Parameterization of the 3-PG model for Pinus elliottii stands using alternative methods to estimate fertility rating, biomass partitioning and canopy closure

Forest Ecology and Management

Volumn 327, Issue , 2014, Pages 55-75

  Gonzalez Benecke, Carlos A ^a   Jokela, Eric J ^a   Cropper, Wendell P ^a   Bracho, Rosvel ^a   Leduc, Daniel J ^b  

^a UNIVERSITY OF FLORIDA   (United States)

^b USDA FOREST SERVICE   (United States)

Author keywords

3 PG model; Ecophysiology; Forest modeling; Physiological process based model; Slash pine; Stand dynamics

Indexed keywords

BIOMASS; CLIMATE CHANGE; CLIMATE MODELS; COMPUTER SIMULATION; ESTIMATION; FORESTRY; PARAMETERIZATION; PHYSIOLOGICAL MODELS; PHYSIOLOGY; PRODUCTIVITY;

3-PG MODELS; ECOPHYSIOLOGY; FOREST MODELING; PROCESS-BASED MODELING; SLASH PINES; STAND DYNAMICS; PHYSIOLOGICAL PROCESS;

ECOLOGY;

BIOMASS ALLOCATION; CLIMATE EFFECT; ESTIMATION METHOD; FERTILITY; FOREST CANOPY; FOREST COVER; GROWTH RATE; NUMERICAL MODEL; PARAMETERIZATION; SIMULATION; SPECIES DIVERSITY;

BIOMASS; ECOLOGY; FORESTS; PHYSIOLOGY; PINUS CARIBAEA; PRODUCTIVITY; SEASONAL VARIATION;

URUGUAY;

PINUS ELLIOTTII;

EID: 84901193850     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2014.04.030     Document Type: Article

References (96)

