Access the full text.
Sign up today, get DeepDyve free for 14 days.
L. Galindo, J. Samaniego (2010)
La economía del cambio climático en América Latina y el Caribe: algunos hechos estilizados, 2010
H. Gholz (1982)
Environmental Limits on Aboveground Net Primary Production, Leaf Area, and Biomass in Vegetation Zones of the Pacific NorthwestEcology, 63
M. Benson, B. Myers, R. Raison (1992)
Dynamics of stem growth of Pinus radiata as affected by water and nitrogen supplyForest Ecology and Management, 52
A Neuenschwander (2010)
Neuenschwander, A (2010). El cambio climático en el sector silvoagropecuario de Chile. Fundación para la Innovación Agraria (FIA). Santiago.
E. Mason, Mathijs Diepstraten, Guy Pinjuv, J. Lasserre (2012)
Comparison of direct and indirect leaf area index measurements of Pinus radiata D. DonAgricultural and Forest Meteorology, 166
T. Albaugh, H. Allen, P. Dougherty, L. Kress, J. King (1998)
Leaf Area and Above- and Belowground Growth Responses of Loblolly Pine to Nutrient and Water AdditionsForest Science, 44
(2016)
Resource document
HL Gholz (1986)
Canopy development and dynamics in relation to primary production
R. Rubilar, H. Allen, José Álvarez, T. Albaugh, T. Fox, J. Stape (2010)
Silvicultural manipulation and site effect on above and belowground biomass equations for young Pinus radiataBiomass & Bioenergy, 34
John Roberts, T. Fujimori, D. Whitehead (1987)
Crown and Canopy Structure in Relation to Productivity.Journal of Applied Ecology, 24
M. Kirschbaum, M. Watt, A. Tait, A. Ausseil (2012)
Future wood productivity of Pinus radiata in New Zealand under expected climatic changesGlobal Change Biology, 18
J. Vose, P. Dougherty, J. Long, F. Smith, H. Gholz, P. Curran (1994)
Factors influencing the amount and distribution of leaf area of pine stands, 43
D. White, M. Battaglia, D. Mendham, D. Crombie, J. Kinal, J. McGrath (2010)
Observed and modelled leaf area index in Eucalyptus globulus plantations: tests of optimality and equilibrium hypotheses.Tree physiology, 30 7
V. Gerding, J. Schlatter (1995)
Variables y factores del sitio de importancia para la productividad de Pinus radiata D. Don en ChileBosque, 16
José Álvarez, H. Allen, T. Albaugh, J. Stape, B. Bullock, C. Song (2013)
Factors influencing the growth of radiata pine plantations in ChileForestry, 86
J Del Lungo (2006)
. Global planted forests thematic study: results and analysis. [Working Paper FP/38]. Rome: Forestry Department
(2017)
Changes in drought risk
T. Stow, H. Allen, L. Kress (1992)
Ozone impacts on seasonal foliage dynamics of young loblolly pineForest Science, 38
RA Rubilar (2010)
. Silvicultural manipulation and site effect on above and belowground biomass equations for young Pinus radiata. Biomass and Bioenergy
L. Richards (1941)
A PRESSURE‐MEMBRANE EXTRACTION APPARATUS FOR SOIL SOLUTIONSoil Science, 51
A. Lungo, J. Ball, J. Carle (2006)
Global planted forests thematic study. Results and analysis
S Linder (1987)
. Canopy dynamics and growth of Pinus radiata I. Effects of irrigation and fertilization during a drought. Canadian Journal of Forest Research
(1974)
Environmental variables influencing the increment of radiata pine (1) periodic volume increment
SW Gentle (1971)
Quantitative expression of site-index in terms of certain soil and climate characteristics of D. Don
R. Raison, B. Myers (1992)
The Biology of Forest Growth experiment: linking water and nitrogen availability to the growth of Pinus radiataForest Ecology and Management, 52
N. Breda (2003)
Ground-based measurements of leaf area index: a review of methods, instruments and current controversies.Journal of experimental botany, 54 392
M. Battaglia, M. Cherry, C. Beadle, P. Sands, A. Hingston (1998)
Prediction of leaf area index in eucalypt plantations: effects of water stress and temperatureTree Physiology, 18
G. Hargreaves, Z. Samani (1985)
Reference Crop Evapotranspiration from TemperatureApplied Engineering in Agriculture, 1
R. Cromer, D. Tompkins, N. Barr (1983)
Irrigation of Pinus radiata with waste water: tree growth in response to treatmentAustralian forest research, 13
S. Gower, K. Vogt, C. Grier (1992)
CARBON DYNAMICS OF ROCKY MOUNTAIN DOUGLAS-FIR: INFLUENCE OF WATER AND NUTRIENT AVAILABILITY'Ecological Monographs, 62
(1971)
Quantitative expression of siteindex in terms of certain soil and climate characteristics of Pinus radiata D. Don. Oddział: Plantations in Australia and New Zealand. Państwowe Wydawnictwo Naukowe
R. Rubilar, T. Albaugh, H. Allen, J. Álvarez, T. Fox, J. Stape (2013)
Influences of silvicultural manipulations on above- and belowground biomass accumulations and leaf area in young Pinus radiata plantations, at three contrasting sites in ChileForestry, 86
M. Cannell (1989)
Physiological basis of wood production: A reviewScandinavian Journal of Forest Research, 4
EG Mason (2012)
. Comparison of direct and indirect leaf area index measurements of Pinus radiata D. Don. Agricultural and Forest Meteorology
T. Albaugh, J. Álvarez, R. Rubilar, T. Fox, H. Allen, J. Stape, O. Mardones (2015)
Long-term Pinus radiata productivity gains from tillage, vegetation control, and fertilization.Forest Science, 61
S. Linder, M. Benson, B. Myers, R. Raison (1987)
Canopy dynamics and growth of Pinusradiata.: I. Effects of irrigation and fertilization during a droughtCanadian Journal of Forest Research, 17
R. Daniels, E. Gamble, L. Bartelli, L. Nelson (1968)
APPLICATION OF THE POINT‐COUNT METHOD TO PROBLEMS OF SOIL MORPHOLOGYSoil Science, 106
JM Vose (1994)
. Factors influencing the amount and distribution of leaf area of pine stands. Ecological Bulletins
R. Raison, B. Myers, M. Benson (1992)
Dynamics of Pinus radiata foliage in relation to water and nitrogen stress: I. Needle production and propertiesForest Ecology and Management, 52
U. Benecke (2004)
Photosynthesis and transpiration ofPinus radiata D. Don under natural conditions in a forest standOecologia, 44
F. Flores, H. Allen (2004)
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-PGBosque (valdivia), 25
L. Guo, R. Gifford (2002)
Soil carbon stocks and land use change: a meta analysisGlobal Change Biology, 8
RN Cromer (1983)
. Irrigation of Pinus radiata with waste water: tree growth in response to treatment. Australian Forest Research
New Zealand Forest Owners Association Inc. & New Zealand Farm Forestry Association Ministry for Primary Industries (2016)
//www.nzfoa.org.nz/images/stories/pdfs/2016-NEFD-report_web.pdf. Accessed 09 October 2017.
