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Allometric relationships of different tree species and stand above ground biomass in the Gomera laurel forest (Canary Islands)
ARTICLE IN PRESS
Flora 200 (2005) 264–274 www.elsevier.de/flora
Allometric relationships of different tree species and stand above ground biomass in the Gomera laurel forest (Canary Islands) Jesu´s Ramo´n Aboala,, Jose´ Ramo´n Are´valob, A`ngel Ferna´ndezc A`rea de Ecoloxı´a, Facultade de Bioloxı´a, Universidade de Santiago de Compostela, Campus Sur, 15782, Santiago, A Corun˜a, Spain b Departamento de Ecologı´a, Facultad de Biologı´a, Universidad de La Laguna, 38207, La Laguna, Tenerife, Spain c Parque Nacional de Garajonay, Carretera General del Sur no. 6, San Sebastia´n de La Gomera, 38800, La Gomera, Tenerife, Spain a
Received 13 May 2004; accepted 11 November 2004
Abstract Estimation of net above ground primary productivity in forest ecosystems by non-destructive means requires the development of allometric equations, to allow prediction of above ground biomass from readily measurable variables such as diameter-at-breast-height (DBH). Equations of this type have not been well developed for trees of the Macaronesian laurel forest. In the present study, we characterized trees of five species (Erica arborea, Ilex canariensis, Laurus azorica, Myrica faya and Persea indica) in four types of laurel forest in the Garajonay National Park on Gomera Island in the Canary Islands, with the aim of developing appropriate allometric equations. Among forests, within each species, the slope and elevation (y-axis intersect) of the equations obtained did not vary significantly, so that we were able to pool the data and obtain a single equation for each species. However, considering each species separately, there was significant variation among the slopes and elevations of the equations obtained for each. The difference between DBH-biomass relationships among these species can be attributed to differences in (a) the distribution of biomass among trunk-plus-primary-branches, secondary branches and leaves, and (b) woody tissue density. We applied the new allometric equations to six different forest types in the Garajonay National Park. Above ground biomass ranged from 65,631 to 352,683 kg d.w. ha1. Comparison of these results with those obtained using a previously published allometric model revealed differences of more than 100% for some forests. When we applied the new allometric equations to data from other forests on the island of Tenerife we obtained differences of more than 20% in above ground biomass which ranged from 159,469 to 310,580 kg d.w. ha1. We believe that all previous data corresponding to above ground biomass in Macaronesian laurel forest may contain errors, and propose the new equations to be used in the future, and that other one have to become developed for the remaining species. r 2005 Elsevier GmbH. All rights reserved. Keywords: Canary Islands; Laurel forest; Allometric equations; Biomass area
Abbreviations: a, constant; AGB, above ground biomass; ANCOVA, analysis of covariance; aB , aA , elevations; b, constant; Bd, dry biomass of a given secondary branch; bB , bA , slopes; D, diameter of the branch at 50 cm; DBH, diameter-at-breast-height; DF, degrees of freedom; d.w., dry weight; HLF, hillslope laurel forest; HLFII, immature hillslope laurel forest; L, total length of the branch minus 50 cm; MEF, Myrica/Erica forest; MEFd, disturbed Myrica/Erica forest; MPD, mid-point diameter (mid-point circumference of each trunk section); SMA, standardized major axis regression; V, volume of the distal section of that branch; VLF, valley-bottom laurel forest; VLFII, immature valley-bottom laurel forest Corresponding author. Fax: +34 981 596904. E-mail addresses: [email protected] (J.R. Aboal), [email protected] (J.R. Are´valo), [email protected] (A. Ferna´ndez). 0367-2530/$ - see front matter r 2005 Elsevier GmbH. All rights reserved. doi:10.1016/j.flora.2004.11.001
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Introduction Macaronesian laurel forest, a subtype of the evergreen lucidophyll oak-laurel forests (Tawaga, 1997), is a relic forest, the study of which is important in helping to understand the composition and ecology of Tertiary Mediterranean flora (at the edges of the Tethys Sea in the Late Miocene epoch). This type of forest is now restricted to northern parts of the Canary Islands, Madeira and the Azores (Ceballos and Ortun˜o, 1976; Kunkel, 1987; Santos, 1990). The most important area where this forest type is found is on Gomera Island, most of which was declared a National Park in 1981, and subsequently a World Heritage site (Ferna´ndez, 1990). The area – Garajonay National Park – contains more than 50% of the total remaining area of mature laurel forest in the Canary Islands (Ferna´ndez, 1992). Because of their situation in the arid, subtropical region of the west coast of Africa, and their botanical and physiological characteristics, Macaronesian laurel forests retain certain similarities to tropical mountain forests (Hu¨bl, 1988; Lo¨sch and Fischer, 1994) and some extratropical forests (Meusel, 1965) – mainly Mediterranean sclerophyllous forests and temperate broadleaved evergreen forests (Goodall, 1983). Above ground biomass is of great value for characterizing the composition, structure and function of ecosystems. As pointed out by Ferna´ndez-Palacios et al. (1991), this variable is of value not only for theoretical understanding of energy and element flows within the ecosystem, but also from a more practical point of view, as an indicator of ecological impact. Thus, knowledge of laurel forest above ground biomass may help in understanding the composition, structure and function of Tertiary Mediterranean ecosystems and provide a means of monitoring possible ecological impacts in these protected forests. Non-destructive estimation of above ground biomass (AGB) of trees is generally carried out by means of twodimensional analytical techniques (Whittaker and Maks, 1975), which are based on the relationships between biomass and readily measured biometric variables such as diameter-at-breast-height (DBH). A similar method has previously been used in a study of a Canary Islands laurel forest (Ferna´ndez-Palacios et al., 1991), and the allometric equation obtained (AGB vs. DBH) has been used in a number of posterior studies: Ferna´ndez-Palacios et al. (1991), Ferna´ndez-Palacios et al. (1992), Ferna´ndez-Palacios and Lo´pez (1992), and Morales et al. (1996). Thus, at present all the estimates of above ground biomass in Macaronesian laurel forests are based on the equation proposed by Ferna´ndezPalacios et al. (1991), although they did not take into account differences among species (they grouped data from 10 species), and the model was derived only for trees of up to 20 cm DBH (posterior extrapolations were
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made for trees of DBH4100 cm). In the present study we chose not to use the equations developed in the previous study (op.cit.) and we aimed: (1) to obtain new allometric equations for estimating tree biomass, (2) to examine whether a single equation can be developed for application to all species, and (3) to calculate the above ground biomass of the major forest types present in Garajonay and to re-examine (with the new allometric equations) above ground biomass of another forests in Tenerife.
Material and methods Study area The Garajonay National Park is located in the high central area (800–1486 m a.s.l.) of Gomera Island, in the western Canary Islands. The park covers an area of 3984 ha (10% of the total surface area of the island). Condensation of the water vapour brought in by trade winds frequently produces cloud banks, which give rise to high relative humidity. There are three types of laurel forest present, each of which differs in structure and composition (Wildpret and Martı´ n, 1997): (i) ‘‘valleybottom laurel forest’’ (forest type VLF) (laurisilva de barranco o valle), which occurs in wet sites such as stream sides and valley bottoms, and is dominated by Persea indica (L.) Spreng and Laurus azorica (Seub.) Franco, (ii) ‘‘Myrica/Erica forest’’ (forest type MEF) (fayal/brezal), which occurs at drier south-facing sites, and is typically dominated by Erica arborea L. and Myrica faya Ait., though with Ilex canariensis Poivet. and L. azorica also present, and (iii) ‘‘hillslope laurel forest’’ (forest type HLF) (laurisilva de ladera), which occurs at sites with intermediate environmental conditions and is characterized by a wider range of tree species, including E. arborea, M. faya, I. canariensis and L. azorica. The sampling areas for these three forest types were Acebin˜os, La Can˜ada de Jorge and Los Noruegos. For the present study we also selected a disturbed Myrica/Erica forest site that was cleared several decades ago, and where E. arborea, I. canariensis and M. faya, as well as a few young individuals of L. azorica were growing (forest type MEFd). This site was on the southern side of the Park, in the area known as Palos Pelados. With the single aim of calculating the above ground biomass, we selected another two immature forests, a hillslope laurel forest (HLFII) and a valley-bottom laurel forest (VLFII). The length of each plot was calculated by multiplying the mean height of the trees within the plot by two; the corresponding values obtained were: VLF ¼ 2400 m2, VLFII ¼ 2400 m2, HLF ¼ 1600 m2, HLFII ¼ 900 m2, MEF ¼ 900 m2 and MEFd ¼ 400 m2.
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Table 1. Number of trees of each species characterized in each of the forest types Species
HLF
MEF
MEFd
I. canariensis L. azorica M. faya E. arborea P. indica
10 7 8 12
10 8 9 9
13
Total
37
36
VLF
20
33 31 29 33 20
36
146
16 12 12 37
Total
similar procedure. Finally, the total dry biomass of trunk plus primary branches was estimated using previously published figures for the density of dry wood: E. arborea 0.576 g cm3, I. canariensis 0.888 g cm3, L. azorica 0.627 g cm3, M. faya 0.745 g cm3 and P. indica 0.448 g cm3 (Na´jera et al., 1959; Peraza and Lo´pez De Roma, 1962). The biomass of secondary branches on each tree was estimated by an indirect procedure, based on an allometric equation of the following form, derived for each species:
See text for an description of each of the forest types.
Bd ¼ a þ bV , In the present study, we characterized trees at each of these four sites (Acebin˜os, La Can˜ada de Jorge, Los Noruegos, Palos Pelados), corresponding to forest types VLF, MEF, HLF and MEFd, respectively. At each site, we selected between 8 and 20 individuals of each species present, as summarized in Table 1. Sampling at each site was stratified on the basis of DBH: the individuals of each species were grouped into 4–10 cm DBH classes and two individuals were selected at random from each class, giving a total of 8–20 individuals of each species for each site. Poorly represented classes were not sampled. The total number of trees selected was 146.
