Effect of cell size and thresholds in NDM/NVDM methods on recognizing areas of endemism

Author:

SANTIAGO-ALVARADO MARGARITAORCID,LUNA-VEGA ISOLDAORCID,RIVAS GERARDOORCID,ESPINOSA DAVIDORCID

Abstract

Identifying areas of endemism has represented a great challenge, from the search for their definition, the design of methodologies, and the management of essential information to identify areas where the distributions of at least two taxa overlap. Endemicity Analysis is a widely used method that offers good results; however, an evaluation of the results is necessary. We evaluated the previous establishment of the minimum endemicity index of the species as a criterion to identify areas of endemism, applicated to a set of taxa with endemic and preferential distribution to the Sierra Madre Oriental. The taxa included in our analyses were 178 species of plants, vertebrates, and invertebrates. First, we varied the parameter set minimum score species in the software and the size of the cell. Next, we established criteria to evaluate the results obtained: areas supported by unique sets of species, good fit to the area, and sympatric distribution of taxa (extensive or homopatrid). After choosing the minimum ei with the best performance, we modified the study method for the endemicity analysis (Endemicity Analysis with Progressive Species Elimination). Our results indicate that the variation of the ei influenced the number of areas obtained by the program, decreasing considerably after evaluating the first criterion. The best fit to the cells occurred when we set 0.8 as the minimum ei in both cell sizes. The visually-preview of the sympatrid relationships allowed to recognize areas that do not present congruent distributions, although they meet the two previous criteria evaluated. The areas of endemism identified at different scales and those identified with the implementation of our modification were complementary.  

Publisher

Magnolia Press

Subject

Animal Science and Zoology,Ecology, Evolution, Behavior and Systematics

Reference2 articles.

1.

