Research Article |
Corresponding author: Ana Novoa ( novoa.perez.ana@gmail.com ) Academic editor: Jane Molofsky
© 2023 Ana Novoa, Heidi Hirsch, María L. Castillo, Susan Canavan, Luís González, David M. Richardson, Petr Pyšek, Jonatan Rodríguez, Lurdes Borges Silva, Giuseppe Brundu, Carla M. D’Antonio, Jorge L. Gutiérrez, Megan Mathese, Sam Levin, Luís Silva, Johannes J. Le Roux.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Novoa A, Hirsch H, Castillo ML, Canavan S, González L, Richardson DM, Pyšek P, Rodríguez J, Borges Silva L, Brundu G, D’Antonio CM, Gutiérrez JL, Mathese M, Levin S, Silva L, Le Roux JJ (2023) Genetic and morphological insights into the Carpobrotus hybrid complex around the world. NeoBiota 89: 135-160. https://doi.org/10.3897/neobiota.89.109164
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The genus Carpobrotus N.E.Br. comprises between 12 and 25 species, most of which are native to South Africa. Some Carpobrotus species are considered among the most damaging invasive species in coastal dune systems worldwide. In their introduced areas, these species represent a serious threat to native species and significantly impact soil conditions and geochemical processes. Despite being well studied, the taxonomy of Carpobrotus remains problematic, as the genus comprises a complex of species that hybridize easily and are difficult to distinguish from each other. To explore the population genetic structure of invasive Carpobrotus species (i.e., C. acinaciformis and C. edulis) across a significant part of their native and non-native ranges, we sampled 40 populations across Argentina, Italy, New Zealand, Portugal, South Africa, Spain, and the USA. We developed taxon-specific microsatellite markers using a Next Generation Sequencing approach to analyze the population genetic structure and incidence of hybridization in native and non-native regions. We identified three genetically distinct clusters, which are present in both the native and non-native regions. Based on a set of selected morphological characteristics, we found no clear features to identify taxa morphologically. Our results suggest that the most probable sources of global introductions of Carpobrotus species are the Western Cape region of South Africa and the coastline of California. We suggest that management actions targeting Carpobrotus invasions globally should focus on preventing additional introductions from the east coast of South Africa, and on searching for prospective biocontrol agents in the Western Cape region of South Africa.
Biological invasions, genetic diversity, genetic structure, hybridization, introduction history, invasive alien plant, microsatellite markers, taxonomic uncertainty
Coastal habitats such as coastal dunes, sea cliffs, and coastal prairies are exposed to a variety of extreme environmental conditions, including high salinity, low soil moisture, soil nutrient deficiencies, and intense wind and solar irradiance (
The succulent genus Carpobrotus N.E.Br. (family Aizoaceae) comprises between 12 and 25 species and lower-rank taxa, most of them native to South Africa (
To gain insight into the invasiveness and impact of non-native species, as well as to develop or improve management actions it is important to know the taxonomic identity and the introduction history of the target invasive species (
Two Carpobrotus species are currently considered to be invasive: C. edulis (L.) N.E.Br., and C. acinaciformis (L.) L.Bolus (
Carpobrotus chilensis also provides a good example of the taxonomic and biogeographic uncertainties that plague the genus. Some authors consider this species to be native to California and Chile (
Here, we aim to shed light on the relatedness and introduction history of invasive Carpobrotus spp. around the world. With this overarching aim, we (1) sampled invasive Carpobrotus species in coastal areas across many of their presumed native and invaded ranges and (2) developed and used a set of genus-specific microsatellite markers to assess and compare the genetic diversity and structure among these populations. Moreover, aiming to help managers and other stakeholders with the identification of invasive Carpobrotus species in the field, we (3) compared the morphological characteristics of the Carpobrotus taxa assigned to distinct genetic clusters.
We sampled a total of 40 Carpobrotus populations distributed across their native and invasive ranges (Fig.
Locality details and genetic characteristics of populations of Carpobrotus species sampled in this study (also see Fig.
