Next Article in Journal
The Binary Moderating Effect of Forest New Quality Productive Forces on the Efficiency of Forest Ecosystem Services Value Realization
Previous Article in Journal
Vegetation Growth Carryover and Lagged Climatic Effect at Different Scales: From Tree Rings to the Early Xylem Growth Season
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 16
Issue 7
10.3390/f16071108
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genotypic Variability in Growth and Leaf-Level Physiological Performance of Highly Improved Genotypes of Pinus radiata D. Don Across Different Sites in Central Chile

by
Sergio Espinoza
1,*,
Marco Yáñez
2,
Carlos Magni
3,
Eduardo Martínez-Herrera
3,
Karen Peña-Rojas
4,
Sergio Donoso
4,
Marcos Carrasco-Benavides
5 and
Samuel Ortega-Farias
6
1
Departamento de Ciencias Forestales, Facultad de Ciencias Agrarias y Forestales, Universidad Católica del Maule, Av. San Miguel 3605, Talca 3460000, Chile
2
College of Forestry, Agriculture, and Natural Resources, University of Arkansas at Monticello, 110 University Ct, Monticello, AR 71656, USA
3
Centro Productor de Semillas y Árboles Forestales, Facultad de Ciencias Forestales y de la Conservación de la Naturaleza, Universidad de Chile, Avenida Santa Rosa 11365, La Pintana 8820808, Chile
4
Laboratorio de Bosques Mediterráneos, Facultad de Ciencias Forestales y de la Conservación de la Naturaleza, Universidad de Chile, Avenida Santa Rosa 11365, La Pintana 8820808, Chile
5
Departamento de Ciencias Agrarias, Facultad de Ciencias Agrarias y Forestales, Universidad Católica del Maule, Curicó 3340000, Chile
6
Research and Extension Center for Irrigation and Agroclimatology (CITRA), Faculty of Agricultural Sciences, Universidad de Talca, Talca 3460000, Chile
*
Author to whom correspondence should be addressed.
Forests 2025, 16(7), 1108; https://doi.org/10.3390/f16071108
Submission received: 26 May 2025 / Revised: 26 June 2025 / Accepted: 30 June 2025 / Published: 4 July 2025
(This article belongs to the Special Issue Water Use Efficiency of Forest Trees)
Browse Figures
Review Reports Versions Notes

Abstract

Pinus radiata D. Don is planted in South Central Chile on a wide range of sites using genetically improved genotypes for timber production. As drought events are expected to increase with ongoing climatic change, the variability in gas exchange, which could impact growth and water use, needs to be evaluated. In this study, we assessed the genotypic variability of leaf-level light-saturated photosynthesis (Asat), stomatal conductance (gs), transpiration (E), intrinsic water use efficiency (iWUE), and Chlorophyll a fluorescence (OJIP-test parameters) among 30 P. radiata genotypes (i.e., full-sib families) from third-cycle parents at age 6 years on three sites in Central Chile. We also evaluated tree height (HT), diameter at breast height (DBH), and stem index volume (VOL). Families were ranked for HT as top-15 and bottom-15. In the OJIP-test parameters we observed differences at the family level for the maximum quantum yield of primary PSII photochemistry (Fv/Fm), the probability that a photon trapped by the PSII reaction center enters the electron transport chain (ψEo), and the potential for energy conservation from photons captured by PSII to the reduction in intersystem electron acceptors (PIABS). Fv/Fm, PIABS, and ψEo ranged from 0.82 to 0.87, 45 to 95, and 0.57 to 0.64, respectively. Differences among families for growth and not for leaf-level physiology were detected. DBT, H, and VOL were higher in the top-15 families (12.6 cm, 8.4 m, and 0.10 m3, respectively) whereas Asat, gs, E, and iWUE were similar in both the top-15 and bottom-15 families (4.0 μmol m−2 s−1, 0.023 mol m−2 s−1, 0.36 mmol m−2 s−1, and 185 μmol mol m−2 s−1, respectively). However, no family by site interaction was detected for growth and leaf-level physiology. The results of this study suggest that highly improved genotypes of P. radiata have uniformity in leaf-level physiological rates, which could imply uniform water use at the stand-level. The family variation found in PIABS suggests that this parameter could be incorporated to select genotypes tolerant to environmentally stressful conditions.

1. Introduction

Pinus radiata D. Don is the most common introduced softwood plantation species growing in temperate zones of the Southern Hemisphere. It is also the fastest growing pine species on a global scale [1,2]. In Chile the species was first introduced in the early 1890s [3] and has been widely planted since then. It now occupies 1.24 million ha [4]. The genetic improvement of P. radiata started in the 1970s and has contributed to large increases in plantation productivity through the deployment of highly productive open- pollinated (half-sib), full-sib families, and clones. However, with changes in climate expected to continue [5,6], it is necessary to determine whether differences in productivity among genotypes of P. radiata across sites are related to physiological capacity. In other forest trees (e.g., poplar) a positive correlation has been observed between water use efficiency and productivity [7], but a lack of correlation between both traits has also been reported [8], attributed to specific differences between species and that differences in productivity were more associated to differences in leaf area rather than photosynthetic rate. Similarly, in Pinus taeda L. and Pinus elliottii Engelm., it has been reported that net photosynthesis did not explain differences in stand growth rates [9].
The deployment of less variable genotypes (i.e., full-sib families and clones) could contribute to a uniform stand-level water use [10,11,12]; however, field studies have met with limited success [13,14,15]. For example, Aspinwall et al. [16] tested the physiological performance among genetic groups of P. taeda with inherent differences in genetic diversity (i.e., half- and full-sibs families and clones), and found uniformity in photosynthesis, stomatal conductance, and intrinsic water use efficiency. Other studies in families of P. taeda and clones of P. radiata have also shown physiological uniformity across sites [17,18]. In Chile, Espinoza et al. [19] in a field trial with two-year-old seedlings of P. radiata found that Asat, gs, iWUE, and transpiration (E) did not differ between open- and control-pollinated families and suggested that breeding has impacted growth traits but not photosynthetic capacity. However, no studies have been conducted to investigate if highly improved genotypes exhibit uniformity in physiological performance across different sites. Similarly, a few studies have investigated the variability in Chlorophyll a fluorescence in advanced breeding genotypes (e.g., Bown et al. [20]). This technique has been used for more than 40 years as a selection criterion in different crops, as it enables numerous non-destructive and non-invasive experiments on plants to assess their photosynthetic properties in response to environmental conditions [21,22,23].
Despite the relevance of P. radiata in Chile and in the global economy [2], and the potential importance of physiological traits in water restricted environments, research concerning this species has provided insufficient information on physiological uniformity within highly productive and genetically improved genotypes. As climate change continues to increase the severity and variability of extreme weather events, the understanding of the physiological basis of growth uniformity in elite genotypes of P. radiata can contribute in screening highly productive and drought tolerant genotypes. In this study, we undertook an in situ field study at three sites in Central Chile to investigate differences in growth, leaf-level gas exchange, and Chlorophyll a fluorescence of improved P. radiata genotypes growing under different site conditions. This study aimed to evaluate the genotypic variability of growth and leaf-level physiological variables among 30 P. radiata full-sib families from third-cycle parents at age 6 years.