1. Almeida A.C., Landsberg J.J., Sands P.J. Parameterization of the 3-PG model for fast-growing Eucalyptus grandis plantations. For. Ecol. Manage. 2004, 193:179-195.
2. Almeida A.C., Siggins A., Batista T.R., Beadle C., Fonseca S., Loos R. Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG, a process-based growth model. For. Ecol. Manage. 2010, 259:1730-1740.
3. Aylott M.J., Casella E., Tubby I., Street N.R., Smith P., Taylor G. Yield and spatial supply of bioenergy poplar and willow short-rotation coppice in the UK. New Phytol. 2008, 178:358-370.
4. Baldwin V.C., Dean T.J., Ferguson R.B. A comparison of density indices in controlling growing stock in a slash pine spacing-thinning study. Proceedings of the 8th Biennial Southern Silvicultural Research Conference 1995, 461-466. USDA Forest Service, Southern Research Station, Asheville, NC. E.M. Boyd (Ed.).
5. Barnett, J.P., Sheffield, R.M., 2004. Slash pine: characteristics, history, status and trends. In: Slash Pine: Still Growing and Growing!, Dickens, E.D., Barnett, J.P., Hubbard, W.G., Jokela, E.L. (Eds.), Proceedings of the Slash Pine Symposium, pp. 1-6.
6. Bracho R., Starr G., Gholz H.L., Martin T.A., Cropper W.P., Loescher H.W. Controls on carbon dynamics by ecosystem structure and climate for southeastern U.S. slash pine plantations. Ecol. Monog. 2012, 82:101-128.
7. Booth, T.H., Hong Hai, P., Khac Hieu, N., Jovanovic, T., Landsberg, J., Parsons, M., 2000. Increasing carbon sequestration in planted forests in vietnam through the use of genetically improved planting stock, and modeling to quantify the benefits achieved. Component 2: carbon inventory and growth prediction. CSIRO Forestry and Forest Products Client Report for the International Greenhouse Partnerships Office, Canberra.
8. Bryars C., Maier C., Zhao D., Kane M., Borders B., Will R., Teskey R. Fixed physiological parameters in the 3-PG model produced accurate estimates of loblolly pine growth on sites in different geographic regions. For. Ecol. Manage. 2013, 289:501-514.
9. Burkhart H.E., Tomé M. Modeling Forest Trees and Stands 2012, Springer, 457 p.
10. CFGRP, 2012. Cooperative Forest Genetics Research Program, 54th annual report, pp. 19-20.
11. Chmura D.J., Rahman M.S., Tjoelker M.G. Crown structure and biomass allocation patterns modulate aboveground productivity in young loblolly pine and slash pine. For. Ecol. Manage. 2007, 243:219-230.
12. Chmura D.J., Tjoelker M.G. Leaf traits in relation to crown development, light interception and growth of elite families of loblolly and slash pine. Tree Physiol. 2008, 28:729-742.
13. Clark III, A., Saucier, J.R., 1991. Influence of planting density, intensive culture, geographic location, and species on juvenile wood formation in southern pine. Georgia For. Res. Pap. 85, Georgia For. Comm., 13 p.
14. Clark K.L., Gholz H.L., Moncrieff J.B., Cropley F., Loescher H.W. Environmental controls over net exchanges of carbon dioxide from contrasting Florida ecosystems. Ecol. Appl. 1999, 9:936-947.
15. Clark K.L., Gholz H.L., Castro M.S. Carbon dynamics along a chronosequence of slash pine plantations in north Florida. Ecol. Appl. 2004, 14:1154-1171.
16. Colbert S.R., Jokela E.J., Neary D.G. Effects of annual fertilization and sustained weed control on dry matter partitioning, leaf area, and growth efficiency of juvenile loblolly and slash pine. For. Sci. 1990, 36:995-1014.
17. Coops N.C., Waring R.H. Estimating forest productivity in the eastern Siskiyou Mountains of southwestern Oregon using satellite driven process model, 3-PGS. Can. J. For. Res. 2001, 13:143-154.
18. Coops N.C., Waring R.H., Law B.E. Assessing the past and future distribution and productivity of ponderosa pine in the Pacific Northwest using a process model, 3-PG. Ecol. Model. 2005, 183:107-124.
19. Coops N.C., Hember R.A., Waring R.H. Assessing the impact of current and projected climates on Douglas-Fir productivity in British Columbia, Canada using a process-based model (3-PG). Can. J. For. Res. 2010, 40:511-524.
20. Crescente-Campo F., Soares P., Tomé M., Dieguez-Aranda U. Modelling annual individual-tree growth and mortality of Scots pine with data obtained at irregular measurement intervals and containing missing observations. For. Ecol. Manage. 2010, 260:1965-1974.
21. Cropper W.P., Gholz H.L. Simulation of the carbon dynamics of a Florida slash pine plantation. Ecol. Model. 1993, 66:213-249.
22. Cropper W.P. SPM2: A simulation model for slash pine (Pinus elliottii) forests. For. Ecol. Manage. 2000, 126:201-212.
