on methods for estimating forest productivity: field measurement, remote sensing & modelling...

On Methods For Estimating Forest Productivity: Field Measurement, Remote Sensing & Modelling

Project EFFEctivity Workshop No 2 - Croatian Forestry Society, Zagreb, 24th November 2015

HRVATSKI ŠUMARSKI INSTITUTCROATIAN FOREST RESEARCH INSTITUTE

SUPPORTED BY:

Maša Z. Ostrogović Sever 1

Dóra Hidy 2

Zoltan Barcza 3

WORKSHOPOn Methods For Estimating Forest Productivity:

Field Measurement, Remote Sensing & Modelling

1 Croatian Forest Research Institute, Department for Forest Management and Forestry Economics, Jastrebarsko, Croatia2 Institute of Ecology and Botany, Centre for Ecological Research, Hungarian Academy of Sciences, Budapest, Hungary3 Eotvös Lorand University, Deparment of Meteorology, Budapest, Hungary

HRVATSKI ŠUMARSKI

INSTITUT

CROATIAN FOREST RESEARCH INSTITUTE

Modelling forest productivity

with biogeochemical model Biome-BGC MuSo

- Case study of lowland oak forest -




Biome-BGC model in general




Biome-BGC MuSo modelModel version developed by the group of Hungarian scinetists from Eotvos Lorand University, Szent Istvan University, and Institute of Ecology and Botany, Centre for Ecological Research, Hungarian Academy of Sciences

IMPROVEMENTS:- soil hidrology- management modul- water stress effect- groundwater table info

+- many others…




Modelling process

- temp. & precip.- altitude, Tav, soil texture- list of ecophysiological

parameters

Equilibrium∆SOC<0,005 tC/ha

MORTALITY- harvest- fires- water stress

>600 outputs




In practicefilepath to main directoryF:\BBGC\Biome-BGC_MuSo_4_jlug

f:cd f:\BBGC\Biome-BGC_MuSo_4_jlug\MuSo4.exe ini\spinup.iniMuSo4.exe ini\normal.ini




Jastrebarsko site description

- Mixed pedunculate oak forest(black alder, hornbeam, narow-leaved ash)

- 40 y. old, soil mainly gleysol with low vertical water conductivity- 10,6°C, 962 mm, groundwater table at 60 - 200 cm

- EC measurments (NEP, GPP, Reco)- meteo measurements (SWC, T, Rh, Srad, PAR, P)- field measurements

(dendrometer bands, littertraps, oak chronosequence exp.)




IMPORTANT!GOOD PARAMETER

LIST!!

WHITE et al. 2000(ENF, DNF, DBF, shrub, grass)

PIETSCH et al. 2005 (oak)

BOND-LAMBERTY et al. 2005 (ENL, DBL)

CIENCIALA i TATARINOV 2006(beech, oak, pine, spruce)




ADJUSTED PARAMETERSParameter Oak forest Source

yearday to start new growth* 80 doy Field observations (H. Marjanović)

yearday to end litterfall* 310 doy Field observations (H. Marjanović)

transfer growth period as fraction of growing season 0.3 (prop.)

GDD for start of fruit allocation 1000 (°C) Field observations (H. Marjanović)

GDD for start of leaf senescence 2350 (°C) Field observations (H. Marjanović)

annual whole-plant mortality fraction 0.02 (1/y) Field observations (H. Marjanović)

annual fire mortality fraction 0 (1/y) Personal assessment

new fine root C : new leaf C 0.95 Ostrogović, 2013

new fruit c : leaf c 0.14 Ostrogović, 2013

new woody stem C : new leaf C 1.42 Ostrogović, 2013

C:N of leaves 24.5 Seletković, 2003

C:N of leaf litter, after retranslocation 47.5 Laboratory analysis (H. Marjanović)

C:N of fine roots 43 Gordon and Jackson 2000, Zadworny et al. 2015

C:N of fruit 33 Toscano and Cimino, 2013

fruit litter labile proportion 0.3 Toscano and Cimino, 2013

fruit litter cellulose proportion 0.29 Toscano and Cimino, 2013

relative SWC (prop. to FC) to calc. soil moisture limit 1 0.9 Heavy clay soil, optimal soil moisture condition below FC

relative SWC (prop. to SAT) to calc. soil moisture limit 2 0.985 Heavy clay soil, stress due to excess water starts before SAT

senescence mortality coefficient of leaf (after maturity) 0.025 Field observations of litterfall dynamics (app. 40 days)

bulk N denitrification proportion (WET) 0.02 Personal assessment

symbiotic+asymbiotic fixation of N 0.0036 kgN m-2 y-1 Binkley et al., 1994, Marjanović et al., 2011

ratio of the storage and the actual pool mortality due to management 0.9 Personal assessment

critical number of stress days after which senescence mortality is complete 90 days Personal assessment

maximum depth of rooting zone 1.0 m Personal assessment

maintenance respiration in kgC/day per kg of tissue N 0.4 kgC kgN-1 day-1 Cannell and Thornley, 2000




Measured vs. Modelled (2008-2011)




Measured vs. Modelled (2008-2011)

Comparison with oak chronosequence results (2011,2012)

OVERESTIMATED C STOCKS IN DEAD BIOMASS!!

measured modelled




NEP & NPP (2008-2010/2011)

Model is still developing.There is a place for more improvements and beter representations of some new proceses(soil water movement, drought stress effect, etc.)




NPP cummulative year sum (2008-2011)

Comparison with field measurements from dendrometer bands.(Marjanović et al. 2011)




PARAMETERIZATION NEEDED!

According to obtained results it is clear that more precise parameterization in needed. But, as this is a very complex model with more then 100 ecophysiological parameters, parameterization would mean large number of simulation runs - very high computational skills and requirements!

Answer is to use existing/available on-line tools, grids and tutorials like…

1. Biome-BGC Projects Database & Management System - on-line tool developed within the BioVeL project. It help Users in the application of the model and using infrastructure of the SZTAKI Desktop Grid process of calibration/parameterization can be performed.

2. Calibrating dynamic vegetation models – A tutorial developed within a COST Action FP1304 – PROFOUND, Working Group 3: Model comparisons and multi-model assessments, Task group 13: Review of model parameterization methods (Florian Hartig / Björn Reineking)




ACKNOWLEDGEMENTS

- to HRZZ (Croatian Science Foundation, EFFEctivity project UIP-11-2013-2492)

- to Hungarian Academy of Sciences (MTA PD 450012), the Hungarian Scientific Research Fund (OTKA K104816), the BioVeL project (FP7-INFRASTRUCTURES-2011-2, project number 283359)

- to COST Action FP1304 – PROFOUND, Working Group 3: Model comparisons and multi-model assessments




THANK YOU FOR YOUR ATTENTION!

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