Sampling and analysis Above ground biomass estimation Park regulations meant that trees could not be felled, so AGB was estimated by non-destructive means, in the summer of 1994. Total AGB was estimated as the sum of the estimated dry biomass of (a) trunk and primary branches (except the distal sections, from the point at which the diameter fell below 7 cm) and (b) secondary branches and the most distal sections of trunk and primary branches. The biomass of the trunk and primary branches (except the distal sections) was estimated directly for each tree, as follows. One person climbed the tree, marking the height on the trunk every 2 m (for trees of total height410 m) or 1 m (for trees of total heighto10 m), until reaching the point at which the trunk diameter fell below 7 cm, so that the penultimate section (i.e. the one before the distal section) was typically shorter than the rest. We then measured the mid-point circumference of each section to obtain the mid-point diameter (MPD), which allowed estimation of the volume of that section, assuming it to be a cylinder of diameter MPD (Huber0 s formula in Hustich et al., 1972). The total volume of primary branches (i.e. those inserting directly to the trunk) was measured by a
where Bd is the dry biomass of a given secondary branch, a and b are constants and V is the volume of the distal section of that branch, in turn estimated (assuming that section to be perfectly conical) as V ¼ 1=3pD2 L; where D is the diameter of the branch at 50 cm from its point of insertion and L is the total length of the branch minus 50 cm. In order to obtain this relationship (Bd ¼ a þ bV ) for each species, a single secondary branch was cut from each of a total of 80 trees: 20 I. canariensis from MEF and HLF, 17 E. arborea from MEF, MEFd and HLF, 11 P. indica from VLF, 16 M. faya from MEF, MEFd and HLF, and 16 L. azorica from VLF and HLF. In each case, we recorded D and L. The volume of the proximal section (first 50 cm) was estimated by assuming it to be a cylinder of diameter D. The volume of the distal section was estimated by assuming it to be a perfect cone of base diameter D and length L. The fresh weight of the distal section was obtained before and after removal of leaves. We then cut two slices of 100–200 g of wood from each branch and took two leaf samples each weighing about 100 g. These samples were oven dried at 105 1C to constant weight, allowing estimation of the fresh-to-dry weight ratio for secondary-branch wood and leaves, which in turn allowed estimation of the total dry biomass (Bd) of that secondary branch. For each tree species, we then performed a linear regression of total Bd on distalsection volume as estimated from D and L, giving the allometric relationship Bd ¼ a þ bV for that species. Subsequently, we determined D and L for all secondary branches of each tree characterized, allowing estimation of Bd for each branch and thus total secondary-branch dry biomass for that tree. The weight of the proximal section was estimated using the densities of dry wood; these two values were then summed to give the estimated fresh biomass of that branch. The biomass of the distal sections of the trunk and primary branches was estimated in the same way as that of secondary branches: i.e. an allometric relationship (relating dry biomass to volume as estimated from basal diameter and length) was derived for the distal sections of each species, and this relationship was then used to
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estimate the dry biomass of all sections, from the basal diameter and length.
Statistical analyses For prediction of total above ground biomass of trees from allometric variables, the candidate allometric variables considered were DBH, DBH height and DBH2 height. Normality of the dependent variable (above ground biomass) was confirmed using Lilliefor’s modification of the Kolmogorov-Smirnov test. If this test indicated that normality could not be assumed, the data were subjected to logarithmic transformation. Here we used both the standard regression method and standardized major axis (SMA) slope-fitting techniques. We used the standard regression method because it remains valid when the only aim is to detect interspecific variations and not to calculate regression parameters (Kohyama, 1987; Kohyama and Hotta 1987; Yamada et al., 2000). Standardized major axis slopefitting techniques were considered to be the most appropriate for describing bivariate relationships, as there was variation associated with measurement error and species sampling for both x and y variables; hence, it was inappropriate to minimize sums of squares in the y dimension only (Sokal and Rohlf, 1995). These ‘‘scaling’’ slopes, calculated on log-transformed variables, give the proportional relationship between variables. We compared the slopes and elevation multiples by applying analysis of covariance (ANCOVA) (Zar, 1984) to the straight lines obtained by the standard regression method. Where significant differences were detected, pairwise comparisons were made by Tukey tests.
Results Allometric analysis To estimate the total above ground dry biomass, we generally considered standard regression models in which the predictor was DBH, and models in which both DBH and height were used as predictors. In both cases AGB was subjected to a natural log transformation to normalize its distribution (testing through box-cox transformation). For all tree species and all forest types, the model selected was a double logarithmic model, using DBH as predictor (i.e. models of the type ln AGB ¼ a þ b ln DBH); other models (e.g. polynomial models) gave a worse fit, and were rejected. Models in which the dependent variable included height (a þ DBH height; a þ bDBH2 height; or aDBHb heightc ) gave poor results in all cases.
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Among-forest-type within-species comparisons of model parameters (slopes and elevations) were carried out by analyses of covariance, considering each forest type separately for each species. We firstly developed the ANCOVA for slopes (ln DBH vs. ln AGB), which revealed no significant differences among forests for each species: E. arborea F 0:05ð1Þ;2;27 ¼ 0:297; I. canariensis F 0:05ð1Þ;2;27 ¼ 0:498; L. azorica F 0:05ð1Þ;2;25 ¼ 0:448; M. faya F 0:05ð1Þ;2;23 ¼ 0:286; the corresponding value for P. indica was not calculated because this species was found in only one of the forests studied. According to Zar (1984) if no significant differences are found among regression slopes of each forest, we must calculate the common regression slope after test for differences among elevations (y-axis intersects); no significant differences were found among forest types for withinspecies elevations (ln DBH vs. ln AGB): E. arborea F 0:05ð1Þ;2;29 ¼ 3:084; I. canariansis F 0:05ð1Þ;2;29 ¼ 0:234; L. azorica F 0:05ð1Þ;2;27 ¼ 2:212; M. faya F 0:05ð1Þ;2;25 ¼ 0:441; in the case of P. indica the analysis could not be carried out for the same reasons as before. In view of the lack of significantly different variations of the parameters among forests, we constructed a standard regression model (ln DBH vs. ln AGB) in which the data for these forests, and for each species, were considered together (as a single data pool). We also employed SMA slope-fitting techniques to the same data pools. The results of both techniques (model parameters and goodness-of-fit statistics) are shown in Fig. 1; the results for each species with both types of model were almost identical, except for P. indica, which showed some differences. All correlation coefficients were highly significant (Po0:001). We then used multiple analyses of variance to compare among-species variation in model parameters (ln DBH vs. ln AGB slopes and elevations) considering all the data for each species separately as a single entity, or pooled without distinguishing among forest types. This ANCOVA revealed significant differences among species, both in slopes (F 0:05ð1Þ;4;136 ¼ 11:326) and elevations (F 0:05ð1Þ;5;140 ¼ 25:423). Subsequent pairwise comparisons by means of post hoc Tukey test for slopes (test H 0 : bB ¼ bA ; (S 2YX )p ¼ 0.038; DFp ¼ 136), revealed significant differences (Po0:05) for all pairs except M. faya and I. canariensis: L. azorica and P. indica, P. indica and M. faya and I. canariensis and E. arborea. The results obtained are summarized in Table 2. In the same way, subsequent pairwise comparisons by post hoc Tukey test for elevations (test H 0 : aB ¼ aA ; (S2YX)p ¼ 0.053; DFp ¼ 136), revealed significant differences (Po0:05) for all pairs except for L. azorica and M. faya and P. indica and E. arborea. The results obtained are summarized in Table 3. We did not find any pairs of species for which there were no significant differences in slopes and elevations;
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MEFd
Ln Dry weight
8 y = 1.8989x- 0.8955 r 2 = 0.97***
6
MEF
VLF
y = 2.0062x- 0.7229 r 2 = 0.97***
6
4
4 y1 = 0.570 + 0.506 y2
y1 = 0.478 + 0.477 y2
2
2 I. canariensis
E. arborea 0
0 1
2
3
4
5
8
1
2
3
4
5
8 y = 2.4392x -2.1484
Ln Dry Weight
HLF
8
r 2 = 0.99***
6
y = 2.1628x-1.3412 r 2 = 0.99***
6 4
4
y1 = 0.570 + 0.506 y2
y1 = 1.783 + 0.202y2 2
2 L. azorica
M. faya 0
0 1
2
3
4
5
8
1
2
3 Ln DBH
4
5
Ln Dry Weight
y = 2.3377x- 2.2932 r 2 = 0.98***
6 4
y1 = 0.570 + 0.506 y2 2 P. indica 0 1
2
3 Ln DBH
4
5
Fig. 1. Results and parameters of the allometric equations used to predict total above ground dry biomass (AGB) (kg d.w.) from DBH (cm) for each of the species considered. Regression method (solid line, y ¼ a þ bx) and standardized major axis (SMA) (broken line, y1 ¼ a þ by2 ) slope-fitting techniques. In all cases the predictive equation was of the form ln AGB ¼ a+b ln DBH. Correlation coefficients and significance levels (***Po0:001) are also shown. Each point represents an individual tree. VLF: ‘‘valleybottom laurel forest’’; MEF: ‘‘Myrica/Erica forest’’; HLF: ‘‘hillslope laurel forest’’, and MEFd: ‘‘disturbed Myrica/Erica forest’’.
therefore we could not create a new data pool using the data from two or more species to calculate a new model. Collective representation of the model for each species is shown in Fig. 2, including the model proposed by Ferna´ndez-Palacios et al. (1991).
