# Low genetic diversity and high phenotypic plasticity for growth traits and growth-climate relationships in Pinus nigra Arnold, the European black pine

Guia Giovannelli, Clara Tallieu, Hendrik Davi, Frédéric Guibal, Caroline Scotti-Saintagne, Bruno Fady

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Guia Giovannelli, Clara Tallieu, Hendrik Davi, Frédéric Guibal, Caroline Scotti-Saintagne, et al.. Low genetic diversity and high phenotypic plasticity for growth traits and growth-climate relationships in Pinus nigra Arnold, the European black pine. 2025. hal-05195614v2

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For the purpose of Open Access, a CC-BY 4.0 public copyright license has been applied by the authors to the present document (https://creativecommons.org/licenses/by/4.0/).

# Title: Low genetic diversity and high phenotypic plasticity for growth traits and growth-climate relationships in *Pinus nigra* Arnold, the European black pine

Authors : Guia Giovannelli¹,², Clara Tallieu¹,³, Hendrik Davi¹, Frédéric Guibal², Caroline Scotti-Saintagne¹, Bruno Fady¹

## Addresses:

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¹: INRAE, UR629, Ecologie des Forêts Méditerranéennes (URFM), Domaine Saint Paul, 84914 Avignon, France.

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²: IMBE, Aix Marseille Univ, Avignon Univ, CNRS, IRD, Technopôle de l'environnement Arbois Méditerranée, Avenue Louis Philibert, 13545 Aix en Provence, France.

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³: Région Grand Est, Direction de l'Eau, de la Biodiversité et du Climat, Service Biodiversité, 1 place Adrien Zeller, BP 91006, 67070 Strasbourg Cedex.

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## Abstract

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Radial growth is a fitness-related adaptive trait in forest trees that is expected to vary among populations under variable habitat conditions. Common gardens are widely used for the investigation of genetic variability, genotype by environment interactions and phenotypic plasticity of fitness related traits and provide information on adaptation useful for breeding and plantation forestry. *Pinus nigra* J.F. Arnold (1785), the European black pine, is a forest tree species widely but patchily distributed throughout southern Europe, from isolated locations in
north Africa to the Black Sea and Western Asia. While it has been widely used as plantation species since the mid-19th century because of its strong growth on rather poor soils, the diversity of the growth traits of its different genetic lineages and geographic origins has rarely been compared in similar environments before. In this study, we analyzed the radial growth performance of sixteen different geographic origins (provenances) of *P. nigra* growing in four bioclimatically contrasted common gardens in France.

Using a tree-ring to climate relationship approach and a 40-year long chronology, we first estimated how variable the effect of monthly climate was on radial growth, depending on phylogenetic or geographic origin, and plantation habitat. We then used the tree ring data to estimate genetic and plasticity effects on growth and to test for the existence of genotype by environment interactions. Lastly, we ranked the growth performance of the different subspecies and provenances measured in each common garden, having in mind a typology for forest management.

Results showed few climate effect differences among provenances and subspecies, with late spring minimum temperatures affecting growth negatively and early summer precipitations positively, overall. Winter maximum temperatures affected growth differently depending on the site, with a negative correlation at the warmest sites and a positive correlation at the coldest one. The provenance effect was stronger than the subspecies effect for radial growth and phenotypic plasticity was very high across the four sites (doubling of growth from low to high fertility sites). Results also showed a relative stability of provenance ranking among the four study sites. While some provenances of *P.n.* subsp. *pallasiana*, *P.n.* subsp. *laricio* and *P.n.* subsp. *nigra* performed well in all sites, others from the same subspecies displayed significant genotype by environment interactions. Provenances of the subspecies *P.n.* subsp. *salzmannii* displayed higher early growth up to 15 years of age compared to the other provenances, across all sites, but became poorly ranked afterwards except in the least fertile test site.

Provenance variability within subspecies and not just subspecies variability should be considered in plantation forestry, both for restoration and timber production.

**Keywords:** European black pine, radial growth, height growth, provenance test, climate change, dendroecology.

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**Introduction**

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Radial (or secondary) growth is an adaptive, fitness-related trait in forest trees that is expected to vary among populations if habitat conditions are variable (Eilmann et al. 2014, Gárate-Escamilla et al. 2019, Latreille et al. 2017). Radial growth is frequently measured using tree ring-width in relation to age as it correlates well with biomass production, a trait of high interest in forestry (Campbell et al. 2004, Graumlich et al. 1989). It is also measured to decipher past climate variations and, conversely, analyze the effects of climate on growth patterns across time (Fritts 1971, Rathgeber et al. 2000). Understanding how species and population radial growth reacts to climate and their local environment in plantation settings is particularly important in a context of rapidly changing climate and adaptive management techniques that increasingly advocate the use of assisted migration, the translocation of potentially pre-adapted material to future, warmer climates (Chakraborty et al. 2024, Gray et al. 2011, Palik et al. 2022).

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Common garden tests are a widely employed experimental tool for the investigation of genetic variability, genotype by environment interaction and phenotypic plasticity of fitness-related traits (Schwinning et al. 2022, Taïbi et al. 2014, Vitasse et al. 2010). Provenance tests, a particular type of common garden, are composed of plant material (often seed lots) of known geographic origin collected from (reputedly) unrelated seed trees. Provenances from widely diverging local environments potentially display local adaptations that are then expressed differentially in replicated common gardens installed in different environmental and climatic conditions (Fady & Rihm 2022, Langlet 1971). Provenance tests can thus provide key genetic and phenotypic information free of confounding environmental effects, about the performance of populations from diverse geographical and climatic origins (Varelides et al. 2001), making it possible to improve forest genetic resource conservation and deploy adapted reproductive materials for reforestation programs (Koskela et al. 2014, Vinceti et al. 2020, Woolridge et al. 2023).

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*Pinus nigra* J.F. Arnold (1785), the European black pine, belongs to the family *Pinaceae*, genus *Pinus* and subgenus *Pinus* (Mirov 1967, Price et al. 1998). Its current distribution extends from isolated locations in North Africa eastwards to larger populations across southern and central Europe and to Türkiye and Crimea, covering a wide range of soil types, topographic conditions and climates (Isajev et al. 2004, Zaghi 2008). Its currently large but highly fragmented geographic distribution contrasts with its relatively limited genetic differentiation and high levels of admixture which result from incomplete lineage sorting during the
Pleistocene glacial cycles and recent divergence during the Holocene (Bogunic et al. 2007, Scotti-Saintagne et al. 2019). Plantations using material of unknown origin during the 19th and 20th centuries may have locally further admixed populations (Scotti-Saintagne et al. 2023). As a result, morphological, anatomical and physiological traits are highly variable within geographic origins (Isajev et al. 2004, Naydenov et al. 2006) and complicate taxonomy, with nomenclatures recognizing two to seven subspecies-level taxa (Enescu et al. 2016, Fukarek 1958). International taxonomic authorities such as The Catalogue of Life (http://www.catalogueoflife.org/), Plant the World Online (https://powo.science.kew.org/) or Euro+Med PlantBase (https://europlusmed.org/), based on the morphological and biogeographic work of Gaussen et al. (1964), recognize five subspecies, from west to east: *Pinus nigra* subsp. *salzmannii* (Dunal) Franco in North Africa, Spain and continental France, *Pinus nigra* subsp. *laricio* (Poir.) Maire in Corsica (France), Calabria and Sicily (Italy), *Pinus nigra* subsp. *dalmatica* (Vis.) Franco on the coast of Croatia, *Pinus nigra* subsp. *nigra* in northern Italy, Austria and most of Central Europe and the western Balkans, and *Pinus nigra* subsp. *pallasiana* (Lamb.) Holmboe in parts of Greece and the eastern Balkans, Cyprus, Türkiye and Crimea. The most recent phylogenetic study of the species (Scotti-Saintagne et al. 2019) identified six lineages, splitting *P.n.* subsp. *pallasiana* into two distinct genetic groups, one homogeneous in Cyprus and one relatively admixed encompassing all other eastern Mediterranean and Black Sea populations, confirming results obtained from common gardens (Wheeler et al. 1976) and isozyme analyses (Nikolić and Tucić 1983).

