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A novel method for estimation of wild fire intensity based on ash pH and soil microarthropod community
Pedobiologia 45, 98–106 (2001) © Urban & Fischer Verlag http://www.urbanfischer.de/journals/pedo
A novel method for estimation of wild fire intensity based on ash pH and soil microarthropod community Nava Henig-Sever*, Dina Poliakov and Meir Broza Department of Biology, University of Haifa at Oranim, Tivon 36006, Israel Submitted: 21. July 2000 Accepted: 1. November 2000
Summary 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 present study was to evaluate a novel method for fire intensity estimation, based on measurements of post-fire ash pH and soil microarthropod community. Estimation of fire intensity by the novel method was compared to estimation by the mean minimum diameter of burned branch technique (MMDB), described by Moreno & Oechel (1989). The study was carried out in a Pinus halepensis Mill. forest on Mt. Carmel that burned in a wildfire in October 1998. The intensity 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 technique. 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 was found between the ash layer pH and minimum diameter of burned branches, with increasing fire intensities. A negative correlation was found between the size of microarthropod community and fire intensity, which also affected the composition of the arthropod community. Thus, estimation of fire intensity 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 recovery time of the whole ecosystem. *E-mail corresponding author: [email protected]
0031–4056/01/45/02–98 $ 15.00/0
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Key words: Fire-Intensity, ash, pH, soil-microarthropods, Collembola, minimum diameter of burned branches
Introduction Fires occur frequently in Mediterranean ecosystems around the world. Intensity is frequently used as a characteristic of fire regime (Moreno & Oechel 1989; Moore et al. 1995). The factors that affect fire intensity are usually grouped in three main categories: fuels (load, type, distribution, structure and humidity), meteorology (solar radiation, air temperature, relative humidity and wind speed) and topography (slope and aspect) (Rundel 1981; Christensen 1987; Whelan 1995; Bond & van Wilgen 1996; Viegas 1998). Prediction of fire intensity and fire impact on the ecosystem is limited because of the complexity of the fire phenomenon. Several theoretical models of the interactions between the factors mentioned above have been developed in order to predict fire occurrence and intensity (Rothermel 1991; van Wagner et al. 1992; Weber et al. 1995; Finney 1998; Hesseln et al. 1998; Viegas 1998). Over the last 40 years Byram’s (1959) fire intensity concept, which combines heat release during combustion and rate of fire front spread, has been used for the characterization of prescribed fires (Tolhurst 1995). However, Byram’s concept and the theoretical models do not give a complete picture of the ecological impact of wildfires on ecosystems. Using post-fire indicators of fire severity proved to be useful in understanding ecosystem responses to wildfires. Some of the qualitative approaches that have been used are: color of the ash layer, cool or hot fires and the degree of fuel combustion (Moreno & Oechel 1989). A quantitative estimation of heat output per unit area can be made from the amount of fuel consumed by the fire (Riggan et al. 1994). In the last decades biological indicators have been used for post-fire quantitative estimation of wildfire intensity and in ecological studies of fire impacts on ecosystems. Common biological indicators that are used include: height of leaf scorch, thickness of bark lost, height of leaf char (Moore et al. 1995; Tolhurst 1995), minimum branch diameters remaining after fire and height above ground of plant remains (Moreno & Oechel 1989; Keeley 1998). The minimum branch diameter technique has proved to be a reliable post fire index of wildfire intensity in shrublands, and a good predictor of plant and soil responses to fire severity (Moreno & Oechel 1989, 1991; Rice 1993; Keeley 1998; Perez & Moreno 1998). Nonetheless, in woodlands post hoc estimation of fire intensity has rarely been studied. The aims of the present study were to reveal the impact of fire intensity on the forest bed pH, soil microarthropod community and minimum branch diameters remaining after fire in an Aleppo pine (Pinus halepensis Mill.) forest. According to the results we propose a simple method for estimating wild fire intensity in woodlands, based on measurements of post fire soil and ash pH and soil microarthropod populations.
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Materials and Methods Study site The study was carried out in an Aleppo pine forest on Mt. Carmel, Israel, that was burned in a wildfire in October 1998. Measurements and sampling were taken 26 days post-fire.
Samplings and measurements Burned pine trees were classified into three fire intensity groups – light, medium and high according to the color of the ash layer that accumulated under their canopy projection (Table 1). Pine trees in an adjacent unburned site were chosen as a control group. Each group included seven trees (replications). Tree trunk diameters at breast height (DBH) and the thickness of the ash layer were measured. pH measurements. Ash samples (10 x 10 cm) were collected in the middle of the canopy projection of trees burned at high and medium intensities. Mixed ash and soil samples (1 cm depth) were collected under trees burned at light intensity (because the ash cover was too thin to be separated from the upper soil). Soil samples (1 cm depth) were collected under trees in the unburned site. pH was measured in aqueous saturated pastes made from the ash and soil samples (with a pH meter model PBS 730, El-Hama Instruments, Mevo-Hama, Israel). Simulation of increasing fire intensity. Pine ash collected one week after a wildfire in the Upper Galilee, Israel was sifted (2 mm) and divided into 1 kg sub–samples. To simulate various fire intensities, the sub-samples were heated at 250 °C, 350 °C, 550 °C and 1000 °C for 24 hours in an electrical furnace. pH was measured in saturated pastes made from the unheated and heated ash. Minimum diameter of burned branches. The minimum diameter of burned branches remaining after fire were measured and the mean per tree was calculated according to the MMDB technique described by Moreno & Oechel (1989). The mean minimum diameter of burned branches of the seven trees in each fire intensity group was calculated. Monitoring of microarthropod populations. Ash and soil were sampled using a standard soil corer, 19.6 cm2, to a depth of 15 cm. The samples were collected in the middle of the canopy projection of the burned and unburned trees. From each sample, 200 g was placed for 48 hours in Berlese funnels for extraction of microarthropods. The microarthropods extracted from each sample were identified (Magdalena Gruia, Bucharest) and counted.
