Effect of fire and retardant on soil microbial activity and functional diversity in a Mediterranean pasture

Geoderma 153 (2009) 186–193

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Geoderma j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / g e o d e r m a

Effect of fire and retardant on soil microbial activity and functional diversity in a Mediterranean pasture A. Garcia-Villaraco Velasco a, A. Probanza a, F.J. Gutierrez Mañero a, A. Cruz Treviño b,1, J.M. Moreno b, J.A. Lucas Garcia a,⁎ a b

Univ. San Pablo CEU, Facultad de Farmacia, Dpto. Biología, 28668-Boadilla del Monte, Madrid, Spain Univ. Castilla la Mancha, Facultad de CC. del Medio Ambiente, Dpto. CC. Ambientales, Avda. Carlos III s/n, 45071 Toledo, Spain

a r t i c l e

i n f o

Article history: Received 16 December 2008 Received in revised form 13 July 2009 Accepted 5 August 2009 Available online 5 September 2009 Keywords: Disturbance Fire Soil microbial diversity Multivariate analysis Resilience Retardant

a b s t r a c t The effect of fire and retardants on functional diversity and total activity of soil microorganisms has been studied in a Mediterranean pasture. Soil samples were collected once a month during 1 year after the fire in burnt and un-burnt plots and in one treated with retardant and subsequently burnt. In all cases, samples were taken at two soil depths. Functional diversity was measured by Biolog Eco plates and microbial activity was measured by radioactive labelled thymidine and leucine incorporation technique. In the upper layer, a higher metabolic speed (kinetics of average well colour development (AWCD)) and functional diversity (Shannon's functional diversity) were found irrespective of the treatment (fire or retardant), despite the short distance between them. Results also showed that environmental factors have a greater influence than the treatments (fire and retardant), especially soil moisture. This fact was clearly shown in the seasonal variation of microbial communities throughout the year after the fire, showing a similar successional behaviour irrespective of the treatment. Nevertheless, the techniques used were able to detect changes caused by the fire and, especially, by retardant which is very interesting in public management of fire. Changes caused by the application of retardant to the soils, did not lead to any major adverse effects on the microbial community as compared to the untreated soils. Based on the results, we could hypothesise that bacterial communities studied show a noteworthy grade of fire-accommodation, which can be correlated with the inherent presence of fire in the Mediterranean ecosystems. In particular, we can assume an important resilience and resistance of Mediterranean pastures to fire at the soil bacterial level. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Mediterranean landscapes of European countries have undergone deep transformations during the last century due to changes produced in land use and, especially, due to the widespread abandonment of agricultural soils (Margaris et al., 1996). As an indirect consequence of this transformation, great fires have spread in the Mediterranean Basin the last few decades (Vélez, 1997; Moreno et al., 1998). For instance, in the region of Catalonia (north eastern Spain) during the period 1941–1962 only 5 fires larger than 500 ha were recorded, accounting for 27% of the 12,388 ha burned. During the following two 20-year periods, 74 and 73 fires were recorded, affecting 59% and 75%, respectively, of the 210,039 and 255,554 ha burned (González and Pukkala, 2007). Although the main reason for this increase in the number of fires is probably the anthropogenic factors (mainly due to changes in land ⁎ Corresponding author. Tel.: +34 913724733; fax: +34 91 351 04 96. E-mail address: [email protected] (J.A. Lucas Garcia). 1 In memoriam, December 14, 2006. 0016-7061/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.geoderma.2009.08.005

use), climatic factors cannot be ruled out (Pausas and Vallejo, 1999). With regard to anthropogenic factors, Mediterranean ecosystems in Europe have been subjected to a long-term history of human use (Wainwright, 1994; Grove, 1996; Margaris et al., 1996), and this has provoked older and very intense disturbance regime when compared to other Mediterranean-climate regions in the world (Fox and Fox, 1986). Many centuries of severe human pressure, resulting in burning, cutting and grazing on non-arable lands and clearing, terracing, cultivating, and later abandonment of arable portions, have created a strongly human-influenced landscape (Pausas and Vallejo, 1999). With regard to climatic factors, it is important to note that fires tend to concentrate in summer, when temperatures are high and environmental and biomass humidity is low. Climatic changes predicted for the near future will probably cause an increase in the risk of fires, not only in the Mediterranean area, but also in other regions of the world prone to fires (Flannigan and van Wagner, 1991; Torn and Fried, 1992). The models of climatic change for the southern Mediterranean area, predict a decrease of precipitation (25%) and air temperatures increase (2 °C) with respect to mean monthly values recorded for the last 40 years (Custovic and Vlahinic, 2009).

