# Black poplar establishment on alluvial bars: seed rain homogeneity over a few kilometres

Lucas Mazal, Dov Corenblit, Boris B. Fumanal, Irène Till-Bottraud

► To cite this version:

Lucas Mazal, Dov Corenblit, Boris B. Fumanal, Irène Till-Bottraud. Black poplar establishment on alluvial bars: seed rain homogeneity over a few kilometres. Dendrobiology, 2022, 87, pp.69-78. 10.12657/denbio.087.005. hal-04551964

HAL Id: hal-04551964

https://uca.hal.science/hal-04551964

Submitted on 10 Jun 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Lucas Mazal, Dov Corenblit, Boris Fumanal, Irène Till-Bottraud

# Black poplar establishment on alluvial bars: seed rain homogeneity over a few kilometres

Received: ; Accepted:

**Abstract:** The Black poplar is a pioneer tree species occurring along many river courses across Europe. Seedlings establish at very high density and experience various stresses (e.g., hydric, mechanical). In a previous study conducted in 2017 on the same population we described the fine-scale genetic structure (FSGS) of three age cohorts (5, 10 and > 20 years old) and found a significant SGS in the younger cohort. In this study, we aim to determine the FSGS in Black poplar cohorts of one-year-old seedlings, which is the most informative about seed dispersal. We used microsatellite markers to explore the FSGS of four different patches of Black poplar seedlings from two riverbanks in the Val d'Allier National Natural Reserve (France). We found a high genetic diversity and detected no FSGS in any of the four sampled seedlings patches. The absence of SGS at the seedling stage suggests that in this natural population, seeds from different mother trees are widely dispersed, well mixed and are deposited homogeneously on the various germination sites available over few kilometres.

**Keywords:**

**List of abbreviations:** SGS – spatial genetic structure, FSGS – fine-scale spatial genetic structure

**Addresses:** L. Mazal, D. Corenblit, I. Till-Bottraud, Université Clermont Auvergne, CNRS, GEOLAB, F-63000 Clermont-Ferrand, France, e-mail: lucas.mazal@etu.uca.fr
B. Fumanal, Université Clermont Auvergne, INRAE, PIAF, 63000 Clermont-Ferrand, France
*Corresponding author

## Introduction

The Black poplar (Populus nigra L., Salicaceae) is a pioneer tree species with a good tolerance to submersion, sediment burial and high temperatures occurring along many river courses across Europe (Chamaillard, 2011). The species is dioecious, and a female tree produces each year millions of short living seeds which are transported by both wind and water (Barrat-Segretain, 1996; Karrenberg et al., 2002). Seeds germinate immediately after arrival on suitable bare moist alluvial bars (Barsoum & Hughes, 1998; Guilloy-Froget et al., 2002). During favourable years, Black poplar seedlings generally establish in

very high density (e.g., > 4000/m²; Braatne, 1996) at the immediate margins of the main or secondary channels. Suitably positioned seedlings on alluvial bars near the channels generally form elongated recruitment bands or patches composed of individuals of the same age (cohort) (Guilloy-Froget et al., 2002; Corenblit et al., 2009; 2016). As a pioneer species, the eco-hydrological conditions for regeneration include freshly disturbed, competitor-free sediments and it is highly dependent on water table level fluctuations (Mahoney & Rood, 1998; Corenblit et al., 2014). Harsh summer (drought) and winter (submersion, erosion and/or burial) conditions on alluvial bars allow seedlings to establish only during restricted
Lucas Mazal, Dov Corenblit, Boris Fumanal, Irène Till-Bottraud

# Black poplar establishment on alluvial bars: seed rain homogeneity over a few kilometres

*Received: ; Accepted:*

**Abstract:** The Black poplar is a pioneer tree species occurring along many river courses across Europe. Seedlings establish at very high density and experience various stresses (e.g., hydric, mechanical). In a previous study conducted in 2017 on the same population we described the fine-scale genetic structure (FSGS) of three age cohorts (5, 10 and > 20 years old) and found a significant SGS in the younger cohort. In this study, we aim to determine the FSGS in Black poplar cohorts of one-year-old seedlings, which is the most informative about seed dispersal. We used microsatellite markers to explore the FSGS of four different patches of Black poplar seedlings from two riverbanks in the Val d'Allier National Natural Reserve (France). We found a high genetic diversity and detected no FSGS in any of the four sampled seedlings patches. The absence of SGS at the seedling stage suggests that in this natural population, seeds from different mother trees are widely dispersed, well mixed and are deposited homogeneously on the various germination sites available over few kilometres.

**Keywords:**

**List of abbreviations:** SGS – spatial genetic structure, FSGS – fine-scale spatial genetic structure

**Addresses:** L. Mazal, D. Corenblit, I. Till-Bottraud, Université Clermont Auvergne, CNRS, GEOLAB, F-63000 Clermont-Ferrand, France, e-mail: lucas.mazal@etu.uca.fr
B. Fumanal, Université Clermont Auvergne, INRAE, PIAF, 63000 Clermont-Ferrand, France
*Corresponding author

## Introduction

The Black poplar (Populus nigra L., Salicaceae) is a pioneer tree species with a good tolerance to submersion, sediment burial and high temperatures occurring along many river courses across Europe (Chamaillard, 2011). The species is dioecious, and a female tree produces each year millions of short living seeds which are transported by both wind and water (Barrat-Segretain, 1996; Karrenberg et al., 2002). Seeds germinate immediately after arrival on suitable bare moist alluvial bars (Barsoum & Hughes, 1998; Guilloy-Froget et al., 2002). During favourable years, Black poplar seedlings generally establish in

very high density (e.g., > 4000/m²; Braatne, 1996) at the immediate margins of the main or secondary channels. Suitably positioned seedlings on alluvial bars near the channels generally form elongated recruitment bands or patches composed of individuals of the same age (cohort) (Guilloy-Froget et al., 2002; Corenblit et al., 2009; 2016). As a pioneer species, the eco-hydrological conditions for regeneration include freshly disturbed, competitor-free sediments and it is highly dependent on water table level fluctuations (Mahoney & Rood, 1998; Corenblit et al., 2014). Harsh summer (drought) and winter (submersion, erosion and/or burial) conditions on alluvial bars allow seedlings to establish only during restricted
time periods and years (Barsoum & Hughes, 1998; Mahoney & Rood, 1998; Stella & Battles, 2010; Guil-loy et al., 2011). The relatively long period of seed production of Black poplar (2-3 months according to Braatne, 1996; Guilloy-Froget et al., 2002) combined to the variability of dispersal conditions (i.e., wind and hydrological regimes, location and number of father- and mother-trees, geomorphological config-uration) may lead to strong intra- and inter-annual variability in seedling relatedness on the colonization sites. Patterns of dispersal of pollen and seeds have important consequences for the spatial distribution of genotypes at the colonisation stage (Banks et al., 2013).

The spatial genetic structure (SGS), defined as the non-random distribution of genotypes, characteriz-es the relationship between relatedness of individ-uals and their physical proximity within population (Loiselle et al., 1995; Hardy, 2003). The presence of a significant SGS may be the result of historical founding events and/or population expansion, selec-tion pressures and, limited or structured gene dis-persal (Vekemans & Hardy, 2004). In pioneer tree species, investigating the SGS helps improve our un-derstanding of dispersal and colonisation patterns, and the subsequent development of the woodland ecosystems they inhabit (Jones et al., 2006). More-over the comparison of SGS between different age cohorts or at different spatial scales allows to make inferences about gene flow (pollen and seed disper-sal) and, therefore, valuable for the conservation of threatened species (Gaudeul & Till-Bottraud, 2008; Batista Leite et al., 2014). Studies of SGS in trees generally address large geographic areas; at the river reach scale (Imbert & Lefevre, 2003; Jelić et al., 2015; Kettenring et al., 2019; González-Ro-bles et al., 2020) or from kilometres (Pospišková & Šálková, 2006; Born et al., 2008; Wójkiewicz et al., 2019) to hundreds of meter (Rathmacher et al., 2010; Sagnard et al., 2011; Deng et al., 2020). How-ever, sampling often neglects the very fine scale, at less than a meter. Hereafter, we will use “fine-scale spatial genetic structure” (FSGS) to refer to scale of a meter or less which correspond to the distance at which individuals interact with each other (i.e., including the zone of interaction among immediate neighbours at fine spatial scales as defined by Fajar-do et al., 2016). FSGS has been studied in trees in an agricultural setting (Baldauf et al., 2014; Sjölund et al., 2015; Ramos et al., 2016), and also in woodland environments (Till-Bottraud et al., 2012; Bessega et al., 2016; Fajardo et al., 2016; Kitamura et al., 2018), but to our knowledge, very few have explored FSGS of Black poplar within river corridors (Mazal et al., 2021).

In a previous study we described the FSGS of three cohorts (5, 10 and > 20 years old individuals) in the

Allier and the Garonne rivers and found a significant FSGS for the young cohort (5 years old individuals) but not in older cohorts (Mazal et al., 2021). How-ever, we did not investigate the FSGS for seedlings of the year, which are the most informative about seed dispersal. Investigating the evolution of FSGS in populations across different developmental stages can provide a better understanding of their local pat-terns of dispersal and colonization and could provide valuable information on Black poplar’s ability to col-onize alluvial bars within the fluvial corridor. Follow-ing our previous results, we hypothesised that dur-ing dispersion seeds may get aggregated into clumps of related seeds and form micro-patches of related seedlings on the alluvial surfaces, resulting in FSGS for the seedlings of the year. The goal of this paper was to study the FSGS in cohorts of seedlings in the same natural population studied previously in order to improve our understanding of seed dispersal and spatial genetic structuration during recruitment. We used microsatellite markers to explore the FSGS of four different patches of black poplar seedlings from two riverbanks distant by at most 1.2 km in a natural reserve of the Allier River (France) and discussed our previous results obtained in 2017 on older cohorts from the same population (Mazal et al., 2021) in the light of these results.