Statistic analysis A graph probability plot test was used to check normal distribution of the results. The effect of fire intensity on minimum diameter of burned branches, which had a normal distribution, was analyzed by one-way analysis of variance. Significant results were followed by a Tukey multiple range test (P<0.05). The effects of trunk diameter on fire intensity and of fire intensity on pH, which were not normally distributed, were analyzed by non-parametric procedures (Kruskal Wallis one way test). Correlation was tested between the pH of ash to heating temperature, and between ash pH to minimum diameter of burned branches. The statistic analyses were performed using SYSTAT 8 (1996).
Results A significant difference in trunk diameter of burned trees was observed at various fire intensities (Kruskal Wallis one way test, χ23= 24.13, P < 0.0001). Fire intensity increased with an increase in tree size from light fire under the canopy projection of
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Table 1. Color and thickness (cm) of the ash layer around pine trees burned at various fire intensities
Ash thickness Color
Light cannot be separated from the soil black
Medium 3.6 black-gray
High 6.9 gray-white
trees with a trunk diameter of 20 cm, to high intensity fire under the canopy projection of trees with a trunk diameter of 48 cm. The thickness of the ash layer increased up to 6.9 cm with an increase in fire intensity (Table 1). Ash pH increased with heating temperature and a positive correlation was found between the pH of the ash and heating temperature (Pearson r = 0.99, P = 0.001). pH values were: 10.0 for unheated ash, 10.4, 10.7, 11.7 and 13.0 for ash samples heated at 250˚C, 350˚C, 550˚C and 1000˚C, respectively. A significant increase in the minimum diameter of burned pine branches (F2,18= 29.6, P < 0.0001) and in the ash layer pH (χ23= 25.4, P < 0.0001) with increasing fire intensity was observed. The ash layer pH under the canopy projection of burned pine trees increased from pH 7.8 at light fire to pH 10.3 at high intensity fire. The mean minimum diameter of burned branches remaining on pine trees increased from 1.6 mm at light fire to 5.4 mm at high intensity fire. A positive correlation was found between the ash layer pH and minimum diameter of burned branches, with increasing fire intensities (Pearson r = 0.83, P = 0.0001) (Fig. 1). The size of the soil microarthropods community decreased with increasing fire intensity (Fig. 2), and fire intensity also affected the composition of the arthropods and collembolan groups (Fig. 3, Table 2). Isotomidae (Isotomidae sens. lat.) and Onychi-
Fig. 1. Ash pH under the canopy projections and mean minimum diameter of burned branches remaining on pine trees burned at various fire intensities
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Fig. 2. Total number of microarthropods in the seven soil samples (137 cm2) collected under the canopy projection of pine trees burned at each fire intensity
Fig. 3. Total Collembola number (A) and percentage of Collembola groups (out of total Collembola number) (B), in the seven samples collected under the canopy projection of pine trees burned at each fire intensity. Hyp – Hypogastruridae. Ony – Onychiuridae. Iso – Isotomidae. Ento – Entomobryidae
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Table 2. List of microarthropod species found in the upper soil layer (15 cm) of an unburned P. halepensis forest and in adjacent sites burned at various wildfire intensities Unburned Light Fam. Isotomidae Isotomodes maroccanus Stach, 1947 Cryptopygus ponticus (Stach, 1947) Fam. Hypogastruridae Xenylla maritima Tullberg, 1869 Fam. Onychiuridae Protaphorura levantina Christiansen, 1959 Fam. Entomobryidae Seira dori Gruia et al., 2000 Orchesella lineata Brown, 1926 Entomobrya multifasciata Tullberg, 1871
Medium
High
– –
+ +
– +
– –
+
+
–
–
–
+
–
–
+ + +
+ – –
+ – –
– – –
uridae were present only in the burned plots. In light fire the isotomids group (Isotomidae sens. lat.) was the dominant one, and some Entomobryidae, Hypogastruridae and Onychiuridae were found as well. In the medium fire the last two groups disappeared and the ratio of isotomids was lowered to some extent. In the high fire intensity all collembolan representatives disappeared.
