The stump then remains in the plantation, while the shoot biomass is removed. Root nodules were treated separately. The corresponding measurement results were later added to the results of the fine root pool for data evaluation. Average aboveground biomass stock per compartment and hectare was determined by multiplying the average dry weight per plant with the average plant densities of the plantations Table 1. All plant parts shoots, stump, coarse, and fine roots were measured independently. For calculation of the belowground biomass, a unit soil area per plant according to Bengough et al.
The dimensions of this rectangular-shaped area were defined as half of the distance to the next tree in the tree row and to the next tree in the neighboring tree row. Based on the regular planting pattern within the plantations, it was assumed that the soil below each unit soil area contained a total root length equal to the mean root length per plant.
Many of the roots within the minimum area may belong to neighboring plants, but, similarly, an equal number of roots from the plant may have extended outside the area. For each sampled tree, the root biomass in the unit soil area was calculated and then multiplied with the plant density to achieve the root biomass for the entire plantation. Average annual shoot growth increments were calculated by dividing the shoot biomass by the corresponding plant age. The summarized average dry matter production of all woody plant parts was calculated by summarizing the shoot, stump, coarse root, and fine root biomass and dividing the result by the corresponding plant age.
The data sets were joined to form a pseudo-chronosequence from a tree age of one year up to an age of twelve years. GNU R [ 32 ] was used for the statistical exploration and plotting of the data sets. The data were tested for significant differences between the different plantations with the nonparametric Mann-Whitney U-test [ 33 ]. Biomass accumulation in the first two years of growth was seen to be rapid in the R. The results showed a distinct increase in the biomass of each plant compartment with plant age Tables 2 and 3. Average stocks per hectare ranged for shoot biomass from 0.
While the biomass stocks for stump were 0.
The corresponding total C stocks in the biomass were The measured average C contents in the biomass pools were Differences in absolute biomass for each compartment and stand age were found to be significant for shoot, stump, coarse, and fine roots with higher values in older stands. Only for the coarse root biomass between the two-and the twelve-year-old plants, a slightly lower significance level of was calculated. The overall annual shoot growth increment was seen to be increasing in the first years starting at 0. The increase was significant comparing the one-, two- and twelve-year-old stand ; Figure 3 , indicating a general higher biomass productivity in older stands.
Coarse root growth increments did not show significant differences between stand ages. The fine root growth increments decreased comparing the one- and two-year-old stands with the twelve years old stand with no significant difference between the one- and the two-year-old plantation. The annual stump growth increments were significantly lower in the one-year-old stand compared to the two-year-old stand as well as compared to the twelve-year-old stand , but no significant difference was observed between two and twelve years.
Comparing the different aged plants, the relative allocation of the biomass compartments is seen to change Figure 4 , Table 2. The ratio of shoot aboveground biomass to root belowground biomass for the seedlings is 3. This allocation pattern changes between the one-year and the two-year-old plants, and then more biomass is allocated to the aboveground biomass than to the belowground biomass slope.
Total N stocks in the woody biomass amounted to 0. For the calculation the measured average N contents of 1. The shoot compartment represents yield biomass and therefore the direct economical value of an energy plantation. The obtained results for the biomass productivity of R. Furthermore, they reported average biomass accumulations ranging from 3. Even higher annual growth increments of up to 9.
Growth data on R. Remarkably, the measured growth increments of R. For the Helmstedt study site biomass accumulations between 2. The study results suggest that at least in the Lusatian region R. This is especially true for the harsh growth conditions on marginal reclamation sites. The proportion of biomass allocated belowground increased considerably within the early growth years Figure 4.
This allocation pattern reflects the growth conditions in the seed bed and might be influenced by a general loss of root biomass caused by replanting the seedlings from the seed bed into the plantation. Therefore, the results of the seedlings may not reflect an undisturbed growth of R. In the subsequent early growing seasons, the plants seem to invest a lot in the expansion of their root systems; the aboveground plant parts become more and more dominant and at the age of twelve, the distribution of the biomass has changed. Figure 5 indicates that equilibrium appears to have been reached between ages 2 and 12 slight gradient between two and twelve years meaning allometry has become constant.
Such a distribution of biomass allocated aboveground to that belowground is frequently found in mature forests, whereas the reported ratios vary considerably [ 38 , 39 ]. The observed change in the shoot: Furthermore, Boring and Swank [ 41 ] used allometric functions to estimate large lateral root biomass. These differences in approach might have contributed to lower reported shares of total root biomass by Boring and Swank [ 41 ], especially for the older stands.
However, studies on the C allocation patterns of R. For poplar and willow more comprehensive studies have been conducted. Accordingly, Coleman et al. The results, however, may not be directly comparable with those reported in this study. Fortunately, compared to other sources of error in forest C accounting [ 33 ], redressing accuracies in AGB-C conversion factors or wood C fractions is relatively tractable through a comprehensive synthesis of existing literature.
However to our knowledge no such effort has been made to date.
In addition to accounting for interspecific variation, recent studies have also pointed to a critical methodological consideration when deriving wood C fractions through elemental analysis. First identified by Lamlom and Savidge [ 1 ], studies have shown that the traditional method of oven-drying wood prior to elemental analysis significantly underestimates observed wood C content.
For example, in 59 tropical angiosperm species we found oven drying wood leads to underestimates in wood C content of 2.
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Similarly, oven-drying samples has been found to result in 2. Capturing the contribution of C vol to total wood C has primarily been done by comparing C content found in freeze-dried or desiccated wood samples vs. Although only a small number of studies have approximated C vol , because new data is quickly being amassed, it is important to review and highlight the contribution of C vol to total wood C content.
In doing so, we aim to provide synthesis of data that can then be easily integrated into estimates of forest C stocks and fluxes in forest systems generally. Additional studies were then identified in the reference sections of papers found in the databases. We included papers that were published or in press as of April 1, To ensure that only reliable and comparable data was used, studies incorporated into our analyses: See also discussion on within-stem variation below ; and 3 explicitly described field- and lab methodologies.
In cases where a single publication had two or more wood C records for the same species [ 35 ] we calculated the average value for use in our analysis. When conducting our search, we also found a small number of studies provided wood C data taken from different trunk heights. Here we chose to report data taken from 1. In nearly all cases data was taken directly from tables, with two exceptions: Temperate and boreal species were combined under one classification due to boreal records being found strictly in general analyses of North American trees [ 1 ] or Scandinavian studies that sampled south of the boreal zone [ 40 ].
In addition to reviewing published estimates of stem wood C content, we compiled data from studies presenting tissue-specific C content. In addition to the criteria noted above, we considered only studies that presented data on two or more of the following tissue types: Some studies provide analyses of additional tree tissues and wood anatomical features, but insufficient data were reported to support a cross-species analysis. All statistical analyses were conducted using R v.
Our first analysis step was to evaluate variation in species wood C content as a function of biome and species type. We also found uneven sample sizes for records of C vol , therefore we conducted the same least squares means calculations and analysis of variance tests on C vol data. This was done using a one-sided t test that compared mean C vol values against a population with a mean of 0. As in the case of stem wood, we compiled data from studies presenting values for C content of other plant tissues, in all cases using data presented in tables or text.
Where multiple tissue-specific values were presented within a given study, we computed an average across all values presented in table form. Where multiple studies presented values for the same species and tissue type we computed a simple unweighted mean across studies using the subset of studies presenting C content values across multiple tissue types. We also tested for non-linearity of these relationships on the basis of a second-order polynomial term in a least squares regression in which stem wood was considered the independent variable.
International Journal of Forestry Research
To test for deviations of the relationship from a linear 1: Differences in tissue-stem C relationships between conifers and angiosperms were also evaluated using analysis of covariance in which C content of a given tissue type was the dependent variable, and stem wood C content and tree type were independent variables; an interaction term was also included in the model to test for heterogeneity of slopes.
We found a total of 31 published studies reporting species-specific C content data for stem wood, representing species-specific C records Table 1 , see also [ 44 ]. Tropical angiosperm species were the most-well represented group with species-specific records found from seven published studies Table 2 , while tropical conifers had the poorest representation with only one species-specific record for Pinus caribaea available Table 2.
