Molecular, quantitative and abiotic variables for the delineation of evolutionary significant units: case of sandalwood (Santalum austrocaledonicum Vieillard) in New Caledonia
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Various approaches have been developed to define conservation units for plant and animal species. In this study we combined nuclear microsatellites (from a previous published study) and chloroplast microsatellites (assessed in the present study), leaf and seed morphology traits and abiotic variables (climate and soil) to define evolutionary significant units (ESU) of Santalum austrocaledonicum, a tree species growing in New Caledonia. Results for chloroplast microsatellites showed that the total population heterozygosity was␣high, (H cp = 0.84) but varied between islands. Differentiation was strong in the total population (F stcp = 0.66) but also within the main island Grande Terre (F stcp = 0.73) and within Iles Loyauté (F stcp = 0.52), highlighting a limited gene flow between populations. These results confirmed those obtained with nuclear microsatellites. The cluster analysis on molecular markers discriminated two main groups constituted by the populations of Grande Terre and the populations of Iles Loyauté. A principal component analysis of leaf and seed morphology traits singled out the populations of Iles Loyauté and the western populations of Grande Terre. Quantitative genetic analyses showed that the variation between populations was under genetic control (broad sense heritability close to 80%). A high correlation between rainfall and morphological traits suggested an impact of climate on this variation. The integration of these results allows to define two ESUs, one corresponding to Grande Terre and Ile des Pins and the other the Iles Loyauté archipelago. This study stresses the need to restore some populations of Grande Terre that are currently threatened by their small size.
KeywordsSantalum austrocaledonicum Nuclear microsatellites Chloroplastic microsatellites Morphological traits Evolutionary significant units
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These results are part of Lorraine Bottin 9s PhD thesis on the analysis of genetic diversity of Santalum austrocaledonicum. This study was supported by the sandalwood project funded by the MEDD, the French Ministry of Ecology and Sustainable Development. The laboratory work and analyses were done in the Forest Department of Cirad in Montpellier, France, where J.M. Bouvet is the head of the “Forest Genetics” research unit. We would like to thank Alexandre Vaillant for laboratory work, and Alexandre Lagrange and Géraldine Derroire for field work in New Caledonia. Many thanks go to IAC (Institut Agronomique néo-Calédonien) and to the Development Services of the Provinces of Islands, North and South which facilitated the field operation.
- Addinsoft (2005) XLSTAT software version 7.5.2 http://www.xlstat.comGoogle Scholar
- Andrianoelina O, Rakotondraoelina H, Ramamonjisoa L et al. (2006) Genetic diversity of Dalbergia monticola (Fabaceae), an endangered tree species in the fragmented oriental forest of Madagascar. Biodivers Conserv DOI 10.1007/s10531-004-2178-6Google Scholar
- Barrett SCH (1998) The reproductive biology and genetics of island plants. In: Grant PR (ed) Evolution on islands. Oxford University Press, Oxford UK, pp 18–34Google Scholar
- Carlquist S (1980) Hawaï: a natural history. geology, climate, native flora and fauna above the shoreline, 2nd edn. Pacific Tropical Botanical Garden, Lawa 9i Hawa 9iGoogle Scholar
- Ennos RA (1994) Estimating the relative rates of pollen and seed migration among plant populations. Heredity 72:250–259Google Scholar
- Falconer DS, Mckay TFC (1996) Introduction to quantitative genetics. Longman Sci and Tech, Harlow United KingdomGoogle Scholar
- Gibbs D, Barnes E, Cox J (2001) Pigeons and doves. A guide to the pigeons and doves of the world. Pica press, SussexGoogle Scholar
- Nei M (1978) Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583–590Google Scholar
- ORSTOM (1981), Atlas de Nouvelle Calédonie et DépendancesGoogle Scholar
- Perrier X, Flori A, Bonnot F (2003). Data analysis methods. In: Hamon P, Seguin M, Perrier X, Glaszmann JC (eds) Genetic diversity of cultivated tropical plants. Enfield Science Publishers, Montpellier, pp 43–76Google Scholar
- Pizo MA, Von Allmen C, Morellato LPC (2006) Seed size variation in the palm Euterpe edulis and of seed predators on germination and seedling survival. Acta Oecologia (in press) doi:10.1016/j.actao.2005.11.011Google Scholar
- Raymond M, Rousset F (1995) GENEPOP (Version 3.2a): population genetics software for exact tests and ecumenism. J Heredity 86:248–249Google Scholar
- Sanou H, Picard N, Lovett PN, Dembélé M, Korbo A, Diarisso D, Bouvet JM (2006) Phenotypic variation of agromorphological traits of the shea tree, Vitellaria paradoxa C.F Gaertn, in Mali. Genet. Resour Crop Evol 53:145–161 DOI 10.1007/s10722-004-1809-9Google Scholar
- SAS Institute Inc (1990) SAS/STAT user 9s guide, release 6.03 edn. SAS Institute Inc., Gary N.CGoogle Scholar
- Schneider S, Roessli D, Excoffier L (2000) Arlequin: a software for population genetics data analysis. User manual ver 2.0. Genetics and Biometry Lab, Dept. Anthropology, University of Geneva. 11 pages. Free program distributed by the authors over internet from lgb.unige.ch/arlequin/Google Scholar
- Shineberg D (1967) They came for sandalwood. Melbourne University PressGoogle Scholar
- Silvertown J (1989). The paradox of seed size and adaptation. Trends Ecol Evol 4:24–26Google Scholar
- Wright S (1951) The genetical studies of population. Ann Eugen 15:328–354Google Scholar