# Material and Methods

## Study site and sampling strategy

The study site is located along the lower reaches of the Allier River in the Val d'Allier National Nat-ural Reserve, near Châtel-de-Neuvre (46°25'06.5"N, 003°19'43.2"E; 220 m a.s.l.) in central France. This site is the same as described and studied in Mazal et al. (2021). The area benefits from a certain degree of protection and has experienced moderate anthropo-genic impacts (e.g., few bank protections or rip rap) (Petit, 2006; Dejaifve & Esquirol, 2011). This reach of the Allier River is characterized by active lateral erosion on the outer bends of meanders, with point bar formation and migration on the inner bends within the Réserve Naturelle Nationale du Val d'Al-lier (Garófano-Gómez et al., 2017). The progressive

<table><caption>Table 1. Summary of the characteristics of the four patches sampled for *P. nigra* seedlings along the Allier River.</caption><thead><tr><td>Patch</td><td>Patch area (m²)</td><td>Number of individuals sampled</td><td>Density (ind/m²)</td></tr></thead><tbody><tr><td>A</td><td>1</td><td>90</td><td>90</td></tr><tr><td>B</td><td>0.3</td><td>93</td><td>310</td></tr><tr><td>C</td><td>2</td><td>93</td><td>47</td></tr><tr><td>D</td><td>1.04</td><td>92</td><td>89</td></tr><tr><td>Mean</td><td>1.09</td><td>92</td><td>134</td></tr></tbody></table>
time periods and years (Barsoum & Hughes, 1998; Mahoney & Rood, 1998; Stella & Battles, 2010; Guil-loy et al., 2011). The relatively long period of seed production of Black poplar (2-3 months according to Braatne, 1996; Guilloy-Froget et al., 2002) combined to the variability of dispersal conditions (i.e., wind and hydrological regimes, location and number of father- and mother-trees, geomorphological config-uration) may lead to strong intra- and inter-annual variability in seedling relatedness on the colonization sites. Patterns of dispersal of pollen and seeds have important consequences for the spatial distribution of genotypes at the colonisation stage (Banks et al., 2013).

The spatial genetic structure (SGS), defined as the non-random distribution of genotypes, characteriz-es the relationship between relatedness of individ-uals and their physical proximity within population (Loiselle et al., 1995; Hardy, 2003). The presence of a significant SGS may be the result of historical founding events and/or population expansion, selec-tion pressures and, limited or structured gene dis-persal (Vekemans & Hardy, 2004). In pioneer tree species, investigating the SGS helps improve our un-derstanding of dispersal and colonisation patterns, and the subsequent development of the woodland ecosystems they inhabit (Jones et al., 2006). More-over the comparison of SGS between different age cohorts or at different spatial scales allows to make inferences about gene flow (pollen and seed disper-sal) and, therefore, valuable for the conservation of threatened species (Gaudeul & Till-Bottraud, 2008; Batista Leite et al., 2014). Studies of SGS in trees generally address large geographic areas; at the river reach scale (Imbert & Lefevre, 2003; Jelić et al., 2015; Kettenring et al., 2019; González-Ro-bles et al., 2020) or from kilometres (Pospišková & Šálková, 2006; Born et al., 2008; Wójkiewicz et al., 2019) to hundreds of meter (Rathmacher et al., 2010; Sagnard et al., 2011; Deng et al., 2020). How-ever, sampling often neglects the very fine scale, at less than a meter. Hereafter, we will use “fine-scale spatial genetic structure” (FSGS) to refer to scale of a meter or less which correspond to the distance at which individuals interact with each other (i.e., including the zone of interaction among immediate neighbours at fine spatial scales as defined by Fajar-do et al., 2016). FSGS has been studied in trees in an agricultural setting (Baldauf et al., 2014; Sjölund et al., 2015; Ramos et al., 2016), and also in woodland environments (Till-Bottraud et al., 2012; Bessega et al., 2016; Fajardo et al., 2016; Kitamura et al., 2018), but to our knowledge, very few have explored FSGS of Black poplar within river corridors (Mazal et al., 2021).

In a previous study we described the FSGS of three cohorts (5, 10 and > 20 years old individuals) in the

Allier and the Garonne rivers and found a significant FSGS for the young cohort (5 years old individuals) but not in older cohorts (Mazal et al., 2021). How-ever, we did not investigate the FSGS for seedlings of the year, which are the most informative about seed dispersal. Investigating the evolution of FSGS in populations across different developmental stages can provide a better understanding of their local pat-terns of dispersal and colonization and could provide valuable information on Black poplar’s ability to col-onize alluvial bars within the fluvial corridor. Follow-ing our previous results, we hypothesised that dur-ing dispersion seeds may get aggregated into clumps of related seeds and form micro-patches of related seedlings on the alluvial surfaces, resulting in FSGS for the seedlings of the year. The goal of this paper was to study the FSGS in cohorts of seedlings in the same natural population studied previously in order to improve our understanding of seed dispersal and spatial genetic structuration during recruitment. We used microsatellite markers to explore the FSGS of four different patches of black poplar seedlings from two riverbanks distant by at most 1.2 km in a natural reserve of the Allier River (France) and discussed our previous results obtained in 2017 on older cohorts from the same population (Mazal et al., 2021) in the light of these results.

# Material and Methods

## Study site and sampling strategy

The study site is located along the lower reaches of the Allier River in the Val d'Allier National Nat-ural Reserve, near Châtel-de-Neuvre (46°25'06.5"N, 003°19'43.2"E; 220 m a.s.l.) in central France. This site is the same as described and studied in Mazal et al. (2021). The area benefits from a certain degree of protection and has experienced moderate anthropo-genic impacts (e.g., few bank protections or rip rap) (Petit, 2006; Dejaifve & Esquirol, 2011). This reach of the Allier River is characterized by active lateral erosion on the outer bends of meanders, with point bar formation and migration on the inner bends within the Réserve Naturelle Nationale du Val d'Al-lier (Garófano-Gómez et al., 2017). The progressive

<table><caption>Table 1. Summary of the characteristics of the four patches sampled for *P. nigra* seedlings along the Allier River.</caption><thead><tr><td>Patch</td><td>Patch area (m²)</td><td>Number of individuals sampled</td><td>Density (ind/m²)</td></tr></thead><tbody><tr><td>A</td><td>1</td><td>90</td><td>90</td></tr><tr><td>B</td><td>0.3</td><td>93</td><td>310</td></tr><tr><td>C</td><td>2</td><td>93</td><td>47</td></tr><tr><td>D</td><td>1.04</td><td>92</td><td>89</td></tr><tr><td>Mean</td><td>1.09</td><td>92</td><td>134</td></tr></tbody></table>
<figure><img src="image_1.png" /><figcaption>Fig. 1. Aerial photograph of the Allier River study site, showing the position of the Black poplar patches (A, B, C and D) sampled along the two gravel bars. River flow direction is from South to North. In the four patches, the white vials (6 cm high) are positioned next to each sampled individual</figcaption></figure>
<figure><img src="image_2.png" /><figcaption>Fig. 1. Aerial photograph of the Allier River study site, showing the position of the Black poplar patches (A, B, C and D) sampled along the two gravel bars. River flow direction is from South to North. In the four patches, the white vials (6 cm high) are positioned next to each sampled individual</figcaption></figure>
shifting of the river channel allows for periodic re-
cruitment events on many germination sites on allu-
vial bars, resulting in different aged cohorts of *P. nigra*
recruits growing in elongated bands parallel to the
main channel (Hortobágyi et al., 2017).

In August 2019, we sampled seedlings of 1 year old in four patches on two alluvial bars. We chose two patches of seedlings in each bar and collected approximately 90 individuals in each patch (Table 1, Fig. 1). Density was very high in the four patches (mean density = 133±59.61 individuals/m²) and the patches sampled were relatively small (1 m²). Patches were distant by at most 1.2 km. Table 1 lists the number of black poplar seedlings, patch area, and patch plant density. For each patch, we built a distance matrix between each pair of individuals at a centimetre scale using pictures on which we digitized the location of each individual (ArcGis™ v.12.4). The studied patches were located in similar conditions, including the proximity and elevation relative to the channel. Numerous adult trees are present close to our studied site. A few km downstream from our site, Wendelgaß (2016) found approximately 130 adult trees (> 20 years-old, based on tree-ring counts) out of 330 measured over an area of 11,500 m². This indicate that more than 20,000 adult trees are present in the Reserve.

DNA extraction and genotyping

Total DNA was extracted from leaves using the NucleoSpin 96 Plant Core Kit extraction kit (Mache-rey Nagel™) according to the manufacturer instruc-tions. We used 12 unlinked (Gaudet et al., 2007) nuclear microsatellites markers to genotype individ-uals (see details in Table S1): WPMS06, WPMS07, WPMS09, WPMS13, WPMS14, WPMS16, WPMS20, WPMS22 PMGC93, PMGC2578, PMGC14, and ORPM221 (Smulders et al., 2002; Van Oosterhout et al., 2004; Chenault et al., 2011; Faivre-Ram-pant et al., 2016). Markers were arranged in three PCR-multiplex reactions. Multiplex1: ORPM221, WPMS07, WPMS13, WPMS22; Multiplex2: PMGC14, PMGC93, PMGC578, WPMS14; Multi-plex 3: WPMS06, WPMS09, WPMS16, WPMS20. We used indirect tagging with M13-tailed primer method (O settings et al., 1995). In this method, in-stead of synthesizing one specific fluorescently la-belled primer for each SSR marker, only a dye la-belled M13 primer is needed. Marker amplification was performed according to Mazal et al. (2021). Analysis of The PCR products were performed in a 3750xl Genetic Analyser (Applied Biosystems™) with GeneScanTM 500 LIZ® internal size standard. Genotypes were scored using Geneious™ v.2020.1.1. and confirmed manually.

Genetic analyses

Three markers did not amplify (WPMS06, WPMS07, WPMS22) and were removed from the analysis. Loci were tested for null allele frequencies with Brookfield's methods (Brookfield, 1996) using Microchecker v2.2.3 (Van Oosterhout et al., 2004) low DNA concentrations and primer-site mutations may result in the incorrect assignment of microsatel lite genotypes, potentially biasing population genetic analyses. MICRO-CHECKER is WINDOWS®-based software that tests the genotyping of microsatellites from diploid populations. The program aids identifi cation of genotyping errors due to nonamplified al leles (null alleles. Three markers (PMGC14, WPMS09 and WPMS16) presented a high null-allele frequency and were therefore removed from the dataset. To es timate the discrimination power of the dataset, we calculated the probability of sampling two different genotypes with the same multilocus SSR phenotype (probability of identity) with one to six markers us ing GenAIEx v6.5 (Peakall & Smouse, 2012). This probability decreased from 2.9e-02 with one marker, and reached a plateau around 7.5e-07 with four mark ers suggesting a high discrimination power of our six markers combination

We estimated allele frequencies, total and effec-
tive number of alleles, expected and observed hete-
rozygosities and inbreeding coefficient using SPAGe-
Di 1.5 (Hardy & Vekemans, 2002). Genetic structure
was analysed using the STRUCTURE 2.3.4 (Pritchard
et al., 2000) with a burn-in period of 100,000 it-
erations followed by 200,000 additional MCMC it-
erations. The analysis was based on the admixture
model and uncorrelated allele frequencies with the
recessive alleles option. Twenty independent runs for
each number of groups (K), ranging from 1 to 5 were
used. The best number K was estimated and visual-
ly verified as the highest value of Ln(P) following
Puechmaille (2016) because the ΔK method does not
evaluate K=1 causing an overestimation (Evanno et
al., 2005).