Discussion Woodlands are mosaics of life forms and sizes distributed in space, resulting in micro scale variations in fire intensity. Based on our experience in previous wildfires, burned pine trees were qualitatively classified in this study, according to the color of the ash layer under their canopy projection into fire intensity groups. Fire intensity and the thickness of the ash layer that accumulated under burned trees increased with the increase in tree size (Table 1), probably due to accumulation of higher amounts of litter under big trees. Similar observations were made by Ne’eman et al. (1992), who found an increase in ash accumulation and a decrease in seedling density under the canopy projection of burned pine trees, with an increase in tree size. A direct relationship was found between fire intensity and the pH of the ash layer (Fig. 1), and ash pH was highly correlated with heating temperature. The pH of the ash is directly related to the impact of fire intensity on the chemical properties of the forest floor. In previous works the increase in pH and concentration of basic cations in the ash and upper soil layers of burned pine forests were found to be correlated with the increase in fire intensity (HenigSever 1997; Eshel et al. 1999). The increase in pH values was caused by an increase in concentrations of carbonates, oxides and hydroxides of basic cations with increasing fire temperature, as was found by Soto & Dias Fierros (1993) and Khanna et al. (1994). A high correlation was found between the increase in the ash layer pH and minimum diameters of burned branches that remained on pine trees, with the increase in
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fire intensity (Fig. 1). Minimum branch diameter was shown to be a reliable post-fire index of wildfire intensity in shrublands (Moreno & Oechel 1989; Perez & Moreno 1998). This technique was applied here for the first time in a burnt pine forest. Although the ash layer pH was very easy to determine, we found the minimum branch diameter technique to be difficult to perform in pine forests, because of the height of the remaining burned branches. Accordingly we found the pH technique preferable in pine forests. Ecological impacts of fires result from the interaction between fire intensity, physical and chemical properties of the ecosystem and physiological properties of the fauna and the flora. Fire temperatures of up to 125 °C affect soil biological activity. Temperatures of 200 °C–600 °C affect soil chemistry, and temperatures above 600 °C affect the physical structure of the soil (Tolhurst 1995). Fires can alter above and below ground species composition (Shaw 1997; Neary et al. 1999). Microarthropod community size and composition were directly related to the ecological impacts of fire intensity (Figs. 2 and 3; Table 2), and collembolan populations showed dramatic changes with increase in fire intensity (Fig. 3B, Table 2). Decreases in collembolan populations after wildfire were found in previous studies of Broza and Izhaki (1997), who also found a distinct occurrence of high pioneer populations of macroarthropod orders (Homoptera) and Psocoptera (Broza 2000) in burned sites. The stability of community composition at a specific site provides a good bioindication of changes in soil properties and impact of disturbances (van Straalen 1998). Vulnerability of organisms to fire depends on their trophic level, seasonal activity and vertical distribution in the soil (Prodon et al. 1987). In Mediterranean ecosystems fires affect only the 3 upper cm of the soil (Tolhurst 1995) and usually occur during summer when most soil arthropods migrate into deeper soil layers or enter a crypozoic stage. Litter inhabiting arthropods were more affected by fire than organisms inhabiting deeper soil layers, and decomposers and detrivores feeding on dead plant material or fungi were less sensitive (Metz & Dindal 1975; Prodon et al. 1987; Sgardelis & Margaris 1993; Sgardelis et al. 1995). Therefore inhabitants of the litter layer, like Acari and Collembola, can serve as good bio-indicators of ecological impacts of fire intensity on ecosystems. Indirect effects of fires on soil inhabitants due to the loss of above ground vegetation, destruction of the litter layer and release of nutrients were higher than direct effects caused by increase in soil temperature (Webb 1994; Sgardelis et al. 1995). Acidity is one of the main factors determining the species composition of soil invertebrate communities (van Straalen 1998). Collembola and Acari taxa were shown to differ in their sensitivity to soil pH, several species preferred acidic pH whereas others preferred basic pH (Hagvar & Abrahamsen 1980). Accordingly an ‘arthropod acidity index’, which measures the average pH preference of a microarthropod community, was proposed (van Straalen 1998). This index enables evaluation of the bio-indicator response to soil pH. Based on the presented results we suggest using ash pH and post fire changes in soil microarthropods community composition, especially in Collembolan populations, for estimation micro-scale variations in fire intensity and their impact on ecosystem. Further studies should be conducted at other sites with various topographic, geologic and vegetation cover properties, in order to examine the use of ash pH and soil microarthropods as post hoc indicators of fire intensity.