P. Jarvis, J. Leverenz (1983)
Productivity of temperate de-ciduous and evergreen forests
J. Vose, H. Allen (1988)
Leaf Area, Stemwood Growth, and Nutrition Relationships in Loblolly PineForest Science, 34
P. Beets, D. Pollock (1987)
ACCUMULATION AND PARTITIONING OF DRY MATTER IN PINUS RADIATA AS RELATED TO STAND AGE AND THINNING
D. Grey (1989)
Site Requirements of Pinus radiata: A ReviewSouth African forestry journal, 148
S. Linder (1987)
. Responses to water and nutrients in coniferous ecosystems (pp. 180–202). Springer-Verlag
M. Watt, D. Palmer, M. Kimberley, B. Hock, T. Payn, D. Lowe (2010)
Development of models to predict Pinus radiata productivity throughout New ZealandCanadian Journal of Forest Research, 40
S. Linder (1987)
Responses to Water and Nutrients in Coniferous EcosystemsEcological studies, 61
I. Hunter, A. Gibson (1984)
PREDICTING PINUS RADIATA SITE INDEX FROM ENVIRONMENTAL VARIABLES
B. Mullan (2005)
. Changes in drought risk with climate change. Prepared for Ministry for the Environment (NZ Climate Change Office) and Ministry of Agriculture and Forestry. NIWA Client Report: WLG2005–23. (National Institute of Water and Atmospheric Research
R. Team (2014)
R: A language and environment for statistical computing.MSOR connections, 1
NJ. Breda (2003)
. Ground‐based measurements of leaf area index: a review of methods
LM Galindo (2010)
algunos hechos estilizados. Revista Cepal.
DJ Mead (2013)
Food and Agriculture Organization of the United Nations.
(1977)
Leaf area of mature northwestern coniferous forests: relation to site water
Background: Pinus radiata D.Don has been established in a wide range of soils and climatic conditions, showing high variability in both leaf area and volume productivity. Previous research has shown that plantation yield is affected by water availability, but the majority of this work has been done in unthinned stands and provided little insight on the effect of water availability on the productivity of thinned plantations. In order to improve forest productivity for plantations under a climate change scenario, we must understand the effect of plantation management, including thinning on the relationships among available water, leaf area index, and productivity. The aim of this work is to evaluate the effect of site water availability on the leaf area production and consequent volume growth in thinned radiata pine plantations over a water availability gradient. Methods: The effect of site available water on leaf area production and consequent volume growth in thinned Pinus radiata plantations over a water availability gradient across five sites in central and southern-central Chile was determined. Results: Regression analysis revealed water deficit to be relatedtobothleafareaindex andvolumegrowthaccounting for 77 and 78% of the variation respectively. Eighty-one percent of the variation in volume growth was explained by the 3 −1 leaf area index. Results showed a growth efficiency of 5 m ha perunitofleafareaindex. Conclusions: Strong linear positive relationships between site water availability, leaf area, and stand growth after thinning found in this research suggest that water is the key factor controlling current productivity of radiata pine plantations across sites. A simple and robust water index that is well correlated with leaf area and stand annual volume growth allows for the construction of a simple predictive model that may support management decisions for radiata pine plantations. Keywords: Growth efficiency, Leaf area index, Pinus radiata, Productivity, Water deficit Background The productivity of this species is strongly influenced Radiata pine (Pinus radiata D.Don) is the most widely by site conditions (Grey 1989) and varies more than 3 −1 distributed of commercial pine species. There are more twofold from 12 to 34 m ha year in commercial plan- than 4 million ha planted with radiata pine in the world, tations (Del Lungo and Carle 2006; Álvarez et al. 2013). with the largest areas in New Zealand (1.7 million ha), Early work relating the growth of radiata pine to site and Chile (1.5 million ha), Australia (0.77 million ha), Spain climatic factors showed that rainfall and its seasonal dis- (0.29 million ha), and South Africa (57,000 ha) (Mead tribution, effective soil depth, total nitrogen, available 2013; Ministry for Primary Industries, New Zealand phosphorous, and temperature all affected productivity Forest Owners Association Inc. and New Zealand Farm (Jackson and Gifford 1974). Forestry Association 2016). Plantation available water, determined by rainfall and soil water holding capacity, is the main determinant of * Correspondence: hebertojeda@udec.cl; hojeda@arauco.cl both actual and potential radiata pine productivity in New Facultad de Ciencias Forestales, Universidad de Concepción, Victoria 631, Zealand (Jackson and Gifford 1974; Hunter and Gibson Barrio Universitario, Concepción, Chile 1984), Australia (Czarnowski et al. 1971), South Africa Bioforest S.A., Camino a Coronel km 15 s/n, Coronel, Chile Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 2 of 11 (Grey 1989), and Chile (Gerding and Schlatter 1995; These sites represent a gradient of climate and soils with Flores and Allen 2004). Álvarez et al. (2013) showed that known differences in productivity (Table 1). In 2000 or both water availability and evaporative demand were im- 2001, all sites were planted with radiata pine at an initial portant limits to the growth of the species in Chile. stocking of 1250 trees per hectare. Sites were labelled ac- Forest, including plantation, productivity is positively cor- cording to their average annual rainfall (833 mm, P800; related with leaf area index (LAI) (Jarvis and Leverenz 1078 mm, P1100; 1492 mm, P1500; 1683 mm, P1700; 1983;Linder 1987; Vose and Allen 1988; Álvarez et al. 1733 mm, P1750). Within each site, four 0.36-ha plots 2013)which determines therateofenergyand gas ex- were located on smooth hills with no drainage problems change (CO ,O ,and H O) between the forest canopy and and no signs of fungi, insects, or nutritional deficits. Plot 2 2 2 the atmosphere (Vose et al. 1994). The LAI is, in turn, af- locations were selected to cover the range of local vari- fected by the supply of nutrients and water and by ation in productivity. All plots had pre-planting weed temperature (Battaglia et al. 1998; White et al. 2010). control as well as 2 years of competition release after In many situations, especially in plantations where nutri- planting. Stands were thinned down to 800 trees per ha ent supply is adequate, available water is the primary deter- at the time at either age 6 or 7 years. Trees were re- minant of leaf area index and tree growth (Benecke 1980; moved from all diameter classes. Buffers that were 15 m Cromer et al. 1983; Linder et al. 1987;Raisonetal. 1992; wide were set aside around each plot, leaving measured Albaugh et al. 1998;Bensonetal. 