23. Dalla-Tea F., Jokela E.J. Needlefall, canopy light interception, and productivity of young intensively managed slash and loblolly pine stands. For. Sci. 1991, 37:1298-1313.
24. Dye P.J. Modelling growth and water use in four Pinus patula stands with the 3-PG model. South. Afr. For. J. 2001, 191:53-64.
25. Dye P.J., Jacobs S., Drew D. Verification of 3-PG growth and water-use prediction in twelve Eucalyptus plantation stands in Zululand, South Africa. For. Ecol. Manage. 2004, 193:197-218.
26. Dye P.J., Olbrich B.W. Estimating transpiration from 6-year-old Eucalyptus grandis trees: development of a canopy conductance model and comparison with independent sap flux measurements. Plant, Cell Environ. 1993, 16:45-53.
27. Flores F.J., Allen H.L. Efectos del clima y capacidad de almacenamiento de agua del suelo en la productividad de rodales de pino radiata en Chile: un análisis utilizando el modelo 3-PG. Bosque 2004, 25:11-24.
28. Fontes L., Landsberg J., Tomé J., Tomé M., Pacheco C.A., Soares P., Araujo C. Calibration and testing of a generalized process-based model for use in Portuguese Eucalyptus plantations. Can. J. For. Res. 2006, 36:3209-3221.
29. Gibson, M.O., McMillin, C.W., Shoulders, E., 1985. Preliminary results for weight and volume of even-aged, unthinned, planted southern pines on three sites in Louisiana. In: Saucier, J.R. (Ed.), Proceeding of Southern Forest Biomass Workshop Athens, GA, June 5-7, 1984, pp. 69-74.
30. Gibson M.O., McMillin C.W., Shoulders E. Moisture content and specific gravity of the four major southern pines under the same age and site conditions. Wood Fiber Sci. 1986, 18:428-435.
31. Gholz H.L., Fisher R.F. Organic matter production and distribution in slash pine (Pinus elliottii) plantations. Ecology 1982, 63:1827-1839.
32. Gholz H.L., Perry C.S., Cropper W.P., Hendry L.C. Litterfall, decomposition and N and P immobilization in a chronosequence of slash pine (Pinus elliottii) plantations. For. Sci. 1985, 31:463-478.
33. Gholz H.L., Hendry L.C., Cropper W.P. Organic matter dynamics of fine roots in plantations of slash pine (Pinus elliottii) in north Florida. Can. J. For. Res. 1986, 16:529-538.
34. Gholz H.L., Vogel S.A., Cropper W.P., McKelvel K., Ewel K.C. Dynamics of canopy structure and light interception in Pinus elliottii stands, North Florida. Ecol. Monog. 1991, 61:33-61.
35. Gholz H.L., Clark K.L. Energy exchange across a chronosequence of slash pine forests in Florida. Agric. For. Meteorol. 2002, 112:87-102.
36. Gonzalez-Benecke C.A., Martin T.A., Cropper W.P. Hydraulic architecture and tracheid allometry in mature Pinus palustris and Pinus elliottii trees. Tree Physiol. 2010, 30:361-375.
37. Gonzalez-Benecke C.A., Martin T.A., Jokela E.J., De La Torre R. A Flexible Hybrid Model of Life Cycle Carbon Balance for Loblolly Pine (Pinus taeda L.) Management Systems. Forests 2011, 2:749-776.
38. Gonzalez-Benecke C.A., Jokela E.J., Martin T.A. Modelling the effects of stand development, site quality and silviculture on leaf area index, litterfall, and forest floor accumulation in loblolly and slash pine plantations. For. Sci. 2012, 58:457-471.
39. Gonzalez-Benecke C.A., Gezan S.A., Albaugh T.J., Allen H.L., Burkhart H.E., Jokela E.J., Maier C.A., Martin T.A., Rubilar R.A., Samuelson L.J. Local and general above-stump biomass functions for loblolly and slash pine trees. For. Ecol. Manage. 2014, (In Review).
40. Gonzalez-Benecke C.A., Gezan S.A., Samuelson L.J., Cropper W.P., Leduc D.J., Martin T.A. Estimating Pinus palustris tree diameter and stem volume from tree height, crown area and stand-level parameters. J. For. Res. 2014, 25:43-52.
41. Harding, K.L., 2008. Resource characterization of slash pine plantation wood quality. Project Report, Forest and wood products Australia, p. 22.
42. Harding R.B., Jokela E.J. Long-term effects of forest fertilization on site organic matter and nutrients. Soil Sci. Soc. Am. J. 1994, 58:216-221.
43. Hodge G.R., Punell R.C. Genetic parameter estimates for wood density, transition age, and radial growth in slash pine. Can. J. For. Res. 1993, 23:1881-11891.
44. Howard E.T. Physical and chemical properties of slash pine tree parts. Wood Sci. 1972, 5:312-317.
45. Jokela E.J., Martin T.A. Effects of ontogeny and soil nutrient supply on production, allocation and leaf area efficiency in loblolly and slash pine stands. Can. J. For. Res. 2000, 30:1511-1524.
46. Jokela E.J., Wilson D., Allen J.E. Early growth responses of slash and loblolly pine following fertilization and herbaceous weed control treatments at establishment. South J. Appl. For. 2000, 24:23-30.
