0
000-0001-8401-5880  
SPatial Structure of PhenotyPic traitS in Seven  
ProvenanceS of neltuma alba (fabaceae)  
eStructura eSPacial de caractereS fenotíPicoS en Siete  
ProcedenciaS de neltuma alba (fabaceae)  
1
& Juan C. Vilardi  
María V. Vega * , Beatriz O. Saidman  
Summary  
Backgrounds: Neltuma alba is one of the most important native woody species in  
Argentina in the Dry Chaco, part of the Argentine Mesopotamia and the Paraguayan  
Chaco. It shows great variability due to interspecific hybridization and introgression  
associated with protogyny and self-incompatibility systems. This species is adapted  
to arid and semi-arid climates with saline and degraded soils. Environmental  
heterogeneity and wide distribution may result in local adaptation and autocorrelated  
spatial patterns in genetic and quantitative variables.  
1
.
Laboratory of Plants  
Biotechnology, FRN, SECyT, UNaF,  
Formosa, Argentina  
2
. Department of Ecology, Genetics  
and Evolution. FCEN. UBA, IEGEBA,  
CONICET, Buenos Aires, Argentina  
Aim: To analyze the spatial structure in provenances of N. alba influenced by isolation  
by distance in the Gran Chaco Region.  
*mavivega@yahoo.es  
M&M: This work studied spatial structure in seven provenances of N. alba from the  
Dry and Humid Chaco regions, based on fifteen foliar, fruit and germination traits in  
Citar este artículo  
VEGA, M. V., B. O. SAIDMAN & J.  
C. VILARDI. 2023. Spatial structure  
68 individuals, together with five environmental variables.  
Results and Conclusion: univariate statistical analyses showed significant or highly  
significant differences among provenances. According to Moran’s I index phenotypic  
and geographical distances are significantly autocorrelated for the first distance  
class (0-0.643 km). Partial Mantel test showed significant correlation for the first  
two distance classes. The overall analysis showed that 11 of the analyzed traits  
showed significant spatial autocorrelation. The local spatial analysis indicated that  
for several traits their hot spots of high similarity between neighboring individuals  
and cold spots where nearby individuals are highly differentiated.  
of phenotypic traits in seven  
provenances of Neltuma alba  
(
5
Fabaceae). Bol. Soc. Argent. Bot.  
8: 547-560.  
KeyS wordS  
Local adaptation, morphological traits, Neltuma, origin, Prosopis, spatial  
autocorrelation analyses.  
reSumen  
Introducción: Neltuma alba es una de las leñosas nativas más importantes de  
Argentina. Ocupa la ecorregión de Gran Chaco y parte de la MesopotamiaArgentina.  
Muestra gran variabilidad parcialmente atribuida a hibridación e introgresión con  
otros algarrobos, asociados a la protoginia y sistemas de autoincompatibilidad.  
Se adapta a climas áridos y semiáridos con suelos salinos y degradados. La  
heterogeneidad ambiental y su amplia distribución pueden asociarse a adaptación  
local y autocorrelacionados espacial en variables genéticas y cuantitativas.  
Objetivo: Analizar la estructura espacial en procedencias de N. alba influenciada por  
el aislamiento por distancia en la Región del Gran Chaco.  
M&M: Se evaluó la autocorrelación en siete procedencias de N. alba de las  
ecorregiones del Chaco Seco y el Chaco Húmedo, basado en quince rasgos  
foliares, de fruto y germinación en 68 individuos adultos, incluyendo información de  
cinco variables ambientales.  
Resultados y conclusión: Los análisis estadísticos univariados demostraron  
diferencias significativas  
o altamente significativas entre procedencias. La  
asociación entre la similitud fenotípica y la distancia geográfica mostró valores de  
autocorrelación significativa para la primera clase de distancia (0-0.643 km). El test  
de Mantel parcial indicó que la correlación entre la distancia fenotípica y geográfica  
se pierde a partir de 40 - 50 km. El análisis global mostró que 11 de los rasgos  
analizados presentaron una autocorrelación significativa. El análisis espacial local  
indicó que para varios rasgos existen puntos de alta similitud entre individuos  
vecinos (hotspots) y puntos donde los individuos cercanos están muy diferenciados  
Recibido: 24 Nov 2022  
Aceptado: 29 Sep 2023  
Publicado impreso: 22 Dic 2023  
Editora: Paola Gaiero  
(coldspots).  
