Modelling the decadal trend of ecosystem carbon fluxes demonstrates the important role of functional changes in a temperate deciduous forest

Abstract Temperate forests are globally important carbon sinks and stocks. Trends in net ecosystem exchange have been observed in a Danish beech forest and this trend cannot be entirely attributed to changing climatic drivers. This study sought to clarify the mechanisms responsible for the observed trend, using a dynamic ecosystem model (CoupModel) and model data fusion with multiple constraints and model experiments. Experiments with different validation datasets showed that a multiple constraints model data fusion approach that included the annual tree growth, the seasonal canopy development, the latent and sensible heat fluxes and the CO 2 fluxes decreased the parameter uncertainty considerably compared to using CO 2 fluxes as validation data alone. The fitted model was able to simulate the observed carbon fluxes well ( R 2  = 0.8, mean error = 0.1 g C m −2  d −1 ) but did not reproduce the decadal (1997–2009) trend in carbon uptake when global parameter estimates were used. Annual parameter estimates were able to reproduce the decadal scale trend; the yearly fitted posterior parameters (e.g. the light use efficiency) indicated a role for changes in the ecosystem functional properties. A possible role for nitrogen demand during mast years is supported by the inter-annual variability in the estimated parameters. The inter-annual variability of photosynthesis parameters was fundamental to the simulation of the trend in carbon fluxes in the investigated beech forest and this demonstrates the importance of functional change in carbon balance.

[1]  David Gustafsson,et al.  Simulated climate change impacts on fluxes of carbon in Norway spruce ecosystems along a climatic transect in Sweden , 2008 .

[2]  Jehn-Yih Juang,et al.  Multiscale model intercomparisons of CO2 and H2O exchange rates in a maturing southeastern US pine forest , 2006 .

[3]  Ari Nissinen,et al.  Evaluation of six process‐based forest growth models using eddy‐covariance measurements of CO2 and H2O fluxes at six forest sites in Europe , 2002 .

[4]  Per-Erik Jansson,et al.  Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem , 2011 .

[5]  Oleg Panferov,et al.  Variation in photosynthetic light-use efficiency in a mountainous tropical rain forest in Indonesia. , 2008, Tree physiology.

[6]  R. Houghton.  Balancing the Global Carbon Budget , 2007 .

[7]  Eliot J. B. McIntire,et al.  Masting in whitebark pine (Pinus albicaulis) depletes stored nutrients. , 2012, The New phytologist.

[8]  Heinrich Spiecker,et al.  Silvicultural management in maintaining biodiversity and resistance of forests in Europe-temperate zone. , 2003, Journal of environmental management.

[9]  B. Law,et al.  An improved analysis of forest carbon dynamics using data assimilation , 2005 .

[10]  Philippe Ciais,et al.  Update on CO2 emissions , 2010 .

[11]  H. Hasenauer,et al.  Assessing the impacts of climate change and nitrogen deposition on Norway spruce (Picea abies L. Karst) growth in Austria with BIOME-BGC. , 2011, Tree physiology.

[12]  Ian G. Enting,et al.  A review of applications of model–data fusion to studies of terrestrial carbon fluxes at different scales , 2009 .

[13]  Niels Otto Jensen,et al.  Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009 , 2011 .

[14]  David Gustafsson,et al.  Bayesian calibration of a model describing carbon, water and heat fluxes for a Swedish boreal forest stand. , 2008 .

[15]  Nuno Carvalhais,et al.  Comparing observations and process‐based simulations of biosphere‐atmosphere exchanges on multiple timescales , 2010 .

[16]  Y. Xue,et al.  Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis , 2012 .

[17]  Philippe Ciais,et al.  Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO2 exchange , 2012 .

[18]  Keith Beven,et al.  Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .

[19]  R. Houborg,et al.  Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data , 2008 .

[20]  N. Jensen,et al.  Two years of continuous CO2 eddy-flux measurements over a Danish beech forest , 2001 .

[21]  P. Hari,et al.  Predicting spring phenology and frost damage risk of Betula spp. under climatic warming: a comparison of two models. , 2000, Tree physiology.

[22]  P. Ambus,et al.  Fluxes of NO3-, NH4+, NO, NO2, and N2O in an Old Danish Beech Forest , 2001 .

[23]  Pierre Friedlingstein,et al.  Comparing and evaluating process‐based ecosystem model predictions of carbon and water fluxes in major European forest biomes , 2005, Global change biology.

[24]  E. Davidson,et al.  Using model‐data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling , 2012 .

[25]  Per-Erik Jansson,et al.  Modelling soil C sequestration in spruce forest ecosystems along a Swedish transect based on current conditions , 2008 .

[26]  Erkki Tomppo,et al.  A report to the food and agriculture organization of the united nations (FAO) in support of sampling study for National Forestry Resources Monitoring and Assessment (NAFORMA) in Tanzania , 2010 .

[27]  Per-Erik Jansson,et al.  A coupled model of water, heat and mass transfer using object orientation to improve flexibility and functionality , 2001, Environ. Model. Softw..

[28]  Per-Erik Jansson,et al.  The role of air and soil temperature in the seasonality of photosynthesis and transpiration in a boreal Scots pine ecosystem , 2012 .

[29]  A. Ibrom,et al.  Effects of climate variability and functional changes on the interannual variation of the carbon balance in a temperate deciduous forest , 2011 .

[30]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[31]  E. Falge,et al.  Toward a consistency cross‐check of eddy covariance flux–based and biometric estimates of ecosystem carbon balance , 2009 .

[32]  M. Pihlatie,et al.  Interactions between leaf nitrogen status and longevity in relation to N cycling in three contrasting European forest canopies , 2012 .

[33]  Per Ambus,et al.  Field measurements of atmosphere-biosphere interactions in a Danish beech forest , 2003 .

[34]  Russell K. Monson,et al.  Coupling between carbon cycling and climate in a high-elevation, subalpine forest: a model-data fusion analysis , 2007, Oecologia.

[35]  P. Jarvis.  The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[36]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[37]  Heikki Hänninen,et al.  Effects of climatic change on trees from cool and temperate regions: an ecophysiological approach to modelling of bud burst phenology , 1995 .

[38]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[39]  Per-Erik Jansson,et al.  Coupmodel: Model use, calibration, and validation , 2012 .

[40]  Jim Freer,et al.  Towards a limits of acceptability approach to the calibration of hydrological models : Extending observation error , 2009 .