In total, angiosperms were better represented compared to conifer species, with vs. Our analysis showed that across the whole dataset, conifer species exhibited mean wood C content Tropical angiosperms maintained the lowest wood C fractions with an average of IPCC values only provided a slight overestimate 0. We found only 70 species-specific records for C vol , owing to three studies [ 1 , 2 , 3 ]. When grouped by biome and type, tropical species exhibited the highest mean C vol 2. In analyses of tissue-specific C content values, all tissues with the exception of leaves showed statistically significant linear relationships with stem wood C content Figure 4 ; in no case was a significant non-linear trend detected.
Considering pooled data sets angiosperms and conifers , all of the standardized major regressions did not differ significantly from a 1: A number of relationships are remarkably tight: In spite of this, there is some evidence for systematic differences in these relationships between angiosperms and conifers. The cases of heterogeneity of slopes are driven entirely by a single outlying species Pinus massoniana , for which very high stem C is reported [ 63 ]. In all cases showing differences in intercept value, the pattern is consistently of higher C content values for a given tissue in conifers than in angiosperms, given the observed stem C value.
Our review of existing literature yielded a total of species-specific stem wood C fractions, owing to 31 peer-reviewed publications; 16 of these presented tissue-specific C fractions among 34 tree species Table 1. For stem wood values, tropical angiosperms were the best represented group with species-specific records found, while only one record was found for a tropical conifer species Table 2.
We also found significant variation in wood C content across biomes, and between conifers and angiosperms Table 3. Our analysis is consistent with previous literature [ 1 , 3 ] in finding that conifers have higher wood C content than angiosperms, a trend that was consistent when all biomes were considered individually Table 2 , Figure 1. C vol averaged 2. Analyses of tissue-specific wood C values indicate that stem wood C provides a surprisingly good direct approximation for C content in other tissues Figure 4 , particularly those tissues that represent the most important biomass fractions in large trees after stem wood namely branches and coarse roots.
This result suggests that in spite of tissue-specific functional demands, there are important constraints on genetic determination of the key chemical traits of woody tissues such as lignin-cellulose ratio and non-structural carbohydrate content that determine C content. Although the pooled relationships between stem wood C and other tissues did not differ from a 1: In each instance, conifers show higher than expected tissue-specific C content than do angiosperms, at a given value of stem wood C content Figure 4.
Likely explanations for this pattern are a higher relative degree of lignification of tissues in conifers [ 64 ], differences in conifer vs. One important consideration not addressed quantitatively in this review is differences in wood C content within stems, among different wood types: Heartwood is expected to show high C content due to chemical transformations occurring during formation, including deposition of phenolic compounds and reductions in starch and other non-structural carbon compounds [ 38 ].
Thus, while heartwood may have appreciably higher C content then sapwood, this appears to be strongly taxon-specific, with by far the largest differences reported for pines, and the lowest differences generally reported for angiosperms [see also 37]. Moreover, data from Lamlom and Savidge [ 1 ] suggests the trend of increased wood C in heartwood vs.
Instead, in Sequoiadendron giganteum changes in wood C from pith to bark were non-monotonic [ 1 ]. Since studies quantifying chemical changes from pith to bark tend to overlook this transition zone [ 68 ], we suggest a careful evaluation of the expected pattern that wood C decreases linearly from pith i. Extractives deposited in heartwood may commonly include volatile C constituents, and thus analyses that include the volatile C fraction are particularly important for this question. Along these lines, Lamlom and Savidge [ 1 ] report sapwood C values slightly higher than heartwood values for conventionally dried samples of Thuja occidentalis , but the reverse pattern for desiccated wood samples prepared to retain volatile C.
Another important confounding factor we do not address is differences between juvenile wood and mature wood. Predictable changes in wood properties are often assumed to occur between juvenile and mature wood, with much of the evidence for these patterns coming from commercially viable North American conifer species [reviewed by 68]. With respect to wood C, juvenile wood generally has a higher lignin: However, here we also caution against generalizations, as expected chemical differences between juvenile and mature wood have tended to be determined based on categorical comparisons that overlook the relatively large transition zone between pith and bark [ 68 ].
Lastly, an additional source of within-stem variation in wood chemistry that has received little attention is the effect of reaction wood compression wood in conifers and tension wood in angiosperms. Development of reaction wood is expected to have large effects on wood chemistry [ 69 ], but we are unaware of data on C content in relation to reaction wood formation.