PalabraS clave  
Análisis de autocorrelación espacial, caracteres adaptativos, Neltuma, origen,  
Prosopis, rasgos morfológicos.  
ISSN versión impresa 0373-580X  
ISSN versión on-line 1851-2372  
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Bol. Soc. Argent. Bot. 58 (4) 2023  
and their derivatives are used for human food  
and fodder and their wood is of high quality  
for furniture and charcoal production. They  
introduction  
In 1943, Wright introduced the term isolation show high morphological variability and  
by distance to describe a pattern in which ecological amplitude, offering the possibility of  
genetic differentiation increases with geographic selecting trees adapted to diverse environments.  
distance. In this context, genetic differentiation Morphometric studies carried out in Neltuma  
among populations would be the result of the species, account for phenotypic differentiation  
interaction between drift and gene flow. Wang among populations, which can be attributed  
&
Bradburd (2014) incorporate the concept to genetic differences caused by adaptation to  
of isolation by environment as a pattern in various environmental conditions (Bessega et  
which genetic differentiation increases with al., 2015; Fontana et al., 2018), observable at  
environmental differences, regardless the different levels: species, populations, individuals  
geographic distance. Together, processes that and even within the same individual (Fontana et  
reduce the rate of dispersal and environmental al., 2018; Castillo et al., 2021).  
differences among populations will generate  
The factors capable of generating SA patterns  
patterns of increased genetic differentiation. and affecting the genetic coherence among  
These distribution patterns of variation can be provenances include the mechanisms of pollen  
generated by climatic and edaphic variations and seed dispersal and the environmental  
and geographic isolation (Siabato & Guzman heterogeneity (Roser, 2017). Based on studies  
Manrique, 2019).  
conducted by researchers on Neltuma species,  
One way to assess the association between the dispersal distances of pollen and seeds  
phenotypic similarity and geographic distance is are short, which is why in local populations a  
spatial autocorrelation (SA) analysis, defined as marked reduction in kinship and phenotypic  
the property of pairs of spatial objects of being resemblance among individuals was observed  
more (positive SA) or less similar (negative SA) depending on the distance that separates them  
to each other than randomly expected (Getis (Bessega et al., 2012; Roser, 2017).  
&
Ord, 1992). The first index to measure SA,  
proposed by Moran (Moran’s Global I index) in  
1
950, was used to evaluate whether the values materialS and methodS  
of one (phenotypic) variable studied tended  
to cluster spatially. In the 90s, measurements Sampling  
of local autocorrelation were developed, that  
Relatively homogeneous natural areas within  
allowed to capture local spatial autocorrelation the distribution of Neltuma alba (Griseb.)  
indicators such as the coefficients Gi and Gi* C.E.Hughes & G.P.Lewis were identified, and  
(
Ord & Getis, 1995; Garcia, 2019), which individuals from seven provenances representing  
described spatial clustering around individual three complexes of two ecoregions within the  
sites, to discover local “packages” (hot spots) of Argentine Chaco region were collected covering  
autocorrelated points. In the early 2000s, a new a latitudinal and longitudinal geographic gradient  
approach defined as landscape genetics emerged, (Table 1). Five provenances correspond to the  
oriented to the analysis of interactions between Dry Chaco Ecoregion: Ibarreta (ib), Laguna  
landscape features and evolutionary processes Yema (ly), Isla Cuba (ic), Las Breñas (lb)  
such as gene flow and selection (Bessega et al., and Charata (ch). The other two provenances  
2
015).  
