restricted maximum likelihood analysis. Scand J For Res. 2002;17:103–10.

49. Persson T, Andersson B. Genetic variance and covariance patterns of growth and survival in Northern *Pinus sylvestris*. Scand J For Res. 2003;18:332–43.

50. Kroon J, Ericsson T, Jansson G, Andersson B. Patterns of genetic parameters for height in field genetic tests of *Picea abies* and *Pinus sylvestris* in Sweden. Tree Genet Genomes. 2011;7:1099–111.

51. Persson T, Andersson B, Ericsson T. Relationship between autumn cold hardiness and field performance in northern *Pinus sylvestris*. Silva Fenn. 2010;44:255–66.

52. Calleja-Rodriguez A, Andersson Gull B, Wu HX, Mullin TJ, Persson T. Genotype-by-environment interactions and the dynamic relationship between tree vitality and height in northern *Pinus sylvestris*. Tree Genet Genomes. 2019; 15, 36. A particularly wide-scale work addressing the relationship between growth and survival/vitality in Scots pine, indicating stronger positive genetic correlation between survival and height in harsher (colder) than in milder environments.

53. Rousi M, Possen BJMH, Ruotsalainen S, Silfver T, Mikola J. Temperature and soil fertility as regulators of tree line Scots pine growth and survival—implications for the acclimation capacity of northern populations. Glob Chang Biol. 2018;24:e545–59.

54. Russo SE, Brown P, Tan S, Davies SJ. Interspecific demographic trade-offs and soil-related habitat associations of tree species along resource gradients. J Ecol. 2008;96:192–203.

55. Bigler C, Veblen TT. Increased early growth rates decrease longevities of conifers in subalpine forests. Oikos. 2009;118:1130–8.

56. Negreiros D, Fernandes GW, Efremova AA, Le Stradic S, Neves ACO. Growth-survival trade-off in shrub saplings from Neotropical mountain grasslands. South African J Bot. 2016;106:17–22.

57. Yang W, Liu F, Zhou L, Zhang S, An S. Trade-offs between growth and survival of non-pioneer light-demanding tree seedlings in tropical forest of Hainan Island. China J Trop Ecol. 2011;27:611–20.

58. Ramírez-Valiente JA, Santos del Blanco L, Alía R, Robledo-Arnuncio JJ, Climent J. Adaptation of Mediterranean forest species to climate: lessons from common garden experiments. J Ecol. 2021;1022–42. A review and analysis of common garden data showing that no negative association between growth- and persistence-related traits at the intraspecific level, but marked adaptation to temperature and precipitation regimes.

59 Villar-Salvador P, Puértolas J, Cuesta B, Peñuelas JL, Uscola M, Heredia-Guerrero N, et al. Increase in size and nitrogen concentration enhances seedling survival in Mediterranean plantations. Insights from an ecophysiological conceptual model of plant survival. New For. 2012;43:755–70.

60. Reekie E, Bazzaz FA. Reproductive allocation in plants. Elsevier Academic Press; 2005.

61. Obeso JR. The costs of reproduction in plants. New Phytol. 2002;155:321–48.

62. Karlsson PS, Méndez M. The resource economy of plant reproduction. Reprod Alloc Plants. 2005;1–49.

63. Barringer BC, Koenig WD, Knops JMH. Interrelationships among life-history traits in three California oaks. Oecologia. 2013;171:129–39.

64. Vilà-Cabrera A, Martínez-Vilalta J, Retana J. Variation in reproduction and growth in declining Scots pine populations. Perspect Plant Ecol Evol Syst. 2014;16:111–20.

65. Leal DB, Thomas SC. Vertical gradients and tree-to-tree variation in shoot morphology and foliar nitrogen in an old-growth *Pinus strobus* stand. Can J For Res. 2003;33:1304–14.

66. Reznick D. Costs of reproduction: an evaluation of the empirical evidence. Oikos. 1985;44:257.

67. Santos-del-Blanco L, Climent J. Costs of female reproduction in a conifer tree: a whole-tree level assessment. J Ecol. 2014; 102:1310–7. This paper undertakes a singular cone-withdrawal manipulative experiment to unveil costs of reproduction in young Aleppo pines to demonstrate experimentally an effect in next female reproduction, while effect on vegetative growth was marginal.

68. Thomas SC. Age-related changes in tree growth and functional biology: the role of reproduction. 2011;33–64.

69. Bonser SP, Ladd B. The evolution of competitive strategies in annual plants. Plant Ecol. 2011;212:1441–9.

70. Sala A, Hopping K, McIntire EJB, Delzon S, Crone EE. Mast-ing in whitebark pine (*Pinus albicaulis*) depletes stored nutri-ents. New Phytol. 2012;196:189–99.

71. Qiu T, Aravena MC, Andrus R, Ascoli D, Bergeron Y, Berretti R, et al. Is there tree senescence? The fecundity evidence. Proc Natl Acad Sci USA. 2021;118:1–10.

72. McDowell SCL, McDowell NG, Marshall JD, Hultine K. Carbon and nitrogen allocation to male and female reproduction in Rocky Mountain Douglas-fir (*Pseudotsuga menziesii* var. glauca, *Pinaceae*). Am J Bot. 2000;87:539–46.

73. Verdú M, Spanos K, Čaňová I, Slobodník B, Paule L. Similar gender dimorphism in the costs of reproduction across the geographic range of *Fraxinus ornus*. Ann Bot. 2007;99:183–91.

74. Savolainen O, Karkkainen K, Harju A, Nikkanen T, Rusanen M. Fertility variation in *Pinus sylvestris*: a test of sexual allocation theory. Am J Bot. 1993;80:1016–20.

75. Santos-Del-Blanco L, Climent J, González-Martínez SC, Pan-nell JR. Genetic differentiation for size at first reproduction through male versus female functions in the widespread Medi-terranean tree *Pinus pinaster*. Ann Bot. 2012;110:1449–60.

76. Mutke S, Sievänen R, Nikinmaa E, Perttunen J, Gil L. Crown architecture of grafted Stone pine (*Pinus pinea* L.): shoot growth and bud differentiation. Trees-Struct Funct. 2005;19:15–25.

77. Leslie AB. Branching habit and the allocation of reproductive resources in conifers. Ann Bot. 2012;110:915–21.

78. Ne’eman G, Goubitz S, Werger MJA, Shmida A. Relationships between tree size, crown shape, gender segregation and sex allocation in *Pinus halepensis*, a Mediterranean pine tree. Ann Bot. 2011;108:197–206.

79. Santos-del-Blanco L, Alía R, González-Martínez SC, Sampe-dro L, Lario F, Climent J. Correlated genetic effects on reproduction define a domestication syndrome in a forest tree. Evol Appl. 2015; 403–10. This work examined the genetic change and correlated responses of reproductive traits as a result of selection for timber yield in *Pinus pinaster* progenies, find-ing a strikingly high correlated effect after a single event of artificial selection, interpreted as evidence of an underlying genetic trade-off.

80. Bravo F, Maguire DA, González-Martínez SC. Factors affecting cone production in *Pinus pinaster* Ait.: lack of growth-repro-duction trade-offs but significant effects of climate and tree and stand characteristics. For Syst. 2017;26/2): e07S.

81. Kelly D, Sork VL. Mast seeding in perennial plants: why, how, where? Annu Rev Ecol Syst. 2002;33:427–47.

82. Shestakova TA, Mutke S, Gordo J, Camarero JJ, Sin E, Pemán J, et al. Weather as main driver for masting and stem growth variation in stone pine supports compatible timber and nut co-production. Agric For Meteorol. 2021;298–299:108287.

83. Sadras VO. Evolutionary aspects of the trade-off between seed size and number in crops. F Crop Res. 2007;100:125–38.

84. Qiu T, Andrus R, Aravena MC, Ascoli D, Bergeron Y, Berretti R, et al. Limits to reproduction and seed size-number trade-offs
restricted maximum likelihood analysis. Scand J For Res. 2002;17:103–10.

49. Persson T, Andersson B. Genetic variance and covariance patterns of growth and survival in Northern *Pinus sylvestris*. Scand J For Res. 2003;18:332–43.

50. Kroon J, Ericsson T, Jansson G, Andersson B. Patterns of genetic parameters for height in field genetic tests of *Picea abies* and *Pinus sylvestris* in Sweden. Tree Genet Genomes. 2011;7:1099–111.

51. Persson T, Andersson B, Ericsson T. Relationship between autumn cold hardiness and field performance in northern *Pinus sylvestris*. Silva Fenn. 2010;44:255–66.

52. Calleja-Rodriguez A, Andersson Gull B, Wu HX, Mullin TJ, Persson T. Genotype-by-environment interactions and the dynamic relationship between tree vitality and height in northern *Pinus sylvestris*. Tree Genet Genomes. 2019; 15, 36. A particularly wide-scale work addressing the relationship between growth and survival/vitality in Scots pine, indicating stronger positive genetic correlation between survival and height in harsher (colder) than in milder environments.

53. Rousi M, Possen BJMH, Ruotsalainen S, Silfver T, Mikola J. Temperature and soil fertility as regulators of tree line Scots pine growth and survival—implications for the acclimation capacity of northern populations. Glob Chang Biol. 2018;24:e545–59.

54. Russo SE, Brown P, Tan S, Davies SJ. Interspecific demographic trade-offs and soil-related habitat associations of tree species along resource gradients. J Ecol. 2008;96:192–203.

55. Bigler C, Veblen TT. Increased early growth rates decrease longevities of conifers in subalpine forests. Oikos. 2009;118:1130–8.

56. Negreiros D, Fernandes GW, Efremova AA, Le Stradic S, Neves ACO. Growth-survival trade-off in shrub saplings from Neotropical mountain grasslands. South African J Bot. 2016;106:17–22.

57. Yang W, Liu F, Zhou L, Zhang S, An S. Trade-offs between growth and survival of non-pioneer light-demanding tree seedlings in tropical forest of Hainan Island. China J Trop Ecol. 2011;27:611–20.

58. Ramírez-Valiente JA, Santos del Blanco L, Alía R, Robledo-Arnuncio JJ, Climent J. Adaptation of Mediterranean forest species to climate: lessons from common garden experiments. J Ecol. 2021;1022–42. A review and analysis of common garden data showing that no negative association between growth- and persistence-related traits at the intraspecific level, but marked adaptation to temperature and precipitation regimes.

59 Villar-Salvador P, Puértolas J, Cuesta B, Peñuelas JL, Uscola M, Heredia-Guerrero N, et al. Increase in size and nitrogen concentration enhances seedling survival in Mediterranean plantations. Insights from an ecophysiological conceptual model of plant survival. New For. 2012;43:755–70.

60. Reekie E, Bazzaz FA. Reproductive allocation in plants. Elsevier Academic Press; 2005.

61. Obeso JR. The costs of reproduction in plants. New Phytol. 2002;155:321–48.

62. Karlsson PS, Méndez M. The resource economy of plant reproduction. Reprod Alloc Plants. 2005;1–49.

63. Barringer BC, Koenig WD, Knops JMH. Interrelationships among life-history traits in three California oaks. Oecologia. 2013;171:129–39.

64. Vilà-Cabrera A, Martínez-Vilalta J, Retana J. Variation in reproduction and growth in declining Scots pine populations. Perspect Plant Ecol Evol Syst. 2014;16:111–20.

65. Leal DB, Thomas SC. Vertical gradients and tree-to-tree variation in shoot morphology and foliar nitrogen in an old-growth *Pinus strobus* stand. Can J For Res. 2003;33:1304–14.

66. Reznick D. Costs of reproduction: an evaluation of the empirical evidence. Oikos. 1985;44:257.

67. Santos-del-Blanco L, Climent J. Costs of female reproduction in a conifer tree: a whole-tree level assessment. J Ecol. 2014; 102:1310–7. This paper undertakes a singular cone-withdrawal manipulative experiment to unveil costs of reproduction in young Aleppo pines to demonstrate experimentally an effect in next female reproduction, while effect on vegetative growth was marginal.

68. Thomas SC. Age-related changes in tree growth and functional biology: the role of reproduction. 2011;33–64.

69. Bonser SP, Ladd B. The evolution of competitive strategies in annual plants. Plant Ecol. 2011;212:1441–9.

70. Sala A, Hopping K, McIntire EJB, Delzon S, Crone EE. Mast-ing in whitebark pine (*Pinus albicaulis*) depletes stored nutri-ents. New Phytol. 2012;196:189–99.

71. Qiu T, Aravena MC, Andrus R, Ascoli D, Bergeron Y, Berretti R, et al. Is there tree senescence? The fecundity evidence. Proc Natl Acad Sci USA. 2021;118:1–10.

72. McDowell SCL, McDowell NG, Marshall JD, Hultine K. Carbon and nitrogen allocation to male and female reproduction in Rocky Mountain Douglas-fir (*Pseudotsuga menziesii* var. glauca, *Pinaceae*). Am J Bot. 2000;87:539–46.

73. Verdú M, Spanos K, Čaňová I, Slobodník B, Paule L. Similar gender dimorphism in the costs of reproduction across the geographic range of *Fraxinus ornus*. Ann Bot. 2007;99:183–91.

74. Savolainen O, Karkkainen K, Harju A, Nikkanen T, Rusanen M. Fertility variation in *Pinus sylvestris*: a test of sexual allocation theory. Am J Bot. 1993;80:1016–20.

75. Santos-Del-Blanco L, Climent J, González-Martínez SC, Pan-nell JR. Genetic differentiation for size at first reproduction through male versus female functions in the widespread Medi-terranean tree *Pinus pinaster*. Ann Bot. 2012;110:1449–60.

76. Mutke S, Sievänen R, Nikinmaa E, Perttunen J, Gil L. Crown architecture of grafted Stone pine (*Pinus pinea* L.): shoot growth and bud differentiation. Trees-Struct Funct. 2005;19:15–25.

77. Leslie AB. Branching habit and the allocation of reproductive resources in conifers. Ann Bot. 2012;110:915–21.

78. Ne’eman G, Goubitz S, Werger MJA, Shmida A. Relationships between tree size, crown shape, gender segregation and sex allocation in *Pinus halepensis*, a Mediterranean pine tree. Ann Bot. 2011;108:197–206.

79. Santos-del-Blanco L, Alía R, González-Martínez SC, Sampe-dro L, Lario F, Climent J. Correlated genetic effects on reproduction define a domestication syndrome in a forest tree. Evol Appl. 2015; 403–10. This work examined the genetic change and correlated responses of reproductive traits as a result of selection for timber yield in *Pinus pinaster* progenies, find-ing a strikingly high correlated effect after a single event of artificial selection, interpreted as evidence of an underlying genetic trade-off.

80. Bravo F, Maguire DA, González-Martínez SC. Factors affecting cone production in *Pinus pinaster* Ait.: lack of growth-repro-duction trade-offs but significant effects of climate and tree and stand characteristics. For Syst. 2017;26/2): e07S.

81. Kelly D, Sork VL. Mast seeding in perennial plants: why, how, where? Annu Rev Ecol Syst. 2002;33:427–47.

82. Shestakova TA, Mutke S, Gordo J, Camarero JJ, Sin E, Pemán J, et al. Weather as main driver for masting and stem growth variation in stone pine supports compatible timber and nut co-production. Agric For Meteorol. 2021;298–299:108287.

