Response to comment on "habitat split and the global decline of amphibians"

Science

Volumn 320, Issue 5878, 2008, Pages

  Fonseca, Carlos Roberto ^a   Becker, Carlos Guilherme ^a,b   Haddad, Célio Fernando Baptista ^c   Prado, Paulo Inácio ^d  

^a UNIVERSIDADE DO VALE DO RIO DOS SINOS   (Brazil)

^b UNIVERSITY OF CAMPINAS   (Brazil)

^c SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^d UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

AMPHIBIA; BIODIVERSITY; BRAZIL; FOREST; HABITAT; HABITAT FRAGMENTATION; MONTE CARLO METHOD; NOTE; PRIORITY JOURNAL;

AMPHIBIA;

EID: 46449086824     PISSN: 00368075     EISSN: 10959203     Source Type: Journal    
DOI: 10.1126/science.1155686     Document Type: Note

References (15)

1. C. G. Becker, C. R. Fonseca, C. F. B. Haddad, R. F. Batista, P. I. Prado, Science 318, 1775 (2007).
2. D. C. Cannatella, Science 320, 874 (2008); www.sciencemag.org/cgi/content/full/320/5878/874c.
3. W. S. Comulada, R. E. Weiss, Biometrics 63, 610 (2007).
4. A. J. Dobson, An Introduction to Generalized Linear Models (Chapman & Hall/CRC, New York, ed. 2, 2002).
5. P. McCullagh, J. A. Nelder, Generalized Linear Models (Chapman & Hall/CRC, New York, ed. 2, 1989).
6. R Development Core Team, R Version 2.6.1 (R Foundation for Statistical Computing, Vienna, www.R-project.org, 2007).
7. B. Bolker, bbmle: Tools for general maximum likelihood estimation (R package, Version 0.8.2, www.cran.r-project.org/, 2008).
8. SYSTAT, SYSTAT for Windows, version 10.2.01 (Richmond, CA, 2002).
9. SAS Institute Inc., SAS/STAT, version 8.3 (Cary, NC, 2001).
10. G. Zou, Am. J. Epidemiol. 159, 702 (2004).
11. D. Spiegelman, E. Hertzmark, Am. J. Epidemiol. 162, 199 (2005).
12. An alternative approach to test the influence of habitat split, habitat loss, and habitat fragmentation on the proportion of amphibian species with aquatic larvae is the use of a Poisson multiple regression model with a robust error variance implemented in the module Proc Genmod in SAS (9). This method, which assumes a log link and a binomial distribution, has proven to perform better than logistic regression when frequencies are considerably high and sample sizes are small (10, 11). In our data set, the proportions of species aquatic larvae in communities are high (minimum = 0.47, maximum = 0.80), and the number of independent data points is limited (N = 12 sites). The response variable is defined by the number of species with aquatic larvae (number of events) and by the total species richness (number of trials). The full model contained the three landscape variables and their higher-order interactions as explanatory variables; the minimal adequate model was established by a stepwise multiple regression, with backward deletion. The proportion of species with aquatic larvae was negatively associated to habitat split (b = -0.0122 ± 0.004, z = -3.06, P = 0.0022) and positively associated to habitat loss (b = 0.0102 ± 0.0031, z = 3.32, P = 0.0009). This reinforces the results presented by the path analysis.
13. S. Blank, C. Seiter, P. Bruce, Resampling Stats in Excel (Arlington, VA, 1999).
14. R. Melnick, B. Johnson, K. Hill, Ecology and Design: Frameworks for Learning (Island Press, Washington, DC, 2001).
15. We thank K. R. Zamudio and G. Ganade for critically reviewing previous versions of the manuscript and J. Fox and E. M. Wendland for assistance in the statistical analyses. C.G.B. received a scholarship from the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP: 04/13132-3). C.R.F. and C.F.B.H. received fellowships from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq: 305428/2005-5, 302512/2005-5). This project was supported by the Programa de Pesquisas em Caracterização, Conservação e Uso Sustentável da Biodiversidade do Estado de São Paulo da Fundação de Amparo à Pesquisa do Estado de São Paulo (BIOTA/FAPESP 01/13341-3 and 02/08558-6) and Universidade do Vale do Rio dos Sinos.