47. Jokela E.J., Martin T.A., Vogel J.G. Twenty-five Years of intensive forest management with southern pines: Important lessons learned. J. For. 2010, 108:338-347.
48. Kelliher F.M., Leuning R., Raupach M.R., Shulze E.D. Maximum conductances for evaporation for global vegetation types. Agric. For. Meteorol. 1995, 73:1-16.
49. Kinerson R., Higginbotham K.O., Chapman R.C. The dynamics of foliage distribution within a forest canopy. J. Appl. Ecol. 1974, 11:347-353.
50. Landsberg J.J., Waring R.H. A generalized model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. For. Ecol. Manage. 1997, 95:209-228.
51. Landsberg J.J., Johnsen K.H., Albaugh T.J., Allen H.L., McKeand S.E. Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments. For. Sci. 2001, 47:43-51.
52. Landsberg J.J., Waring R.H., Coops N.C. Performance of the productivity model 3-PG applied to a wide range of forest types. For. Ecol. Manage. 2003, 172:199-214.
53. Landsberg J.J., Sands P.J. Physiological Ecology of Forest Production: Principles, Processes and Modelling 2011, Elsevier Inc., Oxford, UK, pp. 241-282.
54. Law B.E., Waring R.H., Anthoni P.M., Aber J.D. Measurements of gross and net productivity and water vapor exchange of a Pinus ponderosa ecosystem, and an evaluation of two generalized models. Global Change Biol. 2000, 6:155-168.
55. Liu S., Riekerk H., Gholz H.L. Leaf litterall, leaf area index, and radiation transmittance in cypress wetlands and slash pine plantations in north-central Florida. Wetlands Ecol. Manage. 1997, 4:257-271.
56. Lowertz, G.A., Zoerb, M.H., 1989. Variation of slash pine wood specific gravity in different progeny test environments. In: Proceeding of the 20th Southern Forest Tree Improvement Conference, Charleston, SC, June 26-30, 1989, pp. 235-241.
57. Manis S.V., 1977. Biomass and nutrient distribution within plantation and natural slash pine stands on wet coastal sites. MSc. Thesis, University of Florida, Gainesville, FL, USA.
58. Miller, S.R., 1959. Variation in inherent wood characteristics in slash pine. In: Proceeding of the 5th Southern Forest Tree Improvement Conference, Raleigh, NC, June 11-12, 1959, pp. 97-106.
59. Muñoz Del Valle P.R., Hiber D.A., Martin T.A. Relative contributions of crown and phenological traits to growth of a pseudo-backcross pine family ((slash×loblolly)×slash) and its pure species progenitors. Tree Gen. Genom. 2012, 8:1281-1292.
60. Neter, J., Kutner, M.H., Nachtsheim, C.J., Wasserman, W., 1996. Applied Linear Statistical Models. Irwin, fourth ed., 1996, 770 p.
61. Pérez-Cruzado C., Munóz-Sáez F., Riesco G., Rodríguez-Soalleiro R. Combining empirical models and the process-based model 3-PG to predict Eucalyptus nitens plantations growth in Spain. For. Ecol. Manage. 2011, 262:1067-1077.
62. Perry, C.S. 1983. Litterfall, decomposition and N and P immobilization in a chronosequence of slash pine (Pinus elliottii) plantations, M.S. thesis, Univ. of Florida, Gainesville, FL.
63. Pienaar, L.V., Rheney, J.W., 1993. A test for PMRC slash pine volume equations for intensively managed plantations. PMRC Technical, Report 1993-1. 10 p.
64. Pienaar, L.V., Shiver, B.D., Rheney, J.W., 1996. Yield prediction for mechanically site-prepared slash pine plantations in the southeastern coastal plain. PMRC Technical, Report 1996-3. 57 p.
65. Pinjuv G., Mason E.G., Watt M. Quantitative validation and comparison of a range of forest growth model types. For. Ecol. Manage. 2006, 236:37-46.
66. Powell T.L., Starr G., Clark K.L., Martin T.A., Gholz H.L. Ecosystem and understory water and energy exchange for amature, naturally regenerated pine flatwoods forest in North Florida. Can. J. For. Res. 2005, 35:1568-1580.
67. Powers R.F., Scott D.A., Sanchez F.G., Voldseth R.A., Page-Dumroese D., Elliof J.D., Stone D.M. The North American long-term soil productivity experiment: findings from the first decade of research. For. Ecol. Manage. 2005, 220:31-50.
68. Pretzsch H., Matthew C., Dieler J. Allometry of tree crown structure. Relevance for space occupation at the individual plant level and for self-thinning at the stand level. Growth and Defence in Plants 2012, 287-310. Springer. Matyssek (Ed.).
69. Radtke P.J., Burkhart H.E. Basal area growth and crown closure in a loblolly pine spacing trial. For. Sci. 1999, 45:35-44.
70. Reineke L.H. Perfecting a stand-density index for even-aged forest. J. Agric. Res. 1933, 46:627-638.
71. Rodríguez R., Espinosa M., Real P., Inzunza J. Productivity analysis of radiata pine plantations under different silvicultural regimes using the 3-PG process-based model. Aust. For. J. 2002, 65:165-172.
