatperiod were probably not significant, it is always pref-erable to use recent remote sensing imagery. We at-tempted to compensate for the age of the aerialphotographs by applying a sample-based calibrationfactor from field verifications.

Field sample size was relatively small, again forbudgetary reasons. However, by the integration of aerial

photo plots, relatively good precision was achieved.Aerial photographs were available for 89 out of a se-lected set of 103 first-stage sample plots; the remaining14 needed to be considered as non-response where weassumed that their characteristics did not differ signifi-cantly from those of the assessed sample plots.

Table 1 Development classes

Development class (definitions adapted from London ˜ o 1998) Relative frequency (SE% in parenthesis)

Shoots: From emergence of the new shoot until reaching its maximum height.Culm protected by culm leaves, and without developing branches or foliage

3.7 (12.8)

Young Guadua:Loss of the culm leaves, development of intense green colour,branches and foliage

18.6 (10.8)

Mature Guadua: The culm loses its bright green colour and turns into anopaque green and then gradually to grey, as lichens, fungi and mossesappear on the culm’s surface

69.0 (7.1)

Dry Guadua: The plants death phase. It is expressed by yellow colourof the culm, and dryness of the middle section of the branches

6.4 (15.9)

Broken Guadua: Damaged culms which are not complete 2.3 (18.9)

Obs: these classes are those that are commonly used in Guadua management and operations in the Coffee Region in Colombia. They arebased on directly observable attributes and are suitable for practical application. It is hardly possible to link these development classesdirectly to age classes, because age is virtually impossible to determine

0%

10%

20%

30%

40%

50%

60%

4-8 8-12 12-16 16-20 >=20

Diameter Classes (Dbh) (cm)

A b u n d a n c

e

( % )

Shoots Young Mature Dry Total

Fig. 4 Diameter distribution broken down to development classes

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Many trees are found interspersed in Guadua stands.These trees serve many ecological functions, such asproviding food source for wildlife. Most of the treespecies found were non-commercial. If interest is incombining wood production of both trees and bamboo,research will be required towards the selection of suit-able species and suitable silvicultural treatments.

Looking at the estimated composition of the Guadua

stands, a relatively small percentage of regeneration(shoots and young Guadua) is found, only 22.3% of theculms belong to the corresponding development classes.Among the reasons for this situation may be what Ar-ango (2002) writes, that cattle moving into and throughthe Guadua stands trample down parts of the regener-ation as most of the Guadua stands are adjacent topastures. In this context, if we follow the observation of London ˜ o (1998) and CVC (2000), that there should beabout 40% in the development classes ‘‘shoots andyoung Guadua’’ to guarantee ‘‘sustainability of har-vesting’’; we would conclude that, on the average, sus-tainability of the regeneration of the Guadua stands in

the study area is not guaranteed. However, in ouropinion, the assessment of the sustainability of Guaduastand management—which is such a complex and stillnot a perfectly understood matter—should be done bymore than just the one attribute ‘‘percentage of shootsand young Guadua’’. The number of shoots per hectarevaries considerably and does also show seasonaldynamics. The sustainability issue is certainly anotherimportant future research topic for the management of Guadua stands.

From this inventory, we could not confirm whatRian ˜ o et al. (2002) stated, that number of culms perhectare and mean diameter are negatively correlated. In

our case, there was no significant correlation betweenthese variables. Probably, mean diameter is determinedby a more complex set of factors and their interactions,where stand variables (such as number of culms) are butone set of variables, together with site and geneticsvariables. This is certainly an important topic for themanagement of Guadua stands and worth forfutureresearch.

Our biomass values are higher than those reportedfor many other bamboo species (Hunter and Junqui2002); however, their comparative study refers to bam-

boo plantations while our inventory covered almostexclusively natural stands; and, Guadua is a bamboospecies that grows to bigger dimensions than many otherbamboo species. Estimation of volume and biomass wasa challenge, because we found that there is still a lack of availability of basic mensurational models for predictingapparent volume, wood volume, biomass, and carbon.This is also true for other bamboo species as Hunter and

Junqui (2002) state: ‘‘more, simple biomass determina-tions are needed’’. Our approximations are based on theconventional approach used in Colombia, and on asimple geometric approach, where the results forapparent commercial volume differ consider-ably—between 479 and 654 m3 —indicating the uncer-tainty which is implicit in Guadua volume estimations.The volume and biomass figures must be taken asapproximations, where we needed to use various modelassumptions: on culm length, on horizontal (circularcross-section) and vertical culm shape (degree of conic-ity) and on wall thickness. These models are all backedby published studies, but they are at the same time

sources of variability in addition to the specified stan-dard error.

These manifold sources of variability point to the factthat comprehensive research is needed to fill the gap inknowledge about the basic mensurational characteristicsand relationships of Guadua culms and Guadua stands.Attributes like volume and biomass are maybe currentlynot so crucial for marketing of Guadua when utilizationis mainly for construction, furniture and handicraft;there, number of culms and culm length—as currentlyused—are sufficient for the assessment of growing stock.However, we need volume and biomass estimations,when we want to research into biomass productivity and

carbon sequestration.Altogether, this inventory exercise produced infor-

mation of high interest for the Guadua development andmanagement in the Coffee Region of Colombia. Themethodological framework may be recommended forsimilar bamboo assessments in other regions.

Acknowledgements Parts of the results presented here were pro-duced in the ‘‘Guadua Bamboo Project’’, which had been funded2001–2004 by the European Union (Contract No. ICA4-2000-10209), with project partners from Colombia (Universidad Tec-nolo ´ gica de Pereira), Costa Rica (UCR and CATIE), Germany

Table 2 Approximations to apparent volume, wood volume, biomass and carbon content

Developmentclass

N/ha Relativefrequency (%)

Commercial Total

Apparentvolume (m3/ha)

Woodvolume (m3/ha)

Apparentvolume (m3/ha)

Woodvolume (m3/ha)

Dry biomass(ton/ha)

Carbon(ton/ha)

Shoots 258 3.7 – – – – – – Young 1,290 18.6 – – 223.0 99.0 66.0 33.0Mature 4,785 69.0 654.0 304.0 729.0 339.0 227.0 113.5Dry 445 6.4 – – 56.0 27.0 18.0 9.0

Broken 162 2.3 – – – – – – Total 6,940 100.00 654.0 304.0 1,008.0 465.0 311.0 155.5

See text (Methods section) for definition of ‘‘commercial’’ and ‘‘total’’

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(Universita ¨ t Freiburg), and the United Kingdom (Imperial Collegeof Science). The financial support to the second author is highlyappreciated. Special and particular thanks are due to our colleagueand friend Dr Juan Carlos Camargo, professor at the Faculty of Environmental Sciences at the Technical University of Pereira,Colombia, for his continuing support and suggestions, to Dr Mi-chael Tistl, principal advisor in a German technical cooperationproject at that University, and to Dr Ximena London ˜ o, presidentof the Colombian Bamboo Society. An inventory is a study inwhich many people participate to all of whom we extend ourthanks. Our particular thanks for assistance in different fields aredue to Marco Antonio Cha ´ vez, Gustavo Cardona, Gabriel JaimeAranjo and the field teams, Diego Rubiano, Jhon Mario Rodrı ´-guez, Lidieth Marı ń, Lorena Orozco, Juan Carlos Ramı ´rez andVictor Madrigal. We are indebted to Prof. Walter Liese, for hisvaluable suggestions on this manuscript and his continued advisesto our Guadua related projects. The observations of an anonymousreviewer helped improving the manuscript and are highly appre-ciated.

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