83. Sadras VO. Evolutionary aspects of the trade-off between seed size and number in crops. F Crop Res. 2007;100:125–38.

84. Qiu T, Andrus R, Aravena MC, Ascoli D, Bergeron Y, Berretti R, et al. Limits to reproduction and seed size-number trade-offs
that shape forest dominance and future recovery. Nat Commun.
2022; 13:1–12. This work showed that seed production is
not constrained by a strict trade-off between seed size and
numbers across plant phylogeny. In addition, gymnosperms
showed lower seed production than angiosperms, potentially
due to their extra investments in protective woody cones.

85. Herms DH, Mattson WJ. Does reproduction compromise defense in woody plants? In: Baranchikov Y, Mattson WJ, Hain FP, Payne TL, editors. For insect Guid patterns interactions with For trees. USDA Forest Service; 1991. p. 35–46.

86. Schiestl FP, Kirk H, Bigler L, Cozzolino S, Desurmont GA. Herbivory and floral signalling: phenotypic plasticity and tradeoffs between reproduction and indirect defense. New Phytol. 2014;203:257–66.

87. Redmond MD, Davis TS, Ferrenberg S, Wion AP. Resource allocation trade-offs in a mast-seeding conifer: Piñon pine prioritizes reproduction over defence. AoB Plants. 2019;11:1–11.

88. Larrinaga AR, Sampedro L, Zas R. Resource availability and herbivory alter defence-growth-reproduction trade-offs in a masting Mediterranean pine. Environ Exp Bot. 2024;217:105546.

89.• Lauder JD, Moran E V., Hart SC. Fight or flight? Potential trade-offs between drought defense and reproduction in conifers. Tree Physiol. 2019; 39:1071–85. This is an interesting theoretical and literature review postulating divergent life-history strategies among conifers in response to water stress: enhancing allocation to stress avoidance and tolerance, versus enhancing allocation to reproduction at the expenses of higher mortality risk due to drought.

90. Prada E, Climent J, Alía R, Díaz R. Life-history correlations with seasonal cold hardiness in maritime pine. Am J Bot. 2016;103:20126–2135.

91. Schulman E. Longevity under adversity in conifers. Science.
1954;119:883-4.

92. Paine TD, Lieutier F (eds). Insects and diseases of Mediterranean forest systems. Springer International Publishing Switzerland. 2016.

93. Franceschi VR, Krokene P, Christiansen E, Krekling T. Anatomical and chemical defenses of conifer bark against bark beetles and other pests. New Phytol. 2005;167:353–76.

94. Mumm R, Hilker M. Direct and indirect chemical defence of pine against folivorous insects. Trends Plant Sci. 2006;11:351–8.

95. Pagán I, García-Arenal F. Tolerance to plant pathogens: theory and experimental evidence. Int J Mol Sci. 2018;19:810.

96. Daniel A, Herms WJM. The dilemma of plants: to grow or defend. Q Rev Biol. 1992;67:283-335.

97. Belsky AJ, Carson WP, Jensen CLL, Fox GA. Overcompensation by plants: herbivore optimization or red herring? Evol Ecol. 1993;7:109–21.

98. Sampedro L, Moreira X, Zas R. Costs of constitutive and herbivore-induced chemical defences in pine trees emerge only under low nutrient availability. J Ecol. 2011;99:818–27.

99. Koricheva J. Meta-analysis of sources of variation in fitness costs of plant antiherbivore defenses. Ecology. 2002;83:176.

100.• Sampedro L. Physiological trade-offs in the complexity of pine tree defensive chemistry. Tree Physiol. 2014; 34:915–8. This review deals with the paramount difference in defensive strategy between constitutive and induced defences in pines, and postulating that plant resistance based on inducible defences, although energy saving, is a risky strategy as its benefits are based on the reliable identification of biotic cues.

101. Villari C, Faccoli M, Battisti A, Bonello P, Marini L. Testing phenotypic trade-offs in the chemical defence strategy of Scots pine under growth-limiting field conditions. Tree Physiol. 2014;34:919–30.

102. Coley PD, Bryant JB, Chapin FS. Resource availability and plant antiherbivore defense. Adv Sci. 1985;230:895-9.

103. Rhoades DF, Cates RG. Toward a general theory of plant anti-herbivore chemistry. Biochem Interact Between Plants Insects. 1976;168-213.

104. Eyles A, Bonello P, Ganley R, Mohammed C. Induced resistance to pests and pathogens in trees. New Phytol. 2010;185:893–908.

105. Cipollini D, Heil M. Costs and benefits of induced resistance to herbivores and pathogens in plants. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour. 2010;5:005.

106.●● Agrawal AA. A scale-dependent framework for trade-offs, syndromes, and specialization in organismal biology. Ecology. 2020; 101:1–24. This paper evaluates leaf economics spectrum traits and their associations with plant defense against herbivory. Scale-dependent predictions emerge for understanding plant ecology holistically, and this approach can be fruitfully applied more generally in evolutionary ecology. Adaptive specialization and community context are two of the primary drivers of trade-offs and syndromes across biological scales.

107 Zas R, Sampedro L, Prada E, Lombardero MJ, Fernández-López J. Fertilization increases *Hylobius abietis* L. damage in *Pinus pinaster* Ait. seedlings. For Ecol Manage. 2006;222:137-44.

108. Hood S, Sala A. Ponderosa pine resin defenses and growth: metrics matter. Tree Physiol. 2015;35:1223–35.

109. Endara MJ, Coley PD. The resource availability hypothesis revisited: a meta-analysis. Funct Ecol. 2011;25:389–98.

110. Moreira X, Mooney KA, Rasmann S, Petry WK, Carrillo-Gavilán A, Zas R, et al. Trade-offs between constitutive and induced defences drive geographical and climatic clines in pine chemical defences. Ecol Lett. 2014;17:537–46.

110. Pearse IS, Hipp AL. Global patterns of leaf defenses in oak species. Evolution. 2012;66:2272–86.

112.• López-Goldar X, Villari C, Bonello P, Borg-Karlson AK, Grivet D, Sampedro L, et al. Genetic variation in the constitutive defensive metabolome and its inducibility are geographically structured and largely determined by demographic processes in maritime pine. J Ecol. 2019; 107:2464–77. This papers check the neutral evolutionary hypothesis in the genetic differentiation in secondary metabolites in Pinus pinaster. Neutral differentiation was predominant, and evidence of local adaptation was only found for total constitutive sesquiterpenes and a few individual plant secondary metabolites.

113. Lorio PL. Growth-differentiation balance: a basis for understanding southern pine beetle-tree interactions. For Ecol Manage. 1986;14:259–73.

114. Gershenson J. The cost of plant chemical defense against herbivory: a biochemical perspective. In: Bernays EA, editor. Insect-Plant Interact. Boca Raton: CRC Press; 1993. p. 73.

115. Moreira X, Zas R, Solla A, Sampedro L. Differentiation of persistent anatomical defensive structures is costly and determined by nutrient availability and genetic growth-defence constraints. Tree Physiol. 2015;35:112–23.

116. Fernandez C, Monnier Y, Santonja M, Gallet C, Weston LA, Prévosto B, et al. The impact of competition and allelopathy on the trade-off between plant defense and growth in two contrasting tree species. Front Plant Sci. 2016;7:1–14.

117. Kovalchuk A, Keriö S, Oghenekaro AO, Jaber E, Raffaello T, Asiegbu FO. Antimicrobial defenses and resistance in forest trees: challenges and perspectives in a genomic era. Annu Rev Phytopathol. 2013;51:221–44.

118. Koricheva J, Nykänen H, Gianoli E. Meta-analysis of trade-offs among plant antiherbivore defenses: are plants jacks-of-all-trades, masters of all? Am Nat. 2004;163:e64–75.

119. Eichenberg D, Purschke O, Ristok C, Wessjohann L, Bruelheide H. Trade-offs between physical and chemical carbon-based leaf
that shape forest dominance and future recovery. Nat Commun.
2022; 13:1–12. This work showed that seed production is
not constrained by a strict trade-off between seed size and
numbers across plant phylogeny. In addition, gymnosperms
showed lower seed production than angiosperms, potentially
due to their extra investments in protective woody cones.

85. Herms DH, Mattson WJ. Does reproduction compromise defense in woody plants? In: Baranchikov Y, Mattson WJ, Hain FP, Payne TL, editors. For insect Guid patterns interactions with For trees. USDA Forest Service; 1991. p. 35–46.

86. Schiestl FP, Kirk H, Bigler L, Cozzolino S, Desurmont GA. Herbivory and floral signalling: phenotypic plasticity and tradeoffs between reproduction and indirect defense. New Phytol. 2014;203:257–66.

87. Redmond MD, Davis TS, Ferrenberg S, Wion AP. Resource allocation trade-offs in a mast-seeding conifer: Piñon pine prioritizes reproduction over defence. AoB Plants. 2019;11:1–11.

88. Larrinaga AR, Sampedro L, Zas R. Resource availability and herbivory alter defence-growth-reproduction trade-offs in a masting Mediterranean pine. Environ Exp Bot. 2024;217:105546.

89.• Lauder JD, Moran E V., Hart SC. Fight or flight? Potential trade-offs between drought defense and reproduction in conifers. Tree Physiol. 2019; 39:1071–85. This is an interesting theoretical and literature review postulating divergent life-history strategies among conifers in response to water stress: enhancing allocation to stress avoidance and tolerance, versus enhancing allocation to reproduction at the expenses of higher mortality risk due to drought.

90. Prada E, Climent J, Alía R, Díaz R. Life-history correlations with seasonal cold hardiness in maritime pine. Am J Bot. 2016;103:20126–2135.

91. Schulman E. Longevity under adversity in conifers. Science.
1954;119:883-4.

92. Paine TD, Lieutier F (eds). Insects and diseases of Mediterranean forest systems. Springer International Publishing Switzerland. 2016.

93. Franceschi VR, Krokene P, Christiansen E, Krekling T. Anatomical and chemical defenses of conifer bark against bark beetles and other pests. New Phytol. 2005;167:353–76.

94. Mumm R, Hilker M. Direct and indirect chemical defence of pine against folivorous insects. Trends Plant Sci. 2006;11:351–8.

95. Pagán I, García-Arenal F. Tolerance to plant pathogens: theory and experimental evidence. Int J Mol Sci. 2018;19:810.

96. Daniel A, Herms WJM. The dilemma of plants: to grow or defend. Q Rev Biol. 1992;67:283-335.

97. Belsky AJ, Carson WP, Jensen CLL, Fox GA. Overcompensation by plants: herbivore optimization or red herring? Evol Ecol. 1993;7:109–21.

98. Sampedro L, Moreira X, Zas R. Costs of constitutive and herbivore-induced chemical defences in pine trees emerge only under low nutrient availability. J Ecol. 2011;99:818–27.

99. Koricheva J. Meta-analysis of sources of variation in fitness costs of plant antiherbivore defenses. Ecology. 2002;83:176.

100.• Sampedro L. Physiological trade-offs in the complexity of pine tree defensive chemistry. Tree Physiol. 2014; 34:915–8. This review deals with the paramount difference in defensive strategy between constitutive and induced defences in pines, and postulating that plant resistance based on inducible defences, although energy saving, is a risky strategy as its benefits are based on the reliable identification of biotic cues.

101. Villari C, Faccoli M, Battisti A, Bonello P, Marini L. Testing phenotypic trade-offs in the chemical defence strategy of Scots pine under growth-limiting field conditions. Tree Physiol. 2014;34:919–30.

102. Coley PD, Bryant JB, Chapin FS. Resource availability and plant antiherbivore defense. Adv Sci. 1985;230:895-9.

103. Rhoades DF, Cates RG. Toward a general theory of plant anti-herbivore chemistry. Biochem Interact Between Plants Insects. 1976;168-213.

104. Eyles A, Bonello P, Ganley R, Mohammed C. Induced resistance to pests and pathogens in trees. New Phytol. 2010;185:893–908.

105. Cipollini D, Heil M. Costs and benefits of induced resistance to herbivores and pathogens in plants. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour. 2010;5:005.

106.●● Agrawal AA. A scale-dependent framework for trade-offs, syndromes, and specialization in organismal biology. Ecology. 2020; 101:1–24. This paper evaluates leaf economics spectrum traits and their associations with plant defense against herbivory. Scale-dependent predictions emerge for understanding plant ecology holistically, and this approach can be fruitfully applied more generally in evolutionary ecology. Adaptive specialization and community context are two of the primary drivers of trade-offs and syndromes across biological scales.

107 Zas R, Sampedro L, Prada E, Lombardero MJ, Fernández-López J. Fertilization increases *Hylobius abietis* L. damage in *Pinus pinaster* Ait. seedlings. For Ecol Manage. 2006;222:137-44.

108. Hood S, Sala A. Ponderosa pine resin defenses and growth: metrics matter. Tree Physiol. 2015;35:1223–35.

109. Endara MJ, Coley PD. The resource availability hypothesis revisited: a meta-analysis. Funct Ecol. 2011;25:389–98.

110. Moreira X, Mooney KA, Rasmann S, Petry WK, Carrillo-Gavilán A, Zas R, et al. Trade-offs between constitutive and induced defences drive geographical and climatic clines in pine chemical defences. Ecol Lett. 2014;17:537–46.

110. Pearse IS, Hipp AL. Global patterns of leaf defenses in oak species. Evolution. 2012;66:2272–86.

112.• López-Goldar X, Villari C, Bonello P, Borg-Karlson AK, Grivet D, Sampedro L, et al. Genetic variation in the constitutive defensive metabolome and its inducibility are geographically structured and largely determined by demographic processes in maritime pine. J Ecol. 2019; 107:2464–77. This papers check the neutral evolutionary hypothesis in the genetic differentiation in secondary metabolites in Pinus pinaster. Neutral differentiation was predominant, and evidence of local adaptation was only found for total constitutive sesquiterpenes and a few individual plant secondary metabolites.

113. Lorio PL. Growth-differentiation balance: a basis for understanding southern pine beetle-tree interactions. For Ecol Manage. 1986;14:259–73.

114. Gershenson J. The cost of plant chemical defense against herbivory: a biochemical perspective. In: Bernays EA, editor. Insect-Plant Interact. Boca Raton: CRC Press; 1993. p. 73.

115. Moreira X, Zas R, Solla A, Sampedro L. Differentiation of persistent anatomical defensive structures is costly and determined by nutrient availability and genetic growth-defence constraints. Tree Physiol. 2015;35:112–23.

116. Fernandez C, Monnier Y, Santonja M, Gallet C, Weston LA, Prévosto B, et al. The impact of competition and allelopathy on the trade-off between plant defense and growth in two contrasting tree species. Front Plant Sci. 2016;7:1–14.

117. Kovalchuk A, Keriö S, Oghenekaro AO, Jaber E, Raffaello T, Asiegbu FO. Antimicrobial defenses and resistance in forest trees: challenges and perspectives in a genomic era. Annu Rev Phytopathol. 2013;51:221–44.

118. Koricheva J, Nykänen H, Gianoli E. Meta-analysis of trade-offs among plant antiherbivore defenses: are plants jacks-of-all-trades, masters of all? Am Nat. 2004;163:e64–75.

119. Eichenberg D, Purschke O, Ristok C, Wessjohann L, Bruelheide H. Trade-offs between physical and chemical carbon-based leaf
defence: of intraspecific variation and trait evolution. J Ecol.
2015;103:1667-79.