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Long-term fire retardants are chemical products which, when applied to the vegetation, alter the combustion reaction and make fire propagation more difficult for long periods of time after an application. Because of their effectiveness in reducing the rate of fire spread, fire retardants are widely used for the control and management of wild land fires. Such is the case in the Mediterranean-type climate areas, prone to fire, where the use of these products is fairly recent (Basanta et al., 2002). More than 2000 tons of fire retardants are used each year to combat fires in the Mediterranean (Luna et al., 2007). Despite the common use of fire retardants, relatively little information is available on their potential environmental effects, including impacts on the microbial soil community. Retardants usually contain ammonium salts that may be potentially toxic to biota (Gimenez et al., 2004). Acute toxicity tests have shown harmful effects of retardants on aquatic organisms, and ammonia is the component which has most impact (Gaikowsky et al., 1996; McDonald et al., 1997; Buhl and Hamilton, 1998, 2000; Little and Calfee, 2002). Surprisingly, the effects of the liberation of these chemicals on terrestrial environments are poorly known. On the other hand, the presence of nitrogen compounds in the retardant solutions suggests that moderate retardant applications on terrestrial ecosystems would cause effects similar to those produced by fertilisers. The literature reports effects of retardants on plants (Larson and Duncan, 1982; Bradstock et al., 1987; Larson et al., 1999; Luna et al., 2007), but there are no reports on the effects on soil microbial communities. Soil microorganisms are critical for the maintenance of soil function because of their involvement in such key processes as soil structure formation, decomposition of organic matter, toxin removal, and the cycling of carbon, nitrogen, phosphorus, and sulphur (van Elsas and Trevors, 1997). Although microbiologists have been investigating the impact of microbial diversity on the stability of ecosystem function since the 1960s (Hairston et al., 1968), there is now an increasing interest in the effect that the diversity of microbial communities has on ecological function and resilience against disturbances such as fire. Relationships are often observed between the extent of microbial diversity in soil and ecosystem sustainability (Nitta, 1991; Abawi and Widmer, 2000). Soil microbial community diversity is so high that there is a certain degree of redundancy in species, and therefore, a certain degree of resilience in the biological functions of the system (Finlay et al., 1997). Although high microbial species richness might not always play an important role in the maintenance of the characteristics of the ecosystem under usual conditions, it could have an important role when conditions change (Yachi and Loreau, 1999). In fact, high biodiversity is an important property of soil in recovering after disturbances (Pankhurst et al., 1997). This is clear both in terrestrial (King and Pimm, 1983; Sankaran and McNaughton, 1999) and aquatic systems (McGrady-Steed et al., 1997; Naeem and Li, 1997). In soil, any change affecting any component of the system, will result in alterations. The extent and soundness of these changes will be defined by soil characteristics and function, which determine its resistance and resilience, and therefore, the response to potential disturbances. International programmes monitoring soil quality include microorganism biomass and respiration measures and also nitrogen mineralisation, microbial diversity, and functional groups of soil microbiota (Schloter et al., 2003). With respect to the latter, Biolog plates (Garland and Mills, 1991) used in this work have been proved as a useful tool in studying microbial community metabolic profiles. Bacterial capacity to use the different Biolog plate compounds is a reflection of metabolic capacities of these bacteria at the moment of the sampling. Vegetation recovery after a fire has been studied before (Kennard and Gholz, 2001; Hanley et al., 2003) as well as physicochemical characteristics of burnt soil (De Bano, 2000; Choromanska and