2. Materials and Methods

2.1. Sites

The data for the study were collected from P. radiata genetic field trials, named PC1801, PC1802, and PC1803, covering a total of 9.94 ha established in the winter of 2018 close to the towns of Cauquenes (35° S, 72° W), Laja (37° S, 72° W), and Quilleco (37° S, 72° W) in Central Chile (Table 1). The genetic trials were planted on Forestal Mininco land; thus, the company’s routine silvicultural treatments were applied. Site preparation consisted of subsoiling at up to 50 cm depth. Granular NPK fertilizer was applied by hand at the planting hole (Multicote™ 8M, at 25 g plant−1, Haifa Chemical Ltd., Haifa, Israel). The planted material consisted of seedlings raised from seed and obtained from 195 to 212 full-sib P. radiata families, i.e., with known mother and father trees. In total, 9675 seedlings were planted. All families were selected based on their superior growth performance from the Forestal Mininco Tree Improvement Program, which was based on progeny tests of third-cycle parents. The field experimental design was a randomized complete block with 15 blocks and one seedling per family per block (i.e., single-tree plot). Each block had from 195 to 212 families (Table 1). HT (m) and DBH (cm) were measured at three sites at age 6, before complete canopy closure. VOL (m3) was calculated as the product of HT and DBH squared.
With the aim of conducting physiological measurements on contrasting genotypes (genotypes with inherent small genetic variation were used) we selected a subsample of 30 families based on a simple phenotypic ranking built from average data for HT across sites. We selected 15 families from the top and 15 families from the bottom part of the ranking (i.e., 30 families × 3 blocks × 3 sites = 270 trees). During the sampling period, the orders of sample collection from the three blocks and families within each block were randomly selected. The same family was sampled in all three blocks in the three sites. The 30 families represent extreme differences in growth performance for the populations under study. In the top-15 families, HT, DBH, and VOL were 8.4 m, 12.6 cm, and 0.10 m3, respectively, whereas in the bottom-15 families, these values were 7.5 m, 11.5 cm, and 0.07 m3 for HT, DBH, and VOL.

2.2. Leaf-Level Physiological Measurements

Light-saturated photosynthesis, transpiration, and stomatal conductance were measured in January 2025 on clear and sunny days in the 30 selected families (30 families × 3 blocks × 3 sites = 270 trees) using a portable gas exchange meter (LI-6800, Li-Cor Biosciences, Lincoln, NE, USA). One fascicle (three needles) was excised from the lower-canopy branches exposed to full light and immediately placed in the LI-6800 cuvette (leaf area 6 cm2) under a light source (90% red and 10% blue) providing a photosynthetic photon flux density of 1800 mmol m−2 s−1. Studies in P. taeda indicated that photosynthesis of detached needles did not change within 20 min of removal and that irradiances of 1500–1600 µmol m−2 s−1 are a saturating light [16,27]. Thus, the level of irradiance applied was expected to exceed the light saturation point of P. radiata, so carbon assimilation rates are reported as light saturated (i.e., Asat). Intrinsic water use efficiency (iWUE) was calculated as Asat/gs. Gas-exchange measurements were corrected on a fascicle-area basis following Ginn et al. [28]. Briefly, the fascicles are assumed to have a cylindrical shape [29], with all the needles having the same cross-sectional dimensions. The diameter of each fascicle was measured in two dimensions using a digital caliper immediately after gas exchange measurements were completed, and the average of these two measurements was used to compute the all-sided leaf area enclosed in the LI-6800 cuvette. During all gas exchange measurements, CO2 gas concentration was set to 400 ppm, and relative humidity and temperature were matched to ambient conditions (25% and 25 °C, respectively). Measurements were conducted sequentially by block to partition diurnal environmental variation. Measurements per site were taken on two consecutive days between 10.00 and 12.00 h local time.

2.3. Chlorophyll Fluorescence

Chlorophyll a (Chl a) fluorescence transient was measured at 11.00 h local time with a modulated fluorimeter (OSp30+, Optisciences, Hudson, NH, USA) set for OJIP-test protocol. Needles attached to the tree were dark-adapted in clips for 30 min prior to measurements and later, Chl a fluorescence transients were measured. The transients were induced by 1 s illumination providing a maximum light intensity of 3500 μmol (photon) m−2 s−1. This light intensity was safe and allowed us to reach Fm and the OJIP seps were clearly revealed. The OSp30+ fluorimeter was at O (20 µs), J (2 ms), and I (30 ms) as the intermediate stage, and P (300 ms) as the peak. The data obtained were used in the OJIP-test to calculate the parameters of photosystem II (PSII) photochemistry. Concerning the entire list of OJIP-test parameters [30,31], we addressed our attention to the key parameters that are the major plant stress indicators [32,33], i.e., the maximum quantum yield of primary PSII photochemistry (Fv/Fm); the probability that a photon trapped by the PSII reaction center enters the electron transport chain (ψEo); the efficiency of electron flux through PSI to reduce the final acceptors of the electron transport chain (ΔVIP); and the potential for energy conservation from photons absorbed by PSII to the reduction in intersystem electron acceptors (PIABS). The other variables related to phenomenological fluxes (per cross-section, CS) and specific fluxes (per reaction center, RC) were excluded from the analyses.

