What processes happen in the soil and plants during a shift?
Authors: Ángeles G. Mayor, V Ramón Vallejo, Susana Bautista with Peter de Ruiter, Lia Hemerik, Violette Geissen, Jaap Bloem, Jacob Kéizer, Óscar González-Pelayo, Ana Isabel Machado, Ana Vasques, Christel van Eck, Martinho Martins, Paula Maia, Alejandro Valdecantos, Jaime Baeza, Joan Llovet and David Fuentes
Editor: Jane Brandt
Source document: Mayor et al. (2015) Identification of critical changes preceding catastrophic shifts: ecosystems affeced by increasing wildfire recurrence. CASCADE Project Deliverable 3.1a

 

The main objectives of the measurements were

  1. to determine whether fire recurrence levels promoting shifts from pine woodlands to shrubland communities in Southern Europe are associated with shifts in soil fertility,
  2. to assess if different types of soil surface cover (i.e., that below shrub patches and that in the openings between shrubs) have different sensitivity to fire recurrence effects, and
  3. to identify the most sensitive indicators of changes in soil functioning in response to repeated fires.

Study sites

Two of the CASCADE study sites, Várzea (Portugal) and Ayora (Spain), are affected by increased wildfire recurrence and high fire frequencies have promoted a transition from pine woodlands to shrublands. The two sites are representative of fire-prone regions in Southern Europe, Ayora under fully Mediterranean climate and Várzea under Atlantic climate with some Mediterranean influence.

For a general description of these sites see

»Várzea Portugal: Description of site and main causes of degradation
»Ayora Spain: Description of site and main causes of degradation

The sites include plots characterized by different fire histories that are summarized in Table 1. We combine a diachronic approach (Várzea) for assessing short-term fire effects with a synchronic approach (Ayora) for long-term effects of fire recurrence. In Várzea, two fire recurrence areas (1 and 4 fires), both last burned by a wildfire in the summer of 2012, and a reference fire-free area for the last 35 years were selected. Three plots (30 x 30 m) were set up in each of the three areas (total of 9 plots). The study site in Ayora has plots affected by natural and experimental fires from previous studies and represents a chronosequence in fire recurrence and time since the last burn. It includes three fire recurrence levels (1, 2, and 3 fires) and a reference fire-free for the last 30 years in three different areas (Ayora, Alcoy, and Onil). Three plots (30 x 30 m) were set up in each fire level and area (total of 12 plots). In each site, the plots were selected to have physiographic and edaphic properties as comparable as possible (Table 1).

D3.1a tab01
Table 1

Sampling and chemical analysis

In both study sites, microsites beneath and between shrubs (hereafter, shrub and intershrub) of the most representative species were identified and three 1-m² subplots per plot were randomly located in each microsite. Shrub microsites were Pterospartum tridentatum (resprouter) in Várzea, and Quercus coccifera (resprouter) and Rosmarinus officinalis (obligate seeder) in Ayora. One sample of mineral soil at 0-5 cm was taken in each subplot in spring 2013. For both study sites, soil samples were analysed for total organic carbon (SOC), total nitrogen (N), NH4, NO3, Potentially Mineralizable Nitrogen (PMN), and available phosphorus (Pava). Additionally, hot-water extractable carbon (HWC) and dissolved organic carbon (DOC) were analysed in Várzea and Ayora, respectively. HWC was determined as the amount of dissolved organic carbon that is released during incubation of a soil sample in hot water during 16 hours at 80°C (Ghani et al, 2003). This is a measure of easily decomposable (labile) organic carbon. The HWC fraction of organic matter is rich in amorphous polysaccharides (mucigel) which originate mainly from microbial exudates and to a lesser extent from plant exudates. This fraction is highly available to microorganisms and is also regarded as one of the key labile components of organic matter responsible for soil micro-aggregation, which is an important soil physical parameter to consider in terms of soil quality (Ghani et al. 2003, Haynes 2005). Total organic C was determined using the potassium dichromate oxidation (Walkley-Black) method (Nelson and Sommers, 1982). Total N was determined by the Kjeldahl method (Bremmer and Mulvaney, 1982), and available P by the NaHCO3-extractable Pi (Olsen-Pi) as described by Watanabe and Olsen (1965). Potentially mineralizable N was determined by anaerobic incubation of a soil sample under water for 1 week at 40°C (Keeny and Nelson, 1982; Canali and Benedetti, 2006) These warm and anoxic conditions are optimal for a quick mineralization of organic matter by anaerobic bacteria. The lack of oxygen prevents conversion of released NH4+ to NO3- (nitrification) and uncontrolled N losses by denitrification cannot occur. The amount of mineral nitrogen (NH4-N) released is a measure of the quality (N-content and decomposability) of the organic matter, and thus for biological soil fertility.
In addition to the total values, we calculated the next ratios expressing the values of different nutrients relative to their source: HWC:SOC, PMN:N, NH4:N, NO3:N, and Pava:SOC. These ratios are used as indicators of the quality of the soil organic matter and allow comparisons between sites with contrasting amounts of soil organic matter, as it is the case for the two study sites.

Statistical analysis

An analysis of variance was performed for each of the soil variables measured, using recurrence and microsite as fixed factors. Additionally, plot (nested in recurrence), and area and plot (this latter nested in the interaction recurrence X area) were used as random factors in the Várzea and Ayora datasets, respectively.

Principal component analysis (PCA) was used to reduce the original set of variables of the soil organic matter quantity matrix (SOC, N, NH4, NO3, PMN, Pava, and HWC or DOC) and quality matrix (HWC:SOC, PMN:N, NH4:N, NO3:N, and Pava:SOC) into a smaller set of uncorrelated components that represent most of the information found in the original variables. Variables were transformed if needed to fit normal distributions. Statistical analyses were performed with SPSS vs. 20.

For the detailed results from the two sites see

» Várzea Portugal: Critical changes preceding a catastrophic shift
» Ayora, Spain: Critical changes preceding a catastrophic shift


Note: For full references to papers quoted in this article see

» References

Go To Top