HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions. I. Carbon fluxes and tree dimensional growth

Abstract. Given the multiple abiotic and biotic stressors resulting from global changes, management systems and practices must be adapted in order to maintain and reinforce the resilience of forests. Among others, the transformation of monocultures into uneven-aged and mixed stands is an avenue to improve forest resilience. To explore the forest response to these new silvicultural practices under a changing environment, one need models combining a process-based approach with a detailed spatial representation, which is very rare. We therefore decided to develop our own model (HETEROFOR) according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). HETEROFOR was progressively elaborated through the integration of various modules (light interception, phenology, water cycling, photosynthesis and respiration, carbon allocation, mineral nutrition and nutrient cycling) within CAPSIS, a collaborative modelling platform devoted to tree growth and stand dynamics. The advantage of using such a platform is to use common development environment, model execution system, user- interface and visualization tools and to share data structures, objects, methods and libraries. This paper describes the carbon-related processes of HETEROFOR (photosynthesis, respiration, carbon allocation and tree dimensional growth) and evaluates the model performances for a mixed oak and beech stand in Wallonia (Belgium). This first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size-growth relationships. We also noticed that the more empirical options for describing maintenance respiration and crown extension provide the best results while the process-based approach best performs for photosynthesis. To illustrate how the model can be used to predict climate change impacts on forest ecosystems, the growth dynamics in this stand was simulated according to four IPCC climate scenarios. According to these simulations, the tree growth trends will be governed by the CO2 fertilization effect with the increase in vegetation period length and in water stress also playing a role but offsetting each other.

[1]  Sylvain Delzon,et al.  Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? , 2014, Journal of environmental management.

[2]  F. D. Vries,et al.  The cost of maintenance processes in plant cells , 1975 .

[3]  A. Held,et al.  Dark Leaf Respiration in Light and Darkness of an Evergreen and a Deciduous Plant Species , 1995, Plant physiology.

[4]  Pekka Nöjd,et al.  Fine root biomass in relation to site and stand characteristics in Norway spruce and Scots pine stands. , 2007, Tree physiology.

[5]  V. Grimm,et al.  Competition among plants: Concepts, individual-based modelling approaches, and a proposal for a future research strategy , 2008 .

[6]  Mathieu Jonard,et al.  Biomass and nutrient content of sessile oak (Quercus petraea (Matt.) Liebl.) and beech (Fagus sylvatica L.) stem and branches in a mixed stand in southern Belgium. , 2010, The Science of the total environment.

[7]  Piet Termonia,et al.  Validation of the ALARO-0 model within the EURO-CORDEX framework , 2015 .

[8]  Douglas Maraun,et al.  Statistical Downscaling and Bias Correction for Climate Research , 2018 .

[9]  Lael Parrott,et al.  From Management to Stewardship: Viewing Forests As Complex Adaptive Systems in an Uncertain World , 2015 .

[10]  H. Pretzsch,et al.  Modelling the impact of climate change on the productivity and water-use efficiency of a central European beech forest , 2013 .

[11]  J. Cottrell,et al.  Is the introduction of novel exotic forest tree species a rational response to rapid environmental change? – A British perspective , 2019, Forest Ecology and Management.

[12]  Gilles Le Moguédec,et al.  Fagacées: a tree-centered growth and yield model for sessile oak (Quercus petraea L.) and common beech (Fagus sylvatica L.) , 2012, Annals of Forest Science.

[13]  Mathieu Jonard,et al.  Tree species mediated effects on leaf litter dynamics in pure and mixed stands of oak and beech , 2008 .

[14]  I. Prentice,et al.  A general model for the light-use efficiency of primary production , 1996 .

[15]  Brendan Mackey,et al.  Forest resilience, biodiversity, and climate change: a synthesis of the biodiversity/resilience/stability relationship in forest ecosystems , 2009 .

[16]  B. Courbaud,et al.  Managing understory light to maintain a mixture of species with different shade tolerance , 2014 .

[17]  P. Heuberger,et al.  Calibration of process-oriented models , 1995 .

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

[19]  Hans Pretzsch,et al.  Representation of species mixing in forest growth models. A review and perspective , 2015 .

[20]  O. Tetens,et al.  Uber einige meteorologische begriffe , 1930 .

[21]  C. Pichot,et al.  Disentangling the factors driving tree reproduction , 2016 .

[22]  S. Rambal,et al.  Stem CO2 efflux and its contribution to ecosystem CO2 efflux decrease with drought in a Mediterranean forest stand , 2014 .