2.4. Statistical Analyses

Analyses of variance were conducted to test whether there were significant differences among growth and physiological variables for families and sites. To meet the assumptions of normality and constant variances of the residuals, traits were transformed according to the Box–Cox transformation when appropriate. Where significant effects were observed (p < 0.05), post hoc means comparisons were conducted using Tukey’s comparison test. We assessed the performance of the families nested within the phenotypic ranking at different sites with the following model:
Y = μ + S + B(S) + F(R) + F(R) × S + ε
where Y is the observed phenotypic value, µ is the overall mean, S is the fixed effect of site, B(S) is the random effect of block nested within site (IID (0, σ2B(S))), F(R) is the fixed effect of family nested within the phenotypic ranking, F(R) × S is the interaction between family nested within the phenotypic ranking and site, and is ε the experimental random error N (0, σ2ε). Because the genotypes included in this study were selected based on previous assessments of productivity, and do not represent the productivity and physiological performance of a P. radiata population, the genotype effect was considered a fixed effect. We also explored the relationship between growth and physiological variables by means of the simple Pearson coefficient of correlation. All the statistical analyses were performed with SPSS version 21.0 software (SPSS Inc, Chicago, IL, USA).

3. Results

3.1. Differences in Growth Across Genotypes

We found differences for growth associated with the site and family (Table 2). Lower growth was found at site PC1803 (HT = 4.5 m, DBH = 6.5 cm), whereas HT and DBH at sites PC1801 and PC1802 averaged 8.2 m and 11.1 cm, respectively. In the top-15 families, the average for DBT, H, and VOL were 12.6 cm, 8.4 m, and 0.10 m3, while coefficients of variation were 40, 33 and 86% for the same traits. In the bottom-15 families, the average for DBT, H, and VOL were 11.5 cm, 7.5 m, and 0.07 m3, while coefficients of variation were 46, 37, 97% for DBT, H, and VOL, respectively. As expected, families from the top-ranking showed the highest growth, particularly families P02623, P02891, P02962, and P02983 (Figure 1). Families from the bottom-ranking were the poorest performers, particularly families P02884, P02895, and P03063.

3.2. Differences in Gas Exchange and Chl a Fluorescence for Genotypes Across Sites

Except for E, no differences in the gas exchange variables were found for all the factors analyzed (Table 3, Figure 2). E was higher on site PC1801 (0.52 mmol) and lower at site PC1803 (0.23 mmol). On the other hand, the variables related to photoprotective mechanisms of photosystem II, i.e., ΔVIP and ψEo, differed among sites and were higher at site PC1803 (ΔVIP = 0.21, ψEo = 0.61) and lower at sites PC1801 and PC1802 (average ΔVIP = 0.15, average ψEo = 0.58). Fv/Fm, ψEo, and PIABS differed among families and most of the variation was associated with family P02938 from the top part of the phenotypic ranking, which exhibited the highest Fv/Fm and PIABS (Figure 3A,B). Coefficients of variation for gas exchange and Chlorophyll a fluorescence traits were similar between the top-15 families and bottom-15 families (Table 4). In the analyses of correlation, we did not detect any significant relationship between HT and DBH with iWUE, gs, and Asat (Figure 4).

