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清華大學、交通大學
統 計 學 研 究 所
專 題 演 講
題
目: Community Assembly: From Small to Large Spatial Scales
主講人: Prof. Nicholas J. Gotelli
(Department of Biology, University of Vermont)
時
間: 98年10月08日（星期四）上午 10：40 - 11：30
（上午10：20- 10：40茶會於統計所821室舉行）
地
點:
清大綜合三館 837 室
Abstract
Two fundamental questions in community ecology are 1) what determines the
relative abundance (commonness and rarity) of species in a community? 2) what factors
contribute to variation in species richness among communities? This talk describes two
different empirical studies that address these questions. The community of aquatic
invertebrates and microbes that inhabit rain-filled leaves of the carnivorous pitcher
plant Sarracenia purpurea are a model system for studying the problem of relative
abundance. Because the leaves represent a miniature self-contained ecosystem, removal
of top predators and alteration of habitat volume can be successfully conducted in field
experiments. These experimental manipulations generate a range of community types.
Path analysis can be used to quantify different ecological hypotheses and test their
relative fit to the abundance data.
The problem of variation in species richness is addressed through a continental
scale study of the entire South American avifauna (> 2200 endemic species), the richest
continental avifauna in the world. Ecologists have traditionally investigated the
relationship between species richness and climatic factors with simple regression
models but these approaches are not satisfactory because the data are spatially
autocorrelated and the regression analyses may not provide explicit tests of mechanistic
hypotheses. An alternative approach is to use process-based simulation models that
describe the origin and spread of species geographic ranges within a bounded domain.
These models point to the importance of climatic variables, but also suggest that
historical factors (which are not explicitly included in the model) are very important,
especially for species with small geographic ranges.
Both studies highlight the statistical challenges that community ecologists face, as
they try to formulate quantitative hypotheses to account for patterns, and then test those
hypotheses with limited, non-independent data..
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