[23]  B. Reineking,et al.  Models for forest ecosystem management: a European perspective. , 2007, Annals of botany.

[24]  Tree allometry variation in response to intra- and inter-specific competitions , 2018, Trees.

[25]  Jean-Michel Leban,et al.  Nitrogen footprint in a long-term observation of forest growth over the twentieth century , 2011, Trees.

[26]  Mathieu Jonard,et al.  Influence of species and rain event characteristics on stemflow volume in a temperate mixed oak–beech stand , 2008 .

[27]  F. Lebourgeois,et al.  Stand density, tree social status and water stress influence allocation in height and diameter growth of Quercus petraea (Liebl.). , 2015, Tree physiology.

[28]  Rodolphe Palm,et al.  Tables de cubage des arbres et des peuplements forestiers. , 1985 .

[29]  A. Ibrom,et al.  Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate , 2018, Journal of advances in modeling earth systems.

[30]  A. Mäkelä,et al.  The ratio of NPP to GPP: evidence of change over the course of stand development. , 2001, Tree physiology.

[31]  E. Dufrene,et al.  Age-related variation in carbon allocation at tree and stand scales in beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.) using a chronosequence approach. , 2010, Tree physiology.

[32]  John Tenhunen,et al.  The effect of tree height on crown level stomatal conductance , 2000 .

[33]  François Jonard,et al.  Sap flux density and stomatal conductance of European beech and common oak trees in pure and mixed stands during the summer drought of 2003 , 2011 .

[34]  V. Kint,et al.  Current status and predicted impact of climate change on forest production and biogeochemistry in the temperate oceanic European zone: review and prospects for Belgium as a case study , 2012, Journal of Forest Research.

[35]  S. Running,et al.  Impacts of climate change on natural forest productivity – evidence since the middle of the 20th century , 2006 .

[36]  D. Forrester,et al.  Light absorption and light-use efficiency in mixtures of Abies alba and Picea abies along a productivity gradient , 2014 .

[37]  Paul-Henry Cournède,et al.  Parametric identification of a functional-structural tree growth model and application to beech trees (Fagus sylvatica). , 2008, Functional plant biology : FPB.

[38]  François Jonard,et al.  Soil carbon dioxide efflux in pure and mixed stands of oak and beech , 2007, Annals of Forest Science.

[39]  Olivier Bouriaud,et al.  Crown plasticity enables trees to optimize canopy packing in mixed-species forests , 2015 .

[40]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[41]  Quentin Ponette,et al.  Tree mineral nutrition is deteriorating in Europe , 2014, Global change biology.

[42]  M. G. Ryan,et al.  Effects of Climate Change on Plant Respiration. , 1991, Ecological applications : a publication of the Ecological Society of America.

[43]  Owen L. Petchey,et al.  Biodiversity and Resilience of Ecosystem Functions. , 2015, Trends in ecology & evolution.

[44]  Guillaume Marie,et al.  Influence of vegetation spatial structure on growth and water fluxes of a mixed forest: Results from the NOTG 3D model , 2016 .

[45]  E. Ceschia,et al.  Stem and branch respiration of beech: from tree measurements to estimations at the stand level , 2002 .

[46]  M. Fortin,et al.  The effect of light availability and basal area on cone production in Abies balsamea and Picea glauca , 2002 .

[47]  V. Dantec,et al.  Seasonal dynamics of soil carbon dioxide efflux and simulated rhizosphere respiration in a beech forest. , 2001, Tree physiology.

[48]  Hans Pretzsch,et al.  A Model for Individual Tree Development Based on Physiological Processes , 2002 .

[49]  C. Tebaldi,et al.  Long-term Climate Change: Projections, Commitments and Irreversibility , 2013 .

[50]  Denis Loustau,et al.  Sensitivity of water and carbon fluxes to climate changes from 1960 to 2100 in European forest ecosystems , 2006 .

[51]  V. O. Tetens.  Uber einige meteorologische , 1930 .

[52]  Michael Obersteiner,et al.  Nutrient availability as the key regulator of global forest carbon balance , 2014 .

[53]  L. Saint-Andre,et al.  Ontogeny partly explains the apparent heterogeneity of published biomass equations for Fagus sylvatica in central Europe , 2011 .

[54]  Christopher R. Schwalm,et al.  A process-based model of forest ecosystems driven by meteorology , 2004 .

[55]  Annikki Mäkelä,et al.  Implications of the pipe model theory on dry matter partitioning and height growth in trees , 1985 .

