Relationships between renewable emergy storage or flow and biodiversity: A modeling investigation

TitleRelationships between renewable emergy storage or flow and biodiversity: A modeling investigation
Publication TypeJournal Article
Year of Publication2016
AuthorsCampbell, ET, Tilley, DR
JournalEcological Modelling
Volume340
Pagination134 - 148
Date Published2016/11/24/
ISBN Number0304-3800
KeywordsBiodiversity, Disturbance regime, Ecological network, Emergy, Forest eco-regions
Abstract

In this study we investigate the relationships of emergy storage or flow to biodiversity using three different models—a dynamic simulation model, a static scenario model, and a modified ecological network model. These models attempt to explain how disturbance regime, latitude, and trophic complexity are related to observed patterns of renewable emergy flows and storages and biodiversity. A prior hypothesis, which this work seeks to examine, suggests that as renewable emergy flow increases biodiversity will increase. In this regard, we simulate how H.T. Odum’s original CLIMAX model, which tracks forest biomass and diversity over 100 years of succession, responds to a periodic disturbance. The static scenario model compares emergy flow, storage and diversity in five forest eco-regions along the east coast of the United States. An emergy flow matrix ecological network model was used to simulate biodiversity in a mature forest ecosystem and in a typical suburban forest system to investigate how the complexity of a forest system will affect emergy throughput. Comparisons were made for the Shannon diversity index and transformity at the individual trophic level. These comparisons seek to further our understanding of the relationship of emergy and biodiversity and to validate the use of renewable emergy flow to explain ecological phenomena (e.g., biodiversity increasing as latitude decreases, biodiversity increasing through the stages of forest succession).

URLhttp://www.sciencedirect.com/science/article/pii/S0304380016302848
Short TitleEcological Modelling