Challenges for evaluating process-based models of gas exchange at forest sites with fetches of various species

Physiologically-based (or process-based) models are commonly applied to describe plant responses mechanistically in dependence on environmental conditions. They are increasingly evaluated with eddy-covariance measurements that integrate carbon and water exchange of an area of several hectares (called the fetch). However, almost all models applied to date in such exercises have considered only the dominant tree species and neglected other species that contributed to the measured gas exchange rates-either in separate patches or in mixture. This decreases the transferability of the model from one site to another because the contributions from other species might be different. It is therefore a major challenge in modeling today to separate the measured gas exchanges by sources. In this study, a detailed physiologically-based biosphere model is applied that allows distinguishing between tree species in mixed forests, considering them as «vegetation cohorts» that interact with each other. The sensitivity of the model to different assumptions about how different tree species contribute to an integrated measurement of standscale gas exchange is investigated. The model exercise is carried out for a forest site in Finland with dominant Scots pine but presence of significant amounts of Norway spruce and birch. The results demonstrate that forest structure affects simulated gas exchange rates indicating a possible importance of considering differences in physiological properties at the species level. It is argued that the variation of stand structure within the range of eddy-covariance measurements should be better accounted for in models and that inventory measurements need to consider this variation.

[1]  A. Mäkelä,et al.  Optimal co-allocation of carbon and nitrogen in a forest stand at steady state. , 2008, The New phytologist.

[2]  M. Cannell,et al.  Modelling the Components of Plant Respiration: Representation and Realism , 2000 .

[3]  Kurt H. Johnsen,et al.  Applying 3-PG, a Simple Process-Based Model Designed to Produce Practical Results, to Data from Loblolly Pine Experiments , 2001, Forestry sciences.

[4]  H. Grip,et al.  Micrometeorology and hydrology of pine forest ecosystems. I. Field studies. , 1980 .

[5]  T Vesala,et al.  Contributions of climate, leaf area index and leaf physiology to variation in gross primary production of six coniferous forests across Europe: a model-based analysis. , 2009, Tree physiology.

[6]  P. Kupper,et al.  Within-crown variation in leaf conductance of Norway spruce: effects of irradiance, vapour pressure deficit, leaf water status and plant hydraulic constraints , 2004 .

[7]  Harald Kunstmann,et al.  Modelling and observation of biosphere–atmosphere interactions in natural savannah in Burkina Faso, West Africa , 2009 .

[8]  J. Landsberg,et al.  PHYSIOLOGY IN FOREST MODELS: HISTORY AND THE FUTURE , 2003 .

[9]  W. Oechel,et al.  FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities , 2001 .

[10]  S. Delagrange Light- and seasonal-induced plasticity in leaf morphology, N partitioning and photosynthetic capacity of two temperate deciduous species , 2011 .

[11]  T. Kuuluvainen Long-term development of needle mass, radiation interception and stemwood production in naturally regenerated Pinus sylvestris stands on Empetrum-Vaccinium site type in the northern boreal zone in Finland: an analysis based on an empirical study and simulation , 1991 .

[12]  Ü. Rannik,et al.  Footprints and Fetches for Fluxes over Forest Canopies with Varying Structure and Density , 2003 .

[13]  P. De Angelis,et al.  Effects of elevated (CO2) on photosynthesis in European forest species: a meta-analysis of model parameters , 1999 .

[14]  Tiina Markkanen,et al.  Effect of thinning on surface fluxes in a boreal forest , 2005 .

[15]  Mark A. Sutton,et al.  Dry deposition of reactive nitrogen to European ecosystems: a comparison of inferential models across the NitroEurope network , 2010 .

[16]  R. Ceulemans,et al.  Under-story contributions to stand level GPP using the process model SECRETS , 2006 .

[17]  Andrew D. Richardson,et al.  Drought Stress and Paper Birch (Betula Papyrifera) Seedlings: Effects of an Organic Biostimulant on Plant Health and Stress Tolerance, and Detection of Stress Effects With Instrument-Based, Noninvasive Methods , 2004, Arboriculture & Urban Forestry.