[56]  D. Landgraf,et al.  Key drivers of competition and growth partitioning among Robinia pseudoacacia L. trees , 2018, Forest Ecology and Management.

[57]  Hans Pretzsch,et al.  Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities , 2019, Forest Systems.

[58]  P. Lasch-Born,et al.  Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide , 2014, Annals of Forest Science.

[59]  Mathieu Jonard,et al.  Modeling leaf dispersal in mixed hardwood forests using a ballistic approach. , 2006, Ecology.

[60]  R. Neilson,et al.  Forest Processes and Global Environmental Change: Predicting the Effects of Individual and Multiple Stressors , 2001 .

[61]  Miles S. Kersten,et al.  Laboratory research for the determination of thermal properties of soils , 1949 .

[62]  Céline Meredieu,et al.  Capsis: an open software framework and community for forest growth modelling , 2011, Annals of Forest Science.

[63]  H. Pretzsch,et al.  Stem growth is favored at expenses of root growth in mixed stands and humid conditions for Douglas-fir (Pseudotsuga menziesii) and European beech (Fagus sylvatica) , 2017, Trees.

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

[65]  D. Coomes,et al.  Predictable changes in aboveground allometry of trees along gradients of temperature, aridity and competition , 2012 .

[66]  Treecision.  Tree Disease Concepts , 2002 .

[67]  François de Coligny,et al.  Simulating radiation distribution in a heterogeneous Norway spruce forest on a slope , 2003 .

[68]  Hans Pretzsch,et al.  Canopy space filling and tree crown morphology in mixed-species stands compared with monocultures , 2014 .

[69]  J. Oleksyn,et al.  Stem CO2 efflux in six co-occurring tree species: underlying factors and ecological implications. , 2015, Plant, cell & environment.

[70]  Mathieu Jonard,et al.  Precipitation water storage capacity in a temperate mixed oak–beech canopy , 2008 .

[71]  Benjamin Smith,et al.  Changes in European ecosystem productivity and carbon balance driven by regional climate model output , 2007 .

[72]  J. Monteith.  Climate and the efficiency of crop production in Britain , 1977 .

[73]  H. Douville,et al.  The CNRM-CM5.1 global climate model: description and basic evaluation , 2013, Climate Dynamics.

[74]  A. Granier,et al.  Modelling carbon and water cycles in a beech forest: Part I: Model description and uncertainty analysis on modelled NEE , 2005 .

[75]  Quirijn de Jong van Lier,et al.  Testing a finite-difference model for soil heat transfer by comparing numerical and analytical solutions , 2004, Environ. Model. Softw..

[76]  B. Medlyn,et al.  MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO 2 ] × drought interactions , 2012 .

[77]  I. Prentice,et al.  Is NPP proportional to GPP? Waring’s hypothesis 20 years on , 2019 .

[78]  Lonnie W. Aarssen,et al.  The interpretation of stem diameter–height allometry in trees: biomechanical constraints, neighbour effects, or biased regressions? , 1999 .

[79]  H. Goosse,et al.  CO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia , 2020, Annals of Forest Science.

[80]  Challenges to modelling NPP in diverse eastern deciduous forests: species-level comparisons of foliar respiration responses to temperature and nitrogen , 1999 .

[81]  Elena Cantarello,et al.  Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape , 2017, Ecology and evolution.

[82]  Alexandre Bosc,et al.  EMILION, a tree functional-structural model: Presentation and first application to the analysis of branch carbon balance , 2000 .

[83]  M. G. Ryan,et al.  Hydraulic Limits to Tree Height and Tree Growth , 1997 .

[84]  L. Saint-Andre,et al.  Improving the robustness of biomass functions: from empirical to functional approaches , 2015, Annals of Forest Science.

[85]  K. Hikosaka,et al.  Temperature response of photosynthesis in C3, C4, and CAM plants: temperature acclimation and temperature adaptation , 2013, Photosynthesis Research.

[86]  Scott R. Charlton,et al.  Modules based on the geochemical model PHREEQC for use in scripting and programming languages , 2011, Comput. Geosci..

[87]  A. Barbati,et al.  Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems , 2010 .

[88]  Axel Göttlein,et al.  Comparison of new foliar nutrient thresholds derived from van den Burg’s literature compilation with established central European references , 2012, European Journal of Forest Research.

[89]  H. Davi,et al.  HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 1: Carbon fluxes and tree dimensional growth , 2020, Geoscientific Model Development.

[90]  François Jonard,et al.  HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions. II. Phenology and water cycle , 2019 .