Aaron M. Ellison & Nicholas J. Gotelli 
Scaling in Ecology with a Model System [PDF ebook] 

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A groundbreaking approach to scale and scaling in ecological theory and practice
Scale is one of the most important concepts in ecology, yet researchers often find it difficult to find ecological systems that lend themselves to its study. Scaling in Ecology with a Model System synthesizes nearly three decades of research on the ecology of Sarracenia purpurea—the northern pitcher plant—showing how this carnivorous plant and its associated food web of microbes and macrobes can inform the challenging question of scaling in ecology.
Drawing on a wealth of findings from their pioneering lab and field experiments, Aaron Ellison and Nicholas Gotelli reveal how the Sarracenia microecosystem has emerged as a model system for experimental ecology. Ellison and Gotelli examine Sarracenia at a hierarchy of spatial scales—individual pitchers within plants, plants within bogs, and bogs within landscapes—and demonstrate how pitcher plants can serve as replicate miniature ecosystems that can be studied in wetlands throughout the United States and Canada. They show how research on the Sarracenia microecosystem proceeds much more rapidly than studies of larger, more slowly changing ecosystems such as forests, grasslands, lakes, or streams, which are more difficult to replicate and experimentally manipulate.
Scaling in Ecology with a Model System offers new insights into ecophysiology and stoichiometry, demography, extinction risk and species distribution models, food webs and trophic dynamics, and tipping points and regime shifts.

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Об авторе

Aaron M. Ellison is the Senior Research Fellow Emeritus in Ecology at Harvard University. Website unbalancedecologist.net Twitter @AMax Ell17
Nicholas J. Gotelli is the George H. Perkins Professor of Zoology at the University of Vermont. Website uvm.edu/~ngotelli/homepage.html They are the coauthors of
A Primer of Ecological Statistics and
A Field Guide to the Ants of New England.

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язык английский ● Формат PDF ● страницы 338 ● ISBN 9780691222783 ● Размер файла 8.1 MB ● издатель Princeton University Press ● город Princeton ● Страна US ● опубликованный 2021 ● Загружаемые 24 месяцы ● валюта EUR ● Код товара 7766425 ● Защита от копирования Adobe DRM
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