Aagesen, L., Szumik, C. & Goloboff, P. (2013) Consensus in the search for areas of endemism. Journal of Biogeography, 40, 2011–2016. https://doi.org/10.1111/jbi.12172
Alvez-Valles, C.M., Balslev, H., Carvalho, F.A., Garcia-Villacorta R., Grandez, C. & Neto, L.M. (2018) Endemism and conservation of Amazon palms. Biodiversity and Conservation, 27, 765–784. https://doi.org/10.1007/s10531-017-1463-0
Brown, J. H. & Lomolino, M.V. (1998) Biogeography. 2nd Edition, Sinauer Associates Inc., Sunderland, Massachusetts, 691 pp.
Carine, M.A., Humphries, C.J., Guma, I.R., Reyes-Betancort, J.A. & Santos-Guerra, A. (2009) Areas and algorithms: evaluating numerical approaches for the delimitation of areas of endemism in the Canary Islands archipelago. Journal of Biogeography, 36, 593–611. https://doi.org/10.1111/j.1365-2699.2008.02016.x
Casagranda, M.D, Roig-Juñent, S. & Szumik, C. (2009a) Endemismo a diferentes escalas espaciales: un ejemplo con Carabidae (Coleoptera: Insecta) de América del Sur austral. Revista Chilena de Historia Natural, 82, 17–42. https://doi.org/10.4067/S0716-078X2009000100002 
Casagranda, M.D., Arias, J.S., Goloboff, P.A., Szumik, C.A., Taher, L.M., Escalante, T. & Morrone, J.J. (2009b) Proximity, interpenetration, and sympatry networks: a reply to Dos Santos et al. Systematic Biology, 58, 271–276. https://doi.org/10.1093/sysbio/syp022
CONABIO (2021) Sistema Nacional de Información sobre Biodiversidad. Registros de ejemplares. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad. Mexico City. [unknown pagination]
Crother, B.I. & Murray, C.M. (2011) Ontology of areas of endemism. Journal of Biogeography, 38 (6), 1009–1015. https://doi.org/10.1111/j.1365-2699.2011.02483.x
Escalante, T. (2009) Un ensayo sobre regionalización biogeográfica. Revista Mexicana de Biodiversidad, 80, 551–560. https://doi.org/10.22201/ib.20078706e.2009.002.627
Escalante, T. (2015) Parsimony analysis of endemicity and analysis of endemicity: a fair comparison. Systematics and Biodiversity, 13, 413–418. https://doi.org/10.1080/14772000.2015.1046966
Escalante, T., Szumik, C. & Morrone, J.J. (2007) Áreas de endemismo de los mamíferos de México: reanálisis y comparación con estudios previos. Darwiniana, 45, 41–43. [https://www.redalyc.org/articulo.oa?id=66909920]
Escalante, T., Szumik, C. & Morrone, J.J. (2009) Areas of endemism of Mexican mammals: reanalysis applying the optimality criterion. Biological Journal of the Linnean Society, 98, 468–478. https://doi.org/10.1111/j.1095-8312.2009.01293.x
Espinosa, D., Aguilar, C. & Escalante, T. (2001) Endemismo, áreas de endemismo y regionalización biogeográfica. In: Llorente-Bousquets, J. & Morrone J.J. (Eds.), Introducción a la biogeografía en Latinoamérica: teorías, conceptos, métodos y aplicaciones. UNAM, Mexico City, pp. 31–­­37.
Fattorini, S. (2017) Endemism in historical biogeography and conservation biology: concepts and implications. Biogeographia–The Journal of Integrative Biogeography, 32, 47–75. https://doi.org/10.21426/B632136433
Ferro, I. & Morrone, J.J. (2014) Biogeographical transition zones: a search for conceptual synthesis. Biological Journal of the Linnean Society, 113, 1–12. https://doi.org/10.1111/bij.12333
Fick, S.E. & Hijmans, R.J. (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, 4302–4315.
  https://doi.org/10.1002/joc.5086
García-Barros, E., Gurrea, P., Luciáñez, M.J., Cano, J.M., Munguira, M.L., Moreno, J.C., Sainz, H., Sanz, M.J. & Simón, J.C. (2002) Parsimony analysis of endemicity and its application to animal and plant geographical distributions in the Ibero-Balearic region (western mediterranean). Journal of Biogeography, 29, 109–124. https://doi.org/10.1046/j.1365-2699.2002.00653.x
Gatto, C.A. & Cohn-Haft, M. (2021) Spatial congruence analysis (scan): a method for detecting biogeographical patterns based on species range congruences. PlosOne, 16, e0245818. https://doi.org/10.1371/journal.pone.0245818
GBIF—Global Biodiversity Information Facility (2020) Available from: http://www.gbif.org/ (accessed 13 February 2020)
Goloboff, P. (2004) NDM/VNDM, Programs for identification of areas of endemism. Program and documentation. Available from: www.zmuc.dk/public/phylogeny/endemism (accessed 3 April 2020)
Harold, A.S. & Mooi, R.D. (1994) Areas of endemism: definition and recognition criteria. Systematic Biology, 43, 261–266. https://doi.org/10.1093/sysbio/43.2.261
Henderson, I. (1991) Biogeography without area? Australian Systematic Botany, 4, 59–71. https://doi.org/10.1071/SB9910059
