Study area and sites
This study was conducted near Várzea (40°46’059”N, 7°51’726”W), North-central Portugal, after a wildfire on 9th September 2012 that burnt through a Pinus pinaster Ait. forest area. Climate is humid Mediterranean, classified as Csb (FAO 2006), with a dry period from June to August and peak rainfalls between October and March. Mean annual rainfall and temperature are 1200 mm and 14°C, respectively (SNIRH 2015). The earliest available wildfire records of this fire-prone area are from 1975 to present, and no prescribed fires have been recorded from this time interval (ICNF 2013). Within this area, we selected three hillslopes for each of the following wildfire frequencies (Fig. 1): 1) unburnt from 1975 to 2012; 2) burnt 1 time by one wildfire on Sept 2012 (1 fire); and 3) burnt 4 times namely by four wildfires on 1978, 1985, 2005 and 2012 (4 fires). The average wildfire frequencies corresponded, respectively, to > 39 years, 37 years and 9 years. Soil burn severity for the 2012 wildfire was estimated as moderate at the two burnt areas (using soil visual indicators described in Vega et al. 2013) with all the litter being transformed to a uniform black layer of charcoal, although in the hillslopes burnt 4 times the ash colour was grey in some spots (Table 1). As a consequence of the wildfire frequency, pre-fire vegetation cover was different between sites. The unburnt and the areas burnt 1 time (1 fire) were covered by mature Pinus pinaster woodland, with Pterospartum tridentatum (L.) Willk., Calluna vulgaris (L.) Hull and Agrostis spp., as the dominant understory vegetation. The areas burnt 4 times (4 fires) were shrubland, characterized by sparse 7 years old young pines regenerated from the previous wildfire in 2005, and dominated by Pterospartum tridentatum shrubs and the co-occurring species Agrostis spp., Calluna vulgaris, Cistus spp., and Halimium spp. (Fig. 1).
Table 1
General site characteristics, soil type and properties in the Ah topsoil layer (0–5 cm depth) of each site (unburnt (0x), 1 or 4 times burnt areas). Mean (and standard deviation) for the granulometric composition (%, n = 54), bulk density (g cm− 3, n = 54), soil organic matter content (SOM in %, n = 54), pH (n = 54), pF-curves (pF1, pF2, pF2.5, pF3.5, and pF4.2, in %, n = 54), and available water content (AWC in %, n = 54) on each area followed by a different letter were statistically different at p < 0.05. Comparisons were analyzed per mean values as well as per plant and bare microenvironments
Site
|
Unburnt
(0x)
|
Burnt 1 time
(1x)
|
Burnt 4 times
(4x)
|
General characteristics
|
|
|
|
Slope aspect (°)
|
210
|
210
|
200
|
Slope angle (°)
|
7–14
|
7–15
|
7–17
|
Pre-fire vegetation
|
Woodland
|
Woodland
|
Shrubland
|
Fire severity
|
Unburnt
|
Moderate
|
Moderate
|
Soil type and properties
|
Soil type (IUSS 2015)
|
Humic Cambisol
|
Umbric leptosol
|
Epileptic Umbrisol
|
Soil depth (cm)
|
30-35-40
|
15-20-25
|
30-35-40
|
Texture class
|
sandy loam
|
loam
|
loam
|
Sand/silt/clay (%)
|
55a/29b/15a
|
46b/38a/16a
|
48b/35a/16a
|
Bulk density (g cm− 3)
|
1.0(0.2)a
|
0.9(0.2)b
|
1.0(0.1)ab
|
SOM (%)
|
13(3) b
|
17(1) a
|
19(3) a
|
pH
|
4.9(0.1)a
|
4.6(0.1)a
|
4.7(0.1)a
|
Soil hydrological properties
|
pF0(%)
|
52(13)a
|
56(19)a
|
48(10)a
|
pF1(%)
|
52(13)a
|
55(18)a
|
46(10)a
|
pF2(FC; %)
|
38(10)a
|
40(14)a
|
34(7)a
|
pF2.5(%)
|
23(4)a
|
25(7)a
|
25(4)a
|
pF3.2(%)
|
12(1)c
|
16(3)b
|
18(3)a
|
pF4.2(PWP; %)
|
5(2)c
|
9(3)b
|
11(3)a
|
AWC (FC-PWP; %)
|
33(11)a
|
31(16)a
|
23(9)b
|
All selected sites had similar elevation (450–550 m.a.s.l.), slope aspect (200–210° azimuths) and steepness (7–8° on top to 14–17° on bottom slope positions), and the soils were developed from pre-Ordovician schist of the Hesperic Massif. According to IUSS (2015), the soils were classified at the unburnt areas as an association of Humic cambisol and Epileptic Umbrisol (dystric). In the 1 fire areas corresponded to Umbric leptosol and in the 4 fires areas to Epileptic Umbrisol. These soils were all acidic sandy loam in the unburnt areas and loam in the 1 and 4 fires areas. Soils were somewhat deeper in the unburnt and the 4 fires hillslopes (30–40 cm) as compared to 1 fire hillslopes (less than 25 cm). Topsoil Ah layers showed similar bulk density and pH, although the unburnt soils showed a somewhat coarser texture and lower SOM than the two burnt soils (Table 1).