Recent studies have shown it is technically tractable to incorporate species-specific C fractions into forest C accounting when detailed inventories are available [ 2 , 70 ]. Incorporation of species-specific wood C data may be also particularly challenging, given that recent progress in estimating forest AGB relies heavily on remotely sensed data [ 73 , 74 ]. Such technologies may be able to discriminate species in temperate forests [ 75 ], but are likely to perform only limited species- or tree functional type discrimination in diverse tropical forests [ 76 ]. However, examining the magnitude of this error with forest inventory data similar to [ 2 ] would be needed to confirm this.
However, given the large consistent differences between conifers and angiosperms, and availability of wood C data for both groups in all three provenances defined here Table 2 , there appears no reason to continue use of generalized global wood C values. Consistent with previous studies [ 1 , 2 , 3 ], our analysis indicates that C vol is a non-negligible component of total wood C content.
Overlooking C vol in analysis of woody tissues underestimates total wood C content by 1. Biomass stocks are then converted to C stocks by multiplying the oven-dried biomass i. Accurate C fractions determined from wood samples should represent both the volatile- and non-volatile C mass as a percentage of oven-dried biomass. Therefore, to correct for the effects of differences in drying treatments and to account for the contribution of C vol it is important to account for the mass loss associated with loss of volatile constituents during the drying process.
Specifically, we suggest for the purposes of estimating forest C stocks and fluxes, wood C content should be calculated as:. This proposed C conv calculation has been used in only two studies to date [ 2 , 34 ], both of which only analyze stem wood. We reiterate our suggestion that if volatile C is to be included in forest carbon assessments, this should be done on the basis of the C conv parameter described above to correctly express total live C in tree tissues as a proportion of conventionally determined measures of biomass.
In the absence of additional comparative studies, data from our tropical comparative study [ 2 ] may be used to derive a function to approximate C conv on the basis of C content determined from conventionally dried samples C heat:. Although our review found more than species-specific wood C records Table 1 , Figure 1 , there is still clearly a need to accumulate more species-specific wood chemical information.
Similarly, in Hieronyma alchorneoides plantations, planted trees made up Of 3, individuals sampled, Of 97 different species found, 92 were identified to species, 1 to genus, and 4 species to morphotype. Tree plantations were separated from secondary forest plots along Axis 2 of the ordination, whereas plots near to primary forest were separated from those far from primary forest along Axis 1 Figure 2. NMDS ordination plot of naturally regenerating woody plants in V. Each circle represents a different forest plot and circle size is scaled to distance from primary forest larger means farther from PF.
The distance from primary forest vector is shown by the arrow. For full species names, see Table S2. Polygon connects secondary forest plots for clarity. Axis 2 represents a shift from understory species dispersed by small birds or bats e. Axis 1 represents a shift from long-lived pioneers and shade-tolerant species near primary forest e. Forest type but not distance from primary forest was included as an explanatory variable in the best model for abundance of understory species Table S3.
Abundance of understory species was significantly higher in secondary forests Abundance of canopy species was not affected by forest type or distance from primary forest Table S3. Average canopy species abundance was Abundance of different ecological categories of woody plants in different forest types. These categories were not significantly related to distance to primary forest Table S2.
Forest types are secondary forest SF , H. Twenty-five species of those identified were short-lived pioneers Significantly more short-lived pioneers were found in secondary forests Distance from primary forest but not forest type was included in both best models for abundance of long-lived pioneers and shade-tolerant species Table S3. Relationship between distance to primary forest and abundance of different ecological categories of woody plants. None of these variables were affected by forest type Table S2.
Forest types are secondary forest open symbols , H. Variables which were log-transformed for analysis are shown with a nonlinear trendline. Ten species were wind-dispersed 4. Wind-dispersal abundance was not related to forest type or distance from primary forest Table S3. Both categories were at least twice as abundant in secondary forests than in both types of tree plantations Figure 3. Mean rarefied richness was not affected by forest type and was Across all forest types, mean species density was The interaction between forest type and distance was not significant in this model or any other variable tested.
Individual-based species accumulation curves showed slightly slower species accumulation in H. Diversity of naturally regenerating woody plants in tree plantations and secondary forests. There was no significant difference between forest types: Species composition of natural regeneration in tree plantations was different from secondary forests, and we identified ecological groups associated with this difference.