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References Bond, W. J., van Wilgen, B. W. (1996) Fire and Plants. Chapman and Hall, London. Broza, M. (2000) Soil arthropods in east Mediterranean Pinus halepensis forests. In: Ne’eman, G., Trabaud, L. (eds) Ecology, Biogeography and Management of Pinus halepensis and P. brutia forest ecosystems. Backhuys Publishers, Leiden, pp. 203–216. Broza, M., Izhaki, I. (1997) Post fire arthropod assemblages in Mediterranean forest soils in Israel. International Journal of Wildland Fire 7, 317–325. Byram, G. M. (1959) Combustion of forest fuels. In: Davis, K. P. (ed) Forest fire: Control and use. McGraw-Hill, New York, pp. 61–89. Christensen, N. L. (1987) The biogeochemical consequences of fire and their effect on the vegetation of the coastal plain of the southeastern United States. In: Trabaud, L. (ed) The Role of Fire in Ecological Systems. S.P.B. Academic Publishers, The Hague, pp. 1–22. Eshel, A., Henig-Sever, N., Ne’eman, G. (2000) Spatial variation of seedling distribution in an east Mediterranean pine woodland at the beginning of post-fire succession. (Accepted by Plant Ecology) Finney, M. A. (1998) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Research paper RMRS-RP-4. Gruia, M., Poliakov, D., Broza, M. (2000) The Collembola of northern Israel, II. Contribution of Biological Laboratory of Kyoto University 29, 117–131. Hagvar, S., Abrahamsen, G. (1980) Colonization by Enchytraeidae, Collembola and Acari in sterile soil samples with adjusted pH levels. Oikos 34, 245–259. Henig-Sever, N. (1997) Regulation of Germination by Ash and its Ecological Significance in Post-fire Regeneration of Mediterranean Vegetation. Ph.D. dissertation, Tel-Aviv University (in Hebrew). Hesseln, H., Rideout, D. B., Omi, P. N. (1998) Using catastrophe theory to model wildfire behavior and control. Canadian Journal of Forest Research 28, 852–862. Keeley, J. E. (1998) Post fire ecosystem recovery and management: the October 1993 large fire episode in California. In: Moreno, J. M. (ed.) Large forest fires. Backbuys Publishers, Leiden, pp. 69–90. Khanna, P. K., Raison, R. J., Falkiner, R. A. (1994) Chemical properties of ash derived from Eucalyptus litter and its effects on forest soil. Forest Ecology and Management 66, 107–125. Metz, L. J., Dindal, D. (1975) Collembola populations and prescribed burning. Environmental Entomology 4, 583–587. Moore, P. H. R., Gill, A. M., Kohnert, R. (1995) Quantifying bushfires for ecology using two electronic devices and biological indicators. CALM Science Supplement 4, 83–88. Moreno, J. M., Oechel, W. (1989) A simple method for estimating fire intensity after a burn in California chaparral. Acta Ecologica/Ecologia Plantarum 10, 57–68. Moreno, J. M., Oechel, W. (1991) Fire intensity effects on germination of shrubs and herbs in southern California chaparral. Ecology 72, 1993–2004. Neary, D. G., Klopatek, C. C., DeBano, L. F., Folliott, P. F. (1999) Fire effects on belowground sastainability: a review and synthesis. Forest Ecology and Management 122, 51–71. Ne’eman, G., Lahav, H., Izhaki, I. (1992) Spatial pattern of seedlings one year after fire in a Mediterranean pine forest. Oecologia 91, 365–370. Perez, B., Moreno, J. M. (1998) Methods for quantifying fire severity in shrubland-fires. Plant Ecology 139, 91–101. Prodon, R., Fons, R., Athias-Binche, F. (1987) The impact of fire on animal communities in Mediterranean area. In: Trabaud, L. (ed) The role of fire in ecological systems. SPB Academic Publishing, The Hague, pp. 121–157. Rice, S. K. (1993) Vegetation establishment in post fire Adenostoma chaparral in relation to finescale pattern in fire intensity and soil nutrients. Journal of Vegetation Science 4, 115–124.
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Riggan, P. J., Franklin, S. E., Brass, J. A., Brooks, F. E. (1994) Perspectives on fire managements in Mediterranean ecosystems of Southern California. In: Moreno, J. M., Oechel, W. C. (eds) The role of fire in Mediterranean ecosystems. Ecological Studies, Vol 107, Springer-Verlag, New York, pp. 140–162. Rothermel, R. (1991) Predicting behavior and size of crown fires in the northern Rocky mountains. USDA Forest Service, Research paper INT-438. Rundel, P. W. (1981) Fire as an ecological factor. In: Lange, O. L., Nobel, P. S., Osmond, C. B., Ziegler, H. (eds) Physiological Plant Ecology I. Responses to the Physical Environment. Springer Verlag, Berlin, pp. 501–538. Sgardelis, S. P., Margaris, N. S. (1993) Effects of fire on soil microarthropods of phryganic ecosystem. Pedobiologia 37, 83–94. Sgardelis, S. P., Pantis, J. D., Argyropoulou, M. D., Stamou, G.P. (1995) Effects of fire on soil macroinvertebrates in a Mediterranean of phryganic ecosystem. International Journal of Wildland Fire 5, 113–121. Shaw, P. J. A. (1997) Post-fire succession of Collembola in lowland in South-Eastern UK. Pedobiologia 41, 80–87. Soto, B., Diaz-Fierros, F. (1993) Interactions between plant ash leachates and soil. International Journal of Wildland Fire 3, 207–216. SYSTAT (1996) SYSTAT 8.0 Statistics. SPSS Inc., Chicago, IL. Tolhurst, K. G. (1995) Fire from a flora, fauna and soil perspective: sensible heat measurement. CALM Science Supplement 4, 45–58. van Straalen, N. M. (1998) Evaluation of bioindicator systems derived from soil arthropod communities. Applied Soil Ecology 9, 429–437. van Wagner, C. E., Stocks, B.J., Alexander, M. E., Lanson, B.D. (1992) Development and structure of Canadian forest fire behavior prediction system. Forestry Canada fire danger group, information report ST-X-3, Ottawa, Canada. Viegas, D. X. (1998) Weather, fuel status and fire occurrence: predicting large fires. In: Moreno, J. M. (ed) Large forest fires. Backbuys Publishers, Leiden, pp. 31–48. Webb, N. R. (1994) Post fire succession of cryptostigmatic mites (Acari, Cryptostigmata) in a Calluna-heathland soil. Pedobiologia 38, 138–145. Weber, R. O., Gill, A. M., Lyons, P. R. A., Moore, P. H. R., Bradstock, R. A., Mercer, G. N. (1995) Modelling wildland fire temperatures. CALM Science Supplement 4, 23–26. Whelan, R. J. (1995) The Ecology of Fire. Cambridge University Press, Cambridge, pp. 200–293.
