Linking patterns and processes across scales: the application of scale-transition theory to algal dynamics on rocky shores

Author:

Benedetti-Cecchi Lisandro1,Tamburello Laura1,Bulleri Fabio12,Maggi Elena1,Gennusa Vincenzo12,Miller Matthew34

Affiliation:

1. Department of Biology, University of Pisa, CoNISMa, Via Derna 1, Pisa, Italy

2. Dipartimento di Science Botaniche, Ecologiche e Geologiche, Università di Sassari, Via Piandanna 4, 07100, Sassari, Italy

3. Department of Mathematics, 1523 Greene Street, University of South Carolina, Columbia, SC 29208, USA

4. Mathematical Biosciences Institute, Jennings Hall, 1735 Neil Avenue Columbus, OH 43210, USA

Abstract

SUMMARY Understanding how species and environments respond to global anthropogenic disturbances is one of the greatest challenges for contemporary ecology. The ability to integrate modeling, correlative and experimental approaches within individual research programs will be key to address large-scale, long-term environmental problems. Scale-transition theory (STT) enables this level of integration, providing a powerful framework to link ecological patterns and processes across spatial and temporal scales. STT predicts the large-scale (e.g. regional) behavior of a system on the basis of nonlinear population models describing local (e.g. patch-scale) dynamics and the interaction between these nonlinearities and spatial variation in population abundance or environmental conditions. Here we use STT to predict the dynamics of turf-forming algae on rocky shores at Capraia Island, in the northwest Mediterranean. We developed a model of algal turf dynamics based on density-dependent growth that included the effects of local interactions with canopy algae. The model was parameterized with field data and used to scale up the dynamics of algal turfs from the plot scale (20×20 cm) to the island scale (tens of km). The interaction between nonlinear growth and spatial variance in cover of turfing algae emerged as a key term to translate the local dynamics up to the island scale. The model successfully predicted short-term and long-term mean values of turf cover estimated independently from a separate experiment. These results illustrate how STT can be used to identify the relevant mechanisms that drive large-scale changes in ecological communities. We argue that STT can contribute significantly to the connection between biomechanics and ecology, a synthesis that is at the core of the emerging field of ecomechanics.

Publisher

The Company of Biologists

Subject

Insect Science,Molecular Biology,Animal Science and Zoology,Aquatic Science,Physiology,Ecology, Evolution, Behavior and Systematics

Reference44 articles.

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