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Ioan Dutcă
Buckinghamshire New University, Queen Alexandra Rd, High Wycombe HP11 2JZ, UK

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Journal article
Published: 16 June 2021 in Forests
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We investigated the effects of forest management on the carbon (C) dynamics in Romanian forest soils, using two model simulations: CBM-CFS3 and Yasso15. Default parametrization of the models and harmonized litterfall simulated by CBM provided satisfactory results when compared to observed data from National Forest Inventory (NFI). We explored a stratification approach to investigate the improvement of soil C prediction. For stratification on forest types only, the NRMSE (i.e., normalized RMSE of simulated vs. NFI) was approximately 26%, for both models; the NRMSE values reduced to 13% when stratification was done based on climate only. Assuming the continuation of the current forest management practices for a period of 50 years, both models simulated a very small C sink during simulation period (0.05 MgC ha−1 yr−1). Yet, a change towards extensive forest management practices would yield a constant, minor accumulation of soil C, while more intensive practices would yield a constant, minor loss of soil C. For the maximum wood supply scenario (entire volume increment is removed by silvicultural interventions during the simulated period) Yasso15 resulted in larger emissions (−0.3 MgC ha−1 yr−1) than CBM (−0.1 MgC ha−1 yr−1). Under ‘no interventions’ scenario, both models simulated a stable accumulation of C which was, nevertheless, larger in Yasso15 (0.35 MgC ha−1 yr−1) compared to CBM-CSF (0.18 MgC ha−1 yr−1). The simulation of C stock change showed a strong “start-up” effect during the first decade of the simulation, for both models, explained by the difference in litterfall applied to each scenario compared to the spinoff scenario. Stratification at regional scale based on climate and forest types, represented a reasonable spatial stratification, that improved the prediction of soil C stock and stock change.

ACS Style

Viorel Blujdea; Toni Viskari; Liisa Kulmala; George Gârbacea; Ioan Dutcă; Mihaela Miclăuș; Gheorghe Marin; Jari Liski. Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations. Forests 2021, 12, 795 .

AMA Style

Viorel Blujdea, Toni Viskari, Liisa Kulmala, George Gârbacea, Ioan Dutcă, Mihaela Miclăuș, Gheorghe Marin, Jari Liski. Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations. Forests. 2021; 12 (6):795.

Chicago/Turabian Style

Viorel Blujdea; Toni Viskari; Liisa Kulmala; George Gârbacea; Ioan Dutcă; Mihaela Miclăuș; Gheorghe Marin; Jari Liski. 2021. "Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations." Forests 12, no. 6: 795.

Journal article
Published: 26 October 2020 in 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.

ACS Style

Ioan Dutcă; Dimitris Zianis; Ion Cătălin Petrițan; Cosmin Ion Bragă; Gheorghe Ștefan; Jorge Curiel Yuste; Any Mary Petrițan. Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations. Forests 2020, 11, 1136 .

AMA Style

Ioan Dutcă, Dimitris Zianis, Ion Cătălin Petrițan, Cosmin Ion Bragă, Gheorghe Ștefan, Jorge Curiel Yuste, Any Mary Petrițan. Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations. Forests. 2020; 11 (11):1136.

Chicago/Turabian Style

Ioan Dutcă; Dimitris Zianis; Ion Cătălin Petrițan; Cosmin Ion Bragă; Gheorghe Ștefan; Jorge Curiel Yuste; Any Mary Petrițan. 2020. "Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations." Forests 11, no. 11: 1136.

Erratum
Published: 21 September 2020 in Ecological Indicators
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ACS Style

Ioan Dutcă; Richard Mather; Florin Ioraș. Corrigendum to “Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision?” [Environ. Sustain. Indic. (2020) 106553]. Ecological Indicators 2020, 119, 106938 .

AMA Style

Ioan Dutcă, Richard Mather, Florin Ioraș. Corrigendum to “Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision?” [Environ. Sustain. Indic. (2020) 106553]. Ecological Indicators. 2020; 119 ():106938.

Chicago/Turabian Style

Ioan Dutcă; Richard Mather; Florin Ioraș. 2020. "Corrigendum to “Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision?” [Environ. Sustain. Indic. (2020) 106553]." Ecological Indicators 119, no. : 106938.