1992; Rubilar et al. 2013). plots of 0.09 ha (30 × 30 m), which each contained 72 For instance, Rubilar et al. (2013) established a linear rela- trees. tion between LAI and stem growth in three stands of radiata pine, located in sites with different productivities, Tree foliage biomass finding that the growth efficiency (slope of this relation) At the time of thinning, foliage biomass was estimated was affected by water availability of the sites. Similar rela- on ten trees representing the diameter distribution for tions between LAI and productivity have been found by each stand. After, the diameter of tree stems, located at other researchers (Gower et al. 1992; Albaugh et al. 1998; 1.3 m above the ground (DBH), was measured; the sam- Guo and Gifford 2002). Strong correlations between LAI ple trees were cut at the ground line and divided into and water availability have been observed for a wide range stem, leaves, and branches. Branch diameter and dis- of forest types and climatic conditions (Grier and Running tance from the tree top were measured for all branches 1977;Gholz 1982). However, little information is available on each felled tree. Between 10 and 15 branches were on this important relationship for radiata pine plantations selected from each tree to cover the range of branch di- of intermediate ages and particularly for thinned stands. ameters on the felled trees. Foliage and branch tissues In recent decades in Chile, climatic trends have reduced were separated for each sampled branch and dried at water availability and resulted in more erratic rainfall 70 °C to a constant weight. within years and more frequent and severe summer Regression was used to derive a relationship between droughts; this has been associated with reduced forest foliage biomass from branch and both relative distance growth (Neuenschwander 2010). It is anticipated that this from the top and branch diameter as described by trend of reduced rainfall in temperate and Mediterranean Rubilar et al. (2010). The resultant relationship (Eq. 1) plantation zones will continue in the future (Mullan et al. was used to estimate foliage biomass for the other 2005;Galindo and Samaniego 2010; Neuenschwander branches. 2010; Kirschbaum et al. 2012). It is therefore important to lnðÞ 1000 Y þ 1¼ a þ b lnðÞ BD þ 1þ c quantify the effect of water availability on LAI and conse- i i quently stand growth. In order to improve forest product- RDFT þ 1 þ ε ð1Þ i i ivity for plantations under a climate change scenario, we must understand the effect of plantation management, in- where: cluding thinning on the relationships among available Y is the foliage biomass (g) at the ith branch water, LAI, and productivity. BD is branch diameter in cm at the ith branch The aim of this study was to evaluate the effect of site RDFT is the relative distance of insertion of the available water on leaf area production and consequent branch from the top of the tree (0.0–1.0) at the ith volume growth in thinned radiata pine plantations over a branch water availability gradient. ε is the error associated with the ith branch The total foliage biomass was then calculated as the Methods sum of the values for all branches. Finally, a model was Study area fitted between foliage biomass at the tree level and DBH Five sites were selected in central and southern-central for each site. The adjusted model (Eq. 2) has the follow- Chile between latitudes 35° S and 40°30′ S (Fig. 1). ing form: Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 3 of 11 Fig. 1 Location of the study areas in central and southern-central Chile βþb ðÞ j was estimated by dividing the projected leaf area by the bf ¼ α d þ ε ; ð2Þ ij i ij dry weight. The leaf area of each tree was estimated by where: multiplying the specific leaf area by the total dry weight bf is the leaf biomass of the ith tree in site j (kg) of the total foliage of each tree (Eq. 1). Leaf area index ij α, β are fixed parameters (LAI) was then estimated from the total sum of the en- d is the diameter of the ith tree (cm) tire estimated leaf area of all post-thinning remnant trees b is site-specific parameter at the plot, derived from the allometric equation de- ε is the model error scribed before, and divided by the total area of the plot. ij This estimate represents LAI for each stand. Although Specific leaf area and leaf area index the optical projection method used could produce some Five trees were selected at each site and 20 fascicles were bias compared to the displacement method in the esti- selected at random and removed from within each verti- mation of specific leaf area, the final leaf area values cal third of the tree canopy. Sampled fascicles were re- used in this study produced satisfactory relationships frigerated at − 1 °C until they were processed. The across the study sites. projected leaf area was estimated using an optical pro- jection system (LI-COR LI-3100C area meter, Li-Cor, Growth measurements Lincoln, NE, EE. UU.). Samples were oven-dried at 70 °C The height and diameter of all trees in each plot were until constant weight, and the specific leaf area of each measured immediately after thinning, during the Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 4 of 11 Table 1 Site and stand characteristics Site P800 P1100 P1500 P1700 P1750 Latitude 35°29′39″ S 37°58′48″ S 40°12′2″ S 37°37′6″ S 39°28′22″ S Longitude 72°14′8″ W 72°26′24″ W 73°10′26″ W 73°16′40″ W 72°53′8″ W Annual mean temperature (°C) 13.2 12.0 10.5 11.1 11.4 Annual mean precipitation (mm) 833 (25 years) 1078 (25 years) 1492 (25 years) 1683 (25 years) 1733 (25 years) Geology Metamorphic Old volcanic ash Old volcanic ash Metamorphic Recent volcanic ash Soil taxonomy Typical Rhodoxeralfs Typical Paleudalfs Typical Paleudults Rhodic Paleudults Typical Haplohumults Texture Clay Clay Clay Clay Silt-loam Organic matter (%) 1.2 3.9 6.8 4.2 11.1 pH 5.8 5.3 5.3 5.2 5.4 Age (year) 6 6 7 6 6 −1 Stocking before thinning (tree ha ) 1250 (16) 1093 (15) 1156 (13) 1074 (21) 1022 (22) −1 Stocking after thinning (tree ha ) 800 (0) 800 (0) 800 (0) 800 (0) 800 (0) Height (m) 8.7 (0.2) 9.5 (0.3) 7.9 (0.2) 8.6 (0.2) 8.3 (0.4) Diameter (cm) 10.9 (0.2) 13.6 (0.8) 15.3 (0.3) 14.6 (0.2) 13.9 (0.4) 2 −1 Basal area (m ha ) 7.7 (0.3) 11.9 (1.3)15(0.7) 13.6 (0.3) 12.6 (0.7) 3 −1 Volume (m ha ) 26.7 (1.2)45(6.3) 47.3 (2.6) 46.8 (1.7) 44.1 (4.1) Italicized data in parentheses indicate standard errors vegetative recess period (June) and 1 year later (period distance to the site location. Annual precipitation (AP) 2007–2008). The increment in diameter growth (IDG) was calculated from the total sum of the monthly pre- and the increment in height growth (IHG) were calcu- cipitation (August–July). For the estimation of reference lated as the difference between initial measurements and evapotranspiration of the sites, the method described by those after 1 year following thinning. The individual vol- Hargreaves