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A Framework for Community Ecology

by Paul a. Keddy , Daniel C. Laughlin
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Current price ₹11,589.00
Original price ₹11,830.00
Original price ₹11,830.00
Original price ₹11,830.00
(-2%)
₹11,589.00
Current price ₹11,589.00

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Book cover type: Hardcover
  • ISBN13: 9781316512609
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Cambridge University Press
  • Publisher Imprint: Cambridge University Press
  • Publication Date:
  • Pages: 368
  • Original Price: GBP 91.0
  • Language: English
  • Edition: N/A
  • Item Weight: 667 grams
  • BISAC Subject(s): Ecology

This book addresses an important problem in ecology: how are communities assembled from species pools? This pressing question underlies a broad array of practical problems in ecology and environmental science, including restoration of damaged landscapes, management of protected areas, and protection of threatened species. This book presents a simple logical structure for ecological assembly and addresses key areas including species pools, traits, environmental filters, and functional groups. It demonstrates the use of two predictive models (CATS and Traitspace) and consists of many wide-ranging examples including plants in deserts, wetlands, and forests, and communities of fish, amphibians, birds, mammals, and fungi. Global in scope, this volume ranges from the arid lands of North Africa, to forests in the Himalayas, to Amazonian floodplains. There is a strong focus on applications, particularly the twin challenges of conserving biodiversity and understanding community responses to climate change.

Laughlin, Daniel C.: - Daniel C. Laughlin is an Associate Professor of plant ecology and ecological modelling in the Department of Botany at the University of Wyoming. Daniel's research focuses on developing quantitative approaches to understand and predict how plant species and communities respond to global change. His lab develops trait-based models that translate ecological processes into statistical frameworks to predict how communities assemble along environmental gradients and how species interact at local scales.

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