are located in the Humid Chaco Ecoregion:  
In the arid and semiarid forest regions of the Formosa (fo) and Villa Dos Trece (vi) (Table  
Humid Chaco and Dry Chaco in Argentina, the 1, Fig. 1). The provenances of ib, ly and ic are  
woody species of the Neltuma Raf. (formerly located in the Pilcomayo-Bermejo Interfluvial  
Prosopis L., Hughes et al., 2022) genus stand Complex, while lb and ch are located in the  
out, constituting an important multipurpose Antiguos Cauces of Juramento-Salado Complex  
natural resource. The fruits of these species (Table 1). These complexes belong to the Dry  
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Bol. Soc. Argent. Bot. 58 (4) 2023  
Fig. 1. Distribution of the Dry Chaco (red) and Humid Chaco (blue) ecoregions in Argentina with the  
geographic location of the sampled sites (provenances). The distribution of the ecoregions was obtained  
from Morello et al. (2012). Abbreviations: fo: Formosa; ch: Charata, ib: Ibarreta, ic: Isla Cuba, lb: Las Breñas,  
ly: Laguna Yema, vi: Villa Dos Trece.  
Chaco Ecoregion, where the warm continental the area of the large river collectors and about  
subtropical climate predominates, with absolute 750 mm in the border with the Dry Chaco. The  
maximum temperatures exceeding 47°C. Eastern Complex of the Lower Paraguay River  
Absolute minimum temperatures range between is located approximately 150-400 km from the  
-
6° and -7°C in the plains and foothills, and Bermejo-Pilcomayo Interfluvial Complex, and  
between -12° and -16°C in the foothills of Chaco 430 km from the Antiguos Cauces of Juramento-  
Serrano (Morello et al., 2012). Precipitation Salado Complex. While the Bermejo-Pilcomayo  
ranges from 700 mm (isohyet between Santiago Interfluvial Complex and the Antiguos Cauces  
and Northern Santa Fe and Central Southern del Juramento-Salado Complex are 496 km apart  
Chaco) to 400 mm in the valleys of Güemes, (Table 1; Fig. 1).  
Tapia-Trancas and Catamarca hills (Morello et  
al., 2012).  
To capture a good representation of the  
variation, 10 individuals (mother plants) per  
The provenances of fo and vi are located in the provenance were randomly chosen, with typical  
Eastern Complex of the Lower Paraguay River morphological characteristics of N. alba,  
(
Table 1), where annual precipitation decreases according to the description of Burkart (1976).  
from West to East with more than 1300 mm in Seeds were collected from each individual to set  
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M. V. Vega et al. - Spatial structure in Neltuma alba  
up a progeny trial in a nursery in the Formosa which leaves, seeds and fruits were randomly  
National University. The set of seeds collected collected from branches located in the basal  
from each mother plant was considered a family part of each individual in each provenance. Ten  
made up of half-sibs, following the criterion that measurements were made of each of the organs  
trees should be at least 50 m apart (Saidman & mentioned in each of the 68 families sampled/  
Vilardi, 1993; Bessega et al., 2000) to reduce the provenance. To make up the herbarium, two  
probability of duplications in the sampling due duplicates were prepared, all from the same plant  
to the possible relationship among neighboring and with the same collection number.  
trees.  
Individual records of leaf, pod and seed traits,  
The geographic location of the harvested were based on the averages of 10 measurements  
individuals was recorded using a GPS (Garmin per individual. To assess the germination traits,  
Etrex 10). Harvesting data sheets were filled 25 seeds were used for each provenance and  
in using the passport information described family. They were planted in plastic trays  
by the International Plant Genetic Resources (260 mm x 190 mm x 60 mm) containing 400  
Institute, adapted to the species under study, g of sterilized sand, treated with Kaptan 50  
and documenting the topographic, edaphic and % WP (CAS Nº 133-06-2). Later, they were  
climatic characteristics of each provenance. For placed in an incubation chamber at 27°C±2°C,  
each sampled site, five environmental variables under continuous fluorescent white light of 150  
-
2
-1  
were analyzed: mean rainfall (mr), mean mmol.m .s with a photoperiod of 8 h of light,  
temperature (mean T), maximum temperature for 20 days, recording the number of germinated  
(
max T), minimum temperature (min T) and seeds daily. Seeds were considered germinated  
water vapor pressure (wvp). These data were when their coats were broken by the radicles.  
collected from: https://worldclim.org, with a  
3
0 sec resolution. The information corresponds  
The germination rate (GR) was measured as  
to the 1970-2000 period. For each variable, 12 follows:  
GeoTiff files were obtained, one for each month  
of the year. The environmental variables of each  
sampling site were extracted from the GeoTiff  
files using the extract function of the raster  
where g is the number of germinated seeds at  
package (Hijmans, 2019) of the R program (R the end of the trial and s is the total number of  
Core Team, 2020). In each case, the records of planted seeds.  
all the months were averaged to obtain an annual  
mean (Table 1).  
