Abstract
In this chapter we consider different methods of estimating the inputs to the tree and stand growth models presented in this book. How does the selected method depend on the specific questions we want to ask with the model? To gain insights into this, we first outline some general ideas and theory about linking models with data. We then illustrate input quantification for model applications by introducing different methods of parameterisation for the core model presented in Chap.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Albaugh TJ, Allen HL, Kress LW (2006) Root and stem partitioning of Pinus taeda. Trees 20(2):176–185
Bravo-Oviedo A, del Rio M, Calama R, Valentine HT (2013) New approaches to modelling cross-sectional area to height allometry in four mediterranean pine species. Forestry 87(3):399–406
Cajander AK (1949) Finnish forest types and their significance. Acta Forestalia Fennica 56:1–71
Cannell MGR, Thornley JHM (2000) Modelling the components of plant respiration: some guiding principles. Ann Bot 85:45–54
Cao T, Valsta L, Mäkelä A (2010) A comparison of carbon assessment methods for optimizing timber production and carbon sequestration in Scots pine stands. For Ecol Manage 260: 1726–1734
Dewar RC, Medlyn BE, McMurtrie RE (1999) Acclimation of the respiration/photosynthesis ratio to temperature: insights for a model. Glob Change Biol 5:612–622
Green EJ, MacFarlane DW, Valentine HT, Strawderman WE (1999) Assessing uncertainty in a stand growth model by Bayesian synthesis. For Sci 45(4):528–538
Gregoire TG, Valentine HT (2008) Sampling strategies for natural resources and the environment. Chapman & Hall/CRC, Boca Raton
Gregoire TG, Valentine HT, Furnival GM (1995) Sampling methods to estimate foliage and other characteristics of individual trees. Ecology 76:1181–1194
Härkönen S, Pulkkinen M, Duursma RA, Mäkelä A (2010) Estimating annual GPP, NPP and stem growth in Finland using summary models. For Ecol Manage 259:524–533
Högberg P, Nordgren A, Buchmann N, Taylor AFS, Ekblad A, Högberg MN, Nyberg G, Ottosson-Löfvenius M, Read DJ (2001) Large-scale forest girdling shows that current photosynthesis drives soil respiration. Nature 411:789–792
Helmisaari HS, Derome J, Nöjd P, Kukkola M (2007) Fine root biomass in relation to site and stand characteristics in norway spruce and scots pine stands. Tree Physiol 27:1493–1504
Hu M, Lehtonen A, Minunno F, Mäkelä A (2020) Age effect on tree structure and biomass allocation in Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] Karst.). Manuscript submitted to Ann For Sci
Hyytiäinen K, Hari P, Kokkila T, Mäkelä A, Tahvonen O, Taipale J (2004) Connecting a process-based forest growth model to stand-level economic optimization. Can J For Res 34:2060–2073
Ilomäki S, Nikinmaa E, Mäkelä A (2003) Crown rise due to competition drives biomass allocation in silver birch (Betula pendula l.). Can J For Res 33:2395–2404
Jessen RJ (1955) Determining the fruit count on a tree by randomized branch sampling. Biometrics 11:99–109
Kalliokoski T, Nygren P, Sievänen R (2008) Coarse root architecture of three boreal tree species growing in mixed stands. Silva Fenn 42:189–210
Kalliokoski T, Mäkinen H, Linkosalo T, Mäkelä A (2016) Evaluation of stand-level hybrid PipeQual model with permanent sample plot data of Norway spruce. Can J For Res 47:234–245
Kantola A, Mäkelä A (2006) Development of biomass proportions in Norway spruce (Picea abies [l.] Karst.). Trees 20:111–121
Kantola A, Mäkinen H, Mäkelä A (2007) Stem form and branchiness of Norway spruce as sawn timber – predicted by a process-based model. For Ecol Manage 241:209–222
Kershaw JA, Ducey MJ, Beers TW, Husch B (2017) Forest mensuration. John Wiley & Sons, West Sussex
Kikuzawa K (1991) A cost-benefit analysis of leaf habit and leaf longevity of trees and their geographical pattern. Am Nat 138:1250–1263
Kikuzawa K, Lechowicz MJ (2011) Ecology of leaf longevity. Ecological research monographs. Springer, Tokyo/Dordrecht/Heidelberg/London/New York
Landsberg JJ (1986) Physiological ecology of forest production. Academic Press, London