120. Howe M, Mason CJ, Gratton C, Keefover-Ring K, Wallin K, Yanchuk A, et al. Relationships between conifer constitutive and inducible defenses against bark beetles change across levels of biological and ecological scale. Oikos. 2020;129:1093-107. This work postulated that biological and ecological scale may influence potential trade-offs. Experimentally, focused on one system, conifer phloem monoterpenes that resist bark beetle attack and analysed constitutive-induced relationships from genotypic to interspecific levels. This work provided a general model for understanding how underlying physiological trade-offs are variably manifested across scales.

121. Agrawal AA. Current trends in the evolutionary ecology of plant defence. Funct Ecol. 2011;25:420-32.

122. Hahn PG, Maron JL. A framework for predicting intraspecific variation in plant defense. Trends Ecol Evol. 2016;31:646-56. This key work reviewed studies documenting intraspecific variation in plant defence across resource gradients and found little support for RAH (resource availability hypothesis), one of the most well-supported theories regarding the evolution of plant defences.

123 Zas R, Sampedro L, Prada E, Fernandez-Lopez J. Genetic variation of *Pinus pinaster* Ait. seedlings in susceptibility to the pine weevil Hylobius abietis L. Ann For Sci. 2005;62:681-8.

124. Di MG, Voltas J. Multienvironment evaluation of *Pinus pinaster* provenances: evidence of genetic trade-offs between adaptation to optimal conditions and resistance to the maritime pine bast scale (Matsucoccus feytaudi). For Sci. 2016;62:553-63.

125. Simler-Williamson AB, Rizzo DM, Cobb RC. Interacting effects of global change on forest pest and pathogen dynamics. Annu Rev Ecol Evol Syst. 2019;50:381-403.

126. Santini A, Ghelardini L, De Pace C, Desprez-Loustau ML, Capretti P, Chandelier A, et al. Biogeographical patterns and determinants of invasion by forest pathogens in Europe. New Phytol. 2013;197:238-50.

127. Chuine I, Beaubien EG. Phenology is a major determinant of tree species range. Ecol Lett. 2001;4:500-10.

128. Savolainen O, Pyhäjärvi T, Knürr T. Gene flow and local adaptation in trees. Annu Rev Ecol Evol Syst. 2007;38:595-619.

129. Aitken SN, Yeaman S, Holliday JA, Wang T, Curtis-McLane S. Adaptation, migration or extirpation: climate change outcomes for tree populations. Evol Appl. 2008;1:95-111.

130. Petterle A, Karlberg A, Bhalerao RP. Daylength mediated control of seasonal growth patterns in perennial trees. Curr Opin Plant Biol. 2013;16:301-6.

131. Singh RK, Svystun T, AlDahmash B, Jönsson AM, Bhalerao RP. Photoperiod- and temperature-mediated control of phenology in trees – a molecular perspective. New Phytol. 2017;213:511-24. This paper discuss current knowledge of the molecular-level regulation of the annual growth cycle of woody trees in temperate and boreal regions, and identify key questions that need to be addressed in the future, considering the striking similarities between key components mediating photoperiodic control of growth cessation and bud set in trees with signalling pathways controlling growth cessation and floral transition in Arabidopsis.

132. Gárate-Escamilla H, Hampe A, Vizcaíno-Palomar N, Robson TM, Benito Garzón M. Range-wide variation in local adaptation and phenotypic plasticity of fitness-related traits in *Fagus sylvatica* and their implications under climate change. Glob Ecol Biogeogr. 2019;28:1336-50. Using a huge database of *Fagus sylvatica* trees in Europe, this work assessed how local adaptation and phenotypic plasticity are trait-dependent (growth and phenology) and traits covary along climatic gradients, with differential consequences for fitness.

133. Benito Garzón M, Robson TM, Hampe A. ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity. New Phytol. 2019;222:1757-65.

134. Cooper HF, Grady KC, Cowan JA, Best RJ, Allan GJ, Whitham TG. Genotypic variation in phenological plasticity: reciprocal common gardens reveal adaptive responses to warmer springs but not to fall frost. Glob Chang Biol. 2019;25:187-200. In this paper, changes in two key phenology traits (fall bud set and spring bud flush) in a widespread riparian tree species were assessed in a reciprocal transplant experiment. They found different plastic responses on phenology due to transfer, depending on the climate of origin, with trees from hotter, southern populations exhibiting greater plasticity compared to the northern, frost-adapted populations.

135. Gárate-Escamilla H, Brelsford CC, Hampe A, Robson TM, Garzón MB. Greater capacity to exploit warming temperatures in northern populations of European beech is partly driven by delayed leaf senescence. Agric For Meteorol. 2020;284:107908.

136. Howe GT, Aitken SN, Neale DB, Jermstad KD, Wheeler NC, Chen THH. From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees 1. Can J Bot. 2003;81:1247-66.

137. Notivol E, Garcia-Gil MR, Alía R, Savolainen O. Genetic variation of growth rhythm traits in the limits of a latitudinal cline in Scots pine. Can J For Res. 2007;37:540-51.

138. Aitken SN, Hannerz M. Genecology and gene resource management strategies for conifer cold hardiness. In: Bigras, F.J., Colombo, S.J. (eds) Conifer Cold Hardiness. Tree Physiology, vol 1. Springer, Dordrecht. 2001;23-53.

139. Westin J, Sundblad LG, Strand M, Hällgren JE. Phenotypic differences between natural and selected populations of *Picea abies*. I Frost Hardiness. Scand J For Res. 2010;15:5:489-99.

140. MacLachlan IR, Wang T, Hamann A, Smets P, Aitken SN. Selective breeding of lodgepole pine increases growth and maintains climatic adaptation. For Ecol Manage. 2017;391:404-16. By comparing natural stand and selectively bred lodgepole pine seedlots in a common garden, this work assessed the effects of selection on phenotypic variation and climatic associations among breeding zones for growth, phenology and cold hardiness, to conclude that breeding has produced taller lodgepole pine seedlings that are not adaptively compromised relative to their natural seedling counterparts.

141. Larson PR. Wood formation and the concept of wood quality. Bull. Ser. 74. Yale University, School of Forestry; 1969.

142. Jayawickrama KJS, McKeand SE, Jett JB, Wheeler EA. Date of earlywood-latewood transition in provenances and families of loblolly pine, and its relationship to growth phenology and juvenile wood specific gravity. Can J For Res. 1997;27:1245-53.

143. Fukatsu E, Nakada R. The timing of latewood formation determines the genetic variation of wood density in *Larix kaempferi*. Trees - Struct Funct. 2018;32:1233-45.

144. Nilsson JE. Seasonal changes in phenological traits and cold hardiness of F1-populations from plus-trees of *Pinus sylvestris* and *Pinus contorta* of various geographical origins. Scand J For Res. 2001;16:7-20.

145. Sarris D, Christodoulakis D, Körner C. Recent decline in precipitation and tree growth in the eastern Mediterranean. Glob Chang Biol. 2007;13:1187-200.

146. Van Asch M, Visser ME. Phenology of forest caterpillars and their host trees: the importance of synchrony. Annu Rev Entomol. 2007;52:37-55.

147. Elzinga JA, Atlan A, Biere A, Gigord L, Weis AE, Bernasconi G. Time after time: flowering phenology and biotic interactions. Trends Ecol Evol. 2007;22:432-9.

148. Hammond WM, Williams AP, Abatzoglou JT, Adams HD, Klein T, López R, et al. Global field observations of tree

<figure><img src="image_11.png" /></figure>
defence: of intraspecific variation and trait evolution. J Ecol.
2015;103:1667-79.

120. Howe M, Mason CJ, Gratton C, Keefover-Ring K, Wallin K, Yanchuk A, et al. Relationships between conifer constitutive and inducible defenses against bark beetles change across levels of biological and ecological scale. Oikos. 2020;129:1093-107. This work postulated that biological and ecological scale may influence potential trade-offs. Experimentally, focused on one system, conifer phloem monoterpenes that resist bark beetle attack and analysed constitutive-induced relationships from genotypic to interspecific levels. This work provided a general model for understanding how underlying physiological trade-offs are variably manifested across scales.

121. Agrawal AA. Current trends in the evolutionary ecology of plant defence. Funct Ecol. 2011;25:420-32.

122. Hahn PG, Maron JL. A framework for predicting intraspecific variation in plant defense. Trends Ecol Evol. 2016;31:646-56. This key work reviewed studies documenting intraspecific variation in plant defence across resource gradients and found little support for RAH (resource availability hypothesis), one of the most well-supported theories regarding the evolution of plant defences.

123 Zas R, Sampedro L, Prada E, Fernandez-Lopez J. Genetic variation of *Pinus pinaster* Ait. seedlings in susceptibility to the pine weevil Hylobius abietis L. Ann For Sci. 2005;62:681-8.

124. Di MG, Voltas J. Multienvironment evaluation of *Pinus pinaster* provenances: evidence of genetic trade-offs between adaptation to optimal conditions and resistance to the maritime pine bast scale (Matsucoccus feytaudi). For Sci. 2016;62:553-63.

125. Simler-Williamson AB, Rizzo DM, Cobb RC. Interacting effects of global change on forest pest and pathogen dynamics. Annu Rev Ecol Evol Syst. 2019;50:381-403.

126. Santini A, Ghelardini L, De Pace C, Desprez-Loustau ML, Capretti P, Chandelier A, et al. Biogeographical patterns and determinants of invasion by forest pathogens in Europe. New Phytol. 2013;197:238-50.

127. Chuine I, Beaubien EG. Phenology is a major determinant of tree species range. Ecol Lett. 2001;4:500-10.

128. Savolainen O, Pyhäjärvi T, Knürr T. Gene flow and local adaptation in trees. Annu Rev Ecol Evol Syst. 2007;38:595-619.

129. Aitken SN, Yeaman S, Holliday JA, Wang T, Curtis-McLane S. Adaptation, migration or extirpation: climate change outcomes for tree populations. Evol Appl. 2008;1:95-111.

130. Petterle A, Karlberg A, Bhalerao RP. Daylength mediated control of seasonal growth patterns in perennial trees. Curr Opin Plant Biol. 2013;16:301-6.

131. Singh RK, Svystun T, AlDahmash B, Jönsson AM, Bhalerao RP. Photoperiod- and temperature-mediated control of phenology in trees - a molecular perspective. New Phytol. 2017;213:511-24. This paper discuss current knowledge of the molecular-level regulation of the annual growth cycle of woody trees in temperate and boreal regions, and identify key questions that need to be addressed in the future, considering the striking similarities between key components mediating photoperiodic control of growth cessation and bud set in trees with signalling pathways controlling growth cessation and floral transition in Arabidopsis.

132. Gárate-Escamilla H, Hampe A, Vizcaíno-Palomar N, Robson TM, Benito Garzón M. Range-wide variation in local adaptation and phenotypic plasticity of fitness-related traits in *Fagus sylvatica* and their implications under climate change. Glob Ecol Biogeogr. 2019;28:1336-50. Using a huge database of *Fagus sylvatica* trees in Europe, this work assessed how local adaptation and phenotypic plasticity are trait-dependent (growth and phenology) and traits covary along climatic gradients, with differential consequences for fitness.

133. Benito Garzón M, Robson TM, Hampe A. ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity. New Phytol. 2019;222:1757-65.

134. Cooper HF, Grady KC, Cowan JA, Best RJ, Allan GJ, Whitham TG. Genotypic variation in phenological plasticity: reciprocal common gardens reveal adaptive responses to warmer springs but not to fall frost. Glob Chang Biol. 2019;25:187-200. In this paper, changes in two key phenology traits (fall bud set and spring bud flush) in a widespread riparian tree species were assessed in a reciprocal transplant experiment. They found different plastic responses on phenology due to transfer, depending on the climate of origin, with trees from hotter, southern populations exhibiting greater plasticity compared to the northern, frost-adapted populations.

135. Gárate-Escamilla H, Brelsford CC, Hampe A, Robson TM, Garzón MB. Greater capacity to exploit warming temperatures in northern populations of European beech is partly driven by delayed leaf senescence. Agric For Meteorol. 2020;284:107908.

136. Howe GT, Aitken SN, Neale DB, Jermstad KD, Wheeler NC, Chen THH. From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees 1. Can J Bot. 2003;81:1247-66.

137. Notivol E, Garcia-Gil MR, Alía R, Savolainen O. Genetic variation of growth rhythm traits in the limits of a latitudinal cline in Scots pine. Can J For Res. 2007;37:540-51.

138. Aitken SN, Hannerz M. Genecology and gene resource management strategies for conifer cold hardiness. In: Bigras, F.J., Colombo, S.J. (eds) Conifer Cold Hardiness. Tree Physiology, vol 1. Springer, Dordrecht. 2001;23-53.

139. Westin J, Sundblad LG, Strand M, Hällgren JE. Phenotypic differences between natural and selected populations of *Picea abies*. I Frost Hardiness. Scand J For Res. 2010;15:5:489-99.

140. MacLachlan IR, Wang T, Hamann A, Smets P, Aitken SN. Selective breeding of lodgepole pine increases growth and maintains climatic adaptation. For Ecol Manage. 2017;391:404-16. By comparing natural stand and selectively bred lodgepole pine seedlots in a common garden, this work assessed the effects of selection on phenotypic variation and climatic associations among breeding zones for growth, phenology and cold hardiness, to conclude that breeding has produced taller lodgepole pine seedlings that are not adaptively compromised relative to their natural seedling counterparts.

141. Larson PR. Wood formation and the concept of wood quality. Bull. Ser. 74. Yale University, School of Forestry; 1969.

142. Jayawickrama KJS, McKeand SE, Jett JB, Wheeler EA. Date of earlywood-latewood transition in provenances and families of loblolly pine, and its relationship to growth phenology and juvenile wood specific gravity. Can J For Res. 1997;27:1245-53.

143. Fukatsu E, Nakada R. The timing of latewood formation determines the genetic variation of wood density in *Larix kaempferi*. Trees - Struct Funct. 2018;32:1233-45.

144. Nilsson JE. Seasonal changes in phenological traits and cold hardiness of F1-populations from plus-trees of *Pinus sylvestris* and *Pinus contorta* of various geographical origins. Scand J For Res. 2001;16:7-20.

145. Sarris D, Christodoulakis D, Körner C. Recent decline in precipitation and tree growth in the eastern Mediterranean. Glob Chang Biol. 2007;13:1187-200.

146. Van Asch M, Visser ME. Phenology of forest caterpillars and their host trees: the importance of synchrony. Annu Rev Entomol. 2007;52:37-55.

147. Elzinga JA, Atlan A, Biere A, Gigord L, Weis AE, Bernasconi G. Time after time: flowering phenology and biotic interactions. Trends Ecol Evol. 2007;22:432-9.

148. Hammond WM, Williams AP, Abatzoglou JT, Adams HD, Klein T, López R, et al. Global field observations of tree
die-off reveal hotter-drought fingerprint for Earth's forests. Nat Commun. 2022;13:1761. This meta-analysis of a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970, quantified a global "hotter-drought fingerprint": a hotter and drier climate signal for tree mortality—across 675 locations encompassing 1,303 plots, and postulated that the frequency of mortality-year climate conditions strongly increases nonlinearly under projected warming.

