| Project/Area Number |
22657008
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Single-year Grants |
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| Research Field |
Ecology/Environment
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| Research Institution | University of the Ryukyus |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
MURAKAMI Masashi 千葉大学, 理学研究科, 准教授 (50312400)
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| Co-Investigator(Renkei-kenkyūsha) |
SHIMATANI Ken-ichiro 統計数理研究所, モデリング研究系, 准教授 (70332129)
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| Project Period (FY) |
2010 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥3,420,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥420,000)
Fiscal Year 2011: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2010: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | 生物多様性 / 生物地理学 / 群集生態学 / マクロ生態学 / マクロ進化 / 中立理論 / 系統的多様性 / ネイマン・スコット点過程モデル / 群集集合 / コアレセント理論 / 琉球諸島 |
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| Research Abstract |
Sessile organisms demonstrate a variety of spatial assembly patterns, which are a result of demographic processes interacting with abiotic conditions. Determining factors are propagule dispersal and environmental gradients in a space ; a plant is present if and only if there were/are seed sources present and a dispersed seed can establish. Fitness in relation to environment has often been conceptualized as one of the principal components of the ecological niche, while dispersal is the first principle in the neutral theory. Therefore, quantitative evaluation of the relative importance of environmental filtering and dispersal limitation is needed, which will also lead us to a breakthrough in the debate on niche versus neutrality. In order to achieve such quantification, we need statistical models that can separately evaluate environmental filtering and dispersal in a common theoretical framework. For individual-based spatially explicit models, point processes can play a central role. An inhomogeneous Neyman. Scott process(I-NS) in which both environmental effects and dispersal processes are incorporated, has been introduced under different formulations. The objective of this study was to extend the likelihood-based method to the I-NS and to demonstrate the methodology using spatial data of forest communities. In addition, this study tried to examine the framework of biogeography and macroecology for incorporating macoevolutionary processes.
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