4. Discussion

The genetic materials in this study comprised 30 control-pollinated families that were tested across three sites for growth and foliar physiological traits. Other than our results, we found no studies concerning P. radiata that have explicitly compared physiological capacity among highly improved genotypes planted in contrasting sites. In P. taeda, it has been proposed that the performance of genotypes with high levels of genetic diversity (i.e., half-sib families) is stable across sites as it appears to buffer environmental heterogeneity, resulting in uniformity of physiological process rates and possibly stand-level resource assimilation [16,17]. Genotypes with less genetic diversity (i.e., full-sibs or clones) have shown genotype × environment interactions (e.g., Roth et al. [34]) but also, no genotypic variation for physiological performance has been found (e.g., Seiler and Johnson, and Yang et al. in P. taeda [35,36], Cregg 1994, Zhang and Marshall 1995 in Pinus ponderosa Dougl. ex Laws. and Pseudotsuga menziessii (Mirb.) Franco) [37,38]. Aspinwall et al. [16], by assessing full-sibs, half-sibs, and clones of P. taeda, found physiological uniformity among genetic groups. Asat ranged from 3.79 to 4.73 μmol m−2 s−1 and gs from 0.05 to 0.07 mol m−2 s−1. Similarly, Espinoza et al. [19] found similar results in physiological performance by assessing genotypes of P. radiata from the first to third generation of breeding. Asat ranged from 2.86 to 3.40 μmol m−2 s−1, E from 0.64 to 0.78 mmol m−2 s−1, and gs was 0.02 mol m−2 s−1 across breeding generations. The latter authors suggested that three cycles of selection and breeding of highly productive individuals resulted in more physiologically homogeneous genotypes. Moreover, all of the genotypes used in our study were coastal selections, and we might have found significant differences in physiology if we had compared genotypes adapted to a broader range of edaphic conditions. This has been the case of Pinus ponderosa L., in which crosses of coastal parents had significantly higher rates of Asat, gs, and E than crosses of coastal and interior source parents [39].
We detected no interaction between genotype × site for most leaf-level physiology traits, but we found family variation for important traits related to the efficiency of the photosynthetic apparatus. The Performance Index (PIABS); one of the most important parameters of Chl a fluorescence, which is related to plant vitality [40], was the most variable trait at the family level (Figure 3B). PIABS is a consolidated parameter summarizing the effects of light trapping (ABS/RC), the maximum quantum yield of PSII primary photochemistry (Fv/Fm), and the efficiency with which electrons are transferred beyond quinone QA in the electron transport chain (ψEo) [41]. In our study, families P02938, P02960, P03063, and P03035 showed higher values for PIABS (Figure 3B), which suggest that light trapping and electron transport beyond QA functions better in these families, conferring a superior physiological state under light, water, or heat stress conditions. This agrees with the growth of these families because families P02938, P02960, and P03035 were among the 15 families located in the superior part of the phenotypic ranking for HT. The parameter Fv/Fm was also variable at the family level, but all families exhibited values in the range of 0.78 to 0.82, which is considered free of stress [42].
The correlation analyses of growth with physiology indicated a lack of relationship similar to that reported by Marron et al., Monclus et al., and Bonhome et al. [43,44,45] in poplar; however, the top-15 families had HT, DBH, and VOL that was 15, 15, and 30% superior to that of the bottom-15 families. It may be possible that differences in growth were more associated with the leaf area than physiology. In P. taeda, it has been observed that differences in productivity among different sources were strongly correlated to differences in leaf area rather than photosynthetic rate [46,47]. In our study, by using the formula for crown growth (i.e., crown width = 0.75 + 0.2073 × DBH) developed by Leech [48] for P. radiata, we estimated that crown width was 3.34 ± 0.03 m in the top-15 families and 3.14 ± 0.03 m in the bottom-15 families (p < 0.05). This estimation of crown width could approximately indicate total leaf area and can partially explain why genotypes differed in growth but not in physiology. However, this approach has limitations and needs to be further investigated.
Our results suggest that improvement of gas exchange traits and their incorporation in breeding programs may necessitate estimations of physiological yield at the stand level and an understanding of seasonal and spatial patterns of physiological activity. If there is genetic variation in gas exchange traits, then it may only be expressed at specific times of the year [49,50] or under specific environmental conditions [13]. It seems that the incorporation of instantaneous measurements of gas exchange traits as a selection criterion in elite genotypes of P. radiata seems not promising, as it only provides a snapshot of photosynthesis in genotypes with lack of variability in physiological capacity. Furthermore, the genetic control of gas exchange traits seems to be under little genetic control in forest species [51]. The Chl a measurements have shown utility in screening forests trees for physiological capacity and productivity [23,52,53], and it has been demonstrated that they are under genetic control in forests species (e.g., Čepl et al. [54] in Pinus sylvestris L. and Xue et al. [55] in P. radiata). Chl a fluorescence has been widely used to investigate the function of photosynthetic systems under different environmental conditions, or between different species [56]. In our study, the family variation found in PIABS suggests that this parameter could be incorporated for screening families with superior plant vitality under stressful environmental conditions. The parameter Fv/Fm has also been investigated in a few studies in P. radiata but with contrasting results. Bown et al. [20] found lack of variability in five 1.5-year-old clones with different growth performance, whereas Xue et al. [55] reported the opposite by assessing 40 four-year-old clones of the species (20 improved and 20 unimproved clones).
The differences in growth and volume in the 30 tested elite genotypes of P. radiata in our study were not large, which suggest that the effect of advanced breeding has contributed to the deployment of genotypes that perform well across a wide range of environments. However, as drought events will become an important environmental factor affecting forest productivity, genetic improvement programs will have to reduce establishment failure in seasonally dry ecosystems by identifying and selecting genotypes more resistant to drought. In our study, families P02938, P02960, and P03035 exhibited high PIABS and growth. PIABS is sensitive to various environmental stresses, such as drought, temperature extremes, and nutrient deficiencies, and has been proposed as a tool to identify plants with higher stress tolerance [57]. Thus, these families could provide appropriate planting material for forest plantations under stressful environmental conditions in Central Chile. Genotypes in this study were tested at an age that can be considered approximately one-third of rotation age for ”early selection” in some conifers [58]; thus, it may be expected that this early performance could be correlated to the performance at an adult age.

5. Conclusions

Our findings indicate that highly improved genotypes of P. radiata exhibit lack of variability in the leaf-level physiological performance across the different sites tested in Central Chile. Under field test conditions, physiological uniformity was not consistently related to growth, which implies that factors other than Asat, gs, iWUE, and E explain differences in growth. Needle instantaneous gas exchange measurements are not a promising tool for screening superior performance in advanced breeding genotypes, but Chlorophyll a fluorescence parameters, particularly PIABS, have potential to assist in this task.

Author Contributions

Conceptualization, S.E., M.Y. and C.M.; methodology, S.E. and M.Y.; formal analysis, S.E.; writing—original draft preparation, S.E.; writing—review and editing, E.M.-H., K.P.-R., S.D., M.C.-B. and S.O.-F.; funding acquisition, S.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Agencia Nacional de Investigación y Desarrollo (ANID), Fondecyt Regular, grant number 1240449, to Sergio Espinoza. Project title: Using ground data and thermal imagery to assist the physiology-based selection of Pinus radiata.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The lead author is grateful to Forestal Mininco S.A. for in-kind support and providing the information on growth of trials and granting access to the families that were tested. Special thanks to Verónica Emhart, Lionel Rivera, Berta Rothen, and Alex Medina for their support in the identification of families to be studied. We thank the Laboratorio de Bosques Mediterráneos from the Universidad de Chile for providing us the LICOR LI-6800 for field measurements. Many thanks also go to Sebastian Casali, Miguel Quintanilla, and Nicolas Castillo, from the Universidad de Chile, for their assistance in collecting field data. We also thank John Gajardo from the Universidad Austral de Chile and Luis Apiolaza from the University of Canterbury for providing valuable comments on the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
HTHeight (m)
DBHDiameter at the breast height (cm)
VOLStem index volume (m3)
MAPMean annual precipitation (mm)
MATMean annual temperature (°C)
AsatLight-saturated photosynthesis (μmol m−2 s−1)
gsStomatal conductance (mol m−2 s−1)
ETranspiration (mmol m−2 s−1)
iWUEIntrinsic water use efficiency (μmol m−2 s−1 mol m−2 s−1)
Fv/FmQuantum yield of primary PSII photochemistry
PIABSPotential for energy conservation from photons absorbed by PSII to the reduction of intersystem electron acceptors
ΔVIPEfficiency of electron flux through PSI to reduce the final acceptors of the electron transport chain
ψEoProbability that a photon trapped by the PSII reaction center enters the electron transport chain

