Abstract

Humans who interact directly with local ecosystems possess traditional ecological knowledge that enables them to detect and predict ecosystem changes. Humans who use scientific ecological methods can use species such as mollusks that lay down annual growth rings to detect past environmental variation and use statistical models to make predictions about future change. We used traditional ecological knowledge shared by local Inupiaq, combined with growth histories of two species of mollusks, at different trophic levels, to study local change in the coastal ecosystems of Kotzebue, Alaska, an area in the Arctic without continuous scientific monitoring. For the mollusks, a combination of the Arctic Oscillation and total Arctic ice coverage, and summer air temperature and summer precipitation explained 79-80% of the interannual variability in growth of the suspension feeding Greenland cockle (Serripes groenlandicus) and the predatory whelk (Neptunea hero) respectively, indicating these mollusks seem to be impacted by local and regional environmental parameters, and should be good biomonitors for change in coastal Alaska. The change experts within the Kotzebue community were the elders and the fishers, and they observed changes in species abundance and behaviors, including benthic species, and infer that a fundamental change in the climate has taken place within the area. We conclude combining traditional and scientific ecological knowledge provides greater insight than either approach alone, and offers a powerful way to document change in an area that otherwise lacks widespread quantitative monitoring.

Highlights

  • The average atmospheric temperature in the Arctic has increased twice as fast as the average temperature for the rest of the world over the past 50 years, and is predicted to continue to increase rapidly over the 100 years (Arctic Climate Impact Assessment, 2005)

  • We examined two Arctic climate indices with potential influence on the region: the Arctic Climate Regime Index (ACRI), and the Arctic Oscillation (AO)

  • We investigated the time-dependence between data in consecutive years, leading us to incorporate two data transformations: 2-year running means of environmental data to reduce the magnitude of interannual variability of environmental data, and a 1-year lag in both the original variables and in their running means to account for the time it may take for physical processes to be reflected in shell growth

Read more

Summary

Introduction

The average atmospheric temperature in the Arctic has increased twice as fast as the average temperature for the rest of the world over the past 50 years, and is predicted to continue to increase rapidly over the 100 years (Arctic Climate Impact Assessment, 2005). The marine and terrestrial ecosystem changes accompanying these rising temperatures have especially strong impacts on the humans who depend on these ecosystems for their survival and quality of life (Morison et al, 2000; Huntington et al, 2012). Whereas many studies of climate change only use key indicators that are physical in nature (e.g., atmospheric concentrations of carbon dioxide, sea surface temperature), we advocate here for combining knowledge from key ecosystem components and key human observers in an integrated approach to monitoring and assessing environmental change, especially in areas without continual monitoring of physical variables

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call