Several dendroclimatic studies have shown that black pine is sensitive to high summer temperatures and to water deficit during spring and summer (Amodei et al. 2013, Lebourgeois 2000, Martín-Benito et al. 2008). This sensitivity is critical in areas where drought is frequent, such as the Mediterranean region (Génova & Fernández 1999, Lebourgeois 2000, Linares & Tíscar 2011, Martin-Benito et al. 2010, Richter et al. 1991), where an increase in mean temperature and a decrease in precipitation is likely in the foreseeable future (Sumner et al. 2003, Giorgi & Lionello 2008, MedECC 2020). Camarero et al. (2013) showed that, in relict rear-edge *P. nigra* populations in southern Spain and Morocco, growth responses to drought changed along an aridity gradient, and that dry conditions before tree-ring formation constituted the major constrain for growth. Previous studies have also highlighted that *P. nigra* growth in Iberian forests was enhanced by wet and cold conditions during the previous autumn and by warm late winters (Andreu et al. 2007, Martín-Benito et al. 2010). Finally, soil texture and its relative ability to store water were identified as major drivers for radial growth (Génova &
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Martinez-Morillas 2002, Camarero et al. 2013), including at very short spatial scales (Amodei et al. 2013).

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Yet, little data and few analyses exist on the genetic diversity of the correlation between radial growth and climate in adult black pines (see Thiel et al. 2012. for seedling experiment showing lack of diversity). Most multi-site common gardens were established with the aim of providing information on the best seed sources for plantation forestry and as a basis for breeding, focusing on traits such as mortality, height and diameter growth, and resistance to insects and pathogens. Results showed that genetic diversity for growth traits was high among subspecies and provenances. They also tended to demonstrate a stronger hardiness in *Pinus nigra* subsp. *nigra*, and fast growth, slender branches and higher volume in *P.n.* subsp. *laricio* in high fertility, milder climate sites (Kreyling et al. 2012, Seho et al. 2010, Wheeler et al. 1976, Wilcox & Miller 1975). Most of these experiments poorly sampled the easternmost and westernmost *Pinus nigra* lineages (but see Varelides et al. 2001) and led to breeding programs focused on Corsican black pine (for France, see Portefaix et al. 1987, Portefaix 1989), while Austrian black pine was mostly used in erosion control, restauration projects.

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In this context, the objective of our study is to understand how variable the effect of monthly climate is on radial growth, depending on phylogenetic or geographic origin, and plantation habitat. We then use tree ring data to estimate the relative contribution of genetic and plasticity effects on growth and to test for the existence of genotype by environment interactions. Lastly, we ranked the growth performance of the different subspecies and provenances measured in each common garden, having in mind a typology for forest management.

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## Materials and methods

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### Common garden and provenance description

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Growth data were collected from four sites located in different habitats covering the main bioclimatic zones of France (Table 1, Figure 1): Cestas in southwestern France (oceanic climate), Levens in southeastern France (Mediterranean mountain climate), Pomet (two adjacent tests with different provenances) in southeastern France (peri-Mediterranean climate with a slight water deficit during the summer) and Verdun (two adjacent tests with different provenances) in northeastern France (continental climate).
Figure 1: Ombrothermic diagrams of the four Pinus nigra experimental sites. The temperature scale is twice that of the precipitation scale. Precipitations are featured as blue bars, temperatures as red curves. Months are numbered from January onward.

<figure><img src="image_2.png" /></figure>

The common gardens were planted between 1968 and 1974 with the initial purpose of comparing the performance of provenances and subspecies for breeding and reproductive material selection in environmental conditions where black pine plantation forests were a target of management, both for wood production and erosion control.
<table><caption>Table 1: Common garden sites selected for the study and their main characteristics (* trial design: BICA: incomplete blocks with random composition; BC: complete blocks). Common garden characteristics are described in detail in Fady et al. (2024).</caption><thead><tr><th></th><th>Cestas</th><th>Levens</th><th>Pomet</th><th>Verdun</th></tr></thead><tbody><tr><td>Trial name</td><td></td><td></td><td></td><td></td></tr><tr><td>Trial code</td><td>01-4200-09-02</td><td>01-4200-02-01</td><td>01-4200-09-03 (latt / mono)</td><td>01-4200-02-03 / 01-4200-06-03</td></tr><tr><td>Site status</td><td>Private (INRAE)</td><td>State forest</td><td>State forest</td><td>State forest</td></tr><tr><td>Plantation date (year-month-day)</td><td>1974-03-06</td><td>1968-Spring</td><td>1973-Fall</td><td>1968-03-08 / 1971-05-28</td></tr><tr><td>Trial design*</td><td>CB</td><td>BICA</td><td>BICA / CB</td><td>BICA / BICA</td></tr><tr><td>Seedlings age at plantation time</td><td>2+0</td><td>1+2</td><td>1+1</td><td>1+2</td></tr><tr><td>Mean annual precipitation (mm)</td><td>980</td><td>840</td><td>763</td><td>882</td></tr><tr><td>Mean annual temperature (°C)</td><td>12.3</td><td>7.4</td><td>10.2</td><td>9</td></tr><tr><td>Mean monthly minimum temperature (°C)</td><td>5.7</td><td>-1</td><td>1.1</td><td>1.3</td></tr><tr><td>Mean monthly maximum temperature (°C)</td><td>19.6</td><td>16.8</td><td>19.9</td><td>17.2</td></tr><tr><td>Initial spacing (m)</td><td>4x1.1</td><td>2x2</td><td>2x2</td><td>2x2</td></tr><tr><td>Total area (ha)</td><td>2.21</td><td>4.83</td><td>0.96 / 0.53</td><td>3.2 / 3.46</td></tr><tr><td>Number of provenances</td><td>105</td><td>31</td><td>25 / 19</td><td>31 / 25</td></tr><tr><td>Number of blocks</td><td>7</td><td>30</td><td>30 / 70</td><td>36 / 30</td></tr><tr><td>Number of plots / block</td><td>105</td><td>6</td><td>5 / 19</td><td>6 / 5</td></tr><tr><td>Number of trees / plot</td><td>6</td><td>56</td><td>16 / 1</td><td>25 / 36</td></tr><tr><td>Total number of trees / test</td><td>4716</td><td>10109</td><td>2400 / 1330</td><td>5400 / 5410</td></tr><tr><td>Bioclimate</td><td>Oceanic</td><td>Mountain</td><td>Supra-Mediterranean</td><td>Continental</td></tr><tr><td>Latitude (degree decimal)</td><td>44.7388</td><td>43.8775</td><td>44.2926</td><td>49.2111</td></tr><tr><td>Longitude (degree decimal)</td><td>-0.7623</td><td>6.2939</td><td>5.7952</td><td>5.4496</td></tr><tr><td>Elevation (m)</td><td>58</td><td>1332</td><td>838</td><td>335</td></tr><tr><td>Aspect</td><td>Flat</td><td>North-West</td><td>South-West</td><td>Flat</td></tr><tr><td>Substrate</td><td>Sedimentary sil-ica</td><td>Sedimentary limestone</td><td>Sedimentary limestone</td><td>Sedimentary limestone</td></tr></tbody></table>

Sixteen provenances from a large part of the European geographic range of *Pinus nigra* were selected for this study (Table 2). Most of the provenances were present in at least three of the four sites and seven were present in all sites. The sixteen provenances belonged to four black pine subspecies: *P.n.* subsp. salzmannii, *P.n.* subsp. laricio, *P.n.* subsp. nigra and *P.n.* subsp. pallasiana. Together, they sample all genetic lineages described in *Pinus nigra* (Scotti-Saintagne 2019), either as pure or admixed provenances (Table 2).
<table><caption>Table 2: Pinus nigra provenances selected for the study and their main geographic characteristics. Genetic group is according to Figure 3 of Scotti-Saintagne et al. 2019.</caption><thead><tr><th rowspan="2">Provenance name</th><th rowspan="2">Provenance Code</th><th rowspan="2">Subspecies</th><th rowspan="2">Country</th><th rowspan="2">Genetic group</th><th colspan="3">Geographic coordinates</th><th colspan="4">Presence (x) in each common garden</th></tr><tr><th>Latitude</th><th>Longitude</th><th>Altitude (m)</th><th>Pomet</th><th>Cestas</th><th>Levens</th><th>Verdun</th></tr></thead><tbody><tr><td>Aspromonte</td><td>ASPR</td><td>P.n. laricio</td><td>Italy</td><td>2</td><td>38°05′N</td><td>16°00′E</td><td>1300</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Cosenza</td><td>COSE</td><td>P.n. laricio</td><td>Italy</td><td>2+3</td><td>39°15′N</td><td>16°17′E</td><td>1300</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Valdoniello</td><td>VALD</td><td>P.n. laricio</td><td>France</td><td>2</td><td>41°51′N</td><td>9°06′E</td><td>1100</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Doblhoff</td><td>DOBL</td><td>P.n. nigra</td><td>Austria</td><td>3</td><td>48°00′N</td><td>16°13′E</td><td>280</td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>Perithorion</td><td>PERT</td><td>P.n. nigra</td><td>Greece</td><td>3</td><td>38°05′N</td><td>22°15′E</td><td>1300</td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>Studenica</td><td>STUD</td><td>P.n. nigra</td><td>Serbia</td><td>3+4</td><td>43°30′N</td><td>20°33′E</td><td>930</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>Thasos</td><td>THAS</td><td>P.n. nigra</td><td>Greece</td><td>4+5</td><td>40°40′N</td><td>24°40′E</td><td>850</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>Tzarvaritza / Kustendil</td><td>TZKU</td><td>P.n. nigra</td><td>Bulgaria</td><td>3</td><td>42°01′N</td><td>22°50′E</td><td>1050</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Aluchtin</td><td>CRIM</td><td>P.n. pallasiana</td><td>Crimea</td><td>5</td><td>44°33′N</td><td>34°17′E</td><td>500</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Ayanick</td><td>AYAN</td><td>P.n. pallasiana</td><td>Türkiye</td><td>5</td><td>41°43′N</td><td>34°31′E</td><td>1400</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Popova-Livada</td><td>POLV</td><td>P.n. pallasiana</td><td>North Macedonia</td><td>3+4</td><td>41°10′N</td><td>21°55′E</td><td>1450</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>Yilanli / Mugla</td><td>YIMU</td><td>P.n. pallasiana</td><td>Türkiye</td><td>4+5+6</td><td>37°20′N</td><td>28°24′E</td><td>975</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>Cazorla</td><td>CAZO</td><td>P.n. salzmannii</td><td>Spain</td><td>1</td><td>37°50′N</td><td>3°00′W</td><td>1500</td><td></td><td></td><td>x</td><td>x</td></tr><tr><td>Fresneda</td><td>FRES</td><td>P.n. salzmannii</td><td>Spain</td><td>1</td><td>40°23′N</td><td>2°08′W</td><td>1025</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>Priego</td><td>PRIE</td><td>P.n. salzmannii</td><td>Spain</td><td>1</td><td>40°27′N</td><td>2°18′W</td><td>850</td><td>x</td><td>x</td><td></td><td>x</td></tr><tr><td>St.Guilhem / Gagnières</td><td>GAS-GUL</td><td>P.n. salzmannii</td><td>France</td><td>2</td><td>44°07′N</td><td>4°17′E</td><td>350</td><td>x</td><td>x</td><td>x</td><td>x</td></tr></tbody></table>

## Climate data

Climatic data were collected from SAFRAN® (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie), a reanalysis dataset initially designed to provide atmospheric forcing data in mountainous areas for avalanche hazard forecasting (Durand et al. 1993) and successively extended to feed macroscale soil-vegetation-atmosphere transfer models over the whole France (Le Moigne 2002). SAFRAN provides hourly climatic data with a resolution of 8 km using the Lambert-II projection (Pagé 2008). Climatic data were collected, for each of the four sites, for the period extending from 1959 to 2013. The period is characterized by some exceptional years, such as 1976 (summer drought except in southern France) and 2003 (summer heat wave). To estimate relationships between ring-width and climate and account for black pine's known sensitivity to high summer temperatures and water deficit during spring and summer (Amodei et al. 2013, Lebourgeois 2000, Martin-Benito et al. 2008), we selected monthly variables potentially able to limit the European black pine radial
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growth: mean minimal and maximal temperature and the annual precipitations. The climate
data used are available open access in Fady et al. (2024).

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## Description of response variables

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Annual tree ring-widths were measured on wood cores collected in 2014 on a subset of twenty individuals per provenance in each common garden using a Swedish increment borer mounted on a combustion engine. We sampled two radii per individual at breast height. As radial growth is sensitive to competition and social status (Lebourgeois et al. 2014, Martín-Benito et al. 2008), we selected healthy, dominant and cylindrical trees without forking defects, surrounded by an equal number of four codominant neighbors.

