A novel method for estimation of wild fire intensity based on ash pH and soil microarthropod community

Citation
N. Henig-sever et al., A novel method for estimation of wild fire intensity based on ash pH and soil microarthropod community, PEDOBIOLOG, 45(2), 2001, pp. 98-106
Citations number
37
Categorie Soggetti
Environment/Ecology
Journal title
PEDOBIOLOGIA
ISSN journal
00314056 → ACNP
Volume
45
Issue
2
Year of publication
2001
Pages
98 - 106
Database
ISI
SICI code
0031-4056(200103)45:2<98:ANMFEO>2.0.ZU;2-K
Abstract
Wild fires are a complex and unpredictable phenomenon. Post hoc estimation of wild fire intensity is important in understanding the ecological impact of fire on ecosystems and their post fire regeneration. The aim of the pres ent study was to evaluate a novel method for fire intensity estimation, bas ed on measurements of post-fire ash pH and soil microarthropod community. E stimation of fire intensity by the novel method was compared to estimation by the mean minimum diameter of burned branch technique (MMDB), described b y Moreno & Oechel (1989). The study was carried out in a Pinus halepensis M ill. forest on Mt. Carmel that burned in a wildfire in October 1998. The in tensity of the fire was estimated by measuring thickness and pH of the ash layer under the canopy projection of burned trees, as well as by the MMDB t echnique. Variations in arthropod community were monitored in soil samples collected under the burned trees. Ash accumulation and increase of the ash layer pH were directly related to fire intensity. A positive correlation wa s found between the ash layer pH and minimum diameter of burned branches, w ith increasing fire intensities. A negative correlation was found between t he size of microarthropod community and fire intensity, which also affected the composition of the arthropod community. Thus, estimation of fire inten sity by integration of two factors, pH of the ash layer and composition of the microarthropod community, can give a wider understanding of fire impact on ecosystems. This integrated method is reliable, quick and inexpensive. Estimation of fire intensity can also be important for prediction of recove ry time of the whole ecosystem.