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DeLuca, 2002; Badía and Martí, 2003; González-Pérez et al., 2004; Certini, 2005; Cerdà and Doerr, 2008). However, there are few studies of the effect of fire on the biological properties of soil (Certini, 2005), some of which attend to invertebrates, mainly nematodes (Matlack, 2001), others to mycorrhiza (Vilariño and Arines, 1991) or other fungi (Persiani et al., 2002). Works referring to the soil microbial community are mainly focused on determination of microbial biomass (Andersson et al., 2004), microbial structure (Pettersson and Bååth, 2003; Fierer et al., 2003; Diaz-Raviña et al., 2006), or microbial activity (Díaz-Raviña et al., 1996). The objective of the present work was to analyse fire and retardant effects on soil microbial community in a Mediterranean pasture in Toledo (Spain) throughout 1 year following the perturbation (fire), evaluating the impact and the recovery process using: i) catabolic profiles and microbial community functional diversity using Biolog plates and ii) microbial activity using the radioactive labelled thymidine and leucine incorporation technique. 2. Material and methods 2.1. Experimental design Soil samples were taken from an experimental plot located in a nature reserve named Quintos de Mora, under the auspices of the Spanish Environmental Ministry, situated in Toledo, Spain (39° 24′ 47.85″N, 4° 3′53.90″W), with typical Mediterranean climate: annual average temperature 14.5 °C; annual average maximum temperature 19.9 °C; annual average minimum temperature 9.26 °C and annual average precipitation 445.36 mm (10 years data obtained from meteorological station located in Quintos de Mora). This place is a valley between mountains, with practically flat slope. Over a clay– stony acidic pH material, Dystric Cambisols and Dystric Regosols (according to FAO) are developed. These soils are acidic, sandy or sandy–clay and quite rocky. The experimental plot (60 × 30 m) was a Mediterranean pasture with Agrostis castellana as the dominant plant species. In this plot, 9 subplots (1 m diameter) were delimitated. The experiment was a completely randomised block design with 3 replicates. The treatments were: i) subplots burnt (F); ii) subplots burnt previously adding retardant (FR), and iii) subplots un-burnt (NF). Samples were taken the day of the fire (t1; 04/September/2003); 21 days after fire (t2); and from that time on, once a month during a year until September 2004. In addition, samples were taken at two different soil depths, using a hollow steel cylinder (1.5 cm diameter), and separating soil from 0 to 1 cm soil depth (depth A) and from 3 to 4 cm soil depth (depth B). Burning was carried out with a propane burner. Before that, the plant biomass of all circular subplots that were going to be burnt, was cut and removed in order to apply fire directly to the soil, avoiding fire intensity differences between circular plots due to different biomass accumulation. The plant biomass from each subplot was taken to the laboratory, air-dried and burned. The ash was collected and evenly spread over the surface of the corresponding subplot later on. The average temperatures reached were 221.6 °C, and temperatures over 100 °C remained for 103 seconds following the procedure described by Cruz et al. (2003). These temperatures were measured using four K type thermocouples (Campbell), distributed over the burned area. The retardant used was Fire-Trol 934™, containing ammonium polyphosphate, (the active agent in fire fighting), a corrosion inhibitor (sodium ferrocyanide), an adhesive agent (gum or clay) and water. In all cases, 20% (v:v) diluted retardant was used and applied 1 L per m2 by hand with a pressure watering system, at the beginning of July 2003. In each sampling time during the study, the temperature of both depths (A and B) and soil moisture (gravimetric method) were measured (Table 1). In addition, data corresponding to the total rainfall

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Table 1 Soil temperature and humidity. and environmental conditions (environmental temperature of sampling day and total rainfall 10 days before sampling).

Temperature of depth A (°C) Temperature of depth B (°C) Soil humidity (g/kg of dry soil) Total rainfall 10 days before sampling (mm) Environmental temperature of sampling day (°C)

t1 09/04/03

t2 09/25/03

t3 10/30/03

t4 11/27/03

26

26

14

7

5

5

7

11

14

17

25

25

14

7

5

6

8

11

14

58.1

19.2

190.7

218.0

236.9

271.5

268.2

242.1

0

1

71.8

22

6.2

12

69.2

23

23

12.5

5.5

4

6

6.5

t5 12/29/03

t6 01/29/04

t7 02/26/04

t8 04/01/04

t9 04/29/04

t10 05/27/04

t11 06/24/04

t12 07/26/04

t13 09/09/04

23

35

25

16

23

34

24

216.0

244.0

238.6

57.6

29.9

70

30.1

46.5

38

0.5

2

10

12.5

16.5

17.5

30

24.5

Data were kindly provided by the meteorological station of Quintos de Mora (National Meteorological Institute). Data of soil temperature and humidity were measured in each sampling time (n = 3). A: 0–1 cm soil depth. B: 3–4 cm soil depth.

10 days before each sampling and the sampling day average environmental temperature were measured (Table 1). 2.2. Sample processing For each replicate and in all sampling times, 2 g of soil in 20 ml of sterile distilled water were homogenized with an Omnimixer at 16,000 rpm during 1 minute, then centrifuged at 2500 rpm for 10 minutes. The supernatant was filtered through glass wool. The bacterial suspension obtained was used both to inoculate Biolog Eco plates (Garland and Mills, 1991) and to incubate with radioactive labelled thymidine and leucine (Bååth, 1992).

described by Bååth (1992, 1994). The bacterial suspension was incubated for 2 h in 200 nM methyl-[3H]-thymidine and 775 nM l[U-14C]-leucine (Amersham, 925 GBq mmol− 1 and 11.9 GBq mmol− 1, respectively). After adding 1 ml of 5% formalin, the suspension was filtered through a Whatman GF/F fiberglass filter and washed with 3 × 5 ml of ice-cold 80% ethanol followed by 3 × 5 ml ice-cold 5% trichloroacetic acid. The filter was placed in a scintillation vial, and after the addition of 1 ml of 0.1 M NaOH, the vial was kept at 90 °C for 2 h. Once the vial was cooled, 10 ml of scintillation cocktail was added, and radioactivity was counted in a liquid scintillation spectrometer (Beckman LS-6500). 2.5. Statistics