References

  1. McDonald, P.M.; Laacke, R.J. Pinus radiata D. Don. Monterey Pine. In Silvics of North America. Volume 1, Conifers. Agriculture Handbook; Burns, R., Honkala, B., Eds.; Department of Agriculture, Forest Service: Washington, DC, USA, 1990; pp. 433–441. [Google Scholar]
  2. Mead, D.J. Sustainable Management of Pinus radiata Plantations; Food and Agriculture Organization of the United Nations (FAO): Roma, Italy, 2013. [Google Scholar]
  3. Contesse, G.D. Apuntes y consideraciones para la historia del pino radiata en Chile. Bol. Acad. Chil. Hist. 1987, 97, 351–373. [Google Scholar]
  4. INFOR. Anuario Forestal 2024. Instituto Forestal, Chile. Boletín Estadístico N° 199. 2025. Available online: https://wef.infor.cl/index.php/publicaciones/boletines-estadisticos/anuario-forestal (accessed on 19 May 2025).
  5. IPCC. Summary for Policymakers. In Climate Change 2013: The Physical Science Basis; Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2013; pp. 1–27. [Google Scholar]
  6. Carrasco, G.; Almeida, A.C.; Falvey, M.; Olmedo, G.F.; Taylor, P.; Santibañez, F.; Coops, N.C. Effects of climate change on forest plantation productivity in Chile. Glob. Change Biol. 2022, 28, 7391–7409. [Google Scholar] [CrossRef] [PubMed]
  7. Zhang, X.; Zang, R.; Li, C. Population differences in physiological and morphological adaptations of Populus davidiana seedlings in response to progressive drought stress. Plant Sci. 2004, 166, 791–797. [Google Scholar] [CrossRef]
  8. Rae, A.M.; Robinson, K.M.; Street, N.R.; Taylor, G. Morphological and physiological traits influencing biomass productivity in short rotation coppice poplar. Can. J. For. Res. 2004, 34, 1488–1498. [Google Scholar] [CrossRef]
  9. Will, R.E.; Barron, G.A.; Burkes, E.C.; Shiver, B.; Teskey, R.O. Relationship between intercepted radiation, net photosynthesis, respiration, and rate of stem volume growth of Pinus taeda and Pinus elliottii stands of different densities. For. Ecol. Manag. 2001, 154, 155–163. [Google Scholar] [CrossRef]
  10. Jansson, G.; Li, B. Genetic gains of full-sib families from disconnected diallels in loblolly pine. Silvae Genet. 2004, 53, 60–64. [Google Scholar] [CrossRef]
  11. Isik, F.; Goldfarb, B.; LeBude, A.; Li, B.; McKeand, S. Predicted genetic gains and testing efficiency from two loblolly pine clonal trials. Can. J. For. Res. 2005, 35, 1754–1766. [Google Scholar] [CrossRef]
  12. Bettinger, P.; Clutter, M.; Siry, J.; Kane, M.; Pait, J. Broad implications of southern United States pine clonal forestry on planning and management of forests. Int. For. Rev. 2009, 11, 331–345. [Google Scholar] [CrossRef]
  13. Major, J.E.; Johnsen, K.H. Family variation in photosynthesis of 22-year-old black spruce: A test of two models of physiological response to water stress. Can. J. For. Res. 1996, 26, 1922–1933. [Google Scholar] [CrossRef]
  14. Major, J.E.; Johnsen, K.H. Shoot water relations of mature black spruce families displaying a genotype × environment interaction in growth rate. II. Temporal trends and response to varying soil moisture conditions. Tree Physiol. 1999, 19, 375–382. [Google Scholar] [CrossRef]
  15. Johnsen, K.H.; Major, J.E. Shoot water relations of mature black spruce families displaying a genotype × environment interaction in growth rate. I. Family and site effects over three growing seasons. Tree Physiol. 1999, 19, 367–374. [Google Scholar] [CrossRef] [PubMed]
  16. Aspinwall, M.J.; King, J.S.; McKeand, S.E.; Domec, J.C. Leaf-level gas-exchange uniformity and photosynthetic capacity among loblolly pine (Pinus taeda L.) genotypes of contrasting inherent genetic variation. Tree Physiol. 2011, 31, 78–91. [Google Scholar] [CrossRef] [PubMed]
  17. McKeand, S.E.; Jokela, E.J.; Huber, D.A.; Byram, T.D.; Allen, H.L.; Li, B.; Mullin, T.J. Performance of improved genotypes of loblolly pine across different soils, climates, and silvicultural inputs. For. Ecol. Manag. 2006, 227, 178–184. [Google Scholar] [CrossRef]
  18. Baltunis, B.S.; Brawner, J.T. Clonal stability in Pinus radiata across New Zealand and Australia. I. Growth and form traits. New For. 2010, 40, 305–322. [Google Scholar] [CrossRef]
  19. Espinoza, S.E.; Magni, C.R.; Rubilar, R.A.; Yañez, M.A.; Santelices, R.E.; Cabrera, A.M.; Ivković, M. Field performance of various Pinus radiata breeding families established on a drought-prone site in central Chile. N. Z. J. For. Sci. 2017, 47, 12. [Google Scholar] [CrossRef]
  20. Bown, H.E.; Mason, E.G.; Clinton, P.W.; Watt, M.S. Chlorophyll fluorescence response of Pinus radiata clones to nitrogen and phosphorus supply. Cienc. Investig. Agrar. 2009, 36, 451–464. [Google Scholar] [CrossRef]
  21. Havaux, M.; Lannoye, R. Drought resistance of hard wheat cultivars measured by a rapid chlorophyll fluorescence test. J. Agric. Sci. 1985, 104, 501–504. [Google Scholar] [CrossRef]
  22. Araus, J.L.; Amaro, T.; Voltas, J.; Nakkoul, H.; Nachit, M.M. Chlorophyll fluorescence as a selection criterion for grain yield in durum wheat under Mediterranean conditions. Field Crops Res. 1998, 55, 209–223. [Google Scholar] [CrossRef]
  23. Swoczyna, T.; Kalaji, H.M.; Bussotti, F.; Mojski, J.; Pollastrini, M. Environmental stress- what can we learn from chlorophyll a fluorescence analysis in woody plants? A review. Front. Plant Sci. 2023, 13, 1048582. [Google Scholar] [CrossRef]
  24. Hijmans, R.J.; Cameron, S.E.; Parra, J.L.; Jones, P.G.; Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005, 25, 1965–1978. [Google Scholar] [CrossRef]
  25. CIREN. Estudio Agrológico, VII Región. Descripciones de Suelos Materiales y Símbolos; Centro de Información de Recursos Naturales (CIREN): Santiago, Chile, 1997. [Google Scholar]
  26. CIREN. Descripciones de Suelos Materiales y Símbolos Estudio Agrológico VIII Región; Centro de Información de Recursos Naturales (CIREN): Santiago, Chile, 1999. [Google Scholar]
  27. King, N.T.; Seiler, J.R.; Fox, T.R.; Johnsen, K.H. Post-fertilization physiology and growth performance of loblolly pine clones. Tree Physiol. 2008, 28, 703–711. [Google Scholar] [CrossRef] [PubMed]
  28. Ginn, S.E.; Seiler, J.R.; Cazell, B.H.; Kreh, R.E. Physiological and growth responses of eight-year-old loblolly pine stands to thinning. For. Sci. 1991, 37, 1030–1040. [Google Scholar] [CrossRef]
  29. Johnson, J.D. A rapid technique for estimating total surface area of pine needles. For. Sci. 1984, 30, 913–921. [Google Scholar]
  30. Strasser, R.J.; Tsimilli-Michael, M.; Srivastava, A. Analysis of the chlorophyll a fluorescence transient. In Chlorophyll a Fluorescence: A Signature of Photosynthesis. Advances in Photosynthesis and Respiration; Papageorgiou, G.C., Govindjee, Eds.; Springer: Dordrecht, the Netherlands, 2004; pp. 321–362. [Google Scholar]