and Samani (1985) was used. Annual water ume of each tree was estimated through a function de- deficit (WD) was calculated as the sum of the monthly veloped for young radiata pine used by Albaugh et al. deficits (when evapotranspiration is greater than annual (2015), Eq. (3): precipitation for the study period (Eq. 4)). WD ¼ ðÞ PP −ET ; when j ETjj > jPP ; ð4Þ i 0i 0i i V ¼ð−0:00214 þ 0:0000295 d þ 0:001349 ð3Þ i i i¼1 h þ 0:00002486 d h Þ; i i i where: −1 where: WD is the water deficit during the year (mm year ) 3 −1 V is the volume of the ith tree (m tree ) PP is the precipitation of the ith month i i −1 d is the diameter of the ith tree (cm) (mm month ) h is the height of the ith tree (cm) ET is the evapotranspiration of the ith month i 0i −1 Individual tree volumes were summed to obtain vol- (mm month ) ume per plot and then scaled at the hectare level. Peri- odic volume growth (IVG) was calculated by subtracting Soil water holding capacity the estimated volumes between measurement periods Soil water holding capacity (WSC) was estimated (2007–2008). through soil pits and soil sampling at each study site. Soil profile was evaluated up to 2 m depth on each plot. Climate information For each horizon, soil thickness was recorded and 400-g Daily precipitation and temperature values were ob- samples were obtained for laboratory determination of tained from meteorological weather stations located less permanent wilting point (PWP) and field capacity (FC) than 25 km from each site, belonging to the Chilean In- to estimate soil water retention capacity (Richards 1941). stitute of Agricultural Research and the Forestal Arauco Percentage of stones of each soil horizon was estimated S.A. Company. Monthly averages of air temperature and using the point-count method described by Daniels et al. precipitation were calculated as the average of all sta- (1968). The soil water holding capacity was defined in tions within 25 km weighted by the inverse of their Eq. 5 as: Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 5 of 11 regression models using IVG as the dependent variable WSC ¼ ðÞ FC −PWPðÞ D ðÞ 1−S ; ð5Þ i i i i and water variables (WDI, WD, and AP) and LAI as in- i¼0 dependent variables. In addition, we ran regressions using LAI as the dependent variable and water variables where: (WDI, WD, and AP) as independent variables. The as- WSC is the soil water holding capacity (mm) sumptions of the ANOVAS were checked by graphic FC is the soil water retention capacity at 0.33 bar of analysis (independence), Barlett test (homoscedasticity), the ith horizon (%) and Shapiro-Wilk test (normality). Adjusted regression PWP is the soil water retention capacity at 15 bar of models were diagnosed through graphical and analytical the ith horizon (%) analysis, verifying the assumptions of linearity (graphic D is the soil depth of the ith horizon (mm) analysis), normality (Kolmogorov-Smirnov test), homo- S is the volumetric percentage of stones of the ith scedasticity (Breusch-Pagan test), and residual independ- horizon (%) ence (Durbin-Watson test). Results are reported as significant where p < 0.05. All analyses were carried out Water deficit index using R software version 3.0.1 (R Core Team 2014). Water deficit index (WDI) was estimated as the differ- The relationships between the annual average ence between water deficit and soil water holding cap- temperature versus the growth and the leaf area were acity (Eq. 6): also explored, but their correlations presented values of r less than the water deficit; therefore, the water deficit WDI ¼ WD−WSC; ð6Þ presented a greater force in the determination of the re- where: sponse variable (IVG and LAI). WDI is the water deficit index during the year −1 (mm year ) Results −1 WD is the water deficit during the year (mm year ) Effect of water availability on leaf area 2 −2 WSC is the soil water holding capacity (mm) At the age of 6 years, the average LAI was 1.9 m m , 2 −2 Despite the lower within-site rainfall variation between with a range of 0.6 to 3.1 m m (Fig. 2). The significant the four replicates, water storage capacity was calculated differences between sites are presented in Table 3.The using intensive soil sampling within each plot, resulting LAI was larger at sites P1500 and P1750 being 3.3 and in a gradient of water deficit index within site. 3.7 times greater than P800 site respectively. The −1 AP varied between 972 and 1624 mm year across Statistical analysis the study sites. This was associated with a range of −1 We adjusted a nonlinear mixed effects model using 70 and − 751 mm year for the WDI and 285 and −1 maximum likelihood for the estimation of leaf biomass − 809 mm year for the WD (Table 3). The site of individual trees from diameter at breast height (Eq. 1), with the most severe water limitation was P800 site, show- depending on the study site (Table 2). ing the lowest AP and the most negative values for WD We performed analysis of variance (ANOVA) and and WDI from all the sites. The LAI had a positive linear multiple comparison test (Tukey) to evaluate differences relationship with AP, WD, and WDI (Fig. 2), showing the between sites in LAI, water variables (WDI, WD, and strongest correlation with the WDI (r = 0.91), followed by AP), and incremental growth post-thinning variables the WD (r = 88), and finally with AP (r =0.64). Adjusted (IVG, IDG, and IHG). We adjusted simple linear regression models between LAI and water variables Table 2 Parameters of the nonlinear model of mixed effects adjusted for maximum likelihood to predict leaf biomass of radiata pine Fixed effects Parameter Value Standard error Degrees of freedom t value p value α 0.0075 0.0025 44 3.0470 0.0039 β 2.6328 0.1289 44 20.4229 0.0000 Random effects Parameter Site P800 Site P1100 Site P1500 Site P1700 Site P1750 b − 0.1674 0.0898 0.0460 0.0640 − 0.0325 Schwarz’s Bayesian criterion Akaike information criterion Bayesian information criterion Log-likelihood value N 171.3124 178.9605 − 81.6562 50 Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 6 of 11 Fig. 2 Relationship between leaf area index and precipitation (a), water deficit (b), and water deficit index (c) for sites P800 (filled triangle), P1100 (filled square), P1500 (open circles), P1700 (filled circles), and P1750 (filled diamond) (Table 4)were highly significant(p < 0.003); 83, 77, and WDI (r = 0.83), and finally with AP (r =0.78). Adjusted re- 41% of the variation in LAI could be predicted with WDI, gression models between IVG and water variables (Table 3) WD, and AP respectively. were highly significant (p < 0.001) and 69, 78, and 60% of the variation in IVG could be explained by WDI, WD, and Effect of water availability on growth AP respectively. 