Journal article
Published: 29 May 2020 in Ecological Indicators
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Developing allometric biomass models is an important process because reliability of forest biomass and carbon estimations largely depend on the accuracy and precision of such models. The effects of tree sampling on tree aboveground biomass (AGB) prediction accuracy and precision are complex and can, therefore, be difficult to quantify. In this paper we use a Monte Carlo simulation to investigate how model prediction accuracy and precision are affected by tree sampling approaches. Because diameter at breast height (D, in cm) is the most common predictor of tree AGB (in kg dry weight), we focused our analysis on the AGB-D relationship. The following sample characteristics were investigated: (i) sample size; (ii) extent of the D-range (difference between the largest and the smallest D value); (iii) position of D-range (characterized by the starting point of D-range); and (iv) the size-distribution (distribution of D) of sample trees. We found that, although the natural variability of AGB-D relationship was a key driver for both prediction accuracy and precision, the above sample characteristics were important for improving prediction accuracy. Although having a negligible effect on precision, both sample size and size-distribution of sample trees, greatly influenced prediction accuracy. We demonstrate that selecting a constant number of trees for each D class (i.e. uniform distribution of the sample trees over the D-range) generally produced models that were more accurate predictors of AGB. The extent and position of D-range, although considerably affecting the goodness of fit and the standard errors of allometric model parameters, had only a marginal effect on AGB prediction accuracy and precision. Furthermore, we showed that R2 was a poor indicator of model prediction accuracy and precision, due to its sensitivity to changes in D-range. These findings inform certain practical recommendations we report for improving the accuracy and precision of biomass prediction.

ACS Style

Ioan Dutcă; Richard Mather; Florin Ioraș. Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision? Ecological Indicators 2020, 117, 106553 .

AMA Style

Ioan Dutcă, Richard Mather, Florin Ioraș. Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision? Ecological Indicators. 2020; 117 ():106553.

Chicago/Turabian Style

Ioan Dutcă; Richard Mather; Florin Ioraș. 2020. "Sampling trees to develop allometric biomass models: How does tree selection affect model prediction accuracy and precision?" Ecological Indicators 117, no. : 106553.

Journal article
Published: 27 March 2020 in Sustainability
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The role of values in climate-related decision-making is a prominent theme of climate communication research. The present study examines whether forest professionals are more driven by values than scientists are, and if this results in value polarization. A questionnaire was designed to elicit and assess the values assigned to expected effects of climate change by forest professionals and scientists working on forests and climate change in Europe. The countries involved covered a north-to-south and west-to-east gradient across Europe, representing a wide range of bio-climatic conditions and a mix of economic–social–political structures. We show that European forest professionals and scientists do not exhibit polarized expectations about the values of specific impacts of climate change on forests in their countries. In fact, few differences between forest professionals and scientists were found. However, there are interesting differences in the expected values of forest professionals with regard to climate change impacts across European countries. In Northern European countries, the aggregated values of the expected effects are more neutral than they are in Southern Europe, where they are more negative. Expectations about impacts on timber production, economic returns, and regulatory ecosystem services are mostly negative, while expectations about biodiversity and energy production are mostly positive.

ACS Style

Johannes Persson; Kristina Blennow; Luísa Gonçalves; Alexander Borys; Ioan Dutcă; Jari Hynynen; Emilia Janeczko; Mariyana Lyubenova; Simon Martel; Jan Merganic; Katarína Merganičová; Mikko Peltoniemi; Michal Petr; Fernando H. Reboredo; Giorgio Vacchiano; Christopher P.O. Reyer. No polarization–Expected Values of Climate Change Impacts among European Forest Professionals and Scientists. Sustainability 2020, 12, 2659 .

AMA Style

Johannes Persson, Kristina Blennow, Luísa Gonçalves, Alexander Borys, Ioan Dutcă, Jari Hynynen, Emilia Janeczko, Mariyana Lyubenova, Simon Martel, Jan Merganic, Katarína Merganičová, Mikko Peltoniemi, Michal Petr, Fernando H. Reboredo, Giorgio Vacchiano, Christopher P.O. Reyer. No polarization–Expected Values of Climate Change Impacts among European Forest Professionals and Scientists. Sustainability. 2020; 12 (7):2659.

Chicago/Turabian Style

Johannes Persson; Kristina Blennow; Luísa Gonçalves; Alexander Borys; Ioan Dutcă; Jari Hynynen; Emilia Janeczko; Mariyana Lyubenova; Simon Martel; Jan Merganic; Katarína Merganičová; Mikko Peltoniemi; Michal Petr; Fernando H. Reboredo; Giorgio Vacchiano; Christopher P.O. Reyer. 2020. "No polarization–Expected Values of Climate Change Impacts among European Forest Professionals and Scientists." Sustainability 12, no. 7: 2659.

