@article {bnh-4118, title = {Improving forest sampling strategies for assessment of fuel reduction burning}, journal = {Forest Ecology and Management}, volume = {392}, year = {2017}, month = {05/2017}, pages = {78-89}, chapter = {78}, abstract = {

Land managers\ typically make\ post hoc\ assessments of the effectiveness of fuel reduction burning (FRB), but often lack a rigorous sampling framework. A general, but untested, assumption is that variability in soil and fuel properties increases from small (\~{}1\ m) to large spatial scales (\~{}10{\textendash}100\ km). Based on a recently published field-based sampling scheme, we addressed the following questions: (i) How much variability is captured in measurements collected at different spatial scales? (ii) What is the optimal number of sampling plots required for statistically robust characterisation of burnt areas? (iii) How can land managers improve their assessment of the effectiveness of FRB? We found that measurement variability does not increase with scale for all fuel components. Results showed that\ coarse woody debris\ is as variable at the small scale (plot, m) as it is at the landscape scale (km). For certain fuel components, such as litter biomass (in unburnt areas),\ overstorey\ biomass and leaf area, and\ soil properties\ such as total carbon and total nitrogen, samples taken at the small (plot) scale were indicative of variation at the larger scale of an individual FRB and more broadly across the landscape.

We then tested the hypothesis that site stratification can reduce variability between sampling plots and as a consequence will reduce the required number of sampling plots. To test this hypothesis we used Landsat Normalized Difference Vegetation Index (NDVI) across areas treated with FRB and compared the number of sampling plots required to estimate mean fuel biomass with and without stratification. Stratification of burnt areas using remotely sensed vegetation indices reduced the number of sampling plots required. We provide a model of green biomass from Landsat NDVI and make recommendations on how sampling schemes can be improved for assessment of fuel reduction burning.

}, doi = {https://doi.org/10.1016/j.foreco.2017.03.001}, url = {http://www.sciencedirect.com/science/article/pii/S0378112716310751?via\%3Dihub}, author = {Gharun, Mana and Malcolm Possell and Jenkins, Meaghan E. and Lai Fan Poon and Bell, Tina and Adams, Mark A.} } @article {bnh-3416, title = {Production of pyrogenic carbon during planned fires in forests of East Gippsland, Victoria}, journal = {Forest Ecology and Management}, volume = {373}, year = {2016}, month = {08/2016}, pages = {9-16}, chapter = {9}, abstract = {

Management strategies such as planned burning for fuel reduction can help mitigate the effects of wildfires. The amount of biomass consumed is of interest to fire managers as reduction of fuel loads is imperative to reducing the risk and extent of a wildfire event. Biomass regeneration is also of importance for ecosystem recovery and resilience. Pyrogenic carbon (PyC), a product of combustion during both planned and unplanned fires, plays a key role in global carbon stores and balances. A three-year study of planned burning practices examined fires in Lowland temperate Eucalypt forest of south eastern Australia. We collected data on overstorey, understorey, coarse woody debris, fine litter, PyC and soil across nine sites to determine biomass consumption, PyC production and changes in ecosystem carbon during planned burning. Lowland forest showed significant recovery of combustible biomass (fine litter and understorey) one year after planned fire. Across our sites, PyC was produced at a rate of approximately 5\% of the biomass consumed. The PyC produced is destined to become part of soil and litter carbon and contributes to long-term carbon storage. Planned burning had a short-term (\<1\ year) impact on forest carbon balance, and on reduction risk of wildfire and associated losses of biomass carbon, but no long-term impact, through deposition of PyC and recovery of biomass.

}, doi = {10.1016/j.foreco.2016.04.028}, url = {http://www.sciencedirect.com/science/article/pii/S0378112716301979}, author = {Jenkins, Meaghan E. and Bell, Tina and Lai Fan Poon and Cristina Aponte and Adams, Mark A.} }