Germination power (GP) was quantified using  
the Djavanshir & Pourbeik (1976) expression, as  
follows:  
Analyzed traits  
Herbarium vouchers and fruit samples were  
obtained from each sampled individual in order  
to measure the following morphological traits:  
where GDM represents the average daily  
leaflet length (LL) and width (LW) (cm), petiole germination and is calculated as the total  
length (PEL, cm), length of the longest pinnae percentage of germinated seeds at the end of  
of each leaf (PIL, cm), number of pinnae per the trial divided by the number of days the trial  
leaf (NPL), interleaf distance (ID, cm), number lasted, that is,  
of leaflet pairs per pinnae (LP), pod length (PL)  
and width (PW, cm), seed length (SL) and width  
(
(
SW, cm), number of developed seeds per pod  
SN), germination rate (GR) (%), germination  
where G is the number of germinated seeds,  
power (GP) and mean germination time (GT, S is the total number of seeds sown and T is  
days) (Table 2). Measurements were carried the total length of the trial in days. In addition,  
out on fresh samples, using the methodology VP is the peak or maximum value obtained by  
proposed by Palacios & Bravo (1981), for dividing the germination rate accumulated day  
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Bol. Soc. Argent. Bot. 58 (4) 2023  
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M. V. Vega et al. - Spatial structure in Neltuma alba  
by day, by the number of days elapsed. Finally, entire area analyzed. Significance was obtained  
mean germination time (GT) was quantified as using a permutation test with 1000 simulations.  
proposed by Silva & Nakagawa (1995):  
The fourth was a local spatial analysis by the eco.  
lsa function, using the Gi* coefficient (Getis &  
Ord, 1992, 1995). This analysis identified points  
of high similarity or high dissimilarity between  
where T = number of days elapsed since neighbors and significance was obtained by a  
i
the beginning of germination, N = number of permutation test (1000 simulations). In all the  
i
germinated seeds on day i, and N = total number cases, the distance classes were defined so that  
of germinated seeds at the end of the trial.  
they all included the same number of individuals  
pairs, representing with intense red coloration  
sites where neighbors tended to be very similar  
Statistical Methods  
To characterize the phenotypic variation among to each other (hot spots), and with intense  
the provenances, the following linear model was blue coloration sites where there was high  
used:  
dissimilarity between neighbors (cold spots).  
reSultS  
where Zij is the trait observation of the  
individual j from provenance i, μ is the general  
The measurements obtained for leaf, fruit,  
mean, P is the provenance effect and e is the see, and germination traits are specified in Table  
i
ij  
residual component. For continuous traits, a 2. Highly significant differences were recorded  
conventional linear model was applied, while in for most of the variables, even after correction  
the case of GP, a generalized model was applied for multiple comparisons. The only variables  
considering that the response is a binomial that did not show significant differences were ID  
variable. All the analyses were carried out using and PW. The multivariate analysis of variance  
R, version 4.2.1 (R Core Team, 2020). To control showed that the differences among provenances  
the Type 1 error, the significance P values of the were highly significant considering the total set  
-
16  
individual tests were corrected for multiple tests of traits (Pillai = 3.3 P<10 ).  
using the FDR (false discovery rate) method (R  
Core Team, 2020).  