Leppälammi-Kujansuu J, Aro L, Salemaa M, Hansson K, Kleja DB, Helmisaari HS (2014a) Fine root longevity and carbon input into soil from below- and aboveground litter in climatically contrasting forests. For Ecol Manage 326:79–90
Leppälammi-Kujansuu J, Salemaa M, Kleja DB, Linder S, Helmisaari HS (2014b) Fine root turnover and litter production of Norway spruce in a long-term temperature and nutrient manipulation experiment. Plant Soil 374:73–88
Litton CM, Giardina CP (2008) Below-ground carbon flux and partitioning: global patterns and response to temperature. Funct Ecol 22:941–954
Mäkelä A (1999) Acclimation in dynamic models based on structural relationships. Funct Ecol 13:145–156
Mäkelä A (2002) Derivation of stem taper from the pipe theory in a carbon balance framework. Tree Physiol 22:891–905
Mäkelä A (2003) Process-based modelling of tree and stand growth: towards a herarchical treatment of multiscale processes. Can J For Res 23:398–409
Mäkelä A, Mäkinen H (2003) Generating 3D sawlogs with a process-based growth model. For Ecol Manage 184:337–354
Mäkelä A, Valentine HT (2001) The ratio of NPP to GPP: evidence of change over the course of stand development. Tree Physiol 21:1015–1030
Mäkelä A, Landsberg J, Ek AR, Burk TE, Ter-Mikaelian M, Ågren GI, Oliver CD, Puttonen P (2000) Process-based models for forest ecosystem management: current state of the art and challenges for practical implementation. Tree Physiol 20:289–298
Mäkelä A, Kolari P, Karimäki J, Nikinmaa E, Perämäki M, Hari P (2006) Modelling five years of weather-driven variation of GPP in a boreal forest. Agric For Meteorol 139:382–398
Mäkelä A, Pulkkinen M, Mäkinen H (2016) Bridging empirical and carbon-balance based forest site productivity – significance of below-ground allocation. For Ecol Manage 372:64–77
Mäkelä A, Pulkkinen M, Kolari P, Lagergren F, Berbigier P, Lindroth A, Loustau D, Nikinmaa E, Vesala T, Hari P (2008a) Developing an empirical model of stand GPP with the LUE approach: analysis of eddy covariance data at five contrasting conifer sites in Europe. Glob Change Biol 14:92–108
Medlyn BE, Duursma RA, Zeppel MJ (2011) Forest productivity under climate change: a checklist for evaluating model studies. Wiley Interdiscip Rev Clim Change 2:332–355
Minunno F, Peltoniemi M, Launiainen S, Aurela M, Lindroth A, Lohila A, Mammarella I, Minkkinen K, Mäkelä A (2016) Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region. Ecol Modell 341:37–52
Niinimäki S, Tahvonen O, Mäkelä A (2012) Applying a process-based model in Norway spruce management. For Ecol Manage 265:102–115
Näsholm T, Högberg P, Franklin O, Metcalfe D, Keel SG, Campbell C, Hurry V, Linder S, Högberg MN (2013) Are ectomycorrhizal fungi alleviating or aggravating nitrogen limitation of tree growth in boreal forests? New Phytol 198(1):214–221
Ostonen I, Helmisaari HS, Borken W, Tedersoo L, Kiukumägi M, Bahram M, Lindroos AJ, Nöjd P, Uri V, Merilä P, Asi E, Lõhmus K (2011) Fine root foraging strategies in norway spruce forests across a european climate gradient. Glob Change Biol 17:3620–3632
Peltoniemi M, Pulkkinen M, Kolari P, Duursma R, Montagnani L, Wharton S, Lagergren F, Takagi K, Verbeeck H, Christensen T, Vesala T, Falk M, Loustau D, Mäkelä A (2012) Does canopy mean N concentration explain differences in light use efficiencies of canopies in 14 contrasting forest sites? Tree Physiol 32:200–218
Peltoniemi M, Pulkkinen M, Aurela M, Pumpanen J, Kolari P, Mäkelä A (2015) A semi-empirical model of boreal forest gross primary production, evapotranspiration, and soil water – calibration and sensitivity analysis. Boreal Environ Res 20:151–171
Reich PB, Rich RL, Lu X, Wang YP, Oleksyn J (2014) Biogeographic variation in evergreen conifer needle longevity and impacts on boreal forest carbon cycle projections. Proc Natl Acad Sci U S A 111:13703–13708
Reynolds JF, Hilbert DW, Kemp PR (1993) Scaling ecophysiology from the plant to the ecosystem: a conceptual framework. In: Ehleringerl JR, Field CB (eds) Scaling physiological processes. Leaf to globe. Academic Press, San Diego, pp 127–140