A novel method for estimation of wild fire intensity based on ash pH and soil microarthropod community Nava Henig-Sever*, Dina Poliakov and Meir Broza Department of Biology, University of Haifa at Oranim, Tivon 36006, Israel Submitted: 21. July 2000 Accepted: 1. November 2000
Summary 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 present study was to evaluate a novel method for fire intensity estimation, based on measurements of post-fire ash pH and soil microarthropod community. Estimation of fire intensity by the novel method was compared to estimation by the mean minimum diameter of burned branch technique (MMDB), described by Moreno & Oechel (1989). The study was carried out in a Pinus halepensis Mill. forest on Mt. Carmel that burned in a wildfire in October 1998. The intensity 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 technique. 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 was found between the ash layer pH and minimum diameter of burned branches, with increasing fire intensities. A negative correlation was found between the size of microarthropod community and fire intensity, which also affected the composition of the arthropod community. Thus, estimation of fire intensity 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 recovery time of the whole ecosystem. *E-mail corresponding author: [email protected]
0031–4056/01/45/02–98 $ 15.00/0
Collembola and pH as fire intensity indicators
99
Key words: Fire-Intensity, ash, pH, soil-microarthropods, Collembola, minimum diameter of burned branches
Introduction Fires occur frequently in Mediterranean ecosystems around the world. Intensity is frequently used as a characteristic of fire regime (Moreno & Oechel 1989; Moore et al. 1995). The factors that affect fire intensity are usually grouped in three main categories: fuels (load, type, distribution, structure and humidity), meteorology (solar radiation, air temperature, relative humidity and wind speed) and topography (slope and aspect) (Rundel 1981; Christensen 1987; Whelan 1995; Bond & van Wilgen 1996; Viegas 1998). Prediction of fire intensity and fire impact on the ecosystem is limited because of the complexity of the fire phenomenon. Several theoretical models of the interactions between the factors mentioned above have been developed in order to predict fire occurrence and intensity (Rothermel 1991; van Wagner et al. 1992; Weber et al. 1995; Finney 1998; Hesseln et al. 1998; Viegas 1998). Over the last 40 years Byram’s (1959) fire intensity concept, which combines heat release during combustion and rate of fire front spread, has been used for the characterization of prescribed fires (Tolhurst 1995). However, Byram’s concept and the theoretical models do not give a complete picture of the ecological impact of wildfires on ecosystems. Using post-fire indicators of fire severity proved to be useful in understanding ecosystem responses to wildfires. Some of the qualitative approaches that have been used are: color of the ash layer, cool or hot fires and the degree of fuel combustion (Moreno & Oechel 1989). A quantitative estimation of heat output per unit area can be made from the amount of fuel consumed by the fire (Riggan et al. 1994). In the last decades biological indicators have been used for post-fire quantitative estimation of wildfire intensity and in ecological studies of fire impacts on ecosystems. Common biological indicators that are used include: height of leaf scorch, thickness of bark lost, height of leaf char (Moore et al. 1995; Tolhurst 1995), minimum branch diameters remaining after fire and height above ground of plant remains (Moreno & Oechel 1989; Keeley 1998). The minimum branch diameter technique has proved to be a reliable post fire index of wildfire intensity in shrublands, and a good predictor of plant and soil responses to fire severity (Moreno & Oechel 1989, 1991; Rice 1993; Keeley 1998; Perez & Moreno 1998). Nonetheless, in woodlands post hoc estimation of fire intensity has rarely been studied. The aims of the present study were to reveal the impact of fire intensity on the forest bed pH, soil microarthropod community and minimum branch diameters remaining after fire in an Aleppo pine (Pinus halepensis Mill.) forest. According to the results we propose a simple method for estimating wild fire intensity in woodlands, based on measurements of post fire soil and ash pH and soil microarthropod populations.
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Materials and Methods Study site The study was carried out in an Aleppo pine forest on Mt. Carmel, Israel, that was burned in a wildfire in October 1998. Measurements and sampling were taken 26 days post-fire.
Samplings and measurements Burned pine trees were classified into three fire intensity groups – light, medium and high according to the color of the ash layer that accumulated under their canopy projection (Table 1). Pine trees in an adjacent unburned site were chosen as a control group. Each group included seven trees (replications). Tree trunk diameters at breast height (DBH) and the thickness of the ash layer were measured. pH measurements. Ash samples (10 x 10 cm) were collected in the middle of the canopy projection of trees burned at high and medium intensities. Mixed ash and soil samples (1 cm depth) were collected under trees burned at light intensity (because the ash cover was too thin to be separated from the upper soil). Soil samples (1 cm depth) were collected under trees in the unburned site. pH was measured in aqueous saturated pastes made from the ash and soil samples (with a pH meter model PBS 730, El-Hama Instruments, Mevo-Hama, Israel). Simulation of increasing fire intensity. Pine ash collected one week after a wildfire in the Upper Galilee, Israel was sifted (2 mm) and divided into 1 kg sub–samples. To simulate various fire intensities, the sub-samples were heated at 250 °C, 350 °C, 550 °C and 1000 °C for 24 hours in an electrical furnace. pH was measured in saturated pastes made from the unheated and heated ash. Minimum diameter of burned branches. The minimum diameter of burned branches remaining after fire were measured and the mean per tree was calculated according to the MMDB technique described by Moreno & Oechel (1989). The mean minimum diameter of burned branches of the seven trees in each fire intensity group was calculated. Monitoring of microarthropod populations. Ash and soil were sampled using a standard soil corer, 19.6 cm2, to a depth of 15 cm. The samples were collected in the middle of the canopy projection of the burned and unburned trees. From each sample, 200 g was placed for 48 hours in Berlese funnels for extraction of microarthropods. The microarthropods extracted from each sample were identified (Magdalena Gruia, Bucharest) and counted.