Biomass Finally, we applied the new allometric equations to the individual diameters of each of the trees in each forest obtained during the inventory (Fig. 3); the AGB values obtained for each age class are shown in Fig. 4. In the case of Picconia excelsa, we applied the equation of Ferna´ndez et al. (1991), as we did not have enough data
to be able to derive new allometric equations. Likewise, we applied the allometric equation proposed by these authors (op.cit.) to our data – the AGB values obtained are shown in Fig. 4 and Table 4; in almost all cases the AGB values were overestimated by the Ferna´ndez et al. (1991) equation (MEF 73%, VLFII 131%, VLF 185%, HLFII 28%, HLF 123%), except for that corresponding to MEFd, which was underestimated (10%). We applied the new equations, where applicable, to data available from inventories carried out in seven plots in the north of the island of Tenerife (6 – each of 2500 m2 – in the Anaga peninsula and another – of 3390 m2 – in Agua Garcı´ a). Where not applicable, we applied the equation of Ferna´ndez et al. (1991); the results are shown in Table 4. The differences in biomass
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Table 2. Results of the Tukey test, comparing the slopes (bB ¼ bA ) for different pairs of species
269
Fdez. -Palacios et al. (1991)
L.a vs. E.a L.a vs. I.c L.a vs. M.f L.a vs. P.i P.i vs. E.a P.i vs. I.c P.i vs. M.f M.f vs. E.a M.f vs. I.c I.c vs. E.a
Difference (bB bA )
SE
q
Conclusion
0.542 0.435 0.278 0.103 0.439 0.331 0.175 0.264 0.157 0.107
0.060 0.062 0.061 0.062 0.058 0.060 0.060 0.058 0.060 0.058
9.065 7.030 4.524 1.672 7.555 5.508 2.924 4.564 2.613 1.843
Reject Ho Reject Ho Reject Ho Accepted Ho Reject Ho Reject Ho Accepted Ho Reject Ho Accepted Ho Accepted Ho
(S2YX)p ¼ 0.038; DFp ¼ 136; (ranked samples b: E. arborea: 1.899; I. canariensis: 2.006; M. faya: 2.163; P. indica: 2.338 and L. azorica 2.441). SE: standard error, q: obtained value of the q statistic; tabulated value of the q statistic q0;05;136;5 ¼ 3:858:
Table 3. Results of the Tukey test, comparing heights of the slopes (aB ¼ aA ) for the different pairs of species
L.a vs. E.a L.a vs. I.c L.a vs. M.f L.a vs. P.i P.i vs. E.a P.i vs. I.c P.i vs. M.f M.f vs. E.a M.f vs. I.c I.c vs. E.a
SE
q
Conclusion
0.041 0.041 0.042 0.056 0.051 0.052 0.052 0.041 0.041 0.040
7.119 5.199 1.205 4.758 0.582 9.143 6.031 8.360 3.906 12.659
Reject Ho Reject Ho Accept Ho Reject Ho Accept Ho Reject Ho Reject Ho Reject Ho Reject Ho Reject Ho
(S2YX)p ¼ 0.053; DFp ¼ 136. SE: standard error, q: obtained value of the q statistic; value of the q statistic q0;05;136;5 ¼ 3:858:
estimated by the new equations and by that of Ferna´ndez et al. (1991), for the five species to which both methods were applied, are also shown in Table 4.
Discussion Various authors have stated that the most important advantage of two-dimensional analytical techniques for estimating above ground biomass of trees is that the same equation is often valid for all tree species within the ecosystem under consideration (Whittaker and Woodwell, 1968). This has been confirmed for forest types including tropical forest and temperate deciduous woodland (Duvigneaud, 1974), and has been assumed to apply to laurel forests (Ferna´ndez-Palacios et al., 1991).
Ln AGB
8
M. faya
I. canariensis
6
E. arborea 4 P. indica L. azorica 2 2
3
4 Ln DBH
Fig. 2. Plot of the natural logarithm of total above ground dry biomass (kg d.w.) against the natural logarithm of DBH (cm), for each of the tree species considered, with data from all fourforest types. Comparison of the biomass-DBH relations obtained in the present study with that obtained by Ferna´ndez-Palacios et al. (1991). To facilitate the comparison, the original equation of Ferna´ndez-Palacios et al. (1991) (AGB ¼ 0.0551+DBH2.7157) has been converted to double logarithmic form (ln AGB ¼ 2.7157 ln DBH2.8986).
The latter authors studied 10 laurel forest tree species (n ¼ 27) using destructive methods and considered individuals of DBHo20 cm, although only seven of the trees were of DBH410 cm. The AGB–DBH equation obtained in the present study for each species is very similar to the general AGB–DBH equation reported by these authors (Fig. 2), for DBH ranging between 7 and 20 cm (ln DBH ¼ 223). However, for DBH420 cm (ln DBH43), the equation of Ferna´ndezPalacios et al. (1991) lies above all the single species equations. In mature laurel forests, however, the DBH may reach 100 cm or more, and the use of the equation of Ferna´ndez-Palacios et al. (1991) might be expected to give rise to considerable error. The results of the present study suggest that the assumption that the same equation is often valid for all tree species within the ecosystem under consideration, is not valid in laurel forests, because there were significant differences between the allometric equations for all the species pairs. On the other hand, we did not detect significant among-forest-type within-species differences in allometric equations in the present study, so that the species studied show the same allometric relationships (relating DBH and AGB) independently of the type of forest, thereby allowing all the data for one species to be pooled to derive a single allometric equation for each species.
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Fig. 3. Distribution of tree density (all species) in the laurel forests under study, based on diameter at breast height (DBH) classes. Note the differences in the y-axis values in the different graphs.
The difference in the DBH–AGB relationships of these five species can be attributed to differences in (a) woody tissue density, and (b) the distribution of biomass between woody tissue and leaves. As regards the woody tissue density, there is a relationship between the height of the slope and the corresponding density of the wood of each species (Fig. 2), so that the lower the density of the wood, the lower the height of the slope (the lowest wood densities were those of P.indica, 0.448 g cm3 and E.arborea, 0.576 g cm3), and the higher the density (I.canariensis, 0.888 g cm3) the higher the height of the slope. The proposed equations are based on the relationship between volume and weight, as we related DBH to AGB; thus, the DBH gives us an ‘‘idea’’ of the volume of the tree, since DBH is similar to that of the base of a cone. It is obvious that because we were relating volume to weight and there exist large differences in density among the five species (ranging from 0.448 to 0.888 g cm3, i.e. the highest density is almost twice the lowest), the heights of the slopes of the allometric equations were different. However, where the densities of the wood were similar (e.g. in the pairs
M.faya-L.azorica and P.indica-E.arborea) there were no significant differences in the heights of the slopes. As regards the distribution of biomass, the relative proportions in leaves and woody tissue change over time. Thus, all the slopes for the relations between DBH (Eage) and the percentage of the weight accounted for by woody tissue (trunk-plus-primary and secondarybranches) were positive and significant (Po0:001 in all cases). The change in the distribution of biomass differed for each of the species, leading to differences in the slopes for the allometric equation relating DBH and AGB. If the relation between DBH and the percentage of weight made up by woody tissue was always the same for all species, we would obtain parallel lines, ordered only by the density of the woody tissue. These differences in distribution of biomass as either woody tissue or as leaves result from the widely known phenomenon of variability in allocation of net production that occurs with increasing age in trees (Smith and Smith, 2000), i.e., the higher the DBH, the higher the proportion of biomass made up of woody tissue (up to more than 99% in this case); the variability in allocation
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Fig. 4. Distribution of tree above ground biomass (dry weight, kg ha1) (all species) in the laurel forests under study, based on diameter at breast height (DBH) classes. The biomass values predicted using the equation of Ferna´ndez-Palacios et al. (1991) are shown as points joined by a line. For the Hillslope Laurel Forest, the value corresponding to the 157–162 cm DBH class is shown as a number above the graph. Note the difference in the y-axis values in the different graphs.
of net production with increasing age varied among all tree species. Having recognized the need to derive allometric equations (relating DBH and AGB) for each species, and the underlying reasons for this, we then turned out attention to the application of these in calculating the AGB for each forest. Application of the new equations to the Garajonay forest data, along with application of the model proposed by Ferna´ndez-Palacios et al. (1991) to the same inventories (Table 4) revealed differences in the estimation of AGB that were sometimes extremely significant (185% overestimation using the latter equation in the case of HLF). Examination of the differences between the two estimates at the level of species (Table 4) and diameter classes (Fig. 4) revealed that the differences are due to a combination of three factors: (a) the already mentioned need to derive an allometric equation for each species; (b) the weight contribution of each species to the total for the plot; and (c) the extrapolation of the equation of Ferna´ndez-Palacios et al. (1991) to DBH420 cm. As regards the need to
derive an allometric equation for each species, we can deduce from Fig. 3 that if the slope corresponding to a species lies above the slope obtained using the model of Ferna´ndez-Palacios et al. (1991), the latter underestimates the values, and if the slope lies below, the latter overestimates the values, and the degree of under- or overestimation is related to the difference in the height of the slopes. Whether the different slopes intersect depends on the DBH; therefore, the degree of under- or overestimation will depend on the size of individual trees in a plot. The weights of I. canariensis are therefore underestimated, and the lower the DBH, the greater the underestimation (i.e. MEFd 48%); the weights of P.indica are overestimated and the higher the DBH, the higher the overestimation (i.e. VLF 197%), mainly due to the presence of individuals of large DBH (Fig. 4). In one case, the size of a single individual was overestimated by more than 285% (P. indica in VLF). For other species, such as L. azorica, consistency between the previous and new estimates occurred because, in almost all the forests, trees of this species were of the
MA 1
Erica Heberdenia Ilex scoparia excelsa canariensis
Ilex Laurus perado azorica
Myrica faya
Persea indica
Picconia Prunus Rhamnus Viburnum Visnea excelsa lusitanica glandulosa tinus mocanera
2752 259326(16)
92 6896 7–21 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
300 9767 7–17 288 16242 7–21 736 37357 7–26 32 3619 10–25 120 7190 8–18 184 7275 7–18 — — — — — — — — — — — — — — — — — — — — —
— — — — — — — — — 80 11165 8–30
344 58652(25) 7–47 124 32169(38) 7–40 284 61844(30) 7–46 108 30417(34) 8–36 100 15909(15) 13–32 56 15802(32) 11–38 283 81086(33) 7–46 289 63306(39) 7–47 750 48965(8) 7–22 — — — — — — 150 169485(174) 7–159 67 11601(30) 9–35
4 279(57) 16–16 4 249(54) 16–16 — — — — — — — — — — — — 236 18831(68) 7–28 — — — — — — 304 328918(197) 7–124 588 255171(164) 7–95 — — — — — —
4 5314 41–41 20 20136 18–57 — — — — — — — — — 8 3934 19–35 — — — — — — — — — — — — 4 56 8–8 — — — — — —
2728 310580(3) 2240 180877(10) 3176 165196(3) 3264 159469(9) 2652 187635(8) 1696 182396(26) 1411 264705(73) 3175 125409(10) 492 352683(185) 1408 327325(131) 906 319172(123) 578 65631(28)
808 60086(46) 7–35 48 3349(41) 7–24 140 11626(55) 7–33 96 11786(69) 12–33 44 6312(89) 12–35 592 51007(49) 7–32 469 27935(25) 7–25 444 125019(138) 8–51 2300 72157(9) 7–15 — — — — — — 138 38548(178) 8–61 344 24339(58) 7–33
216 15756 7–23 488 103418 7–43 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
328 19404(33) 7–21 256 24773(18) 7–26 344 29700(19) 7–28 652 26855(44) 7–15 1124 63060(32) 7–36 792 43312(–34) 7–25 32 2306(29) 7–18 500 72498(6) 9–32 125 4286(48) 7–9 — — — 88 100(13) 7–48 81 37660(60) 7–60 167 29692(4) 8–35
32 3851 12–21 41 1938 7–20
520 56325(11) 7–45 744 45880(2) 7–42 716 40008(1) 7–26 784 26477(7) 7–22 660 20744(1) 7–15 392 19486(2) 7–25 634 50300(3) 7–29 178 3881(14) 7–12 — — — 188 23765(20) 8–58 729 71998(15) 7–61 538 73478(10) 8–33 — — —
76 19855 8–41 580 43564 7–45 — — — 624 9639 7–11 1216 46255 7–29 596 42968 7–27 — — — — — — — — — — — — — — — — — — — — —
36 6144 12–27 40 12783 8–41 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
— — — 136 8018 7–41 20 342 7–9 800 45237 9–26 — — — — — — — — — — — — — — — — — — — — — — — — — — —
24 848 7–13 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
(MA: Monte Aguirre, M: Moquinal; AG: Agua Garcı´ a) and 6 in Gomera (Ga: Garajonay). The figure in parenthesis after the value of AGB is the percentage difference in the present estimate and that estimated using the equation of Ferna´ndez-Palacios et al. (1991).
