Normalized burn ratios link fire severity with patterns of avian occurrence
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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.
| 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) | Coop Res Unit Atlanta, Core Science Analytics and Synthesis, Core Science Analytics, Synthesis, and Libraries, GAP Analysis Project |
| Description | 14 p. |
| First page | 1537 |
| Last page | 1550 |
| Online Only (Y/N) | N |
| Additional Online Files (Y/N) | N |
| Google Analytic Metrics | Metrics page |