Analytical methods
Rainfall
The rainfall data were recorded using 3 rainfall automatic gauges (ECRN-100 from Decagon devices) as well as 3 storage gauges in each of the three areas. In order to characterize rain volume and intensity for the whole area, median values were used.
Field measurements
During early November 2012, five resprouting Pterospartum tridentatum shrubs (target specie) and paired bare spots were randomly selected on each slope. In April 2013, three of these five shrubs (excluding the biggest and the smallest shrubs), together with their paired bare spots (total of 54 spots), were selected as experimental microsites to monitor the direct effects of wildfire (plant recovery and soil cover) as well as the indirect effects of wildfire (soil physical and hydrological properties). On each shrub, the maximum plant height and the length and diameter of five stems were measured in May, July and September 2013. On each of the 54 spots, soil samples were taken on May 2013.
Topsoil cover was measured on six 0.5 x 0.5 m plots per hillslope (three on shrub and three on bare microsites (n = 54 plots). Ground cover was assessed twice; three months and one year after the 2012 wildfire. Five cover categories were considered and classified as biotic (litter and vegetation) or abiotic (ash, bare soil and stones) cover components (Ruiz-Sinoga and Romero-Díaz 2010). Ground cover was quantified by laying a square grid of 0.5 m × 0.5 m at a fixed position over the plot and recording the cover category at 100 grid intersection points as a percentage (Prats et al. 2019).
Soil water repellence (SWR) was measured in the field by the molarity of ethanol droplet (MED) method at 2–3 cm depth, after removal of the ash and/or litter layer (Doerr et al. 1998). The measurements were made on a monthly basis in one hillslope per area (unburnt, 1 and 4 fires) in five equidistant sampling points along the slope length in bare soil spots. A total of 15 SWR measurements were made at every sampling occasion. The nine MED classes, ranging from 0 to 9, corresponded to increases in ethanol concentrations of 0%, 1%, 3%, 5%, 8.5%, 13%, 18%, 24%, 36 and > 36%. MED classes were grouped as follow: class 0, very wettable; classes 1, 2, 3, wettable/slightly water-repellent; classes 4, 5, moderate/strongly water-repellent; class 6, 7, very strongly water-repellent; and class 8, 9, extremely water-repellent.
Soil sampling
Main soil properties were characterized at each of the nine hillslopes by sampling the topsoil with 5 cm-height steel cores in April 2013. At each hillslope, topsoil samples were taken under the three shrubs and at three bare soil microsites (n = 54), after removing the above ash and/or litter layer. The samples were gathered with 100 cm3 steel cores for soil moisture content (SMC; % volume) after drying at 105ºC 24 h and soil organic matter (SOM; % volume) determination after sieving at < 2mm and incineration by loss-on-ignition at 550°C 4 h (ISO 11465, 1993). Another set of 54 samples was gathered for pH (ISO 10390, 2005), granulometric determination (Guitian & Carballas 1976) and bulk density analyses with 250 cm3 steel cores (Malvar et al. 2016). A third set of 54 samples (100 cm3 steel cores) was used for the assessment of soil water retention curves using a sandbox apparatus (Van der Harst and Stakman 1961) and a pressure plate device (Stolte 1997). The amount of water retained in the soil was calculated at five suction pressures: -1, -10, -33, -124, and − 1550kPa; corresponding respectively to: pF1 (saturation water), pF2 (field capacity, FC), pF2.5, pF3.2, and pF4.2 (permanent wilting point, PWP). Available water content (AWC; %) was calculated as FC - PWP, once water retained at PWP is not accessible for plant uptake (Chen et al. 2007; González-Pelayo et al. 2006). Additional soil samplings were carried out in June 2013 (n = 54) and September 2013 (n = 54), before the beginning of the dry period, to determine SOM and SMC.
