Next Article in Journal
How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?
Previous Article in Journal
Arthropod Diversity and Functional Importance in Old-Growth Forests of North America
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Forests 2017, 8(4), 99; doi:10.3390/f8040099

Estimating Large Area Forest Carbon Stocks—A Pragmatic Design Based Strategy

1
European Forest Institute, Sant Pau Art Nouveau Site, Sant Leopold Pavilion, St. Antoni M. Claret, 167 08025 Barcelona, Spain
2
Department of Forest Ecosystem Science, The University of Melbourne, 4 Water Street, Creswick, VIC 3363, Australia
3
School of Mathematical and Geospatial Sciences, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia
4
New South Wales Department of Industry—Lands, Forest Science, Locked Bag 5123, Parramatta, NSW 2124, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: P. K. Ramachandran Nair
Received: 17 January 2017 / Revised: 8 March 2017 / Accepted: 20 March 2017 / Published: 26 March 2017
View Full-Text   |   Download PDF [1208 KB, uploaded 26 March 2017]   |  

Abstract

Reducing uncertainty in forest carbon estimates at local and regional scales has become increasingly important due to the centrality of the terrestrial carbon cycle in issues of climate change. In Victoria, Australia, public natural forests extend over 7.2 M ha and constitute a significant and important carbon stock. Recently, a wide range of approaches to estimate carbon stocks within these forests have been developed and applied. However, there are a number of data and estimation limitations associated with these studies. In response, over the last five years, the State of Victoria has implemented a pragmatic plot-based design consisting of pre-stratified permanent observational units located on a state-wide grid. Using the ground sampling grid, we estimated aboveground and belowground carbon stocks (including soil to 0.3 m depth) in both National Parks and State Forests, across a wide range of bioregions. Estimates of carbon stocks and associated uncertainty were conducted using simple design based estimators. We detected significantly more carbon in total aboveground and belowground components in State Forests (408.9 t ha−1, 95% confidence interval 388.8–428.9 t ha−1) than National Parks (267.6 t ha−1, 251.9–283.3 t ha−1). We were also able to estimate forest carbon stocks (and associated uncertainty) for 21 strata that represent all of Victoria’s bioregions and public tenures. It is anticipated that the lessons learnt from this study may support the discussion on planning and implementing low cost large area forest carbon stock sampling in other jurisdictions. View Full-Text
Keywords: Victorian Forest Monitoring Program; National Forest Inventory; carbon stocks; designed based estimation Victorian Forest Monitoring Program; National Forest Inventory; carbon stocks; designed based estimation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Haywood, A.; Stone, C. Estimating Large Area Forest Carbon Stocks—A Pragmatic Design Based Strategy. Forests 2017, 8, 99.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Forests EISSN 1999-4907 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top