Title

A Discrete Mathematical Extension of Conceptual Ecological Models - Application for the SE Florida Shelf

Document Type

Article

Publication Date

9-2014

Keywords

DPSER model, Digraph, End-to-end model, Conceptual ecological model, Quantification, Coral reef, Waste water, Climate change

Publication Title

Ecological Indicators

ISSN

1470-160X

Volume

44

First Page

40

Last Page

56

Peer Reviewed

1

Abstract

Conceptual ecological models (CEM) respond to the need for improved management of natural resources due to increasing scale and severity of human impacts. CEMs, like the EBM-DPSER framework, serve as non-quantitative planning tools identifying stressors and drivers on natural systems, effects and biological indicators best suited to show these effects. A disadvantage of CEMs is their non-quantitative nature restraining users from performing sensitivity and quantitative scenario analysis. Here we develop a quantitative extension of a EBM-DPSER model of the SE Florida shelf based on the assumption that the CEM flow diagrams express as digraphs. It was quantified with transition weights from literature research and local data, turning the digraph into a network. The usefulness of the network extension and its underlying weighted adjacency matrix were verified using monitoring data from the Florida Keys Reef Tract. The network extension was then used to explore outcomes of two different management scenarios. Model results suggest that advanced waste water treatment in SE Florida would increase reef diversity and framework growth and could reduce macroalgae cover while increasing coral cover, fish and shellfish abundance and eliminating phytoplankton blooms. Climate change is projected to have an effect on sea level rise, acidification and bleaching but probably with a minor influence on coral cover, reef framework and diversity – which are already low. Tested scenarios show that the modeled impact of regulation processes can vary profoundly even if the number of arcs and vertices in their largest possible out-tree are comparable. Such a tool extends the power of the conceptual model by adding significant new information and the ability to quantifiably test of hypotheses.

Comments

©2014 Elsevier Ltd. All rights reserved.

ORCID ID

0000-0002-6003-9324

ResearcherID

F-8807-2011

DOI

10.1016/j.ecolind.2014.04.012

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