Citation:

Eason, T., A. Garmestani, AND D. Angeler. Spatiotemporal variability in Swedish lake ecosystems. PLOS ONE . Public Library of Science, San Francisco, CA, 17(3):e0265571, (2022). https://doi.org/10.1371/journal.pone.0265571

Impact/Purpose:

Lake ecosystems are complex and adaptive; hence, their conditions vary over time and across scale.  Although they are often able to maintain function, processes and structure, anthropogenic activity coupled with accelerating environmental change can have dire impacts on these systems causing their resilience to erode, thereby reducing their capacity to withstand disturbances and resulting in undesirable consequences.   Accordingly, monitoring and managing the condition of lakes is critically important.

Description:

Studying ecosystem dynamics is critical to monitoring and managing linked systems of humans and nature. Due to the growth of tools and techniques for collecting data, information on the condition of these systems is more widely available. While there are a variety of approaches for mining and assessing data, there is a need for methods to detect latent characteristics in ecosystems linked to temporal and spatial patterns of change. Resilience-based approaches have been effective at not only identifying environmental change but also providing warning in advance of critical transitions in social-ecological systems (SES). In this study, we examine the usefulness of one such method, Fisher Information (FI) for spatiotemporal analysis. FI is used to assess patterns in data and has been established as an effective tool for capturing complex system dynamics to include regimes and regime shifts. We employed FI to assess the biophysical condition of eighty-five Swedish lakes from 1996–2018. Results showed that FI captured spatiotemporal changes in the Swedish lakes and identified distinct spatial patterns above and below the Limes Norrlandicus, a hard ecotone boundary which separates northern and southern ecoregions in Sweden. Further, it revealed that spatial variance changed approaching this boundary. Our results demonstrate the utility of this resilience-based approach for spatiotemporal and spatial regimes analyses linked to monitoring and managing critical watersheds and waterbodies impacted by accelerating environmental change.

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