2.3. Microbial community catabolic profile Bacterial microbial communities were characterised for their metabolic profiles using Biolog Eco plates (BIOLOG Inc., Hayward, CA) (Garland and Mills, 1991; Grayston et al., 2001). The bacterial suspension was diluted to 10− 2, and used to inoculate Biolog Eco plates with 150 µL per well. Plates were incubated at 25 °C in darkness. Each well contained a substrate and tetrazolium salts, which turns violet when reduced by the activity of microorganisms. Absorbance at 595 nm was measured every 24 h for 168 h with an Asys High Tech Expert 96 spectrophotometer and Microwin 2000 analysis software. Absorbance values were blanked against the control (or blank) well. All negative absorbance values were set to zero. Overall colour development, expressed as average well colour development (AWCD), was calculated as the mean of the blanked absorbance values for all the 31 wells per reading time. AWCD= ∑(C −R)/N where C is colour production with each well (optical density measurement at 595 nm), R is the absorbance value of the plate's blank well, and N is the number of substrates (ECO plates, N = 31). Three replicates per treatment and sampling time were performed. Kinetics of AWCD were used to determine the speed and the level of development of the bacterial communities using the 31 provided substrates. Moreover, the absorbance value of each well at 120 h of incubation was then divided by the AWCD in order to normalize the values and to minimize the influence of inoculum density between plates (Baudoin et al., 2001; Graham and Haynes, 2005). These data from 120 h were used to calculate the functional diversity using Shannon's functional diversity index: H = −Σ[Pi ⁎ Log Pi], where Pi is the ratio of the blanked absorbance value of each well to the sum of absorbance values of all wells. 2.4. Thymidine and leucine incorporation Analysis of radioactively labelled thymidine and leucine incorporation was performed to study microbial community activity as

Regression analysis were carried out between environmental factors (temperature of both depths (A and B), soil moisture, the total rainfall 10 days before each sampling and the sampling day average environmental temperature), and Shannon's functional diversity index and AWCD value at 120 h in each sampling time. Two-way ANOVA were performed for functional diversity, for activity values and for kinetics of AWCD values. When significant differences appeared (p < 0.05), average values were compared by means of LSD statistic (Sokal and Rohlf, 1979). In addition, a Canonical correspondence analysis (CCA) was also carried out (CANOCO™ v4.5 software) with blanked absorbance values measured at 120 h of incubation, together with soil moisture, soil temperature at the two depths (A and B), average environmental temperature on sampling day, total rainfall 10 days before each sampling, total rainfall of the month, monthly average temperature, and thymidine and leucine incorporation data. 3. Results Table 1 shows soil moisture (g/Kg of dry soil), soil temperatures, environmental temperature and rainfall data at each sampling time. It is possible to appreciate the clear seasonal variation with the lowest values of moisture during the summer months (t1, t11, t12 and t13), the highest during the winter (t5, t6 and t7) and the intermediate values in spring and autumn (t3, t4, t8, t9 and t10). In the case of temperature, a clear seasonal variation corresponding to Mediterranean climate was also evident. Regression analysis between these environmental factors and Shannon's functional diversity index and AWCD at 120 h, showed that soil moisture and the total rainfall 10 days before each sampling were the factors that produced a higher number of significant correlations (Table 2). Slopes of regression lines obtained in statistically significant correlations, showed that retardant treatments were higher.

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Table 2 Simple regression analyses between different environmental factors and Shannon's functional diversity index value measured with Biolog data at 120 h and Average Well Colour Development (AWCD) value at 120 h of incubation.

Functional diversity of FA Functional diversity of FRA Functional diversity of NFA Functional diversity of FB Functional diversity of FRB Functional diversity of NFB AWCD FA AWCD FRA AWCD NFA AWCD FB AWCD FRB AWCD NFB

Total rainfall 10 days before sampling (mm)

Environmental temperature of sampling day (°C)

Temperature of depth A (°C)

Temperature of depth B (°C)

Soil humidity (g/kg dry soil)

p = 0.05 (r = 0.536) s = 471.92 p = 0.02 (r = 0.627) s = 926.46 N.S (r = 0.343) s = 398.95 p = 0.04 (r = 0.559) s = 302.38 N.S (r = 0.521) s = 308.76 p = 0.01 (r = 0.636) s = 257.95 p = 0.03 (r = 0.595) s = 67.56 p = 0.04 (r = 0.577) s = 116.38 N.S (r = 0.379) s = 53.25 p = 0.02 (r = 0.627) s = 63.84 N.S (r = 0.237) s = 25.55 p = 0.03 (r = 0.609) s = 60.23