Secondary forests had substantially more short-lived pioneers, understory species, and bat-dispersed species than tree plantations. However, secondary forests and tree plantations had similar abundances of mid- to late-successional categories long-lived pioneers, shade-tolerant, bird-dispersed, and mammal-dispersed.
Since these tree plantation sites had a shorter period of undisturbed regeneration and lower overall stem density than secondary forest, it was difficult to determine whether recruitment of early-successional species was suppressed or whether recruitment of mid- to late-successional species was enhanced. Regardless, our results suggest that tree plantations may catalyze succession of species composition in areas of extended land use and habitat fragmentation. We found substantially fewer understory species in tree plantations than in secondary forest, a group made up mostly of shrubs and treelets in the Melastomataceae, Piperaceae, and Rubiaceae families.
Lower light availability in tree plantations compared with pastures may have inhibited germination and growth of many shade-intolerant understory species. Forest type effects on species composition may also be attributable to habitat preferences of seed dispersers. The most common bat-dispersed plants in our sites were pioneer species Cecropia obtusifolia, Piper colonense, Piper friedrichsthallii , and Senna papillosa , all of which were more abundant in secondary forests. Tree plantations had similar abundances of a mid-successional category long-lived pioneers as secondary forests.
Our study does not suggest that tree plantations substantially enhance recovery of mature forest species during the first two decades of succession. Guild categories in our study are coarse distinctions based on subjective assessments by ecologists. To gain a more complete understanding of successional stages of these forests, an objective classification based on habitat preferences or functional traits would be useful. We found that rarefied species richness of woody plants was similar in tree plantations grown for carbon sequestration and secondary forests.
However, tree plantations in our study had a more intense management e. Given the landscape and management context, we suspect that in our sites, tree plantations could have enhanced diversity of seed rain, but that diversity of recruitment did not exceed secondary forest perhaps because understory clearings delayed the period of natural regeneration. Our findings show that single-species tree plantations with native species and moderate management practices can still support levels of diversity comparable to secondary forests.
Careful selection of species for tree plantations could enhance the conservation value of forest planted for carbon sequestration.
Why Be a Shrub? A Basic Model and Hypotheses for the Adaptive Values of a Common Growth Form
As distance from primary forest increased, species richness declined and species composition shifted. Abundances of bird- and mammal-dispersed species, only mammal-dispersed species, shade-tolerant species, and long-lived pioneers declined as distance to primary forest increased. As noted previously, distance from primary forest in our study is correlated with a decline in forest cover of all forest types.
Seed sources for sites that were closer to primary forest were probably more diverse and composed of later successional species than for sites far from primary forest. The interaction between forest type and distance from primary forest was not significant for any variables tested.
Why Be a Shrub? A Basic Model and Hypotheses for the Adaptive Values of a Common Growth Form
We may have lacked the statistical power to identify the interaction. Contrary to our expectations, tree plantations may have been affected more by amount of surrounding forest cover than secondary forests.
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Large frugivorous bats, which appear to be dispersing more seeds in our secondary forests sites than tree plantations, can disperse seeds over distances of several kilometers and in fragmented landscapes in the tropics Corlett, However, if this finding is supported by further evidence, it may suggest that tree plantations provide larger conservation benefits in landscapes with less forest fragmentation.
Differences in species composition between tree plantations and secondary forests may have implications for both carbon sequestration and successional trajectories. Fewer early-successional species in tree plantations than in secondary forests may result in greater rates of carbon sequestration in tree plantations. Also, these compositional differences demonstrate that succession in secondary forest is delayed compared with tree plantations. And the fact that tree plantations had lower canopy openness than secondary forests suggests that, in the coming years, light-demanding species are more likely to be inhibited in tree plantations than in secondary forests.
However, long-term research of tree plantations is needed since the majority of studies have been of tree plantations younger than 20 years old. It remains unknown if differences in species composition between tree plantations and secondary forest are persistent and whether the legacy of the planted trees inhibits successional dynamics at later stages. Land managers interested in reforestation of agricultural land in Costa Rica and across the tropics often choose between allowing natural regeneration and planting tree plantations.
Public and private organizations directing carbon sequestration projects also makes decisions regarding reforestation strategy. Our results demonstrate that tree plantations may represent a slightly more advanced succession stage than secondary forest, and therefore greater conservation value at this forest age. However, it should be noted that these plantations used native species and had a light management.