Spatial genetic structure and relatedness

We checked for the absence of clonality using the
GenAIEx (Peakall & Smouse, 2012). FSGS was as-
sessed within patches using the SPAGeDi. Loiselle
multilocus kinship coefficients, R<sub>ij</sub> (Loiselle et al.,
1995), were calculated between each pair of individ-
uals. Because R<sub>ij</sub> is a kinship coefficient relative to the
population mean, negative values can result, mean-
ing that two individuals are less related on average
than randomly selected individuals from the popu-
lation (Hardy, 2003). Kinship coefficient values were
averaged within distance classes (d), giving F(d) and
plotted against geographical distances. Ten distance
shifting of the river channel allows for periodic re-
cruitment events on many germination sites on allu-
vial bars, resulting in different aged cohorts of *P. nigra*
recruits growing in elongated bands parallel to the
main channel (Hortobágyi et al., 2017).

In August 2019, we sampled seedlings of 1 year old in four patches on two alluvial bars. We chose two patches of seedlings in each bar and collected approximately 90 individuals in each patch (Table 1, Fig. 1). Density was very high in the four patches (mean density = 133±59.61 individuals/m²) and the patches sampled were relatively small (1 m²). Patches were distant by at most 1.2 km. Table 1 lists the number of black poplar seedlings, patch area, and patch plant density. For each patch, we built a distance matrix between each pair of individuals at a centimetre scale using pictures on which we digitized the location of each individual (ArcGis™ v.12.4). The studied patches were located in similar conditions, including the proximity and elevation relative to the channel. Numerous adult trees are present close to our studied site. A few km downstream from our site, Wendelgaß (2016) found approximately 130 adult trees (> 20 years-old, based on tree-ring counts) out of 330 measured over an area of 11,500 m². This indicate that more than 20,000 adult trees are present in the Reserve.

DNA extraction and genotyping

Total DNA was extracted from leaves using the NucleoSpin 96 Plant Core Kit extraction kit (Mache-rey Nagel™) according to the manufacturer instruc-tions. We used 12 unlinked (Gaudet et al., 2007) nuclear microsatellites markers to genotype individ-uals (see details in Table S1): WPMS06, WPMS07, WPMS09, WPMS13, WPMS14, WPMS16, WPMS20, WPMS22 PMGC93, PMGC2578, PMGC14, and ORPM221 (Smulders et al., 2002; Van Oosterhout et al., 2004; Chenault et al., 2011; Faivre-Ram-pant et al., 2016). Markers were arranged in three PCR-multiplex reactions. Multiplex1: ORPM221, WPMS07, WPMS13, WPMS22; Multiplex2: PMGC14, PMGC93, PMGC578, WPMS14; Multi-plex 3: WPMS06, WPMS09, WPMS16, WPMS20. We used indirect tagging with M13-tailed primer method (O settings et al., 1995). In this method, in-stead of synthesizing one specific fluorescently la-belled primer for each SSR marker, only a dye la-belled M13 primer is needed. Marker amplification was performed according to Mazal et al. (2021). Analysis of The PCR products were performed in a 3750xl Genetic Analyser (Applied Biosystems™) with GeneScanTM 500 LIZ® internal size standard. Genotypes were scored using Geneious™ v.2020.1.1. and confirmed manually.

Genetic analyses

Three markers did not amplify (WPMS06, WPMS07, WPMS22) and were removed from the analysis. Loci were tested for null allele frequencies with Brookfield's methods (Brookfield, 1996) using Microchecker v2.2.3 (Van Oosterhout et al., 2004) low DNA concentrations and primer-site mutations may result in the incorrect assignment of microsatel lite genotypes, potentially biasing population genetic analyses. MICRO-CHECKER is WINDOWS®-based software that tests the genotyping of microsatellites from diploid populations. The program aids identifi cation of genotyping errors due to nonamplified al leles (null alleles. Three markers (PMGC14, WPMS09 and WPMS16) presented a high null-allele frequency and were therefore removed from the dataset. To es timate the discrimination power of the dataset, we calculated the probability of sampling two different genotypes with the same multilocus SSR phenotype (probability of identity) with one to six markers us ing GenAIEx v6.5 (Peakall & Smouse, 2012). This probability decreased from 2.9e-02 with one marker, and reached a plateau around 7.5e-07 with four mark ers suggesting a high discrimination power of our six markers combination

We estimated allele frequencies, total and effec-
tive number of alleles, expected and observed hete-
rozygosities and inbreeding coefficient using SPAGe-
Di 1.5 (Hardy & Vekemans, 2002). Genetic structure
was analysed using the STRUCTURE 2.3.4 (Pritchard
et al., 2000) with a burn-in period of 100,000 it-
erations followed by 200,000 additional MCMC it-
erations. The analysis was based on the admixture
model and uncorrelated allele frequencies with the
recessive alleles option. Twenty independent runs for
each number of groups (K), ranging from 1 to 5 were
used. The best number K was estimated and visual-
ly verified as the highest value of Ln(P) following
Puechmaille (2016) because the ΔK method does not
evaluate K=1 causing an overestimation (Evanno et
al., 2005).

Spatial genetic structure and relatedness

We checked for the absence of clonality using the
GenAIEx (Peakall & Smouse, 2012). FSGS was as-
sessed within patches using the SPAGeDi. Loiselle
multilocus kinship coefficients, R<sub>ij</sub> (Loiselle et al.,
1995), were calculated between each pair of individ-
uals. Because R<sub>ij</sub> is a kinship coefficient relative to the
population mean, negative values can result, mean-
ing that two individuals are less related on average
than randomly selected individuals from the popu-
lation (Hardy, 2003). Kinship coefficient values were
averaged within distance classes (d), giving F(d) and
plotted against geographical distances. Ten distance
classes were defined manually. Significance of $F(d)$ for each distance class was tested by running permutations of the spatial position of individuals 10,000 times, yielding a 95% confidence interval for $F(d)$ for each distance class. To test for SGS, we tested the significance of the regression of $R_{ij}$ values on the spatial distance ($d$) (Vekmans & Hardy, 2004). The spatial positions of the individuals were permuted 10 000 times in order to get the frequency distribution of the slope under the null hypothesis that $R_{ij}$ and $d$ were uncorrelated (Hardy 2003).

To determine whether patches originated from different groups of related seeds, we tested if kinship coefficients (Rij) between individuals from the same patch were higher than between individuals from different patches. Pairwise Rij are not independent when individuals are related to each other within patches. Consequently, we sampled randomly all independent Rij's within patches and we compared the Rij distributions (within and among patches) with a Wilcoxon rank test. We repeated this procedure 9,999 times. Because of multiple comparison tests, we corrected the p-values of the different tests with the Benjamini-Hochberg method (Benjamini & Hochberg, 1995). To test the significance of the comparisons, we used the average corrected p-value and the percentage of tests passing the significance level ($\alpha$ = 0.05) after correction.

# Results

## Genetic structure

As expected for seedlings, we found no identical multilocus genotypes in different samples in our dataset. The multilocus inbreeding coefficient was low ($Fis$ = 0.007) and does not show deviation from Hardy-Weinberg equilibrium (p-value = 0.441) indicating no population sub-structure. The absence of population subdivision was confirmed by the STRUCTURE analysis that indicates $K$=1 as an optimal genetic cluster (Fig. S1). Moreover, all pairwise comparisons between patches showed low and not statistically significant values of genetic differentiation ($F_{ST}$ ranging from 0 to 0.007; Table S2).

A

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

B

<figure><img src="image_3.png" /></figure>

C

<figure><img src="image_4.png" /></figure>

D

<figure><img src="image_5.png" /><figcaption>Fig. 2. Spatial autocorrelation plots for the four patches (A, B, C and D). The average kinship coefficient $F(d)$ is plotted against geographical distance between individuals. Confidence intervals (95%) are indicated by dashed lines. All values within the confidence interval are not significantly different from 0 ($\alpha$ = 0.05)</figcaption></figure>

<table><caption>Table 2. Population genetic parameters (multilocus) for each patch sampled. $N$ = number of individuals; $Na$ = total number of alleles; $Nae$ = effective number of alleles (Nielsen et al., 2003); $He$ and $Ho$ = expected and observed heterozygosities, respectively; $Fis$ = inbreeding coefficient; $P$ ($Fis \neq 0$) = the p-value of the permutation test</caption><thead><tr><th>Patch</th><th>N</th><th>Na</th><th>Nae</th><th>He</th><th>Ho</th><th>Fis</th><th>P (Fis ≠ 0)</th></tr></thead><tbody><tr><td>A</td><td>90</td><td>12.00</td><td>5.83</td><td>0.805</td><td>0.807</td><td>-0.002</td><td>0.956</td></tr><tr><td>B</td><td>93</td><td>13.50</td><td>5.84</td><td>0.808</td><td>0.828</td><td>-0.024</td><td>0.175</td></tr><tr><td>C</td><td>93</td><td>12.50</td><td>7.05</td><td>0.854</td><td>0.827</td><td>0.032</td><td>0.084</td></tr><tr><td>D</td><td>92</td><td>12.33</td><td>6.39</td><td>0.822</td><td>0.837</td><td>-0.018</td><td>0.341</td></tr><tr><td>All</td><td>368</td><td>15.33</td><td>6.37</td><td>0.822</td><td>0.816</td><td>0.007</td><td>0.441</td></tr></tbody></table>
classes were defined manually. Significance of *F*(*d*) for each distance class was tested by running permutations of the spatial position of individuals 10,000 times, yielding a 95% confidence interval for *F*(*d*) for each distance class. To test for SGS, we tested the significance of the regression of *R*<sub>ij</sub> values on the spatial distance (*d*) (Vekmans & Hardy, 2004). The spatial positions of the individuals were permuted 10 000 times in order to get the frequency distribution of the slope under the null hypothesis that *R*<sub>ij</sub> and *d* were uncorrelated (Hardy 2003).