N.S (r = − 0.5) s = − 131.35 N.S (r = − 0.520) s = − 231.52 N.S (r = − 0.290) s = − 100.38 N.S (r = − 0.480) s = − 78.36 N.S (r = − 0.470) s = − 82.62 p = 0.02 (r = − 0.60) s = − 73.09 N.S. (r = − 0.470) s = − 15.95 N.S (r = − 0.418) s = − 25.24 N.S (r = − 0.230) s = − 9.83 p = 0.05 (r = − 0.54) s = − 16.43 p = 0.02 r(− 0.610) s = − 19.83 p = 0.02 r(− 0.610) s = − 18.06

N.S (r = − 0.47) s = − 141.79 N.S (r = − 0.48) s = − 243.79 N.S (r = − 0.26) s = − 102.14 –

–

p = 0.008 (r = 0.70) s = 210.41 p = 0.002 (r = 0.776) s = 392.32 p = 0.04 (r = 0.56) s = 223.66 p = 0.002 (r = 0.774) s = 143.24 p = 0.003 r = 0.743 s = 150.67 p = 0.0002 (r = 0.85) s = 117.96 p = 0.003 (r = 0.745) s = 28.94 p = 0.0045 (r = 0.731) s = 50.51 N.S (r = 0.48) s = 23.09 p = 0.0005 (r = 0.829) s = 28.82 p = 0.04 (r = 0.57) s = 20.96 p = 0.0002 (r = 0.85) s = 28.93

– – N.S (r = − 0.43) s = − 16.63 N.S (r = − 0.38) s = − 25.91 N.S (r = − 0.23) s = − 10.84 – – –

– – N.S (r = − 0.43) s = − 73.70 N.S (r = − 0.45) s = − 85.83 p = 0.05 (r = − 0.55) s = − 70.65 – – – N.S (r = − 0.49) s = − 15.82 p = 0.02 (r = −0.61) s = − 21.13 p = 0.04 (r = − 0.57) s = − 17.99

F = burnt. FR = burnt with retardant. NF = non-burnt. A: 0–1 cm soil depth. B: 3–4 cm soil depth. p = statistical significance of correlation. r = correlation coefficient. s = slope. N.S = non-significant.

3.1. Microbial community catabolic profile Community metabolic diversity data (Fig. 1), was lowest 21 days after the fire (t2). In addition, metabolic diversity in depth A was significantly higher within each treatment (FA vs. FB; FRA vs. FRB and NFA vs. NFB). Metabolic speed assessed using kinetics of AWCD values (Fig. 2) were significantly higher for FA than FB from t1 to t8. In addition, trends curves of treatment FR showed statistically lower metabolic speed in depth B than for depth A in all sampling times. In un-burnt soils higher metabolic speed were found for A than for B depth in all cases except in t7, t9 and t12 (Fig. 2). Within depth A, FR provoked a significant higher metabolic speed with regard to NF in t2, t5, t6, t7 and t8. With regard to depth B, significant differences were found only between retardant treatments (FR) and control (NF), with a significantly higher metabolic speed in t5, t6 and t8, and lower metabolic speed in t4, t7, t9, t10 and t11caused by FR with regard to NF (Fig. 2).

Canonical correspondence analysis (CCA) carried out with blanked absorbance values measured at 120 h of incubation, together with soil moisture, soil temperature at the two depths (A and B), the average environmental temperature of sampling day, the total rainfall 10 days before each sampling day, total rainfall of the month, average month's temperature, and thymidine and leucine incorporation data, is presented in Fig. 3. Samples, irrespective from the treatment, were grouped by sampling time and it is possible to appreciate a seasonal variation, showing the same successional behaviour. The first (t1) and last (t13) sampling times grouped together, despite the 1-year gap between these two sampling times (both correspond to September). Vectors in this figure correspond to the variables that significantly influenced sampling ordination: soil moisture (p = 0.001), depth A soil temperature (p = 0.001), depth B soil temperature (p = 0.048) and thymidine incorporation rate (p = 0.002). 3.2. Thymidine and leucine incorporation Fig. 4 shows all the average data, including all the incorporation of thymidine and leucine data from all sampling times. Soil microbial community activity was higher in depth A than in B being this difference significant in the case of FR and NF. A lower activity (both for thymidine and leucine incorporation) of microbial community under fire treatment (F) with regard to the control (NF) was found within each soil depth, being this difference significant only in A depth (Fig. 4). 4. Discussion

Fig. 1. Bacterial community functional diversity (average values, n = 3) of each sampling time. t1 to t13 are the sampling times. F = burnt. FR = burnt with retardant. NF = non-burnt. A: 0–1 cm soil depth. B: 3–4 cm soil depth. Data in brackets are average values of metabolic diversity along time of each treatment. Letters a, b and c indicate significant differences in trends along time between treatments (two-way ANOVA). Different letters indicate significant differences between treatments (p < 0.05), and the same letter indicate no statistical differences.