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The collected cores were dried at room temperature for one month and then sanded. Ring-width was measured with a precision of 1/100th mm using LINTAB, a robust and precise table for the measurement of ring-width series for increment cores in association with a Leica stereo microscope and the TSAP-WIN software (Frank Rinn®). Individual annual ring-width were calculated as the mean of the two radii collected on each tree and were used for the analysis of growth-climate relationships.

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From annual tree rings, we derived five variables: mean ring-width (rw), early-stage mean ring-width (between 0 and 15 years of age, rw15), young adult-stage mean ring-width (between 16 and 39 years of age, rw39), diameter at 15 years old calculated using ring-width (D15), diameter at 39 years old calculated using ring-width (D39). The two different lifetime periods selected for calculating tree ring-width means derive from an observation of the growth-chronology curves obtained from the aggregated subspecies raw data in the four sites (Figure 2). The period (0-15 years, rw15) is a phase of establishment where trees are less prone to competition, whereas during the second period (16-39 years, rw39) individuals are more established in their environment, among tree competition is stronger and tree ring-width declines. While rw15 and rw39 provide an idea of growth speed at two different periods, D15 and D39 provide an idea of basal area at the same two different periods.

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<figure><img src="image_3.png" /><figcaption>Figure 2: Growth chronology curves spanning four decades made of individual ring-width raw data aggregated as means at four different test sites for four Pinus nigra subspecies.</figcaption></figure>

We measured two additional, more integrated, phenotypic traits on all individuals in all common gardens: total height at 8 years old (the only height measurement available concurrently on all sites, H8) and circumference at breast height measured in 2014 when trees were cored (Circ). All datasets are described and available open access in Fady et al. (2024).

## Data analysis

Data analysis was carried out considering adjacent tests within the same location as a single analytical unit. We used the datasets containing all provenances, thus replicated two to four times across sites, to analyze overall climate-growth trends and genetic diversity at subspecies and provenance levels. To assess site effects, we used the dataset restricted to the seven provenances present in all sites (Table 2).
231 *Effect of climate on tree ring-width*

232 To identify the relationships between climatic variables and radial growth, individual ring- 233 width series were standardized using the “detrend series” function of the R package “dplR” 234 (Bunn et al. 2016). The detrending estimates and removes the low and intermediate frequency 235 variability that is due to biological or stand effects; this is done by dividing each series by the 236 growth trend to produce dimensionless ring-width indices (rwi) with constant mean and 237 standard deviation over time. In this study, ring-width series were standardized with the 238 autoregressive method which removes all but the high frequency variation in the series and 239 which is well adapted to short chronologies such as ours. The detrended ring-width series were 240 then used to build mean chronologies with the “chron” function of the R package “dplR” (Bunn 241 et al. 2016). Pearson’s correlation coefficients were then calculated between each mean 242 chronology and their corresponding climatic variables over a twelve-month period, from 243 October of the previous year to September of the current year, using the “dcc” function of the 244 R package “bootRes” (Zang & Biondi 2012).

245 *Among subspecies and provenance variation in growth traits*

246 We estimated the block, provenance and subspecies effects on all response variable within 247 each site using the full dataset and an analysis of variance (ANOVA) and the following linear 248 model implemented in the “lmer” function in R (R Core Team 2015):

249 $$ Y = \mu + P + B + \varepsilon \quad (\text{equation 1}) $$

250 where Y is the response variable, μ is the general mean, P is the provenance (or subspecies) 251 random effect, B is the random block effect and ε is the error term.

252 We then used the reduced, seven-provenance dataset and the following “lmer” function to 253 further explore environmental effects on provenance variation:

254 $$ Y = \mu + S + P(S) + B(S) + \varepsilon \quad (\text{equation 2}) $$

255 where Y is the response variable, μ is the general mean, S is the site fixed effect, P(S) is the 256 random provenance effect within each site, B(S) is the random block effect within each site and 257 ε is the error term. To estimate phenotypic plasticity, block effect adjusted provenance means 258 were then compared across sites using the non-parametric rank comparison “rank Kruskal- 259 Wallis” test in R (R Core Team 2015) under the null hypothesis that provenance means are
260 identical while the alternative hypothesis is that at least one provenance is different from the mean (Hollander & Wolfe 1973). Finally, site differences in mean trait values were tested using a two-sided Student T-test.

263

## 264 Results

### 265 Climate-growth relationships

266 We obtained high quality annual ring-width data spanning the period 1970 to 2013 from 867 individuals sampled from all common gardens (Table 3) which were used to explore climate-growth relationships at species, subspecies and provenance levels.

269

<table><caption>Table 3: Ring-width mean values (mm, 1970 to 2013) obtained for the four subspecies and the 16 provenances of *P. nigra* within each test site.</caption><thead><tr><th></th><th>Sites</th><th>CESTAS</th><th>LEVENS</th><th>POMET</th><th>VERDUN</th></tr></thead><tbody><tr><td rowspan="5">Subspecies</td><td>All provenances</td><td>3.21</td><td>3.31</td><td>2.51</td><td>3.04</td></tr><tr><td><i>P.n. laricio</i></td><td>3.59</td><td>3.26</td><td>2.48</td><td>3.07</td></tr><tr><td><i>P.n. nigra</i></td><td>3.31</td><td>3.28</td><td>2.55</td><td>3.33</td></tr><tr><td><i>P.n. pallasiana</i></td><td>3.02</td><td>3.49</td><td>2.58</td><td>3.09</td></tr><tr><td><i>P.n. salzmannii</i></td><td>2.89</td><td>3.14</td><td>2.34</td><td>2.65</td></tr><tr><td rowspan="15">Provenances</td><td>ASPR</td><td>3.48</td><td>3.18</td><td>2.38</td><td>2.94</td></tr><tr><td>AYAN</td><td>3.6</td><td>3.5</td><td>2.72</td><td>3.12</td></tr><tr><td>CAZO</td><td>na</td><td>3.11</td><td>na</td><td>2.82</td></tr><tr><td>COSE</td><td>3.71</td><td>3.4</td><td>2.63</td><td>3.19</td></tr><tr><td>CRIM</td><td>3.05</td><td>3.81</td><td>2.45</td><td>3.24</td></tr><tr><td>DOBL</td><td>2.86</td><td>na</td><td>2.25</td><td>na</td></tr><tr><td>FRES</td><td>2.83</td><td>na</td><td>2.73</td><td>2.8</td></tr><tr><td>GASGUL</td><td>2.81</td><td>3.14</td><td>2.18</td><td>2.45</td></tr><tr><td>PERT</td><td>2.18</td><td>na</td><td>2.33</td><td>na</td></tr><tr><td>POLV</td><td>2.76</td><td>na</td><td>2.55</td><td>2.8</td></tr><tr><td>PRIE</td><td>3.1</td><td>na</td><td>2.51</td><td>na</td></tr><tr><td>STUD</td><td>3.89</td><td>na</td><td>2.57</td><td>3.23</td></tr><tr><td>THAS</td><td>3.45</td><td>na</td><td>2.7</td><td>3.54</td></tr><tr><td>TZKU</td><td>3.29</td><td>3.28</td><td>2.74</td><td>3.27</td></tr><tr><td>VALD</td><td>3.59</td><td>3.19</td><td>2.36</td><td>3.09</td></tr><tr><td>YIMU</td><td>2.95</td><td>na</td><td>2.59</td><td>3.13</td></tr></tbody></table>

