Growth decline assessment in Pinus sylvestris L. and Pinus nigra Arnold. forest by using 3-PG model.

Rafael M. Navarro-Cerrillo, Jesus Beira, Juan Suarez, Georgios Xenakis, Raúl Sánchez-Salguero, Rocío Hernández-Clemente

Abstract


Aim of the study: We assessed the ability of the 3-PG process-based model to accurately predict growth of Pinus sylvestris and P. nigra plantations across a range of sites, showing declining growth trends, in southern Spain.

Area of study: The study area is located in “Sierra de Los Filabres” (Almería).

Material and methods: The model was modified in fifteen parameters to predict diameter (DBH, cm), basal area increment (BAI, cm2 yr-1) and leaf area index (LAI, m2 m-2) in healthy trees and trees showing declining growth. We assumed that a set of specific physiological parameters (stem partitioning ratio-pFS20, maximum litterfall rate-γFx, maximum canopy conductance-gCx, specific leaf area for mature aged stands-σ1, age at which specific leaf area = ½ (σ0 + σ1), age at full canopy cover-tc, and canopy boundary layer conductance-gB) included in 3-PG would be suitable for predicting growth decline related to climate conditions. The calibrated model was evaluated using dendrochronological and LAI data obtained from plots.

Main results: Observed and simulated DBH showed a high correlation (R2 > 0.99) between modelled and measured values for both species. In contrast, modelled and observed BAI showed lower correlation (R2 < 0.68). Sensitivity analysis on 3-PG outputs showed that the foliage parameters - maximum litterfall rate, maximum canopy conductance, specific leaf area for mature aged stands, age at which specific leaf area, and age at full canopy cover - were important for DBH and BAI predictions under drought stress.

Research highlights: Our overall results indicated that the 3-PG model could predict growth response of pine plantations to climatic stress with desirable accuracy in southern Spain by using readily available soil and climatic data with physiological parameters derived from experiments.

Keywords: Hybrid process model; forest management models; growth prediction; Pinus spp, Parameterization; forest decline. 


Keywords


Hybrid process model; forest management models; growth prediction; Pinus spp, Parameterization; forest decline.

Full Text:

PDF HTML XML

References


References

Aguilar J, Simón M, Fernández J, García I, Milán JM, 1987. Mapa de Suelos. E 1: 100.000. Fiñana. Hoja 1012. LUCDEME. ICONA. Universidad de Granada. Madrid, Spain.

Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Kitzberger T, Rigling A, Breshears et al., 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecol Manag 259: 660–684. http://dx.doi.org/10.1016/j.foreco.2009.09.001

Almeida AC, Landsberg JJ, Sands PJ, 2004. Parameterisation of 3-PG model for fast-growing Eucalyptus grandis plantations. Forest Ecol Manag 193: 179–195. http://dx.doi.org/10.1016/j.foreco.2004.01.029

Almeida AC, Siggins A, Batista TR, Beadle C, Fonseca S, Loos R, 2010. Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG, a process-based growth model. Forest Ecol Manag 259: 1730-1740. http://dx.doi.org/10.1016/j.foreco.2009.10.008

Amichev BY, Hangs RD, van Rees KC, 2011. A novel approach to simulate growth of multi-stem willow in bioenergy production systems with a simple process-based model (3PG). Biomass Bioenerg 35(1): 473-488. http://dx.doi.org/10.1016/j.biombioe.2010.09.007

Beadle CL, Talbot H, Jarvis PG, 1982. Canopy structure and leaf-area index in a mature Scots pine forest. Forestry, 55: 105–123. http://dx.doi.org/10.1093/forestry/55.2.105

Beadle CL, Neilson RE, Talbot H, Jarvis PG, 1985a. Stomatal conductance and photosynthesis in a mature Scots pine forest 1 Diurnal, seasonal and spatial variation in shoots. J App Ecol 22: 557–571. http://dx.doi.org/10.2307/2403185

Beadle CL, Jarvis PG, Talbot H, Neilson RE, 1985b. Stomatal conductance and photosynthesis in a mature Scots pine forest 2 Dependence on environmental variables of single shoots. J App Ecol 22: 573–586. http://dx.doi.org/10.2307/2403186

Beadle CL, Talbot H, Neilson RE, Jarvis PG, 1985c. Stomatal conductance and photosynthesis in a mature Scots pine forest 3 Variation in canopy conductance and canopy photosynthesis. J App Ecol 22: 587–595. http://dx.doi.org/10.2307/2403187