The effect of fire and retardants on the functional diversity and total activity of soil microorganisms have been studied in a Mediterranean pasture in the present work. Both parameters (functional diversity and activity) can be affected by a shift in the composition or by a functional change of the microbial community, and fire and retardants could produce changes in microbial community composition. The Biolog technique used in this work to assess functional diversity, appears as a rapid and convenient assay for culturable heterotrophic organisms, consistent with other studies that show Biolog

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Fig. 2. Kinetics of AWCD (mean average values, n = 3) of each sampling time. F = burnt. FR = burnt with retardant. NF = non-burnt. A: 0–1 cm soil depth. B: 3–4 cm soil depth. Letters a, b, c, d and e indicate significant differences in curves trends between treatments. Different letters indicate significant differences between treatments and the same letter indicate no statistical differences.

analysis to provide sensitive indicators of changes in soil microbial functional diversity due to different disturbances and under different management strategies (Garland, 1997; Grayston et al., 1998; Grayston et al., 2001; Rogers and Tate, 2001; Graham and Haynes, 2005; Grayston and Prescott, 2005; White et al., 2005). Consistent with this, differences between treatments in both depths of soil using this tool (Biolog plates) were detected in the present work. Retardant treatments caused the highest number of significant differences over fire treatment, and in most cases, retardant increased functional diversity (Fig. 1) and speed up of metabolic kinetics (Fig. 2), as already shown by other authors (Basanta et al., 2002; Basanta et al., 2004; Diaz-Raviña et al., 2006). Moreover, Biolog technique has also revealed differences between soils under other disturbances, such as soil treated with plant residues (mulch treatment) with regard to control soil (non-mulch treatment) (Huang et al., 2008). Furthermore, shifts in Biolog metabolic diversity patterns have been related to shifts

in community composition (Schutter and Dick, 2001; Crecchio et al., 2004). Irrespective of the treatment applied to soils, significant differences between the two soil depths assayed (A and B) were found (Figs. 1 and 2). Therefore, these differences must be due to environmental factors. In fact, the importance of environmental factors (mainly soil moisture and soil temperature) on soil microorganism functions has also been demonstrated in the present work, as indicated by the results provided by CCA (Fig. 3) and the regression analysis (Table 2) which presented significant correlations between environmental factors and data obtained from Biolog plates. These results demonstrate that Biolog plates are a suitable tool to detect functional capacities of microbial communities in soil in a given time point, and do not homogenize these abilities between different sampling times or treatments, fact already showed by other authors (Crecchio et al., 2004).

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Fig. 3. Canonical correspondence analysis (CCA) carried out with data of Biolog Eco plates measured at 120 h of incubation, together with other variables (see Statistics section). Vectors in the plot represent only those variables which significantly (p < 0.05) contribute to sample ordination (temp A, temp B, humidity and thymidine).

There are several works showing that variations in humidity could influence soil fungi and bacterial community composition (Schimel et al., 1999; Wilkinson et al., 2002). These variations in humidity seem to be important only in regulating microbial community composition in the upper part of the soil (which is in direct contact with the atmosphere), where changes in water content are sufficiently rapid and important to select bacterial groups with a high tolerance to stress because of lack of water (Harris, 1981). In addition, in the deeper soil layers, the quality and quantity of carbon substrates decrease and moisture and temperature became less variable (Richter and

Fig. 4. Average values of thymidine (solid bars), and leucine (empty bars) incorporation of all the sampling times (except t9 and t11) for each treatment. F = burnt. FR = burnt with retardant. NF = non-burnt. A: 0–1 cm soil depth. B: 3–4 cm soil depth. Letters a, b and c indicate significant differences between treatments within thymidine incorporation (n = 44). Letters x, y and z indicate significant differences between treatments within leucine incorporation (n = 44). Different letters indicate significant differences between treatments and the same letter indicate no statistical differences.