  31. Strasser, R.J.; Srivastava, A.; Tsimilli-Michael, M. The fluorescence transient as a tool to characterize and screen photosynthetic samples. In Probing Photosynthesis: Mechanisms, Regulation and Adaptation; Yunus, M., Pathre, U., Mohanty, P., Eds.; Taylor & Francis: London, UK, 2000; pp. 445–483. [Google Scholar]
  32. Kalaji, H.M.; Schansker, G.; Ladle, R.J.; Goltsev, V.; Bosa, K.; Allakhverdiev, S.I.; Brestic, M.; Bussotti, F.; Calatayud, A.; Dabrowski, P.; et al. Frequently asked questions about in vivo chlorophyll fluorescence: Practical issues. Photosynth. Res. 2014, 122, 121–158. [Google Scholar] [CrossRef]
  33. Kalaji, H.M.; Schansker, G.; Brestic, M.; Bussotti, F.; Calatayud, A.; Ferroni, L.; Goltsev, V.; Guidi, L.; Jajoo, A.; Li, P.; et al. Frequently asked questions about chlorophyll fluorescence, the sequel. Photosynth. Res. 2017, 132, 13–66. [Google Scholar] [CrossRef]
  34. Roth, B.E.; Jokela, E.J.; Martin, T.A.; Huber, D.A.; White, T.L. Genotype × environment interactions in selected loblolly and slash pine plantations in the Southeastern United States. For. Ecol. Manag. 2007, 238, 175–188. [Google Scholar] [CrossRef]
  35. Seiler, J.R.; Johnson, J.D. Physiological and morphological responses of three half-sib families of loblolly pine to water-stress conditioning. For. Sci. 1988, 34, 487–495. [Google Scholar] [CrossRef]
  36. Yang, W.Q.; Murthy, R.; King, P.; Topa, M.A. Diurnal changes in gas exchange and carbon partitioning in needles of fast- and slow- growing families of loblolly pine (Pinus taeda). Tree Physiol. 2002, 22, 489–498. [Google Scholar] [CrossRef]
  37. Cregg, B.M. Carbon allocation, gas exchange, and needle morphology of Pinus ponderosa genotypes known to differ in growth and survival under imposed drought. Tree Physiol. 1994, 14, 883–898. [Google Scholar] [CrossRef]
  38. Zhang, J.W.; Marshall, J.D. Variation in carbon isotope discrimination and photosynthetic gas exchange among populations of Pseudotsuga menziesii and Pinus ponderosa in different environments. Funct. Ecol. 1995, 9, 402–412. [Google Scholar] [CrossRef]
  39. Monson, R.K.; Grant, M.C. Experimental studies of ponderosa pine. III. Differences in photosynthesis, stomata1 conductance, and water-use efficiency between two genetic lines. Am. J. Bot. 1989, 76, 1041–1047. [Google Scholar]
  40. Mehta, P.; Jajoo, A.; Mathur, S.; Bharti, S. Chlorophyll a fluorescence study revealing effects of high salt stress on Photosystem II in wheat leaves. Plant Physiol. Biochem. 2010, 48, 16–20. [Google Scholar] [CrossRef] [PubMed]
  41. Stirbet, A.; Lazár, D.; Kromdijk, J.; Govindjee, G. Chlorophyll a fluorescence induction: Can just a one second measurement be used to quantify abiotic stress responses? Photosynthetica 2018, 56, 86–104. [Google Scholar] [CrossRef]
  42. Maxwell, K.; Johnson, G.N. Chlorophyll fluorescence—A practical guide. J. Exp. Bot. 2000, 51, 659–668. [Google Scholar] [CrossRef]
  43. Marron, N.; Villar, M.; Dreyer, E.; Delay, D.; Boudouresque, E.; Petit, J.-M.; Delmotte, F.M.; Guehl, J.M.; Brignolas, F. Diversity of leaf traits related to productivity in 31 Populus deltoides × Populus nigra clones. Tree Physiol. 2005, 25, 425–435. [Google Scholar] [CrossRef]
  44. Monclus, R.; Dreyer, E.; Delmotte, F.M.; Villar, M.; Delay, D.; Boudouresque, E.; Petit, J.-M.; Maroron, N.; Brédnet, C.; Brignolas, F. Productivity, leaf traits and carbon isotope discrimination in 29 Populus deltoides × P. nigra clones. New Phytol. 2005, 167, 53–62. [Google Scholar] [CrossRef]
  45. Bonhome, L.; Barbaroux, C.; Monclus, R.; Morabito, D.; Berthelot, A.; Villar, M.; Dreyer, E.; Brignolas, F. Genetic variation in productivity, leaf traits and carbon isotope discrimination in hybrid poplars cultivated on contrasting sites. Ann. For. Sci. 2008, 65, 503. [Google Scholar] [CrossRef]
  46. Boltz, B.A.; Bongarten, B.C.; Teskey, R.O. Seasonal patterns of net photosynthesis of loblolly pine from diverse origins. Can. J. For. Res. 1986, 16, 1063–1068. [Google Scholar] [CrossRef]
  47. Bongarten, B.C.; Teskey, R.O. Dry weight partitioning and its relationship to productivity in loblolly pine seedlings from seven sources. For. Sci. 1987, 33, 255–267. [Google Scholar] [CrossRef]
  48. Leech, J.W. Estimating crown width from diameter at breast height for open grown radiata pine trees in South Australia. Aust. For. Res. 1984, 14, 333–337. [Google Scholar]
  49. Johnsen, K.H.; Seiler, J.R.; Major, J.E. Growth, shoot phenology and physiology of diverse seed sources of black spruce: II. 24-year-old trees. Tree Physiol. 1996, 16, 375–380. [Google Scholar] [CrossRef] [PubMed]
  50. Marshall, J.D.; Rehfeldt, G.; Monserud, R.A. Family differences in height growth and photosynthetic traits in three conifers. Tree Physiol. 2001, 21, 727–734. [Google Scholar] [CrossRef] [PubMed]
  51. de Miguel, M.; Sánchez-Gómez, D.; Cervera, M.T.; Aranda, I. Functional and genetic characterization of gas exchange and intrinsic water use efficiency in a full-sib family of Pinus pinaster Ait. in response to drought. Tree Physiol. 2012, 32, 94–103. [Google Scholar] [CrossRef] [PubMed]
  52. Pollastrini, M.; Holland, V.; Brüggemann, W.; Koricheva, J.; Jussila, I.; Scherer-Lorenzen, M.; Berger, S.; Bussotti, F. Interactions and competition processes among tree species in young experimental mixed forests, assessed with chlorophyll fluorescence and leaf morphology. Plant Biol. 2014, 16, 323–331. [Google Scholar] [CrossRef]
  53. Masek, J.G.; Hayes, D.J.; Hughes, M.J.; Healey, S.P.; Turner, D.P. The role of remote sensing in process-scaling studies of managed forest ecosystems. For. Ecol. Manag. 2015, 355, 109–123. [Google Scholar] [CrossRef]
  54. Čepl, J.; Holá, D.; Stejskal, J.; Korecký, J.; Kočová, M.; Lhotáková, Z.; Lstibůrek, M. Genetic variability and heritability of chlorophyll a fluorescence parameters in Scots pine (Pinus sylvestris L.). Tree Physiol. 2016, 36, 883–895. [Google Scholar] [CrossRef]
  55. Xue, J.; Clinton, P.W.; Davis, M.R.; Siddiqui, T.; Beets, P.N.; Leckie, A.C. Genotypic variation in foliar nutrient concentrations, δ13C, and chlorophyll fluorescence in relation to tree growth of radiata pine clones in a serpentine soil. J. Plant Nutr. Soil. Sci. 2013, 176, 724–733. [Google Scholar] [CrossRef]
  56. Stirbet, A.; Govindjee, G. On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and photosystem II: Basics and applications of the OJIP fluorescence transient. J. Photochem. Photobiol. B Biol. 2011, 104, 236–257. [Google Scholar] [CrossRef]