Hortal, J., de Bello, F., Diniz-Filho, J.A.F., Lewinsohn, T.M., Lobo, J.M. & Ladle, R.J. (2015) Seven shortfalls that beset large-scale knowledge of biodiversity. Annual Review of Ecology, Evolution, and Systematics, 46, 523–549. https://doi.org/10.1146/annurev-ecolsys-112414-054400
Humphries, C.J. & Parenti, L.R. (1999) Cladistic biogeography. Oxford University Press, Oxford, 199 pp.
Linder, H.P. (2001) On areas of endemism, with an example from the African Restionaceae. Systematic Biology, 50, 892–912. https://doi.org/10.1080/106351501753462867
Luna-Vega, I., Alcántara-Ayala, O., Espinosa-Organista, D. & Morrone, J.J. (1999) Historical relationships of the Mexican cloud forests: a preliminary vicariance model applying Parsimony Analysis of Endemicity to vascular plant taxa. Journal of Biogeography, 26, 1299–1305. https://doi.org/10.1046/j.1365-2699.1999.00361.x
Minn, M. (2018) MMQGIS. A collection of QGIS vector layer operation plugins. Available from: http://michaelminn.com/linux/mmqgis/ (accessed 20 December 2020)
Morales-Guerrero, A., Miranda, T.P. & Marques, A.C. (2017) Comparison between Parsimony Analysis of Endemicity (PAE), Endemicity Analysis (EA), and an alternative coding of Three-Distribution Statements based on hypothetical distributions. Systematics and Biodiversity, 15, 391–398. https://doi.org/10.1080/14772000.2016.1257519
Morrone, J.J. (1994) On the identification of areas of endemism. Systematic Biology, 43, 438–441. https://doi.org/10.1093/sysbio/43.3.438
Morrone, J.J. (2014) Parsimony analysis of endemicity (PAE) revisited. Journal of Biogeography, 41, 842–854. https://doi.org/10.1111/jbi.12251
Morrone, J.J. (2018) The spectre of biogeographical regionalization. Journal of Biogeography, 45, 282–288.
  https://doi.org/10.1111/jbi.13135
Morrone, J.J. & Crisci, J.V. (1995) Historical biogeography: introduction to methods. Annual Review of Ecology and Systematics, 26, 373–401. https://doi.org/10.1146/annurev.es.26.110195.002105
Noguera-Urbano, E.A. (2017) El endemismo: diferenciación del término, métodos y aplicaciones. Acta Zoológica Mexicana, 33, 89–107. https://doi.org/10.21829/azm.2017.3311016
Oliveira, U., Brescovit, A.D. & Santos, A.J. (2015) Delimiting areas of endemism through kernel interpolation. PlosOne, 10, e0116673. https://doi.org/10.1371/journal.pone.0116673
Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burgess, N.D., Powell, G.V.N., Underwood, E.C., D’amico, J.A., Itoua, I., Strand, H.E., Morrison, J.C., Loucks, C.J., Allnutt, T.F., Ricketts, T.H., Kura, Y., Lamoreux, J.F., Wettengel, W.W., Hedao, P. & Kassem, K.R. (2001) Terrestrial Ecoregions of the World: A New Map of Life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience, 51, 933–938. https://doi.org/10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2
Papavero, N., Llorente-Bousquets, J. & Minore-Abe, J. (1994) Formal definitions of some new biological and geological terms for use in biogeography. Biogeographica (Paris), 70, 193–203.
Platnick, N. (1991) On areas of endemism. In: Ladiges, P.Y., Humphries, C.J. & Martinelli, L.W. (Eds.), Austral biogeography. CSIRO Melbourne, preface. [unpaginated]
Prado, J.R., Brennand, P.G.G., Godoy, L.P., Libardi, G.S., de Abreu-Júnior, E.F., Roth, P.R.O., Chiquito, E.A. & Percequillo, A.R. (2015) Species richness and areas of endemism of oryzomyine rodents (Cricetidae, Sigmodontinae) in South America: an ndm/vndm approach. Journal of Biogeography, 42, 540–551. https://doi.org/10.1111/jbi.12424
QGIS Development Team (2018) QGIS Geographic Information System. Open Source Geospatial Foundation Project. Available from: http://qgis.osgeo.org (accessed 11 April 2022)
R Core Team (2016) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Available from: https://www.R-project.org/ (accessed 11 April 2022)
Szumik, C., Pereyra, V.V. & Casagranda, M.D. (2019) Areas of endemism: to overlap or not to overlap, that is the question. Cladistics, 35, 198–229. https://doi.org/10.1111/cla.12343
Szumik, C.A., Cuezzo, F., Goloboff, P.A. & Chalup, A.E. (2002) An optimality criterion to determine areas of endemism. Systematic Biology, 51, 806–816. https://doi.org/10.1080/10635150290102483
Szumik, C.A. & Goloboff, P.A. (2004) Areas of endemism: an improved optimality criterion. Systematic Biology, 53, 968–977. https://doi.org/10.1080/10635150490888859

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