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Comparing relative model fit of several species-accumulation functions to local Papilionoidea and Hesperioidea butterfly inventories of Mediterranean habitats

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Abstract

When compiling an inventory of hyperdiverse taxa, it is impossible to record the total number of species during fieldwork. To ensure the accuracy of species-richness data it is necessary to assess the reliability of inventories. Accumulation curves are an easy method for doing this and are extensively described in the literature. In this study, we compare the relative fit of various models of species-accumulation functions for six local butterfly inventories, evaluating them by a consideration of the values of the fit, coefficient of determination and sum-of-squares, and the residual patterns and Akaike’s Information Criterion. In general, complex functions, such as the Weibull or Chapman-Richards, performed better than simpler and more widely used models (e.g., the Clench and negative exponential models). The performance of models varied among sampling plots, indicating the influence of factors such as land use and community structure. Thus, although the application of more complex models should replace the use of simple ones, further research into the factors affecting model fit of accumulation functions is necessary.

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References

  • Chao A. 1987. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43: 783–791.

    Article  PubMed  CAS  Google Scholar 

  • Chiarucci A., Enrigut N.J., Perry G.L.W., Miller B.P. and Lamont B.B. 2003. Performance of nonparametric species richness estimators in a high diversity plant community. Div. Distribut. 9: 283–295.

    Article  Google Scholar 

  • Colwell R.K. 2000. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples (Software and User’s Guide), Version 6.0. Available at http://viceroy.eeb.uconn.edu/estimates.

    Google Scholar 

  • Colwell R.K. and Coddington J.A. 1994. Estimating terrestrial biodiversity through extrapolation. Philos. Trans. R. Soc. Ser. B 345: 101–118.

    Article  CAS  Google Scholar 

  • Costa Tenorio M., Morla Juaristi C. and Sainz Ollero H. (eds) 1998. Los bosques ibéricos. Una interpretación geobotánica. Geoplaneta, Barcelona.

    Google Scholar 

  • Dennis R.L.H. and Shreeve T.G. 2003. Gains and losses of French butterflies: tests of predictions, under-recording and regional extinction from data in a new atlas. Biol. Conserv. 110: 131–139.

    Article  Google Scholar 

  • Dennis R.L.H., Shreeve T.G., Sparks T.H. and Lhonore J.E. 2002. A comparison of geographical and neighbourhood models for improving atlas databases. The case of the French butterfly atlas. Biol. Conserv. 108: 143–159.

    Article  Google Scholar 

  • Dennis R.L.H., Sparks T.H. and Hardy P.B. 1999. Bias in butterfly distribution maps: the effects of sampling effort. J. Insect Conserv. 3: 33–42.

    Article  Google Scholar 

  • Dennis R.L.H. and Thomas C.D. 2000. Bias in butterfly distribution maps: the influence of hot spots and recorder’s home range. J. Insect Conserv. 4: 73–77.

    Article  Google Scholar 

  • Fagan W.F. and Kareiva P.M. 1997. Using compiled species lists to make biodiversity comparisons among regions: a test case using Oregon butterflies. Biol. Conserv. 80: 249–259.

    Article  Google Scholar 

  • Flather C.H. 1996. Fitting species-accumulation functions and assessing regional land use impacts on avian diversity. J. Biogeogr. 23: 155–168.

    Article  Google Scholar 

  • García-Barros E., García-Pereira P. and Munguira M.L. 2000. The geographic distribution and state of butterfly faunistic studies in Iberia (Lepidoptera Papilionoidea Hesperioidea). Belg. J Entomol. 2: 111–124.

    Google Scholar 

  • García-Barros E. and Munguira M.L. 1999. Faunística de mariposas diurnas en España peninsular. Áreas poco estudiadas: una evaluación en el umbral del siglo XXI (Lepidoptera: Papilionidae and Hesperiidae). SHILAP Revista de Lepidopterología 27(106): 189–202.