149. Brodribb TJ, Bowman DJMS, Nichols S, Delzon S, Burlett R. Xylem function and growth rate interact to determine recovery rates after exposure to extreme water deficit. New Phytol. 2010;188:533-42.

150. Urli M, Porté AJ, Cochard H, Guengant Y, Burlett R, Delzon S. Xylem embolism threshold for catastrophic hydraulic failure in angiosperm trees. Tree Physiol. 2013;33:672-83.

151. Plomion C, Bartholomé J, Bouffier L, Brendel O, Cochard H, de Miguel M, et al. Understanding the genetic bases of adaptation to soil water deficit in trees through the examination of water use efficiency and cavitation resistance: maritime pine as a case study. J Plant Hydraul. 2016;3:23.

152. Nardini A, Luglio J. Leaf hydraulic capacity and drought vulnerability possible trade-offs and correlations with climate across three major biomes. Funct Ecol. 2014;28:810-8.

153. Martínez-Villalta J, Prat E, Oliveras I, Piñol J. Xylem hydraulic properties of roots and stems of nine Mediterranean woody species. Oecologia. 2002;133:19-29.

154. Gleason SM, Westoby M, Jansen S, Choat B, Hacke UG, Pratt RB, et al. Weak tradeoff between xylem safety and xylem-specific hydraulic efficiency across the world's woody plant species. New Phytol. 2016;209:123-36.

155. Pritzkow C, Szota C, Williamson VG, Arndt SK. Phenotypic plasticity of drought tolerance traits in a widespread eucalypt (Eucalyptus obliqua). Forests. 2020;11:1-14.

156. Song Y, Bouteiller XP, Larter M, Plomion C, Sin F, Delzon S. A safe breeding ground: genetically improved maritime pine for growth and stem form has more efficient but not more vulnerable xylem. Tree Physiol. 2023;43:366-78. This paper compared the hydraulic efficiency and hydraulic safety in four varieties of Pinus pinaster over successive cycles of genetic improvement for shape and growth, and found that improved varieties presented higher hydraulic conductivity with larger tracheid lumen size and tracheid lumen fraction, and smaller wall thickness reinforcement and tracheid density, but not at the cost of reduced embolism resistance.

157. Sáenz-Romero C, Lamy JB, Loya-Rebollar E, Plaza-Aguilar A, Burlett R, Lobit P, et al. Genetic variation of drought-induced cavitation resistance among *Pinus hartwegii* populations from an altitudinal gradient. Acta Physiol Plant. 2013;35:2905-13.

158. Lamy JB, Delzon S, Bouche PS, Alia R, Vendramin GG, Cochard H, et al. Limited genetic variability and phenotypic plasticity detected for cavitation resistance in a Mediterranean pine. New Phytol. 2014;201:874-86.

159. López R, Cano FJ, Choat B, Cochard H, Gil L. Plasticity in vulnerability to cavitation of *Pinus canariensis* occurs only at the driest end of an aridity gradient. Front Plant Sci. 2016;7:1-10. This work assessed intraspecific variation and relative contribution of plasticity to adaptation of vulnerability to cavitation, efficiency of the xylem to conduct water and biomass allocation, in six populations of *Pinus canariensis* growing in three provenance trials (wet, dry, and xeric). They found that the variability for hydraulic traits was largely due to phenotypic plasticity, whereas, genetic variation was limited and almost restricted to hydraulic safety traits and survival.

160. Nguyen-Queyrens A, Bouchet-Lannat F. Osmotic adjustment in three-year-old seedlings of five provenances of maritime pine (*Pinus pinaster*) in response to drought. Tree Physiol. 2003;23:397-404.

161. López R, Aranda I, Gil L, L G. Osmotic adjustment is a significant mechanism of drought resistance in *Pinus pinaster* and *Pinus canariensis*. For Syst. 2009;18:159-166.

162. Bulfe NML, Fernández ME. Morpho-physiological response to drought of progenies of *Pinus taeda* L. contrasting in mean growth rate. New For. 2016;47:431-51.

163. Gray EF, Wright IJ, Falster DS, Eller ASD, Lehmann CER, Bradford MG, et al. Leaf-wood allometry and functional traits together explain substantial growth rate variation in rainforest trees. AoB Plants. 2019;11:1-11. This paper is focused in the functional traits that drive interspecific variation in growth rate in adult plants of 41 woody species of an Australian rainforest. While it was widely assumed that the key trait drivers would be the same than in seedlings (e.g. specific leaf area, or SLA), the authors propose using cost-benefit approaches teamed with combinations of leaf, wood and allometric variables to attain a more complete understanding of growth rates under field conditions.

164. Corcuera L, Cochard H, Gil-Pelegrin E, Notivol E. Phenotypic plasticity in mesic populations of *Pinus pinaster* improves resistance to xylem embolism (P50) under severe drought. Trees - Struct Funct. 2011;25:1033-42.

165. Fichot R, Barigah TS, Chamaillard S, Le Thiec D, Laurans F, Cochard H, et al. Common trade-offs between xylem resistance to cavitation and other physiological. Plant Cell Environ. 2010;33:1553-68.

166. Cochard H, Casella E, Mencuccini M. Xylem vulnerability to cavitation varies among poplar and willow clones and correlates with yield. Tree Physiol. 2007;27:1761-7.

167. Ducrey M, Huc R, Ladjal M, Guehl JM. Variability in growth, carbon isotope composition, leaf gas exchange and hydraulic traits in the eastern Mediterranean cedars *Cedrus libani* and *C. brevifolia*. Tree Physiol. 2008;28:689-701.

168. Ramírez-Valiente JA, Cavender-Bares J. Evolutionary trade-offs between drought resistance mechanisms across a precipitation gradient in a seasonally dry tropical oak (*Quercus oleoides*). Tree Physiol. 2017;37:889-901.

169. Valliere JM. Tradeoffs between growth rate and water-use efficiency in seedlings of native perennials but not invasive annuals. Plant Ecol. 2019;220:361-9. This paper compared the growth-WUE trade-off among seedlings of native perennials in California and the invasive annuals displacing them in mesocosms under altered N and water availability. Native species suffered a trade-off between relative growth rate (RGR) and water-use efficiency (WUE), while non-natives exhibited both high RGR and high WUE, especially under high resource availability.

170. Lauteri M, Pliura A, Monteverdi MC, Brugnoli E, Villani F, Eriksson G. Genetic variation in carbon isotope discrimination in six European populations of *Castanea sativa* Mill. originating from contrasting localities. J Evol Biol. 2004;17:1286-96.

171. Lamy J-BB, Bouffier L, Burlett R, Plomion C, Cochard H, Delzon S. Uniform selection as a primary force reducing population genetic differentiation of cavitation resistance across a species range. Ingvarsson PK, editor. PLoS One. 2011;6:e23476.

172. Dixit A, Kolb T, Burney O. Trade-off between growth rate and water use efficiency in southwestern ponderosa pine provenances. For Ecol Manage. 2022;515:120239. In a common garden of *Pinus ponderosa*, seedlings with higher growth rate had greater Δ13C, suggesting a trade-off between growth rate and water use efficiency. Provenances from warmer
die-off reveal hotter-drought fingerprint for Earth's forests. Nat Commun. 2022;13:1761. This meta-analysis of a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970, quantified a global "hotter-drought fingerprint": a hotter and drier climate signal for tree mortality—across 675 locations encompassing 1,303 plots, and postulated that the frequency of mortality-year climate conditions strongly increases nonlinearly under projected warming.

149. Brodribb TJ, Bowman DJMS, Nichols S, Delzon S, Burlett R. Xylem function and growth rate interact to determine recovery rates after exposure to extreme water deficit. New Phytol. 2010;188:533-42.

150. Urli M, Porté AJ, Cochard H, Guengant Y, Burlett R, Delzon S. Xylem embolism threshold for catastrophic hydraulic failure in angiosperm trees. Tree Physiol. 2013;33:672-83.

151. Plomion C, Bartholomé J, Bouffier L, Brendel O, Cochard H, de Miguel M, et al. Understanding the genetic bases of adaptation to soil water deficit in trees through the examination of water use efficiency and cavitation resistance: maritime pine as a case study. J Plant Hydraul. 2016;3:23.

152. Nardini A, Luglio J. Leaf hydraulic capacity and drought vulnerability possible trade-offs and correlations with climate across three major biomes. Funct Ecol. 2014;28:810-8.

153. Martínez-Villalta J, Prat E, Oliveras I, Piñol J. Xylem hydraulic properties of roots and stems of nine Mediterranean woody species. Oecologia. 2002;133:19-29.

154. Gleason SM, Westoby M, Jansen S, Choat B, Hacke UG, Pratt RB, et al. Weak tradeoff between xylem safety and xylem-specific hydraulic efficiency across the world's woody plant species. New Phytol. 2016;209:123-36.

155. Pritzkow C, Szota C, Williamson VG, Arndt SK. Phenotypic plasticity of drought tolerance traits in a widespread eucalypt (Eucalyptus obliqua). Forests. 2020;11:1-14.

156. Song Y, Bouteiller XP, Larter M, Plomion C, Sin F, Delzon S. A safe breeding ground: genetically improved maritime pine for growth and stem form has more efficient but not more vulnerable xylem. Tree Physiol. 2023;43:366-78. This paper compared the hydraulic efficiency and hydraulic safety in four varieties of Pinus pinaster over successive cycles of genetic improvement for shape and growth, and found that improved varieties presented higher hydraulic conductivity with larger tracheid lumen size and tracheid lumen fraction, and smaller wall thickness reinforcement and tracheid density, but not at the cost of reduced embolism resistance.

157. Sáenz-Romero C, Lamy JB, Loya-Rebollar E, Plaza-Aguilar A, Burlett R, Lobit P, et al. Genetic variation of drought-induced cavitation resistance among *Pinus hartwegii* populations from an altitudinal gradient. Acta Physiol Plant. 2013;35:2905-13.

158. Lamy JB, Delzon S, Bouche PS, Alia R, Vendramin GG, Cochard H, et al. Limited genetic variability and phenotypic plasticity detected for cavitation resistance in a Mediterranean pine. New Phytol. 2014;201:874-86.

159. López R, Cano FJ, Choat B, Cochard H, Gil L. Plasticity in vulnerability to cavitation of *Pinus canariensis* occurs only at the driest end of an aridity gradient. Front Plant Sci. 2016;7:1-10. This work assessed intraspecific variation and relative contribution of plasticity to adaptation of vulnerability to cavitation, efficiency of the xylem to conduct water and biomass allocation, in six populations of *Pinus canariensis* growing in three provenance trials (wet, dry, and xeric). They found that the variability for hydraulic traits was largely due to phenotypic plasticity, whereas, genetic variation was limited and almost restricted to hydraulic safety traits and survival.

160. Nguyen-Queyrens A, Bouchet-Lannat F. Osmotic adjustment in three-year-old seedlings of five provenances of maritime pine (*Pinus pinaster*) in response to drought. Tree Physiol. 2003;23:397-404.

161. López R, Aranda I, Gil L, L G. Osmotic adjustment is a significant mechanism of drought resistance in *Pinus pinaster* and *Pinus canariensis*. For Syst. 2009;18:159-166.

162. Bulfe NML, Fernández ME. Morpho-physiological response to drought of progenies of *Pinus taeda* L. contrasting in mean growth rate. New For. 2016;47:431-51.

163. Gray EF, Wright IJ, Falster DS, Eller ASD, Lehmann CER, Bradford MG, et al. Leaf-wood allometry and functional traits together explain substantial growth rate variation in rainforest trees. AoB Plants. 2019;11:1-11. This paper is focused in the functional traits that drive interspecific variation in growth rate in adult plants of 41 woody species of an Australian rainforest. While it was widely assumed that the key trait drivers would be the same than in seedlings (e.g. specific leaf area, or SLA), the authors propose using cost-benefit approaches teamed with combinations of leaf, wood and allometric variables to attain a more complete understanding of growth rates under field conditions.

164. Corcuera L, Cochard H, Gil-Pelegrin E, Notivol E. Phenotypic plasticity in mesic populations of *Pinus pinaster* improves resistance to xylem embolism (P50) under severe drought. Trees - Struct Funct. 2011;25:1033-42.

165. Fichot R, Barigah TS, Chamaillard S, Le Thiec D, Laurans F, Cochard H, et al. Common trade-offs between xylem resistance to cavitation and other physiological. Plant Cell Environ. 2010;33:1553-68.

166. Cochard H, Casella E, Mencuccini M. Xylem vulnerability to cavitation varies among poplar and willow clones and correlates with yield. Tree Physiol. 2007;27:1761-7.

167. Ducrey M, Huc R, Ladjal M, Guehl JM. Variability in growth, carbon isotope composition, leaf gas exchange and hydraulic traits in the eastern Mediterranean cedars *Cedrus libani* and *C. brevifolia*. Tree Physiol. 2008;28:689-701.

168. Ramírez-Valiente JA, Cavender-Bares J. Evolutionary trade-offs between drought resistance mechanisms across a precipitation gradient in a seasonally dry tropical oak (*Quercus oleoides*). Tree Physiol. 2017;37:889-901.

169. Valliere JM. Tradeoffs between growth rate and water-use efficiency in seedlings of native perennials but not invasive annuals. Plant Ecol. 2019;220:361-9. This paper compared the growth-WUE trade-off among seedlings of native perennials in California and the invasive annuals displacing them in mesocosms under altered N and water availability. Native species suffered a trade-off between relative growth rate (RGR) and water-use efficiency (WUE), while non-natives exhibited both high RGR and high WUE, especially under high resource availability.

170. Lauteri M, Pliura A, Monteverdi MC, Brugnoli E, Villani F, Eriksson G. Genetic variation in carbon isotope discrimination in six European populations of *Castanea sativa* Mill. originating from contrasting localities. J Evol Biol. 2004;17:1286-96.

171. Lamy J-BB, Bouffier L, Burlett R, Plomion C, Cochard H, Delzon S. Uniform selection as a primary force reducing population genetic differentiation of cavitation resistance across a species range. Ingvarsson PK, editor. PLoS One. 2011;6:e23476.

172. Dixit A, Kolb T, Burney O. Trade-off between growth rate and water use efficiency in southwestern ponderosa pine provenances. For Ecol Manage. 2022;515:120239. In a common garden of *Pinus ponderosa*, seedlings with higher growth rate had greater Δ13C, suggesting a trade-off between growth rate and water use efficiency. Provenances from warmer
sites had lower growth rate and Δ13C (higher water use effi-
ciency) than provenances from cooler sites during the driest
year.

173. Nguyen-Queyrens A, Ferhi A, Loustau D, Guehl J-M. Within-
ring δ13C spatial variability and interannual variations in wood
cellulose of two contrasting provenances of *Pinus pinaster*. Can
J For Res. 1998;28:766–73.

174. Marguerit E, Bouffier L, Chancerel E, Costa P, Lagane F, Guehl JM, et al. The genetics of water-use efficiency and its relation to growth in maritime pine. J Exp Bot. 2014;65:4757–68.

175. Bacon M. (ed) Water use efficiency in plant biology. Blackwell Publishing Ltd. Oxford. 2009;344.

176 De Miguel M, Sánchez-Gómez D, Cervera MT, 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.

177. Moran E, Lauder J, Musser C, Stathos A, Shu M. The genetics of drought tolerance in conifers. New Phytol. 2017;216:1034–48.

