Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach

Renken, Henk; Mumby, Peter J.

doi:10.1016/j.ecolmodel.2009.02.022

Cited by 62 publications

(45 citation statements)

References 80 publications

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“…There are many methods (e.g. [54,55]) that can be used to cross levels of organization and therefore abstract the necessary and sufficient information from the levels below [23] consumes, while for an individual prey the decision matters greatly. Therefore, at one trophic level, which individual dies is a matter of concern; while at higher level it is not (figure 2).…”

Section: An Alternative Approachmentioning

confidence: 99%

Modelling ecological systems in a changing world

Evans

2012

Phil. Trans. R. Soc. B

157

184

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The world is changing at an unprecedented rate. In such a situation, we need to understand the nature of the change and to make predictions about the way in which it might affect systems of interest; often we may also wish to understand what might be done to mitigate the predicted effects. In ecology, we usually make such predictions (or forecasts) by making use of mathematical models that describe the system and projecting them into the future, under changed conditions. Approaches emphasizing the desirability of simple models with analytical tractability and those that use assumed causal relationships derived statistically from data currently dominate ecological modelling. Although such models are excellent at describing the way in which a system has behaved, they are poor at predicting its future state, especially in novel conditions. In order to address questions about the impact of environmental change, and to understand what, if any, action might be taken to ameliorate it, ecologists need to develop the ability to project models into novel, future conditions. This will require the development of models based on understanding the processes that result in a system behaving the way it does, rather than relying on a description of the system, as a whole, remaining valid indefinitely.

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Section: An Alternative Approachmentioning

confidence: 99%

Modelling ecological systems in a changing world

Evans

2012

Phil. Trans. R. Soc. B

157

184

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“…The data have contributed to new and existing research studies, publications, and management programs for both Smithsonian researchers and an increasing number of organizations from the region (e.g., Renken and Mumby, 2009). …”

Section: Environmental Monitoring Systemmentioning

confidence: 99%

Proceedings of the Smithsonian Marine Science Symposium

Lang¹,

Macintyre²,

Rützler³

2009

Smithsonian Contributions to the Marine Sciences

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s m i t h s o n i a n c o n t r i b u t i o n s t o t h e m a r i n e s c i e n c e s • n u m b e r 3 8 SERIES PUBLICATIONS OF THE SMITHSONIAN INSTITUTIONEmphasis upon publication as a means of "diffusing knowledge" was expressed by the fi rst Secretary of the Smithsonian. In his formal plan for the Institution, Joseph Henry outlined a program that included the following statement: "It is proposed to publish a series of reports, giving an account of the new discoveries in science, and of the changes made from year to year in all branches of knowledge." This theme of basic research has been adhered to through the years by thousands of titles issued in series publications under the Smithsonian imprint, commencing with Smithsonian Contributions to Knowledge in 1848 and continuing with the following active series: Smithsonian Contributions to Anthropology Smithsonian Contributions to Botany Smithsonian Contributions in History and Technology Smithsonian Contributions to the Marine Sciences Smithsonian Contributions to Museum Conservation Smithsonian Contributions to Paleobiology Smithsonian Contributions to ZoologyIn these series, the Institution publishes small papers and full-scale monographs that report on the research and collections of its various museums and bureaus. The Smithsonian Contributions Series are distributed via mailing lists to libraries, universities, and similar institutions throughout the world.Manuscripts submitted for series publication are received by the Smithsonian Institution Scholarly Press from authors with direct affi liation with the various Smithsonian museums or bureaus and are subject to peer review and review for compliance with manuscript preparation guidelines. General requirements for manuscript preparation are on the inside back cover of printed volumes. For detailed submissions requirements and to review the "Manuscript Preparation and Style Guide for Authors," visit the Submissions page at www.scholarlypress.si.edu. The paper used in this publication meets the minimum requirements of the American National Standard for Permanence of Paper for Printed Library Materials Z39. Foreword N early two-thirds of Earth's surface is covered by the ocean, a global system essential to all life. Impacts on one part of the ocean can have worldwide effects. The ocean moderates our climate, provides valuable resources, and produces at least half the oxygen we breathe: it makes our planet livable. We know little, however, about the physical, chemical, geological, and biological aspects of this crucial life support system. s m i t h s o n i a n c o n t r i b u t i o n s t o t h e m a r i n S M I T H S O N I A N C O N T R I B U T I O N S T O T H E M A R I N E S C I E N C E S MARINE BIODIVERSITY, EVOLUTION, AND SPECIATION S M I T H S O N I A N C O N T R I B U T I O N S T O T H E M A R I N E S C I E N C E S i i i • S M I T H S O N I A N C O N T R I B U T I O N S T O T H E M A R I N E S C I E N C E SThe Smithsonian Institution, in efforts to increase knowledge about the ocean, has established a ...

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“…Some of the issues we have raised in relation to limited data availability can possibly be overcome using alternative approaches such as Bayesian belief networks (BBNs; e.g., Wooldridge and Done 2004, Wooldridge et al 2005, Renken and Mumby 2009), although BBN approaches are perhaps less transparent for non-scientist end users and existing BBN applications for coral reef systems are not spatially explicit. Importantly, the most robust management and associated decision support will attempt to utilize a toolbox of several model types.…”

Section: General Categories Specific Issuesmentioning

confidence: 99%

Regional-scale scenario modeling for coral reefs: a decision support tool to inform management of a complex system

Melbourne-Thomas¹,

Johnson²,

Fung³

et al. 2011

Ecological Applications

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Abstract. The worldwide decline of coral reefs threatens the livelihoods of coastal communities and puts at risk valuable ecosystem services provided by reefs. There is a pressing need for robust predictions of potential futures of coral reef and associated human systems under alternative management scenarios. Understanding and predicting the dynamics of coral reef systems at regional scales of tens to hundreds of kilometers is imperative, because reef systems are connected by physical and socioeconomic processes across regions and often across international boundaries. We present a spatially explicit regional-scale model of ecological dynamics for a general coral reef system. In designing our model as a tool for decision support, we gave precedence to portability and accessibility; the model can be parameterized for dissimilar coral reef systems in different parts of the world, and the model components and outputs are understandable for nonexperts. The model simulates local-scale dynamics, which are coupled across regions through larval connectivity between reefs. We validate our model using an instantiation for the Meso-American Reef system. The model realistically captures local and regional ecological dynamics and responds to external forcings in the form of harvesting, pollution, and physical damage (e.g., hurricanes, coral bleaching) to produce trajectories that largely fall within limits observed in the real system. Moreover, the model demonstrates behaviors that have relevance for management considerations. In particular, differences in larval supply between reef localities drive spatial variability in modeled reef community structure. Reef tracts for which recruitment is low are more vulnerable to natural disturbance and synergistic effects of anthropogenic stressors. Our approach provides a framework for projecting the likelihood of different reef futures at local to regional scales, with important applications for the management of complex coral reef systems.

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Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach

Cited by 62 publications

References 80 publications

Modelling ecological systems in a changing world

Modelling ecological systems in a changing world

Proceedings of the Smithsonian Marine Science Symposium

Regional-scale scenario modeling for coral reefs: a decision support tool to inform management of a complex system

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