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Effect of Hurricane Karl on a plant–ant network occurring in coastal Veracruz, Mexico

Published online by Cambridge University Press:  22 November 2012

Ingrid R. Sánchez-Galván
Affiliation:
Instituto de Ecología, A.C. Apdo. 63, Xalapa, Veracruz 91070, México Present address: CIBIO, Universidad de Alicante, San Vicente del Raspeig (Alicante), 03080, Spain
Cecilia Díaz-Castelazo
Affiliation:
Instituto de Ecología, A.C. Apdo. 63, Xalapa, Veracruz 91070, México
Víctor Rico-Gray*
Affiliation:
Instituto de Ecología, A.C. Apdo. 63, Xalapa, Veracruz 91070, México
*
2Corresponding author. Present address: Instituto de Neuroetología, Universidad Veracruzana, Xalapa, Veracruz 91190, Mexico. Email: [email protected], [email protected]

Abstract:

We analysed the effect of a hurricane on a plant–ant network and on vegetation cover. Plant cover was sampled using linear sampling in several vegetation types: deciduous forest, a dry forest, sand dune pioneers, sand dune scrub, ecotone of freshwater marsh, deciduous forest and dune scrub, and mangrove forest. We sampled ant–plant interactions and vegetation cover before and after Hurricane Karl hitting (September 2010) the central coast of the state of Veracruz, Mexico. The pre-hurricane network consisted of 16 plant and 25 ant species in 52 associations. The post-hurricane network consisted of 17 plant and 20 ant species in 56 associations. We found a significant decrease in the total linear cover of EFN-bearing plants between October 2009 (646 m, no hurricane effect) and October 2010 (393 m, after hurricane Karl) (total sample length 2025 m). Both networks were significantly nested (0.999 and 0.973, P < 0.001), suggesting that network topology remained similar. Our results show changes in several network characteristics and species proportions. The number of plant species that contributed to nestedness vs. idiosyncratic species did not differ significantly in the pre-hurricane network, while the number of plant species that contributed to nestedness vs. idiosyncratic species did differ significantly in the post-hurricane network. The number of ant species that contributed to nestedness vs. idiosyncratic species differed significantly in the pre-hurricane network, and also in the post-hurricane network. Differences in nestedness contributions of species before and after the hurricane reflect an alteration from a generalized, highly nested, more stable pre-disturbance network, to a more low-degree or specialized network (i.e. fewer interactions among generalist species, those species with the most associations). The maintenance of important core components of the network after a huge disturbance, suggests a short-term resilience typical of mutualistic networks.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2012