    Google Scholar 

  • García-Pereira P., García-Barros E. and Munguira M.L. 1999. Evaluación del conocimiento de la fauna de mariposas de Portugal continental. SHILAP Revista de Lepidopterología 27(106): 225–231.

    Google Scholar 

  • Gaston K.J. (ed.) 1996. Biodiversity A Biology of Numbers and Difference. Blackwell Science, Oxford.

    Google Scholar 

  • Gotelli N.J. and Colwell R.K. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4: 379–391.

    Article  Google Scholar 

  • Heltshe J.F. and Forrester N.E. 1983. Estimating species richness using the jackknife procedure. Biometrics 39: 1–11.

    Article  PubMed  CAS  Google Scholar 

  • Hortal J., Lobo J.M. and Martín-Piera F. 2001. Forecasting insect species richness scores in poorly surveyed territories: the case of the Portuguese dung beetles (Col. Scarabaeinae). Biodiv. Conserv. 10: 1343–1367.

    Article  Google Scholar 

  • Jiménez-Valverde A. and Lobo J.M. 2004. Determining a combined sampling procedure for a reliable estimation of Araneidae and Thomisidae assemblages (Arachnida: Araneae). J. Arachnol. 32(3): in press.

    Google Scholar 

  • Jiménez-Valverde A., Martín Cano J. and Munguira M.L. 2002. Fauna de mariposas del Parque Nacional de Cabañeros y su entorno (Lepidoptera: Papilionoidea, Hesperioidea). SHILAP Revista de Lepidopterología 30(120): 271–279.

    Google Scholar 

  • Jiménez-Valverde A., Martín Cano J. and Munguira M.L. 2004. Patrones de diversidad de la fauna de mariposas del Parque Nacional de Cabañeros y su entorno (Ciudad Real, España central) (Lepidoptera: Papilionoidea, Hesperioidea). Anim. Biodiv. Conserv. 27(2): 15–24.

    Google Scholar 

  • Keating K.A. and Quinn J.F. 1998. Estimating species richness: the Michaelis-Menten model revisited. Oikos 81(2): 411–416.

    Article  Google Scholar 

  • Lamas G., Robbins R.K. and Harvey D.J. 1991. A preliminary survey of the butterfly fauna of Pakitza, Parque Nacional del Manu, Peru, with an estimate of its species richness. Publicaciones del Museo de Historia Natural, Universidad Nacional Mayor de San Marcos, Serie A Zoología 40: 1–19.

    Google Scholar 

  • León-Cortés J.L., Soberón-Mainero J. and Llorente-Bousquets J. 1998. Assessing completeness of Mexican sphinx moth inventories through species accumulation functions. Div. Distribut. 4: 37–44.

    Google Scholar 

  • Longino J.T., Coddington J. and Colwell R.K. 2002. The ant fauna of a tropical rain forest: estimating species richness three different ways. Ecology 83: 689–702.

    Google Scholar 

  • Magurran A.E. 1988. Ecological Diversity and Its Measurement. Princeton University Press, New Jersey.

    Google Scholar 

  • Martín J. and Gurrea P. 1999. Áreas de especiación en España y Portugal. Boletín de la Asociación española de Entomología 23(12): 83–103.

    Google Scholar 

  • Martín Cano J., Ferrín J.M., García-Barros E., García-Ocejo A., Gurrea P., Luciañez M.J., Munguira M.L., Perez Barroeta F., Ruiz Ortega M., Sanz Benito M.J., Simon J.C. and Viejo J.L. 1996. Las comunidades de insectos del Parque Regional de la Cuenca Alta del Manzanares (centro de España): estado de conservación. Graellsia 51: 101–111.

    Google Scholar 

  • Moreno C.E. and Halffter G. 2000. Assessing the completeness of bat biodiversity inventories using species accumulation curves. J. Appl. Ecol. 37: 149–158.

