Trend analyses and projections using national forest inventory data

Autores/as

  • Greg C Liknes USDA Forest Service
  • Randall S Morin USDA Forest Service
  • Charles D Canham Cary Institute of Ecosystem Studies image/svg+xml

Palabras clave:

forest inventory, forest monitoring, trends, projections, time series, FIA

Resumen

We present a collection of papers derived from the 2012 Forest Inventory and Analysis (FIA) Symposium held on December 4-6, 2012 in Baltimore, MD, USA. The symposium featured 128 oral presentations with nearly 200 attendees from the United States and other countries. A proceedings from the symposium included 75 papers as well as abstracts for all presentations and posters. The symposium theme, Moving from Status to Trends, focused on the ability to perform trend or time series analysis using national forest inventory data. A wide range of topics were covered including forest products, social dimensions of forestry, landscape change, analytical tools, Landsat time series, forest carbon, and many others. Based on these presentations, we have assembled a selection of several papers that presented examples of trend analyses and projections using forest inventory data. This Special Issue contains four of these papers that passed the MCFNS double-blind peer-review by a minimum of three peers.

Biografía del autor/a

  • Greg C Liknes, USDA Forest Service
    Research Physical Scientist, Forest Inentory and Analysis, Northern Research Station
  • Randall S Morin, USDA Forest Service
    Research Forester, Forest Inentory and Analysis, Northern Research Station
  • Charles D Canham, Cary Institute of Ecosystem Studies
    Forest Ecologist, Cary Institute of Ecosystem Studies

Referencias

Cieszewski, C., and McRoberts, R. 2011. Selected Examples of Advanced FIA Data Analysis. Mathematical And Computational Forestry & Natural-Resource Sciences (MCFNS), 3(2), Pp: 96-97. Retrieved last from http://mcfns.com/index.php/Journal/article/view/MCFNS.3-96/MCFNS.3-96 on Sep. 25, 2013.

Clough, B.J., and E.J. Green. 2013. Comparing spatial and non-spatial approaches for predicting forest soil organic carbon at unsampled locations. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), Pp: 115-125. Retrieved from http://mcfns.com/index.php/Journal/article/view/MCFNS175/MCFNS-175.

Gillespie, A.J.R. 1999. Rationale for a national annual forest inventory program. J. For. 97: 16-20.

LaBau, V.J., J.T. Bones, N.P. Kingsley, H.G. Lund, and W.B. Smith. 2007. A history of the Forest Survey in the United States 1830-2004. USDA For. Serv. FS-877. 82 p.

Morin, R.S., G.C. Liknes, comps. 2012. Moving from status to trends: Forest Inventory and Analysis (FIA) Symposium 2012; USDA For. Serv. Gen. Tech. Rep. NRS-P-105. [CD-ROM]. 478 p.

Potter, K.M., and W.W. Hargrove. 2013. Quantitative assessment of predicted climate change pressure on North American tree species. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), Pp: 151-169. Retrieved from http://mcfns.com/index.php/Journal/article/view/MCFNS169/MCFNS-169.

Tavernia, B.G., M.D. Nelson, M. Goerndt, B. Walters, and C. Toney. 2013. Changes in forest habitat classes under alternative climate and land-use change scenarios in the Northeast and Midwest, USA. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), Pp: 135-150. Retrieved from http://mcfns.com/index.php/Journal/article/view/MCFNS165/MCFNS-165.

USDA Forest Service, 2013. Northern forest futures project. Available online at http://www.nrs.fs.fed.us/futures/; last accessed Sep. 9, 2013.

Van Deusen, P.C., and F.A. Roesch. 2013. Trends and projections from annual forest inventory plots and coarsened exact matching. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), Pp: 126-134. Retrieved from http://mcfns.com/index.php/Journal/article/view/MCFNS157/MCFNS-157.

Wear, D.N., R. Huggett, R. Li, B. Perryman, and S. Liu. 2011. Forecasts of forest conditions in U.S. regions under future scenarios. A technical document supporting the Forest Service 2010 RPA Assessment. USDA For. Serv. Gen. Tech. Rep. SRS-170. 101 p.

Publicado

2013-09-30

Número

Sección

Sampling and Natural Resource Inventories

Cómo citar

Trend analyses and projections using national forest inventory data. (2013). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 5(2), 112-114(3). https://www.tmp.17921125833755a190e36a5857.temporary.link/index.php/Journal/article/view/MCFNS_175

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