To determine whether patches originated from different groups of related seeds, we tested if kinship coefficients (Rij) between individuals from the same patch were higher than between individuals from different patches. Pairwise Rij are not independent when individuals are related to each other within patches. Consequently, we sampled randomly all independent Rij's within patches and we compared the Rij distributions (within and among patches) with a Wilcoxon rank test. We repeated this procedure 9,999 times. Because of multiple comparison tests, we corrected the p-values of the different tests with the Benjamini-Hochberg method (Benjamini & Hochberg, 1995). To test the significance of the comparisons, we used the average corrected p-value and the percentage of tests passing the significance level (α = 0.05) after correction.

# Results

## Genetic structure

As expected for seedlings, we found no identical multilocus genotypes in different samples in our dataset. The multilocus inbreeding coefficient was low (*Fis* = 0.007) and does not show deviation from Hardy-Weinberg equilibrium (p-value = 0.441) indicating no population sub-structure. The absence of population subdivision was confirmed by the STRUCTURE analysis that indicates K=1 as an optimal genetic cluster (Fig. S1). Moreover, all pairwise comparisons between patches showed low and not statistically significant values of genetic differentiation (*F*<sub>ST</sub> ranging from 0 to 0.007; Table S2).

A

<figure><img src="image_3.png" /></figure>

B

<figure><img src="image_4.png" /></figure>

C

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

D

<figure><img src="image_6.png" /><figcaption>Fig. 2. Spatial autocorrelation plots for the four patches (A, B, C and D). The average kinship coefficient *F*(*d*) is plotted against geographical distance between individuals. Confidence intervals (95%) are indicated by dashed lines. All values within the confidence interval are not significantly different from 0 (α = 0.05)</figcaption></figure>

<table><caption>Table 2. Population genetic parameters (multilocus) for each patch sampled. *N* = number of individuals; *Na* = total number of alleles; *Nae* = effective number of alleles (Nielsen et al., 2003); *He* and *Ho* = expected and observed heterozygosities, respectively; *Fis* = inbreeding coefficient; *P* (*Fis* ≠ 0) = the p-value of the permutation test</caption><thead><tr><th>Patch</th><th>N</th><th>Na</th><th>Nae</th><th>He</th><th>Ho</th><th>Fis</th><th>P (Fis ≠ 0)</th></tr></thead><tbody><tr><td>A</td><td>90</td><td>12.00</td><td>5.83</td><td>0.805</td><td>0.807</td><td>-0.002</td><td>0.956</td></tr><tr><td>B</td><td>93</td><td>13.50</td><td>5.84</td><td>0.808</td><td>0.828</td><td>-0.024</td><td>0.175</td></tr><tr><td>C</td><td>93</td><td>12.50</td><td>7.05</td><td>0.854</td><td>0.827</td><td>0.032</td><td>0.084</td></tr><tr><td>D</td><td>92</td><td>12.33</td><td>6.39</td><td>0.822</td><td>0.837</td><td>-0.018</td><td>0.341</td></tr><tr><td>All</td><td>368</td><td>15.33</td><td>6.37</td><td>0.822</td><td>0.816</td><td>0.007</td><td>0.441</td></tr></tbody></table>
We found a high genetic diversity for the whole population (*He* = 0.822; Table S3) and in each patch (Table 2). Moreover, these value of genetic diversity were similar to the ones we found in our previous study (*He* = 0.859 and *Ho* = 0.850 Mazal et al., 2021).

Regressions between Rᵢⱼ values and the spatial
distance were never significant, indicating no spatial
genetic structure in any of the four sampled patch-
es along the 1.2 km river reach (Fig. 2). Kinship
coefficient (Rᵢⱼ) between pairs of seedlings ranged
between -0.31 and 0.55, indicating that some full-
sibs are present in the sample (within and among
patches in the same alluvial bar). However, when
sampling randomly all independent pairwise related-
ness coefficients Rᵢⱼs within patches, we found no dif-
ferences between intra-patch and inter-patch mean
Rᵢⱼ (mean intra = 0.00419±0.00104 SE; mean inter
= -0.00265±0.00102 SE; average = 0.472; aver-
age corrected = 0.907). Only 0.06% of our p-values
where inferior to the 0.05 threshold (Fig. S2), further
confirming the absence of genetic structure over our
sampling area.

Discussion

We found a high level of genetic diversity for the
studied population (for comparison with other pub-
lished data on Black poplar, see Mazal et al. (2021).
Furthermore, the level of genetic diversity detected
for the seedlings in this study is similar to the one
found in the later life stages of the same population
(Mazal et al., 2021). Similar level of genetic diversity
between different life stages were also reported by
Wójkiewicz et al. (2019). The authors proposed that
the maintenance of high genetic variation through
the generations is essential for long term stability of
populations maintaining a balance between genetic
drift and mutation. The high genetic diversity found
here confirms that in the current state, the hydrogeo-
morphological and ecological conditions in the study
reach of the Allier River are suitable for the preser-
vation of the genetic resources of the Black poplar.

We did not detect any significant FSGS for the
four patches of the one-year-old seedlings we stud-
ied in the Allier River, and also genetic structure
across the patches. The results indicate that primary
seed dispersal did not create an initial FSGS pattern
during recruitment in 2019. In plants in general,
the dispersal curves show a maximum of seed dis-
persal relatively close to the source (Nathan, 2006;
Nathan et al., 2008). Black poplar seeds are gen-
erally deposited within only a few hundred meters
of the mother tree (Braatne, 1996). In a previous
study, we found a significant FSGS in five-year-old
cohorts, but not for older cohorts in both the Allier
and Garonne Rivers (Mazal et al., 2021). Following

the idea of a short-distance dispersion, and our pre-
vious results, we proposed that across short disper-
sal distances seeds from different mother trees were
not homogeneously dispersed and could lead to an
initial FSGS pattern after germination. The present
study does not verify this hypothesis. Moreover, the
studied population is located in a natural reserve that
experiences moderate anthropogenic impacts and
no barrier to gene flow were identified (Petit, 2006;
Dejaifve & Esquirol, 2011). Mature trees are abun-
dant in this reserve. Thus, the absence of FSGS we
observed, indicated that seeds from numerous and
different parent trees (both mothers and fathers) are
widely dispersed by wind and water and are deposit-
ed homogeneously on the various germination sites
available along a few kilometres. This result shows
that when reproductive trees are in high density in a
river reach, the diverse genotypes spatially cover the
whole span of local habitat variability thanks to an ef-
ficient mixing of seeds during dispersal only over few
km. Such phenomena may lead to an improved ca-
pacity of the population to reach each year a suitable
recruitment window in a highly variable and shifting
mosaic of habitat conditions. Our results however
suggest that seeds from one mother tree can disperse
at relatively short distances as evidenced by the fact
that some pairs of highly related individuals (high
Rᵢⱼ values) were found in the same patches and by
the FSGS found in the five-year-old cohort (Mazal et
al., 2021). All together, these observations could in-
dicate multiple pathways of seed dispersal resulting
in patches with or without FSGS at the recruitment
stage. The interannual variability of the hydrologi-
cal regime combined with the possibility for *P. nigra*
seeds to disperse by wind and/or water would ex-
plain the proposed pattern of seed dispersal.

FSGS was found in young cohorts of Black poplars
(five-years old) in the Allier and the Garonne rivers
but not in older cohorts (Mazal et al., 2021). The pre-
vious significant FSGS we observed in the five-years
old cohorts in the Allier and the Garonne Rivers may
be the result of a singular group dispersal event, lead-
ing to the formation of patches of related individuals
(Mazal et al., 2021). The change in FSGS between
cohorts (i.e. from seedlings to five-years old) could
also be caused by similar microhabitat requirements
between related individuals, which could lead to dif-
ferential mortality. Similarly, Berens et al. (2014)
showed in *Prunus africana*, that SGS was stronger in
adults than in late juveniles. The authors propose
that similar microhabitat requirements between re-
lated individuals, along with spatial heterogeneity in
abiotic conditions, could allow the survival of related
individuals in later life stages, resulting in a higher
SGS in adults stages.

In our previous study, we did not find global ge-
netic structuring (Mazal et al., 2021). Therefore, for
We found a high genetic diversity for the whole population (*He* = 0.822; Table S3) and in each patch (Table 2). Moreover, these value of genetic diversity were similar to the ones we found in our previous study (*He* = 0.859 and *Ho* = 0.850 Mazal et al., 2021).

Regressions between R<sub>ij</sub> values and the spatial
distance were never significant, indicating no spatial
genetic structure in any of the four sampled patch-
es along the 1.2 km river reach (Fig. 2). Kinship
coefficient (R<sub>ij</sub>) between pairs of seedlings ranged
between -0.31 and 0.55, indicating that some full-
sibs are present in the sample (within and among
patches in the same alluvial bar). However, when
sampling randomly all independent pairwise related-
ness coefficients R<sub>ij</sub>s within patches, we found no dif-
ferences between intra-patch and inter-patch mean
R<sub>ij</sub> (mean intra = 0.00419±0.00104 SE; mean inter
= -0.00265±0.00102 SE; average = 0.472; aver-
age corrected = 0.907). Only 0.06% of our p-values
where inferior to the 0.05 threshold (Fig. S2), further
confirming the absence of genetic structure over our
sampling area.

Discussion

We found a high level of genetic diversity for the
studied population (for comparison with other pub-
lished data on Black poplar, see Mazal et al. (2021).
Furthermore, the level of genetic diversity detected
for the seedlings in this study is similar to the one
found in the later life stages of the same population
(Mazal et al., 2021). Similar level of genetic diversity
between different life stages were also reported by
Wójkiewicz et al. (2019). The authors proposed that
the maintenance of high genetic variation through
the generations is essential for long term stability of
populations maintaining a balance between genetic
drift and mutation. The high genetic diversity found
here confirms that in the current state, the hydrogeo-
morphological and ecological conditions in the study
reach of the Allier River are suitable for the preser-
vation of the genetic resources of the Black poplar.