3 −1 The IVG varied between 12.5 and 25.4 m ha (Fig. 3), and the volume and diameter growth varied significantly among sites (Table 3). The highest volume and diameter growth Effect of leaf area on growth was observed at the P1500 site, which showed 86 and 67% A positive and strong (r = 0.9) linear relation was found greater growth in volume and diameter respectively than between IVG and LAI (Fig. 4). The adjusted regression the site with lowest growth (P800). A positive linear relation model between IVG and LAI (Table 4) proved to be was found between IVG and WDI, and WD and AP (Fig. 3). highly significant (p < 0.001) and in addition showed that The best correlation was with WD (r = 0.89), then with 81% of the variation in IVG can be explained by LAI. Table 3 Averages of leaf area index (LAI), water deficit index (WDI), water deficit (WD), annual precipitation (AP), volume growth (IVG), diameter growth (IDG), and height growth (IHG) for study sites Site LAI WDI WD AP IVG IDG IHG 2 −2 −1 −1 −1 3 −1 (m m ) (mm year ) (mm year ) (mm year)(m ha ) (cm) (m) Mean P800 0.7 c − 723 d − 784 c 1002 e 13.1 b 1.5 c 1.5 a P1100 1.9 b − 382 c − 501 b 1103 d 20.3 a 1.9 bc 1.4 a P1500 2.3 ab − 212 b − 290 a 1623 a 24.4 a 2.5 a 1.4 a P1700 2.0 ab − 231 b − 326 a 1462 b 21.5 a 2.0 b 1.3 a P1750 2.6 a −75 a − 316 a 1322 c 22.0 a 2.2 ab 1.6 a Standard errors P800 0.03 19.76 17.56 25.03 0.41 0.08 0.08 P1100 0.27 8.75 9.33 1.53 1.63 0.11 0.01 P1500 0.13 0.60 2.19 0.59 0.39 0.14 0.05 P1700 0.04 9.14 2.17 4.16 1.05 0.08 0.10 P1750 0.17 2.59 4.41 7.24 0.61 0.05 0.04 n = 4. Different letters indicate significant differences (p < 0.05) between sites Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 7 of 11 Table 4 Linear regression models between leaf area index (LAI), volume growth (IVG) and water variables, water deficit index (WDI), water deficit (WD) and precipitation (AP), in the studied sites Model b b b Residual standard error R squared p value 0 1 2 IVG = b + b * WDI 25.2894* 0.0155* 2.42 0.69 < 0.001 0 1 IVG = b + b * WD 28.9730* 0.0197* 2.03 0.78 < 0.001 0 1 IVG = b + b * AP 1.9264 0.0141* 2.76 0.60 < 0.001 0 1 IVG = b + b * LAI 10.2873* 5.1907* 1.90 0.81 < 0.001 0 1 LAI = b + b * WDI 2.8767* 0.0029* 0.31 0.83 < 0.001 0 1 LAI = b + b * WD 3.4210* 0.0034* 0.36 0.77 < 0.001 0 1 LAI = b + b *AP − 0.7139 0.0020* 0.58 0.41 < 0.003 0 1 *Significance level of the parameter (p < 0.05) For the range of sites studied, a growth efficiency (slope and LAI (e.g., Grier and Running 1977; Gholz 1982; 3 −1 of regression line) of 5 m ha per LAI unit was found. Battaglia et al. 1998). However, our contribution relies on the simplification of these relationships using a water Discussion index that integrates the effects of rainfall, potential Effect of water availability on leaf area evaporation, and available soil water. Alvarez et al. In this study, LAI directly measured through destructive (2013) also used a water index which differs from our sampling were made because LAI estimates based on in- WDI because our index gives a greater weight to the direct methods can significantly underestimate LAI lack of water at the site (water deficit). values. Mason et al. (2012) showed that LAI-2000 under- In our study, correlations between WDI and AP with estimated LAI in radiata pine by 60% for low LAI values LAI in radiata pine were greater than those reported by and between 30 and 45% for high LAI values (depending Alvarez et al. (2013) in unthinned stands. We attributed on stocking). Furthermore, they showed that directly these differences to our lower range of stockings, our measured LAI was less well correlated with LAI esti- smaller climatic annual variability, and the use of mates from hemispherical images. Breda (2003) also destructive sampling to measure LAI instead of using in- showed that methods based on hemispherical photo- direct measurements (e.g., LI-COR LAI-2000 or remote graphs can also suffer from similar underestimation. sensing). Our observation that an increase in leaf area Using the strong gradient in soil moisture deficit occurs at sites with little or no water limitations is also across sites, we have shown strong relationships between supported by the Biology of Forest Growth (BFG) study soil water deficit, LAI, and volume increment. Our study in Australia. The BFG study, investigating radiata pine confirms previous findings about a positive linear rela- under irrigation, showed substantial increases in needle tionship between water availability (WDI, WD, and AP) size, and number of needles, and branch growth, which Fig. 3 Relationship between incremental volume growth 1 year post thinning and precipitation (a), water deficit (b), and water deficit index (c) for sites P800 (filled triangles), P1100 (filled squares), P1500 (open circles), P1700 (filled circles), and P1750 (filled diamonds) Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 8 of 11 et al. (2013) could be due to sampling age, effect of thin- ning, or method of LAI estimation. Effect of water availability on growth The level of water stress at any given site, indicated by the WDI, also showed a strong linear and positive rela- tion with IVG. This effect compares well with the one reported by many authors (Jackson and Gifford 1974; Cromer et al. 1983; Hunter and Gibson 1984; Raison and Myers 1992; Benson et al. 1992; Alvarez et al. 2013). In Chile, Flores and Allen (2004), using the 3-PG-process-based model, evaluated the factors limit- ing the potential productivity of radiata pine; they also found that the most limiting factor across sites was mean annual rainfall, which is highly consistent with the results of our study. Similar to LAI, IVG showed a stronger relationship with WD or WDI compared to AP models. Nevertheless, the use of AP, a simpler predictor variable as an indirect measure of site water availability, may be highly valuable for developing a model explain- ing stand growth after thinning across a broad gradient of sites with limited soil information. Site productivity relationships between IVG and either WDI or AP in our study were stronger than those found Fig. 4 Relationship between leaf area index and incremental volume by Alvarez et al. (2013) or Gerding and Schlatter (1995) growth 1 year post thinning for sites P800 (filled triangles), P1100 who observed significant relationships between AP and (filled squares), P1500 (open circles), P1700 (filled circles), and P1750 stand site index. Higher correlations observed in this (filled diamonds) study may be attributed to the use of annual information about both growth and water availability. Highest IVG increased stand LAI (Linder et al. 1987; Benson et al. values were observed in southern and coastal-southern 1992). sites, where greater water availability levels were found. Silvicultural treatments can also affect this relation- This is consistent with Alvarez et al. (2013) and Flores ship. For example, Rubilar et al. (2013) reported that and Allen (2004). LAI increased when weeds were controlled, increasing Lack of rainfall during summer in Chile (Mediterranean water availability of the site. In