Statistic analysis A graph probability plot test was used to check normal distribution of the results. The effect of fire intensity on minimum diameter of burned branches, which had a normal distribution, was analyzed by one-way analysis of variance. Significant results were followed by a Tukey multiple range test (P<0.05). The effects of trunk diameter on fire intensity and of fire intensity on pH, which were not normally distributed, were analyzed by non-parametric procedures (Kruskal Wallis one way test). Correlation was tested between the pH of ash to heating temperature, and between ash pH to minimum diameter of burned branches. The statistic analyses were performed using SYSTAT 8 (1996).
Results A significant difference in trunk diameter of burned trees was observed at various fire intensities (Kruskal Wallis one way test, χ23= 24.13, P < 0.0001). Fire intensity increased with an increase in tree size from light fire under the canopy projection of
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Table 1. Color and thickness (cm) of the ash layer around pine trees burned at various fire intensities
Ash thickness Color
Light cannot be separated from the soil black
Medium 3.6 black-gray
High 6.9 gray-white
trees with a trunk diameter of 20 cm, to high intensity fire under the canopy projection of trees with a trunk diameter of 48 cm. The thickness of the ash layer increased up to 6.9 cm with an increase in fire intensity (Table 1). Ash pH increased with heating temperature and a positive correlation was found between the pH of the ash and heating temperature (Pearson r = 0.99, P = 0.001). pH values were: 10.0 for unheated ash, 10.4, 10.7, 11.7 and 13.0 for ash samples heated at 250˚C, 350˚C, 550˚C and 1000˚C, respectively. A significant increase in the minimum diameter of burned pine branches (F2,18= 29.6, P < 0.0001) and in the ash layer pH (χ23= 25.4, P < 0.0001) with increasing fire intensity was observed. The ash layer pH under the canopy projection of burned pine trees increased from pH 7.8 at light fire to pH 10.3 at high intensity fire. The mean minimum diameter of burned branches remaining on pine trees increased from 1.6 mm at light fire to 5.4 mm at high intensity fire. A positive correlation was found between the ash layer pH and minimum diameter of burned branches, with increasing fire intensities (Pearson r = 0.83, P = 0.0001) (Fig. 1). The size of the soil microarthropods community decreased with increasing fire intensity (Fig. 2), and fire intensity also affected the composition of the arthropods and collembolan groups (Fig. 3, Table 2). Isotomidae (Isotomidae sens. lat.) and Onychi-
Fig. 1. Ash pH under the canopy projections and mean minimum diameter of burned branches remaining on pine trees burned at various fire intensities
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Fig. 2. Total number of microarthropods in the seven soil samples (137 cm2) collected under the canopy projection of pine trees burned at each fire intensity
Fig. 3. Total Collembola number (A) and percentage of Collembola groups (out of total Collembola number) (B), in the seven samples collected under the canopy projection of pine trees burned at each fire intensity. Hyp – Hypogastruridae. Ony – Onychiuridae. Iso – Isotomidae. Ento – Entomobryidae
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Table 2. List of microarthropod species found in the upper soil layer (15 cm) of an unburned P. halepensis forest and in adjacent sites burned at various wildfire intensities Unburned Light Fam. Isotomidae Isotomodes maroccanus Stach, 1947 Cryptopygus ponticus (Stach, 1947) Fam. Hypogastruridae Xenylla maritima Tullberg, 1869 Fam. Onychiuridae Protaphorura levantina Christiansen, 1959 Fam. Entomobryidae Seira dori Gruia et al., 2000 Orchesella lineata Brown, 1926 Entomobrya multifasciata Tullberg, 1871
Medium
High
– –
+ +
– +
– –
+
+
–
–
–
+
–
–
+ + +
+ – –
+ – –
– – –
uridae were present only in the burned plots. In light fire the isotomids group (Isotomidae sens. lat.) was the dominant one, and some Entomobryidae, Hypogastruridae and Onychiuridae were found as well. In the medium fire the last two groups disappeared and the ratio of isotomids was lowered to some extent. In the high fire intensity all collembolan representatives disappeared.