Soil moisture probes
A total of 72 soil moisture sensors (Decagon Inc.) were installed in November 2012 in order to carry out a detailed assessment of the daily variations in SMC between the 1 time and 4 times burnt hillslopes. These burnt hillslopes were both affected by the 2012 wildfire and only differed in the wildfire frequency. Therefore, the sensors were installed at two soil depths (at 2.5 and 7.5 cm depth) under two microsites (shrub and bare) in each of the three shrubs selected in each of the six burnt hillslopes, totalizing 72 sensors (2x2x3x6). The EC5 and GS3 dielectric capacitance soil moisture sensors were connected to Em5b dataloggers, and determine volumetric soil moisture content (SMC; v/v) by measuring the dielectric constant of the media using capacitance/frequency domain differences. A capacitance sensor uses the soil as a capacitor element and use the soil charge storing capacity to calibrate to water content. They have a measuring range of 0.0–1.0 (m3 m− 3) and an accuracy of ± 0.03 m3 m− 3 typical in mineral soil solutions that have an EC < 8 dS/m. Besides volumetric water content, GS3 sensors can also measure bulk electrical conductivity in a range of 0–25 dS/m. To avoid influence of the hillslope aspect, all probes were oriented to 200–210° azimuths. SMC was measured at 5-min time intervals, which were averaged to obtain the daily SMC (n = 350, from 21 Nov. 2012 to 6 Nov. 2013). All the EC5 and GS3 sensors were calibrated before installation and the offset differences between sensors were minimized by making use of individual 4-point calibration in fluids with known apparent dielectric permittivity (following user´s guide available at www.metergroup.com). In this way, the mutual differences between sensors, which is especially important in the dry range, could be minimized and a high relative measuring accuracy could be obtained (van den Elsen et al. 2014).
Data analyses
The daily average SMC (%) and results obtained from pF-curves (FC, PWP) were used to calculate the effective soil water content (ESWC; %). The ESWC approach is intended to assess the water volume that is effectively available for plant uptake. It was assumed that the availability of soil water to plants is at best at FC, and it declines with decreasing SMC (Chen et al. 2007). At PWP, it is generally accepted that the soil water is no longer available for plants. The effective soil water content (% of the total available water) was calculated using the following formula (Porporato et al. 2002):
ESWC=(SMCactual−PWP)/(FC − PWP)
Where SMCactual is the average daily SMC measured with the soil moisture sensors (% volume). FC (field capacity) and PWP (permanent wilting point) were calculated from the pF-curves assessed from the soil samples adjacent to each sensor location (Van Genuchten et al. 1991).
Linear mixed-effects statistical models (Littell et al. 2006) were used to assess the differences in mean plant height, stem diameter, stem length, SMC and SOM with wildfire frequency (unburnt, 1 fire, 4 fires) as the fixed factor, and the plant/ topsoil sample as the random factor. Similarly, linear mixed-models were constructed to assess the differences in the daily SMC and ESWC among four fixed factors: wildfire frequency (1, 4 fires), soil depth (2.5, 7.5 cm), microsite (plant and bare), and season (autumn 2012, winter 2012–2013, spring 2013, summer 2013, autumn 2013). The individual soil moisture sensors were included as the random factor. The covariance structure of the repeated measures was modelled using a compound symmetry function or autoregressive heterogeneous variance, as it gave the lowest − 2 Res Log likelihood model-fitting values (Littell et al. 2006). In order to assure a normal distribution of the model residuals, plant variables, SOM and SMC were fourth-root transformed, while daily SMC and ESWC were log-transformed. Explanatory continuous variables were tested as covariates in a forward selection procedure, including daily rainfall, maximum 30-min rainfall intensity (I30), and accumulated rainfall amount from 1 (Ant_rain_1) and until 14 days (Ant_rain_14) before the daily SMC measurement. As the multiple rainfall characteristics are related, they were tested independently and only the variable with highest F-value was included in the model, following the principle of forward selection. Linear regressions and coefficient of determinations (R2) between the explanatory variables and the daily SMC and ESWC were calculated.
Differences in ground cover, bulk density, pH, pF-values and on SWR, were tested using mixed-effects models with or without repeated measures similar to the models described earlier, except no covariates were used. If the assumptions for equal variance and normality were not met, as it was the case of SWR, relative frequencies of each class were calculated, and the non-parametric Wilcoxon test was used to assess the differences between wildfire frequency and soil depths.
Comparisons among the fixed effects, as well as differences between the levels of the factors were tested by least-squares means and adjusted by the Tukey-Kramer method (Kramer 1956). All statistical data analyses were carried out using the SAS 9.4 software package (SAS Institute, Inc. 2008), and all statistical tests used α = 0.05.