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Patterns of species richness and con...
~
Tognelli, Marcelo Fabio.
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Patterns of species richness and conservation of South American terrestrial mammals.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Patterns of species richness and conservation of South American terrestrial mammals./
Author:
Tognelli, Marcelo Fabio.
Description:
108 p.
Notes:
Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1057.
Contained By:
Dissertation Abstracts International64-03B.
Subject:
Biology, Ecology. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3082569
Patterns of species richness and conservation of South American terrestrial mammals.
Tognelli, Marcelo Fabio.
Patterns of species richness and conservation of South American terrestrial mammals.
- 108 p.
Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1057.
Thesis (Ph.D.)--University of California, Davis, 2003.
This dissertation consists of three chapters. In the first chapter, I compared classical ordinary least squares (OLS) and autoregressive regression models to investigate the effect of spatial autocorrelation when trying to identify what environmental variables are best predictors of the terrestrial mammal fauna of South America. Using autoregressive models, I found that the relative importance of explanatory variables and specific hypotheses changes once the spatial structure in the data is accounted for. The results of this chapter underscore the importance of the spatial arrangement of the data when searching for underlying causal mechanisms of species diversity.Subjects--Topical Terms:
1017726
Biology, Ecology.
Patterns of species richness and conservation of South American terrestrial mammals.
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108 p.
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Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1057.
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Adviser: Douglas A. Kelt.
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Thesis (Ph.D.)--University of California, Davis, 2003.
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This dissertation consists of three chapters. In the first chapter, I compared classical ordinary least squares (OLS) and autoregressive regression models to investigate the effect of spatial autocorrelation when trying to identify what environmental variables are best predictors of the terrestrial mammal fauna of South America. Using autoregressive models, I found that the relative importance of explanatory variables and specific hypotheses changes once the spatial structure in the data is accounted for. The results of this chapter underscore the importance of the spatial arrangement of the data when searching for underlying causal mechanisms of species diversity.
520
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In chapter two, I investigated the explanatory power of four competing hypotheses (i.e. ambient energy, contemporary climate, habitat heterogeneity, and productivity) to explain species richness patterns of South American terrestrial mammals across ten spatial scales, again applying OLS and autoregressive models. I found that the relative importance of environmental variables and proposed hypotheses varied depending on the spatial scale of the analysis. At the two finest scales, variables associated with productivity were relatively more important at determining species richness. However, at coarser scales, variables associated with habitat heterogeneity and ambient energy were more relevant. These findings have implications for conservation in light of the current developments in human-induced fragmentation and global climate change.
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In chapter three I assess the utility and efficiency of different surrogate groups to conserve the mammal fauna for the entire continent, as well as Brazil. I used explicitly selected subsets of the entire mammal fauna of South America (and Brazil) as surrogate groups, and complementarity analysis to select sites for conservation based on these groups. The results show that selecting areas using explicitly selected subsets of species is not significantly more efficient than when random sets of species are chosen. However, a surrogate group composed of geographically rare species protected a significantly higher percentage of the total number of species, as well as significantly higher percentages of endangered and rare species, and total number of genera.
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School code: 0029.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3082569
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