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Multi-scale Drivers of Spatial Variation in Old-Growth Forest Carbon Density Disentangled with Lidar and an Individual-Based Landscape Model

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Abstract

Forest ecosystems are the most important terrestrial carbon (C) storage globally, and presently mitigate anthropogenic climate change by acting as a large and persistent sink for atmospheric CO2. Yet, forest C density varies greatly in space, both globally and at stand and landscape levels. Understanding the multi-scale drivers of this variation is a prerequisite for robust and effective climate change mitigation in ecosystem management. Here, we used airborne light detection and ranging (Lidar) and a novel high-resolution simulation model of landscape dynamics (iLand) to identify the drivers of variation in C density for an old-growth forest landscape in Oregon, USA. With total ecosystem C in excess of 1 Gt ha−1 these ecosystems are among the most C-rich globally. Our findings revealed considerable spatial variability in stand-level C density across the landscape. Notwithstanding the distinct environmental gradients in our mountainous study area only 55.3% of this variation was explained by environmental drivers, with radiation and soil physical properties having a stronger influence than temperature and precipitation. The remaining variation in C stocks was largely attributable to emerging properties of stand dynamics (that is, stand structure and composition). Not only were density- and size-related indicators positively associated with C stocks but also diversity in composition and structure, documenting a close link between biodiversity and ecosystem functioning. We conclude that the complexity of old-growth forests contributes to their sustained high C levels, a finding that is relevant to managing forests for climate change mitigation.

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Acknowledgments

This study was funded by a Marie Curie Fellowship awarded to R. Seidl under the European Community’s Seventh Framework Program (Grant agreement 237085). We are grateful for the support from National Science Foundation Grant DEB 08-23380, the USDA Forest Service, Pacific Northwest Research Station, and from the H.J. Andrews community for making available data for this study. We thank M. Liermann, NOAA’s Northwest Fisheries Science Center for statistical insight. We are furthermore grateful to B. Bond, Oregon State University, and V. R. Kane, University of Washington, as well as to two anonymous reviewers for helpful comments on an earlier version of the manuscript.

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Authors and Affiliations

  1. Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, Corvallis, Oregon, USA

    Rupert Seidl, Robert J. Pabst & Keith Olsen

  2. Institute of Silviculture, Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria

    Rupert Seidl & Werner Rammer

  3. USDA Forest Service, Pacific Northwest Research Station, Corvallis, Oregon, USA

    Thomas A. Spies

  4. USDA Forest Service, Pacific Northwest Research Station, Seattle, Washington, USA

    E. Ashley Steel

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  1. Rupert Seidl
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  2. Thomas A. Spies
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  3. Werner Rammer
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  4. E. Ashley Steel
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  5. Robert J. Pabst
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  6. Keith Olsen
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Correspondence to Rupert Seidl.

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Authors Contributions

RS designed the study, developed the model, performed the research, analyzed the data, and wrote the paper; TAS contributed to study design, data analysis, and writing; WR contributed new methods and models, assisted in research and data analysis, and contributed to writing; EAS contributed new methods and models, and helped writing the paper; RJP assisted in performing the research and analyzing the data, and contributed to writing the paper; KO assisted in performing the research and analyzing the data.

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Seidl, R., Spies, T.A., Rammer, W. et al. Multi-scale Drivers of Spatial Variation in Old-Growth Forest Carbon Density Disentangled with Lidar and an Individual-Based Landscape Model. Ecosystems 15, 1321–1335 (2012). https://doi.org/10.1007/s10021-012-9587-2

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