Biogeochemical Modelling vs. Tree-Ring Measurements - Comparison of Growth Dynamic Estimates at Two Distinct Oak Forests in Croatia

Sever, Maša Zorana Ostrogović; Paladinić, Elvis; Barcza, Zoltán; Hidy, Dóra; Kern, Anikó; Anić, Mislav; Marjanović, Hrvoje

doi:10.15177/seefor.17-17

Cited by 5 publications

(4 citation statements)

References 37 publications

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“…The postponed response in plants is often explained by the presence of carbon reserve pools in the form of non-structural carbohydrates (NSCs). This mechanism has evolved to help trees to cope with adverse effects, such as climate extremes and dampens the visible signal in trees growth [28][29][30][31]. Nevertheless, over a longer time period, a multi-year convergence of these two independent estimates has been observed [19,22,32,33].In this paper, we provide a comprehensive overview of the measurements of CO 2 fluxes and biometric measurements that were conducted in a young, managed forest of pedunculate oak during the period from 2008 to 2017.…”

mentioning

confidence: 99%

Eddy Covariance vs. Biometric Based Estimates of Net Primary Productivity of Pedunculate Oak (Quercus robur L.) Forest in Croatia during Ten Years

Anić

Sever

Alberti

et al. 2018

Forests

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We analysed 10 years (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) of continuous eddy covariance (EC) CO 2 flux measurements of net ecosystem exchange (NEE) in a young pedunculate oak forest in Croatia. Measured NEE was gap-filled and partitioned into gross primary productivity (GPP) and ecosystem reparation (R ECO ) using the online tool by Max Planck Institute for Biogeochemistry in Jena, Germany. Annual NEE, GPP, and R ECO were correlated with main environmental drivers. Net primary productivity was estimated from EC (NPP EC ), as a sum of −NEE and R h obtained using a constant R h :R ECO ratio, and from independent periodic biometric measurements (NPP BM ). For comparing the NPP at the seasonal level, we propose a simple model that aimed at accounting for late-summer and autumn carbon storage in the non-structural carbohydrate pool. Over the study period, Jastrebarsko forest acted as a carbon sink, with an average (±std. dev.) annual NEE of −319 (±94) gC m −2 year −1 , GPP of 1594 (±109) gC m −2 year −1 , and R ECO of 1275 (±94) gC m −2 year −1 . Annual NEE showed high inter-annual variability and poor correlation with annual average global radiation, air temperature, and total precipitation, but significant (R 2 = 0.501, p = 0.02) correlation with the change in soil water content between May and September. Comparison of annual NPP EC and NPP BM showed a good overall agreement (R 2 = 0.463, p = 0.03), although in all years NPP BM was lower than NPP EC , with averages of 680 (±88) gC m −2 year −1 and 819 (±89) gC m −2 year −1 , respectively. Lower values of NPP BM indicate that fine roots and grasses contributions to NPP, which were not measured in the study period, could have an important contribution to the overall ecosystem NPP. At a seasonal level, two NPP estimates showed differences in their dynamic, but the application of the proposed model greatly improved the agreement in the second part of the growing season. Further research is needed on the respiration partitioning and mechanisms of carbon allocation. IntroductionCurrently global forests store approximately 30% of total anthropogenic CO 2 emissions [1], however, the potential of forests to act as a carbon sink in the future is uncertain due to possible saturation effect [2], or negative impact of changed environmental conditions on forest productivity [3]. The eddy covariance (EC) technique is a widely used, state-of-the-art method, and it has become a standard in the estimation and monitoring of high frequency (typically half-hourly) carbon and water fluxes within terrestrial ecosystems [4]. Long-term data series of net ecosystem carbon exchange (NEE) or net ecosystem productivity (NEP, NEP = −NEE), in combination with meteorological and biometric measurements, provide invaluable information on the response of forest ecosystem to environmental conditions and climate change [5][6][7][8].EC data are essential for calibration of process-based models like Biome-BGC and its variants [9,10] and they are also used for calibration and testi...

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confidence: 99%

Eddy Covariance vs. Biometric Based Estimates of Net Primary Productivity of Pedunculate Oak (Quercus robur L.) Forest in Croatia during Ten Years

Anić

Sever

Alberti

et al. 2018

Forests

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“…Biome-BGCMuSo was previously evaluated with flux and biometric data for C3 grassland, C4 maize and pedunculate oak forest [34], in addition to tree-rings data for oak forests [73]. In this research, validation of the model was performed through comparison of modelled and measured SOC 30 data at three different levels: land use (regardless of the biogeographical region), land use × biogeographical region and plot.…”

Section: Model Evaluationmentioning

confidence: 99%

Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses

Sever

Barcza

Hidy

et al. 2021

Land

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Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia’s GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC30) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC30 with no overall bias, and showed good performance at the LU level with no significant (p < 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC30 and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting.

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“…In that context, radial tree growth chronologies are high-resolution proxy sources used to reconstruct climatic variation at longer time scales (Esper and Gärtner 2001). Additionally, in their annual rings, trees preserve an archive of past growing conditions reflecting competition, disturbance, soil characteristics or species-specific growth patterns, as well as human-induced disturbances (Ostrogović Sever et al 2017).…”

Section: Introductionmentioning

confidence: 99%

First Dendroclimatological Insight into Austrian Pine (Pinus nigra Arnold) Climate-Growth Relationship in Belgrade Area, Serbia

Stajić

Kazimirović

Dukić

et al. 2020

SEEFOR

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In order to assess the impact of climate variations on Austrian pine forest in the Belgrade area, the radial growth of artificially-established Austrian pine trees and its dependence on temperature and precipitation was studied using dendroclimatological methods. The site is classified as Quercetum-frainetto cerris Rudski. Standard and residual chronologies were established and several common statistics were calculated. A dendroclimatic study was carried out using the correlation and response function analysis. The Pearson correlation coefficients between the chronology indices and 13 seasonal (3-month period) precipitation and temperature data were calculated for the period from 1959 to 2014. The applied response function analysis included 24 precipitation and temperature variables from October of the prior year to September of the current year. The results of the correlation analysis pointed out that there was a strong tendency towards a positive response to the summer and late summer/early autumn precipitation and a weak significant negative response to the spring and summer temperatures. Climate-growth relationships were further first studied using the response functions for the significant seasons that were detected from the correlation analysis and then for individual months from previous October to current September. These results also highlighted the findings that higher precipitation in the current summer months has a beneficial effect on the tree-ring width. The conducted correlation between the residual chronology and the Standardised Precipitation Evapotranspiration Index indicated that a high summer value of this drought index had a positive impact on the pine growth and reinforced the previously detected relevance of September as an important month for the Austrian pine growth. These preliminary results point out that some additional climate-Austrian pine growth studies (application of various tree-ring features, growth data with a much longer time span, more sites/stands, etc.) should be performed to obtain new and valuable knowledge important for the sustainable management of Austrian pine forests.

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Biogeochemical Modelling vs. Tree-Ring Measurements - Comparison of Growth Dynamic Estimates at Two Distinct Oak Forests in Croatia

Cited by 5 publications

References 37 publications

Eddy Covariance vs. Biometric Based Estimates of Net Primary Productivity of Pedunculate Oak (Quercus robur L.) Forest in Croatia during Ten Years

Eddy Covariance vs. Biometric Based Estimates of Net Primary Productivity of Pedunculate Oak (Quercus robur L.) Forest in Croatia during Ten Years

Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses

First Dendroclimatological Insight into Austrian Pine (Pinus nigra Arnold) Climate-Growth Relationship in Belgrade Area, Serbia

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