ID | Region | Locality | Coordinates (Lat, Long) | N | Cluster | Genetic diversity | Clonal diversity | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Na | HO | HE | FIS | G | Ne | HE | Gd | ||||||
NZ1 | New Zealand | Whirinaki | -39.829, 176.8914 | 10 | A | 2.167 | 0.483 | 0.335 | -0.440 | 8 | 6.250 | 0.933 | 0.840 |
NZ2 | New Zealand | Foxton | -40.4557, 175.2168 | 10 | A | 2.167 | 0.533 | 0.336 | -0.490 | 7 | 6.250 | 0.933 | 0.840 |
NZ3 | New Zealand | Rough Island | -41.2709, 173.1137 | 14 | A | 1.667 | 0.524 | 0.299 | -0.707 | 4 | 2.882 | 0.703 | 0.653 |
NZ4 | New Zealand | Rarangi | -41.4188, 174.0357 | 20 | A | 1.833 | 0.550 | 0.336 | -0.634 | 8 | 4.255 | 0.805 | 0.765 |
NZ5 | New Zealand | Lake Ellsmere | -43.8599, 172.3534 | 20 | A | 2.000 | 0.542 | 0.367 | -0.393 | 11 | 9.524 | 0.942 | 0.895 |
SE1 | Azores | São Vicente | 37.8325, -25.6647 | 30 | A | 1.500 | 0.417 | 0.229 | -0.778 | 1 | 1.000 | 0 | 0 |
SE2 | Spain | Punta de Rons | 42.497, -8.8790 | 16 | A | 1.500 | 0.500 | 0.250 | -1.000 | 1 | 1.000 | 0 | 0 |
SE3 | Spain | A Lanzada | 42.4328, -8.875215 | 24 | A | 1.500 | 0.500 | 0.250 | -1.000 | 1 | 1.000 | 0 | 0 |
ZA1 | South Africa | Rooisand | -34.3490, 19.0909 | 16 | A | 2.500 | 0.469 | 0.330 | -0.344 | 7 | 2.415 | 0.625 | 0.586 |
ZA3 | South Africa | Vogelgat | -34.4021, 19.3199 | 16 | A | 2.500 | 0.533 | 0.358 | -0.308 | 7 | 3.879 | 0.792 | 0.742 |
ZA4 | South Africa | Belvidere | -34.0532, 22.9964 | 13 | A | 2.000 | 0.474 | 0.368 | -0.201 | 8 | 6.259 | 0.910 | 0.840 |
CA2 | California | Celeste | 40.8520, -124.1710 | 23 | B | 1.333 | 0.341 | 0.174 | -0.674 | 1 | 1.000 | 0 | 0 |
CA3 | California | Point Reyes | 38.0457, -122.9888 | 20 | B | 2.167 | 0.544 | 0.431 | -0.279 | 11 | 8.333 | 0.926 | 0.880 |
CA4 | California | For Ord | 36.6587, -121.8226 | 20 | B | 2.333 | 0.563 | 0.427 | -0.320 | 15 | 10.526 | 0.953 | 0.905 |
CA5 | California | Soberanes Point | 36.45065, -121.9280 | 19 | B | 1.833 | 0.536 | 0.358 | -0.399 | 4 | 2.391 | 0.614 | 0.582 |
CA6 | California | Minuteman beach | 34.8563, -120.6086 | 8 | B | 1.833 | 0.542 | 0.296 | -0.736 | 3 | 2.133 | 0.607 | 0.531 |
CA7 | California | Wall beach | 34.70521, -120.5995 | 18 | B | 2.333 | 0.576 | 0.418 | -0.341 | 10 | 7.364 | 0.915 | 0.864 |
CA8 | California | South Base | 34.70520, -120.6012 | 7 | B | 2.333 | 0.494 | 0.422 | -0.179 | 5 | 3.769 | 0.857 | 0.735 |
SE6 | Azores | Ribeira Grande | 37.8305, -25.5163 | 28 | B | 1.667 | 0.648 | 0.333 | -0.947 | 1 | 1.000 | 0 | 0 |
SE7 | Spain | Samil | 42.2144, -8.7755 | 20 | B | 1.500 | 0.500 | 0.250 | -1.000 | 1 | 1.000 | 0 | 0 |
SE8 | Spain | Marina | 38.1443, -0.6343 | 20 | B | 1.833 | 0.333 | 0.212 | -0.232 | 2 | 1.220 | 0.189 | 0.180 |
ZA5 | South Africa | Mdumbi | -31.9443, 29.2100 | 15 | B | 1.333 | 0.333 | 0.167 | -1.000 | 1 | 1.000 | 0 | 0 |
ZA10 | South Africa | Cape St Francis | -34.1766, 24.8231 | 8 | C | 1.667 | 0.229 | 0.142 | -0.300 | 4 | 2.286 | 0.643 | 0.562 |
ZA11 | South Africa | Port Elizabeth | -34.0247, 25.6480 | 19 | C | 2.167 | 0.364 | 0.251 | -0.322 | 7 | 4.056 | 0.795* | 0.753 |
ZA12 | South Africa | Port Alfred | -33.6093, 26.8900 | 19 | C | 1.333 | 0.225 | 0.131 | -0.606 | 2 | 1.870 | 0.491* | 0.465 |
ZA13 | South Africa | Cintsa | -32.8268, 28.1194 | 19 | C | 2.000 | 0.322 | 0.258 | -0.232 | 3 | 1.994 | 0.526 | 0.499 |
ZA14 | South Africa | Port Edward | -31.0441, 30.2276 | 18 | C | 1.500 | 0.250 | 0.166 | -0.502 | 4 | 2.945 | 0.699 | 0.660 |
ZA9 | South Africa | Keurboomstrand | -34.0286, 23.3975 | 20 | C | 2.000 | 0.400 | 0.270 | -0.434 | 8 | 5.405 | 0.858 | 0.815 |
ARG1 | Argentina | Mar Chiquita | -37.7550, -57.4304 | 22 | Admixed | 2.000 | 0.424 | 0.309 | -0.251 | 4 | 1.967 | 0.515 | 0.492 |
ARG2 | Argentina | San Eduardo del Mar | -38.2355, -57.7548 | 10 | Admixed | 2.000 | 0.412 | 0.339 | -0.254 | 6 | 4.167 | 0.844 | 0.760 |
ARG3 | Argentina | Quequén | -38.5675, -58.6499 | 9 | Admixed | 1.500 | 0.500 | 0.250 | -1.000 | 1 | 1 | 0 | 0 |
CA1 | California | Mackerricher | 39.4912, -123.7950 | 16 | Admixed | 1.500 | 0.500 | 0.250 | -1.000 | 3 | 2.415 | 0.625 | 0.586 |
SE5 | Azores | Mosteiros | 37.8986, -25.8175 | 36 | Admixed | 1.500 | 0.343 | 0.184 | -0.507 | 2 | 1.117 | 0.108 | 0.105 |
SE4 | Spain | Cádiz | 36.5678, -6.2225 | 12 | Admixed | 1.833 | 0.475 | 0.315 | 0.330 | 4 | 2.880 | 0.712 | 0.653 |
SE9 | Italy | Marina di Sorso | 40.8194, 8.4953 | 21 | Admixed | 1.833 | 0.443 | 0.276 | -0.484 | 6 | 2.96 | 0.695 | 0.662 |
ZA2 | South Africa | Springfontein | -34.4287, 19.4065 | 10 | Admixed | 2.333 | 0.494 | 0.381 | -0.362 | 10 | 10 | 1* | 0.900 |
ZA6 | South Africa | Mossel Bay | -34.1715, 22.1226 | 20 | Admixed | 2.667 | 0.507 | 0.444 | -0.171 | 14 | 10.526 | 0.953 | 0.905 |
ZA7 | South Africa | Melkbosstrand | -33.7065, 18.4482 | 17 | Admixed | 2.333 | 0.331 | 0.303 | -0.048 | 4 | 2.513 | 0.64 | 0.602 |
ZA8 | South Africa | Cape Point | -34.3530, 18.4888 | 17 | – | – | – | – | – | – | – | – | – |
ZA15 | South Africa | Durban | -30.1268, 30.8457 | 18 | Admixed | 2.500 | 0.400 | 0.370 | -0.170 | 8 | 3.951 | 0.791 | 0.747 |
Populations of Carpobrotus species sampled in this study (see Table
We excluded Chile from our studied area due to issues encountered with exporting plant material from that country. Carpobrotus species are also found all along Australia’s coastline (Fig.
In each locality (Fig.
Microsatellite sequences were isolated by Ecogenics GmbH (Balgach, Switzerland). Size selected fragments from Carpobrotus genomic DNA were enriched for microsatellite repeats by using magnetic streptavidin beads and biotin-labelled CT and GT repeat oligonucleotides. The microsatellite enriched library was analyzed on a Roche 454 Titanium technology (Roche Diagnostics Corporation). This resulted in 89 reads containing microsatellite motifs of at least six microsatellite nucleotide repeat units. Suitable primer design was possible for 32 reads, of which 25 primer pairs were selected and tested for amplification and polymorphism. We extracted DNA from Carpobrotus leaf material using a modified cetyltrimethylammonium bromide (CTAB) protocol (
We used the software Micro-Checker (version 2.2;
Linkage disequilibrium was evaluated with the “poppr” package (version 2.9.3;
At the population level, we calculated the number of alleles per locus (Na), number of effective alleles (Ne), Shannon’s index (I), and observed and expected heterozygosity (HO and HE, respectively). To account for different sample numbers among populations, a rarefaction correction based on the smallest sample size (i.e., population CA8 with seven samples; Table
To investigate the genetic structure among sampled populations, we performed Bayesian assignment tests, as implemented in STRUCTURE (version 2.3.4;
Aiming to explore whether diagnostic morphological characters could help managers and other stakeholders identify invasive Carpobrotus species, we collected data on several morphological characteristics of 10 randomly chosen ramets per sampled population, many of which have been used by previous authors (
Morphological characteristics of Carpobrotus species measured in this study (see text for details).
We then built a regression tree using morphological characteristics as predictors and the genetic cluster to which each population was allocated as the response variable. We excluded those populations with admixed ancestry (Table
The datasets generated during and/or analyzed during the current study are available in https://doi.org/10.5281/zenodo.8123272.
We found no evidence of scoring errors due to band stuttering in our genotype dataset. All six loci were polymorphic in the overall dataset and the number of alleles per locus ranged between two and nine.
Samples from Cape Point had a high incidence of missing data and were removed from subsequent analyses. This population likely represents a species that is distantly related to all other species we sampled in our study (average pairwise population FST = 0.7). For the remaining populations, we found the association index of alleles at different loci to be lower than expected in all populations, indicating the presence of linkage disequilibrium (r̅d = 0.013; p > 0.001; Suppl. material
In all populations, Na was low (range 1.4–3.00). Observed heterozygosity was slightly higher (range 0.225–0.648) than HE (range 0.131–0.444; Fig.
Genetic diversity metrics of native and non-native populations of Carpobrotus species. Colours indicate the cluster to which each population has been assigned (See Table
Bar plots showing the genetic structure of the A native South African and B non-South African populations of Carpobrotus species included in this study. Note that both plots represent the same analysis and were split into two panes for better visualization. The delta K method following
Population pairwise FST estimates (excluding population ZA8 from Cape Point) ranged from low (FST = 0.015; between populations ZA1 and ZA2) to high (FST = 0.6; between populations ZA5 and ZA10) (Suppl. material
Geographical distribution of the populations of Carpobrotus species sampled in this study (see Table
Principal coordinates analysis for the populations of Carpobrotus species included in this study. The analysis was based on genetic distances (following
We found no clear link between morphological characteristics and the identified genetic clusters of Carpobrotus plants sampled in our study (Figs
Classification tree analysis of the Carpobrotus genetic clusters based on morphological characteristics. The most significant characteristic is indicated at each node, with the corresponding values relating to branches on the left. Morphological differences between genetic clusters could be best explained by the color of the filaments of the stamens (Stamen_c), the flower diameter (Flower_d), the position of the calyx globes (CG), the ovary surface (Ovary), the leaf cross section area (Triangle), the leaf length (Leaf_len) and the diameter of the stamen ring (SR). Leaf_len, Flower_d and SR are indicated in cm. Colours of circles at the end of branches correspond to the genetic clusters. n = number of individuals assigned to each cluster. See Fig.
Our results confirm the complex identification, biosystematics and biogeography of the invasive Carpobrotus spp. The west coast of South Africa, and possibly California, were identified as the most likely sources of invasive populations worldwide.
The Bayesian assignment analysis grouped the sampled populations into three genetic clusters (clusters A, B and C; Fig.
Only one South African population, consisting of a single genotype, was assigned to cluster B (shared by some populations from southern Europe and California; Table
Outside South Africa and California, all sampled populations were assigned to either cluster A or B, or were identified as admixed. These findings suggest that the Western Cape province of South Africa and coastal California may have served as the sources for many introduced Carpobrotus populations in the rest of the world. This is not surprising, given that Carpobrotus species have been widely introduced as ornamental plants (
The Italian and Argentinian populations included in our analyses were not clearly assigned to particular genetic clusters, suggesting that genetically distinct groups or species of Carpobrotus were introduced to these areas from different sources, leading to extensive admixture (
Overall, our results indicate that there have been multiple introductions of Carpobrotus species from different sources globally. Typically, multiple introductions increase the genetic diversity and probability of success of invasive species (
Accurate identification of invasive Carpobrotus species or hybrid combinations could improve risk assessment and guide early detection and rapid response management actions (
However, identifying invasive Carpobrotus species is challenging. Several diagnostic morphological characters have been proposed to differentiate between species, with petal colour being the most popular one (
Despite the challenges related to the morphological identification of invasive Carpobrotus species using morphological characters, our results have important implications for the development of management programmes. First, no introductions of individuals from cluster C have been detected in any of the sampled sites. However, the rate of introduction of alien species is rapidly increasing (
Our work highlights exciting opportunities for future research on Carpobrotus invasions. For example, high-resolution population genomic analyses (e.g., single nucleotide polymorphism genotyping or whole genome sequencing), coupled with common garden experiments, would provide valuable insights into the diversity and evolutionary dynamics of the genus, the invasiveness of its representatives and their interactions with insects with the potential to be used for biological control. For instance, a highly flexible breeding system that allows extensive hybridization (i.e., outcrossing) and high levels of clonal reproduction (via vegetative structures) suggest the stabilization of highly successful hybrid genotypes is likely to occur. Determining whether certain hybrid combinations and/or clones are more prevalent in native or invasive ranges should be included in future research to inform future management of the group.
AN, MLC, SC, JR and JJLR acknowledge funding by project no. 19-13142S, and PP by EXPRO grant no. 19-28807X (both from Czech Science Foundation). SC was supported by the Irish Research Council COALESCE/2021/117 award. JR acknowledges funding from the Spanish Ministry of Universities under application 33.50.460A.752 and the European Union NextGenerationEU/PRTR through a contract Margarita Salas of the Universidade de Vigo (UP2021-046). AN, MLC, SC, JR, DMR and PP were supported by a long-term research development project no. RVO 67985939 (Czech Academy of Sciences). DMR also received support from Mobility 2020 project no. CZ.02.2.69/0.0/0.0/ 18_053/0017850 (Ministry of Education, Youth and Sports of the Czech Republic). CMD thanks L. Lum for access to federal govt land for plant collections in California.
Pairwise estimates of genetic differentiation based on microsatellite data (FST)
Data type: xlsx
Explanation note: Pairwise estimates of genetic differentiation based on microsatellite data (FST) for all populations included in this study. Note that ‘population ID’ refers to the same IDs provided in Table
Testing for linked disequilibrium on 681 samples of Carpobrotus species
Data type: pdf
Explanation note: The blue line (r̅d) indicates the expected index of association of alleles at different loci that is independent of sample size. A distribution below r̅d indicates linkage disequilibrium and evidence for clonal reproduction.