72. Rodríguez R., Real P., Espinosa M., Perry D.A. A process-based model to evaluate site quality for Eucalyptus nitens in the Bio-Bio Region of Chile. Forestry 2009, 82:149-162.
73. Roth B.E., Jokela E.J., Martin T.A., Huber D.A., White T.L. Genotype x environment interactions in selected loblolly and slash pine plantations in the Southeastern United States. For. Ecol. Manage. 2007, 238:175-188.
74. Sampson D.A., Waring R.H., Maier C.A., Gough C.M., Ducey M.J., Johnsen K.H. Fertilization effects on forest carbon storage and exchange, and net primary production: a new hybrid process model for stand management. For. Ecol. Manage. 2006, 221:91-109.
75. Sanchez F.G., Scott D.A., Ludovici K.H. Negligible effects of severe organic matter removal and soil compaction on loblolly pine growth over 10 years. For. Ecol. Manage. 2006, 227:145-154.
76. Sands, P.J., 2004. Adaptation of 3-PG to novel species: guidelines for data collection and parameter assignment. Technical Report 141, CRC for Sustainable Production Forestry, Hobart, Australia, 34 p.
77. Sands, P.J., 2010. 3PGPJS user manual, 27 p.
78. Sands P.J., Landsberg J.J. Parameterization of 3-PG for plantation-grown Eucalyptus globulus. For. Ecol. Manage. 2002, 163:273-292.
79. Shan J., Morris L.A., Hendrick R.L. The effects of management on soil and plant carbon sequestration in slash pine plantations. J. Appl. Ecol. 2001, 38:932-941.
80. Smith, J.E., Heath, L.S. 2002. A model of forest floor carbon mass for United States forest types. US For. Serv. Res. Paper NE-722. Northeastern Research Station, Newtown Square, PA. 37 p.
81. Sohn, S.I., Goddard, R.E., 1974. Genetic study of wood specific gravity in slash pine. In: Proceeding of the 22nd Northeastern Forest Tree Improvement Conference, Syracuse, NY, August 7-9, 1974, pp. 61-72.
82. Stape J.L., Binkley D., Ryan M.G. Testing the utility of the 3-PG model for growth of Eucalyptus grandis x urophylla with natural and manipulated supplies of water and nutrients. For. Ecol. Manage. 2004, 193:219-234.
83. Stape J.L., Binkley D., Ryan M.G. Production and carbon allocation in a clonal Eucalyptus plantation with water and nutrient manipulations. For. Ecol. Manage. 2008, 255:920-930.
84. Sun G., Alstad K., McNulty S.G., Myers J.A.M., Cohen E.C. Impacts of multiple stresses on water demand and supply across the southeastern United States. J. Am. Water Resour. Assoc. 2011, 44:1441-1457.
85. Swindel B.F., Neary D.G., Comerford N.B., Rockwood D.L., Blakeslee G.M. Fertilization and competition control accelerate early southern pine growth on flatwoods. Southern J. Appl. For. 1988, 12:116-121.
86. Teskey R.O., Gholz H.L., Cropper W.P. Influence of climate and nutrient availability on net photosynthesis of mature slash pine. Tree Physiol. 1994, 14:1215-1227.
87. Vogel J., Suau L.J., Martin T.A., Jokela E.J. Long-term effects of weed control and fertilization on the carbon and nitrogen pools of a slash and loblolly pine forest in north central Florida. Can. J. For. Res. 2011, 41:552-567.
88. Wang S., Yang Y., Trishchenko A.P. Modeling the response of canopy stomatal conductance to humidity. J. Hydrometeor. 2009, 10:521-532.
89. Waring R.H. A process model analysis of environmental limitations on growth of Sitka spruce plantations in Great Britain. Forestry 2000, 73:65-79.
90. Waring R., Nordmeyer A., Whitehead D., Hunt J., Newton M., Thomas C., Irvine J. Why is the productivity of Douglas-fir higher in New Zealand than in its native range in the Pacific Northwest, USA?. For. Ecol. Manage. 2008, 255:4040-4046.
91. Weiskittel A.R., Hann D.W., Kershaw J.A., Vanclay J.K. Forest Growth and Yield Modeling 2011, Wiley-Blackwell, Chicester, UK, 415 p. second edn.
92. Whitehead D., Hall G.M.J., Walcroft A.S., Brown K.J., Landsberg J.J. Analysis of the growth of rimu (Dacrydium cupressinum) in South Westland, New Zealand, using process based simulation models. Int. J. Biometeorol. 2002, 46:66-75.
93. Xenakis G., Ray D., Mencuccini M. Sensitivity and uncertainty analysis from coupled 3-PG and soil organic matter decomposition model. Ecol. Model. 2008, 219:1-16.
94. Xiao, Y., 2000. Crown structure, growth performance, nutritional characteristics, and their genetic parameter estimates in juvenile loblolly and slash pine, Ph.D. Dissertation. University of Florida, Gainesville, FL, 221 p.
95. Yin R., Pienaar L.V., Aronow M.E. The productivity and profitability of fiber farming. J. For. 1998, 96:13-18.
96. Zhao M.F., Xiang W.H., Peng C.H., Tian D.L. Simulating age-related changes in carbon storage and allocation in a Chinese fir plantation growing in southern China using the 3-PG model. For. Ecol. Manage. 2009, 257:1520-1531.