    Article  Google Scholar 

  • Moreno C.E. and Halffter G. 2001. On the measure of sampling effort used in species accumulation curves. J. Appl. Ecol. 38: 487–490.

    Article  Google Scholar 

  • Motulsky H.J. and Christopoulos A. 2003. Fitting Models to Biological Data Using Linear and Nonlinear Regression. A practical guide to curve fitting, Available at http://www.graphpad.com. GraphPad Software Inc., San Diego CA.

    Google Scholar 

  • New T.R. 1997. Are Lepidoptera an effective ‘umbrella group’ for biodiversity conservation? J. Insect Conserv. 1: 5–12.

    Article  Google Scholar 

  • Palmer M.W. 1990. The estimation of species richness by extrapolation. Ecology 71(3): 1195–1198.

    Article  Google Scholar 

  • Pearson D.L. 1994. Selecting indicator taxa for the quantitative assessment of biodiversity. Philos. Trans. R. Soc. Ser. B 345: 75–79.

    Article  CAS  Google Scholar 

  • Petersen F.T. and Meier R. 2003. Testing species-richness estimation methods on single-sample collection data using the Danish Diptera. Biodiv. Conserv. 12: 667–686.

    Article  Google Scholar 

  • Petersen F.T., Meier R. and Larsen M.N. 2003. Testing species richness estimation methods using museum label data on the Danish Asilidae. Biodiv. Conserv. 12: 687–701.

    Article  Google Scholar 

  • Peterson A.T. and Slade N.A. 1998. Extrapolating inventory results into biodiversity estimates and the importance of stopping rules. Div. Distribut. 4: 95–105.

    Article  Google Scholar 

  • Pollard E. 1977. A method for assessing changes in the abundance of butterflies. Biol. Conserv. 12: 115–134.

    Article  Google Scholar 

  • Pollard E. 1982. Monitoring butterfly abundance in relation to the management of a nature reserve. Biol. Conserv. 24: 317–328.

    Article  Google Scholar 

  • Pollard E. and Yates T.J. 1993. Monitoring Butterflies for Ecology and Conservation. Chapman & Hall, London.

    Google Scholar 

  • Rivas Martínez S. 1987. Mapas de series de vegetación de España 1:400.000 y Memoria. ICONA, Ministerio de Agricultura, Pesca y Alimentación, Spain.

    Google Scholar 

  • Smith E.P. and van Belle G. 1984. Nonparametric estimation of species richness. Biometrics 40: 119–129.

    Article  Google Scholar 

  • Soberón J. and Llorente J. 1993. The use of species accumulation functions for the prediction of species richness. Conserv. Biol. 7(3): 480–488.

    Article  Google Scholar 

  • Statsoft. 2001. STATISTICA (Data Analysis Software System and User’s Manual). Version 6. StatSoft Inc., Tulsa, OK.

    Google Scholar 

  • Tjørve E. 2003. Shapes and functions of species-area curves: a review of possible models. J. Biogeogr. 30: 827–835.

    Article  Google Scholar 

  • Vaquero de la Cruz J. 1997. Flora vascular y vegetación. In: García Canseco V. et al. (eds), Parque Nacional de Cabañeros. Ecohábitat, Ciudad Real, Spain pp. 95–154.

    Google Scholar 

  • Willott S.J. 2001. Species accumulation curves and the measure of sampling effort. J. Appl. Ecol. 38: 484–486.

    Article  Google Scholar 

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David L. Hawksworth Alan T. Bull

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Jiménez-Valverde, A., Mendoza, S.J., Cano, J.M., Munguira, M.L. (2006). Comparing relative model fit of several species-accumulation functions to local Papilionoidea and Hesperioidea butterfly inventories of Mediterranean habitats. In: Hawksworth, D.L., Bull, A.T. (eds) Arthropod Diversity and Conservation. Topics in Biodiversity and Conservation, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5204-0_11

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