this regard, it is possible climate) results in severe water limitations for tree growth that the WDI could act as a surrogate of water competi- even on wetter sites; this is especially relevant in northern tion index accommodating weed competition as well as regions where radiata pine is planted. Greater growth nitrogen uptake. Variation in water availability is only values for radiata pine can be found in stands located in one of the potential site effects on the leaf area index. the foothills of the Andes and the southern coast where LAI can also be affected by nutrition (Linder et al. 1987; water deficit value is low. Cannell 1989; Raison et al. 1992; Albaugh et al. 1998), Both WD and WDI take into account the annual sea- light (Gholz 1982), air pollution (Stow et al. 1992), and sonal water availability (rainfall and evapotranspiration) temperature (Gholz 1986). allowing a better understanding of growth differences be- 2 −2 The LAI range observed in this study (0.6–3.1 m m ) tween radiata pine plantations growing at sites with con- is similar to the range reported by Rubilar et al. (2013) trasting water regimes such as Chile, South Africa, 2 −2 (0.51–3.13 m m ), who also estimated LAI through de- Australia, and New Zealand. Although an index that takes structive samples, in 4-year-old radiata pine on contrast- into account leaf area considering seasonal transpiration ing sites in Chile. Alvarez et al. (2013)reported LAI values could be more precise, the greater inference is given by 2 −2 between 1.2 and 3.7 m m using remote sensing tech- the large water differences between sites, which allows us niques in 11-year-old unthinned radiata pine plantations to explore that the WDI could be considered independent with an environmental range of sites similar to our study, of the leaf area. Our intention is to use a simple index that but the upper limit of their observations was slightly would allow practitioners in forest biometrics to add water greater than those found in this study. This small differ- balance components in an easy way to serve as an applied ence between the values in our study and those of Alvarez tool by being a proxy from the current water balance. Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 9 of 11 3 −1 Therefore, given the wide water gradient between sites, Results of our study show a slope of 5.2 m ha per unit our water deficit index proxy for a more complete water of LAI, which is within the range reported by Rubilar et balance sufficed the purpose. al. (2013) for younger unthinned stands and under the Undoubtedly, other factors will affect the LAI or growth mean value reported by Alvarez et al. (2013) for older response. In addition to water stress, other authors (Jackson unthinned stands showing larger growth rates. Changes and Gifford 1974; Hunter and Gibson 1984;Gerding and in the slope between LAI and CAI indicate differences Schlatter 1995;Wattetal. 2010; Alvarez et al. 2013)have in growth efficiency (GE) among stands. Increases in concluded that the variability found in growth is not only water and nutrient availability have shown increases in influenced by other climate variables, such as maximum GE for radiata pine (Linder et al. 1987; Raison and average growing season temperature and vapor pressure Myers 1992). Rubilar et al. (2013) presented large differ- deficit, but also by soil variables such as organic soil carbon, ences in GE in radiata pine between low fertility dry organic matter, and soil water holding capacity. Mean an- sands and medium fertility red clay sites sustaining simi- nual temperature, closely related to vapor pressure deficit, lar leaf area levels for younger stands. Sites in our study strongly influences evapotranspiration in Chile and both did not show nutritional limitations or low fertilities that variables decrease with latitude contrasting with precipita- affect growing trees, although the water gradient of the tion, which increases with latitude. Given the above, it can sites could have an impact on nutrients uptake. How- be argued concordance with the exposed by Alvarez et al. ever, and despite the large water gradient considered in (2013), who suggested temperature and vapor pressure def- our study, we were not able to observe differences in GE icit as the variables that mostly explain the growth of among stands. radiata pine plantations in Chile, also mean annual rainfall Although the focus of the research was on the water can be considered as a strong predictor alone. gradient of the sites, it should be noted that the soil types affect the water availability and hence leaf area and Effect of leaf area on growth tree growth. Among the soil characteristics that can The strong linear relationship between LAI and IVG is affect water availability and productivity, Gerding and consistent with the observation that both LAI and IVG Schlatter (1995) highlight the negative effect of sandy are well correlated with water availability. Interestingly, textures and high bulk density and the positive effect of although stands in this study were thinned at or near a higher soil water holding capacity, higher total volume canopy closure decreasing their maximum leaf area and of pores, and higher content of organic matter. The our study only consider records for one single growing types of soil present in this study, varied from meta- period, the observed relationship is similar to unthinned morphic to volcanic ashes, showing mostly clay soil tex- radiata pine stands reported in Australia, New Zealand, ture, the biggest differences that could affect water and Chile (Linder et al. 1987; Beets and Pollock 1987; availability between the sites, were related to the levels Raison and Myers 1992; Alvarez et al. 2013; Rubilar et of organic matter, depth, and soil water holding capacity. al. 2013) and also for unthinned Pinus taeda L. (Albaugh Metamorphic soils especially with low rainfall showed et al. 1998). the lowest values of organic matter and soil water hold- The adjusted regression model to estimate IVG from ing capacity; in addition, the metamorphic soils showed LAI (Table 3) showed a good fit (r = 0.81) similar to that to be the least deep; on the other hand, the soils of re- reported by Rubilar et al. (2013)(r >0.8) and above the cent volcanic ash showed the highest values of organic one shown by Alvarez et al. (2013)(r = 0.46). However, it matter and soil water holding capacity. should be noted that for a Mediterranean climate and Declines in spring-summer rainfall are expected in within the water gradient of sites presented in this re- areas where radiata pine is planted due to climate search, the leaf area is directly related to water stress. change in Chile (Galindo and Samaniego 2010). Our re- Similar relationships have also been shown in the litera- sults suggest that reductions in site water availability ture by process-based models considering the impact