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Testing Biogeographic Theories Using Syntheses of Plant Traits

出版	McGill University Libraries, 2022
URL	http://books.google.com.hk/books?id=TEldzwEACAAJ&hl=&source=gbs_api

註釋"Biogeographic patterns in species distributions that are consistent across taxa, geographic scales, and time periods have long fascinated ecologists. Many theories exist about the mechanisms driving these patterns, but testing them can be difficult as it is not always clear what specific variables need to be measured. In this thesis, I explore two cases where measuring variables in different ways can alter the predictions or interpretations of a classic biogeographic pattern. First, I unpack Darwin's prediction that species interactions should be stronger at lower latitudes, elevations, and/or climatically benign environments into two components of interaction strength: interaction intensity and exposure time. Studies on terrestrial interaction intensity generally support Darwin's prediction, but exposure time has been relatively ignored. I tested latitudinal, elevational and climatic gradients in the exposure time of seeds, a commonly used experimental prey, and found that that variation in time to germination differed depending on the gradient in question, with no overall clear geographic pattern. Second, I explore species-area relationships in the Galápagos Islands. Many hypotheses have been proposed to explain why species richness should increase with island area, together suggesting that the "area" that drives the increase in species richness is therefore not necessarily the total area of the island, but only the area that is capable of capturing new immigrants, or providing habitat and resources for existing species, which I term the "effective island area". I explore the concept of effective island area in four examples, using different measures of plant species richness and area subsets from the Galápagos Islands. I provide a conceptual framework for comparisons that can be made across systems to infer processes driving species distributions. In both chapters I show how breaking down biogeographic patterns and measuring their individual components can help to better understand underlying patterns influencing species distributions across space"--