Journal article
Published: 14 December 2019 in Sustainability
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In the modern context of the strict protection of large carnivores, the competition for resources between local community dwellers and these animals has become an important challenge for ensuring coexistence—the key for conservation success. To assess the perceptions of this intricate relationship, six local communities from Central Romania, located in areas with high-density brown bear (Ursus arctos L.) population and frequent conflicts, were investigated. A large proportion of the respondents (69%) showed various forms of intolerance (e.g., relocation, punishment, or killing) towards aggressive bears. However, the cognitive evaluation score derived from the level of interaction with bears showed a non-significant (p = 0.470) segregation by tolerance levels, suggesting that not only the tangible costs (direct damage) but rather the psychological costs of fear, danger, or risk are more important drivers of negative attitudes towards bears. Furthermore, the prevalent experienced emotions towards an inoffensive bear (fear, terror, and hate, which represent 73%) underline the general preference for living in “separate worlds”. This requires that bears should avoid humans and their settlements, a goal unlikely to be achieved under the current strict protection regime. Therefore, an alternative strategy that ensures mutual avoidance of the two players may be more appropriate for successful human–bear coexistence.

ACS Style

Petru Tudor Stăncioiu; Ioan Dutcă; Marian Cristian Bălăcescu; Ștefan Vasile Ungurean. Coexistence with Bears in Romania: A Local Community Perspective. Sustainability 2019, 11, 7167 .

AMA Style

Petru Tudor Stăncioiu, Ioan Dutcă, Marian Cristian Bălăcescu, Ștefan Vasile Ungurean. Coexistence with Bears in Romania: A Local Community Perspective. Sustainability. 2019; 11 (24):7167.

Chicago/Turabian Style

Petru Tudor Stăncioiu; Ioan Dutcă; Marian Cristian Bălăcescu; Ștefan Vasile Ungurean. 2019. "Coexistence with Bears in Romania: A Local Community Perspective." Sustainability 11, no. 24: 7167.

Journal article
Published: 04 November 2019 in Forests
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Background and Objectives: It is commonly assumed that allometric biomass models are species-specific and site-specific. However, the magnitude of species and site dependency in these models is not well-known. This study aims to investigate the variation in allometric models (i.e., aboveground biomass predicted by diameter at breast height and tree height) that has originated from the differences between tree species and between sites, thereby contributing to a better understanding of species and site-specificity issue in these models. Materials and Methods: The study is based on two large biomass datasets of 4921 and 5199 trees, from Eurasia and Canada. Using a nested ANOVA model on relative aboveground biomass residuals (with species and site as random effects), the proportion of variance explained by species or site was assessed by means of Variance Partition Coefficient (VPC). Results: The proportion of variance explained by species (VPCspecies = 42.56%, SE = 6.10% for Dataset 1 and VPCspecies = 47.54%, SE = 6.07% for Dataset 2) was larger than that explained by site (VPCsite = 20.08%, SE = 3.35% for Dataset 1 and VPCsite = 8.27%, SE = 1.38% for Dataset 2). The proportion of variance explained by site decreased by 24%–44% and the proportion of variance explained by species changed only slightly, when height is included in the allometric biomass models (i.e., models based on diameter at breast height alone, compared to models based on diameter at breast height and tree height). Conclusions: Allometric biomass models were more species-specific than they were site-specific. Therefore, the species (i.e., differences between species) seems to be a more important driver of variability in allometric models compared to site (i.e., differences between sites). Including height in allometric biomass models helped reduce the dependency of these models, on sites only.

ACS Style

Ioan Dutcă. The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models. Forests 2019, 10, 976 .

AMA Style

Ioan Dutcă. The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models. Forests. 2019; 10 (11):976.

Chicago/Turabian Style

Ioan Dutcă. 2019. "The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models." Forests 10, no. 11: 976.

Journal article
Published: 24 August 2019 in Forestry: An International Journal of Forest Research
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Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy.

ACS Style

I Dutcă; R E McRoberts; E Næsset; V N B Blujdea. A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models. Forestry: An International Journal of Forest Research 2019, 92, 627 -634.

AMA Style

I Dutcă, R E McRoberts, E Næsset, V N B Blujdea. A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models. Forestry: An International Journal of Forest Research. 2019; 92 (5):627-634.