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Apollonias Erica barbujana arborea
J.R. Aboal et al. / Flora 200 (2005) 264–274
n AGB dbh MA 2 n AGB dbh MA 3 n AGB min M1 n AGB dbh M2 n AGB dbh M3 n AGB dbh AG n AGB dbh G MEF n AGB dbh G MEFd n AGB dbh G VLF n AGB dbh G VLFII n AGB dbh G HLF n AGB dbh G HLFII n AGB dbh
Total
272
Table 4. Values of stand density, n (trees ha1), above ground biomass, AGB (kg ha–1d.w.) and minimum and maximum diameter at breast height DBH (cm) for 7 laurel forest plots in Tenerife
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same size as the estimated values, and this changed only where large individuals were found (i.e. VLF). The least amount of residuals generated when using the equation of Ferna´ndez-Palacios et al. (1991) corresponded to this species, which is consistent with the estimates being closest to those obtained by the individual equation. As we have observed, overestimates occurred when extrapolations from the equation of Ferna´ndez-Palacios et al. (1991) were made, so that the larger the trees, the greater the error. However, we did not use particularly large DBH values when constructing the slopes (the maximum DBH values were: 56.0 cm for E. arborea; 49.7 cm for I. canariensis; 39.5 cm for L. azorica; 55.2 cm for M. Faya and 76.9 cm for P. indica), which were within the normal range found for these species, but were not the maximum DBH existing. On some occasions, extrapolations must be made, with the consequent risk of error. However, because we sampled a much wider range of DBH and obtained an almost perfect linear response, the change in the individual slopes should be minimal on including individuals of greater DBH. Lastly, because of the contribution of the weight of each species to the total weight in the plot, under- or overestimates of individual species may be either counterbalanced or biased by the weight of the species relative to the total weight, so that the results obtained using our equations and that of Ferna´ndez-Palacios et al. (1991) are consistent (i.e. MEF, total 10% including 48% de I.canariensis, which is not the predominant species in the plot). Finally, we wish to compare our results with those of previous studies concerning the AGB of Macronesian laurel forests. The results available to date are from: Morales et al. (1996), who estimated the AGB of a forest in Agua-Garcı´ a in the north of Tenerife (the same plot for which values are presented here, but from an inventory carried out in previous years) as 198,460 kg ha1 d.w. for individuals of DBH47 cm; Ferna´ndez-Palacios et al. (1991) for 10 plots in the north of Tenerife (Moquinal) with estimated values of 391 100, 285 900, 307 100, 179 100, 160 500, 170 000, 257 000, 382 000, 252 300 and 165 900 kg ha1 d.w. and Ferna´ndez-Palacios et al. (1992) and Ferna´ndez-Palacios and Lo´pez (1992) for six plots in Moquinal with an estimated value of 296700 kg ha1 d.w. – in both the latter the data included individuals of DBHo7 cm, which did not contribute a lot of biomass to the total (for the two Moquinal plots included in the present study, the total AGB only decreased by 2.1% and 7.3% on omitting individuals of DBHo7 cm). The values shown are similar to those calculated in the present study. The values obtained by the equation of Ferna´ndez-Palacios et al. (1991) for the Agua-Garcı´ a plots were overestimated by 26% relative to our results. Since the species of this forest are almost the same as those we used to calculate the new allometric equations, we consider the new estimate to be more reliable. The
273
overestimation is mostly attributable to M. faya (33% due to the large DBH values and its predominance in the plot) and P. indica (68%); the AGB value for this plot is not high, possibly because it is an immature forest in the process of recovering from felling carried out in the 1950s. As regards the Anaga forest, in the present study almost all the under- or overestimates were low (9% to 16%), although the equation of Ferna´ndez-Palacios et al. (1991) was used to calculate the total biomass of species for which new allometric equations were not derived, so that the differences found only correspond to the five species for which new equations were derived. However, we can see that the DBH values for these forests are much lower than those calculated for Gomera and Agua-Garcı´ a, so that the problem of extrapolation does not exist. Although the final result does not vary greatly, the results for individual species do (differences of 34% to 89%). This indicates that although satisfactory results can be obtained using the equation of Ferna´ndez-Palacios et al. (1991) for DBHo20 cm, because under- and overestimates will counterbalance each other within the total, the biomass distribution obtained with this equation for each individual species will be erroneous. Thus, the previous values referring to Moquinal may be close to the real values and are very similar to those obtained in the present study in terms of each plot, but not in terms of the individual contribution of each species to the total.
Conclusions Separate allometric equations (relating DBH and AGB) should be derived for each tree species studied as there are inappreciable differences among-forest-type within-species. There were no differences in the results obtained using regression and standardized major axis (SMA) slope-fitting techniques. We applied the new allometric equation obtained and also that published by Ferna´ndez-Palacios et al. (1991) to the data corresponding to the Gomera forest and a forest in the north of Tenerife, and found that when the latter expression was applied to individuals of DBH420 m, overestimated values were obtained. We therefore believe that the most accurate data on above ground biomass are those published here. In future studies, allometric equations should be derived for those species for which they have not been developed and a suitable range of DBH should be included in the expressions.
Acknowledgements This project formed part of the Garajonay National Park Ecological Monitoring Programme financed by
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ICONA and directed by Asuncio´n Delgado. Data were collected by Javier Leone´s (who climbed the trees), and by Pedro Marichal, Antonio Niebla and Ellen Fetzer. We thank Dr. Rube´n Retuerto for his advice and Dr. Alejo Carballeira for his help and support.
References Ceballos, L., Ortun˜o, F., 1976. Vegetacio´n y flora forestal de las Canarias Occidentales. Cabildo Insular de Santa Cruz de Tenerife, Tenerife. Duvigneaud, P., 1974. La synthe`se e´cologique. Doin, Paris. Ferna´ndez, A., 1990. El Parque Nacional de Garajonay. In: Pe´rez De Paz, P.L. (Ed.), Parque Nacional de Garajonay, Patrimonio Mundial. Excmo. Cabildo Insular de la Gomera, ICONA, Madrid, pp. 66–71. Ferna´ndez, A., 1992. Los problemas de los Parques Nacionales, Garajonay. Montes 30, 34–41. Ferna´ndez-Palacios, J.M., Lo´pez, R.J., 1992. Evaluacio´n del mantillo en los ecosistemas tinerfen˜os ma´s caracterı´ sticos. Rev. Acad. Canar. Cienc. 4 (3–4), 65–78. Ferna´ndez-Palacios, J.M., Garcı´ a Esteban, J.J., Lo´pez, R.J., Luzardo, M.C., 1991. Aproximacio´n a la estima de la biomasa y produccio´n neta ae´reas en una estacio´n dela Laurisilva tinerfen˜a. Vieraea 20, 11–20. Ferna´ndez-Palacios, J.M., Lo´pez, R.J., Luzardo, M.C., Garcı´ a Esteban, J.J., 1992. Descripcio´n ecolo´gica y evaluacio´n de la produccio´n neta de cuatro estaciones representativas de los ecosistemas ma´s caracterı´ sticos de Tenerife (Islas Canarias). Studia Oecol. 9, 105–124. Goodall, D.W., 1983. Ecosystems of the world. 10: Terrestrial ecosystems: Temperate broad-leaved evergreen forest. Amsterdam. Hustich, B., Miller, C., Beers, T., 1972. Forest Mensuration. The Ronald Press Company, New York. Hu¨bl, E., 1988. Lorbeerwa¨lder und Hartlaubwa¨lder (Ostasien, Mediterraneis und Makaronesien). Du¨sseldorfer Geobot. Koll. 5, 3–26. Kohyama, T., 1987. Significance of architecture and allometry in samplings. Func. Ecol. 1, 339–404. Kohyama, T., Hotta, M., 1987. Significance of allometry in tropical samplings. Func. Ecol. 5, 515–521.