Breda N, Huc R, Granier A, Dreyer E, 2006. Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Ann For Sci 63: 625–644. http://dx.doi.org/10.1051/forest:2006042

Breshears DD, Myers OB, Meyer CW, Barnes FJ, Zou CB, Allen CD, McDowell NG, Pockman WT, 2009. Tree die-off in response to global-change type drought: Mortality insights from a decade of plant water-potential measurements. Frontiers Ecol Environ 7: 185-189. http://dx.doi.org/10.1890/080016

Bryars C, Maier C, Zhao D, Kane M, Borders B, Will R, Teskey R, 2013. Fixed physiological parameters in the 3-PG model produced accurate estimates of loblolly pine growth on sites in different geographic regions. Forest Ecol Manag 289: 501-514. http://dx.doi.org/10.1016/j.foreco.2012.09.031

Costa M, 2005. Los bosques ibéricos: una interpretación geobotánica. Ed. Planeta, Madrid.

Dobbertin M, 2005. Tree growth as indicator of tree vitality and of tree reaction to environmental stress: a review. Eur J For Res 124: 319–333. http://dx.doi.org/10.1007/s10342-005-0085-3

Dobbertin M, Brang P, 2001. Crown defoliation improves tree mortality models. For Ecol Manag 141: 271–84.

Dufrêne E, Bréda N, 1995. Estimation of deciduous forest leaf area index using direct and indirect methods. Oecologia, 104(2): 156-162. http://dx.doi.org/10.1007/BF00328580

Esprey LJ, Sands PJ, Smith CW, 2004. Understanding 3-PG using a sensitivity analysis. Forest Ecol Manag 193 :235–250. http://dx.doi.org/10.1016/j.foreco.2004.01.032

Fontes L, Bontemps JD, Bugmann H, van Oijen M, Gracia C, Kramer K, Lindner M, Rötzer T, Skovsgaard JP, 2010. Models for supporting forest management in a changing environment. Forest Systems 19: 8-29.

Galiano L, Martínez-Vilalta J, Lloret F, 2011. Carbon reserves and canopy defoliation determine the recovery of Scots pine 4 year after a drought episode. New Phytol 190: 750–759. http://dx.doi.org/10.1111/j.1469-8137.2010.03628.x

Gonzalez-Benecke CA, Jokela EJ, Cropper WP, Bracho R, Leduc DJ, 2014. Parameterization of the 3PG model for Pinus elliottii stands using alternative methods to estimate fertility rating, biomass partitioning and canopy closure. Forest Ecol Manag 327: 55–75. http://dx.doi.org/10.1016/j.foreco.2014.04.030

Grissino-Mayer HD, 2001. Evaluating crossdating, accuracy: a manual and tutorial for the computer program COFECHA. Tree-Ring Res 57: 205–221.

Guada G, Camarero JJ, Sánchez-Salguero R, Navarro Cerrillo RM, 2016. Limited growth recovery after drought-induced forest dieback in very defoliated trees of two pine species. Front Plant Sci, 7: 418. http://dx.doi.org/10.3389/fpls.2016.00418

Hernandez-Clemente R, Navarro-Cerrillo RM, Suarez L, Morales F, Zarco-Tejada PJ, 2011. Assessing structural effects on PRI for stress detection in conifer forests. Remote Sens Environ 115: 2360–2375. http://dx.doi.org/10.1016/j.rse.2011.04.036

Landsberg JJ, 1986. Physiological ecology of forest production. Academic Press, London, UK.

Landsberg JJ, Johnsen KH, Albaugh TJ, Allen L, McKeand SE, 2001. Applying 3-PG, a simple process-based model designed to produce practical results, to data from Loblolly pine experiments. For Sci 47: 43–51.

Landsberg JJ, Waring RH, 1997. A generalized model of forest productivity using simplified concepts of radiation – use efficiency, carbon balance and partitioning. Forest Ecol Manag 95: 209 – 228. http://dx.doi.org/10.1016/S0378-1127(97)00026-1

Landsberg JJ, Mäkelä A, Sievänen R, Kukkola M, 2005. Analysis of biomass accumulation and stem size distributions over long period in managed stands of Pinus sylvestris in Finland using the 3-PG model. Tree Physiol 25: 781–792. http://dx.doi.org/10.1093/treephys/25.7.781

Landsberg JJ, Sands P, 2010. Physiological ecology of forest production: principles, processes and models. Vol. 4. Academic Press.

