Ewa Siwicka
University of Auckland
4 Papers
Ewa Siwicka is an academic researcher from University of Auckland. The author has contributed to research in topics: Ecosystem & Scenario planning. The author has an hindex of 3, co-authored 4 publications.
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Papers
Linking changes in species-trait relationships and ecosystem function using a network analysis of traits.
TL;DR: It is demonstrated that under medium (150g Nm-2 ) N treatment, functional diversity remained consistent, whereas increasing disturbance to high (600g Ntidal sandflat) N treatment affected the species-trait network structure and caused merging of functional clusters implying a loss of functional trait diversity.
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Beyond the single index: Investigating ecological mechanisms underpinning ecosystem multifunctionality with network analysis
Ewa Siwicka,Rebecca V. Gladstone-Gallagher,Rebecca V. Gladstone-Gallagher,Judi E. Hewitt,Simon F. Thrush +4 more
TL;DR: In this article, a multivariate network analysis that uses network theory to assess multifunctionality in terms of the relationships between species' functional traits, environmental characteristics, and functions is presented.
10
Advancing approaches for understanding the nature-people link
Ewa Siwicka,Simon F. Thrush +1 more
TL;DR: The Bayesian Belief Multifunctionality Framework can deliver insightful messages into multifunctionality links helping to reveal the multifunctional nature of diverse and complex natural ecosystems.
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Old Tools, New Ways of Using Them: Harnessing Expert Opinions to Plan for Surprise in Marine Socio-Ecological Systems
Rebecca V. Gladstone-Gallagher,Rebecca V. Gladstone-Gallagher,Julie A. Hope,Richard H. Bulmer,Dana Clark,Dana Clark,Fabrice Stephenson,Stephanie Mangan,Vera Rullens,Ewa Siwicka,Samuel F. Thomas,Conrad A. Pilditch,Candida Savage,Candida Savage,Simon F. Thrush +14 more
TL;DR: In this article, the authors discuss how current tools for developing risk assessments and scenario planning, coupled with expert opinions, can be adapted to bridge gaps in quantitative data, enabling scientists and managers to prepare for many plausible futures.