Kunkel, G., 1987. Die Kanarischen Inseln und ihre Pflanzenwelt. 2. Aufl. Ulmer, Stuttgart. Lo¨sch, R., Fischer, E., 1994. Vikariierende Heidebuschwalder und ihre Kontaktgesellschaften in Makaronesien und Zentralafrika. Phytocoenologia 24, 695–720. Meusel, H., 1965. Die Reliktvegetation der Kanarischen Inseln in ihren Beziehungen zur su¨d- und mitteleuropa¨ischen Flora. In: Gersch, A. (Ed.), Gesammelte Vortra¨ge. Probl. moderner Abstammungslehre 1. Jena, pp. 117–136. Morales, D., Jime´nez, M.S., Gonzalez-Rodriguez, A.M., Cermak, J., 1996. Laurel forests in Tenerife, Canary Islands: I. The site, stand structure and stand leaf area distribution. Trees 11, 34–40. Na´jera, F., Peraza, C., Lo´pez, V., Boga, E., Cruzado, J., 1959. Estudio de cinco especies de flora forestal de Canarias, notables por las caracterı´ sticas de sus maderas. Anal. Inst. Forest Invest. Exp. 4, 55–73. Peraza, C., Lo´pez De Roma, V., 1962. Las maderas de los a´rboles de Canarias. Instituto Espan˜ol de Investigaciones Forestales, Madrid. Santos, A., 1990. Evergreen forest in Macaronesian region. Council of Europe, Strasbourg. Smith, R.L., Smith, T.M., 2000. Elements of Ecology. Addison Weley Longman, Inc., London. Sokal, R.R., Rohlf, F.J., 1995. Biometry: the Principles and Practice of Statistics in Biological research. WH Freeman, New York. Tawaga, H., 1997. World-wide distribution of evergreen lucidophyll oak-laurel forest. Tropics 6, 295–316. Whittaker, R.H., Maks, P.L., 1975. Methods of assessing terrestrial productivity. In: Lieth, R.J., Whittaker, R.H. (Eds.), Primary productivity of the biosphere. Springer, New York, pp. 101–131. Whittaker, R.H., Woodwell, G.M., 1968. Dimension and production relations of trees and shrubs in the Brookhaven Forest. New York. J. Ecol. 56, 1–25. Wildpret, W., Martı´ n, V.E., 1997. Laurel forest in the Canary Islands: biodiversity, historical use and conservation. Tropics 6, 371–381. Yamada, T., Yamakura, T., Lee, H.S., 2000. Architectural and allometric differences among Scaphium species are related to microhabitat preferences. Funct. Ecol. 14, 731–737. Zar, J.H., 1984. Biostatistical analysis. Prentice-Hall International Editions, London.
Flora 200 (2005) 264–274 www.elsevier.de/flora
Allometric relationships of different tree species and stand above ground biomass in the Gomera laurel forest (Canary Islands) Jesu´s Ramo´n Aboala,, Jose´ Ramo´n Are´valob, A`ngel Ferna´ndezc A`rea de Ecoloxı´a, Facultade de Bioloxı´a, Universidade de Santiago de Compostela, Campus Sur, 15782, Santiago, A Corun˜a, Spain b Departamento de Ecologı´a, Facultad de Biologı´a, Universidad de La Laguna, 38207, La Laguna, Tenerife, Spain c Parque Nacional de Garajonay, Carretera General del Sur no. 6, San Sebastia´n de La Gomera, 38800, La Gomera, Tenerife, Spain a
Received 13 May 2004; accepted 11 November 2004
Abstract Estimation of net above ground primary productivity in forest ecosystems by non-destructive means requires the development of allometric equations, to allow prediction of above ground biomass from readily measurable variables such as diameter-at-breast-height (DBH). Equations of this type have not been well developed for trees of the Macaronesian laurel forest. In the present study, we characterized trees of five species (Erica arborea, Ilex canariensis, Laurus azorica, Myrica faya and Persea indica) in four types of laurel forest in the Garajonay National Park on Gomera Island in the Canary Islands, with the aim of developing appropriate allometric equations. Among forests, within each species, the slope and elevation (y-axis intersect) of the equations obtained did not vary significantly, so that we were able to pool the data and obtain a single equation for each species. However, considering each species separately, there was significant variation among the slopes and elevations of the equations obtained for each. The difference between DBH-biomass relationships among these species can be attributed to differences in (a) the distribution of biomass among trunk-plus-primary-branches, secondary branches and leaves, and (b) woody tissue density. We applied the new allometric equations to six different forest types in the Garajonay National Park. Above ground biomass ranged from 65,631 to 352,683 kg d.w. ha1. Comparison of these results with those obtained using a previously published allometric model revealed differences of more than 100% for some forests. When we applied the new allometric equations to data from other forests on the island of Tenerife we obtained differences of more than 20% in above ground biomass which ranged from 159,469 to 310,580 kg d.w. ha1. We believe that all previous data corresponding to above ground biomass in Macaronesian laurel forest may contain errors, and propose the new equations to be used in the future, and that other one have to become developed for the remaining species. r 2005 Elsevier GmbH. All rights reserved. Keywords: Canary Islands; Laurel forest; Allometric equations; Biomass area
Abbreviations: a, constant; AGB, above ground biomass; ANCOVA, analysis of covariance; aB , aA , elevations; b, constant; Bd, dry biomass of a given secondary branch; bB , bA , slopes; D, diameter of the branch at 50 cm; DBH, diameter-at-breast-height; DF, degrees of freedom; d.w., dry weight; HLF, hillslope laurel forest; HLFII, immature hillslope laurel forest; L, total length of the branch minus 50 cm; MEF, Myrica/Erica forest; MEFd, disturbed Myrica/Erica forest; MPD, mid-point diameter (mid-point circumference of each trunk section); SMA, standardized major axis regression; V, volume of the distal section of that branch; VLF, valley-bottom laurel forest; VLFII, immature valley-bottom laurel forest Corresponding author. Fax: +34 981 596904. E-mail addresses: [email protected] (J.R. Aboal), [email protected] (J.R. Are´valo), [email protected] (A. Ferna´ndez). 0367-2530/$ - see front matter r 2005 Elsevier GmbH. All rights reserved. doi:10.1016/j.flora.2004.11.001
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Introduction Macaronesian laurel forest, a subtype of the evergreen lucidophyll oak-laurel forests (Tawaga, 1997), is a relic forest, the study of which is important in helping to understand the composition and ecology of Tertiary Mediterranean flora (at the edges of the Tethys Sea in the Late Miocene epoch). This type of forest is now restricted to northern parts of the Canary Islands, Madeira and the Azores (Ceballos and Ortun˜o, 1976; Kunkel, 1987; Santos, 1990). The most important area where this forest type is found is on Gomera Island, most of which was declared a National Park in 1981, and subsequently a World Heritage site (Ferna´ndez, 1990). The area – Garajonay National Park – contains more than 50% of the total remaining area of mature laurel forest in the Canary Islands (Ferna´ndez, 1992). Because of their situation in the arid, subtropical region of the west coast of Africa, and their botanical and physiological characteristics, Macaronesian laurel forests retain certain similarities to tropical mountain forests (Hu¨bl, 1988; Lo¨sch and Fischer, 1994) and some extratropical forests (Meusel, 1965) – mainly Mediterranean sclerophyllous forests and temperate broadleaved evergreen forests (Goodall, 1983). Above ground biomass is of great value for characterizing the composition, structure and function of ecosystems. As pointed out by Ferna´ndez-Palacios et al. (1991), this variable is of value not only for theoretical understanding of energy and element flows within the ecosystem, but also from a more practical point of view, as an indicator of ecological impact. Thus, knowledge of laurel forest above ground biomass may help in understanding the composition, structure and function of Tertiary Mediterranean ecosystems and provide a means of monitoring possible ecological impacts in these protected forests. Non-destructive estimation of above ground biomass (AGB) of trees is generally carried out by means of twodimensional analytical techniques (Whittaker and Maks, 1975), which are based on the relationships between biomass and readily measured biometric variables such as diameter-at-breast-height (DBH). A similar method has previously been used in a study of a Canary Islands laurel forest (Ferna´ndez-Palacios et al., 1991), and the allometric equation obtained (AGB vs. DBH) has been used in a number of posterior studies: Ferna´ndez-Palacios et al. (1991), Ferna´ndez-Palacios et al. (1992), Ferna´ndez-Palacios and Lo´pez (1992), and Morales et al. (1996). Thus, at present all the estimates of above ground biomass in Macaronesian laurel forests are based on the equation proposed by Ferna´ndezPalacios et al. (1991), although they did not take into account differences among species (they grouped data from 10 species), and the model was derived only for trees of up to 20 cm DBH (posterior extrapolations were
265
made for trees of DBH4100 cm). In the present study we chose not to use the equations developed in the previous study (op.cit.) and we aimed: (1) to obtain new allometric equations for estimating tree biomass, (2) to examine whether a single equation can be developed for application to all species, and (3) to calculate the above ground biomass of the major forest types present in Garajonay and to re-examine (with the new allometric equations) above ground biomass of another forests in Tenerife.
Material and methods Study area The Garajonay National Park is located in the high central area (800–1486 m a.s.l.) of Gomera Island, in the western Canary Islands. The park covers an area of 3984 ha (10% of the total surface area of the island). Condensation of the water vapour brought in by trade winds frequently produces cloud banks, which give rise to high relative humidity. There are three types of laurel forest present, each of which differs in structure and composition (Wildpret and Martı´ n, 1997): (i) ‘‘valleybottom laurel forest’’ (forest type VLF) (laurisilva de barranco o valle), which occurs in wet sites such as stream sides and valley bottoms, and is dominated by Persea indica (L.) Spreng and Laurus azorica (Seub.) Franco, (ii) ‘‘Myrica/Erica forest’’ (forest type MEF) (fayal/brezal), which occurs at drier south-facing sites, and is typically dominated by Erica arborea L. and Myrica faya Ait., though with Ilex canariensis Poivet. and L. azorica also present, and (iii) ‘‘hillslope laurel forest’’ (forest type HLF) (laurisilva de ladera), which occurs at sites with intermediate environmental conditions and is characterized by a wider range of tree species, including E. arborea, M. faya, I. canariensis and L. azorica. The sampling areas for these three forest types were Acebin˜os, La Can˜ada de Jorge and Los Noruegos. For the present study we also selected a disturbed Myrica/Erica forest site that was cleared several decades ago, and where E. arborea, I. canariensis and M. faya, as well as a few young individuals of L. azorica were growing (forest type MEFd). This site was on the southern side of the Park, in the area known as Palos Pelados. With the single aim of calculating the above ground biomass, we selected another two immature forests, a hillslope laurel forest (HLFII) and a valley-bottom laurel forest (VLFII). The length of each plot was calculated by multiplying the mean height of the trees within the plot by two; the corresponding values obtained were: VLF ¼ 2400 m2, VLFII ¼ 2400 m2, HLF ¼ 1600 m2, HLFII ¼ 900 m2, MEF ¼ 900 m2 and MEFd ¼ 400 m2.
