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Measuring the Health of the Earth Using the Theory of Island Biography

Author(s): Jana Eggleston, Stephanie Renee Campau, Farshid Ahrestani, Holly D Gaff1

Old Dominion University

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Summary:
This module uses a variety of available datasets to explore methods of calculating biodiversity and measuring landscape as well as the relationship between those.

Licensed under CC Attribution-NonCommercial-NoDerivatives 4.0 International according to these terms

Version 1.0 - published on 25 Oct 2018 doi:10.25334/Q4WX47 - cite this

Description

Biodiversity has been shown to be a good measure of the health of the planet system (McGrady-Steed et al. 1997). The more species and genetic diversity, the more stable the ecosystem (Butchart et al. 2010). As we focus on the sustainability of the planet, we need this diversity to withstand stresses from changing weather patterns, disease and human population growth (Heller and Zavaleta 2009).

Island biogeography is the study of the factors affecting species diversity of natural communities. As our natural landscape is becoming more and more fragmented, it resembles a series of islands. While the Theory of Island Biogeography was developed in the 1960’s (MacArthur and Wilson 1963), this attempt to predict the number of species on an "island" is still very valid today. Continuing research supports that the loss of species can have definite consequences for an ecosystem (Worm et al. 2006) .

This module uses a variety of available datasets to explore methods of calculating biodiversity and measuring landscape as well as the relationship between those. These points are then used to teach logarithms by estimating slopes and intercepts from a log-log plot of the number of species in a given location against a variety of metrics including island size and distance from mainland. Optionally, this could then be adapted to fragmented habitats near a national park or the like. Finally, the plots are used to estimate the level of fragmentation that would push the system to a given level of species loss.

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