Normalized burn ratios link fire severity with patterns of avian occurrence

Landscape Ecology
By: , and 

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Abstract

Context

Remotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.

Objectives

We evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.

Methods

We identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.

Results

Agreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.

Conclusions

DNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Normalized burn ratios link fire severity with patterns of avian occurrence
Series title Landscape Ecology
DOI 10.1007/s10980-015-0334-x
Volume 31
Issue 7
Year Published 2016
Language English
Publisher Springer
Contributing office(s) Core Science Analytics, Synthesis, and Libraries, Core Science Analytics and Synthesis, Coop Res Unit Atlanta, GAP Analysis Project
Description 14 p.
First page 1537
Last page 1550
Online Only (Y/N) N
Additional Online Files (Y/N) N