4.5 Article

Overstory-derived surface fuels mediate plant species diversity in frequently burned longleaf pine forests

Journal

ECOSPHERE
Volume 8, Issue 10, Pages -

Publisher

WILEY
DOI: 10.1002/ecs2.1964

Keywords

light detection and ranging (LiDAR); overstory-derived fuels; Pinus palustris; prescribed fire; species richness; structural equation model

Categories

Funding

  1. Department of Defense [RC-2243]
  2. Earthwatch Institute

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Frequently burned low-latitude coniferous forests maintain a high-diversity understory. Longleaf pine (Pinus palustris Mill.) forests and woodlands have exceptionally high diversity at fine scales and very frequent fire return intervals (1-3 yr). Furthermore, the positive association between high-frequency, low-intensity surface fires and high species richness in longleaf pine ecosystems is well documented but poorly understood. Recent studies have demonstrated additional linkages between specific fuel assemblages and fire intensity at small spatial scales. In this study, we build upon both patterns by using long-term datasets to examine the relationship between fire and specific fuel types, and how the combination of these two elements contributes to ground cover species diversity. We used 11 yr of monitoring data from longleaf pine forests at Eglin Air Force Base, Florida (USA), to parameterize a structural equation model that examines causal relationships between fuels and fire history on ground cover plant diversity. Overstory-derived fuels, including pine needle litter, pine cones, and other 10 and 100-h woody fuels, had the greatest positive impact on diversity in relatively open-canopied, frequently burned reference stands. A second model examined surface fuel components originating from the forest overstory as characterized by airborne light detection and ranging and found that pine needle litter was positively associated with canopy density. Our parameter estimates for causal relationships between easily measured variables and plant diversity will allow for the development of management models at the stand scale while being informed by fuels measured at the plot scale.

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