178. Brendel O, Pot D, Plomion C, Rozenberg P, Guehl JM. Genetic parameters and QTL analysis of δ 13 C and ring width in mari- time pine. Plant Cell Environ. 2002;25:945–53.

179. Martínez-Villalta J, Cochard H, Mencuccini M, Sterck F, Her-
ero A, Korhonen JFJ, et al. Hydraulic adjustment of Scots pine
across Europe. New Phytol. 2009;184:353–64.

180. Fichot R, Chamaillard S, Depardieu C, Le Thiec D, Cochard H, Barigah TS, et al. Hydraulic efficiency and coordination with xylem resistance to cavitation, leaf function, and growth perfor- mance among eight unrelated *Populus deltoides*×*Populus nigra* hybrids. J Exp Bot. 2011;62:2093–106.

181. Guet J, Fichot R, Lédée C, Laurans F, Cochard H, Delzon S, et al. Stem xylem resistance to cavitation is related to xylem structure but not to growth and water-use efficiency at the within-popula- tion level in *Populus nigra* L. J Exp Bot. 2015;66:4643–52.

182. Gutschick VP, BassiriRad H. Extreme events as shaping physiology, ecology, and evolution of plants: toward a unified definition and evaluation of their consequences. New Phytol. 2003;160:21–42.

183. Zimmermann NE, Yoccoz NG, Edwards TC, Meier ES, Thu-
iller W, Guisan A, et al. Climatic extremes improve predic-
tions of spatial patterns of tree species. Proc Natl Acad Sci.
2009;106:19723–8.

184. Korner C, Basler D, Hoch G, Kollas C, Lenz A, Randin CF, et al. Where, why and how? Explaining the low-temperature range limits of temperate tree species. J Ecol. 2016;104:1076–88.

185.● Neumann M, Mues V, Moreno A, Hasenauer H, Seidl R. Climate variability drives recent tree mortality in Europe. Glob Chang Biol. 2017;23:4788–97. This work describes kontinental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe, finding that warm summers as well as high seasonal variability in precipitation increased the likelihood of tree mortality.

186. Bi H, Parekh J, Li Y, Murphy S, Lei Y. Adverse influences of drought and temperature extremes on survival of potential tree species for commercial environmental forestry in the dryland areas on the western slopes of New South Wales. Australia Agric For Meteorol. 2014;197:188–205.

187. Crockett JL, Westerling AL. Greater temperature and precipita-
tion extremes intensify Western U.S. droughts, wildfire severity,
and Sierra Nevada tree mortality. J Clim. 2018;31:341–54.

188. McDowell NG, Williams AP, Xu C, Pockman WT, Dickman LT, Sevanto S, et al. Multi-scale predictions of massive coni- fer mortality due to chronic temperature rise. Nat Clim Chang. 2016;6:295–300.

189. Anderegg WRL, Kane JM, Anderegg LDL. Consequences of widespread tree mortality triggered by drought and temperature stress. Nat Clim Chang. 2013;3:30–6.

190. Allen CD, Breshears DD, McDowell NG. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere. 2015;6:129.

191. Matusick G, Ruthrof KX, Brouwers NC, Dell B, Hardy GSJ. Sudden forest canopy collapse corresponding with extreme drought and heat in a Mediterranean-type eucalypt forest in southwestern Australia. Eur J For Res. 2013;132:497–510.

192. Leuzinger S, Vogt R, Körner C. Tree surface temperature in an urban environment. Agric For Meteorol. 2010;150:56–62.

193.● Hagmann RK, Hessburg PF, Prichard SJ, Povak NA, Brown PM, Fulé PZ, et al. Evidence for widespread changes in the structure, composition, and fire regimes of western North American for- ests. Ecol Appl. 2021;31. The cumulative results document a substantial fire deficit and widespread alterations to eco- logical structures and functions. The loss of the once abun- dant influence of low- and moderate-severity fires suggests that even the least fire-prone ecosystems may be affected by alteration of the surrounding landscape and, consequently, ecosystem functions.

194. Chakraborty D, Matulla C, Andre K, Weissenbacher L, Schueler S. Survival of Douglas-fir provenances in Austria: site-specific late and early frost events are more important than provenance origin. Ann For Sci. 2019;76.

195. Hänninen H. Does climatic warming increase the risk of frost damage in northern trees? Plant Cell Environ. 1991;14:449–54.

196.● Zohner CM, Mo L, Renner SS, Svenning JC, Vitasse Y, Ben-
ito BM, et al. Late-spring frost risk between 1959 and 2017
decreased in North America but increased in Europe and Asia.
Proc Natl Acad Sci. 2020; 117: 12192-12200. Starting from
observations in many species at botanical gardens, this work
modelled the change in frost damage across temperate and
boreal regions of the world. The greatest increase in leaf-
damaging spring frost has occurred in Europe and East Asia,
where species are more vulnerable to spring frost than in
North America.

197. Teskey R, Wertin T, Baueraerts I, Ameye M, McGuire MA, Steppe K. Responses of tree species to heat waves and extreme heat events. Plant Cell Environ. 2015;38:1699–712.

198. Smith W. Tree pathology: a short introduction. New York, Lon-
don: Academic Press; 1970. p. 308.

199. Martinez-Meier A, Sanchez L, Dalla-Salda G, Pastorino MJM, Gautry J-Y, Gallo LA, et al. Genetic control of the tree-ring response of Douglas-fir (*Pseudotsuga menziesii* Mirb. Franco) to the 2003 drought and heat-wave in France. Ann For Sci. 2008;65:102–10.

200. Christiansen MN. The physiology of plant tolerance to tempera-
ture extremes. In: Jung GA, editor. Crop Toler to Suboptimal L
Cond. ASA Special Publications. Madison, WI, USA: American
Society of Agronomy, Crop Science Society of America, and
Soil Science Society of America; 1978;173–91.

201. Bassow SL, McConnaughay KDM, Bazzaz FA. The response of temperate tree seedlings grown in elevated CO₂ to extreme temperature events. Ecol Appl. 1994;4:593–603.

202. Warren JM, Norby RJ, Wullschleger SD, Oren R. Elevated CO₂ enhances leaf senescence during extreme drought in a temperate forest. Tree Physiol. 2011;31:117–30.

203. Pausas JG, Bradstock RA, Keith DA, Keeley JE, Network GF. Plant functional traits in relation to fire in crown-fire ecosystems. pdf. Ecology. 2004;85:1085–100.

204.● Keeley JE, Pausas JG. Evolutionary ecology of fire. Annu Rev Ecol Evol Syst. 2022; 53:203–25. This work reviews the dif- ferent traits and syndromes providing fitness benefits follow- ing fires, depending on the fire regime. Some of these traits
sites had lower growth rate and Δ13C (higher water use effi-
ciency) than provenances from cooler sites during the driest
year.

173. Nguyen-Queyrens A, Ferhi A, Loustau D, Guehl J-M. Within-
ring δ13C spatial variability and interannual variations in wood
cellulose of two contrasting provenances of *Pinus pinaster*. Can
J For Res. 1998;28:766–73.

174. Marguerit E, Bouffier L, Chancerel E, Costa P, Lagane F, Guehl JM, et al. The genetics of water-use efficiency and its relation to growth in maritime pine. J Exp Bot. 2014;65:4757–68.

175. Bacon M. (ed) Water use efficiency in plant biology. Blackwell Publishing Ltd. Oxford. 2009;344.

176 De Miguel M, Sánchez-Gómez D, Cervera MT, 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.

177. Moran E, Lauder J, Musser C, Stathos A, Shu M. The genetics of drought tolerance in conifers. New Phytol. 2017;216:1034–48.

178. Brendel O, Pot D, Plomion C, Rozenberg P, Guehl JM. Genetic parameters and QTL analysis of δ 13 C and ring width in mari- time pine. Plant Cell Environ. 2002;25:945–53.

179. Martínez-Villalta J, Cochard H, Mencuccini M, Sterck F, Her-
ero A, Korhonen JFJ, et al. Hydraulic adjustment of Scots pine
across Europe. New Phytol. 2009;184:353–64.

180. Fichot R, Chamaillard S, Depardieu C, Le Thiec D, Cochard H, Barigah TS, et al. Hydraulic efficiency and coordination with xylem resistance to cavitation, leaf function, and growth perfor- mance among eight unrelated *Populus deltoides*×*Populus nigra* hybrids. J Exp Bot. 2011;62:2093–106.

181. Guet J, Fichot R, Lédée C, Laurans F, Cochard H, Delzon S, et al. Stem xylem resistance to cavitation is related to xylem structure but not to growth and water-use efficiency at the within-popula- tion level in *Populus nigra* L. J Exp Bot. 2015;66:4643–52.

182. Gutschick VP, BassiriRad H. Extreme events as shaping physiology, ecology, and evolution of plants: toward a unified definition and evaluation of their consequences. New Phytol. 2003;160:21–42.

183. Zimmermann NE, Yoccoz NG, Edwards TC, Meier ES, Thu-
iller W, Guisan A, et al. Climatic extremes improve predic-
tions of spatial patterns of tree species. Proc Natl Acad Sci.
2009;106:19723–8.

184. Korner C, Basler D, Hoch G, Kollas C, Lenz A, Randin CF, et al. Where, why and how? Explaining the low-temperature range limits of temperate tree species. J Ecol. 2016;104:1076–88.

185. • Neumann M, Mues V, Moreno A, Hasenauer H, Seidl R. Climate variability drives recent tree mortality in Europe. Glob Chang Biol. 2017;23:4788–97. This work describes kontinental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe, finding that warm summers as well as high seasonal variability in precipitation increased the likelihood of tree mortality.

186. Bi H, Parekh J, Li Y, Murphy S, Lei Y. Adverse influences of drought and temperature extremes on survival of potential tree species for commercial environmental forestry in the dryland areas on the western slopes of New South Wales. Australia Agric For Meteorol. 2014;197:188–205.

187. Crockett JL, Westerling AL. Greater temperature and precipita-
tion extremes intensify Western U.S. droughts, wildfire severity,
and Sierra Nevada tree mortality. J Clim. 2018;31:341–54.

188. McDowell NG, Williams AP, Xu C, Pockman WT, Dickman LT, Sevanto S, et al. Multi-scale predictions of massive coni- fer mortality due to chronic temperature rise. Nat Clim Chang. 2016;6:295–300.

189. Anderegg WRL, Kane JM, Anderegg LDL. Consequences of widespread tree mortality triggered by drought and temperature stress. Nat Clim Chang. 2013;3:30–6.

190. Allen CD, Breshears DD, McDowell NG. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere. 2015;6:129.

191. Matusick G, Ruthrof KX, Brouwers NC, Dell B, Hardy GSJ. Sudden forest canopy collapse corresponding with extreme drought and heat in a Mediterranean-type eucalypt forest in southwestern Australia. Eur J For Res. 2013;132:497–510.

192. Leuzinger S, Vogt R, Körner C. Tree surface temperature in an urban environment. Agric For Meteorol. 2010;150:56–62.

193. • Hagmann RK, Hessburg PF, Prichard SJ, Povak NA, Brown PM, Fulé PZ, et al. Evidence for widespread changes in the structure, composition, and fire regimes of western North American for- ests. Ecol Appl. 2021;31. The cumulative results document a substantial fire deficit and widespread alterations to eco- logical structures and functions. The loss of the once abun- dant influence of low- and moderate-severity fires suggests that even the least fire-prone ecosystems may be affected by alteration of the surrounding landscape and, consequently, ecosystem functions.

194. Chakraborty D, Matulla C, Andre K, Weissenbacher L, Schueler S. Survival of Douglas-fir provenances in Austria: site-specific late and early frost events are more important than provenance origin. Ann For Sci. 2019;76.

195. Hänninen H. Does climatic warming increase the risk of frost damage in northern trees? Plant Cell Environ. 1991;14:449–54.

196. • Zohner CM, Mo L, Renner SS, Svenning JC, Vitasse Y, Ben-
ito BM, et al. Late-spring frost risk between 1959 and 2017
decreased in North America but increased in Europe and Asia.
Proc Natl Acad Sci. 2020; 117: 12192-12200. Starting from
observations in many species at botanical gardens, this work
modelled the change in frost damage across temperate and
boreal regions of the world. The greatest increase in leaf-
damaging spring frost has occurred in Europe and East Asia,
where species are more vulnerable to spring frost than in
North America.

197. Teskey R, Wertin T, Baueraerts I, Ameye M, McGuire MA, Steppe K. Responses of tree species to heat waves and extreme heat events. Plant Cell Environ. 2015;38:1699–712.

198. Smith W. Tree pathology: a short introduction. New York, Lon-
don: Academic Press; 1970. p. 308.

199. Martinez-Meier A, Sanchez L, Dalla-Salda G, Pastorino MJM, Gautry J-Y, Gallo LA, et al. Genetic control of the tree-ring response of Douglas-fir (*Pseudotsuga menziesii* Mirb. Franco) to the 2003 drought and heat-wave in France. Ann For Sci. 2008;65:102–10.

200. Christiansen MN. The physiology of plant tolerance to tempera-
ture extremes. In: Jung GA, editor. Crop Toler to Suboptimal L
Cond. ASA Special Publications. Madison, WI, USA: American
Society of Agronomy, Crop Science Society of America, and
Soil Science Society of America; 1978;173–91.

201. Bassow SL, McConnaughay KDM, Bazzaz FA. The response of temperate tree seedlings grown in elevated CO₂ to extreme temperature events. Ecol Appl. 1994;4:593–603.

202. Warren JM, Norby RJ, Wullschleger SD, Oren R. Elevated CO₂ enhances leaf senescence during extreme drought in a temperate forest. Tree Physiol. 2011;31:117–30.

203. Pausas JG, Bradstock RA, Keith DA, Keeley JE, Network GF. Plant functional traits in relation to fire in crown-fire ecosystems. pdf. Ecology. 2004;85:1085–100.

204. • Keeley JE, Pausas JG. Evolutionary ecology of fire. Annu Rev Ecol Evol Syst. 2022; 53:203–25. This work reviews the dif- ferent traits and syndromes providing fitness benefits follow- ing fires, depending on the fire regime. Some of these traits
enhance fire survival, while others promote recruitment in the postfire environment. Demonstrating that these traits are fire adaptations is challenging, since many arose early in the paleontological record, although increasingly better fossil records and phylogenetic analysis make timing of these trait origins to fire more certain.

205. Tapias R, Climent J, Pardos JA, Gil LA. Life histories of Mediterranean pines. Plant Ecol. 2004;171:53-68.

206. Hernández-Serrano A, Verdú M, Santos-Del-Blanco L, Climent J, González-Martínez SC, Pausas JG. Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait. Ann Bot. 2014;114:571-7.

207. Pausas JG, Keeley JE. Evolutionary ecology of resprouting and seeding in fire-prone ecosystems. New Phytol. 2014;204:55-65.

208. Schwilk DW, Ackerly DD. Flammability and serotiny as strategies: correlated evolution in pines. Oikos. 2001;94:326-36.

209. Martín-Sanz RC, Santos-Del-Blanco L, Notivol E, Chambel MR, San-Martín R, Climent J. Disentangling plasticity of serotiny, a key adaptive trait in a Mediterranean conifer. Am J Bot. 2016;103:1582-91.

210. Van Gelder HA, Poorter L, Sterck FJ. Wood mechanics, allometry, and life-history variation in a tropical rain forest tree community. New Phytol. 2006;171:367-78.