We did not detect any significant FSGS for the
four patches of the one-year-old seedlings we stud-
ied in the Allier River, and also genetic structure
across the patches. The results indicate that primary
seed dispersal did not create an initial FSGS pattern
during recruitment in 2019. In plants in general,
the dispersal curves show a maximum of seed dis-
persal relatively close to the source (Nathan, 2006;
Nathan et al., 2008). Black poplar seeds are gen-
erally deposited within only a few hundred meters
of the mother tree (Braatne, 1996). In a previous
study, we found a significant FSGS in five-year-old
cohorts, but not for older cohorts in both the Allier
and Garonne Rivers (Mazal et al., 2021). Following

the idea of a short-distance dispersion, and our pre-
vious results, we proposed that across short disper-
sal distances seeds from different mother trees were
not homogeneously dispersed and could lead to an
initial FSGS pattern after germination. The present
study does not verify this hypothesis. Moreover, the
studied population is located in a natural reserve that
experiences moderate anthropogenic impacts and
no barrier to gene flow were identified (Petit, 2006;
Dejaifve & Esquirol, 2011). Mature trees are abun-
dant in this reserve. Thus, the absence of FSGS we
observed, indicated that seeds from numerous and
different parent trees (both mothers and fathers) are
widely dispersed by wind and water and are deposit-
ed homogeneously on the various germination sites
available along a few kilometres. This result shows
that when reproductive trees are in high density in a
river reach, the diverse genotypes spatially cover the
whole span of local habitat variability thanks to an ef-
ficient mixing of seeds during dispersal only over few
km. Such phenomena may lead to an improved ca-
pacity of the population to reach each year a suitable
recruitment window in a highly variable and shifting
mosaic of habitat conditions. Our results however
suggest that seeds from one mother tree can disperse
at relatively short distances as evidenced by the fact
that some pairs of highly related individuals (high
R<sub>ij</sub> values) were found in the same patches and by
the FSGS found in the five-year-old cohort (Mazal et
al., 2021). All together, these observations could in-
dicate multiple pathways of seed dispersal resulting
in patches with or without FSGS at the recruitment
stage. The interannual variability of the hydrologi-
cal regime combined with the possibility for *P. nigra*
seeds to disperse by wind and/or water would ex-
plain the proposed pattern of seed dispersal.

FSGS was found in young cohorts of Black poplars
(five-years old) in the Allier and the Garonne rivers
but not in older cohorts (Mazal et al., 2021). The pre-
vious significant FSGS we observed in the five-years
old cohorts in the Allier and the Garonne Rivers may
be the result of a singular group dispersal event, lead-
ing to the formation of patches of related individuals
(Mazal et al., 2021). The change in FSGS between
cohorts (i.e. from seedlings to five-years old) could
also be caused by similar microhabitat requirements
between related individuals, which could lead to dif-
ferential mortality. Similarly, Berens et al. (2014)
showed in *Prunus africana*, that SGS was stronger in
adults than in late juveniles. The authors propose
that similar microhabitat requirements between re-
lated individuals, along with spatial heterogeneity in
abiotic conditions, could allow the survival of related
individuals in later life stages, resulting in a higher
SGS in adults stages.

In our previous study, we did not find global ge-
netic structuring (Mazal et al., 2021). Therefore, for
the present study, we chose only a limited number
of patches. In addition, to ensure repeatability of our
analysis, we chose our patches from two different al-
luvial banks. The results of the present study confirm
this lack of structure. However, since the individu-
als sampled in this study are not the same as those
sampled in our previous study, it is not possible to
establish a direct relationship between the patterns
of FSGS found in the different aged cohorts in our
two studies.

Concluding remarks

The present results on FSGS complement those
of our previous study in which the seedling stage
was missing. The absence of FSGS at the seedling
stage suggests that seed dispersal was homogeneous
in the sampled natural population. Further studies,
such as cohort monitoring approach from establish-
ment to the mature stage, would be promising for
precisely understanding how riparian successions
unfold and to point to potential factors that would
explain the changes in FSGS observed between the
different life stages in the Black poplar. Moreover,
we chose to study a site located in a natural reserve
where the flow regime is unregulated, river mor-
phodynamics are only moderately impacted by hu-
man activities and that harbours a large number of
adult trees. This situation where natural processes
are largely undisturbed make it suitable for P. nigra
regeneration. In this site, genetic diversity was high,
similar to, or even higher than, most data available
for European rivers. This site is thus a valuable asset
for the conservation of P. nigra genetic diversity.

Acknowledgements

We would like to thank Guillaume Leroux (Ré-
serve Naturelle Nationale du Val d'Allier) for his help
during sampling in the Réserve, as well as Véronique
George, Vanina Guerin (INRA, Orléans, Génétique, Ad-
aptation et Amélioration (GA²) – Genotypage – Qualité),
Charles Poncet, Lydia Jaffarelo and Carole Confolent
(Plate-forme Gentyane UMR INRA Génétique Diversité et
Ecophysiologie des Céréales) for help with marker choice
and analyses, and Médéric Mouterde (U. de Genève)
for help with the statistical analysis.

Funding

Lucas Mazal was funded under his PhD by the
French Ministry of National Education, Higher Ed-
ucation and Research. The research was financed
by the French government IDEX-ISITE initiative
16-IDEX-0001 (CAP 20-25). Financial support was
provided by the LTSER Zone Atelier Loire – CNRS, the

Fédération des Recherches en Environnement (FR 3467 UCA/CNRS/INRA),

Compliance with ethical standard

The authors declare that they have no conflict of
interest.

Data archiving statement

Genotypes and R script used in this study are cur-
rently being submitted to Zenodo open-access repos-
itory (https://about.zenodo.org/).

Authors' contributions

All authors contributed to the study conception
and design. Sampling, material preparation, data col-
lection and analysis were performed by Lucas Mazal,
Irène Till-Bottraud and Boris Fumanal. Lucas Mazal
led the writing of the article to which all authors
contributed. All authors read and approved the final
manuscript.

References

Banks SC, Cary GJ, Smith AL, Davies ID, Driscoll
DA, Gill AM, Lindenmayer DB & Peakall R (2013)
How does ecological disturbance influence genet-
ic diversity? Trends in Ecology & Evolution 28:
670-679. doi:10.1016/j.tree.2013.08.005.

Baldauf C, Ciampi-Guillardi M, Aguirra TJ, Corrêa
CE, dos Santos FAM, de Souza AP & Sebbenn AM
(2014) Genetic diversity, spatial genetic struc-
ture and realised seed and pollen dispersal of Hi-
matanthus drasticus (Apocynaceae) in the Brazilian
savanna. Conservation Genetics 15: 1073-1083.
doi:10.1007/s10592-014-0600-5.

Barrat-Segretain MH (1996) Strategies of reproduc-
tion, dispersion, and competition in river plants:
A review. Vegetatio 123: 13-37. doi:10.1007/
BF00044885.

Barsoum N (2002) Relative contributions of sex-
ual and asexual regeneration strategies in
*Populus nigra* and Salix alba during the first
years of establishment on a braided gravel
bed river. Evolutionary Ecology 15: 255-279.
doi:10.1023/A:1016028730129.

Barsoum N & Hughes FMR (1998) Regeneration
response of black poplar to changing river lev-
els. Hydrology in a Changing Environment.
Wiley-Blackwell, pp. 397-412.

Batista Leite FA, Brandão RL, Buzatti RS de O, de
Lemos-Filho JP & Lovato MB (2014) Fine-scale
genetic structure of the threatened rosewood Dal-
bergia nigra from the Atlantic Forest: comparing
the present study, we chose only a limited number
of patches. In addition, to ensure repeatability of our
analysis, we chose our patches from two different al-
luvial banks. The results of the present study confirm
this lack of structure. However, since the individu-
als sampled in this study are not the same as those
sampled in our previous study, it is not possible to
establish a direct relationship between the patterns
of FSGS found in the different aged cohorts in our
two studies.

Concluding remarks

The present results on FSGS complement those
of our previous study in which the seedling stage
was missing. The absence of FSGS at the seedling
stage suggests that seed dispersal was homogeneous
in the sampled natural population. Further studies,
such as cohort monitoring approach from establish-
ment to the mature stage, would be promising for
precisely understanding how riparian successions
unfold and to point to potential factors that would
explain the changes in FSGS observed between the
different life stages in the Black poplar. Moreover,
we chose to study a site located in a natural reserve
where the flow regime is unregulated, river mor-
phodynamics are only moderately impacted by hu-
man activities and that harbours a large number of
adult trees. This situation where natural processes
are largely undisturbed make it suitable for P. nigra
regeneration. In this site, genetic diversity was high,
similar to, or even higher than, most data available
for European rivers. This site is thus a valuable asset
for the conservation of P. nigra genetic diversity.

Acknowledgements

We would like to thank Guillaume Leroux (Ré-
serve Naturelle Nationale du Val d'Allier) for his help
during sampling in the Réserve, as well as Véronique
George, Vanina Guerin (INRA, Orléans, Génétique, Ad-
aptation et Amélioration (GA²) – Genotypage – Qualité),
Charles Poncet, Lydia Jaffarelo and Carole Confolent
(Plate-forme Gentyane UMR INRA Génétique Diversité et
Ecophysiologie des Céréales) for help with marker choice
and analyses, and Médéric Mouterde (U. de Genève)
for help with the statistical analysis.

Funding

Lucas Mazal was funded under his PhD by the
French Ministry of National Education, Higher Ed-
ucation and Research. The research was financed
by the French government IDEX-ISITE initiative
16-IDEX-0001 (CAP 20-25). Financial support was
provided by the LTSER Zone Atelier Loire – CNRS, the

Fédération des Recherches en Environnement (FR 3467 UCA/CNRS/INRA),

Compliance with ethical standard

The authors declare that they have no conflict of
interest.

Data archiving statement

Genotypes and R script used in this study are cur-
rently being submitted to Zenodo open-access repos-
itory (https://about.zenodo.org/).

Authors' contributions

All authors contributed to the study conception
and design. Sampling, material preparation, data col-
lection and analysis were performed by Lucas Mazal,
Irène Till-Bottraud and Boris Fumanal. Lucas Mazal
led the writing of the article to which all authors
contributed. All authors read and approved the final
manuscript.

References

Banks SC, Cary GJ, Smith AL, Davies ID, Driscoll
DA, Gill AM, Lindenmayer DB & Peakall R (2013)
How does ecological disturbance influence genet-
ic diversity? Trends in Ecology & Evolution 28:
670-679. doi:10.1016/j.tree.2013.08.005.

Baldauf C, Ciampi-Guillardi M, Aguirra TJ, Corrêa
CE, dos Santos FAM, de Souza AP & Sebbenn AM
(2014) Genetic diversity, spatial genetic struc-
ture and realised seed and pollen dispersal of Hi-
matanthus drasticus (Apocynaceae) in the Brazilian
savanna. Conservation Genetics 15: 1073-1083.
doi:10.1007/s10592-014-0600-5.

Barrat-Segretain MH (1996) Strategies of reproduc-
tion, dispersion, and competition in river plants:
A review. Vegetatio 123: 13-37. doi:10.1007/
BF00044885.

Barsoum N (2002) Relative contributions of sex-
ual and asexual regeneration strategies in
*Populus nigra* and Salix alba during the first
years of establishment on a braided gravel
bed river. Evolutionary Ecology 15: 255-279.
doi:10.1023/A:1016028730129.

Barsoum N & Hughes FMR (1998) Regeneration
response of black poplar to changing river lev-
els. Hydrology in a Changing Environment.
Wiley-Blackwell, pp. 397-412.

Batista Leite FA, Brandão RL, Buzatti RS de O, de
Lemos-Filho JP & Lovato MB (2014) Fine-scale
genetic structure of the threatened rosewood Dal-
bergia nigra from the Atlantic Forest: comparing
saplings versus adults and small fragment versus continuous forest. Tree Genetics & Genomes 10: 307–316. doi:10.1007/s11295-013-0685-x.

Benjamini Y & Hochberg Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 57: 289–300. doi:10.1111/j.2517-6161.1995.tb02031.x.

Bessega C, Pometti CL, Ewens M, Saidman BO & Vilardi JC (2016) Fine-scale spatial genetic structure analysis in two Argentine populations of *Prosopis alba* (Mimosoideae) with different levels of ecological disturbance. European Journal of Forest Research 135: 495–505. doi:10.1007/s10342-016-0948-9.

Born C, Hardy OJ, Chevallier M-H, Ossari S, AttéKé C, Wickings EJ & Hossaert-Mckey M (2008) Small-scale spatial genetic structure in the Central African rainforest tree species *Aucoumea klaineana*: a stepwise approach to infer the impact of limited gene dispersal, population history and habitat fragmentation: SGS in a central african tree species. Molecular Ecology 17: 2041–2050. doi:10.1111/j.1365-294X.2007.03685.x.

Braatne (1996) Life history, ecology and reproduction of riparian cottonwoods in North America.

Brookfield JFY (1996) A simple new method for estimating null allele frequency from heterozygote deficiency. Molecular Ecology 5: 453–455. doi:10.1046/j.1365-294X.1996.00098.x.

Chamaillard S (2011) Efficience de l'utilisation de l'eau chez le peuplier noir (*Populus nigra* L.) : variabilité et plasticité en réponse aux variations de l'environnement.

Chenault N, Arnaud-Haond S, Juteau M, Valade R, Almeida J-L, Villar M, Bastien C & Dowkiw A (2011) SSR-based analysis of clonality, spatial genetic structure and introgression from the Lom bardy poplar into a natural population of *Populus nigra* L. along the Loire River. Tree Genetics & Genomes 7: 1249–1262. doi:10.1007/s11295-011-0410-6.

Corenblit D, Garófano-Gómez V, González E, Hortobágyi B, Julien F, Lambs L, Otto T, Roussel E, Steiger J, Tabacchi E & Till-Bottraud I (2018) Niche construction within riparian corridors. Part II: The unexplored role of positive intraspecific interactions in *Salicaceae* species. Geomorphology 305: 112–122. doi:10.1016/j.geomorph.2017.09.016.

Corenblit D, Steiger J, Charrier G, Darrozes J, Garófano-Gómez V, Garreau A, González E, Gurnell AM, Hortobágyi B, Julien F, Lambs L, Larrue S, Otto T, Roussel E, Vautier F & Voldoire O (2016) *Populus nigra* L. establishment and fluvial landform construction: biogeomorphic dynamics

within a channelized river: Biogeomorphic Dynamics within a Channelized River. Earth Surface Processes and Landforms 41: 1276–1292. doi:10.1002/esp.3954.

Corenblit D, Steiger J, González E, Gurnell AM, Charrier G, Darrozes J, Dousseau J, Julien F, Lambs L, Larrue S, Roussel E, Vautier F & Voldoire O (2014) The biogeomorphological life cycle of poplars during the fluvial biogeomorphological succession: a special focus on *Populus nigra* L.: The biogeomorphological life cycle of poplars. Earth Surface Processes and Landforms 39: 546–563. doi:10.1002/esp.3515.

Corenblit D, Steiger J, Gurnell AM & Naiman RJ (2009) Plants intertwine fluvial landform dynamics with ecological succession and natural selection: a niche construction perspective for riparian systems. Global Ecology and Bio-geography 18: 507–520. doi:10.1111/j.1466-8238.2009.00461.x.

Dejaifve PA & Esquirol N (2011) Quantification et répartition du bois mort échoué dans la Réserve Naturelle Nationale du Val d'Allier. Réserve Naturelle Nationale du Val d'Allier - DIREN-Auvergne, Moulins.

Deng JY, van Noort S, Compton SG, Chen Y & Greeff JM (2020) Conservation implications of fine scale population genetic structure of *Ficus* species in South African forests. Forest Ecology and Management 474: 118387. doi:10.1016/j.foreco.2020.118387.

Evanno G, Regnaut S & Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology 14: 2611–2620. doi:10.1111/j.1365-294X.2005.02553.x.

Faivre-Rampant P, Zaina G, Jorge V, Giacomello S, Se-gura V, Scalabrin S, Guérin V, De Paoli E, Aluome C, Viger M, Cattonaro F, Payne A, PaulStephenRaj P, Le Paslier MC, Berard A, Allwright MR, Villar M, Taylor G, Bastien C & Morgante M (2016) New resources for genetic studies in *Populus nigra*: ge-nome-wide SNP discovery and development of a 12k Infinium array. Molecular Ecology Resources 16: 1023–1036. doi:10.1111/1755-0998.12513.

Fajardo A, Torres-Díaz C & Till-Bottraud I (2016) Disturbance and density-dependent processes (competition and facilitation) influence the fine-scale genetic structure of a tree species' popula-tion. Annals of Botany 117: 67–77. doi:10.1093/aob/mcv148.

Garófano-Gómez V, Metz M, Egger G, Díaz-Redondo M, Hortobágyi B, Geerling G, Corenblit D & Steiger J (2017) Vegetation succession processes and fluvial dynamics of a mobile temperate riparian ecosystem: the lower Allier River (France). Géomorphologie: relief, processus, environne-
saplings versus adults and small fragment versus continuous forest. Tree Genetics & Genomes 10: 307–316. doi:10.1007/s11295-013-0685-x.

Benjamini Y & Hochberg Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 57: 289–300. doi:10.1111/j.2517-6161.1995.tb02031.x.

Bessega C, Pometti CL, Ewens M, Saidman BO & Vilardi JC (2016) Fine-scale spatial genetic structure analysis in two Argentine populations of *Prosopis alba* (Mimosoideae) with different levels of ecological disturbance. European Journal of Forest Research 135: 495–505. doi:10.1007/s10342-016-0948-9.

Born C, Hardy OJ, Chevallier M-H, Ossari S, AttéKé C, Wickings EJ & Hossaert-Mckey M (2008) Small-scale spatial genetic structure in the Central African rainforest tree species *Aucoumea klaineana*: a stepwise approach to infer the impact of limited gene dispersal, population history and habitat fragmentation: SGS in a central african tree species. Molecular Ecology 17: 2041–2050. doi:10.1111/j.1365-294X.2007.03685.x.

Braatne (1996) Life history, ecology and reproduction of riparian cottonwoods in North America.

Brookfield JFY (1996) A simple new method for estimating null allele frequency from heterozygote deficiency. Molecular Ecology 5: 453–455. doi:10.1046/j.1365-294X.1996.00098.x.

Chamaillard S (2011) Efficience de l'utilisation de l'eau chez le peuplier noir (*Populus nigra* L.) : variabilité et plasticité en réponse aux variations de l'environnement.

Chenault N, Arnaud-Haond S, Juteau M, Valade R, Almeida J-L, Villar M, Bastien C & Dowkiw A (2011) SSR-based analysis of clonality, spatial genetic structure and introgression from the Lom bardy poplar into a natural population of *Populus nigra* L. along the Loire River. Tree Genetics & Genomes 7: 1249–1262. doi:10.1007/s11295-011-0410-6.

Corenblit D, Garófano-Gómez V, González E, Hortobágyi B, Julien F, Lambs L, Otto T, Roussel E, Steiger J, Tabacchi E & Till-Bottraud I (2018) Niche construction within riparian corridors. Part II: The unexplored role of positive intraspecific interactions in *Salicaceae* species. Geomorphology 305: 112–122. doi:10.1016/j.geomorph.2017.09.016.

Corenblit D, Steiger J, Charrier G, Darrozes J, Garófano-Gómez V, Garreau A, González E, Gurnell AM, Hortobágyi B, Julien F, Lambs L, Larrue S, Otto T, Roussel E, Vautier F & Voldoire O (2016) *Populus nigra* L. establishment and fluvial landform construction: biogeomorphic dynamics

within a channelized river: Biogeomorphic Dynamics within a Channelized River. Earth Surface Processes and Landforms 41: 1276–1292. doi:10.1002/esp.3954.

Corenblit D, Steiger J, González E, Gurnell AM, Charrier G, Darrozes J, Dousseau J, Julien F, Lambs L, Larrue S, Roussel E, Vautier F & Voldoire O (2014) The biogeomorphological life cycle of poplars during the fluvial biogeomorphological succession: a special focus on *Populus nigra* L.: The biogeomorphological life cycle of poplars. Earth Surface Processes and Landforms 39: 546–563. doi:10.1002/esp.3515.

Corenblit D, Steiger J, Gurnell AM & Naiman RJ (2009) Plants intertwine fluvial landform dynamics with ecological succession and natural selection: a niche construction perspective for riparian systems. Global Ecology and Biogeography 18: 507–520. doi:10.1111/j.1466-8238.2009.00461.x.

