EX SITU CONSERVATION PRIORITIES FOR THE PERUVIAN WILD TOMATO SPECIES (Solanum L. SECT. Lycopersicum (MILL.) WETTST.)

Dioliza Vilchez, Diego A. Sotomayor, Cinthya Zorrilla

Resumen


Tomato (Solanum lycopersicum) is a crop of global importance that has center of origin in Peru, with 11 species of wild relatives (CWR) occurring in the country. These CWR contain genetic material that could be used to improve currently cultivated species, and that is usually stored ex situ in germplasm banks. Hence, assessing the representativeness of germplasm banks is important to strengthen genetic improvement of tomatoes as well as their resilience to globally changing conditions. Here, we used gap analysis methodology on the 11 species of tomato CWR occurring in Peru. This methodology consists in seven steps that consider representativeness in terms of herbaria/germplasm banks, geography and environments within the country, in order to establish conservation priorities. We also assessed conservation priorities for the Instituto Nacional de Innovación Agraria (INIA), which is the main ex situ conservation Institution in Peru. Nationally, we found one species with high priority for conservation: Solanum huaylasense, and for INIA we found six species with high conservation priority: S. huaylasense, S. neorickii, S. chmielewskii, S. corneliomulleri, S. arcanum and S. chilense. We also found that the gap analysis methodology allowed for a proper prioritization of species and be readily applied to other species. We conclude by recommending strategies to improve the genetic coverage of the tomato germplasm held at INIA, as well as by discussing priorities for in situ conservation of tomato CWRs.


Palabras clave


Gap analysis, agrobiodiversity, conservation priorities, crop wild relatives, Solanum.

Texto completo:

PDF

Referencias


Castañeda-Álvarez N.P., Khoury C.K., Achicanoy H.A., Bernau V., Dempewolf H., Eastwood R.J. & et al. 2015a. Global conservation priorities for crop wild relatives. Nature Plants,16022. DOI: 10.1038/NPLANTS.2016.22.

Castañeda-Álvarez N.P., de Haan S., Juárez H., Khoury C.K., Achicanoy H.A. & Sosa C.C. 2015b. Ex Situ Conservation Priorities for the Wild Relatives of Potato (Solanum L. Section Petota). PLoS ONE, 10(4): e0122599. DOI: 10.1371/journal.pone.0122599.

Cocaliadis M. 2012. Desarrollo y utilización de marcadores moleculares para el genotipado de la colección de líneas de introgresión de Solanum lycopersicoides en el fondo genético del tomate cultivado . Tesis Master en Mejora Genética Vegetal. Universidad Politécnica de Valencia. Valencia, España. URLs: http://hdl.handle.net/10251/27382; https://riunet.upv.es/bitstream/handle/10251/27382/Tesi s_de_Master_Flor_Cocaliadis.pdf?sequence=1.

Costa G.C., Nogueira C., Machado R.B. & Colli G.R. 2010. Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot. Biodiversity Conservation, 19: 883–899.

Debouck D.G. 2009. Cahiers de Phaséologie – Synonymie. International Center for Tropical Agriculture, CIAT. URI: https://hdl.handle.net/10568/83129.

Dempewolf H., Baute G., Anderson J., Kilian B., Smith C., & Guarino L. 2017. Past and future use of wild relatives in crop breeding. Crop Science, 57: 1070-1082.

Dormann C.F. 2006. Promising the future? Global change projections of species distributions. Basic Applied Ecology, 8: 387–397.

Elith J., Graham C.H., Anderson R.P., Dudik M. & Ferrier S. 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29(2): 129–151. DOI: https://doi.org/10.1111/j.2006.0906-7590.04596.x.

FAO (Food and Agriculture Organization of the United Nations). 1997. State of the World’s Plant Genetic Resources for Food and Agriculture. Rome, Italy. Available: http://apps3.fao.org/wiews/wiewspage.jsp?i_l=EN&show = SOW1.

GENESYS. 2018. The global gateway to genetic resources. In: GENESYS – Plant Genetic Resources database. URL: https://www.genesys-pgr.org/welcome.

Graham C., Elith J., Hijmans R.J., Guisan A. & Peterson A.T. 2008. The influence of spatial errors in species occurrence data used in distribution models. Journal of Applied Ecology, 45: 239–247.

Guralnick R.P., Wieczorek J., Beaman R. & Hijmans R.J.. 2006 The BioGeomancer: automated georeferencing to map the world´s biodiversity data. PLoS Biology, 4(11): e381.DOI:https://doi.org/10.1371/journal.pbio.0040381.

Hajjar R. & Hodgkin T. 2007. The use of wild relatives in crop improvement: A survey of developments over the last 20 years. Euphytica, 156: 10-13.

Harlan J.R. & de Wet J.M.J. 1971. Toward a Rational Classification of Cultivated Plants. Taxon, 20(4): 509– 517. DOI: 10.2307/1218252.

Hernandez P.A., Graham C.H., Master L.L. & Albert D.L. 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography, 29: 773–785. Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G. & Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25: 1965-1978.

Hijmans R.J. & Graham C. 2006. The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biology, 12(12): 2272–2281. DOI:https://doi.org/10.1111/j.1365-2486.2006.01256.x.

IPCC (Intergovernmental Panel on Climate Change). 2007. IPCC Fourth Assessment Report: Climate Change 2007. IPCC, Geneva.

Khoury C., Laliberte B. & Guarino L. 2010. Trends in ex situ conservation of plant genetic resources: a review of global crop and regional conservation strategies. Genetic Resources and Crop Evolution, 57(4): 625–639. DOI: 10.1007/s10722-010-9534-z.

Khoury C.K., Amariles D., Soto J.S., Diaz M.V., Sotelo S., Sosa C.C., Ramírez-Villegas J., Achicanoy H.A., Velásquez-Tibatá J., Guarino L., León B., Navarro- Racines C., Castañeda-Álvarez N.P., Dempewolf H., Wiersema J.H. & Jarvis A. 2019. Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets. Ecological Indicators, 98: 420-429. DOI: 10.1016/j.ecolind.2018.11.016.

Loiselle B.A., Jorgensen P.M., Consiglio T., Jimenez I. & Blake J.G. 2008. Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes? Journal of Biogeography, 35: 105–116.

Margules C.R. & Pressey R.L. 2000. Systematic conservation planning. Nature, 405: 243-253.

Maxted N. & Kell S. 2009. Establishment of a global network for the in situ conservation of crop wild relatives: status and needs. FAO Commission on Genetic Resources for Food and Agriculture. Rome, Italy.

Maxted N., Dulloo E., Ford-Lloyd B.V., Iriondo J.M. & Jarvis A. 2008. Gap analysis: a tool for complementary genetic conservation assessment. Diversity and Distributions, 14: 1018–1030.

Peralta I., Spooner D. & Knapp S. 2008. Taxonomy of Wild Tomatoes and their Relatives (Solanum sect. Lycopersicoides, sect. Juglandifolia, sect. Lycopersicon; Solanaceae). Book of The American Society of Plant Taxonomists.

Phillips S.J. 2008. Transferability, sample selection bias and background data in presence-only modeling: a response to Peterson, (2007). Ecography, 31: 272–278.

Phillips S.J., Anderson R.P. & Schapire R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190: 231–259.

Phillips S.J. & Dudik M. 2008. Modeling of Species Distributions with Maxent: New Extensions and Comprehensive Evaluation. Ecography, 31: 161–175.

Prescott-Allen C. & Prescott-Allen R. 1986. The First Resource: Wild Species in the North American Economy. Yale University, New Haven.

Ramírez-Villegas J., Khoury C., Jarvis A., Debouck D.G. & Guarino L. 2010. A Gap Analysis Methodology for Collecting Crop Genepools: A Case Study with Phaseolus Beans. PLoS ONE, 5: e13497. DOI: 10.1371/journal.pone.0013497.

Singh S.P. 2001. Broadening the Genetic Base of Common Bean Cultivars: A Review. Crop Science, 41: 1659-1675. Sotomayor D.A., Vilchez D. & Zorrilla C. 2019. Dataset on occurrences of Lycopersicum species from Peru. Figshare dataset: https://doi.org/10.6084/m9.figshare.9880073.v1.

Tanksley S.D. & McCouch S.R. 1997. Seed Banks and Molecular Maps: Unlocking Genetic Potential from the Wild. Science, 277: 1063–1066.

VanDerWal J., Shoo L.P., Graham C.H. & Williams S.E. 2009. Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know? Ecological Modeling, 220(4): 589–594. DOI: 10.1016/j.ecolmodel.2008.11.010.

Veloz S.D. 2009. Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models. Journal of Biogeography, 36(12): 2290–2299. DOI: https://doi.org/10.1111/j.1365-2699.2009.02174.x. Vincent H., Amri A., Castañeda-Álvarez N.P., Dempewolf H., Dulloo E., Guarino L., Hole D., Mba C., Toledo A. & Maxted N. 2019. Modeling of crop wild relative species identifies areas globally for in situ conservation.

Communications Biology, 2: 136. DOI:https://doi.org/10.1038/s42003-019-0372-z.

WorldClim. 2005. Bioclimatic variables. In: WorldClim - Global Climate Data; Free climate data for ecological modeling and GIS. URL: http://www.worldclim.org/bioclim.




DOI: http://dx.doi.org/10.21704/rea.v18i2.1335

Enlaces refback

  • No hay ningún enlace refback.


 width=

 La revista Ecología Aplicada de la Universidad Nacional Agraria La Molina está licenciada bajo una Licencia Internacional Creative Commons Atribución-NoComercial 4.0.                   

Revista Ecología Aplicada
Universidad Nacional Agraria La Molina 
Teléfonos (51-1)-614-7800 anexos 271 - 294 
E-mail: ecolapl@lamolina.edu.pe