211. Poorter L, McDonald I, Alarcón A, Fichtler E, Licona JC, Peña-Claros M, et al. The importance of wood traits and hydraulic conductance for the performance and life history strategies of 42 rainforest tree species. New Phytol. 2010;185:481-92.

212. Zobel BJ, van Buijtenen JP. Wood variation and wood properties. In: Wood variation. Springer Series in Wood Science. Springer, Berlin, Heidelberg. 1989;1-32.

213. Zobel BJ, Jett JB. The importance of wood density (specific gravity) and its component parts. In: Genetics of wood production. Springer Series in Wood Science. Springer, Berlin, Heidelberg. 1995.

214. Dungey HS, Matheson AC, Kain D, Evans R. Genetics of wood stiffness and its component traits in *Pinus radiata*. Can J For Res. 2006;36:1165-78.

215. Saranpää P. Wood density and growth. In: Barnett JR, Jeronimidis G, editors. Wood quality: its biological basis. Blackwell Publishing Ltd; 2003:226.

216. Mork F. Die qualitaat des fichtenholzes unter besonderer rucssichtnahme auf schleif-und papierholz. Papier Fabrikant. 1928;26:741-7.

217. Bendtsen BA, Senft J. Mechanical and anatomical properties in individual growth rings of plantation-grown eastern cottonwood and loblolly pine. Wood Fiber Sci. 2007;18:23-38.

218. Cave ID, Walker JCF. Stiffness of wood in fast-grown plantation softwoods - the influence of microfibril angle. For Prod J. 1994;44:43-8.

219. Gjerdrum P, Säll H, Storø HM. Spiral grain in Norway spruce: constant change rate in grain angle in Scandinavian sawlogs. Forestry. 2002;75:163-70.

220. Chen ZQ, Gil MRG, Karlsson B, Lundqvist SO, Olsson L, Wu HX. Inheritance of growth and solid wood quality traits in a large Norway spruce population tested at two locations in southern Sweden. Tree Genet Genomes. 2014;10:1291-303.

221. Hayatgheibi H, Fries A, Kroon J, Wu HX. Genetic analysis of lodgepole pine (*Pinus contorta*) solid-wood quality traits. Can J For Res. 2017;47:1303-13.

222. Hong Z, Fries A, Wu HX. Age trend of heritability, genetic correlation, and efficiency of early selection for wood quality traits in Scots pine. Can J For Res. 2015;45:817-25.

223. Lenz P, Cloutier A, MacKay J, Beaulieu J. Genetic control of wood properties in *Picea glauca* - an analysis of trends with cambial age. Can J For Res. 2010;40:703-15.

224. Kucera B. A hypothesis relating current annual height increment to juvenile wood formation in Norway spruce. Wood Fiber Sci. 1994;26:152-67.

225. Larson P, Kretschmann DE, Clark A, Isebrants JG. Formation and properties of juvenile wood in southern pines: a synopsis. Madison, WI: USDA Forest Service, Forest Products Laboratory 2001;42.

226. Mellerowicz EJ, Baucher M, Sundberg B, Boerjan W. Unraveling cell wall formation in the woody dicot stem. Plant Mol Biol. 2001;47:239-74.

227. Steffenrem A, Kvaalen H, Hoibo OA, Edvardsen OM, Skroppa T, Høibø OA, et al. Genetic variation of wood quality traits and relationships with growth in *Picea abies*. Scand J For Res. 2009;24:15-27.

228. Merrill REMC. Heritability and genetic correlations for stem diameter and branch characteristics in white spruce. Can J For Res. 1985;15:494-7.

229. Vestøl GI, Høibø OA. Prediction of knot diameter in *Picea abies* (L.) Karst. Holz als Roh - und Werkst. 2001;59:129-36.

230. Høibø OA. The quality of wood of Norway spruce (*Picea abies* (L.) Karst.) planted with different spacing. Agricultural University of Norway; 1991.

231. Johansson K. Effect of initial spacing on the stem and branch properties and graded quality of *Picea abies* (L.) Karst. Scand J For Res. 1992;7:503-14.

232. Vestøl GI, Colin F, Loubere M, Loubère M. Influence of progeny and initial stand density on the relationship between diameter at breast height and knot diameter of *Picea abies*. Scand J For Res. 1999;14:470-80.

233. Karlsson B, Hogberg K-A. Genotypic parameters and clone x site interaction in clone tests of Norway spruce (*Picea abies* (L.) Karst.). For Genet. 1998;5:21-30.

234. Magnussen SYC. Early testing of jack pine.: II Variance and repeatability of stem and branch characters. Can J For Res. 1987;17:460-5.

235. Magnussen SYC. Early testing of jack pine. I. Phenotypic response to spacing. Can J For Res. 1987;17:453-9.

236. Gräns D, Hannrup B, Isik F, Lundqvist SO, McKeand S. Genetic variation and relationships to growth traits for microfibril angle, wood density and modulus of elasticity in a *Picea abies* clonal trial in southern Sweden. Scand J For Res. 2009;24:494-503.

237. Wang X-R, Torimaru T, Lindgren D, Fries A. Marker-based parentage analysis facilitates low input 'breeding without breeding' strategies for forest trees. Tree Genet Genomes. 2009;6:227-35.

238. Hong Z, Fries A, Wu HX. High negative genetic correlations between growth traits and wood properties suggest incorporating multiple traits selection including economic weights for the future Scots pine breeding programs. Ann For Sci. 2014;71:463-72.

239. Fundova I, Funda T, Wu HX. Non-destructive wood density assessment of Scots pine (*Pinus sylvestris* L.) using Resistograph and Pilodyn. PLoS One. 2018;13:1-16.

240. Baltunis BS, Wu HX, Powell MB. Inheritance of density, microfibril angle, and modulus of elasticity in juvenile wood of *Pinus radiata* at two locations in Australia. Can J For Res. 2007;37:2164-74.

241. Wu HX, Ivkovic M, Gaspare WJ, Matheson AC, Baltunis BS, Powell MB, et al. Breeding for wood quality and profit in radiata pine: a review of genetic parameters. New Zeal J For Res. 2008;38:56-87.

242. Fries A, Ulvcrona T, Wu HX, Kroon J. Stem damage of lodgepole pine clonal cuttings in relation to wood and fiber traits, acoustic velocity, and spiral grain. Scand J For Res. 2014;29:764-76.
enhance fire survival, while others promote recruitment in the postfire environment. Demonstrating that these traits are fire adaptations is challenging, since many arose early in the paleontological record, although increasingly better fossil records and phylogenetic analysis make timing of these trait origins to fire more certain.

205. Tapias R, Climent J, Pardos JA, Gil LA. Life histories of Mediterranean pines. Plant Ecol. 2004;171:53-68.

206. Hernández-Serrano A, Verdú M, Santos-Del-Blanco L, Climent J, González-Martínez SC, Pausas JG. Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait. Ann Bot. 2014;114:571-7.

207. Pausas JG, Keeley JE. Evolutionary ecology of resprouting and seeding in fire-prone ecosystems. New Phytol. 2014;204:55-65.

208. Schwilk DW, Ackerly DD. Flammability and serotiny as strategies: correlated evolution in pines. Oikos. 2001;94:326-36.

209. Martín-Sanz RC, Santos-Del-Blanco L, Notivol E, Chambel MR, San-Martín R, Climent J. Disentangling plasticity of serotiny, a key adaptive trait in a Mediterranean conifer. Am J Bot. 2016;103:1582-91.

210. Van Gelder HA, Poorter L, Sterck FJ. Wood mechanics, allometry, and life-history variation in a tropical rain forest tree community. New Phytol. 2006;171:367-78.

211. Poorter L, McDonald I, Alarcón A, Fichtler E, Licona JC, Peña-Claros M, et al. The importance of wood traits and hydraulic conductance for the performance and life history strategies of 42 rainforest tree species. New Phytol. 2010;185:481-92.

212. Zobel BJ, van Buijtenen JP. Wood variation and wood properties. In: Wood variation. Springer Series in Wood Science. Springer, Berlin, Heidelberg. 1989;1-32.

213. Zobel BJ, Jett JB. The importance of wood density (specific gravity) and its component parts. In: Genetics of wood production. Springer Series in Wood Science. Springer, Berlin, Heidelberg. 1995.

214. Dungey HS, Matheson AC, Kain D, Evans R. Genetics of wood stiffness and its component traits in *Pinus radiata*. Can J For Res. 2006;36:1165-78.

215. Saranpää P. Wood density and growth. In: Barnett JR, Jeronimidis G, editors. Wood quality: its biological basis. Blackwell Publishing Ltd; 2003:226.

216. Mork F. Die qualitaat des fichtenholzes unter besonderer rucksichtnahme auf schleif-und papierholz. Papier Fabrikant. 1928;26:741-7.

217. Bendtsen BA, Senft J. Mechanical and anatomical properties in individual growth rings of plantation-grown eastern cottonwood and loblolly pine. Wood Fiber Sci. 2007;18:23-38.

218. Cave ID, Walker JCF. Stiffness of wood in fast-grown plantation softwoods - the influence of microfibril angle. For Prod J. 1994;44:43-8.

219. Gjerdrum P, Säll H, Storø HM. Spiral grain in Norway spruce: constant change rate in grain angle in Scandinavian sawlogs. Forestry. 2002;75:163-70.

220. Chen ZQ, Gil MRG, Karlsson B, Lundqvist SO, Olsson L, Wu HX. Inheritance of growth and solid wood quality traits in a large Norway spruce population tested at two locations in southern Sweden. Tree Genet Genomes. 2014;10:1291-303.

221. Hayatgheibi H, Fries A, Kroon J, Wu HX. Genetic analysis of lodgepole pine (*Pinus contorta*) solid-wood quality traits. Can J For Res. 2017;47:1303-13.

222. Hong Z, Fries A, Wu HX. Age trend of heritability, genetic correlation, and efficiency of early selection for wood quality traits in Scots pine. Can J For Res. 2015;45:817-25.

223. Lenz P, Cloutier A, MacKay J, Beaulieu J. Genetic control of wood properties in *Picea glauca* - an analysis of trends with cambial age. Can J For Res. 2010;40:703-15.

224. Kucera B. A hypothesis relating current annual height increment to juvenile wood formation in Norway spruce. Wood Fiber Sci. 1994;26:152-67.

225. Larson P, Kretschmann DE, Clark A, Isebrants JG. Formation and properties of juvenile wood in southern pines: a synopsis. Madison, WI: USDA Forest Service, Forest Products Laboratory 2001;42.

226. Mellerowicz EJ, Baucher M, Sundberg B, Boerjan W. Unraveling cell wall formation in the woody dicot stem. Plant Mol Biol. 2001;47:239-74.

227. Steffenrem A, Kvaalen H, Hoibo OA, Edvardsen OM, Skroppa T, Høibø OA, et al. Genetic variation of wood quality traits and relationships with growth in *Picea abies*. Scand J For Res. 2009;24:15-27.

228. Merrill REMC. Heritability and genetic correlations for stem diameter and branch characteristics in white spruce. Can J For Res. 1985;15:494-7.

229. Vestøl GI, Høibø OA. Prediction of knot diameter in *Picea abies* (L.) Karst. Holz als Roh - und Werkst. 2001;59:129-36.

230. Høibø OA. The quality of wood of Norway spruce (*Picea abies* (L.) Karst.) planted with different spacing. Agricultural University of Norway; 1991.

231. Johansson K. Effect of initial spacing on the stem and branch properties and graded quality of *Picea abies* (L.) Karst. Scand J For Res. 1992;7:503-14.

232. Vestøl GI, Colin F, Loubere M, Loubère M. Influence of progeny and initial stand density on the relationship between diameter at breast height and knot diameter of *Picea abies*. Scand J For Res. 1999;14:470-80.

233. Karlsson B, Hogberg K-A. Genotypic parameters and clone x site interaction in clone tests of Norway spruce (*Picea abies* (L.) Karst.). For Genet. 1998;5:21-30.

234. Magnussen SYC. Early testing of jack pine.: II Variance and repeatability of stem and branch characters. Can J For Res. 1987;17:460-5.

235. Magnussen SYC. Early testing of jack pine. I. Phenotypic response to spacing. Can J For Res. 1987;17:453-9.

236. Gräns D, Hannrup B, Isik F, Lundqvist SO, McKeand S. Genetic variation and relationships to growth traits for microfibril angle, wood density and modulus of elasticity in a *Picea abies* clonal trial in southern Sweden. Scand J For Res. 2009;24:494-503.

237. Wang X-R, Torimaru T, Lindgren D, Fries A. Marker-based parentage analysis facilitates low input 'breeding without breeding' strategies for forest trees. Tree Genet Genomes. 2009;6:227-35.

238. Hong Z, Fries A, Wu HX. High negative genetic correlations between growth traits and wood properties suggest incorporating multiple traits selection including economic weights for the future Scots pine breeding programs. Ann For Sci. 2014;71:463-72.

239. Fundova I, Funda T, Wu HX. Non-destructive wood density assessment of Scots pine (*Pinus sylvestris* L.) using Resistograph and Pilodyn. PLoS One. 2018;13:1-16.

240. Baltunis BS, Wu HX, Powell MB. Inheritance of density, microfibril angle, and modulus of elasticity in juvenile wood of *Pinus radiata* at two locations in Australia. Can J For Res. 2007;37:2164-74.

241. Wu HX, Ivkovic M, Gaspare WJ, Matheson AC, Baltunis BS, Powell MB, et al. Breeding for wood quality and profit in radiata pine: a review of genetic parameters. New Zeal J For Res. 2008;38:56-87.

242. Fries A, Ulvcrona T, Wu HX, Kroon J. Stem damage of lodgepole pine clonal cuttings in relation to wood and fiber traits, acoustic velocity, and spiral grain. Scand J For Res. 2014;29:764-76.
243. Bridgwater FE, Talbert JT, Jahromi S. Index selection for increased dry weight in a young loblolly pine populations. *Silvae Genet.* 1983;32.

244. Pot D, Chantre G, Rozenberg P, Rodrigues JC, Jones GL, Pereira H, et al. Genetic control of pulp and timber properties in maritime pine (*Pinus pinaster* Ait.). *Ann For Sci.* 2002;59:563-75.

245. Bouffier L, Raffin A, Rozenberg P, Meredieu C, Kremer A. What are the consequences of growth selection on wood density in the French maritime pine breeding programme? *Tree Genet Genomes.* 2008;5:11-25.

246. Hassegawa M, Savard M, Lenz PRN, Duchateau E, Gélinas N, Bousquet J, et al. White spruce wood quality for lumber products: priority traits and their enhancement through tree improvement. *Forestry.* 2020;93:16-37.

247. Lenz P, MacKay J, Rainville A, Cloutier A, Beaulieu J. The influence of cambial age on breeding for wood properties in *Picea glauca*. *Tree Genet Genomes.* 2011;7:641-53.

248. Lenz P, Auty D, Achim A, Beaulieu J, Mackay J. Genetic improvement of white spruce mechanical wood traits-early screening by means of acoustic velocity. *Forests.* 2013;4:575-94.

249. Kennedy SG, Cameron AD, Lee SJ. Genetic relationships between wood quality traits and diameter growth of juvenile core wood in Sitka spruce. *Can J For Res.* 2013;43:1-6.