Moran’s Index  
Spatial autocorrelation analyses were carried  
Univariate correlogram analyses were  
out with the EcoGenetics package (Roser et al., performed for each trait considered individually  
017) of the R program. Spatial autocorrelation and an average correlogram based on Moran’s  
2
was analyzed using four methods. The first one I coefficient (Fig. 2). The first point represents  
was based on correlograms using Moran’s I the autocorrelation among individuals separated  
coefficient (Moran, 1950), applied to each trait from each other by a distance of 0 to 0.643  
analyzed and multivariate correlogram (average) km, which would correspond to the closest  
using Moran’s I coefficient. The analysis was neighbors, located within the same provenance.  
performed using the eco.correlog function and The mean distance between pairs of individuals  
significance was obtained by bootstrap (1000 within this distance class is 0.192 km. The  
simulations). The second method was based on second point is the autocorrelation among  
the comparison of morphological distance and individuals separated from each other by 0.643  
geographical distance matrices by means of to 15.445 km (mean = 7.736 km); in this case  
Mantel correlograms using the eco.cormantel the individuals of each pair belong to the same  
function, including the environmental distances provenance with the exception of some pairs  
among sampling sites as a third matrix. The third involving individuals from lb and ch. In all  
method consisted of a global spatial analysis, remaining classes pairs involve individuals  
using the eco.gsa function, which produced a from different provenances (distances > 15.45  
single global statistic for each trait across the km) (Table 3).  
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Bol. Soc. Argent. Bot. 58 (4) 2023  
Mantel Correlograms  
Table 3. Classes of morphological-geographic  
distances among the individuals analyzed and  
Mantel correlogram significance for the set of traits  
analyzed. Observed correlation, p-values and  
p-values adjusted for multiple tests are reported.  
Black numbers indicate significant differences.  
Mantel correlograms of phenotypic distances  
as a function of geographic distances, using  
environmental distances as a third matrix,  
gave highly significant results for the first  
two distance classes (p = 0.0001 and 0.0002  
respectively) (Table 3, Fig. 3). The Mantel  
correlogram graph cuts the 0 ordinate at  
approximately 50 km and that from distances  
between 40 and 80 km the differentiation among  
individuals does not depend on geographic  
distance suggesting that individuals would be  
virtually isolated.  
Adjusted  
Traits  
LL  
obs  
p-value  
p-value  
0.002  
0.4  
0.3  
0.5  
0.2  
0.6  
0.2  
0.9  
0.2  
0.1  
0.7  
0.2  
0.3  
0.4  
0.5  
0.4  
0.001  
0.02  
0.001  
0.1  
LW  
PEL  
PIL  
NLP  
ID  
0.03  
0.002  
0.1  
0.001  
0.03  
0.001  
0.1  
0.002  
0.04  
0.002  
0.1  
Global Autocorrelation  
Global autocorrelation is significant for  
1
1 of the traits analyzed after correction  
LP  
for multiple comparisons (Table 4). These  
results are consistent with the univariate  
Moran’s correlograms: eight of the traits with  
higher global autocorrelation (LL, LW, NPL,  
LP, SN, GR, GP y GT) showed significant  
autocorrelation in the first two classes (Fig.  
PL  
PW  
SN  
SL  
0.2  
0.2  
0.001  
0.1  
0.002  
0.1  
2
A-B, E, G, J, M-O), while PIL, ID, PW,  
SW  
GR  
GP  
GT  
0.03  
0.001  
0.001  
0.002  
0.04  
0.002  
0.002  
0.004  
SL, and SW did not show significant global  
autocorrelation (Table 4) not even for the first  
class of distance (Fig. 2D, F, I, K-L).  
Local Spatial Analysis Getis Ord Statistics  
In contrast to the global correlation, a  
In 10 of the traits analyzed, autocorrelation marked variation among features and sites was  
was significant at least for the first class of observed for local autocorrelation (Fig. 4A-O).  