Martín-Benito D, del Río M, Heinrich I, Helle G, Cañellas I, 2010. Response of climate-growth relationships and water use efficiency to thinning in a Pinus nigra afforestation. Forest Ecol Manag 259: 967–975. http://dx.doi.org/10.1016/j.foreco.2009.12.001

McDowell NG, Pockman WT, Allen CD, Breshears DD, Cobb N, Kolb T, Plaut J, Sperry J, West A, Williams DG et al., 2008. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytol 178: 719–739. http://dx.doi.org/10.1111/j.1469-8137.2008.02436.x

Medlyn BE, Duursma RA, Zeppel MJB, 2011. Forest productivity under climate change: a checklist for evaluating model studies. Wiley Interdisciplinary Reviews: Climate Change 2: 332-355. http://dx.doi.org/10.1002/wcc.108

Mencuccini M, Bonosi L, 2001. Leaf/sapwood area ratios in Scots pine show acclimation across Europe. Can J For Res 31: 442–456. http://dx.doi.org/10.1139/x00-173

Millar CI, Stephenson NL, Stephens SL, 2007. Climate change and forests of the future: managing in the face of uncertainty. Ecology Applications 17: 2145–2151. http://dx.doi.org/10.1890/06-1715.1

Montero G, Ruiz-Peinado R, Muñoz M, 2005. Producción de biomasa y fijación de CO2 por los bosques españoles. Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid, España.

Mueller-Dombois D, 1993. Biotic Impoverishment and Climate Change: Global Causes of Forest Decline? In Mueller-Dombois, D and Reinhard F.H. Professor. Forest Decline in the Atlantic and Pacific Region, pp 339-348.

Navarro-Cerrillo RM, Varo MA, Lanjeri S, Hernández Clemente R, 2007. Cartografía de defoliación en los pinares de pino silvestre (Pinus sylvestris L.) y pino salgareño (Pinus nigra Arn.) en la Sierra de los Filabres. Ecosistemas 16: 163–171.

Oleksyn J, Reich PB, Chalupka W, Tjoelker MG, 1999. Differential above- and below-ground biomass accumulation of European Pinus sylvestris populations in a 12-year-old provenance experiment. Scan J For Res 14: 7–17. http://dx.doi.org/10.1080/02827589908540804

Patenaude G, Milne R, van Oijen M, Rowland CS, Hill RA, 2008. Integrating remote sensing datasets into ecological modelling: a Bayesian approach. Int J Remote Sens 29(5): 1295-1315. http://dx.doi.org/10.1080/01431160701736414

Peñuelas J, Filella I, 2001. Responses to a warming world. Science, 294(5543): 793-795. http://dx.doi.org/10.1126/science.1066860

Pérez Cruzado C, Muñoz Sáez F, Basurco F, Riesco G, Rodríguez Soalleiro R, 2011. Combining empirical models and the process-based model 3-PG to predict Eucalyptus nitens plantation growth in Spain. Forest Ecol Manag 262 (6): 1067-1077. http://dx.doi.org/10.1016/j.foreco.2011.05.045

Retzlaff WA, Handest JA, O'Malley DM, McKeand SE, Topa MA, 2001. Whole-tree biomass and carbon allocation of juvenile trees of loblolly pine (Pinus taeda): influence of genetics and fertilization. Can J For Res 31(6): 960-970. http://dx.doi.org/10.1139/cjfr-31-6-960

Rodríguez-Suárez JA, Soto B, Iglesias ML, Diaz-Fierros F, 2010. Application of the 3PG forest growth model to a Eucalyptus globulus plantation in Northwest Spain. Eur J Forest Res 129(4): 573-583. http://dx.doi.org/10.1007/s10342-010-0355-6

Rosa D, Baños Moreno C, Mudarra Gómez JL, Barahona E, Moreira Madueño JM, Gago R, Ramos A, 1984. Catálogo de suelos de Andalucía. Junta de Andalucía, Sevilla, España.