Richardson AD, ZuDohna H (2003) Predicting root biomass from branching patterns of douglas-fir root systems. Oikos 100(1):96–104
Ryan MG (1991) A simple method for estimating gross carbon budgets for vegetation in forest ecosystems. Tree Physiol 9:255–266
Ryan MG (1995) Foliar maintenance respiration of subalpine and boreal trees and shrubs in relation to nitrogen content. Plant Cell Environ 18:765–772
Ryan MG, Hubbard RM, Pongracic S, Raison RJ, McMurtrie RE (1996) Foliage, fine-root, woody-tissue and stand respiration in Pinus radiata in relation to nitrogen status. Tree Physiol 16: 333–343
Schlecht RM, Affleck DLR (2014) Branch aggregation and crown allometry condition the precision of randomized branch sampling estimators of conifer crown mass. Can J For Res 44(5):499–508
Schneider R, Berninger F, Ung CH, Mäkelä A, Swift DE, Zang SY (2011) Within crown variation in the relationship between foliage biomass and sapwood area in jack pine. Tree Physiol 31: 22–29
Skovsgaard JP, Vanclay JK (2008) Forest site productivity: a review of the evolution of dendrometric concepts for even-aged stands. Forestry 81(1):13–31
Soetaert K, Petzoldt T (2010) Inverse modelling, sensitivity and Monte Carlo analysis in R using package fme. J Stat Softw 33(3):1–28
Stockfors J, Linder S (1998) The effect of nutrition on the seasonal course of needle respiration in Norway spruce stands. Trees 12:130–138
Stout BB (1956) Studies of the root systems of deciduous trees. Harvard Black Rock Forest, Cornwall-on-the-Hudson
Ťupek B, Mäkipää R, Heikkinen J, Peltoniemi M, Ukonmaanaho L, Hokkanen T, Nöjd P, Nevalainen S, Lindgren M, Lehtonen A (2015) Foliar turnover rates in Finland – comparing estimates from needle-cohort and litterfall-biomass methods. Boreal Environ Res 20:283–304
Valentine HT, Hilton SJ (1977) Sampling oak foliage by the randomized-branch method. Can J For Res 7:295–298
Valentine HT, Mäkelä A (2005) Bridging process-based and empirical approaches to modeling tree growth. Tree Physiol 25:769–779
Valentine HT, Tritton LM, Furnival GM (1984) Subsampling trees for biomass, volume„ or mineral content. For Sci 30:673–681
Valentine HT, Gregoire TG, Burkhart HE, Hollinger DY (1997) A stand-level model of carbon allocation and growth, calibrated for loblolly pine. Can J For Res 27:817–830
Valentine HT, Green EJ, Mäkelä A, Amateis RL, Mäkinen H, Ducey MJ (2012) Models relating stem growth to crown length dynamics: application to loblolly pine and Norway spruce. Trees 26:469–478
Valentine HT, Amateis RL, Gove JH, Mäkelä A (2013) Crown-rise and crown-length dynamics: application to loblolly pine. Forestry 86:371–375
Valentine HT, Baldwin VC Jr, Gregoire TG, Burkhart HE (1994a) Surrogates for foliar dry matter in loblolly pine. For Sci 40(3):576–585
Van Oijen M, Schapendonk A, Höglind M (2010) On the relative magnitude of photosynthesis, respiration, growth andcarbon storage in vegetation. Ann Bot 105:793–797
Van Oijen M, Reyer C, Bohn FJ, Cameron DR, Deckmyn G, Flechsig M, Härkönen S, Hartig F, Huth A, Kiviste A, Lasch P, Mäkelä A, Mette T, Minunno F, Rammer W (2013) Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe. For Ecol Manage 289:255–268
Vuokila Y, Väliaho H (1980) Growth and yield models of planted conifer forests (in Finnish). Publications of the Finnish Forest Research Institute, Helsinki
Wertin TM, Teskey RO (2008) Close coupling of whole-plant respiration to net photosynthesis and carbohydrates. Tree Physiol 28:1831–1840
Williams K, Field CB, Mooney HA (1989) Relationships among leaf construction cost, leaf longevity, and light environment in rain-forest plants of the genus Piper. Am Nat 133: 198–211
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mäkelä, A., Valentine, H.T. (2020). Predicting Stand Growth: Parameters, Drivers, and Modular Inputs. In: Models of Tree and Stand Dynamics. Springer, Cham. https://doi.org/10.1007/978-3-030-35761-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-35761-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35760-3
Online ISBN: 978-3-030-35761-0
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)