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Table 1. Number of trees of each species characterized in each of the forest types Species
HLF
MEF
MEFd
I. canariensis L. azorica M. faya E. arborea P. indica
10 7 8 12
10 8 9 9
13
Total
37
36
VLF
20
33 31 29 33 20
36
146
16 12 12 37
Total
similar procedure. Finally, the total dry biomass of trunk plus primary branches was estimated using previously published figures for the density of dry wood: E. arborea 0.576 g cm3, I. canariensis 0.888 g cm3, L. azorica 0.627 g cm3, M. faya 0.745 g cm3 and P. indica 0.448 g cm3 (Na´jera et al., 1959; Peraza and Lo´pez De Roma, 1962). The biomass of secondary branches on each tree was estimated by an indirect procedure, based on an allometric equation of the following form, derived for each species:
See text for an description of each of the forest types.
Bd ¼ a þ bV , In the present study, we characterized trees at each of these four sites (Acebin˜os, La Can˜ada de Jorge, Los Noruegos, Palos Pelados), corresponding to forest types VLF, MEF, HLF and MEFd, respectively. At each site, we selected between 8 and 20 individuals of each species present, as summarized in Table 1. Sampling at each site was stratified on the basis of DBH: the individuals of each species were grouped into 4–10 cm DBH classes and two individuals were selected at random from each class, giving a total of 8–20 individuals of each species for each site. Poorly represented classes were not sampled. The total number of trees selected was 146.
Sampling and analysis Above ground biomass estimation Park regulations meant that trees could not be felled, so AGB was estimated by non-destructive means, in the summer of 1994. Total AGB was estimated as the sum of the estimated dry biomass of (a) trunk and primary branches (except the distal sections, from the point at which the diameter fell below 7 cm) and (b) secondary branches and the most distal sections of trunk and primary branches. The biomass of the trunk and primary branches (except the distal sections) was estimated directly for each tree, as follows. One person climbed the tree, marking the height on the trunk every 2 m (for trees of total height410 m) or 1 m (for trees of total heighto10 m), until reaching the point at which the trunk diameter fell below 7 cm, so that the penultimate section (i.e. the one before the distal section) was typically shorter than the rest. We then measured the mid-point circumference of each section to obtain the mid-point diameter (MPD), which allowed estimation of the volume of that section, assuming it to be a cylinder of diameter MPD (Huber0 s formula in Hustich et al., 1972). The total volume of primary branches (i.e. those inserting directly to the trunk) was measured by a
where Bd is the dry biomass of a given secondary branch, a and b are constants and V is the volume of the distal section of that branch, in turn estimated (assuming that section to be perfectly conical) as V ¼ 1=3pD2 L; where D is the diameter of the branch at 50 cm from its point of insertion and L is the total length of the branch minus 50 cm. In order to obtain this relationship (Bd ¼ a þ bV ) for each species, a single secondary branch was cut from each of a total of 80 trees: 20 I. canariensis from MEF and HLF, 17 E. arborea from MEF, MEFd and HLF, 11 P. indica from VLF, 16 M. faya from MEF, MEFd and HLF, and 16 L. azorica from VLF and HLF. In each case, we recorded D and L. The volume of the proximal section (first 50 cm) was estimated by assuming it to be a cylinder of diameter D. The volume of the distal section was estimated by assuming it to be a perfect cone of base diameter D and length L. The fresh weight of the distal section was obtained before and after removal of leaves. We then cut two slices of 100–200 g of wood from each branch and took two leaf samples each weighing about 100 g. These samples were oven dried at 105 1C to constant weight, allowing estimation of the fresh-to-dry weight ratio for secondary-branch wood and leaves, which in turn allowed estimation of the total dry biomass (Bd) of that secondary branch. For each tree species, we then performed a linear regression of total Bd on distalsection volume as estimated from D and L, giving the allometric relationship Bd ¼ a þ bV for that species. Subsequently, we determined D and L for all secondary branches of each tree characterized, allowing estimation of Bd for each branch and thus total secondary-branch dry biomass for that tree. The weight of the proximal section was estimated using the densities of dry wood; these two values were then summed to give the estimated fresh biomass of that branch. The biomass of the distal sections of the trunk and primary branches was estimated in the same way as that of secondary branches: i.e. an allometric relationship (relating dry biomass to volume as estimated from basal diameter and length) was derived for the distal sections of each species, and this relationship was then used to
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estimate the dry biomass of all sections, from the basal diameter and length.
Statistical analyses For prediction of total above ground biomass of trees from allometric variables, the candidate allometric variables considered were DBH, DBH height and DBH2 height. Normality of the dependent variable (above ground biomass) was confirmed using Lilliefor’s modification of the Kolmogorov-Smirnov test. If this test indicated that normality could not be assumed, the data were subjected to logarithmic transformation. Here we used both the standard regression method and standardized major axis (SMA) slope-fitting techniques. We used the standard regression method because it remains valid when the only aim is to detect interspecific variations and not to calculate regression parameters (Kohyama, 1987; Kohyama and Hotta 1987; Yamada et al., 2000). Standardized major axis slopefitting techniques were considered to be the most appropriate for describing bivariate relationships, as there was variation associated with measurement error and species sampling for both x and y variables; hence, it was inappropriate to minimize sums of squares in the y dimension only (Sokal and Rohlf, 1995). These ‘‘scaling’’ slopes, calculated on log-transformed variables, give the proportional relationship between variables. We compared the slopes and elevation multiples by applying analysis of covariance (ANCOVA) (Zar, 1984) to the straight lines obtained by the standard regression method. Where significant differences were detected, pairwise comparisons were made by Tukey tests.
Results Allometric analysis To estimate the total above ground dry biomass, we generally considered standard regression models in which the predictor was DBH, and models in which both DBH and height were used as predictors. In both cases AGB was subjected to a natural log transformation to normalize its distribution (testing through box-cox transformation). For all tree species and all forest types, the model selected was a double logarithmic model, using DBH as predictor (i.e. models of the type ln AGB ¼ a þ b ln DBH); other models (e.g. polynomial models) gave a worse fit, and were rejected. Models in which the dependent variable included height (a þ DBH height; a þ bDBH2 height; or aDBHb heightc ) gave poor results in all cases.
267
Among-forest-type within-species comparisons of model parameters (slopes and elevations) were carried out by analyses of covariance, considering each forest type separately for each species. We firstly developed the ANCOVA for slopes (ln DBH vs. ln AGB), which revealed no significant differences among forests for each species: E. arborea F 0:05ð1Þ;2;27 ¼ 0:297; I. canariensis F 0:05ð1Þ;2;27 ¼ 0:498; L. azorica F 0:05ð1Þ;2;25 ¼ 0:448; M. faya F 0:05ð1Þ;2;23 ¼ 0:286; the corresponding value for P. indica was not calculated because this species was found in only one of the forests studied. According to Zar (1984) if no significant differences are found among regression slopes of each forest, we must calculate the common regression slope after test for differences among elevations (y-axis intersects); no significant differences were found among forest types for withinspecies elevations (ln DBH vs. ln AGB): E. arborea F 0:05ð1Þ;2;29 ¼ 3:084; I. canariansis F 0:05ð1Þ;2;29 ¼ 0:234; L. azorica F 0:05ð1Þ;2;27 ¼ 2:212; M. faya F 0:05ð1Þ;2;25 ¼ 0:441; in the case of P. indica the analysis could not be carried out for the same reasons as before. In view of the lack of significantly different variations of the parameters among forests, we constructed a standard regression model (ln DBH vs. ln AGB) in which the data for these forests, and for each species, were considered together (as a single data pool). We also employed SMA slope-fitting techniques to the same data pools. The results of both techniques (model parameters and goodness-of-fit statistics) are shown in Fig. 1; the results for each species with both types of model were almost identical, except for P. indica, which showed some differences. All correlation coefficients were highly significant (Po0:001). We then used multiple analyses of variance to compare among-species variation in model parameters (ln DBH vs. ln AGB slopes and elevations) considering all the data for each species separately as a single entity, or pooled without distinguishing among forest types. This ANCOVA revealed significant differences among species, both in slopes (F 0:05ð1Þ;4;136 ¼ 11:326) and elevations (F 0:05ð1Þ;5;140 ¼ 25:423). Subsequent pairwise comparisons by means of post hoc Tukey test for slopes (test H 0 : bB ¼ bA ; (S 2YX )p ¼ 0.038; DFp ¼ 136), revealed significant differences (Po0:05) for all pairs except M. faya and I. canariensis: L. azorica and P. indica, P. indica and M. faya and I. canariensis and E. arborea. The results obtained are summarized in Table 2. In the same way, subsequent pairwise comparisons by post hoc Tukey test for elevations (test H 0 : aB ¼ aA ; (S2YX)p ¼ 0.053; DFp ¼ 136), revealed significant differences (Po0:05) for all pairs except for L. azorica and M. faya and P. indica and E. arborea. The results obtained are summarized in Table 3. We did not find any pairs of species for which there were no significant differences in slopes and elevations;
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MEFd
Ln Dry weight
8 y = 1.8989x- 0.8955 r 2 = 0.97***
6
MEF
VLF
y = 2.0062x- 0.7229 r 2 = 0.97***
6
4
4 y1 = 0.570 + 0.506 y2
y1 = 0.478 + 0.477 y2
2
2 I. canariensis
E. arborea 0
0 1
2
3
4
5
8
1
2
3
4
5
8 y = 2.4392x -2.1484
Ln Dry Weight
HLF
8
r 2 = 0.99***
6
y = 2.1628x-1.3412 r 2 = 0.99***
6 4
4
y1 = 0.570 + 0.506 y2
y1 = 1.783 + 0.202y2 2
2 L. azorica
M. faya 0
0 1
2
3
4
5
8
1
2
3 Ln DBH
4
5
Ln Dry Weight
y = 2.3377x- 2.2932 r 2 = 0.98***
6 4
y1 = 0.570 + 0.506 y2 2 P. indica 0 1
2
3 Ln DBH
4
5
Fig. 1. Results and parameters of the allometric equations used to predict total above ground dry biomass (AGB) (kg d.w.) from DBH (cm) for each of the species considered. Regression method (solid line, y ¼ a þ bx) and standardized major axis (SMA) (broken line, y1 ¼ a þ by2 ) slope-fitting techniques. In all cases the predictive equation was of the form ln AGB ¼ a+b ln DBH. Correlation coefficients and significance levels (***Po0:001) are also shown. Each point represents an individual tree. VLF: ‘‘valleybottom laurel forest’’; MEF: ‘‘Myrica/Erica forest’’; HLF: ‘‘hillslope laurel forest’’, and MEFd: ‘‘disturbed Myrica/Erica forest’’.