Sampson DA, Waring RH, Maier CA, Gough CM, Ducey MJ, Johnsen KH, 2006. Fertilization effects on forest carbon storage and exchange, and net primary production: A new hybrid process model for stand management. Forest Ecol Manag 221: 91-109. http://dx.doi.org/10.1016/j.foreco.2005.09.010

Samuelson LJ, Johnsen K, Stokes T, 2004. Production, allocation, and stemwood growth efficiency of Pinus taeda L. stands in response to 6 years of intensive management. Forest Ecol Manag 192: 59-70. http://dx.doi.org/10.1016/j.foreco.2004.01.005

Sánchez-Salguero R, Navarro-Cerrillo RM, Camarero JJ, Fernández-Cancio Á, 2010. Drought-induced growth decline of Aleppo and maritime pine forests in south-eastern Spain. Forest Systems, 19: 458-470. http://dx.doi.org/10.5424/fs/2010193-9131

Sánchez-Salguero R, Navarro-Cerrillo RM, Camarero JJ, Fernández-Cancio A, 2012 a. Selective drought-induced decline of pine species in southeastern Spain. Climatic Change 113: 767-785. http://dx.doi.org/10.1007/s10584-011-0372-6

Sánchez-Salguero R, Navarro-Cerrillo RM, Swetnam TW, Zavala MA, 2012 b. Is drought the main decline factor at the rear edge of Europe? The case of southern Iberian pine plantations. Forest Ecol Manag 271: 158–169. http://dx.doi.org/10.1016/j.foreco.2012.01.040

Sánchez-Salguero R, Camarero J, Dobbertin M, Fernández-Cancio A., Vilà-Cabrera A., Manzanedo R, Zavala M, Navarro-Cerrillo RM, 2013. Contrasting vulnerability and resilience to drought-induced decline of densely planted vs. natural rear-edge Pinus nigra forests, Forest Ecol Manag 15: 956-967. http://dx.doi.org/10.1016/j.foreco.2013.09.050

Sands PJ, 2004. Adaptation of 3-PG to novel species: guidelines for data collection and parameter assignment. Technical Report. No. 141, CSIRO, CRC Sustainable Production Forestry, Hobart.

Sands PJ, Landsberg JJ, 2001. 3-PGpjs: a user interface for 3-PG, a forest growth model. Version IDs 3-PGpjs 2 beta. CSIRO.

Stape JL, Ryan M, Binkley D, 2004. Testing the utility of the 3-PG model for growth of Eucalyptus grandis x urophylla with natural and manipulated supplies of water and nutrients. Forest Ecol Manag 193: 219–234. http://dx.doi.org/10.1016/j.foreco.2004.01.031

Stokes MA, Smiley TL, 1996. An introduction to tree-ring dating. University of Arizona Press, Tucson, Arizona, USA.

Thornton PE, Running SW, 1999. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agr Forest Meteorol 93: 211-228. http://dx.doi.org/10.1016/S0168-1923(98)00126-9

Ung CH, Bernier PY, Raulier F, Fournier RA, Lambert MC, Régnière J, 2001. Biophysical site indices for shade tolerant and intolerant boreal species. Forest Sci 47: 83-95.

van Oijen M, Reyer C, Bohn F, Cameron D, Deckmyn G, Flechsig M, Härkönen S, Hartig F, Huth A, Kiviste A et al., 2013. Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe. Forest Ecol Manag 289: 255–268. http://dx.doi.org/10.1016/j.foreco.2012.09.043

Vanninen P, Ylitalo H, Sievänen R, Mäkelä A, 1996. Effects of age and site quality on the distribution of biomass in Scots pine (Pinus sylvestris L). Trees-Struct Funct 10: 231–238. http://dx.doi.org/10.1007/bf02185674

Vega-Nieva DJ; Tomé M; Tomé J; Fontes L; Soares P; Ortiz L; Basurco F; Rodríguez-Soalleiro R, 2013. Developing a general method for the estimation of fertility rating parameter of the 3-PG model: Application in Eucalyptus globulus plantations in Northwestern Spain. Can J For Res 43: 627–636. http://dx.doi.org/10.1139/cjfr-2012-0491

Williams AP, Allen CD, Macalady AK, Griffin D, Woodhouse CA, Meko DM, Swetnam TW, Rauscher SA, Seager R, Grissino-Mayer HD, 2013. Temperature as a potent driver of regional forest drought stress and tree mortality. Nature Climate Change 3: 292–297. http://dx.doi.org/10.1038/nclimate1693

Willmott CJ, 1981. On the validation of models Physiographic Plant Geography 2: 184-194.

Xenakis G, Ray D, Mencuccini M, 2008. Sensitivity and uncertainty from a coupled 3-PG and soil organic matter decomposition model. Ecol Model 219: 1-16. http://dx.doi.org/10.1016/j.ecolmodel.2008.07.020




DOI: 10.5424/fs/2016253-08610

Webpage: www.inia.es/Forestsystems