250. Lindstrom H, Evans R, Abarquez A. Genetic control of the time of transition from juvenile to mature wood in *Pinus radiata* D. Don. *Ann For Sci.* 2006;63:871-8.

251. Hayatgheibi H, Forsberg NEG, Lundqvist SO, Mörling T, Mel-lerowicz EJ, Karlsson B, et al. Genetic control of transition from juvenile to mature wood with respect to microfibril angle in Nor-way spruce (*Picea abies*) and lodgepole pine (*Pinus contorta*). *Can J For Res.* 2018;48:1358-65.

252. Gapare WJ, Wu HX, Abarquez A. Genetic control of the time of transition from juvenile to mature wood in *Pinus radiata* D. Don. *Ann For Sci.* 2006;63:871-8.

253. Abdel-Gadir AY, Krahmer L. Genetic variation in the age of demarcation between juvenile and mature wood in Douglas fir. *Wood Fiber Sci.* 1993;25:384-94.

254. Pérez-Moreno J, Guerin-Laguette A, Rinaldi AC, Yu F, Ver-beken A, Hernández-Santiago F, et al. Edible mycorrhizal fungi of the world: what is their role in forest sustainability, food secu-rity, biocultural conservation and climate change? *Plants People Planet.* 2021;3:471-90.

255. Rodríguez-García A, López R, Martín JA, Pinillos F, Gil L. Resin yield in *Pinus pinaster* is related to tree dendrometry, stand density and tapping-induced systemic changes in xylem anatomy. *For Ecol Manage.* 2014;313:47-54.

256. Calama R, Gordo J, Madrigal G, Mutke S, Conde M, Montero G, et al. Enhanced tools for predicting annual stone pine (*Pinus pinea* L.) cone production at tree and forest scale in Inner Spain. *For Syst.* 2016;25.

257. Tadesse W, Nanos N, Auñon FJ, Alía R, Gil LA. Evaluation of high resin yielders of *Pinus pinaster* Ait. For Genet. 2001;8:271-7.

258. Mutke S, Iglesias S, Gil L. Selección de clones de pino piñonero sobresalientes en la producción de piña. Investig Agrar Sist y Recur For. 2007;16:39-51.

259. Liu Q, Zhou Z, Fan H, Liu Y. Genetic variation and correlation among resin yield, growth, and morphologic traits of *Pinus mas*-soniana. *Silvae Genet.* 2013;62:38-44.

260. Lai M, Dong L, Yi M, Sun S, Zhang Y, Fu L, et al. Genetic variation, heritability and genotype × environment interactions of resin yield, growth traits and morphologic traits for *Pinus elliottii* at three progeny trials. *Forests.* 2017;8:409.

261. Luo J, Xia W, Cao P, Xiao Z, Zhang Y, Liu M, et al. Integrated transcriptome analysis reveals plant hormones jasmonic acid and salicylic acid coordinate growth and defense responses upon functional infection in poplar. *Biomolecules.* 2019;9:12.

262. Eichmann R, Schäfer P. Growth versus immunity-a redirection of the cell cycle? *Curr Opin Plant Biol.* 2015;26:106-12.

263. Berens ML, Berry HM, Mine A, Argueso CT, Tsuda K. Evolution of hormone signalling networks in plant defense. *Annu Rev Phytopathol.* 2017;55:401-25.

264. • Zust T, Agrawal AA. Trade-offs between plant growth and defense against insect herbivory: an emerging mechanistic synthesis. *Annu Rev Plant Biol.* 2017; 68:534. **They provide a working model of the plant defence signalling network for regulation of growth-defence trade-offs and propose a unifying framework for growth-defence trade-offs as a means to study the plant allocation of limiting resources.**

265. Li Y, Yang Y, Hu Y, Liu H, He M, Yang Z, et al. DELLA and EDS1 form a feedback regulatory module to fine-tune plant growth-defense tradeoff in Arabidopsis. *Mol Plant.* 2019;12:1485-98.

266. Neuser J, Metzen CC, Dreyer BH, Feulner C, van Dongen JT, Schmidt RR, et al. HBI1 mediates the trade-off between growth and immunity through its impact on apoplastic ROS homeostasis. *Cell Rep.* 2019;28:1670-1678.e3.

267. Smakowska E, Kong J, Busch W, Belkhadir Y. Organ-specific regulation of growth-defense tradeoffs by plants. *Curr Opin Plant Biol.* 2016;29:129-37.

268. Berens ML, Wolinska KW, Spaepen S, Ziegler J, Nobori T, Nair A, et al. Balancing trade-offs between biotic and abiotic stress responses through leaf age-dependent variation in stress hormone cross-talk. *Proc Natl Acad Sci USA.* 2019;116:2364-73.

269. •• Nguyen HC, Cao PB, San Clemente H, Ployet R, Mounet F, Ladouce N, et al. Special trends in CBF and DREB2 groups in *Eucalyptus gunnii* vs *Eucalyptus grandis* suggest that CBF are master players in the trade-off between growth and stress resistance. *Physiol Plant.* 2017;159:445-67. **This comprehensive transcriptional analysis performed on leaves, stems and roots from two *Eucalyptus* species after cold, heat or drought treatment suggest that factors which promote both stress protection and growth limitation, participate in the trade-off between growth and resistance in this woody species.**

270. • Porth I, White R, Jaquish B. Ritland K. Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce. *New Phytol.* 2018;218:1349-59. **This paper use partial correlation analysis to identify gene networks underlying growth and susceptibility to weevil in spruce. In particular, transcripts that strongly modify the trade-off between growth and defense, and allow identification of networks more central to the trade-off.**

271. • Yu D, Wildhagen H, Tylewicz S, Miskolczi PC, Bhalerao RP, Polle A. Abscisic acid signalling mediates biomass trade-off and allocation in poplar. *New Phytol.* 2019;223:1192-203. **This study analyse genes involved in ABA stress signalling and photoperiodic regulation that affect drought resistance by trade-off with biomass production in poplar trees. The results suggest a critical role for ABA-mediated processes in balancing biomass production and climate adaptation.**

272. • Estravis-Barcala M, Mattera MG, Soliani C, Bellora N, Opge-noorth L, Heer K, et al. Molecular bases of responses to abiotic stress in trees. *J Exp Bot.* 2020;71:3765-79. **This review aims the understanding of the molecular bases of drought and temperature stresses in trees, with a focus on functional, transcriptomic, epigenetic, and population genomic studies. The importance of the review is that long-living trees have evolved a wide spectrum of molecular mechanisms to coordinate growth and development under stressful conditions, thus minimizing fitness costs.**
243. Bridgwater FE, Talbert JT, Jahromi S. Index selection for increased dry weight in a young loblolly pine populations. *Silvae Genet.* 1983;32.

244. Pot D, Chantre G, Rozenberg P, Rodrigues JC, Jones GL, Pereira H, et al. Genetic control of pulp and timber properties in maritime pine (*Pinus pinaster* Ait.). *Ann For Sci.* 2002;59:563–75.

245. Bouffier L, Raffin A, Rozenberg P, Meredieu C, Kremer A. What are the consequences of growth selection on wood density in the French maritime pine breeding programme? *Tree Genet Genomes.* 2008;5:11–25.

246. Hassegawa M, Savard M, Lenz PRN, Duchateau E, Gélinas N, Bousquet J, et al. White spruce wood quality for lumber products: priority traits and their enhancement through tree improvement. *Forestry.* 2020;93:16–37.

247. Lenz P, MacKay J, Rainville A, Cloutier A, Beaulieu J. The influence of cambial age on breeding for wood properties in *Picea glauca*. *Tree Genet Genomes.* 2011;7:641–53.

248. Lenz P, Auty D, Achim A, Beaulieu J, Mackay J. Genetic improvement of white spruce mechanical wood traits-early screening by means of acoustic velocity. *Forests.* 2013;4:575–94.

249. Kennedy SG, Cameron AD, Lee SJ. Genetic relationships between wood quality traits and diameter growth of juvenile core wood in Sitka spruce. *Can J For Res.* 2013;43:1–6.

250. Lindstrom H, Evans R, Abarquez A. Genetic control of the time of transition from juvenile to mature wood in *Pinus radiata* D. Don. *Ann For Sci.* 2006;63:871–8.

251. Hayatgheibi H, Forsberg NEG, Lundqvist SO, Mörling T, Mel-lerowicz EJ, Karlsson B, et al. Genetic control of transition from juvenile to mature wood with respect to microfibril angle in Nor-way spruce (*Picea abies*) and lodgepole pine (*Pinus contorta*). *Can J For Res.* 2018;48:1358–65.

252. Gapare WJ, Wu HX, Abarquez A. Genetic control of the time of transition from juvenile to mature wood in *Pinus radiata* D. Don. *Ann For Sci.* 2006;63:871–8.

253. Abdel-Gadir AY, Krahmer L. Genetic variation in the age of demarcation between juvenile and mature wood in Douglas fir. *Wood Fiber Sci.* 1993;25:384–94.

254. Pérez-Moreno J, Guerin-Laguette A, Rinaldi AC, Yu F, Ver-beken A, Hernández-Santiago F, et al. Edible mycorrhizal fungi of the world: what is their role in forest sustainability, food secu-rity, biocultural conservation and climate change? *Plants People Planet.* 2021;3:471–90.

255. Rodríguez-García A, López R, Martín JA, Pinillos F, Gil L. Resin yield in *Pinus pinaster* is related to tree dendrometry, stand density and tapping-induced systemic changes in xylem anatomy. *For Ecol Manage.* 2014;313:47–54.

256. Calama R, Gordo J, Madrigal G, Mutke S, Conde M, Montero G, et al. Enhanced tools for predicting annual stone pine (*Pinus pinea* L.) cone production at tree and forest scale in Inner Spain. *For Syst.* 2016;25.

257. Tadesse W, Nanos N, Auñon FJ, Alía R, Gil LA. Evaluation of high resin yielders of *Pinus pinaster* Ait. For Genet. 2001;8:271–7.

258. Mutke S, Iglesias S, Gil L. Selección de clones de pino piñonero sobresalientes en la producción de piña. *Investig Agrar Sist y Recur For.* 2007;16:39–51.

259. Liu Q, Zhou Z, Fan H, Liu Y. Genetic variation and correlation among resin yield, growth, and morphologic traits of *Pinus mas*-soniana. *Silvae Genet.* 2013;62:38–44.

260. Lai M, Dong L, Yi M, Sun S, Zhang Y, Fu L, et al. Genetic variation, heritability and genotype × environment interactions of resin yield, growth traits and morphologic traits for *Pinus elliottii* at three progeny trials. *Forests.* 2017;8:409.

261. Luo J, Xia W, Cao P, Xiao Z, Zhang Y, Liu M, et al. Integrated transcriptome analysis reveals plant hormones jasmonic acid and salicylic acid coordinate growth and defense responses upon functional infection in poplar. *Biomolecules.* 2019;9:12.

262. Eichmann R, Schäfer P. Growth versus immunity-a redirection of the cell cycle? *Curr Opin Plant Biol.* 2015;26:106–12.

263. Berens ML, Berry HM, Mine A, Argueso CT, Tsuda K. Evolution of hormone signalling networks in plant defense. *Annu Rev Phytopathol.* 2017;55:401–25.

264. • Zust T, Agrawal AA. Trade-offs between plant growth and defense against insect herbivory: an emerging mechanistic synthesis. *Annu Rev Plant Biol.* 2017; 68:534. **They provide a working model of the plant defence signalling network for regulation of growth–defence trade-offs and propose a unifying framework for growth–defence trade-offs as a means to study the plant allocation of limiting resources.**

265. Li Y, Yang Y, Hu Y, Liu H, He M, Yang Z, et al. DELLA and EDS1 form a feedback regulatory module to fine-tune plant growth–defense tradeoff in Arabidopsis. *Mol Plant.* 2019;12:1485–98.

266. Neuser J, Metzen CC, Dreyer BH, Feulner C, van Dongen JT, Schmidt RR, et al. HBI1 mediates the trade-off between growth and immunity through its impact on apoplastic ROS homeostasis. *Cell Rep.* 2019;28:1670-1678.e3.

267. Smakowska E, Kong J, Busch W, Belkhadir Y. Organ-specific regulation of growth-defense tradeoffs by plants. *Curr Opin Plant Biol.* 2016;29:129–37.

268. Berens ML, Wolinska KW, Spaepen S, Ziegler J, Nobori T, Nair A, et al. Balancing trade-offs between biotic and abiotic stress responses through leaf age-dependent variation in stress hormone cross-talk. *Proc Natl Acad Sci USA.* 2019;116:2364–73.

269. •• Nguyen HC, Cao PB, San Clemente H, Ployet R, Mounet F, Ladouce N, et al. Special trends in CBF and DREB2 groups in *Eucalyptus gunnii* vs *Eucalyptus grandis* suggest that CBF are master players in the trade-off between growth and stress resistance. *Physiol Plant.* 2017;159:445–67. **This comprehensive transcriptional analysis performed on leaves, stems and roots from two *Eucalyptus* species after cold, heat or drought treatment suggest that factors which promote both stress protection and growth limitation, participate in the trade-off between growth and resistance in this woody species.**

270. • Porth I, White R, Jaquish B. Ritland K. Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce. *New Phytol.* 2018;218:1349–59. **This paper use partial correlation analysis to identify gene networks underlying growth and susceptibility to weevil in spruce. In particular, transcripts that strongly modify the trade-off between growth and defense, and allow identification of networks more central to the trade-off.**

271. • Yu D, Wildhagen H, Tylewicz S, Miskolczi PC, Bhalerao RP, Polle A. Abscisic acid signalling mediates biomass trade-off and allocation in poplar. *New Phytol.* 2019;223:1192–203. **This study analyse genes involved in ABA stress signalling and photoperiodic regulation that affect drought resistance by trade-off with biomass production in poplar trees. The results suggest a critical role for ABA-mediated processes in balancing biomass production and climate adaptation.**

272. • Estravis-Barcala M, Mattera MG, Soliani C, Bellora N, Opge-noorth L, Heer K, et al. Molecular bases of responses to abiotic stress in trees. *J Exp Bot.* 2020;71:3765–79. **This review aims the understanding of the molecular bases of drought and temperature stresses in trees, with a focus on functional, transcriptomic, epigenetic, and population genomic studies. The importance of the review is that long-living trees have evolved a wide spectrum of molecular mechanisms to coordinate growth and development under stressful conditions, thus minimizing fitness costs.**
273. Thomas CD. Translocation of species, climate change, and the end of trying to recreate past ecological communities. *Trends Ecol Evol.* 2011;26:216–21.

274. Brown JKM, Rant JC. Fitness costs and trade-offs of disease resistance and their consequences for breeding arable crops. *Plant Pathol.* 2013;62:83–95.

275. Hallingbäck HR, Sánchez L, Wu HX. Single versus subdivided population strategies in breeding against an adverse genetic correlation. *Tree Genet Genomes.* 2014;10:605–17.

276. Gapare WJ, Baltunis BS, Ivković M, Wu HX. Genetic correlations among juvenile wood quality and growth traits and implications for selection strategy in *Pinus radiata* D. Don. *Ann For Sci.* 2009;66:606.

277. Ivković M, Wu HX, McRae TA, Matheson CA. Developing breeding objectives for radiata pine structural wood production. *II. Sensitivity analyses. Can J For Res.* 2006;36:2932–42.