of may be expected to cause reductions in leaf area of site water availability on leaf area production and its effi- radiata pine plantations, which will cause significant ciency in growth. It should be noted that the leaf area productivity declines. A large challenge for foresters is could not only be affected by the water condition of the to implement thinning regime and better genetic mate- site, but also by other variables such as soil characteristics rials that may be more effective at utilizing water re- (nutritional, extreme textures) or other climatic variables sources as the most limiting factor underpinning forest (vapor pressure deficit, temperature) and biotic agents. productivity. The slope of the linear relationship between LAI and IVG, growth efficiency, represents the efficiency of cap- Conclusions tured light and its conversion into annual stand growth Strong linear positive relationships among site water (current annual increment or CAI) per unit of leaf area. availability, leaf area, and stand growth after thinning Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 10 of 11 suggest that water availability plays an important role on Research Cooperative, Warnell School of Forestry and Natural Resources, University of Georgia, EE. UU. predicting current productivity of radiata pine planta- JC Ph.D. is the Dean and Full Professor of Biometrics, Faculty of Forestry tions across sites. Sciences, University of Concepción, Chile. A simple and robust water index, which integrates the ME Ph.D. is the Emeritus Professor of Silviculture, Department of Forestry, Faculty of Forestry Sciences, University of Concepción, Chile. effects of rainfall, potential evaporation, and available soil water, is well correlated with leaf area and stand an- Ethics approval and consent to participate nual volume growth. This index allows the construction Not applicable for this section. of a simple predictive model that may support manage- Consent for publication ment decisions for radiata pine plantations. Not applicable for this section. The results of our study provide useful information for forest managers to estimate stand growth after thinning Competing interests The authors declare that they have no competing interests. of radiata pine plantations under an expected climate change scenario with reductions in site water availability for radiata pine plantations in Chile. Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in Further research should be carried out to establish published maps and institutional affiliations. relationships between site water availability and growth responses to other plantation management activities Author details Facultad de Ciencias Forestales, Universidad de Concepción, Victoria 631, such as stocking or pruning where the leaf area is also Barrio Universitario, Concepción, Chile. Bioforest S.A., Camino a Coronel km modified. 15 s/n, Coronel, Chile. Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green Street, EE.UU,, Athens, Georgia. Abbreviations ANOVA: Analysis of variance; AP: Annual precipitation; BFG: Biology of Forest Received: 5 July 2017 Accepted: 14 June 2018 Growth; CAI: Current annual increment; DBH: Diameter at breast height; GE: Growth efficiency; IDG: Diameter growth; IHG: Height growth; IVG: Volume growth; LAI: Leaf area index; WD: Annual water deficit; References WDI: Water deficit index; WSC: Soil water storage capacity Albaugh, TJ, Allen, HL, Dougherty, PM, Kress, LW, King, JS. (1998). Leaf area and above-and belowground growth responses of loblolly pine to nutrient and Acknowledgements water additions. Forest Science, 44(2), 317–328. We are grateful to Bioforest SA (Forestal Arauco) for sharing study Albaugh, TJ, Alvarez, J, Rubilar, RA, Fox, TR, Allen, HL, Stape, JL, Mardones, O. information, logistic, and financial support to this study. We also (2015). Long-term Pinus radiata productivity gains from tillage, vegetation acknowledge the support of the Forest Productivity Cooperative (FPC) at control, and fertilization. Forest Science, 61(4), 800–808. Universidad de Concepción (Chile) and the Plantation Management Research Álvarez, J,Allen, HL,Albaugh,TJ,Stape,JL,Bullock,BP,Song, C. (2013). Cooperative (PMRC) at University of Georgia (USA) for laboratory space and Factors influencing the growth of radiata pine plantations in Chile. equipment for data analysis. Forestry, 86(1), 13–26. Battaglia, M, Cherry, ML, Beadle, CL, Sands, PJ, Hingston, A. (1998). Prediction of Funding leaf area index in eucalypt plantations: effects of water stress and We acknowledge the generous funding from Bioforest S.A. (Forestal Arauco) for temperature. Tree Physiology, 18(8–9), 521–528. the complete realization of this research and Universidad de Concepción and Beets, PN, & Pollock, DS. (1987). Accumulation and partitioning of dry matter in MECESUP program (Project Code UCO14-10) for funding Mr. Hebert Ojeda’s Pinus radiata as related to stand age and thinning. New Zealand Journal of internship at University of Georgia. Forestry Science, 17(2), 246–271. Benecke, U. (1980). Photosynthesis and transpiration of Pinus radiata D. Don Availability of data and materials under natural conditions in a forest stand. Oecologia, 44(2), 192–198. The data belongs in full to Forestal Arauco S.A., and the results of this Benson, ML, Myers, BJ, Raison, RJ. (1992). Dynamics of stem growth of Pinus publication were authorized as a part of a PhD thesis project developed by radiata as affected by water and nitrogen supply. Forest Ecology and Mr. Hebert Ojeda at Universidad de Concepción. Any request to use the Management, 52(1–4), 117–137. original data for publication purposes requires a specific project proposal to Breda, NJ. (2003). Ground‐based measurements of leaf area index: a review of be approved by the company for any interested scientist in making use of methods, instruments and current controversies. Journal of Experimental the datasets. Botany, 54(392), 2403–2417. Cannell, MGR. (1989). Physiological basis of wood production: a review. Authors’ contributions Scandinavian Journal of Forest Research, 4(1–4), 459–490. HO was the primary author, undertook the analyses, and supervised the field Cromer, RN, Tompkins, D, Barr, NJ (1983). Irrigation of Pinus radiata with waste measurements. RR and CM contributed with the analyses and interpretation water: tree growth in response to treatment. Australian Forest Research, 13(1), of data, and JC and ME provided critical revisions of the manuscript. All 57–65. authors read and approved the final manuscript. Czarnowski, MS, Humpreys, FR, Gentle, SW (1971). Quantitative expression of site- index in terms of certain soil and climate characteristics of Pinus radiata D. Authors’ information Don. Oddział: Plantations in Australia and New Zealand. Państwowe HO is a researcher and Forest Management Program Leader of Bioforest, Wydawnictwo Naukowe. Forestal Arauco, Chile. He