Dejaifve PA & Esquirol N (2011) Quantification et répartition du bois mort échoué dans la Réserve Naturelle Nationale du Val d'Allier. Réserve Naturelle Nationale du Val d'Allier - DIREN-Auvergne, Moulins.

Deng JY, van Noort S, Compton SG, Chen Y & Greeff JM (2020) Conservation implications of fine scale population genetic structure of *Ficus* species in South African forests. Forest Ecology and Management 474: 118387. doi:10.1016/j.foreco.2020.118387.

Evanno G, Regnaut S & Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology 14: 2611–2620. doi:10.1111/j.1365-294X.2005.02553.x.

Faivre-Rampant P, Zaina G, Jorge V, Giacomello S, Segura V, Scalabrin S, Guérin V, De Paoli E, Aluome C, Viger M, Cattonaro F, Payne A, PaulStephenRaj P, Le Paslier MC, Berard A, Allwright MR, Villar M, Taylor G, Bastien C & Morgante M (2016) New resources for genetic studies in *Populus nigra*: genome-wide SNP discovery and development of a 12k Infinium array. Molecular Ecology Resources 16: 1023–1036. doi:10.1111/1755-0998.12513.

Fajardo A, Torres-Díaz C & Till-Bottraud I (2016) Disturbance and density-dependent processes (competition and facilitation) influence the fine-scale genetic structure of a tree species' population. Annals of Botany 117: 67–77. doi:10.1093/aob/mcv148.

Garófano-Gómez V, Metz M, Egger G, Díaz-Redondo M, Hortobágyi B, Geerling G, Corenblit D & Steiger J (2017) Vegetation succession processes and fluvial dynamics of a mobile temperate riparian ecosystem: the lower Allier River (France). Géomorphologie: relief, processus, environnement
ment 23:187-202. doi:10.4000/geomorpholo-
gie.11805.Gaudeul M & Till-Bottraud I (2008)
Genetic structure of the endangered perennial
plant *Eryngium alpinum* (Apiaceae) in an alpine val-
ley: genetic structure of *E. alpinum* within a valley.
Biological Journal of the Linnean Society 93: 667-
677. doi:10.1111/j.1095-8312.2008.00958.x.

González-Robles A, Manzaneda AJ, Salido T, Valera F, García C, Fernández-Ocaña AM & Rey PJ (2020) Spatial genetic structure of a keystone long-lived semiarid shrub: historical effects prevail but do not cancel the impact of recent severe habitat loss on genetic diversity. Conservation Genetics. doi:10.1007/s10592-020-01291-5.

Guilloy H, González E, Muller E, Hughes FMR & Barsoum N (2011) Abrupt drops in water table level influence the development of *Populus nigra* and *Salix alba* seedlings of different ages. Wetlands 31: 1249-1261. doi:10.1007/s13157-011-0238-8.

Guilloy-Froget H, Muller E, Barsoum N & Hughes
FMM (2002) Dispersal, germination, and sur-
vival of *Populus nigra* L. (Salicaceae) in changing
hydrologic conditions. Wetlands 22: 478-488.
doi:10.1672/0277-5212(2002)022[0478:DGAS-
OP]2.0.CO;2

Hardy OJ (2003) Estimation of pairwise relatedness between individuals and characterization of isolation-by-distance processes using dominant genetic markers. Molecular Ecology 12: 1577-1588. doi:10.1046/j.1365-294X.2003.01835.x.

Hardy OJ & Vekemans X (2002) spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618–620. doi:10.1046/j.1471-8286.2002.00305.x.

Hortobágyi B, Corenblit D, Vautier F, Steiger J, Rous-
sel E, Burkart A & Peiry J-L (2017) A multi-scale
approach of fluvial biogeomorphic dynamics us-
ing photogrammetry. Journal of Environmental
Management 202: 348–362. doi:10.1016/j.jen-
vman.2016.08.069.

Imbert E & Lefevre F (2003) Dispersal and gene flow of *Populus nigra* (Salicaceae) along a dynamic river system. Journal of Ecology 91: 447–456. doi:10.1046/j.1365-2745.2003.00772.x.

Jelić M, Patenković A, Skorić M, Mišić D, Kurbalija Novičić Z, Bordács S, Várhidi F, Vasić I, Benke A, Frank G & Šiler B (2015) Indigenous forests of European black poplar along the Danube River: genetic structure and reliable detection of introgression. Tree Genetics & Genomes 11. doi:10.1007/s11295-015-0915-5.

Jones CG, Lawton JH & Shachak M (1994) Organ-
isms as ecosystem engineers. Oikos 69: 373–386.
doi:10.2307/3545850.

Karrenberg S, Edwards PJ & Kollmann J (2002) The
life history of *Salicaceae* living in the active zone

of floodplains. Freshwater Biology 47: 733-748.
doi:10.1046/j.1365-2427.2002.00894.x.

Kettenring KM, Mossman BN, Downard R & Mock KE (2019) Fine-scale genetic diversity and landscape-scale genetic structuring in three foundational bulrush species: implications for wetland revegetation: Bulrush genetic diversity and structuring. Restoration Ecology 27: 408–420. doi:10.1111/rec.12884.

Kitamura K, Nakanishi A, Lian C & Goto S (2018) Distinctions in Fine-Scale Spatial Genetic Structure Between Growth Stages of *Picea jezoensis* Carr. Frontiers in Genetics 9: 490. doi:10.3389/fgene.2018.00490.

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understory shrub, *Psychotria officinalis* (Rubiaceae). American Journal of Botany 82: 1420–1425. doi:10.1002/j.1537-2197.1995.tb12679.x.

Mahoney JM & Rood SB (1998) Streamflow requirements for cottonwood seedling recruitment—An integrative model. Wetlands 18: 634–645. doi:10.1007/BF03161678.

Mazal L, Corenblit D, Barsoum N, Steiger J, Skot L, Fumanal B & Till-Bottraud I (2021) Fine-scale spatial genetic structure and intra-specific interactions of *Populus nigra* within a natural river corridor along the lower Allier River (France). Flora 275: 151763. doi:10.1016/j.flora.2021.151763.

Nathan R (2006) Long-Distance dispersal of plants. Science 313: 786-788. doi:10.1126/science.1124975.

Nathan R, Schurr FM, Spiegel O, Steinitz O, Trakhtenbrot A & Tsoar A (2008) Mechanisms of long-distance seed dispersal. Trends in Ecology & Evolution 23: 638–647. doi:10.1016/j.tree.2008.08.003.

Nielsen R, Tarpy DR & Reeve HK (2003) Estimating effective paternity number in social insects and the effective number of alleles in a population: effective paternity and number of alleles. Molecular Ecology 12: 3157–3164. doi:10.1046/j.1365-294X.2003.01994.x.

O Settings WS, Lee HK & Flanders DJ (1995) Link-
age analysis with multiplexed short tandem re-
peat polymorphisms using infrared fluorescence
and M13 tailed primers. Genomics 30: 450–458.
doi:10.1006/geno.1995.1264.

Peakall R & Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics 28: 2537-2539. doi:10.1093/bioinformatics/bts460.

Petit S (2006) Reconstitution de la dynamique du paysage alluvial de trois secteurs fonctionnels de la rivière Allier (1946-2000), Massif Central,
ment 23:187-202. doi:10.4000/geomorpholo-
gie.11805.Gaudeul M & Till-Bottraud I (2008)
Genetic structure of the endangered perennial
plant *Eryngium alpinum* (Apiaceae) in an alpine val-
ley: genetic structure of *E. alpinum* within a valley.
Biological Journal of the Linnean Society 93: 667-
677. doi:10.1111/j.1095-8312.2008.00958.x.

González-Robles A, Manzaneda AJ, Salido T, Valera F, García C, Fernández-Ocaña AM & Rey PJ (2020) Spatial genetic structure of a keystone long-lived semiarid shrub: historical effects prevail but do not cancel the impact of recent severe habitat loss on genetic diversity. Conservation Genetics. doi:10.1007/s10592-020-01291-5.

Guilloy H, González E, Muller E, Hughes FMR & Barsoum N (2011) Abrupt drops in water table level influence the development of *Populus nigra* and *Salix alba* seedlings of different ages. Wetlands 31: 1249-1261. doi:10.1007/s13157-011-0238-8.

Guilloy-Froget H, Muller E, Barsoum N & Hughes
FMM (2002) Dispersal, germination, and sur-
vival of *Populus nigra* L. (Salicaceae) in changing
hydrologic conditions. Wetlands 22: 478-488.
doi:10.1672/0277-5212(2002)022[0478:DGAS-
OP]2.0.CO;2

Hardy OJ (2003) Estimation of pairwise relatedness between individuals and characterization of isolation-by-distance processes using dominant genetic markers. Molecular Ecology 12: 1577-1588. doi:10.1046/j.1365-294X.2003.01835.x.

Hardy OJ & Vekemans X (2002) spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618–620. doi:10.1046/j.1471-8286.2002.00305.x.

Hortobágyi B, Corenblit D, Vautier F, Steiger J, Rous-
sel E, Burkart A & Peiry J-L (2017) A multi-scale
approach of fluvial biogeomorphic dynamics us-
ing photogrammetry. Journal of Environmental
Management 202: 348–362. doi:10.1016/j.jen-
vman.2016.08.069.

Imbert E & Lefevre F (2003) Dispersal and gene flow of *Populus nigra* (Salicaceae) along a dynamic river system. Journal of Ecology 91: 447–456. doi:10.1046/j.1365-2745.2003.00772.x.

Jelić M, Patenković A, Skorić M, Mišić D, Kurbalija Novičić Z, Bordács S, Várhidi F, Vasić I, Benke A, Frank G & Šiler B (2015) Indigenous forests of European black poplar along the Danube River: genetic structure and reliable detection of introgression. Tree Genetics & Genomes 11. doi:10.1007/s11295-015-0915-5.

Jones CG, Lawton JH & Shachak M (1994) Organ-
isms as ecosystem engineers. Oikos 69: 373–386.
doi:10.2307/3545850.

Karrenberg S, Edwards PJ & Kollmann J (2002) The
life history of *Salicaceae* living in the active zone

of floodplains. Freshwater Biology 47: 733-748.
doi:10.1046/j.1365-2427.2002.00894.x.