272

273 At species level, aggregated data showed significant negative correlations between growth and late spring maximum temperatures at all sites except Levens, the coldest, highest elevation

274
Climate correlations at subspecies level were similar to those aggregated at species level, with some variation depending on site conditions (Table 4). While negative correlations between growth and late spring maximum temperatures remained significant at all sites except Levens, *P.n.* subsp. *nigra* showed less sensitivity overall to maximum temperatures at Verdun and Cestas (the wettest sites) than at Pomet (the driest site). At the continental site of Verdun, *P.n.* subsp. *nigra* showed fewer negative correlations with minimum temperatures while at Pomet and Levens, it was *P.n.* subsp. *laricio*. As for precipitations, *P.n.* subsp. *salzmannii* diverged slightly from the general pattern with a negative effect in August and no effect in June at Verdun, and a positive effect of October at Cestas.

Climate correlations at provenance level were similar to those at subspecies level, also with some noteworthy exceptions (Table 4). For example, the *P.n.* subsp. *laricio* provenances ASPR from Italy and VALD from France (belonging to the same genetic group) were less sensitive to minimum and maximum temperatures than the admixed *P.n.* subsp. *laricio* provenance COSE from Italy, while in Cestas it was the opposite for minimum temperatures. The three *P.n.* subsp. *laricio* provenances diverged in their reaction to precipitations irrespectively of their genetic group at all sites except Levens where precipitation anomalies did not affect growth. Some divergence between the two *P.n.* subsp. *pallasiana* provenances tested at Levens were found for sensitivity to fall minimum temperatures. Few differences were found between the Bulgarian *P.n.* subsp. *nigra* provenance TZKU and the overall subspecies mean in the three sites where comparisons were possible (Cestas, Pomet, Verdun), except at Pomet where TZKU was less negatively influenced by winter maximum temperatures and at Cestas where it was less influenced by summer minimum temperatures, than the overall *P.n.* subsp. *nigra* provenance mean. Finally, the French *P.n.* subsp. *salzmannii* provenance GASGUL diverged from the *P.n.* subsp. *salzmannii* provenance mean for sensitivity to maximum temperatures during cold months at all sites.

319

320 *Environmental, provenance and subspecies effects on phenotypic trait variation.*

Block effects on subspecies phenotypic variance (equation 1, full dataset) ranged from 0 to 55.65% within-site and were statistically significant in over 70% of cases. Similarly, block effects on provenance phenotypic variance ranged from 0 to 31.92% depending on site and response variable, and were statistically significant in over 60% of cases (Table 5). Block
effects were often non-significant for ring-width variables while they were for cumulated variables such as diameter and height (Circ, D15, D39 and H8).

327

<table><caption>Table 5: Percentages of total phenotypic variance explained by the subspecies, provenance and block effects for seven response variables within each of the four study sites, using the 16 provenance dataset. Statistical significance at the 5% level is indicated by (*). The table shows the results of analyses for provenance and block effects (two first columns in each site) and subspecies and block (two last columns in each site).</caption><thead><tr><th></th><th></th><th>rw</th><th>rw15</th><th>rw39</th><th>D15</th><th>D39</th><th>H8</th><th>Circ</th></tr></thead><tbody><tr><td rowspan="4">Cestas</td><td>Prov</td><td>20.28*</td><td>10.32*</td><td>25.75*</td><td>8.98*</td><td>20.15*</td><td>2.14*</td><td>14.58*</td></tr><tr><td>Bloc/Prov</td><td>2.699</td><td>0</td><td>6.35</td><td>5.48*</td><td>1.35*</td><td>0.85*</td><td>0</td></tr><tr><td>Subsp</td><td>11.33</td><td>6.04</td><td>14.08*</td><td>3.02*</td><td>10.91*</td><td>2.25*</td><td>6.82*</td></tr><tr><td>Bloc/Subsp</td><td>1.38</td><td>0</td><td>3.65</td><td>6.01*</td><td>0.82*</td><td>0.9*</td><td>0</td></tr><tr><td rowspan="4">Levens</td><td>Prov</td><td>15.9*</td><td>12.72</td><td>8.85</td><td>30.92*</td><td>21.94*</td><td>20.17*</td><td>23.84*</td></tr><tr><td>Bloc/Prov</td><td>9.94</td><td>13.26</td><td>0</td><td>31.92*</td><td>21.10*</td><td>29*</td><td>12.33*</td></tr><tr><td>Subsp</td><td>13.13</td><td>21.79</td><td>4.99</td><td>55.65*</td><td>25.45*</td><td>23.69*</td><td>29.39*</td></tr><tr><td>Bloc/Subsp</td><td>12.85</td><td>20.61</td><td>0</td><td>17.27*</td><td>18.86*</td><td>31.22*</td><td>12.98*</td></tr><tr><td rowspan="4">Pomet</td><td>Prov</td><td>13.5*</td><td>10.7*</td><td>12.23*</td><td>6.32*</td><td>14.23*</td><td>4.44*</td><td>14*</td></tr><tr><td>Bloc/Prov</td><td>12.1*</td><td>15.01*</td><td>12.02*</td><td>7.32*</td><td>6.59*</td><td>16.33*</td><td>5.84*</td></tr><tr><td>Subsp</td><td>6.25*</td><td>9.51*</td><td>14.36*</td><td>1.9*</td><td>3.41*</td><td>1.9*</td><td>3.34*</td></tr><tr><td>Bloc/Subsp</td><td>17.33*</td><td>16.11*</td><td>16.26*</td><td>8.91*</td><td>12.34*</td><td>16.99*</td><td>7.61*</td></tr><tr><td rowspan="4">Verdun</td><td>Prov</td><td>23.18*</td><td>4.99*</td><td>17.71*</td><td>24.01*</td><td>26.87</td><td>20.75*</td><td>5.76*</td></tr><tr><td>Bloc/Prov</td><td>0</td><td>0.075</td><td>0</td><td>1.64*</td><td>0</td><td>5.7*</td><td>1.44*</td></tr><tr><td>Subsp</td><td>24.65*</td><td>7.61*</td><td>15.26*</td><td>19.65*</td><td>30.05*</td><td>23.2*</td><td>6.87*</td></tr><tr><td>Bloc/Subsp</td><td>3.07</td><td>1.75</td><td>3.34</td><td>3.39*</td><td>0.81*</td><td>5.98*</td><td>1.9*</td></tr></tbody></table>

333

334

Subspecies effects (equation 1, full dataset) were significant for all variables after adjustment to block effects at Pomet and Verdun. They were often not significant for mean ring-width variables at Cestas and Levens. Subspecies effects explained between 1.9 and 55.65% of phenotypic variance depending on the phenotypic trait (Table 5).