therefore we could not create a new data pool using the data from two or more species to calculate a new model. Collective representation of the model for each species is shown in Fig. 2, including the model proposed by Ferna´ndez-Palacios et al. (1991).
Biomass Finally, we applied the new allometric equations to the individual diameters of each of the trees in each forest obtained during the inventory (Fig. 3); the AGB values obtained for each age class are shown in Fig. 4. In the case of Picconia excelsa, we applied the equation of Ferna´ndez et al. (1991), as we did not have enough data
to be able to derive new allometric equations. Likewise, we applied the allometric equation proposed by these authors (op.cit.) to our data – the AGB values obtained are shown in Fig. 4 and Table 4; in almost all cases the AGB values were overestimated by the Ferna´ndez et al. (1991) equation (MEF 73%, VLFII 131%, VLF 185%, HLFII 28%, HLF 123%), except for that corresponding to MEFd, which was underestimated (10%). We applied the new equations, where applicable, to data available from inventories carried out in seven plots in the north of the island of Tenerife (6 – each of 2500 m2 – in the Anaga peninsula and another – of 3390 m2 – in Agua Garcı´ a). Where not applicable, we applied the equation of Ferna´ndez et al. (1991); the results are shown in Table 4. The differences in biomass
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Table 2. Results of the Tukey test, comparing the slopes (bB ¼ bA ) for different pairs of species
269
Fdez. -Palacios et al. (1991)
L.a vs. E.a L.a vs. I.c L.a vs. M.f L.a vs. P.i P.i vs. E.a P.i vs. I.c P.i vs. M.f M.f vs. E.a M.f vs. I.c I.c vs. E.a
Difference (bB bA )
SE
q
Conclusion
0.542 0.435 0.278 0.103 0.439 0.331 0.175 0.264 0.157 0.107
0.060 0.062 0.061 0.062 0.058 0.060 0.060 0.058 0.060 0.058
9.065 7.030 4.524 1.672 7.555 5.508 2.924 4.564 2.613 1.843
Reject Ho Reject Ho Reject Ho Accepted Ho Reject Ho Reject Ho Accepted Ho Reject Ho Accepted Ho Accepted Ho
(S2YX)p ¼ 0.038; DFp ¼ 136; (ranked samples b: E. arborea: 1.899; I. canariensis: 2.006; M. faya: 2.163; P. indica: 2.338 and L. azorica 2.441). SE: standard error, q: obtained value of the q statistic; tabulated value of the q statistic q0;05;136;5 ¼ 3:858:
Table 3. Results of the Tukey test, comparing heights of the slopes (aB ¼ aA ) for the different pairs of species
L.a vs. E.a L.a vs. I.c L.a vs. M.f L.a vs. P.i P.i vs. E.a P.i vs. I.c P.i vs. M.f M.f vs. E.a M.f vs. I.c I.c vs. E.a
SE
q
Conclusion
0.041 0.041 0.042 0.056 0.051 0.052 0.052 0.041 0.041 0.040
7.119 5.199 1.205 4.758 0.582 9.143 6.031 8.360 3.906 12.659
Reject Ho Reject Ho Accept Ho Reject Ho Accept Ho Reject Ho Reject Ho Reject Ho Reject Ho Reject Ho
(S2YX)p ¼ 0.053; DFp ¼ 136. SE: standard error, q: obtained value of the q statistic; value of the q statistic q0;05;136;5 ¼ 3:858:
estimated by the new equations and by that of Ferna´ndez et al. (1991), for the five species to which both methods were applied, are also shown in Table 4.
Discussion Various authors have stated that the most important advantage of two-dimensional analytical techniques for estimating above ground biomass of trees is that the same equation is often valid for all tree species within the ecosystem under consideration (Whittaker and Woodwell, 1968). This has been confirmed for forest types including tropical forest and temperate deciduous woodland (Duvigneaud, 1974), and has been assumed to apply to laurel forests (Ferna´ndez-Palacios et al., 1991).
Ln AGB
8
M. faya
I. canariensis
6
E. arborea 4 P. indica L. azorica 2 2
3
4 Ln DBH
Fig. 2. Plot of the natural logarithm of total above ground dry biomass (kg d.w.) against the natural logarithm of DBH (cm), for each of the tree species considered, with data from all fourforest types. Comparison of the biomass-DBH relations obtained in the present study with that obtained by Ferna´ndez-Palacios et al. (1991). To facilitate the comparison, the original equation of Ferna´ndez-Palacios et al. (1991) (AGB ¼ 0.0551+DBH2.7157) has been converted to double logarithmic form (ln AGB ¼ 2.7157 ln DBH2.8986).
The latter authors studied 10 laurel forest tree species (n ¼ 27) using destructive methods and considered individuals of DBHo20 cm, although only seven of the trees were of DBH410 cm. The AGB–DBH equation obtained in the present study for each species is very similar to the general AGB–DBH equation reported by these authors (Fig. 2), for DBH ranging between 7 and 20 cm (ln DBH ¼ 223). However, for DBH420 cm (ln DBH43), the equation of Ferna´ndezPalacios et al. (1991) lies above all the single species equations. In mature laurel forests, however, the DBH may reach 100 cm or more, and the use of the equation of Ferna´ndez-Palacios et al. (1991) might be expected to give rise to considerable error. The results of the present study suggest that the assumption that the same equation is often valid for all tree species within the ecosystem under consideration, is not valid in laurel forests, because there were significant differences between the allometric equations for all the species pairs. On the other hand, we did not detect significant among-forest-type within-species differences in allometric equations in the present study, so that the species studied show the same allometric relationships (relating DBH and AGB) independently of the type of forest, thereby allowing all the data for one species to be pooled to derive a single allometric equation for each species.
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Fig. 3. Distribution of tree density (all species) in the laurel forests under study, based on diameter at breast height (DBH) classes. Note the differences in the y-axis values in the different graphs.
The difference in the DBH–AGB relationships of these five species can be attributed to differences in (a) woody tissue density, and (b) the distribution of biomass between woody tissue and leaves. As regards the woody tissue density, there is a relationship between the height of the slope and the corresponding density of the wood of each species (Fig. 2), so that the lower the density of the wood, the lower the height of the slope (the lowest wood densities were those of P.indica, 0.448 g cm3 and E.arborea, 0.576 g cm3), and the higher the density (I.canariensis, 0.888 g cm3) the higher the height of the slope. The proposed equations are based on the relationship between volume and weight, as we related DBH to AGB; thus, the DBH gives us an ‘‘idea’’ of the volume of the tree, since DBH is similar to that of the base of a cone. It is obvious that because we were relating volume to weight and there exist large differences in density among the five species (ranging from 0.448 to 0.888 g cm3, i.e. the highest density is almost twice the lowest), the heights of the slopes of the allometric equations were different. However, where the densities of the wood were similar (e.g. in the pairs
M.faya-L.azorica and P.indica-E.arborea) there were no significant differences in the heights of the slopes. As regards the distribution of biomass, the relative proportions in leaves and woody tissue change over time. Thus, all the slopes for the relations between DBH (Eage) and the percentage of the weight accounted for by woody tissue (trunk-plus-primary and secondarybranches) were positive and significant (Po0:001 in all cases). The change in the distribution of biomass differed for each of the species, leading to differences in the slopes for the allometric equation relating DBH and AGB. If the relation between DBH and the percentage of weight made up by woody tissue was always the same for all species, we would obtain parallel lines, ordered only by the density of the woody tissue. These differences in distribution of biomass as either woody tissue or as leaves result from the widely known phenomenon of variability in allocation of net production that occurs with increasing age in trees (Smith and Smith, 2000), i.e., the higher the DBH, the higher the proportion of biomass made up of woody tissue (up to more than 99% in this case); the variability in allocation
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271
Fig. 4. Distribution of tree above ground biomass (dry weight, kg ha1) (all species) in the laurel forests under study, based on diameter at breast height (DBH) classes. The biomass values predicted using the equation of Ferna´ndez-Palacios et al. (1991) are shown as points joined by a line. For the Hillslope Laurel Forest, the value corresponding to the 157–162 cm DBH class is shown as a number above the graph. Note the difference in the y-axis values in the different graphs.