Discussion Woodlands are mosaics of life forms and sizes distributed in space, resulting in micro scale variations in fire intensity. Based on our experience in previous wildfires, burned pine trees were qualitatively classified in this study, according to the color of the ash layer under their canopy projection into fire intensity groups. Fire intensity and the thickness of the ash layer that accumulated under burned trees increased with the increase in tree size (Table 1), probably due to accumulation of higher amounts of litter under big trees. Similar observations were made by Ne’eman et al. (1992), who found an increase in ash accumulation and a decrease in seedling density under the canopy projection of burned pine trees, with an increase in tree size. A direct relationship was found between fire intensity and the pH of the ash layer (Fig. 1), and ash pH was highly correlated with heating temperature. The pH of the ash is directly related to the impact of fire intensity on the chemical properties of the forest floor. In previous works the increase in pH and concentration of basic cations in the ash and upper soil layers of burned pine forests were found to be correlated with the increase in fire intensity (HenigSever 1997; Eshel et al. 1999). The increase in pH values was caused by an increase in concentrations of carbonates, oxides and hydroxides of basic cations with increasing fire temperature, as was found by Soto & Dias Fierros (1993) and Khanna et al. (1994). A high correlation was found between the increase in the ash layer pH and minimum diameters of burned branches that remained on pine trees, with the increase in
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fire intensity (Fig. 1). Minimum branch diameter was shown to be a reliable post-fire index of wildfire intensity in shrublands (Moreno & Oechel 1989; Perez & Moreno 1998). This technique was applied here for the first time in a burnt pine forest. Although the ash layer pH was very easy to determine, we found the minimum branch diameter technique to be difficult to perform in pine forests, because of the height of the remaining burned branches. Accordingly we found the pH technique preferable in pine forests. Ecological impacts of fires result from the interaction between fire intensity, physical and chemical properties of the ecosystem and physiological properties of the fauna and the flora. Fire temperatures of up to 125 °C affect soil biological activity. Temperatures of 200 °C–600 °C affect soil chemistry, and temperatures above 600 °C affect the physical structure of the soil (Tolhurst 1995). Fires can alter above and below ground species composition (Shaw 1997; Neary et al. 1999). Microarthropod community size and composition were directly related to the ecological impacts of fire intensity (Figs. 2 and 3; Table 2), and collembolan populations showed dramatic changes with increase in fire intensity (Fig. 3B, Table 2). Decreases in collembolan populations after wildfire were found in previous studies of Broza and Izhaki (1997), who also found a distinct occurrence of high pioneer populations of macroarthropod orders (Homoptera) and Psocoptera (Broza 2000) in burned sites. The stability of community composition at a specific site provides a good bioindication of changes in soil properties and impact of disturbances (van Straalen 1998). Vulnerability of organisms to fire depends on their trophic level, seasonal activity and vertical distribution in the soil (Prodon et al. 1987). In Mediterranean ecosystems fires affect only the 3 upper cm of the soil (Tolhurst 1995) and usually occur during summer when most soil arthropods migrate into deeper soil layers or enter a crypozoic stage. Litter inhabiting arthropods were more affected by fire than organisms inhabiting deeper soil layers, and decomposers and detrivores feeding on dead plant material or fungi were less sensitive (Metz & Dindal 1975; Prodon et al. 1987; Sgardelis & Margaris 1993; Sgardelis et al. 1995). Therefore inhabitants of the litter layer, like Acari and Collembola, can serve as good bio-indicators of ecological impacts of fire intensity on ecosystems. Indirect effects of fires on soil inhabitants due to the loss of above ground vegetation, destruction of the litter layer and release of nutrients were higher than direct effects caused by increase in soil temperature (Webb 1994; Sgardelis et al. 1995). Acidity is one of the main factors determining the species composition of soil invertebrate communities (van Straalen 1998). Collembola and Acari taxa were shown to differ in their sensitivity to soil pH, several species preferred acidic pH whereas others preferred basic pH (Hagvar & Abrahamsen 1980). Accordingly an ‘arthropod acidity index’, which measures the average pH preference of a microarthropod community, was proposed (van Straalen 1998). This index enables evaluation of the bio-indicator response to soil pH. Based on the presented results we suggest using ash pH and post fire changes in soil microarthropods community composition, especially in Collembolan populations, for estimation micro-scale variations in fire intensity and their impact on ecosystem. Further studies should be conducted at other sites with various topographic, geologic and vegetation cover properties, in order to examine the use of ash pH and soil microarthropods as post hoc indicators of fire intensity.