Provenance effects (equation 1, full dataset) were significant for a slightly larger set of response variables (92%) than subspecies effects (82%). Provenance effects explained between 2.14 and 25.75% of phenotypic variance and were significant for all variables at Cestas, Pomet and Verdun. At Levens, provenance effect was non-significant for early and late stage ring-widths (Table 5). At Cestas (most fertile) and Pomet (least fertile), phenotypic trait variance was better explained by provenance than subspecies effects, while at Levens and Verdun (where there were the least number of provenances tested), subspecies effects were frequently higher than provenance effects (Table 5). On average, overall sites and traits, less than 25% of the
347
348

variance of phenotypic traits was explained by provenance effects after adjustment to block effects.

349
350
351
352
353
354
355
356

Subspecies ranks varied slightly across sites, as shown in Figure 3a for the two traits for which subspecies effect was significant in all sites (Circ and H8, Table 5). However, provenance variation was substantial, significant for almost all traits at all sites, and provided a more heterogeneous vision of performance ranking than subspecies (Table 5). Although *P.n.* subsp. *laricio* rarely ranked last (except at Pomet, the least fertile site), the best performing provenances were never the same at each site for any of the phenotypic traits, including some strong differences within subspecies (Figure 3b).

357
358

<figure><img src="image_4.png" /><figcaption>Figure 3a: Mean values of phenotypic traits with significant subspecies effect within site at all sites. Left panel: Circumference in 2014 (mm). Right panel: Total height at 8 years old (cm).</figcaption></figure>

359
360
Figure 3b: Mean ring width (rw, in mm) over 40 years of growth at all sites for all 16 provenances. Provenances in a blue tone are attributed to subspecies Pinus nigra laricio, those in red tone to P.n. nigra, those in green tone to P.n. pallasiana and those in grey tone to P.n. salzmannii (see Table 2). Vertical bars are standard deviations.

<figure><img src="image_5.png" /></figure>

*Provenance performance across sites: phenotypic plasticity and genotype x site interactions.*

When site effects were taken into consideration (equation 2, seven-provenance dataset), within-site block effects became non-significant (Table 6). Provenance effects remained significant in all sites for the response variables Circ, D15 (except at Pomet), D39, H8 and rw, while there was no significant provenance effect for response variables rw15 and rw39 (Table 6). Provenance effects explained between 0.08 and 25.59% of phenotypic variance overall, while they ranged only from 0.08 to 5.41% at Pomet (the least fertile site), depending on the phenotypic trait considered.
<table><caption>Table 6: Percentages of total phenotypic variance explained by the provenance and the bloc differences for seven response variables among the four test sites (7-provenance dataset). The variables are as follows: Circ is the circumference measured in 2014, D15 is the diameter at 15 years old, D39 is the diameter at 39 years old, H8 is the total height at 8 years old and, rw is the mean ring-width, rw15 is the mean ring-width calculated between 0 and 15 years old and rw39 is the mean ring-width calculated between 15 and 39 years old. Residuals values are also shown. Statistical significance at the 5% level is indicated by (*).</caption><thead><tr><th></th><th></th><th>Circ</th><th>D15</th><th>D39</th><th>H8</th><th>rw</th><th>rw15</th><th>rw39</th></tr></thead><tbody><tr><td>Bloc</td><td></td><td>3.84</td><td>7.78</td><td>1.8</td><td>12.86</td><td>1.33</td><td>3.99</td><td>0.73</td></tr><tr><td rowspan="4">Provenance</td><td>Cestas</td><td><strong>11.97*</strong></td><td><strong>7.3*</strong></td><td><strong>15.54*</strong></td><td><strong>8.73*</strong></td><td><strong>15.6*</strong></td><td>7.92</td><td>22.01</td></tr><tr><td>Levens</td><td><strong>15.42*</strong></td><td><strong>25.59*</strong></td><td><strong>9.02*</strong></td><td><strong>10.21*</strong></td><td><strong>8.25*</strong></td><td>12.37</td><td>7.97</td></tr><tr><td>Pomet</td><td><strong>4.37*</strong></td><td>2.19</td><td><strong>5.01*</strong></td><td><strong>0.08*</strong></td><td><strong>5.41*</strong></td><td>4.03</td><td>6.48</td></tr><tr><td>Verdun</td><td><strong>6.72*</strong></td><td><strong>6.98*</strong></td><td><strong>15.12*</strong></td><td><strong>12.37*</strong></td><td><strong>14.57*</strong></td><td>6.12</td><td>10.3</td></tr><tr><td>Residuals</td><td></td><td>57.66</td><td>50.14</td><td>53.47</td><td>55.72</td><td>54.81</td><td>65.54</td><td>52.48</td></tr></tbody></table>

Phenotypic plasticity was significantly high for all traits except rw39 (in one case), with provenance means increasing by 40 to over 100% between the lowest (Pomet, planted in 1973) and highest (Cestas, planted in 1974) fertility sites depending on the phenotypic trait (Figure 4, Table 7a). Phenotypic trait mean variation was irrespective of plantation date, but followed a clear climatic gradient from warm and wet to hot and dry. Cestas (the wettest, warmest and most recently planted site) showed the highest mean values for most of the analyzed response variables (Circ, D15, D39 and H8), followed by Levens (rw and rw15, Figure 4). Verdun showed the highest rw39 while Pomet (the driest and hottest site in the summer, planted during the same campaign as Cestas) had the smallest mean values for all variables with the exception of rw15 (Figure 4).
<figure><img src="image_6.png" /><figcaption>Table 7a: Values of mean ring-width (rw), mean ring-width calculated between 0 and 15 years (rw15), mean ring width calculated between 15 and 39 years (rw39), diameter at 15 years old (D15), diameter at 39 years old (D39), total height at 8 years old (H8) and circumference (Circ) calculated for each provenance test. Minimum (Min) and maximum (Max) values for each test site are also shown.</figcaption></figure>

<table><thead><tr><th></th><th>Circ (cm)</th><th>D15 (mm)</th><th>D39 (mm)</th><th>H8 (cm)</th><th>rw (mm)</th><th>rw15 (mm)</th><th>rw39 (mm)</th></tr></thead><tbody><tr><td>Overall Mean</td><td>67.136</td><td>60</td><td>179.25</td><td>151.36</td><td>2.93</td><td>5.04</td><td>1.53</td></tr><tr><td>Cestas</td><td>88.117</td><td>84.28</td><td>204.72</td><td>227.74</td><td>3.21</td><td>4.34</td><td>1.65</td></tr><tr><td>Levens</td><td>85.272</td><td>60.53</td><td>199.63</td><td>164.74</td><td>3.31</td><td>5.87</td><td>1.67</td></tr><tr><td>Pomet</td><td>57.308</td><td>45.09</td><td>148.67</td><td>105.02</td><td>2.51</td><td>5.39</td><td>1.16</td></tr><tr><td>Verdun</td><td>78.49</td><td>65.91</td><td>187.44</td><td>180.88</td><td>3.04</td><td>4.65</td><td>1.76</td></tr><tr><td>Min Cestas</td><td>31.5</td><td>18.01</td><td>70.51</td><td>80</td><td>1.25</td><td>2.42</td><td>0.14</td></tr><tr><td>Max Cestas</td><td>145.9</td><td>155.95</td><td>351.19</td><td>410</td><td>5.16</td><td>7.46</td><td>5.52</td></tr><tr><td>Min Levens</td><td>38.7</td><td>2.5</td><td>112.33</td><td>40</td><td>2.02</td><td>1.25</td><td>0.17</td></tr><tr><td>Max Levens</td><td>133</td><td>121.26</td><td>311.65</td><td>310</td><td>4.82</td><td>10.73</td><td>3.805</td></tr><tr><td>Min Pomet</td><td>16.4</td><td>7.73</td><td>80.48</td><td>38</td><td>1.55</td><td>1.68</td><td>0.16</td></tr><tr><td>Max Pomet</td><td>119.3</td><td>116.42</td><td>245.84</td><td>980</td><td>4</td><td>9.76</td><td>3.44</td></tr><tr><td>Min Verdun</td><td>21.7</td><td>4.95</td><td>94.8</td><td>50</td><td>1.58</td><td>2.39</td><td>0.1</td></tr><tr><td>Max Verdun</td><td>138.6</td><td>134.55</td><td>306.56</td><td>420</td><td>4.84</td><td>10.89</td><td>3.9</td></tr></tbody></table>

Over all phenotypic traits and sites, AYAN (P.n. subsp. pallasiana, Türkiye) and COSE (P.n. subsp. laricio, Italy), followed by TZKU (P.n. nigra, Bulgaria) performed best, whereas GASGUL (P.n. subsp. salzmannii, France) was the provenance with the worst performance. However, there were provenance x site interactions for all traits (Table 7b).
412

413

Table 7b: two-sided Student t-test for pair-wide comparisons of mean site values.
Probabilities that the matrices of mean values for seven provenances are identical. One value
only is over the threshold and indicates identical values (in bold italics).

414

415

<table><thead><tr><th>T test</th><th>Circ</th><th>H8</th><th>RW</th><th>RW15</th><th>RW39</th><th>D15</th><th>D39</th></tr></thead><tbody><tr><td>Cestas - Levens</td><td>0.04166</td><td>0.00000</td><td><strong>0.68249</strong></td><td>0.00208</td><td>0.01161</td><td>0.00049</td><td>0.00032</td></tr><tr><td>Cestas - Pomet</td><td>0.00000</td><td>0.00004</td><td>0.00000</td><td>0.00001</td><td>0.00058</td><td>0.00000</td><td>0.00000</td></tr><tr><td>Cestas - Verdun</td><td>0.00001</td><td>0.00061</td><td>0.00044</td><td>0.03986</td><td>0.00817</td><td>0.00010</td><td>0.00035</td></tr><tr><td>Levens - Pomet</td><td>0.00000</td><td>0.00000</td><td>0.00000</td><td>0.00001</td><td>0.00001</td><td>0.00056</td><td>0.00000</td></tr><tr><td>Levens - Verdun</td><td>0.00668</td><td>0.00001</td><td>0.00611</td><td>0.00252</td><td>0.00035</td><td>0.00491</td><td>0.01308</td></tr><tr><td>Pomet - Verdun</td><td>0.00000</td><td>0.00001</td><td>0.00006</td><td>0.00000</td><td>0.00008</td><td>0.00000</td><td>0.00009</td></tr></tbody></table>

416

417

For example, for Circ, all three *P.n.* subsp. *laricio* had the best performance at Cestas, while only COSE (*P.n.* subsp. *laricio*) performed best in Verdun and none where ranked first in either Levens or Pomet where CRIM (*P.n.* subsp. *pallasiana*, Crimea) and AYAN (*P.n.* subsp. *pallasiana*) performed best (Figure 5).

418

419

420

421

422
Figure 5: Comparison of mean provenance values of circumference in 2014 (Circ, in mm) for seven Pinus nigra provenances in four sites. Provenances in a blue tone are attributed to subspecies P.n. laricio, those in red tone to P.n. nigra, those in green tone to P.n. pallasiana and those in grey tone to P.n. salzmannii (see Table 2). Similar letters above vertical bars indicate no statistical differences between mean provenance values using a Kruskall-Wallis test.

<figure><img src="image_7.png" /></figure>

Neutral versus adaptive differentiation

To estimate if the phenotypic differentiation observed among provenances might be attributed to natural selection rather than neutral demographic processes, we compared the provenance effect on phenotypic trait variance (here defined as *PROV*<sub>ST</sub>) in the two sites where it was the lowest (Cestas and Pomet) and where the highest number of provenances were tested, to an estimate of differentiation (*F*<sub>ST</sub> = 0.09) calculated using 14 nuclear microsatellite loci (Scotti-Saintagne et al. 2019, appendix S4). *PROV*<sub>ST</sub> was higher than *F*<sub>ST</sub>, for all phenotypic traits except the early growth traits D15 and H8, both at Cestas and Pomet, with the highest difference shown for the later life-stage phenotypic traits (Table 4). When the comparison was made with the seven-provenance dataset, *PROV*<sub>ST</sub> was lower than *F*<sub>ST</sub>, for all phenotypic traits at Pomet and for all early-stage traits at Verdun (Table 5).
444 **Discussion**

445 **Climate and radial growth**

446 Radial growth is the result of cambium activity which depends mainly on water and carbon
447 availability, both strongly determined by external climatic conditions (Linares & Tíscar 2010).
448 The radial growth of the European black pine was positively correlated with early summer
449 precipitations (June or July) and negatively correlated with spring (March and May) and
450 summer temperatures (June and July) across experimental sites and genotypes, as previously
451 shown by Leal et al. (2008) and Lebourgeois (2000). Other studies have also identified a
452 significant positive influence of spring temperatures and early summer precipitations on ring-
453 width of black pine in Mediterranean sites (Izmir et al. 2024, Jevšenak & Saražin 2023, Martin-
454 Benito et al. 2010) These results highlight the fundamental and beneficial role of precipitations
455 during early wood formation when temperatures are starting to reach their maximum, and the
456 negative effects of summer heat and drought in the European black pine (Andreu et al. 2007,
457 Camarero et al. 2013, Lebourgeois 2000).

458 Site differences for climate effects on radial growth were weak. Perhaps the most striking
459 differences were the opposite positive correlations with winter temperatures at Verdun, the
460 continental site, and negative correlations in other sites, particularly Cestas, the wettest oceanic
461 climate site. This may suggest that under a continental climate, warmer than average winters
462 will increase growth in *P. nigra* as observed in previous studies (Amodei et al. 2013, Andreu
463 et al. 2007). Conversely, too warm winters in mild and wet sites such as Cestas will limit
464 growth, perhaps because of delayed xylem formation or premature dormancy breaking which
465 can expose cambial cell divisions to late spring frost (Begum et al. 2013, Ladwig et al. 2019).

466 Climate-growth relationships among the different European black pine provenances and
467 subspecies at the different sites presented only slight differences such as the positive correlation
468 between growth and October precipitations in *P.n.* subsp. *salzmannii* at Cestas and its negative
469 correlation between growth and August precipitations at Verdun. This could indicate that in wet
470 sites, an excess of precipitations during the Fall season is beneficial to growth of *P.n.* subsp.
471 *salzmannii* while late summer precipitations are not. In the dry calcareous site of Pomet, *P.n.*
472 subsp. *pallasiana* benefited from late spring precipitations potentially indicating an increased
473 drought resistance in comparison to other black pine subspecies.

474 **Genetic diversity, differentiation and plasticity**
475

Although provenance differences in monthly climate sensitivity were weak, they accounted for up to one fourth of observed phenotypic variance depending on the trait and site. Provenance effect on phenotypic trait variance were generally higher than subspecies effects. Among the four sites, Pomet had the lowest provenance level phenotypic trait variance as well as the weakest performance for all the response variables selected for the study, confirming that low fertility tends to reduce phenotypic trait variance. Although our design does not make it possible to measure additive genetic variance and thus formally compare phenotypic trait differentiation due to selection from that due to genetic drift (Leinonen et al. 2013), Fst was lower than the within-site provenance effect for all adult stage traits (but not growth traits before 15 years of age and not when among site effects were considered), suggesting a potentially weak effect of natural selection on provenance phenotypic trait variance.

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Our design, also, cannot formally test for local adaptation as it is not a reciprocal transplant experiment including local and foreign genotypes and sites (Kawecki & Ebert 2004). Yet, the fact that we observed genotype by environment interaction maybe an indication of local adaptation. The provenances from continental France and Spain (*P.n. subsp. salzmannii*) had higher growth during their first 15 years of life at Pomet, the harshest site which resembles most the ecological conditions of their place of origin. Despite the fact that growth later on becomes average or lower than average, this early growth advantage that translates to a larger circumference in the adult life, could reveal some level of local adaptation in *P.n. subsp. salzmannii* (Taïbi et al. 2016). Differences in early growth among *P. nigra* provenances have also been observed in other studies of common gardens (Wheeler et al. 1976, Wilcox & Miller 1975) and Varelides et al. (2001) hypothesized the existence of local adaptation at least for some provenances, such as the Greek provenance Thasos (*P.n. subsp. nigra*) in a Greek common garden.

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Whereas genetic differences among provenances were relatively modest, an average temperature variation between the coldest (Levens) and the warmest (Cestas) site of 4.9 °C and an average precipitation variation between the driest (Pomet) and the wettest (Cestas) site of 217 mm led to up to a 100% increase in some growth traits for some provenances. Such a strong adjustment of growth response to the divergent climates of the common garden suggests a strong provenance-level phenotypic plasticity.

505
506 **Conclusion and limits of the study**

507 Taken together, these results suggest a weak divergent adaptation to different climates in the
508 subspecies of the European black pine and a shared sensitivity of growth to water deficit and
509 early summer drought across subspecies and provenances. We thus confirm for adult trees and
510 a larger coverage of within-species diversity, the results that Thiel et al. (2012) obtained at the
511 seedling stage in growth chambers. This lack of strong differentiation for key fitness-related
512 traits also fits well with genetic inferences showing a recent, Holocene divergence of
513 populations at continental scale in this species (Scotti-Saintagne et al. 2019).

514 Providing a typology for the best subspecies for a given environment is complex, as
515 provenance variation was almost systematically stronger than subspecies variation. Whereas
516 *P.n.* subsp. *salzmannii* never ranked first in any site for adult traits, at least one of its
517 provenances (not always the same) performed well in most sites, particularly in the driest one.
518 At the other end of the growth spectrum, *P.n.* subsp. *laricio* provenances never ranked last
519 except in the driest, most Mediterranean site, while they were outperformed or equaled by *P.n.*
520 subsp. *pallasiana* and *P.n.* subsp. *nigra* provenances in all other sites.

521 As phenotypic plasticity is very strong, this species of pine (like others, see Richter et al.
522 2012) is well adapted to a wide range of environments, both for timber production and
523 ecological restoration. Subspecies *P.n.* subsp. *laricio* and *P.n.* subsp. *nigra* have been a popular
524 plantation forestry choice in Europe, but our results demonstrate that the lesser known and used
525 (at least outside of its distribution range) *P.n.* subsp. *pallasiana* should be considered as well,
526 both on acidic and calcareous soils. Pending different insect and disease susceptibilities, using
527 a mixture of provenances from these subspecies in the highest fertility sites would probably be
528 the safest plantation method both for timber production and ecological restoration outside the
529 natural range of the species (Candido-Ribeiro & Aitken 2024), including in an assisted
530 migration context (Bradley St Clair & Howe 2007). Our study also suggests not disregarding
531 *P.n.* subsp. *salzmannii* for dry site provenance mixtures, and where drought is expected to
532 increase due to climate change during the next decades (MedECC 2020).

533 Our data and analysis are only based on growth traits, not on survival which may influence
534 basal area strongly if mortality is high. This can be the case for *P. nigra* subsp *laricio* which is
535 more susceptible than *P. nigra* subsp *salzmannii* to red band needle blight (*Dothistroma*
536

*septosporum* (Dorogin) M.Morelet, and *D. pini* Hulbary) which, in turn, may be more prevalent
in wet and hot than dry sites (Perret et al. 2021, Watt et al. 2009).

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538

Finally, our study demonstrates the importance of common gardens for forest trees (Fady & Rihm 2022). Hard to manage, expensive and long term, they are the only experimental tools capable of validating phenotypic trait adaptation and plasticity, in the era of genomics and climate change. They also constitute precious ex-situ biodiversity reserves of high patrimonial value. The generation of common gardens used here was designed to select the best material for plantation forestry before global climate change was considered an issue. We suggest that a new generation of common gardens is now needed for this high phenotypic plasticity forest tree species, with wide-ranging testing of new genotypes across contrasted environments, including at the early seedling stage, as suggested for other Mediterranean forest tree species (Ramírez-Valiente et al. 2022). We also suggest, in view of the strong genotype x environment found here, that countries protect their native local resources both in situ and as ex-situ conservation plantations (Scotti Saintagne et al. 2023).

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## Acknowledgements

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We acknowledge the financial support of ANR project “AMTools” (ANR-11-AGRO-0005) and Aix-Marseille Université (Ecole Doctorale EDSE). We thank the following people for their help for wood core sample collection and trait measurements: O. Gilg, F. Rei, N. Turion, D. Vauthier (INRAE UEFM, Avignon, France), L. Severin, N. Cheval, L. Puzos, N. Morrisson, L. Moras, C. Magnin (INRAE UEFP, Pierroton, France), F. Bonne, T. Paul and V. Rousselet (INRAE SILVA, Nancy, France). We thank W. Brunetto (INRAE URFM, Avignon, France), C. Berguet and M. Guillouard (Aix-Marseille Université, IMBE, France) for wood core sample preparation and treatment.

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## Conflict of interest disclosure

562

The authors declare that they have neither financial nor non-financial conflicts of interest.

563
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