278. Schlichting CD. Hidden reaction norms, cryptic genetic variation, and evolvability. *Ann N Y Acad Sci.* 2008;1133:187–203.

279. Willi Y, Buskirk J Van. A review on trade-offs at the warm and cold ends of geographical distributions. *Phil Trans R Soc B Biol Sci.* 2022;377: 20210022. *This review is focused on the evolution of the ecological niche at the edges of distributions and demonstrates that trade-offs overlapped with some of the classic trade-offs reported in life-history evolution or thermal adaptation.*

280. Freer-Smith P, Muys B, Bozzano M, Drössler L, Farrelly N, Jactel H et al. Plantation forests in Europe: challenges and opportunities. From Science to Policy 9. Eur For Inst. 2019;50

281. Brotherstone S, Goddard M. Artificial selection and maintenance of genetic variance in the global dairy cow population. *Philos Trans R Soc B Biol Sci.* 2005;360:1479–88.

282. Dwivedi SL, Reynolds MP, Ortiz R. Mitigating trade-offs in plant breeding. *iScience*. 2021;24:102965. *This study shows that regulating genes in grain crops deploy diverse functions to overcome trade-offs and therefore, mitigating trade-offs through breeding may expose new ones, which pose some caution in breeding for resistance.*

283. Lefèvre F, Koskela J, Hubert J, Kraigher H, Longauer R, Olrik DC, et al. Dynamic conservation of forest genetic resources in 33 european countries. *Conserv Biol.* 2012;27:1–12.

284. Koskela J, Lefèvre F, Schueler S, Kraigher H, Olrik DC, Hubert J, et al. Translating conservation genetics into management: Pan-European minimum requirements for dynamic conservation units of forest tree genetic diversity. *Biol Conserv.* 2013;157:39–49.

285. Aitken SN, Bemmels JB. Time to get moving: assisted gene flow of forest trees. *Evol Appl.* 2016;9:271–90. *This is a particularly comprehensive work addressing the current knowledge on the basis and perspectives of assisted migration (gene flow) in forest trees, with emphasis in N. America.*

286. Pelai R, Hagerman SM, Kozak R. Whose expertise counts? Assisted migration and the politics of knowledge in British Columbia's public forests. *Land Use Policy.* 2021;103:105296.

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
273. Thomas CD. Translocation of species, climate change, and the end of trying to recreate past ecological communities. *Trends Ecol Evol.* 2011;26:216–21.

274. Brown JKM, Rant JC. Fitness costs and trade-offs of disease resistance and their consequences for breeding arable crops. *Plant Pathol.* 2013;62:83–95.

275. Hallingbäck HR, Sánchez L, Wu HX. Single versus subdivided population strategies in breeding against an adverse genetic correlation. *Tree Genet Genomes.* 2014;10:605–17.

276. Gapare WJ, Baltunis BS, Ivković M, Wu HX. Genetic correlations among juvenile wood quality and growth traits and implications for selection strategy in *Pinus radiata* D. Don. *Ann For Sci.* 2009;66:606.

277. Ivković M, Wu HX, McRae TA, Matheson CA. Developing breeding objectives for radiata pine structural wood production. *II. Sensitivity analyses. Can J For Res.* 2006;36:2932–42.

278. Schlichting CD. Hidden reaction norms, cryptic genetic variation, and evolvability. *Ann N Y Acad Sci.* 2008;1133:187–203.

279. Willi Y, Buskirk J Van. A review on trade-offs at the warm and cold ends of geographical distributions. *Phil Trans R Soc B Biol Sci.* 2022;377: 20210022. *This review is focused on the evolution of the ecological niche at the edges of distributions and demonstrates that trade-offs overlapped with some of the classic trade-offs reported in life-history evolution or thermal adaptation.*

280. Freer-Smith P, Muys B, Bozzano M, Drössler L, Farrelly N, Jactel H et al. Plantation forests in Europe: challenges and opportunities. From Science to Policy 9. Eur For Inst. 2019;50

281. Brotherstone S, Goddard M. Artificial selection and maintenance of genetic variance in the global dairy cow population. *Philos Trans R Soc B Biol Sci.* 2005;360:1479–88.

282. Dwivedi SL, Reynolds MP, Ortiz R. Mitigating trade-offs in plant breeding. *iScience.* 2021;24:102965. *This study shows that regulating genes in grain crops deploy diverse functions to overcome trade-offs and therefore, mitigating trade-offs through breeding may expose new ones, which pose some caution in breeding for resistance.*

283. Lefèvre F, Koskela J, Hubert J, Kraigher H, Longauer R, Olrik DC, et al. Dynamic conservation of forest genetic resources in 33 european countries. *Conserv Biol.* 2012;27:1–12.

284. Koskela J, Lefèvre F, Schueler S, Kraigher H, Olrik DC, Hubert J, et al. Translating conservation genetics into management: Pan-European minimum requirements for dynamic conservation units of forest tree genetic diversity. *Biol Conserv.* 2013;157:39–49.

285. Aitken SN, Bemmels JB. Time to get moving: assisted gene flow of forest trees. *Evol Appl.* 2016;9:271–90. *This is a particularly comprehensive work addressing the current knowledge on the basis and perspectives of assisted migration (gene flow) in forest trees, with emphasis in N. America.*

286. Pelai R, Hagerman SM, Kozak R. Whose expertise counts? Assisted migration and the politics of knowledge in British Columbia's public forests. *Land Use Policy.* 2021;103:105296.

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Authors and Affiliations

Jose Climent<fnref n="1" /> ID · Ricardo Alía<fnref n="1" /> ID · Katri Karkkainen<fnref n="2" /> ID · Catherine Bastien<fnref n="3" /> ID · Marta Benito-Garzon<fnref n="4" /> ID ·

Laurent Bouffier<fnref n="4" /> ID · Giovanbattista De Dato<fnref n="5" /> ID · Sylvain Delzon<fnref n="4" /> ID · Arnaud Dowkiw<fnref n="3" /> ID ·

Margarita Elvira-Recuenco<fnref n="1" /> ID · Delphine Grivet<fnref n="1" /> ID · Santiago C. González-Martínez<fnref n="4" /> ID · Haleh Hayatgheibi⁶ ID ·

Sonja Kujala<fnref n="2" /> ID · Jean-Charles Leplé<fnref n="4" /> ID · Ruth C. Martín-Sanz⁷ ID · Marina de Miguel<fnref n="4" /> ID · M. Cristina Monteverdi<fnref n="5" /> ID ·

Sven Mutke<fnref n="1" /> ID · Christophe Plomion<fnref n="4" /> ID · José Alberto Ramírez-Valiente<fnref n="1" /> ID · Leopoldo Sanchez<fnref n="3" /> ID ·

Aida Solé-Medina<fnref n="1" /> ID · Jean-Paul Soularue<fnref n="4" /> ID · Arne Steffenrem⁸ ID · Angela Teani<fnref n="5" /> ID · Johan Westin⁶ ID ·

Richard Whittet⁹ ID · Harry Wu⁶ ID · Rafael Zas¹⁰ ID · Stephen Cavers¹¹ ID

<figure><img src="image_12.png" /></figure>

Jose Climent
climent@inia.csic.es

Ricardo Alía
alia@inia.csic.es

Katri Karkkainen
katri.karkkainen@luke.fi

Catherine Bastien
catherine.bastien@inrae.fr

Marta Benito-Garzon
marta.benito-garzon@inrae.fr

Laurent Bouffier
laurent.bouffier@inrae.fr

Giovanbattista De Dato
giovanbattista.dedato@crea.gov.it

Sylvain Delzon
sylvain.delzon@u-bordeaux.fr

Arnaud Dowkiw
arnaud.dowkiw@inrae.fr

Margarita Elvira-Recuenco
margarita.elvira@csic.es

Delphine Grivet
dgrivet@inia.csic.es

Santiago C. González-Martínez
santiago.gonzalez-martinez@inrae.fr

Haleh Hayatgheibi
haleh.hayatgheibi@slu.se

Sonja Kujala
sonja.kujala@luke.fi

Jean-Charles Leplé
jean-charles.leple@inrae.fr

Ruth C. Martín-Sanz
ruthcristina.martin@uva.es

Marina de Miguel
marina.de-miguel@inrae.fr

M. Cristina Monteverdi
mcristina.monteverdi@crea.gov.it

Sven Mutke
sven.mutke@csic.es

Christophe Plomion
christophe.plomion@inrae.fr

José Alberto Ramírez-Valiente
jose.ramirez@inia.csic.es

Leopoldo Sanchez
leopoldo.sanchez-rodriguez@inrae.fr

Aida Solé-Medina
aidasome@gmail.com

Jean-Paul Soularue
jean-paul.soularue@inra.fr

Arne Steffenrem
Arne.Steffenrem@nibio.no

Angela Teani
angela.teani@crea.gov.it

Johan Westin
johan.westin@slu.se

Richard Whittet
richard.whittet@forestresearch.gov.uk

Harry Wu
harry.wu@slu.se

Rafael Zas
rzas@mbg.csic.es

Stephen Cavers
scav@ceh.ac.uk

<figure><img src="image_13.png" /></figure>

<footnote n="1">¹ ICIFOR-INIA, CSIC, Ctra. A Coruña Km 7.5, 28040 Madrid, Spain</footnote>

<footnote n="2">² Natural Resources Institute Finland (LUKE), Latokartanonkaari 9, FI-00790 Helsinki, Finland</footnote>

<footnote n="3">³ UMR 0588 BioForA, INRAE, 2163 Avenue de La Pomme de Pin, 45000 Orléans, France</footnote>

<footnote n="4">⁴ INRAE, BIOGECO, Univ. Bordeaux, 33400 Pessac, France</footnote>

<footnote n="5">⁵ Council for Agricultural Research and Economics, Research Centre for Forestry and Wood, Viale Santa Margherita, 80, 52100 Arezzo, Italy</footnote>
Authors and Affiliations

Jose Climent<fnref n="1" /> ID · Ricardo Alía<fnref n="1" /> ID · Katri Karkkainen<fnref n="2" /> ID · Catherine Bastien<fnref n="3" /> ID · Marta Benito-Garzon<fnref n="4" /> ID ·

Laurent Bouffier<fnref n="4" /> ID · Giovanbattista De Dato<fnref n="5" /> ID · Sylvain Delzon<fnref n="4" /> ID · Arnaud Dowkiw<fnref n="3" /> ID ·

Margarita Elvira-Recuenco<fnref n="1" /> ID · Delphine Grivet<fnref n="1" /> ID · Santiago C. González-Martínez<fnref n="4" /> ID · Haleh Hayatgheibi⁶ ID ·

Sonja Kujala<fnref n="2" /> ID · Jean-Charles Leplé<fnref n="4" /> ID · Ruth C. Martín-Sanz⁷ ID · Marina de Miguel<fnref n="4" /> ID · M. Cristina Monteverdi<fnref n="5" /> ID ·

Sven Mutke<fnref n="1" /> ID · Christophe Plomion<fnref n="4" /> ID · José Alberto Ramírez-Valiente<fnref n="1" /> ID · Leopoldo Sanchez<fnref n="3" /> ID ·

Aida Solé-Medina<fnref n="1" /> ID · Jean-Paul Soularue<fnref n="4" /> ID · Arne Steffenrem⁸ ID · Angela Teani<fnref n="5" /> ID · Johan Westin⁶ ID ·

Richard Whittet⁹ ID · Harry Wu⁶ ID · Rafael Zas¹⁰ ID · Stephen Cavers¹¹ ID

<figure><img src="image_10.png" /></figure>

Jose Climent
climent@inia.csic.es

Ricardo Alía
alia@inia.csic.es

Katri Karkkainen
katri.karkkainen@luke.fi

Catherine Bastien
catherine.bastien@inrae.fr

Marta Benito-Garzon
marta.benito-garzon@inrae.fr

Laurent Bouffier
laurent.bouffier@inrae.fr

Giovanbattista De Dato
giovanbattista.dedato@crea.gov.it

Sylvain Delzon
sylvain.delzon@u-bordeaux.fr

Arnaud Dowkiw
arnaud.dowkiw@inrae.fr

Margarita Elvira-Recuenco
margarita.elvira@csic.es

Delphine Grivet
dgrivet@inia.csic.es

Santiago C. González-Martínez
santiago.gonzalez-martinez@inrae.fr

Haleh Hayatgheibi
haleh.hayatgheibi@slu.se

Sonja Kujala
sonja.kujala@luke.fi

Jean-Charles Leplé
jean-charles.leple@inrae.fr

Ruth C. Martín-Sanz
ruthcristina.martin@uva.es

Marina de Miguel
marina.de-miguel@inrae.fr

M. Cristina Monteverdi
mcristina.monteverdi@crea.gov.it

Sven Mutke
sven.mutke@csic.es

Christophe Plomion
christophe.plomion@inrae.fr

José Alberto Ramírez-Valiente
jose.ramirez@inia.csic.es

Leopoldo Sanchez
leopoldo.sanchez-rodriguez@inrae.fr

Aida Solé-Medina
aidasome@gmail.com

Jean-Paul Soularue
jean-paul.soularue@inra.fr

Arne Steffenrem
Arne.Steffenrem@nibio.no

Angela Teani
angela.teani@crea.gov.it

Johan Westin
johan.westin@slu.se

Richard Whittet
richard.whittet@forestresearch.gov.uk

Harry Wu
harry.wu@slu.se

Rafael Zas
rzas@mbg.csic.es

Stephen Cavers
scav@ceh.ac.uk

<figure><img src="image_11.png" /></figure>

<footnote n="1">¹ ICIFOR-INIA, CSIC, Ctra. A Coruña Km 7.5, 28040 Madrid, Spain</footnote>

<footnote n="2">² Natural Resources Institute Finland (LUKE), Latokartanonkaari 9, FI-00790 Helsinki, Finland</footnote>

<footnote n="3">³ UMR 0588 BioForA, INRAE, 2163 Avenue de La Pomme de Pin, 45000 Orléans, France</footnote>

<footnote n="4">⁴ INRAE, BIOGECO, Univ. Bordeaux, 33400 Pessac, France</footnote>

<footnote n="5">⁵ Council for Agricultural Research and Economics, Research Centre for Forestry and Wood, Viale Santa Margherita, 80, 52100 Arezzo, Italy</footnote>
⁶ Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, 901 87 Umeå, Sweden

⁷ iuFOR, University of Valladolid, Campus de Palencia, Avda. Madrid s/n, Palencia, Spain

⁸ Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO), Skolegata 22, 7713 Steinkjer, Norway

⁹ Forest Research, Northern Research Station, Roslin, Midlothian EH25 9SY, UK

¹⁰ Misión Biológica de Galicia, CSIC, A Carballeira, 8, 36143 Salcedo, Pontevedra, Spain

¹¹ UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, Midlothian, Scotland, UK
⁶ Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, 901 87 Umeå, Sweden

⁷ iuFOR, University of Valladolid, Campus de Palencia, Avda. Madrid s/n, Palencia, Spain

⁸ Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO), Skolegata 22, 7713 Steinkjer, Norway

⁹ Forest Research, Northern Research Station, Roslin, Midlothian EH25 9SY, UK

¹⁰ Misión Biológica de Galicia, CSIC, A Carballeira, 8, 36143 Salcedo, Pontevedra, Spain

¹¹ UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, Midlothian, Scotland, UK