is a graduate of the Forest Sciences Ph.D. Graduate Daniels, RB, Gamble, EE, Bartelli, LJ, Nelson, LA. (1968). Application of the point- Program, Department of Forestry, Faculty of Forestry Sciences, University of count method to problems of soil morphology. Soil Science, 106(2), 149–152. Concepción, Chile. Del Lungo, J, & Carle, J (2006). Global planted forests thematic study: results and RR Ph.D. is an Associate Professor in Soils, Nutrition and Sustainable Forest analysis. [Working Paper FP/38]. Rome: Forestry Department, Food and Productivity and the Co-Director in Forest Productivity Cooperative, Department Agriculture Organization of the United Nations. of Forestry, Faculty of Forestry Sciences, University of Concepción, Chile. Flores, FJ, & Allen, H. (2004). Efectos del clima y capacidad de almacenamiento CM Ph.D. is an Associate Professor of Natural Resource Biometrics and de agua del suelo en la productividad de rodales de pino radiata en Chile: Timber Management and the Co-Director of Plantation Management un análisis utilizando el modelo 3-PG. Bosque (Valdivia), 25(3), 11–24. Ojeda et al. New Zealand Journal of Forestry Science (2018) 48:10 Page 11 of 11 Galindo, LM, & Samaniego, J (2010). La economía del cambio climático en América Stow, TK, Allen, HL, Kress, LW. (1992). Ozone impacts on seasonal foliage Latina y el Caribe: algunos hechos estilizados. Revista Cepal. dynamics of young loblolly pine. Forest Science, 38(1), 102–119. Gerding, V, & Schlatter, JE (1995). Variables y factores del sitio de importancia Vose, JM, & Allen, HL. (1988). Leaf area, stemwood growth, and nutrition para la productividad de Pinus radiata D. Don en Chile. Bosque, 16(2), 39–56. relationships in loblolly pine. Forest Science, 34(3), 547–563. Gholz, HL. (1982). Environmental limits on aboveground net primary production, Vose, JM, Dougherty, PM, Long, JN, Smith, FW, Gholz, HL, Curran, PJ (1994). leaf area, and biomass in vegetation zones of the Pacific Northwest. Ecology, Factors influencing the amount and distribution of leaf area of pine stands. 63(2), 469–481. Ecological Bulletins, 43, 102–114. Watt, MS, Palmer, DJ, Kimberley, MO, Höck, BK, Payn, TW, Lowe, DJ. (2010). Gholz, HL (1986). Canopy development and dynamics in relation to primary Development of models to predict Pinus radiata productivity throughout production, (pp. 224–242). Ibaraki, Japan: Crown and Canopy Structure in New Zealand. Canadian Journal of Forest Research, 40(3), 488–499. Relation to Productivity. Forestry Products Research Institute. White, DA, Battaglia, M, Mendham, DS, Crombie, DS, Kinal, J, McGrath, JF. (2010). Gower, ST, Vogt, KA, Grier, CC. (1992). Carbon dynamics of Rocky Mountain Observed and modelled leaf area index in Eucalyptus globulus plantations: tests Douglas-fir: influence of water and nutrient availability. Ecological of optimality and equilibrium hypotheses. Tree Physiology, 30(7), 831–844. Monographs, 62(1), 43–65. Grey, DC. (1989). Site requirements of Pinus radiata: a review. South African Forestry Journal, 148(1), 23–27. Grier, CG, & Running, SW. (1977). Leaf area of mature northwestern coniferous forests: relation to site water balance. Ecology, 58(4), 893–899. Guo, LB, & Gifford, RM. (2002). Soil carbon stocks and land use change: a meta analysis. Global Change Biology, 8(4), 345–360. Hargreaves, GH, & Samani, ZA. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1(2), 96–99. Hunter, IR, & Gibson, AR. (1984). Predicting Pinus radiata site index from environmental variables. New Zealand Journal of Forestry Science, 14(1), 53–64. Jackson, DS, & Gifford, HH. (1974). Environmental variables influencing the increment of radiata pine (1) periodic volume increment. New Zealand Journal of Forestry Science, 4,3–26. Jarvis, PG, & Leverenz, JW (1983). Productivity of temperate, deciduous and evergreen forests. In Physiological plant ecology IV (pp. 233–280).Berlin: Springer. Kirschbaum, MU, Watt, MS, Tait, A, Ausseil, AGE. (2012). Future wood productivity of Pinus radiata in New Zealand under expected climatic changes. Global Change Biology, 18(4), 1342–1356. Linder, S. (1987). Responses to water and nutrients in coniferous ecosystems (pp. 180–202). Springer-Verlag, Berlin. Linder, S, Benson, ML, Myers, BJ, Raison, RJ (1987). Canopy dynamics and growth of Pinus radiata I. Effects of irrigation and fertilization during a drought. Canadian Journal of Forest Research, 17(10), 1157–1165. Mason, EG, Diepstraten, M, Pinjuv, GL, Lasserre, JP (2012). Comparison of direct and indirect leaf area index measurements of Pinus radiata D. Don. Agricultural and Forest Meteorology, 166, 113–119. Mead, DJ (2013). Sustainable management of Pinus radiata plantations. Food and Agriculture Organization of the United Nations (FAO). Rome: Food and Agriculture Organization of the United Nations. Ministry for Primary Industries, New Zealand Forest Owners Association Inc. & New Zealand Farm Forestry Association (2016). Forest description as at 1 April 2016. [Resource document]. https://www.nzfoa.org.nz/images/stories/ pdfs/2016-NEFD-report_web.pdf. Accessed 09 October 2017. Mullan, B., Porteous, A., Wratt, D., & Hollis, M. (2005). Changes in drought risk with climate change. Prepared for Ministry for the Environment (NZ Climate Change Office) and Ministry of Agriculture and Forestry. NIWA Client Report: WLG2005– 23. (National Institute of Water and Atmospheric Research, Wellington). Neuenschwander, A (2010). El cambio climático en el sector silvoagropecuario de Chile. Fundación para la Innovación Agraria (FIA). Santiago. R Core Team. (2014). R: a language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org/. Raison, RJ, & Myers, BJ. (1992). The biology of forest growth experiment: linking water and nitrogen availability to the growth of Pinus radiata. Forest Ecology and Management, 52(1–4), 279–308. Raison, RJ, Myers, BJ, Benson, ML. (1992). Dynamics of Pinus radiata foliage in relation to water and nitrogen stress: I. Needle production and properties. Forest Ecology and Management, 52(1–4), 139–158. Richards, LA. (1941). A pressure-membrane extraction apparatus for soil solution. Soil Science, 51(5), 377–386. Rubilar, RA, Albaugh, TJ, Allen, HL, Alvarez, J, Fox, TR, Stape, JL. (2013). Influences of silvicultural manipulations on above-and belowground biomass accumulations and leaf area in young Pinus radiata plantations, at three contrasting sites in Chile. Forestry, 86(1), 27–38. Rubilar, RA, Allen, HL, Alvarez, JS, Albaugh, TJ, Fox, TR, Stape, JL (2010). Silvicultural manipulation and site effect on above and belowground biomass equations for young Pinus radiata. Biomass and Bioenergy, 34(12), 1825–1837.
New Zealand Journal of Forestry Science – Springer Journals
Published: Dec 1, 2018
You can share this free article with as many people as you like with the url below! We hope you enjoy this feature!
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.