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References Bond, W. J., van Wilgen, B. W. (1996) Fire and Plants. Chapman and Hall, London. Broza, M. (2000) Soil arthropods in east Mediterranean Pinus halepensis forests. In: Ne’eman, G., Trabaud, L. (eds) Ecology, Biogeography and Management of Pinus halepensis and P. brutia forest ecosystems. Backhuys Publishers, Leiden, pp. 203–216. Broza, M., Izhaki, I. (1997) Post fire arthropod assemblages in Mediterranean forest soils in Israel. International Journal of Wildland Fire 7, 317–325. Byram, G. M. (1959) Combustion of forest fuels. In: Davis, K. P. (ed) Forest fire: Control and use. McGraw-Hill, New York, pp. 61–89. Christensen, N. L. (1987) The biogeochemical consequences of fire and their effect on the vegetation of the coastal plain of the southeastern United States. In: Trabaud, L. (ed) The Role of Fire in Ecological Systems. S.P.B. Academic Publishers, The Hague, pp. 1–22. Eshel, A., Henig-Sever, N., Ne’eman, G. (2000) Spatial variation of seedling distribution in an east Mediterranean pine woodland at the beginning of post-fire succession. (Accepted by Plant Ecology) Finney, M. A. (1998) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Research paper RMRS-RP-4. Gruia, M., Poliakov, D., Broza, M. (2000) The Collembola of northern Israel, II. Contribution of Biological Laboratory of Kyoto University 29, 117–131. Hagvar, S., Abrahamsen, G. (1980) Colonization by Enchytraeidae, Collembola and Acari in sterile soil samples with adjusted pH levels. Oikos 34, 245–259. Henig-Sever, N. (1997) Regulation of Germination by Ash and its Ecological Significance in Post-fire Regeneration of Mediterranean Vegetation. Ph.D. dissertation, Tel-Aviv University (in Hebrew). Hesseln, H., Rideout, D. B., Omi, P. N. (1998) Using catastrophe theory to model wildfire behavior and control. Canadian Journal of Forest Research 28, 852–862. Keeley, J. E. (1998) Post fire ecosystem recovery and management: the October 1993 large fire episode in California. In: Moreno, J. M. (ed.) Large forest fires. Backbuys Publishers, Leiden, pp. 69–90. Khanna, P. K., Raison, R. J., Falkiner, R. A. (1994) Chemical properties of ash derived from Eucalyptus litter and its effects on forest soil. Forest Ecology and Management 66, 107–125. Metz, L. J., Dindal, D. (1975) Collembola populations and prescribed burning. Environmental Entomology 4, 583–587. Moore, P. H. R., Gill, A. M., Kohnert, R. (1995) Quantifying bushfires for ecology using two electronic devices and biological indicators. CALM Science Supplement 4, 83–88. Moreno, J. M., Oechel, W. (1989) A simple method for estimating fire intensity after a burn in California chaparral. Acta Ecologica/Ecologia Plantarum 10, 57–68. Moreno, J. M., Oechel, W. (1991) Fire intensity effects on germination of shrubs and herbs in southern California chaparral. Ecology 72, 1993–2004. Neary, D. G., Klopatek, C. C., DeBano, L. F., Folliott, P. F. (1999) Fire effects on belowground sastainability: a review and synthesis. Forest Ecology and Management 122, 51–71. Ne’eman, G., Lahav, H., Izhaki, I. (1992) Spatial pattern of seedlings one year after fire in a Mediterranean pine forest. Oecologia 91, 365–370. Perez, B., Moreno, J. M. (1998) Methods for quantifying fire severity in shrubland-fires. Plant Ecology 139, 91–101. Prodon, R., Fons, R., Athias-Binche, F. (1987) The impact of fire on animal communities in Mediterranean area. In: Trabaud, L. (ed) The role of fire in ecological systems. SPB Academic Publishing, The Hague, pp. 121–157. Rice, S. K. (1993) Vegetation establishment in post fire Adenostoma chaparral in relation to finescale pattern in fire intensity and soil nutrients. Journal of Vegetation Science 4, 115–124.
106
Nava Henig-Sever et al.
Riggan, P. J., Franklin, S. E., Brass, J. A., Brooks, F. E. (1994) Perspectives on fire managements in Mediterranean ecosystems of Southern California. In: Moreno, J. M., Oechel, W. C. (eds) The role of fire in Mediterranean ecosystems. Ecological Studies, Vol 107, Springer-Verlag, New York, pp. 140–162. Rothermel, R. (1991) Predicting behavior and size of crown fires in the northern Rocky mountains. USDA Forest Service, Research paper INT-438. Rundel, P. W. (1981) Fire as an ecological factor. In: Lange, O. L., Nobel, P. S., Osmond, C. B., Ziegler, H. (eds) Physiological Plant Ecology I. Responses to the Physical Environment. Springer Verlag, Berlin, pp. 501–538. Sgardelis, S. P., Margaris, N. S. (1993) Effects of fire on soil microarthropods of phryganic ecosystem. Pedobiologia 37, 83–94. Sgardelis, S. P., Pantis, J. D., Argyropoulou, M. D., Stamou, G.P. (1995) Effects of fire on soil macroinvertebrates in a Mediterranean of phryganic ecosystem. International Journal of Wildland Fire 5, 113–121. Shaw, P. J. A. (1997) Post-fire succession of Collembola in lowland in South-Eastern UK. Pedobiologia 41, 80–87. Soto, B., Diaz-Fierros, F. (1993) Interactions between plant ash leachates and soil. International Journal of Wildland Fire 3, 207–216. SYSTAT (1996) SYSTAT 8.0 Statistics. SPSS Inc., Chicago, IL. Tolhurst, K. G. (1995) Fire from a flora, fauna and soil perspective: sensible heat measurement. CALM Science Supplement 4, 45–58. van Straalen, N. M. (1998) Evaluation of bioindicator systems derived from soil arthropod communities. Applied Soil Ecology 9, 429–437. van Wagner, C. E., Stocks, B.J., Alexander, M. E., Lanson, B.D. (1992) Development and structure of Canadian forest fire behavior prediction system. Forestry Canada fire danger group, information report ST-X-3, Ottawa, Canada. Viegas, D. X. (1998) Weather, fuel status and fire occurrence: predicting large fires. In: Moreno, J. M. (ed) Large forest fires. Backbuys Publishers, Leiden, pp. 31–48. Webb, N. R. (1994) Post fire succession of cryptostigmatic mites (Acari, Cryptostigmata) in a Calluna-heathland soil. Pedobiologia 38, 138–145. Weber, R. O., Gill, A. M., Lyons, P. R. A., Moore, P. H. R., Bradstock, R. A., Mercer, G. N. (1995) Modelling wildland fire temperatures. CALM Science Supplement 4, 23–26. Whelan, R. J. (1995) The Ecology of Fire. Cambridge University Press, Cambridge, pp. 200–293.