Chicago/Turabian Style

I Dutcă; R E McRoberts; E Næsset; V N B Blujdea. 2019. "A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models." Forestry: An International Journal of Forest Research 92, no. 5: 627-634.

Journal article
Published: 01 September 2018 in Biomass and Bioenergy
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Although it is commonly assumed that biomass allometric models are site specific, evaluations of site-effects are rarely undertaken. In this paper we develop biomass-allometric models to determine site influences. This study is based on data from 240 Norway spruce trees (Picea abies (L.) Karst.), growing in 24 early-growth plantations. A multilevel modelling approach was adopted and intraclass correlation was used to evaluate site effects. Results indicated that biomass allometric models were highly specific to sites and that, depending on the biomass component and the type of predictor adopted, some 33% and 86% of overall model variance could be attributed to forest stand effects. The remaining variance was attributable within stand variability. Stem biomass was the most site-specific biomass component whereas branch biomass was the least influenced by site effects. Diameter at collar height (D) was less site-specific than height (H) in predicting biomass. Using D and H within the same model as distinct predictors, although improving the model fit, increased the model site-specificity. However, when D and H were combined in one predictor expression (i.e. D2H), this reduced model site specificity, despite requiring fewer parameters than other models. This also compensated for undesirable collinearity effects amongst predictor variables. Furthermore, for the sampled diameter range, the site-specificity was mainly driven by biomass allocation pattern (to branches, needles and roots). The considerable between site variability of allometric relationships suggests that consideration of stand effects is essential for the robust prediction of biomass.

ACS Style

Ioan Dutcă; Richard Mather; Viorel N.B. Blujdea; Florin Ioraș; Mănăilă Olari; Ioan Vasile Abrudan. Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.). Biomass and Bioenergy 2018, 116, 8 -17.

AMA Style

Ioan Dutcă, Richard Mather, Viorel N.B. Blujdea, Florin Ioraș, Mănăilă Olari, Ioan Vasile Abrudan. Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.). Biomass and Bioenergy. 2018; 116 ():8-17.

Chicago/Turabian Style

Ioan Dutcă; Richard Mather; Viorel N.B. Blujdea; Florin Ioraș; Mănăilă Olari; Ioan Vasile Abrudan. 2018. "Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)." Biomass and Bioenergy 116, no. : 8-17.

Research article
Published: 02 August 2018 in PLoS ONE
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This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant.

ACS Style

Ioan Dutcă; Petru Tudor Stăncioiu; Ioan Vasile Abrudan; Florin Ioraș. Using clustered data to develop biomass allometric models: The consequences of ignoring the clustered data structure. PLoS ONE 2018, 13, e0200123 .

AMA Style

Ioan Dutcă, Petru Tudor Stăncioiu, Ioan Vasile Abrudan, Florin Ioraș. Using clustered data to develop biomass allometric models: The consequences of ignoring the clustered data structure. PLoS ONE. 2018; 13 (8):e0200123.

Chicago/Turabian Style

Ioan Dutcă; Petru Tudor Stăncioiu; Ioan Vasile Abrudan; Florin Ioraș. 2018. "Using clustered data to develop biomass allometric models: The consequences of ignoring the clustered data structure." PLoS ONE 13, no. 8: e0200123.

Data article
Published: 19 July 2018 in Data in Brief
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Tree biomass data are essential for developing the biomass allometric models that are necessary for estimating carbon stock and for monitoring changes in forest biomass. In this 'data article' biomass records are presented for 240 Norway spruce trees (Picea abies (L.) Karst.). Trees were between 4 and 15 years of age and were sampled from 24 pure plantations located in Eastern Carpathians of Romania. Ten trees were sampled from each plantation using a cluster sampling method. For each tree, diameter at root collar height (D) and tree height (H) are provided as potential predictors for biomass. Oven-dried biomass is also recorded for the following partitions: stem (ST); branches (BR); needles (ND); roots (RT); as well as their combinations representing total aboveground biomass (AGB) and overall tree biomass (TB). Sampled trees were between 0.6 and 10.0 cm in diameter and between 53.0 and 552.0 cm in height. Total tree biomass ranged between 0.019 and 15.53 kg/tree. This dataset is related to the research article entitled "Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)" (Dutcă et al., 2018) [1].

ACS Style

Ioan Dutca. Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania. Data in Brief 2018, 19, 2384 -2392.