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References

LITERATURE CITED

ALMEIDA-NETO, M., GUIMARÃES, P., GUIMARÃES, P. R., LOYOLA, R. D. & ULRICH, W. 2008. A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement. Oikos 117:12271239.CrossRefGoogle Scholar
ATMAR, W. & PATTERSON, B. D. 1993. The measure of order and disorder in the distribution of species in fragmented habitat. Oecologia 96:373382.CrossRefGoogle ScholarPubMed
BASCOMPTE, J. & JORDANO, P. 2007. Plant–animal mutualistic networks: the architecture of biodiversity. Annual Review of Ecology, Evolution and Systematics 38:567593.CrossRefGoogle Scholar
BASCOMPTE, J., JORDANO, P., MELIÁN, C. J. & OLESEN, J. M. 2003. The nested assembly of plant–animal mutualistic networks. Proceedings of the National Academy of Sciences, USA 100:93839387.CrossRefGoogle ScholarPubMed
BOLTON, B. & ALPERT, G. 2006. Bolton's catalogue of ants of the World 1758–2005. Harvard University Press, Harvard. CD-ROM.Google Scholar
BORGATTI, S. P. & EVERETT, M. G. 1999. Models of core/periphery structures. Social Networks 21:375395.CrossRefGoogle Scholar
CODER, K. D. 2006. Hurricanes, trees, and forests. A selected bibliography. Warnell School of Forestry and Natural Resources Publication FOR06-2. University of Georgia, Athens. 4 pp.Google Scholar
DE NOOY, W., MRVAR, A. & BATAGELJ, V. 2005. Exploratory social network analysis with Pajek. Cambridge University Press, New York. 334 pp.CrossRefGoogle Scholar
DÍAZ-CASTELAZO, C., RICO-GRAY, V., OLIVEIRA, P. S. & CUAUTLE, M. 2004. Extrafloral nectary-mediated ant–plant interactions in the coastal vegetation of Veracruz, México: richness, occurrence, seasonality and ant foraging patterns. Ecoscience 11:472481.CrossRefGoogle Scholar
DÍAZ-CASTELAZO, C., GUIMARÃES, P. R., JORDANO, P., THOMPSON, J. N., MARQUIS, R. J. & RICO-GRAY, V. 2010. Changes of a mutualistic network over time: reanalysis over a 10-year period. Ecology 91:793801.CrossRefGoogle ScholarPubMed
FLYNN, D. F. B., URIARTE, M., CRK, T., PASCARELLA, J. B., ZIMMERMANN, J. K., AIDE, T. M. & CARABALLO ORTIZ, M. A. 2010. Hurricane disturbance alters secondary forest recovery in Puerto Rico. Biotropica 42:149157.CrossRefGoogle Scholar
GUIMARÃES, P. R. & GUIMARÃES, P. 2006. Improving the analyses of nestedness for large sets of matrices. Environmental Modelling Software 21:15121513.CrossRefGoogle Scholar
INGS, T. C., MONTOYA, J. M., BASCOMPTE, J., BLÜTHGEN, N., BROWN, L., DORMANN, C. F., EDWARDS, F., FIGUEROA, D., JACOB, J., JONES, J. I., LAURIDSEN, R. B., LEDGER, M. E., LEWIS, H. M., OLESEN, J. M., FRANK VAN VEEN, F. J., WARREN, P. H. & WOODWARD, G. 2009. Ecological networks – beyond food webs. Journal of Animal Ecology 78:253269.CrossRefGoogle ScholarPubMed
KUNTE, K. 2008. Competition and species diversity: removal of dominant species increases diversity in Costa Rican butterfly communities. Oikos 117:6976.CrossRefGoogle Scholar
KUPFER, J. A., MYERS, A. T., MCLANE, S. E. & MELTON, G. N. 2008. Patterns of forest damage in a southern Mississippi landscape caused by hurricane Katrina. Ecosystems 11:4560.CrossRefGoogle Scholar
LONGINO, J. T. 2010. Ants of Costa Rica. The Evergreen State College, Olympia. http://academic.evergreen.edu/projects/ants/AntsofCostaRica.html.Google Scholar
MENGES, E. S., WEEKLEY, C. W., CLARKE, G. L. & SMITH, S. A. 2011. Effects of hurricanes on rare plant demography in fire-controlled ecosystems. Biotropica 43:450458.CrossRefGoogle Scholar
MORENO-CASASOLA, P. (ed.). 2006. Entornos veracruzanos: la costa de La Mancha. Instituto de Ecología, A.C., Xalapa. 574 pp.Google Scholar
MORRISON, L. W. 2002. Island biogeography and metapopulation dynamics of Bahamian ants. Journal of Biogeography 29:387394.CrossRefGoogle Scholar
PEMBERTON, R. W. 1990. The occurrence of extrafloral nectaries in Korean plants. Korean Journal of Ecology 13:251266.Google Scholar
RICO-GRAY, V. 1993. Use of plant-derived food resources by ants in the dry tropical lowlands of coastal Veracruz, Mexico. Biotropica 25:301315.CrossRefGoogle Scholar
RICO-GRAY, V., DÍAZ-CASTELAZO, C., RAMÍREZ-HERNÁNDEZ, A., GUIMARÃES, P. R. & HOLLAND, J. N. 2012. Abiotic factors shape temporal variation in the structure of an ant–plant network. Arthropod–Plant Interactions 6:289295.CrossRefGoogle Scholar
ROSS, M. S., CARRINGTON, M., FLYNN, L. J. & RUIZ, P. L. 2001. Forest succession in tropical hardwood hammocks of the Florida keys: effects of direct mortality from hurricane Andrew. Biotropica 33:2333.CrossRefGoogle Scholar
SCHULTZ, T. R. & MCGLYNN, T. P. 2000. The interactions of ants with other organisms. Pp. 3544 in Agosti, D., Majer, J. D., Alonso, L. E. & Schultz, T. R. (eds). Ants: standard methods for measuring and monitoring biodiversity. Smithsonian Institution Press, Washington, DC. 280 pp.Google Scholar
TYLIANAKIS, J. M., LALIBERTÉ, E., NIELSEN, A. & BASCOMPTE, J. 2010. Conservation of species interaction networks. Biological Conservation 10:22702279.CrossRefGoogle Scholar
ZAR, J. H. 1999. Biostatistical analysis. Prentice Hall, New Jersey. 663 pp.Google Scholar