  57. Banks, J.M. Chlorophyll fluorescence as a tool to identify drought stress in Acer genotypes. Environ. Exp. Bot. 2018, 155, 118–127. [Google Scholar] [CrossRef]
  58. Lambeth, C.C.; Van Buijtenen, J.P.; Duke, S.D.; McCullough, R.B. Early selection is effective in 20-year-old genetic tests of loblolly pine. Silvae Genet. 1983, 32, 210–215. [Google Scholar]
Forests 16 01108 g001
Figure 1. Variations in tree height (HT) (A), diameter at breast height (DBH) (B), and volume (VOL) (C) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across three sites.
Figure 1. Variations in tree height (HT) (A), diameter at breast height (DBH) (B), and volume (VOL) (C) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across three sites.
Forests 16 01108 g001
Forests 16 01108 g002
Figure 2. Variations in Asat (A), gs (B), E (C), and iWUE (D) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across the three sites.
Figure 2. Variations in Asat (A), gs (B), E (C), and iWUE (D) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across the three sites.
Forests 16 01108 g002
Forests 16 01108 g003
Figure 3. Variations in Fv/Fm (A), PIABS (B), and ψEo (C) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across three sites.
Figure 3. Variations in Fv/Fm (A), PIABS (B), and ψEo (C) of 30 full-sibs families of P. radiata. White bars = top-15 families; gray bars = bottom-15 families. Each bar represents average values for 30 families across three sites.
Forests 16 01108 g003
Forests 16 01108 g004
Figure 4. Relationships among HT with iWUE (A), gs (C) and Asat (E), and among DBH with (iWUE (B), gs (D) and Asat (F)). Each data point represents average values for 30 families across the three sites. In the inset equation of each panel, ns means ”statistically non- significant”.
Figure 4. Relationships among HT with iWUE (A), gs (C) and Asat (E), and among DBH with (iWUE (B), gs (D) and Asat (F)). Each data point represents average values for 30 families across the three sites. In the inset equation of each panel, ns means ”statistically non- significant”.
Forests 16 01108 g004
Table 1. Parent material, climatic characteristics, and previous land use of the three sites.
Table 1. Parent material, climatic characteristics, and previous land use of the three sites.
FeatureSite
PC1801PC1802PC1803
Soil taxonomy— SubgroupMollic Endoaquepts (Inceptisol)Typic Xeropsamments (Entisol)Typic Vitrixerands (Andisol)
Parent materialMetamorphicAlluvial sandsVolcanic sands
Previous land useP. radiata plantationP. radiata plantation. Burned in 2016P. radiata plantation
MAP (mm)87511621303
MAT (°C)14.013.312.4
Latitude (S)35°57′11″37°14′31″37°28′27″
Longitude (W)72°08′36″72°37′14″72°02′00″
Altitude (m)161 m78 m300 m
Water holding capacity (mm m−1)270 45 69
Number of blocks151515
Number of families197212195
Spacing4.1 m × 2.2 m3.5 m × 2.6 m3.6 m × 2.5 m
Number of trees315033753150
Planting date27 June 201817 July 20183 July 2018
Average height (m)7.18.94.8
Average DBH (cm)9.213.47.1
MAP (mean annual precipitation, mm) and MAT (mean annual temperature, °C) were obtained from the Worldclim (www.worldclim.org) high-resolution dataset [24]. Water holding capacity was obtained from CIREN [25,26].
Table 2. F-values and significance from the analysis of variance on growth of 30 full-sibs families of P. radiata established on three sites in Central Chile.
Table 2. F-values and significance from the analysis of variance on growth of 30 full-sibs families of P. radiata established on three sites in Central Chile.
TraitEffect
SiteFamily (Ranking)Family (Ranking) × Site
DBH (cm)6.0 *1.8 *0.9 ns
HT (m)11.3 **2.5 ***0.7 ns
VOL (m3)4.1 ns1.5 *1.1 ns
DBH = diameter at breast height, HT = height, VOL = stem index volume. *** = p < 0.001, ** = p < 0.01, * = p < 0.05, ns = non-significant (p > 0.05).
Table 3. F-values and significance from the analysis of variance on gas exchange and Chl a fluorescence of 30 full-sibs families of P. radiata established on three sites in Central Chile.
Table 3. F-values and significance from the analysis of variance on gas exchange and Chl a fluorescence of 30 full-sibs families of P. radiata established on three sites in Central Chile.
TraitEffect
SiteFamily (Ranking)Family (Ranking) × Site
Asat (μmol m−2 s−1)0.5 ns0.7 ns1.0 ns
gs (mol m−2 s−1)3.3 ns1.0 ns1.1 ns
E (mmol m−2 s−1)5.6 *0.9 ns1.2 ns
iWUE4.0 ns1.2 ns1.0 ns
Fv/Fm0.0 ns1.9 **0.9 ns
PIABS1.0 ns2.0 **1.2 ns
ψEo5.3 *1.5 *1.0 ns
ΔVIP17.3 **1.2 ns1.0 ns
Asat = light-saturated photosynthesis, gs = stomatal conductance, E = transpiration, iWUE = intrinsic water use efficiency, Fv/Fm = quantum yield of primary PSII photochemistry, PIABS = potential for energy conservation from photons absorbed by PSII to the reduction in intersystem electron acceptors, ψEo = probability that a photon trapped by the PSII reaction center enters the electron transport chain, ΔVIP = efficiency of electron flux through PSI to reduce the final acceptors of the electron transport chain. ** = p < 0.01, * = p < 0.05, ns = non-significant (p > 0.05).
Table 4. Means and coefficient of variation on gas exchange and Chl a fluorescence of 30 full-sibs families of P. radiata established on three sites in Central Chile.
Table 4. Means and coefficient of variation on gas exchange and Chl a fluorescence of 30 full-sibs families of P. radiata established on three sites in Central Chile.
TraitFamily Ranking
Top-15Bottom-15
MeanCoefficient of Variation (%)MeanCoefficient of Variation (%)
Asat (μmol m−2 s−1)3.99364.0130
gs (mol m−2 s−1)0.22430.2342
E (mmol m−2 s−1)0.35780.3675
iWUE1863818431
Fv/Fm0.8030.803
PIABS65426341
ψEo0.5980.608
ΔVIP0.16310.1725
Asat = light-saturated photosynthesis, gs = stomatal conductance, E = transpiration, iWUE = intrinsic water use efficiency, Fv/Fm = quantum yield of primary PSII photochemistry, PIABS = potential for energy conservation from photons absorbed by PSII to the reduction in intersystem electron acceptors, ψEo = probability that a photon trapped by the PSII reaction center enters the electron transport chain, ΔVIP = efficiency of electron flux through PSI to reduce the final acceptors of the electron transport chain.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Espinoza, S.; Yáñez, M.; Magni, C.; Martínez-Herrera, E.; Peña-Rojas, K.; Donoso, S.; Carrasco-Benavides, M.; Ortega-Farias, S. Genotypic Variability in Growth and Leaf-Level Physiological Performance of Highly Improved Genotypes of Pinus radiata D. Don Across Different Sites in Central Chile. Forests 2025, 16, 1108. https://doi.org/10.3390/f16071108