Kettenring KM, Mossman BN, Downard R & Mock KE (2019) Fine-scale genetic diversity and landscape-scale genetic structuring in three foundational bulrush species: implications for wetland revegetation: Bulrush genetic diversity and structuring. Restoration Ecology 27: 408–420. doi:10.1111/rec.12884.

Kitamura K, Nakanishi A, Lian C & Goto S (2018) Distinctions in Fine-Scale Spatial Genetic Structure Between Growth Stages of *Picea jezoensis* Carr. Frontiers in Genetics 9: 490. doi:10.3389/fgene.2018.00490.

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understory shrub, *Psychotria officinalis* (Rubiaceae). American Journal of Botany 82: 1420–1425. doi:10.1002/j.1537-2197.1995.tb12679.x.

Mahoney JM & Rood SB (1998) Streamflow require-
ments for cottonwood seedling recruitment—
An integrative model. Wetlands 18: 634–645.
doi:10.1007/BF03161678.

Mazal L, Corenblit D, Barsoum N, Steiger J, Skot L, Fumanal B & Till-Bottraud I (2021) Fine-scale spatial genetic structure and intra-specific interactions of *Populus nigra* within a natural river corridor along the lower Allier River (France). Flora 275: 151763. doi:10.1016/j.flora.2021.151763.

Nathan R (2006) Long-Distance dispersal of plants. Science 313: 786-788. doi:10.1126/science.1124975.

Nathan R, Schurr FM, Spiegel O, Steinitz O, Trakhtenbrot A & Tsoar A (2008) Mechanisms of long-distance seed dispersal. Trends in Ecology & Evolution 23: 638–647. doi:10.1016/j.tree.2008.08.003.

Nielsen R, Tarpy DR & Reeve HK (2003) Estimating effective paternity number in social insects and the effective number of alleles in a population: effective paternity and number of alleles. Molecular Ecology 12: 3157–3164. doi:10.1046/j.1365-294X.2003.01994.x.

O settings WS, Lee HK & Flanders DJ (1995) Link-
age analysis with multiplexed short tandem re-
peat polymorphisms using infrared fluorescence
and M13 tailed primers. Genomics 30: 450–458.
doi:10.1006/geno.1995.1264.

Peakall R & Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics 28: 2537-2539. doi:10.1093/bioinformatics/bts460.

Petit S (2006) Reconstitution de la dynamique du paysage alluvial de trois secteurs fonctionnels de la rivière Allier (1946-2000), Massif Central,
France. Géographie Physique et Quaternaire 60: 271-287. doi:10.7202/018000ar.

Pospíšková M & Šálková I (2006) Population structure and parentage analysis of black poplar along the Morava River. Canadian Journal of Forest Research 36: 1067-1076. doi:10.1139/x06-003.

Pritchard JK, Stephens M & Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945-959. doi:10.1093/ genetics/155.2.945.

Puechmaille SJ (2016) The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem. Molecular Ecology Resources 16: 608-627. doi:10.1111/1755-0998.12512.

Ramos SLF, Dequigiovanni G, Sebbenn AM, Lopes MTG, Kageyama PY, de Macêdo JLV, Kirst M & Veasey EA (2016) Spatial genetic structure, genetic diversity and pollen dispersal in a harvested population of *Astrocaryum aculeatum* in the Brazilian Amazon. BMC Genetics 17: 63. doi:10.1186/s12863-016-0371-8.

Rathmacher G, Niggemann M, Köhnen M, Ziegenhagen B & Bialozyt R (2010) Short-distance gene flow in *Populus nigra* L. accounts for small-scale spatial genetic structures: implications for in situ conservation measures. Conservation Genetics 11: 1327-1338. doi:10.1007/s10592-009-9961-6.

Sagnard F, Oddou-Muratorio S, Pichot C, Vendramin GG & Fady B (2011) Effects of seed dispersal, adult tree and seedling density on the spatial genetic structure of regeneration at fine temporal and spatial scales. Tree Genetics & Genomes 7: 37-48. doi:10.1007/s11295-010-0313-y.

Segovia NI, Vásquez JA, Faugeron S & Haye PA (2015) On the advantage of sharing a holdfast: effects of density and occurrence of kin aggregation in the kelp Lessonia berteroana. Marine Ecology 36: 1107-1117. doi:10.1111/maec.12206.

Sjölund MJ & Jump AS (2015) Coppice management of forests impacts spatial genetic structure but not genetic diversity in European beech (*Fagus sylvestris* L.). Forest Ecology and Management 336: 65-71. doi:10.1016/j.foreco.2014.10.015.

Smulders MJM, Van Der Schoot J, Arens P & Vosman B (2002) Trinucleotide repeat microsatellite markers for black poplar (*Populus nigra* L.): primer note. Molecular Ecology Notes 1: 188-190. doi:10.1016/j.foreco.2007.10.063.

Stella JC & Battles JJ (2010) How do riparian woody seedlings survive seasonal drought? Oecologia 164: 579-590. doi:10.1007/s00442-010-1657-6.

Till-Bottraud I, Fajardo A & Rioux D (2012) Multi-stemmed trees of *Nothofagus pumilio* second-growth forest in Patagonia are formed by highly related individuals. Annals of Botany 110: 905-913. doi:10.1093/aob/mcs146.

Twyford AD, Wong ELY & Friedman J (2020) Multi-level patterns of genetic structure and isolation by distance in the widespread plant *Mimulus guttatus*. Heredity 125: 227-239. doi:10.1038/s41437-020-0335-7.

Van Oosterhout C, Hutchinson WF, Wills DPM & Shipley P (2004) micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4: 535-538. doi:10.1111/j.1471-8286.2004.00684.x.

Vekemans X & Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Molecular Ecology 13: 921-935. doi:10.1046/j.1365-294X.2004.02076.x.

Wendelgaß J (2016) Vegetative und generative Vermehrungsstrategien der Schwarzpappel (Populus nigra) und deren Beziehung zu fluvialen Prozessen und Sukzessionsentwicklungen des Auenökosystems am Allier (Frankreich). Wissenschaftliche Zulassungsarbeit für das Lehramt an Gymnasien im Fach Geographie. KIT – Karlsruher Institut für Technologie.

Wójkiewicz B, Żukowska WB, Wachowiak W & Lewandowski A (2019) The genetic assessment of the natural regeneration capacities of black poplar populations in the modern river valley landscapes. Forest Ecology and Management 448: 150-159. doi:10.1016/j.foreco.2019.06.003.
France. Géographie Physique et Quaternaire 60: 271-287. doi:10.7202/018000ar.

Pospíšková M & Šálková I (2006) Population structure and parentage analysis of black poplar along the Morava River. Canadian Journal of Forest Research 36: 1067-1076. doi:10.1139/x06-003.

Pritchard JK, Stephens M & Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945-959. doi:10.1093/ genetics/155.2.945.

Puechmaille SJ (2016) The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem. Molecular Ecology Resources 16: 608-627. doi:10.1111/1755-0998.12512.

Ramos SLF, Dequigiovanni G, Sebbenn AM, Lopes MTG, Kageyama PY, de Macêdo JLV, Kirst M & Veasey EA (2016) Spatial genetic structure, genetic diversity and pollen dispersal in a harvested population of *Astrocaryum aculeatum* in the Brazilian Amazon. BMC Genetics 17: 63. doi:10.1186/s12863-016-0371-8.

Rathmacher G, Niggemann M, Köhnen M, Ziegenhagen B & Bialozyt R (2010) Short-distance gene flow in *Populus nigra* L. accounts for small-scale spatial genetic structures: implications for in situ conservation measures. Conservation Genetics 11: 1327-1338. doi:10.1007/s10592-009-9961-6.

Sagnard F, Oddou-Muratorio S, Pichot C, Vendramin GG & Fady B (2011) Effects of seed dispersal, adult tree and seedling density on the spatial genetic structure of regeneration at fine temporal and spatial scales. Tree Genetics & Genomes 7: 37-48. doi:10.1007/s11295-010-0313-y.

Segovia NI, Vásquez JA, Faugeron S & Haye PA (2015) On the advantage of sharing a holdfast: effects of density and occurrence of kin aggregation in the kelp Lessonia berteroana. Marine Ecology 36: 1107-1117. doi:10.1111/maec.12206.

Sjölund MJ & Jump AS (2015) Coppice management of forests impacts spatial genetic structure but not genetic diversity in European beech (*Fagus sylvestris* L.). Forest Ecology and Management 336: 65-71. doi:10.1016/j.foreco.2014.10.015.

Smulders MJM, Van Der Schoot J, Arens P & Vosman B (2002) Trinucleotide repeat microsatellite markers for black poplar (*Populus nigra* L.): primer note. Molecular Ecology Notes 1: 188-190. doi:10.1016/j.foreco.2007.10.063.

Stella JC & Battles JJ (2010) How do riparian woody seedlings survive seasonal drought? Oecologia 164: 579-590. doi:10.1007/s00442-010-1657-6.

Till-Bottraud I, Fajardo A & Rioux D (2012) Multi-stemmed trees of *Nothofagus pumilio* second-growth forest in Patagonia are formed by highly related individuals. Annals of Botany 110: 905-913. doi:10.1093/aob/mcs146.

Twyford AD, Wong ELY & Friedman J (2020) Multi-level patterns of genetic structure and isolation by distance in the widespread plant *Mimulus guttatus*. Heredity 125: 227-239. doi:10.1038/s41437-020-0335-7.

Van Oosterhout C, Hutchinson WF, Wills DPM & Shipley P (2004) micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4: 535-538. doi:10.1111/j.1471-8286.2004.00684.x.

Vekemans X & Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Molecular Ecology 13: 921-935. doi:10.1046/j.1365-294X.2004.02076.x.

Wendelgaß J (2016) Vegetative und generative Vermehrungsstrategien der Schwarzpappel (Populus nigra) und deren Beziehung zu fluvialen Prozessen und Sukzessionsentwicklungen des Auenökosystems am Allier (Frankreich). Wissenschaftliche Zulassungsarbeit für das Lehramt an Gymnasien im Fach Geographie. KIT – Karlsruher Institut für Technologie.

Wójkiewicz B, Żukowska WB, Wachowiak W & Lewandowski A (2019) The genetic assessment of the natural regeneration capacities of black poplar populations in the modern river valley landscapes. Forest Ecology and Management 448: 150-159. doi:10.1016/j.foreco.2019.06.003.