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- Creator:
- Trevino, Heather S., Karels, Timothy J., Dobson, F. Stephen, and Skibiel, Amy L.
- Description:
- Results of the study by Blackburn et al. (2004a) of avifauna on oceanic islands suggest that distance from the mainland and time since European colonization have major influences on species extinctions and that island area is a significant but secondary contributing factor. After augmenting the data of the study on geographical properties for some of the islands they examined, we used a causal analysis approach with structural equation modeling to reexamine their conclusions. In our model geographical properties of islands, such as island area and isolation, were considered constraints on biological factors, such as the number of introduced mammalian predators and existing number of avifauna, that can directly or indirectly influence extinction. Of the variables we tested, island area had the greatest total influence on the threat of extinction due to its direct and indirect effects on the size of island avifauna. Larger islands had both a greater number of threatened bird species and more avifauna, increasing the number of species that could become threatened with extinction. Island isolation also had a significant, positive, and direct effect on threats to island avifauna because islands farther from the mainland had fewer current extant avifauna. Time since European colonization had a significant negative, but relatively weaker, influence on threats compared with the traditional biogeographic factors of island area and distance to the mainland. We also tested the hypothesis that the amount of threat is proportionally lower on islands that have had more extinctions (i.e., there is a "filter effect"). Because the proportion of bird extinctions potentially explained only 2.3% of the variation in the proportion of threatened species on islands, our results did not support this hypothesis. Causal modeling provided a powerful tool for examining threat of extinction patterns of known and hypothesized pathways of influence.
- Resource Type:
- Article
- Identifier:
- 0888-8892
- Campus Tesim:
- Northridge
- Creator:
- Trevino, Heather S., Karels, Timothy J., Dobson, F. Stephen, and Skibiel, Amy L.
- Description:
- A recent paper by Karels et al., 'The biogeography of avian extinctions on oceanic islands' (Journal of Biogeography, 2008, 35, 1106-1111), uses structural equation modelling to assess the causes of the number of island bird species driven extinct in the historical period. Here, we critically assess the conclusions of the paper and argue that it does not provide the new insights into the causes of extinction in island birds that its authors claim.
- Resource Type:
- Article
- Identifier:
- 0305-0270
- Campus Tesim:
- Northridge
- Creator:
- Trevino, Heather S., Karels, Timothy J., Dobson, F. Stephen, and Skibiel, Amy L.
- Description:
- We are pleased that Blackburn et al. (2008 [this issue]) have taken an interest in our causal modeling of threatened bird faunas on oceanic islands (Trevino et al. 2007). Our results indicated possible environmental influences on the number of threatened bird species from the physical and biotic characteristics of islands. Blackburn et al. discuss possible strengths and weaknesses of 2 methods of analyzing such influences: generalized?linear mixed modeling and causal modeling with structural equations and standardized partial?regression coefficients (these last used as measures of effect sizes). The former method excludes information because it does not incorporate the logical structure of causes, whereas the latter takes advantage of the fact that physical aspects of islands (island area and isolation from a mainland) might influence biotic factors (number of species in the avifauna, number of introduced mammalian predators, and time since human colonization of the islands) and that physical and biotic factors might influence the dependent variable (number of bird species under threat of extinction) (Fig. 1). Although physical factors are likely to influence biotic factors, we think the reverse is unlikely to be true. The method we used allowed us to test an a priori theoretical model that is a working hypothesis of causal mechanisms (Mitchell 1992) threatening birds on oceanic islands. This method can be used to refine and deepen understanding of the potential collaborative factors that may influence the extinction threat of ocean island avifaunas.
- Resource Type:
- Article
- Identifier:
- 0888-8892
- Campus Tesim:
- Northridge
- Creator:
- Zimbler-DeLorenzo, H.S., Karels, Timothy J., Dobson, F. Stephen, and Skibiel, Amy L.
- Description:
- In their recent comment in this journal, T. M. Blackburn and colleagues called into question the use of standardized partial regression modelling (also called path analysis and structural equation modelling) when null expectations for regression coefficients are not zero. Here, we answer their critique by showing how randomization can be used to illuminate and interpret causal modelling in analyses that have non?zero expectations. Causal modelling is a powerful tool that can yield novel insights in biogeography when properly interpreted.
- Resource Type:
- Article
- Identifier:
- 0305-0270
- Campus Tesim:
- Northridge