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Quantifying the Adaptive Cycle.

Angeler DG, Allen CR, Garmestani AS, Gunderson LH, Hjerne O, Winder M - PLoS ONE (2015)

Bottom Line: The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems.All predictions were supported by our analyses.Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Stockholm University, Department of Ecology, Evolution and Plant Sciences, SE- 106 91, Stockholm, Sweden.

ABSTRACT
The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

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Multivariate ordination.Nonmetric multidimensional scaling (NMDS) ordinations showing seasonal averages of water quality trajectories during spring and summer in the coastal and offshore site between 1994 and 2011. The length of each arrow reflects change from one sampling year to the next.
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pone.0146053.g004: Multivariate ordination.Nonmetric multidimensional scaling (NMDS) ordinations showing seasonal averages of water quality trajectories during spring and summer in the coastal and offshore site between 1994 and 2011. The length of each arrow reflects change from one sampling year to the next.

Mentions: The abiotic environment differed between both seasons at the coastal and offshore site, with average salinity, nutrients (phosphate, DIN), Secchi depth (indicating light conditions) and mixed layer depth being lowest in summer and water temperature being lowest in spring at both sites (Fig 3). Also phytoplankton biomass, measured as chlorophyll a, was lower in summer compared to spring at the coastal and offshore site (Fig 3). The differences in the abiotic conditions between seasons were also evident in the NMDS analysis, with spring and summer patterns clearly separated in ordination space (Fig 4). The between-year variability in water quality was higher in spring compared to summer, and both sites showed similar patterns of change in each season during the study period (Fig 4).


Quantifying the Adaptive Cycle.

Angeler DG, Allen CR, Garmestani AS, Gunderson LH, Hjerne O, Winder M - PLoS ONE (2015)

Multivariate ordination.Nonmetric multidimensional scaling (NMDS) ordinations showing seasonal averages of water quality trajectories during spring and summer in the coastal and offshore site between 1994 and 2011. The length of each arrow reflects change from one sampling year to the next.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4696843&req=5

pone.0146053.g004: Multivariate ordination.Nonmetric multidimensional scaling (NMDS) ordinations showing seasonal averages of water quality trajectories during spring and summer in the coastal and offshore site between 1994 and 2011. The length of each arrow reflects change from one sampling year to the next.
Mentions: The abiotic environment differed between both seasons at the coastal and offshore site, with average salinity, nutrients (phosphate, DIN), Secchi depth (indicating light conditions) and mixed layer depth being lowest in summer and water temperature being lowest in spring at both sites (Fig 3). Also phytoplankton biomass, measured as chlorophyll a, was lower in summer compared to spring at the coastal and offshore site (Fig 3). The differences in the abiotic conditions between seasons were also evident in the NMDS analysis, with spring and summer patterns clearly separated in ordination space (Fig 4). The between-year variability in water quality was higher in spring compared to summer, and both sites showed similar patterns of change in each season during the study period (Fig 4).

Bottom Line: The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems.All predictions were supported by our analyses.Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Stockholm University, Department of Ecology, Evolution and Plant Sciences, SE- 106 91, Stockholm, Sweden.

ABSTRACT
The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Show MeSH
Related in: MedlinePlus