distance (Fig 2A-C, E, G-H, J, M-O). Three The Gi* coefficient allowed the visualization  
traits (LL, LP and GP) showed significant of provenances groupings with similar values  
autocorrelation in the third classes of distance according to geographic area. Within each  
(
15.445 – 90.674 km). In the case of LL, the provenance, traits were observed with non-  
similarity is reduced to approximately 75-80 significant autocorrelation (yellow circles),  
km, since the line that joins the points passes negative (cold spots) represented by intense  
through 0 between points 3 and 4. From that blue dots, which corresponded to values of  
distance, the similarity among individuals would dissimilar individuals in relation to their  
be random (Table 3, Fig. 2A). For LW, LP, SN, neighbors, and positive (hot spots), with intense  
GP and GT, autocorrelation is significant for the red coloration corresponding to individuals  
first and second interval, and autocorrelation is with similar values (Fig. 4). No trend associated  
lost starting at 40 km (Fig. 2B, G, J, N-O). For with the type of trait has been observed, since  
PEL and PL, autocorrelation is significant only the leaf, fruit and germination traits presented  
for the first interval (Fig. 2C, H). The average hot and cold spots in different provenances. For  
correlogram indicates that the phenotypic traits such as PIL, PL, PW and SL the presence  
similarity is significant for the first two classes of families with non-significant Gi* values was  
of distance and the corresponding chart (Fig. 2P) observed in all or almost all provenances (Table  
cuts the ordinate zero approximately at 50 km.  
4, Fig. 4D, H-I, K).  
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M. V. Vega et al. - Spatial structure in Neltuma alba  
Fig. 2. Spatial autocorrelation quantified by the Moran’s I index for the phenotypic traits analyzed. A: Length  
of leaflet, B: Leaflet width, C: Length of petiole, D: Length of pinna, E: Number of pinna/leave, F: Inter-leaf  
distance, G: Number of pairs of leaflets/pinna, H: Pod length, I: Pod width, J: Number of seeds, K: Seed  
length, L: Seed width, M: Germination rate, N: Germination power, O: Mean germination time. P: Average.  
Red dots represent p-values <0.05 and blue dots represent p-values ≥0.05. In all plots the x-axis represents  
geographic distance expressed in kilometers (km).  
Fig. 3. Correlogram based on the partial Mantel statistic correlogram. It compares the morphological  
distance matrices with the geographical ones, with correction for environmental differences. The x-axis  
represents geographic distance expressed in kilometers (km). Red dots represent p-values <0.05 and blue  
dots represent p-values ≥0.05.  
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Fig. 4. Local spatial analysis for the 15 morphological traits analyzed, based on the Getis and Ord statistic  
Gi* (1992). The color scale to the right of each graph represents the Gi* value at each sampled point. On  
the left upper chart, the location of each sampled provenance is shown. Abbreviations: ch: Charata, fo:  
Formosa, ib: Ibarreta, ic: Isla Cuba, lb: Las Breñas, ly: Laguna Yema, vi: Villa Dos Trece. A: Length of leaflet,  
B: Leaflet width, C: Length of petiole, D: Length of pinna, E: Number of pinna/leave, F: Inter-leaf distance,  
G: Number of pairs of leaflets/pinna, H: Pod length, I: Pod width, J: Number of seeds, K: Seed length, L:  
Seed width, M: Germination rate, N: Germination power, O: Mean germination time. In all plots the x-axis  
and y-axis represent geographic distance expressed in kilometers (km).  
diScuSSion and concluSionS  
for this species. In general, it is of interest to quantify  
the association between phenotypic variability and  
One of the forest species that adapts very well genetic variability, since the morphological traits  
to a wide environmental heterogeneity is N. alba, present high variability with the environment  
that may yield local adaptation processes and (Teich et al., 2015). Unpublished preliminary  
autocorrelated spatial patterns. Learning about results developed by our laboratory in nurseries  
these patterns would be useful for the development suggest that most of the traits are associated with  
of genetic improvement and conservation programs environmental variables of the parent’s origin site.  
557  
Bol. Soc. Argent. Bot. 58 (4) 2023  
The global autocorrelation of morphological  
The provenances studied represent three  
variability analysis detected spatial structure for complexes from two ecoregions with different  
most of the analyzed traits, which could indicate the environmental characteristics. In addition, some of  
existence of a joint environment-foliar phenotype these provenances are several hundred kilometers  
variation consistent with that observed by Roser apart, so an important geographic isolation can  
(2017) at a smaller spatial scale in the same species. be expected considering that pollen dispersal in  
The Mantel correlogram revealed the existence Neltuma species (Algarobia section) was estimated  
of distribution patterns of phenotypic variation by Bessega et al. (2000) in approximately 31  
shown by a positive autocorrelation at geographic meters.  
distances with the same geographical location. The  
disappearance of this pattern at longer distances speciessuchasNeltumaflexuosa(DC.)C.E.Hughes  
may be explained by limited gene flow associated G.P.Lewis (Darquier et al., 2013) and  
with short pollen and seed dispersal as described by Neltuma chilensis (Molina) C.E.Hughes  
Likewise, previous studies in other mesquite  
&
&
Bessega et al. (2017). This fact also occurs in other G.P.Lewis (Bessega et al., 2022) show that several  
species in addition to the local action of genetic drift of the leaf traits analyzed in this work would have  
and a strong family structure (Goncalvez, 2019).  
adaptive value, so that they could be affected by  
In N. alba, the low dispersal rate determines that the different environmental conditions of local  
genetic differentiation increases rapidly over short populations, which may contribute to the observed  
distances and the results obtained with the Mantel diversity.  
correlogram are consistent with the analysis based  
Neighboring families, separated by short  
on Moran’s I index, which indicates a marked spatial distances, were highly related, showing high  
structure as observed in other studies on N. alba levels of kinship. However, local analysis with  
(Teich et al., 2015; Goncalvez, 2019) and other tree the Gi* statistic revealed the existence of both  
species (Villareal, 2018; Ortiz et al., 2018). Our hot spots and cold spots within each provenance,  
results indicate that phenotypic correlation among suggesting a complex internal structure that could  
pairs of individuals would be lost on average at a reduce inbreeding by presenting hot spots with  
distance of approximately 50 km. This result might high phenotypic diversity at specific sites within  
mostly depend on the region analyzed since in N. populations.  
chilensis, a species related to N. alba, Contreras Díaz  
The results suggest that traits characterizing  
et al. (2021) indicate that provenances separated leaflet size and number, seed size and number  
by approximately 40 km do not show evidence of and germination are spatially structured. The  
isolation.  
analysis revealed the existence of local phenotypic  
The distribution patterns of variation may be patterns, which could be associated with limited  
due to geographic or environmental isolation. In gene flow. The observed spatial autocorrelation  
the former case individuals mate randomly within a patterns and the high phenotypic diversity among  
neighborhood, but are restricted from mating with the provenances could be explained on the basis  
more distant members (Wright, 1943). This reduction of the isolation model by distance mediated by  
in the phenotypic similarity would be due to the fact restricted gene flow proposed in the present and  
that the dispersion of pollen and seeds in the species of other analyses in N. alba and related species  
the Algarobia section is generally reduced (between 5 (Bessega et al., 2012; Roser, 2017).  
and 31 meters), resulting in a significant decrease in  
the relatedness of individuals with increasing spatial  
distance separating them (Bessega et al., 2012), author contributionS  
and with each mother plant receiving pollen from  
approximately seven different male parents (Bessega  
MVV collected the material, carried out the  
et al., 2017). In other cases, lack of genetic structuring measurements, trials in the nursery, and wrote  
associated with geographic origin has been observed, the manuscript, BS carried out the design and  
due to the dispersal process, and not to large distances collaborated with the manuscript drafting, JV  
(>500 meters), which would not act as a barrier to carried out the experimental design, statistical  
pollen flow (Aguirre Morales, 2017). analysis and final manuscript review.  
558  
M. V. Vega et al. - Spatial structure in Neltuma alba  
This work was carried out thanks to the BURKART, A. 1976. A monograph of the genus Prosopis  
financial support of the Agency National of  
(Leguminosae Subfam. Mimosoideae). J. Arnold  
Technological and Scientific Promotion (PICTO  
Arb. 57: 219-249, 450-525.  
2
011-0081to B.O.S.) and CONICET (PIP Nº  
CASTILLO, M., U. SCHAFFENER, B. van WILGEN,  
N. MONTAÑO, R. BUSTAMANTE,A. COSACOV,  
M. MATHESE & J. LE ROUX. 2021. Genetic  
insights into the globally invasive and taxonomically  
11220130100191CO to JCV and C. Pometti).  
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