AMA Style

Ioan Dutca. Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania. Data in Brief. 2018; 19 ():2384-2392.

Chicago/Turabian Style

Ioan Dutca. 2018. "Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania." Data in Brief 19, no. : 2384-2392.

Journal article
Published: 01 January 2018 in Canadian Journal of Forest Research
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In this paper, we report an investigation of how forest stand mixture may affect biomass allometric relationships in Norway spruce (Picea abies (L.) Karst.). Analysis of aboveground biomass data was conducted for 50 trees: 25 sample trees from a pure Norway spruce stand and 25 from a mixed stand of Norway spruce with European beech (Fagus sylvatica L.). ANCOVA results demonstrated that individual-tree biomass allometry of the pure stand significantly differed from that of the mixed stand. Allometric characteristics depended on the biomass component recorded and the type of biomass predictor used. When predicted by diameter at breast height and (or) height, the total aboveground biomass of mixed-stand trees was significantly less than that for pure-stand trees. This “apparent” lower aboveground biomass was attributed to the lower branch and needle biomass proportions of trees growing in mixed stand. The findings indicate that caution should be exercised when applying biomass allometric models developed from pure stands to predict tree biomass in mixed stands (and vice versa), as such data treatment may introduce significant bias.

ACS Style

Ioan Dutcă; Richard Mather; Florin Ioraş. Tree biomass allometry during the early growth of Norway spruce (Picea abies) varies between pure stands and mixtures with European beech (Fagus sylvatica). Canadian Journal of Forest Research 2018, 48, 77 -84.

AMA Style

Ioan Dutcă, Richard Mather, Florin Ioraş. Tree biomass allometry during the early growth of Norway spruce (Picea abies) varies between pure stands and mixtures with European beech (Fagus sylvatica). Canadian Journal of Forest Research. 2018; 48 (1):77-84.

Chicago/Turabian Style

Ioan Dutcă; Richard Mather; Florin Ioraş. 2018. "Tree biomass allometry during the early growth of Norway spruce (Picea abies) varies between pure stands and mixtures with European beech (Fagus sylvatica)." Canadian Journal of Forest Research 48, no. 1: 77-84.

Journal article
Published: 02 December 2014 in Notulae Botanicae Horti Agrobotanici Cluj-Napoca
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ACS Style

Ioan Dutca; Filofteia Negruţiu; Florin Ioras; Kevin Maher; Viorel N.B. Blujdea; Liviu Alexandru Ciuvăţ. The Influence of Age, Location and Soil Conditions on the Allometry of Young Norway Spruce (Picea abies L. Karst.) Trees. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 2014, 42, 1 .

AMA Style

Ioan Dutca, Filofteia Negruţiu, Florin Ioras, Kevin Maher, Viorel N.B. Blujdea, Liviu Alexandru Ciuvăţ. The Influence of Age, Location and Soil Conditions on the Allometry of Young Norway Spruce (Picea abies L. Karst.) Trees. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2014; 42 (2):1.

Chicago/Turabian Style

Ioan Dutca; Filofteia Negruţiu; Florin Ioras; Kevin Maher; Viorel N.B. Blujdea; Liviu Alexandru Ciuvăţ. 2014. "The Influence of Age, Location and Soil Conditions on the Allometry of Young Norway Spruce (Picea abies L. Karst.) Trees." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 42, no. 2: 1.

Journal article
Published: 06 December 2013 in Notulae Botanicae Horti Agrobotanici Cluj-Napoca
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The aim of the paper was to develop biomass equations for young black locust trees from plantations and coppices established in South-West Romania. A destructive method was used to develop allometric biomass equations and to assess the carbon content of the individual tree and its biomass components. 418 black locust young trees (1-4 years old) from 27 plots established in plantations and coppices growing on sandy soils in Dolj and Olt counties were sampled. Simple linear regression models were developed for biomass estimation. The results shown that root collar diameter was the most accurate biomass predictor, whilst intercept and slope values were similar to those identified in other recent studies. The specific carbon content (mean values) was 45% for roots and 48% for leaves, similar to the values provided by Intergovernmental Panel for Climate Change.

ACS Style

Alexandru Liviu Ciuvat; Ioan Vasile Abrudan; Viorel Blujdea; Ioan Dutca; Ilie Silvestru Nuta; Elena Edu. Biomass Equations and Carbon Content of Young Black Locust (Robinia pseudoacacia L.) Trees from Plantations and Coppices on Sandy Soils in South-Western Romanian Plain. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 2013, 41, 590 -592.