Markewitz, 1995). These two facts have been related to a different microbial community composition and activity between upper and deeper soil layers (Ghiorse and Wilson, 1988; Zvyagintsev, 1994; Fritze et al., 2000; Blume et al., 2002; Fierer et al., 2003). It is possible to presume that environmental gradients found with soil depth, produce changes in the microbial community composition of the soil. In spite of this, we also found statistical differences between treatments (F and FR) and control (NF), especially between FR and NF (Fig. 2), and also between F and NF (Figs. 2 and 4), consistent with D'Ascoli et al. (2005) who reported an effect of fire on soil functional diversity. With regards to effects of the retardant, Basanta et al. (2002) proved that retardant addition to soil did not produce changes in microbial biomass but increased enzymatic activity, suggesting a stimulation more than a toxic effect of that product on the microbial community. Our data support this hypothesis since significant differences were mainly found between control (NF) and retardant (FR) treatments. In some sampling times, retardant seems to have a stimulation effect (e.g. t1, t2, t6, t8), while in others it has an inhibitory effect (mainly in depth B. e.g. t7, t9, t10) (Fig. 2). In this sense, Dunn et al. (1985) and Adams and Attiwill (1991) pointed out that the addition of fertilisers improves microbial biomass and activity; due to the chemical nature of the retardant assayed, it could be acting in some way as a fertiliser, masking the effect of fire in burnt with retardant (FR) soil samples. It cannot be discarded either a retardant effect on some physicochemical properties of soil such as pH, soil aggregation, moisture, oxygen, etc. that could be causing these differences, as proposed by other authors (Diaz-Raviña et al., 2006). The retardant effect is evidenced on the slopes of regression lines obtained in the study of correlations between environmental factors and functional diversity (Table 2). When significant correlations appeared, regression lines slopes of retardant treatments were higher

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than in the others, speaking of a clear activation of microbial metabolism by the retardant. Diaz-Raviña et al. (2006) using the PLFA technique to study the structure of microbial communities, found that retardant increased the total amount of PLFA, indicating an activation in the microbial metabolism. CCA is a multivariate analysis which allows to obtain sample ordination (in this case, based on the Biolog plates substrate utilisation profiles) and it is also possible to include in the analysis other variables to determine if they influence these microoganisms' catabolic profiles. Among all the variables included in the analysis together with Biolog data, soil temperature (at both depths), soil moisture and thymidine incorporation significantly influenced Biolog Eco plates substrate degradation by soil microorganisms (Fig. 3). The influence of temperature and soil moisture has already been widely discussed in this work. However, when this new result about thymidine is considered, a connection between microorganisms activity and function may be established, indicating that the fact that microorganisms are more or less active, significantly influence the utilisation patterns of the substrates of the Biolog plates (Fig. 3). In the two dimensional ordination provided by this CCA, samples were grouped by sampling times. This means that seasonal variations (and therefore, environmental conditions) are stronger than the fire or the retardant effect (Fig. 3). This fact has been showed by others authors working in other ecosystems, Singh et al. (1991) established that fire effects on microbial biomass and on carbon and nitrogen mineralisation rates could be less important than effects of marked seasonal variations in savannah ecosystems, and Andersson et al. (2004) found that changes produced by fire in microbial biomass and activity were small compared with the substantial seasonal variations in the savannah. Angeler and Moreno (2007) also found a seasonal response in the case of zooplankton community resilience with retardant addition to the water at different concentrations. But they also found differences between samples with or without retardant and even within each season between samples from different months of retardant addition. Therefore, it seems that soil bacteria have a higher resilience than zooplankton after the addition of the same retardant. However, in both cases, the seasonal behaviour of those communities (bacteria and zooplankton) is clearly independent from the addition of the retardant. Techniques of labelled thymidine and leucine incorporation by bacteria offer a good possibility of measuring the gross bacterial growth rate in soil, which is not distorted by cell death and predation (Uhlirova and Santruckova, 2003). The thymidine and leucine incorporation by soil bacteria can be measured directly in a soil or in a soil extract obtained after homogenization–centrifugation of a soil sample. The use of the soil extract, i.e. the homogenization–centrifugation method (Bååth, 1992), deals only with an extracted portion of the original soil bacterial community. Although it has been demonstrated that the bacterial community obtained with the homogenization–centrifugation method is not representative of the total bacterial community of the soil (Bååth, 1996), the method has been routinely used in soil microbiology because of its clear advantages: (i) the extract contains fewer soil particles than the slurry; (ii) the isotope dilution is lower in the extract than in the soil slurry and, (iii) the method is markedly less time-consuming (Bååth, 1992). Fig. 4 show average activity values (thymidine and leucine incorporation rates) from all sampling times for each treatment. Burnt soil (F) had lower activity than non-burnt soil (NF) or soil burnt with retardant (FR). In the case of depth A (the soil that was in direct contact with fire) this difference was significant between the burnt (FA) and its control (NFA). Díaz-Raviña et al. (1996) also found an important decrease in thymidine and leucine incorporation in the first moments after the soil heating and afterwards, the incorporation rates were recovered. Based on results obtained, some important conclusions can be pointed out. Throughout the work it has been shown that in Mediterranean pastures and under the conditions of this study, the environmental factors have a deeper effect than the treatments (fire