of net production with increasing age varied among all tree species. Having recognized the need to derive allometric equations (relating DBH and AGB) for each species, and the underlying reasons for this, we then turned out attention to the application of these in calculating the AGB for each forest. Application of the new equations to the Garajonay forest data, along with application of the model proposed by Ferna´ndez-Palacios et al. (1991) to the same inventories (Table 4) revealed differences in the estimation of AGB that were sometimes extremely significant (185% overestimation using the latter equation in the case of HLF). Examination of the differences between the two estimates at the level of species (Table 4) and diameter classes (Fig. 4) revealed that the differences are due to a combination of three factors: (a) the already mentioned need to derive an allometric equation for each species; (b) the weight contribution of each species to the total for the plot; and (c) the extrapolation of the equation of Ferna´ndez-Palacios et al. (1991) to DBH420 cm. As regards the need to
derive an allometric equation for each species, we can deduce from Fig. 3 that if the slope corresponding to a species lies above the slope obtained using the model of Ferna´ndez-Palacios et al. (1991), the latter underestimates the values, and if the slope lies below, the latter overestimates the values, and the degree of under- or overestimation is related to the difference in the height of the slopes. Whether the different slopes intersect depends on the DBH; therefore, the degree of under- or overestimation will depend on the size of individual trees in a plot. The weights of I. canariensis are therefore underestimated, and the lower the DBH, the greater the underestimation (i.e. MEFd 48%); the weights of P.indica are overestimated and the higher the DBH, the higher the overestimation (i.e. VLF 197%), mainly due to the presence of individuals of large DBH (Fig. 4). In one case, the size of a single individual was overestimated by more than 285% (P. indica in VLF). For other species, such as L. azorica, consistency between the previous and new estimates occurred because, in almost all the forests, trees of this species were of the
MA 1
Erica Heberdenia Ilex scoparia excelsa canariensis
Ilex Laurus perado azorica
Myrica faya
Persea indica
Picconia Prunus Rhamnus Viburnum Visnea excelsa lusitanica glandulosa tinus mocanera
2752 259326(16)
92 6896 7–21 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
300 9767 7–17 288 16242 7–21 736 37357 7–26 32 3619 10–25 120 7190 8–18 184 7275 7–18 — — — — — — — — — — — — — — — — — — — — —
— — — — — — — — — 80 11165 8–30
344 58652(25) 7–47 124 32169(38) 7–40 284 61844(30) 7–46 108 30417(34) 8–36 100 15909(15) 13–32 56 15802(32) 11–38 283 81086(33) 7–46 289 63306(39) 7–47 750 48965(8) 7–22 — — — — — — 150 169485(174) 7–159 67 11601(30) 9–35
4 279(57) 16–16 4 249(54) 16–16 — — — — — — — — — — — — 236 18831(68) 7–28 — — — — — — 304 328918(197) 7–124 588 255171(164) 7–95 — — — — — —
4 5314 41–41 20 20136 18–57 — — — — — — — — — 8 3934 19–35 — — — — — — — — — — — — 4 56 8–8 — — — — — —
2728 310580(3) 2240 180877(10) 3176 165196(3) 3264 159469(9) 2652 187635(8) 1696 182396(26) 1411 264705(73) 3175 125409(10) 492 352683(185) 1408 327325(131) 906 319172(123) 578 65631(28)
808 60086(46) 7–35 48 3349(41) 7–24 140 11626(55) 7–33 96 11786(69) 12–33 44 6312(89) 12–35 592 51007(49) 7–32 469 27935(25) 7–25 444 125019(138) 8–51 2300 72157(9) 7–15 — — — — — — 138 38548(178) 8–61 344 24339(58) 7–33
216 15756 7–23 488 103418 7–43 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
328 19404(33) 7–21 256 24773(18) 7–26 344 29700(19) 7–28 652 26855(44) 7–15 1124 63060(32) 7–36 792 43312(–34) 7–25 32 2306(29) 7–18 500 72498(6) 9–32 125 4286(48) 7–9 — — — 88 100(13) 7–48 81 37660(60) 7–60 167 29692(4) 8–35
32 3851 12–21 41 1938 7–20
520 56325(11) 7–45 744 45880(2) 7–42 716 40008(1) 7–26 784 26477(7) 7–22 660 20744(1) 7–15 392 19486(2) 7–25 634 50300(3) 7–29 178 3881(14) 7–12 — — — 188 23765(20) 8–58 729 71998(15) 7–61 538 73478(10) 8–33 — — —
76 19855 8–41 580 43564 7–45 — — — 624 9639 7–11 1216 46255 7–29 596 42968 7–27 — — — — — — — — — — — — — — — — — — — — —
36 6144 12–27 40 12783 8–41 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
— — — 136 8018 7–41 20 342 7–9 800 45237 9–26 — — — — — — — — — — — — — — — — — — — — — — — — — — —
24 848 7–13 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — —
(MA: Monte Aguirre, M: Moquinal; AG: Agua Garcı´ a) and 6 in Gomera (Ga: Garajonay). The figure in parenthesis after the value of AGB is the percentage difference in the present estimate and that estimated using the equation of Ferna´ndez-Palacios et al. (1991).
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Apollonias Erica barbujana arborea
J.R. Aboal et al. / Flora 200 (2005) 264–274
n AGB dbh MA 2 n AGB dbh MA 3 n AGB min M1 n AGB dbh M2 n AGB dbh M3 n AGB dbh AG n AGB dbh G MEF n AGB dbh G MEFd n AGB dbh G VLF n AGB dbh G VLFII n AGB dbh G HLF n AGB dbh G HLFII n AGB dbh
Total
272
Table 4. Values of stand density, n (trees ha1), above ground biomass, AGB (kg ha–1d.w.) and minimum and maximum diameter at breast height DBH (cm) for 7 laurel forest plots in Tenerife
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same size as the estimated values, and this changed only where large individuals were found (i.e. VLF). The least amount of residuals generated when using the equation of Ferna´ndez-Palacios et al. (1991) corresponded to this species, which is consistent with the estimates being closest to those obtained by the individual equation. As we have observed, overestimates occurred when extrapolations from the equation of Ferna´ndez-Palacios et al. (1991) were made, so that the larger the trees, the greater the error. However, we did not use particularly large DBH values when constructing the slopes (the maximum DBH values were: 56.0 cm for E. arborea; 49.7 cm for I. canariensis; 39.5 cm for L. azorica; 55.2 cm for M. Faya and 76.9 cm for P. indica), which were within the normal range found for these species, but were not the maximum DBH existing. On some occasions, extrapolations must be made, with the consequent risk of error. However, because we sampled a much wider range of DBH and obtained an almost perfect linear response, the change in the individual slopes should be minimal on including individuals of greater DBH. Lastly, because of the contribution of the weight of each species to the total weight in the plot, under- or overestimates of individual species may be either counterbalanced or biased by the weight of the species relative to the total weight, so that the results obtained using our equations and that of Ferna´ndez-Palacios et al. (1991) are consistent (i.e. MEF, total 10% including 48% de I.canariensis, which is not the predominant species in the plot). Finally, we wish to compare our results with those of previous studies concerning the AGB of Macronesian laurel forests. The results available to date are from: Morales et al. (1996), who estimated the AGB of a forest in Agua-Garcı´ a in the north of Tenerife (the same plot for which values are presented here, but from an inventory carried out in previous years) as 198,460 kg ha1 d.w. for individuals of DBH47 cm; Ferna´ndez-Palacios et al. (1991) for 10 plots in the north of Tenerife (Moquinal) with estimated values of 391 100, 285 900, 307 100, 179 100, 160 500, 170 000, 257 000, 382 000, 252 300 and 165 900 kg ha1 d.w. and Ferna´ndez-Palacios et al. (1992) and Ferna´ndez-Palacios and Lo´pez (1992) for six plots in Moquinal with an estimated value of 296700 kg ha1 d.w. – in both the latter the data included individuals of DBHo7 cm, which did not contribute a lot of biomass to the total (for the two Moquinal plots included in the present study, the total AGB only decreased by 2.1% and 7.3% on omitting individuals of DBHo7 cm). The values shown are similar to those calculated in the present study. The values obtained by the equation of Ferna´ndez-Palacios et al. (1991) for the Agua-Garcı´ a plots were overestimated by 26% relative to our results. Since the species of this forest are almost the same as those we used to calculate the new allometric equations, we consider the new estimate to be more reliable. The
273
overestimation is mostly attributable to M. faya (33% due to the large DBH values and its predominance in the plot) and P. indica (68%); the AGB value for this plot is not high, possibly because it is an immature forest in the process of recovering from felling carried out in the 1950s. As regards the Anaga forest, in the present study almost all the under- or overestimates were low (9% to 16%), although the equation of Ferna´ndez-Palacios et al. (1991) was used to calculate the total biomass of species for which new allometric equations were not derived, so that the differences found only correspond to the five species for which new equations were derived. However, we can see that the DBH values for these forests are much lower than those calculated for Gomera and Agua-Garcı´ a, so that the problem of extrapolation does not exist. Although the final result does not vary greatly, the results for individual species do (differences of 34% to 89%). This indicates that although satisfactory results can be obtained using the equation of Ferna´ndez-Palacios et al. (1991) for DBHo20 cm, because under- and overestimates will counterbalance each other within the total, the biomass distribution obtained with this equation for each individual species will be erroneous. Thus, the previous values referring to Moquinal may be close to the real values and are very similar to those obtained in the present study in terms of each plot, but not in terms of the individual contribution of each species to the total.
Conclusions Separate allometric equations (relating DBH and AGB) should be derived for each tree species studied as there are inappreciable differences among-forest-type within-species. There were no differences in the results obtained using regression and standardized major axis (SMA) slope-fitting techniques. We applied the new allometric equation obtained and also that published by Ferna´ndez-Palacios et al. (1991) to the data corresponding to the Gomera forest and a forest in the north of Tenerife, and found that when the latter expression was applied to individuals of DBH420 m, overestimated values were obtained. We therefore believe that the most accurate data on above ground biomass are those published here. In future studies, allometric equations should be derived for those species for which they have not been developed and a suitable range of DBH should be included in the expressions.
Acknowledgements This project formed part of the Garajonay National Park Ecological Monitoring Programme financed by
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ICONA and directed by Asuncio´n Delgado. Data were collected by Javier Leone´s (who climbed the trees), and by Pedro Marichal, Antonio Niebla and Ellen Fetzer. We thank Dr. Rube´n Retuerto for his advice and Dr. Alejo Carballeira for his help and support.
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