AMA Style

Alexandru Liviu Ciuvat, Ioan Vasile Abrudan, Viorel Blujdea, Ioan Dutca, Ilie Silvestru Nuta, Elena Edu. Biomass Equations and Carbon Content of Young Black Locust (Robinia pseudoacacia L.) Trees from Plantations and Coppices on Sandy Soils in South-Western Romanian Plain. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2013; 41 (2):590-592.

Chicago/Turabian Style

Alexandru Liviu Ciuvat; Ioan Vasile Abrudan; Viorel Blujdea; Ioan Dutca; Ilie Silvestru Nuta; Elena Edu. 2013. "Biomass Equations and Carbon Content of Young Black Locust (Robinia pseudoacacia L.) Trees from Plantations and Coppices on Sandy Soils in South-Western Romanian Plain." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 41, no. 2: 590-592.

Journal article
Published: 15 January 2012 in Forest Ecology and Management
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The possibility of estimating young trees biomass is rather limited because forest yield tables are constructed starting from higher thresholds of proxy, such as diameter or height, and lack of availability of allometric equations. The aim of this study is to provide species-specific and general biomass equations for young plants often used for plantations on marginal lands in southern and eastern Romania. Power functions based on log-transformed data were applied to seven tree species (Robinia pseudoacacia (L.), Quercus sp., Populus alba (L.), Gleditsia triacanthos (L.), Elaeagnus angustifolia (L.), Salix alba (L.) and Fraxinus excelsior (L.)), one shrub (Rosa canina L.) and to the overall dataset with all the species pooled together (406 plants), using the diameter at collar height (Dch), diameter at breast height (Dbh) or height (H) as single predictor. Dch resulted as being the best predictor for each compartment for very young trees, but H also proved to be a promising individual predictor both for species-specific or general equations. Dbh could satisfactorily predict the aggregated aboveground biomass, but generally could not adequately estimate all biomass components (i.e., belowground biomass or foliage). The goodness of regression was lowest for the foliage and highest for the stem and aggregated biomass compartments. The scaling coefficient (a) and exponent (b) of power functions were influenced both by species-specific factors and by the growth stage of the trees. Parameters to be used for a general equation were also provided for each biomass compartment and predictor. Using Dch as independent variable, we observed that the value of the general scaling exponent estimated to predict total aboveground biomass was the same as the value (2.66) predicted by the WBE functional model. Using Dbh as predictor for the general allometric equation, the resulting value of b (2.36) coincided with the values empirically estimated by previous studies. Equations were finally compared against three independent datasets. Parameters provided by the general equation highlighted permanent overestimation for aggregated biomass compartments and underestimation for branches or roots, but always fell into the range provided by the upper and lower values estimated for a and b. This suggests that, at least for young trees, our equation could be applied without regard for local fertility conditions or plantation management.

ACS Style

V.N.B. Blujdea; R. Pilli; Ioan Dutca; L. Ciuvat; I.V. Abrudan. Allometric biomass equations for young broadleaved trees in plantations in Romania. Forest Ecology and Management 2012, 264, 172 -184.

AMA Style

V.N.B. Blujdea, R. Pilli, Ioan Dutca, L. Ciuvat, I.V. Abrudan. Allometric biomass equations for young broadleaved trees in plantations in Romania. Forest Ecology and Management. 2012; 264 ():172-184.

Chicago/Turabian Style

V.N.B. Blujdea; R. Pilli; Ioan Dutca; L. Ciuvat; I.V. Abrudan. 2012. "Allometric biomass equations for young broadleaved trees in plantations in Romania." Forest Ecology and Management 264, no. : 172-184.

Journal article
Published: 01 March 2010 in International Forestry Review
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ACS Style

P.T Stancioiu; Ioan Vasile Abrudan; I Dutca. The Natura 2000 ecological network and forests in Romania: implications on management and administration. International Forestry Review 2010, 12, 106 -113.

AMA Style

P.T Stancioiu, Ioan Vasile Abrudan, I Dutca. The Natura 2000 ecological network and forests in Romania: implications on management and administration. International Forestry Review. 2010; 12 (1):106-113.

Chicago/Turabian Style

P.T Stancioiu; Ioan Vasile Abrudan; I Dutca. 2010. "The Natura 2000 ecological network and forests in Romania: implications on management and administration." International Forestry Review 12, no. 1: 106-113.