and retardant), especially soil moisture. This fact was clearly shown in the seasonal variation that microbial communities suffer throughout the year after the fire, showing a similar successional behaviour irrespective of the treatment. We could hypothesise that microbial communities show a noteworthy grade of fire-accommodation, which can be correlated with the inherent presence of fire in the Mediterranean ecosystems. In particular, we can assume an important resilience and resistance of Mediterranean pastures to fire at the soil bacterial level. Nevertheless, the techniques used were able to detect changes caused by the fire and retardant. Despite the fact that both treatments produced minor changes, the retardant caused more changes. This is very interesting in public management of fire, since the use of retardants is done preventively, applying it before the fire. Given the tendency to increase large fires and, in particular, multiple large fire episodes, such as the one occurred in Greece in 2007, or in Portugal in 2003 and 2005, and the difficulty and risk of combating fires by the fire crews, the use of aerial means to deter fire spread, which in many instances involves the use of fire retardants, is becoming quite common. A recent concern is that fires are affecting many natural protected areas (Anonymous, 2008). The possibility of repeated use through the years, and the values at hand, indicates that further assessment of the impacts of these chemicals is needed in a different systems and conditions, given its widespread use. Considering the results overall, we can state that the changes caused by the application of retardant to the soils, did not lead to any major adverse effects on the microbial community as compared to the untreated soils. Therefore, it seems that retardants could be used to control wildfires and prescribed burns, since this treatment only slightly modified the composition and function of soil microbial communities and, in addition, the induced changes were negligible compared to those provoked by the burning. Finally, it is important to emphasise that results obtained are valid for the conditions of this study, since changes in length or fire intensity, type of vegetation, type of soil, etc., could produce different effects on the soil microbial community. Acknowledgement We wish to thank Beatriz Ramos Solano for her help in preparing the manuscript. References Abawi, G.S., Widmer, T.L., 2000. Impact of soil health management practices on soilborne pathogens, nematodes and root diseases of vegetable crops. Appl. Soil Ecol. 15, 37–47. Adams, M.A., Attiwill, P.M., 1991. Nutrient balance in forests of Northern Tasmania 2. Alteration of nutrient availability and soil–water chemistry as a result of logging, slash-burning and fertilizer application. Forest. Ecol. Management 44, 115–132. Andersson, M., Michelsen, A., Jensen, M., Kjoller, A., 2004. Tropical savannah woodland: effects of experimental fire on soil microorganisms and soil emissions of carbon dioxide. Soil Biol. Biochem. 36 (5), 849–858. Angeler, D.G., Moreno, J.M., 2007. Zooplankton community resilience after press-type anthropogenic stress in temporary ponds. Ecol. Appl. 17 (4), 1105–1115. Anonymous, 2008. Forest fires in Europe 2007. JRC Scientific and Technical Reports No. 8, p. 82. Bååth, E., 1992. Thymidine incorporation into macromolecules of bacteria extracted from soil by homogenization–centrifugation. Soil Biol. Biochem. 24 (11), 1157–1165. Bååth, E., 1994. Thymidine and leucine incorporation in soil bacteria with different cell size. Microb. Ecol. 27, 267–278. Bååth, E., 1996. Thymidine incorporation of bacteria sequentially extracted from soil using repeated homogenization–centrifugation. Microb. Ecol. 31, 153–166. Badía, D., Marti, C., 2003. Effect of simulated fire on organic matter and selected microbiological properties of two contrasting soils. Arid. Land. Res. Manag. 17 (1), 55–69. Basanta, M.R., Diaz-Ravina, M., González-Prieto, S.J., Carballas, T., 2002. Biochemical properties of forest soils as affected by a fire retardant. Biol. Fert. Soils 36 (5), 377–383. Basanta, M.R., Díaz-Raviña, M., Cuiñas, P., Carballas, T., 2004. Field data of microbial response to a fire retardant. Agrochimica 48, 51–60. Baudoin, E., Benizri, E., Guckert, A., 2001. Metabolic fingerprint of microbial communities from distinct rhizosphere compartments. Eur. J. Soil Biol. 37, 85–93. Blume, E., Bischoff, M., Reichert, J.M., Moorman, T., Konopka, A., Turco, R.F., 2002. Surface and subsurface microbial biomass, community structure and metabolic activity as a function of soil depth and season. Appl. Soil Ecol. 20 (3), 171–181.

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