Journal article
Identifying habitats at risk: simple models reveal complex ecosystem dynamics
Ecological Applications, Vol.25(2), pp.573-587
2015
Abstract
The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predictbecause locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of nonlinear dynamics in ecosystems.
Details
- Title
- Identifying habitats at risk: simple models reveal complex ecosystem dynamics
- Authors
- Paul S Maxwell (Author) - Griffith UniversityKylie A Pitt (Author) - Griffith UniversityAndrew D Olds (Author) - Griffith UniversityDavid Rissik (Author) - Griffith UniversityRod M Connolly (Author) - Griffith University
- Publication details
- Ecological Applications, Vol.25(2), pp.573-587
- Publisher
- Ecological Society of America
- Date published
- 2015
- DOI
- 10.1890/14-0395.1
- ISSN
- 1051-0761
- Copyright note
- Copyright © 2015 Ecological Society of America. Reproduced here in accordance with the publisher's copyright policy.
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99450093502621
- Output Type
- Journal article
Metrics
391 File views/ downloads
1005 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Ecology
- Environmental Sciences
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites