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The Impact of Multiple Drivers on Marine Systems: Novel approaches for studying structural changes
Stockholm University, Faculty of Science, Stockholm Resilience Centre.ORCID iD: 0000-0002-7410-6794
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Human action is transforming the species composition, biogeochemistry and habitats of the world’s oceans at unprecedented rates. The cumulative effect of natural and anthropogenic drivers is challenging to measure, in part due to indirect effects and the complexity of marine systems. Building on the theory of complex adaptive systems, this thesis aims to increase our understanding of how complex, heterogeneous marine social-ecological systems (SES) may respond to changing conditions. This thesis integrates resilience research with network science and describes change and structural patterns at several SES scales in order to advance our knowledge on the effects of multiple drivers.

Paper I proposes a new, quantitative fish stock collapse definition, that accounts for fish stock dynamics and enables standardization and thus comparability across a large number of commercial fish stocks. Recognizing that substantial ecosystem changes are part of SES dynamics, in Paper II we review marine regime shifts worldwide to specify how co-occurring bundles of drivers are related to degraded ecosystem services for management purposes. A more detailed ecological study on regime shifts was performed in Papers III and IV. Paper III describes the late-1980s central Baltic Sea regime shift based on a food-web model. Paper IV uses a novel structural network analysis approach to detect functional shifts in complex food webs. The results of Paper IV imply that the Baltic Sea regime shift may not be a systemwide shift. Paper V uses a network approach to analyze fishing strategy diversification and social-ecological connectivity among Swedish Baltic Sea fishers, indicating that natural resource management evaluations should not be limited only to ecosystem conditions but also take account of social conditions.

Overall, this thesis provides empirical evidence for the emerging perspective that marine resource science and management must account for the complexity of system elements in order to ensure the provision of ecosystem services in the future. The first application of Exponential Random Graph Modeling in ecology and an improved fish stock collapse definition provide new advanced tools for studying oceans from an SES perspective in the future.

Place, publisher, year, edition, pages
Stockholm: Stockholm Resilience Centre, Stockholm University , 2016. , 60 p.
National Category
Environmental Sciences
Research subject
Natural Resources Management
Identifiers
URN: urn:nbn:se:su:diva-129280ISBN: 978-91-7649-414-1 (print)OAI: oai:DiVA.org:su-129280DiVA: diva2:922688
Public defence
2016-06-03, Nordenskiöldsalen, Geovetenskapens hus, Svante Arrhenius väg 12, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 5: Manuscript.

Available from: 2016-05-11 Created: 2016-04-19 Last updated: 2017-02-24Bibliographically approved
List of papers
1. When is a fish stock collapsed?
Open this publication in new window or tab >>When is a fish stock collapsed?
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(English)Manuscript (preprint) (Other academic)
National Category
Biological Sciences
Research subject
Natural Resources Management
Identifiers
urn:nbn:se:su:diva-129506 (URN)
Available from: 2016-04-24 Created: 2016-04-24 Last updated: 2016-04-28Bibliographically approved
2. Marine regime shifts: drivers and impacts on ecosystems services
Open this publication in new window or tab >>Marine regime shifts: drivers and impacts on ecosystems services
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2015 (English)In: Philosophical Transactions of the Royal Society of London. Biological Sciences, ISSN 0962-8436, E-ISSN 1471-2970, Vol. 370, no 1659, 20130273Article in journal (Refereed) Published
Abstract [en]

Marine ecosystems can experience regime shifts, in which they shift from being organized around one set of mutually reinforcing structures and processes to another. Anthropogenic global change has broadly increased a wide variety of processes that can drive regime shifts. To assess the vulnerability of marine ecosystems to such shifts and their potential consequences, we reviewed the scientific literature for 13 types of marine regime shifts and used networks to conduct an analysis of co-occurrence of drivers and ecosystem service impacts. We found that regime shifts are caused by multiple drivers and have multiple consequences that co-occur in a non-random pattern. Drivers related to food production, climate change and coastal development are the most common co-occurring causes of regime shifts, while cultural services, biodiversity and primary production are the most common cluster of ecosystem services affected. These clusters prioritize sets of drivers for management and highlight the need for coordinated actions across multiple drivers and scales to reduce the risk of marine regime shifts. Managerial strategies are likely to fail if they only address well-understood or data-rich variables, and international cooperation and polycentric institutions will be critical to implement and coordinate action across the scales at which different drivers operate. By better understanding these underlying patterns, we hope to inform the development of managerial strategies to reduce the risk of high-impact marine regime shifts, especially for areas of the world where data are not available or monitoring programmes are not in place.

Keyword
regime shifts, critical transitions, drivers, ecosystem services, networks
National Category
Biological Sciences Earth and Related Environmental Sciences
Research subject
Sustainability Science; Natural Resources Management
Identifiers
urn:nbn:se:su:diva-113112 (URN)10.1098/rstb.2013.0273 (DOI)000346147200011 ()
Note

AuthorCount:5;

Available from: 2015-02-11 Created: 2015-01-23 Last updated: 2017-12-04Bibliographically approved
3. Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea
Open this publication in new window or tab >>Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea
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2013 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 10, e75439Article in journal (Refereed) Published
Abstract [en]

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system's resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web.

National Category
Engineering and Technology Ecology
Research subject
Natural Resources Management
Identifiers
urn:nbn:se:su:diva-96098 (URN)10.1371/journal.pone.0075439 (DOI)000325501300028 ()
Note

AuthorCount:6;

Available from: 2013-11-14 Created: 2013-11-11 Last updated: 2017-12-06Bibliographically approved
4. Regime shifts in marine communities: a complex systems perspective on food web dynamics
Open this publication in new window or tab >>Regime shifts in marine communities: a complex systems perspective on food web dynamics
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2016 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 283, no 1825, 20152569Article in journal (Refereed) Published
Abstract [en]

Species composition and habitats are changing at unprecedented rates in the world's oceans, potentially causing entire food webs to shift to structurally and functionally different regimes. Despite the severity of these regime shifts, elucidating the precise nature of their underlying processes has remained difficult. We address this challenge with a new analytic approach to detect and assess the relative strength of different driving processes in food webs. Our study draws on complexity theory, and integrates the network-centric exponential random graph modelling (ERGM) framework developed within the social sciences with community ecology. In contrast to previous research, this approach makes clear assumptions of direction of causality and accommodates a dynamic perspective on the emergence of food webs. We apply our approach to analysing food webs of the Baltic Sea before and after a previously reported regime shift. Our results show that the dominant food web processes have remained largely the same, although we detect changes in their magnitudes. The results indicate that the reported regime shift may not be a system-wide shift, but instead involve a limited number of species. Our study emphasizes the importance of community-wide analysis on marine regime shifts and introduces a novel approach to examine food webs.

Keyword
regime shift, complex adaptive systems, exponential random graph model, Baltic Sea, food web, motifs
National Category
Biological Sciences
Research subject
Natural Resources Management
Identifiers
urn:nbn:se:su:diva-129281 (URN)10.1098/rspb.2015.2569 (DOI)
Available from: 2016-04-19 Created: 2016-04-19 Last updated: 2017-11-30Bibliographically approved
5. How patterns of interactions between and among fishing strategies and targeted fish species affect adaptive capacity: an integrated analysis of the Baltic Sea fishery 1996-2009
Open this publication in new window or tab >>How patterns of interactions between and among fishing strategies and targeted fish species affect adaptive capacity: an integrated analysis of the Baltic Sea fishery 1996-2009
(English)Manuscript (preprint) (Other academic)
National Category
Biological Sciences
Research subject
Natural Resources Management
Identifiers
urn:nbn:se:su:diva-129505 (URN)
Available from: 2016-04-24 Created: 2016-04-24 Last updated: 2016-04-28Bibliographically approved

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