<p>To conserve biodiversity, it is critical to understand the dynamic landscapes and climates through which species move and how the environment influences movement choices. In particular, I am interested in how species respond to human modifications to landscapes and climates. Chapter 1 uses datasets on the spatial and temporal coverage of remotely sensed land cover datasets to examine gaps in the monitoring of environmental priorities. Temporal gaps in Landsat and spatial gaps in commercial high resolution satellites such as QuickBird may hinder land cover change monitoring efforts.</p><p>Chapter 2 uses Global Climate Models and museum specimens to projects the impact of climate change on the flora of California, a global biodiversity hotspot. With anticipated climate change, up to 66% may experience >80% reductions in range size within a century. These projections are less severe if plants are able to disperse in time. With no constraints on dispersal, plant centroids move an average of up to 150 km. The projections identify regions where species undergoing severe range reductions may persist. Protecting these potential future refugia and facilitating species dispersal may be essential to maintain biodiversity in the face of climate change.</p><p>Chapter 3 analyzes the movements of 73 elephants fitted with GPS collars against 4 remotely sensed datasets spanning a strong rainfall gradient across 7 southern African countries. Movements show strong seasonal and geographic differences across the study area. Two major human interventions, artificial water and fences, distort these movement patterns by increasing dry season ranging patterns and increasing the density of wet season movements.</p><p>Chapter 4 uses the datasets described in chapter 3 to explore elephant vegetation preferences. Elephants consistently prefer greener vegetation throughout the year. Vegetation preferences vary seasonally. Elephants prefer less variable vegetation such as forests in the dry season and ephemeral vegetation such as grasslands in the wet season.</p><p>Chapter 5 uses telemetry and remotely sensed landcover data to ask how climatic factors - snow cover - and land cover - agriculture and roads - influence pronghorn movements in South Eastern Alberta. Analysis using a Bayesian movement model reveals that each of these features significantly influences pronghorn movement choices.</p> / Dissertation
| Identifer | oai:union.ndltd.org:DUKE/oai:dukespace.lib.duke.edu:10161/700 |
| Date | 04 August 2008 |
| Creators | Loarie, Scott Robbins |
| Contributors | Pimm, Stuart L |
| Source Sets | Duke University |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 6153073 bytes, application/pdf |
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