Differences in biomass production and carbon sequestration between highland and lowland stands of Picea abies (L.) H. Karst. and Fagus sylvatica L.

Jagodziński, Andrzej M.; Dyderski, Marcin K.; Horodecki, Paweł

doi:10.1016/j.foreco.2020.118329

Cited by 17 publications

(8 citation statements)

References 53 publications

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“…When both D and H were used as predictors of AGB the effect of D on AGB was conditional on a constant H. Therefore, the parameter of D shows the increase in AGB produced by 1% increase in D while H was constant. For European beech, the scaling exponents were in line with those published in the literature; the scaling exponent of D was 2.15, which was similar to that reported by [33] and very close to the value of 2.20 reported by [36]. The scaling exponent of H (that shows the proportional increase in AGB caused by 1% increase in H, under constant D) was somehow different; a value of 0.69 was derived in this study, whereas [36] reported a value of 0.56 and [33] reported a value of 1.14.…”

Section: Discussionsupporting

confidence: 90%

“…European beech (Fagus sylvatica L.) represents one of the widely distributed tree species across Europe [31], in Romania accounting for a third of the Romanian growing stock [32]. Allometric biomass models for European beech have been developed in numerous studies [33][34][35][36][37][38][39]. In contrast, fewer studies reported allometric models for silver fir (Abies alba Mill.…”

Section: Introductionmentioning

confidence: 99%

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Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Dutcă

Zianis

Petriţan

et al. 2020

Forests

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In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Șinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric biomass model development were also investigated. Developing site-specific allometric biomass models requires new measurements of biomass for a sample of trees from that specific site. Yet, measuring biomass is laborious, time consuming, and requires extensive logistics, especially for very large trees. The allometric biomass models were developed for a wide range of diameters at breast height, D (6–86 cm for European beech and 6–93 cm for silver fir) using a logarithmic transformation approach. Two alternative approaches were applied, i.e., random intercept model (RIM) and a Bayesian model with strong informative priors, to enhance the information of the site-specific sample (of biomass observations) by supplementing with a generic biomass sample. The appropriateness of each model was evaluated based on the aboveground biomass prediction of a 1 ha sample plot in Șinca forest. The results showed that models based on both D and tree height (H) to predict tree aboveground biomass (AGB) were more accurate predictors of AGB and produced plot-level estimates with better precision, than models based on D only. Furthermore, both RIM and Bayesian approach performed similarly well when a small local sample (of seven smallest trees) was used to calibrate the allometric model. Therefore, the generic biomass observations may effectively be combined with a small local sample (of just a few small trees) to calibrate an allometric model to a certain site and to minimize the demand for site-specific biomass measurements. However, special attention should be given to the H-D ratio, since it can affect the allometry and the performance of the reduced local sample approach.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Dutcă

Zianis

Petriţan

et al. 2020

Forests

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“…The difference also showed the level of uncertainty when drying temperature is unknown (for country level). We extracted tree and plot level biomasses from our previous studies for three species: P. sylvestris 57 , L. decidua 14 and F. sylvatica 58 (Table S4). We calculated biomass of tree stem and plot stem biomass across gradients of tree DBH and stand volume, for tree and plot level analyses (Table S5).…”

Section: Discussionmentioning

confidence: 99%

Consequences of different sample drying temperatures for accuracy of biomass inventories in forest ecosystems

Jagodziński

Dyderski

Gęsikiewicz

et al. 2020

Sci Rep

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Biomass estimation is one of the crucial tasks of forest ecology. Drying tree material is a crucial stage of preparing biomass estimation tools. However, at this step researchers use different drying temperatures, but we do not know how this influences accuracy of models. We aimed to assess differences in dry biomass between two drying temperatures (75 °C and 105 °C) in tree biomass components and to provide coefficients allowing for recalculation between the given temperatures. We used a set of 1440 samples from bark, branches, foliage and wood of eight European tree species: Abies alba Mill., Alnus glutinosa (L.) Gaertn., Betula pendula Roth., Fagus sylvatica L., Larix decidua Mill., Picea abies (L.) H. Karst., Pinus sylvestris L. and Quercus robur L. The differences between drying temperatures were 1.67%, 1.76%, 2.20% and 0.96% of sample dry masses of bark, branches, foliage and stem wood, respectively. Tree species influenced these differences. Our study provided coefficients allowing for recalculation of masses between the two temperatures, to unify results from different studies. However, the difference in dry mass between the two temperatures studied is lower than the range of uncertainty of biomass models, thus its influence on results of large-scale biomass assessments is low.

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“…Some authors have also pointed to the dependence of the stand biomass-volume relationship on age or stand development stage (Jalkanen et al 2005;Peichl and Arain 2007;Tobin and Nieuwenhuis 2007;Teobaldelli et al 2009;Jagodziński et al 2017). When age data are not available, as is the case in several NFIs, other variables expressing the development stage can be used as a surrogate of age, such as tree size (Soares and Tomé 2004;Kassa et al 2017;Jagodziński et al 2020). In addition, site conditions can influence the relationship between stand biomass and stand volume (Soares and Tomé 2004).…”

Section: Introductionmentioning

confidence: 99%

Stand-level biomass models for predicting C stock for the main Spanish pine species

et al. 2021

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Background National and international institutions periodically demand information on forest indicators that are used for global reporting. Among other aspects, the carbon accumulated in the biomass of forest species must be reported. For this purpose, one of the main sources of data is the National Forest Inventory (NFI), which together with statistical empirical approaches and updating procedures can even allow annual estimates of the requested indicators. Methods Stand level biomass models, relating the dry weight of the biomass with the stand volume were developed for the five main pine species in the Iberian Peninsula (Pinus sylvestris, Pinus pinea, Pinus halepensis, Pinus nigra and Pinus pinaster). The dependence of the model on aridity and/or mean tree size was explored, as well as the importance of including the stand form factor to correct model bias. Furthermore, the capability of the models to estimate forest carbon stocks, updated for a given year, was also analysed. Results The strong relationship between stand dry weight biomass and stand volume was modulated by the mean tree size, although the effect varied among the five pine species. Site humidity, measured using the Martonne aridity index, increased the biomass for a given volume in the cases of Pinus sylvestris, Pinus halepensis and Pinus nigra. Models that consider both mean tree size and stand form factor were more accurate and less biased than those that do not. The models developed allow carbon stocks in the main Iberian Peninsula pine forests to be estimated at stand level with biases of less than 0.2 Mg∙ha− 1. Conclusions The results of this study reveal the importance of considering variables related with environmental conditions and stand structure when developing stand dry weight biomass models. The described methodology together with the models developed provide a precise tool that can be used for quantifying biomass and carbon stored in the Spanish pine forests in specific years when no field data are available.

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Differences in biomass production and carbon sequestration between highland and lowland stands of Picea abies (L.) H. Karst. and Fagus sylvatica L.

Cited by 17 publications

References 53 publications

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Consequences of different sample drying temperatures for accuracy of biomass inventories in forest ecosystems

Stand-level biomass models for predicting C stock for the main Spanish pine species

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