AMA Style

Espinoza S, Yáñez M, Magni C, Martínez-Herrera E, Peña-Rojas K, Donoso S, Carrasco-Benavides M, Ortega-Farias S. Genotypic Variability in Growth and Leaf-Level Physiological Performance of Highly Improved Genotypes of Pinus radiata D. Don Across Different Sites in Central Chile. Forests. 2025; 16(7):1108. https://doi.org/10.3390/f16071108

Chicago/Turabian Style

Espinoza, Sergio, Marco Yáñez, Carlos Magni, Eduardo Martínez-Herrera, Karen Peña-Rojas, Sergio Donoso, Marcos Carrasco-Benavides, and Samuel Ortega-Farias. 2025. "Genotypic Variability in Growth and Leaf-Level Physiological Performance of Highly Improved Genotypes of Pinus radiata D. Don Across Different Sites in Central Chile" Forests 16, no. 7: 1108. https://doi.org/10.3390/f16071108

APA Style

Espinoza, S., Yáñez, M., Magni, C., Martínez-Herrera, E., Peña-Rojas, K., Donoso, S., Carrasco-Benavides, M., & Ortega-Farias, S. (2025). Genotypic Variability in Growth and Leaf-Level Physiological Performance of Highly Improved Genotypes of Pinus radiata D. Don Across Different Sites in Central Chile. Forests, 16(7), 1108. https://doi.org/10.3390/f16071108

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop