Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T12:19:00.207Z Has data issue: false hasContentIssue false

Genetic diversity of Didelphis virginiana related to different levels of disturbance in the Highlands and the Central Depression regions of Chiapas, Mexico

Published online by Cambridge University Press:  15 March 2016

Bárbara Cruz-Salazar*
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
Lorena Ruiz-Montoya
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
Ella Vázquez-Domínguez
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
Darío Navarrete-Gutiérrez
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
Eduardo E. Espinoza-Medinilla
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
Luis-Bernardo Vázquez
Affiliation:
El Colegio de La Frontera Sur, Carretera Panamericana s/n. Barrio de María Auxiliadora. San Cristóbal de Las Casas, Chiapas, México, C. P. 29200
*
1Corresponding author. Email: bcruz@ecosur.edu.mx

Abstract:

The Virginia opossum (Didelphis virginiana) is considered highly adaptable to anthropogenic disturbances; however, the genetic effects of disturbance on this marsupial have not been studied in wild populations in Mexico. Here we evaluated the genetic diversity of D. virginiana at sites with different levels of disturbance within the Highlands and Central Depression regions of Chiapas in southern Mexico. Twelve microsatellite loci were used and the results demonstrated moderate mean heterozygosity (He = 0.60; Ho = 0.50). No significant differences in heterozygosity were found among sites with different levels of disturbance in both regions (range Ho = 0.42–0.57). We observed low but significant levels of genetic differentiation according to disturbance level. The inbreeding coefficient did not differ significantly from zero, suggesting that low genetic differentiation in these environments may be associated with sufficient random mating and gene flow, a result associated with the high dispersal and tolerance characteristics of this marsupial. Our results for D. virginiana in this particular area of Mexico provide a foundation for exploring the impact of human disturbance on the genetic diversity of a common and generalist species.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

LITERATURE CITED

AGUIRRE-PLANTER, E. G., FURNIER, R. & EGUIARTE, L. E. 2000. Low levels of genetic variation within and high levels of genetic differentiation among populations of species of Abies from southern Mexico and Guatemala. American Journal of Botany 87:362371.Google Scholar
BEASLEY, J. C., BEATTY, W. S., OLSON, Z. H. & RHODES, O. E. 2010. A genetic analysis of the Virginia opossum mating system: evidence of multiple paternity in a highly fragmented landscape. Journal of Heredity 101:368373.Google Scholar
BEATTY, W. S., BEASLEY, J. C., DHARMARAJAN, G. & RHODES, O. E. 2012. A genetic structure of a Virginia opossum (Didelphis virginiana) population inhabiting a fragmented agricultural ecosystem. Canadian Journal of Zoology 90:101109.Google Scholar
BEATTY, W. A., BEASLEY, J. C. & RHODES, O. E. 2014. Habitat selection by a generalist mesopredator near its historical range boundary. Canadian Journal of Zoology 92:4148.Google Scholar
BEGON, M., TOWNSEND, C. R. & HARPER, J. L. 2006. Ecology: from individuals to ecosystems. Blackwell, Oxford. 738 pp.Google Scholar
BONNET, E. & VAN DE PEER, Y. 2002. ZT: A software tool for simple and partial Mantel test. Statistical Software 7:112.Google Scholar
BOZEK, C. K., PRANGE, S. & GEHRT, S. D. 2007. The influence of anthropogenic resources on multi-scale habitat selection by raccoons. Urban Ecosystems 10:413425.Google Scholar
BREEDLOVE, D. E. 1973. The phytogeography and vegetation of Chiapas (Mexico). Pp. 149165 in Graham, A. (ed.). Vegetation and vegetational history of northern Latin America. Elsevier, Amsterdam.Google Scholar
CABELLO, D. R. 2006. Reproduction of Didelphis marsupialis (Didelphimorphia: Didelphidae) in the Venezuelan Andes. Acta Theriologica 51:427433.Google Scholar
CAVALLI-SFORZA, L. L. & EDWARDS, A. W. F. 1967. Phylogenetic analysis: models and estimation procedures. American Journal of Human Genetics 19:233257.Google Scholar
CEBALLOS, G. & OLIVA, G. 2005. Los mamíferos silvestres de México. Conabio/FCE, México. 986 pp.Google Scholar
CHAKRABORTY, R., DE ANDRADE, M., DAIGER, S. P. & BUDOWLE, B. 1992. Apparent heterozygote deficiencies observed in DNA typing data and their implications in forensic applications. Annals of Human Genetics 56:4557.Google Scholar
CHAPUIS, M.-P. & ESTOUP, A. 2007. Microsatellite null alleles and estimation of population differentiation. Molecular Biology and Evolution 24:621631.Google Scholar
CHIAPPERO, M. B., PANZETTA-DUTARI, G. M., GÓMEZ, D., CASTILLO, E., POLOP, J. J. & GARDENAL, C. N. 2011. Contrasting genetic structure of urban and rural populations of the wild rodent Calomys musculinus (Cricetidae, Sigmodontinae). Mammalian Biology 76:4150.Google Scholar
CRUZ-SALAZAR, B., RUIZ-MONTOYA, L., NAVARRETE-GUTIÉRREZ, D., ESPINOZA-MEDINILLA, E., VÁZQUEZ-DOMÍNGUEZ, E. & VÁZQUEZ, L.-B. 2014. Diversidad genética y abundancia relativa de Didelphis marsupialis y Didelphis virginiana en Chiapas, México. Revista Mexicana de Biodiversidad 85:251261.Google Scholar
DIAS, I. M. G., AMATO, G., CUNHA, H. M., DESALLE, R., PAGLIA, A. P., PETERSON, J. K. & FONSECA, C. G. 2009. Isolation, characterization and cross-species amplification of new microsatellite markers for three opossum species of the Didelphidae family. Conservation Genetics Resources 1:405410.Google Scholar
ECKERT, A. J., ECKERT, M. L. & HALL, B. D. 2010. Effects of historical demography and ecological context on spatial patterns of genetic diversity within foxtail pine (Pinus balfouriana; Pinaceae) stands located in the Klamath Mountains, California. American Journal of Botany 97:650659.Google Scholar
EVANNO, G., REGNAUT, S. & GOUDET, J. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14:26112620.Google Scholar
EXCOFFIER, L. & LISCHER, H. E. L. 2010. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology and Resources 10:564567.Google Scholar
EXCOFFIER, L., SMOUSE, P. E. & QUATTRO, J. M. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 135: 479491.Google Scholar
FALUSH, D., STEPHENS, M. & PRITCHARD, J. K. 2003. Inference of population structure: extensions to linked loci and correlated allele frequencies. Genetics 164:15671587.Google Scholar
FIKE, J. A., BEASLEY, J. C. & RHODES, O. E. 2009. Isolation of 21 polymorphic microsatellite markers for the Virginia opossum (Didelphis virginiana). Molecular Ecology Resources 9:12001202.Google Scholar
FRANKHAM, R. J., BALLOU, D. & BRISCOE, D. A. 2002. Introduction to conservation genetics. Cambridge University Press, Cambridge. 618 pp.Google Scholar
GANNON, W. L., SIKERS, R. S. & THE ANIMAL CARE AND USE COMMITTEE OF THE AMERICAN SOCIETY OF MAMMALOGISTS. 2007. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. Journal of Mammalogy 88:804823.Google Scholar
GARCÍA, E. 1973. Modificaciones al sistema de clasificación climática de Köppen (para adaptarlo a las condiciones de la República Mexicana). Instituto de Geografía, Universidad Nacional Autónoma de México, Dirección General de Publicaciones, Mexico. 246 pp.Google Scholar
GONZÁLEZ-ESPINOSA, M., RAMÍREZ-MARCIAL, N., MÉNDEZ-DEWAR, G., GALINDO-JAIMES, L. & GOLICHER, D. 2005. Riqueza de especies de árboles en Chiapas: variación espacial y dimensiones ambientales asociadas al nivel regional. Pp. 81125 in González-Espinosa, M., Ramírez-Marcial, N. & Ruiz-Montoya, L. (eds.). Diversidad biológica en Chiapas. ECOSUR, COCyTECH, Plaza y Valdez Editores, México.Google Scholar
HAMILTON, M., PINCUS, E., DI FIORE, A. & FLEISCHER, R. C. 1999. Universal linker and ligation procedures for construction of genomic DNA libraries enriched for microsatellites. Biotechniques 27:500507.Google Scholar
HAMRICK, J. L. & MURAWSKI, D. A. 1990. The breeding structure of tropical tree populations. Plant Species Biology 5:157166.Google Scholar
HEDRICK, P. W. 2000. Genetics of populations. Jones and Bartlett Publishers, Boston. 553 pp.Google Scholar
HENNESSY, C., TSAI, C.-C., BEASLEY, J. C., BEATTY, W. S., ZOLLNER, P. A. & RHODES, O. E. 2015. Elucidation of population connectivity in synanthropic mesopredators: using genes to define relevant spatial scales for management of raccoons and Virginia opossums. Journal of Wildlife Management 79:112121.Google Scholar
HUTCHISON, D. W. & TEMPLETON, A. R. 1999. Correlation of pairwise genetic and geographic distance measures: inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evolution 53:18981914.Google Scholar
JACKSON, N. D. & FAHRIG, L. 2014. Landscape context affects genetic diversity at a much larger spatial extent than population abundance. Ecology 95:871881.Google Scholar
JANSA, S. A. & VOSS, R. S. 2000. Phylogenetic studies on didelphid marsupials I. Introduction and preliminary results from nuclear IRBP gene sequences. Journal of Mammalian Evolution 7:4377.Google Scholar
JIN, Y., TIANHUA, H. & BAO-RONG, L. 2003. Fine scale genetic structure in a wild soybean (Glycine soja) population and the implications for conservation. New Phytologist 159:513519.Google Scholar
KANDA, L. L., FULLER, T. K., SIEVERT, P. R. & KELLOGG, R. 2009. Seasonal source-sink dynamics at the edge of species’ range. Ecology 90:15741585.Google Scholar
KEYGHOBADI, N. 2007. The genetic implications of habitat fragmentation for animals. Canadian Journal of Zoology 85:10491064.Google Scholar
LAMBERT, T. D., MALCOLM, J. R. & ZIMMERMAN, B. L. 2005. Variation in small mammal species richness by trap height and trap type in south-eastern Amazonia. Journal of Mammalogy 86:982990.Google Scholar
LAVERGNE, A., DOUADY, C. & CATZEFLIS, D. M. 1998. Isolation and characterization of microsatellite loci in Didelphis marsupialis (Marsupialia: Didelphidae). Molecular Ecology 8:517518.Google Scholar
LOVELESS, M. D. 1992. Isozyme variation in tropical trees: patterns of genetic organization. New Forests 6:6794.Google Scholar
MARKOVCHICK-NICHOLLS, L., REGAN, H. M., DEUTSCHMAN, D. H., WIDYANATA, A., MARTIN, B., NOREKE, L. & HUNT, T. A. 2007. Relationships between human disturbance and wildlife land use in urban habitat fragments. Conservation Biology 22:99109.Google Scholar
OLIVIERI, G. L., SOUSA, V., CHIKHI, L. & RADESPIEL, U. 2008. From genetic diversity and structure to conservation: genetic signature of recent population declines in three mouse lemur species (Microcebus spp.). Biological Conservation 141:12571271.Google Scholar
ORJUELA, C. O. J. & JIMÉNEZ, G. 2004. Estudio de la abundancia relativa para mamíferos en diferentes tipos de coberturas y carretera, finca hacienda cristales, área Cerritos–La Virginia, municipio de Pereira. Universitas Scientiarum 9:8796.Google Scholar
PEAKALL, R. & SMOUSE, P. E. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6:288295.Google Scholar
PRITCHARD, J. K., STEPHENS, M. & DONNELLY, P. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945959.Google Scholar
RAMÍREZ-MARCIAL, N., GONZÁLEZ-ESPINOSA, M. & WILLIAMS-LINERA, D. 2001. Anthropogenic disturbance and tree diversity in montane rain forests in Chiapas, México. Forest Ecology and Management 154:311326.Google Scholar
RAMÍREZ-PULIDO, J., ARROYO-CABRALES, J. & CASTRO-CAMPILLO, A. 2005. Estado actual y relación nomenclatural de los mamíferos terrestres de México. Acta Zoológica Mexicana (n.s.) 21:2182.Google Scholar
ROCHA-LOREDO, A. G., RAMÍREZ-MARCIAL, N. & GONZÁLEZ-ESPINOSA, M. 2010. Riqueza y diversidad de árboles del bosque tropical caducifolio en la Depresión Central de Chiapas. Boletín de la Sociedad Botánica de México 87:89103.Google Scholar
SOKAL, R. R. & ROHLF, F. J. 2003. Biometry. The principles and practice of statistics in biological research. W. H. Freeman and Company, New York. 880 pp.Google Scholar
STEINER, C. & CATZEFLIS, F. M. 2004. Genetic variation and geographical structure of five mouse-sized opossum (Marsupialia, Didelphidae) throughout the Guiana Region. Journal of Biogeography 31:959973.Google Scholar
STORZ, J. F. & BEAUMONT, M. A. 2002. Testing for genetic evidence of population expansion and contraction: an empirical analysis of microsatellite DNA variation using a hierarchical Bayesian model. Evolution 56:154166.Google Scholar
VAN OOSTERHOUT, C., HUTCHINSON, W. F., WILLIS, D. P. M. & SHIPLEY, P. 2004. Micro-checker: software for identifying and correcting genotyping error in microsatellite data. Molecular Ecology Notes 4:535538.Google Scholar
WRIGHT, J. F., BURT, M. S. & JACKSON, V. L. 2012. Influences of an urban environment on home range and body mass of Virginia opossums (Didelphis virginiana). Northeastern Naturalist 19:7786.Google Scholar