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Comprobación de Hipótesis sobre las Extinciones de Aves en Río Palenque, Ecuador Mediante Listas Informales de Especies
Author(s) -
PEARSON DAVID L.,
ANDERSON COREY DEVIN,
MITCHELL BRIAN R.,
ROSENBERG MICHAEL S.,
NAVARRETE RONALD,
COOPMANS PAUL
Publication year - 2010
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.2009.01383.x
Subject(s) - occupancy , extinction (optical mineralogy) , range (aeronautics) , foraging , ecology , geography , deforestation (computer science) , biology , computer science , paleontology , materials science , composite material , programming language
Informally gathered species lists are a potential source of data for conservation biology, but most remain unused because of questions of reliability and statistical issues. We applied two alternative analytical methods (contingency tests and occupancy modeling) to a 35‐year data set (1973–2007) to test hypotheses about local bird extinction. We compiled data from bird lists collected by expert amateurs and professional scientists in a 2‐km 2 fragment of lowland tropical forest in coastal Ecuador. We tested the effects of the following on local extinction: trophic level, sociality, foraging specialization, light tolerance, geographical range area, and biogeographic source. First we assessed extinction on the basis of the number of years in which a species was not detected on the site and used contingency tests with each factor to compare the frequency of expected and observed extinction events among different species categories. Then we defined four multiyear periods that reflected different stages of deforestation and isolation of the study site and used occupancy modeling to test extinction hypotheses singly and in combination. Both types of analyses supported the biogeographic source hypothesis and the species‐range hypothesis as causes of extinction; however, occupancy modeling indicated the model incorporating all factors except foraging specialization best fit the data.