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Modeling the distribution of white spruce (Picea glauca) for Alaska with high accuracy: an open access role-model for predicting tree species in last remaining wilderness areas

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Abstract

Most wilderness areas still lack accurate distribution information on tree species. We met this need with a predictive GIS modeling approach, using freely available digital data and computer programs to efficiently obtain high-quality species distribution maps. Here we present a digital map with the predicted distribution of white spruce (Picea glauca) in Alaska (4 km resolution, accuracy over 90%). Our presented concept represents a role-model for predicting tree species distribution for remote areas world-wide. Although this model intends to be accurate in making predictions rather than to give detailed biological mechanistic explanations, it can also be used as a baseline for further research and testable hypothesis on the importance of the environmental variables used to build a generalizable model. Further, we emphasize that work like presented here is a pre-condition for assessing human impacts and impacts of climate change on species distribution in a quantitative and transparent fashion, allowing for improved sustainable decision-making world-wide.

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Abbreviations

AGDC:

Alaska Geospatial Data Clearinghouse

CODATA:

Committee on Data for Science and Technology

ESRI:

Environmental Systems Research Institute

FGDC:

Federal Geographic Data Committee

FIA:

Forest inventory and analysis

GIS:

Geographic information system

ICSU:

International Council for Science

IDW:

Inverse distance weighting

IPY:

International Polar Year

NAD83:

North American Datum of 1983

NBII:

National Biological Information Infrastructure

NDVI:

Normalized difference vegetation index

NSF:

National Science Foundation

OA:

Open access

OECD:

Organisation for Economic Collaboration and Development

PRISM:

Parameter-elevation regressions on independent slopes model

ROC:

Receiver operating characteristic

SDM:

Species distribution models

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Acknowledgments

We want to thank everybody who helped: Data for model evaluation were kindly supplied by C. Roland (Central Alaska Network Vegetation Monitoring Program, National Park Service), T. Loomis (ABRinc), S. Winslow (University of Alaska, Fairbanks), and K. Winterberger (Pacific Northwest Experiment Station). We furthermore want to thank V. Steen and T. McMillan for fruitful discussions. Of course, we highly appreciate the contributions of the two reviewers, who significantly helped improve this article. Thanks also to the UAF Department of Natural Resources Management, as well as the Department of Biology and Wildlife for providing technical support. B. Ohse wants to thank the Ev. Studienwerk Villigst and the Fulbright Commission for help fund her studies at UAF. This is EWHALE lab publication # 47.

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Authors and Affiliations

  1. Institute of Botany and Landscape Ecology, University of Greifswald, Grimmer Straße 88, 17489, Greifswald, Germany

    Bettina Ohse

  2. Forest Science Department, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA

    Bettina Ohse & Glenn P. Juday

  3. EWHALE Lab, Biology and Wildlife Department, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, 99775-7000, USA

    Falk Huettmann

  4. Herbarium and Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Museum of the North, 907 Yukon Dr., PO Box 756960, Fairbanks, AK, 99775-6960, USA

    Stefanie M. Ickert-Bond

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  1. Bettina Ohse
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  2. Falk Huettmann
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  3. Stefanie M. Ickert-Bond
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  4. Glenn P. Juday
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Correspondence to Bettina Ohse.

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Ohse, B., Huettmann, F., Ickert-Bond, S.M. et al. Modeling the distribution of white spruce (Picea glauca) for Alaska with high accuracy: an open access role-model for predicting tree species in last remaining wilderness areas. Polar Biol 32, 1717–1729 (2009). https://doi.org/10.1007/s00300-009-0671-9

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