[18]  M. Battaglia,et al.  CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support , 2004 .

[19]  Klaus Butterbach-Bahl,et al.  Future scenarios of N2O and NO emissions from European forest soils , 2006 .

[20]  R. Leuningb,et al.  Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data , 2010 .

[21]  M. Lindner,et al.  Model-based analysis of management alternatives at stand and regional level in Brandenburg (Germany) , 2005 .

[22]  A. Mäkelä,et al.  Acclimation of photosynthetic capacity in Scots pine to the annual cycle of temperature. , 2004, Tree physiology.

[23]  Denis Loustau,et al.  Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data , 2002 .

[24]  Changsheng Li,et al.  A model of nitrous oxide evolution from soil driven by rainfall events: 1. Model structure and sensitivity , 1992 .

[25]  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 .

[26]  Sune Linder,et al.  Modelling the short-term effects of climate change on the productivity of selected tree species in Nordic countries , 2003 .

[27]  A. Huth,et al.  The process-based stand growth model Formix 3-Q applied in a GIS environment for growth and yield analysis in a tropical rain forest. , 2000, Tree physiology.

[28]  Tuomas Laurila,et al.  Parametrization of two photosynthesis models at the canopy scale in a northern boreal Scots pine forest , 2007 .

[29]  Changsheng Li,et al.  A process-oriented model of N2O and NO emissions from forest soils: 1. Model development , 2000 .

[30]  I. Mammarella,et al.  Determining the contribution of vertical advection to the net ecosystem exchange at Hyytiälä forest, Finland , 2007 .

[31]  Steve Frolking,et al.  A model of nitrous oxide evolution from soil driven by rainfall events: 2. Model applications , 1992 .

[32]  J. Monteith,et al.  Principles of Environmental Physics , 2014 .

[33]  Klaus Butterbach-Bahl,et al.  A European-wide inventory of soil NO emissions using the biogeochemical models DNDC/Forest-DNDC , 2009 .

[34]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[35]  E. Falge,et al.  A model of the gas exchange response ofPicea abies to habitat conditions , 1996, Trees.

[36]  E. Falge,et al.  A model of the gas exchange response of , 1996 .

[37]  Hojka Kraigher,et al.  Using the process-based stand model ANAFORE including Bayesian optimisation to predict wood quality and quantity and their uncertainty in Slovenian beech , 2009 .

[38]  Frank Berninger,et al.  Carbon balance of different aged Scots pine forests in Southern Finland , 2004 .

[39]  Risto Sievänen,et al.  A process‐based model for the dimensional growth of even‐aged stands , 1993 .

[40]  Raisa Mäkipää,et al.  Biomass and stem volume equations for tree species in Europe , 2005, Silva Fennica Monographs.

[41]  C. T. Wit,et al.  Simulation of assimilation, respiration, and transpiration of crops , 1978 .

[42]  Rüdiger Grote,et al.  Sensitivity of volatile monoterpene emission to changes in canopy structure: a model-based exercise with a process-based emission model. , 2007, The New phytologist.

[43]  P. Hari,et al.  Uncertainties in measurement and modelling of net ecosystem exchange of a forest , 2006 .

[44]  Andrew D. Richardson,et al.  Phenology of a northern hardwood forest canopy , 2006 .

[45]  A. Mäkelä,et al.  Predicting boreal conifer photosynthesis in field conditions , 2009 .

[46]  Üllar Rannik,et al.  Relative Humidity Effect on the High-Frequency Attenuation of Water Vapor Flux Measured by a Closed-Path Eddy Covariance System , 2009 .

[47]  R. Ceulemans,et al.  Effects of elevated atmospheric CO(2) on phenology, growth and crown structure of Scots pine (Pinus sylvestris) seedlings after two years of exposure in the field. , 1999, Tree physiology.

[48]  A. Alriksson,et al.  Variations in mineral nutrient and C distribution in the soil and vegetation compartments of five temperate tree species in NE Sweden , 1998 .

[49]  R. Ceulemans,et al.  Modelling ozone effects on adult beech trees through simulation of defence, damage, and repair costs: Implementation of the CASIROZ ozone model in the ANAFORE forest model. , 2007, Plant biology.

[50]  Miikka Dal Maso,et al.  Long-term measurements of surface fluxes above a Scots pine forest in Hyytiälä, southern Finland, 1996-2001 , 2003 .

[51]  R. Ceulemans,et al.  Stomatal conductance of forest species after long-term exposure to elevated CO2 concentration: a synthesis. , 2001, The New phytologist.

[52]  P. Hari,et al.  Water balance of a boreal Scots pine forest , 2010 .

[53]  Kai-yun Wang Canopy CO2 exchange of Scots pine and its seasonal variation after four-year exposure to elevated CO2 and temperature , 1996 .

[54]  R. Grote Integrating dynamic morphological properties into forest growth modelling II Allocation and mortality , 1998 .

[55]  B. Muys,et al.  Simulating C cycles in forest soils: Including the active role of micro-organisms in the ANAFORE forest model , 2011 .

[56]  J. Pereira,et al.  Eight years of continuous carbon fluxes measurements in a portuguese eucalypt stand under two main events: drought and felling , 2011 .

[57]  Eero Nikinmaa,et al.  Forest floor vegetation plays an important role in photosynthetic production of boreal forests , 2006 .

[58]  J. Flower-Ellis,et al.  Branch transpiration of pine and spruce scaled to tree and canopy using needle biomass distributions , 2000, Trees.

[59]  Sune Linder,et al.  Climatic factors controlling the productivity of Norway spruce : A model-based analysis , 1998 .

[60]  Ü. Rannik,et al.  Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology , 2000 .

[61]  A. Mäkelä,et al.  Modelling five years of weather-driven variation of GPP in a boreal forest , 2006 .

[62]  W. Havranek,et al.  The influence of soil moisture on water potential, transpiration and photosynthesis of conifer seedlings , 1978, Plant and Soil.

[63]  J. S. Kimball,et al.  Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps. , 2000, Tree physiology.

[64]  N. Coops,et al.  Assessing forest growth across southwestern Oregon under a range of current and future global change scenarios using a process model, 3‐PG , 2001 .

[65]  Michael Battaglia,et al.  Evaluation of a process-based ecosystem model for long-term biomass and stand development of Eucalyptus globulus plantations , 2010, European Journal of Forest Research.

[66]  H. Hänninen,et al.  Models of the spring phenology of boreal and temperate trees: Is there something missing? , 2006, Tree physiology.

[67]  J. Schnitzler,et al.  Modeling of annual variations of oak (Quercus robur L.) isoprene synthase activity to predict isoprene emission rates , 2001 .

[68]  Peter E. Thornton,et al.  BGC-model parameters for tree species growing in central European forests , 2005 .

[69]  Charles T. Driscoll,et al.  Application of the forest–soil–water model (PnET-BGC/CHESS) to the Lysina catchment, Czech Republic , 1999 .

[70]  T. Aalto,et al.  Parametrization of a biochemical CO 2 exchange model for birch (Betula pendula Roth.) , 2001 .

[71]  V. Uri,et al.  Above-ground biomass production and nutrient accumulation in young stands of silver birch on abandoned agricultural land , 2007 .

[72]  M. G. Ryan,et al.  Seasonal respiration of foliage, fine roots, and woody tissues in relation to growth, tissue N, and photosynthesis , 2002 .

[73]  Antonio Donato Nobre,et al.  Acclimation of photosynthetic capacity to irradiance in tree canopies in relation to leaf nitrogen concentration and leaf mass per unit area , 2002 .

[74]  S. Kellomäki,et al.  Effects of elevated O3 and CO2 concentrations on photosynthesis and stomatal conductance in Scots pine , 1997 .

[75]  G. Wallin,et al.  Measuring and modelling stomatal conductance and photosynthesis in mature birch in Sweden , 2005 .

[76]  Alan R. Ek,et al.  Process-based models for forest ecosystem management: current state of the art and challenges for practical implementation. , 2000, Tree physiology.

[77]  E. Falge,et al.  Effects of stand structure and physiology on forest gas exchange: a simulation study for Norway spruce , 1997, Trees.

[78]  Eero Nikinmaa,et al.  Long-term measurements of the carbon balance of a boreal Scots pine dominated forest ecosystem , 2009 .

[79]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[80]  B. Medlyn,et al.  Temperature response of parameters of a biochemically based model of photosynthesis. I. Seasonal changes in mature maritime pine (Pinus pinaster Ait.) , 2002 .

[81]  Frank Berninger,et al.  Simulated irradiance and temperature estimates as a possible source of bias in the simulation of photosynthesis , 1994 .

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

[83]  Jonathan Silvertown,et al.  Plant coexistence and the niche , 2004 .

[84]  Helmut Mayer,et al.  Water fluxes within beech stands in complex terrain , 2010, International journal of biometeorology.

[85]  Ralf Kiese,et al.  Modelling forest carbon balances considering tree mortality and removal , 2011 .

[86]  Hartmut Bossel,et al.  treedyn3 forest simulation model , 1996 .

[87]  A. Friend,et al.  Suitability of process-based tree growth models for addressing tree response to climate change. , 2000, Environmental pollution.

[88]  T. Vesala,et al.  Simulation and scaling of temporal variation in gross primary production for coniferous and deciduous temperate forests , 2004 .

[89]  Rüdiger Grote,et al.  Estimation of crown radii and crown projection area from stem size and tree position , 2003 .

[90]  E. Keskitalo How Can Forest Management Adapt to Climate Change? Possibilities in Different Forestry Systems , 2011 .

[91]  E. Nikinmaa,et al.  Contribution of root and rhizosphere respiration to the annual variation of carbon balance of a boreal Scots pine forest , 2009 .

[92]  R. Matyssek,et al.  Nutrition and the ozone sensitivity of birch (Betula pendula) , 1997, Trees.

[93]  S. Rambal,et al.  Modelling the drought impact on monoterpene fluxes from an evergreen Mediterranean forest canopy , 2009, Oecologia.

[94]  Stephen P. Long,et al.  Modification of the response of photosynthetic productivity to rising temperature by atmospheric CO2 concentrations: Has its importance been underestimated? , 1991 .

[95]  Diane F. Halpern,et al.  A process-oriented model of cognitive sex differences , 1996 .

[96]  Ü. Niinemets,et al.  Structural and physiological plasticity in response to light and nutrients in five temperate deciduous woody species of contrasting shade tolerance , 2007 .

[97]  P. Hari,et al.  Comparison of an optimal stomatal regulation model and a biochemical model in explaining CO‚́‚ exchange in field conditions , 2002 .

[98]  Andreas Huth,et al.  Modelling dynamics of managed tropical rainforests—An aggregated approach , 2006 .

[99]  R. Mickler,et al.  Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale , 2002, Journal of the Air & Waste Management Association.

[100]  Ernst-Detlef Schulze,et al.  Growth and carbon stocks of a spruce forest chronosequence in central Europe , 2002 .

[101]  Eero Nikinmaa,et al.  Station for Measuring Ecosystem-Atmosphere Relations: SMEAR , 2013 .

[102]  J. Thornley,et al.  Instantaneous canopy photosynthesis: analytical expressions for sun and shade leaves based on exponential light decay down the canopy and an acclimated non-rectangular hyperbola for leaf photosynthesis. , 2002, Annals of botany.

[103]  I. Mammarella,et al.  Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2 , 2009 .