Effect of a Wildfire and of Post-fire Restoration Actions in the Organic Matter Structure in Soil Fractions

1 Effect of a wildfire and of post-fire restoration actions in the organic matter structure 1 in soil fractions 2 3 Nicasio T. Jiménez-Morilloa,b, Gonzalo Almendrosc, José M. De la Rosad, Antonio Jordáne, 4 Lorena M. Zavalae, Arturo J.P. Grangede, José A. González-Pérezd* 5 aMED – Mediterranean Institute for Agriculture, Environment and Development, Instituto 6 de Investigação e Formação Avançada, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-7 554 Évora, Portugal. 8 bHERCULES Laboratory, Universidade de Évora, Palácio do Vimioso, 7000-089 Évora, 9 Portugal. 10 cMuseo Nacional de Ciencias Naturales (MNCN, CSIC), C/Serrano 115-B, 28006-Madrid, 11 Spain. 12 dInstituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS, CSIC), MOSS Group. 13 Av. Reina Mercedes, 10, 41012-Seville, Spain. 14 eMed_Soil Research Group, Facultad de Química, Universidad de Sevilla, C/Profesor García 15 González, 1, 41012-Seville, Spain. 16 17 *) Corresponding author: Tel +34 954524711; [email protected] 18 19 *Manuscript (double-spaced and continuously LINE and PAGE numbered)-for final publication Click here to view linked References Postprint of: Science of the Total Environment 728: 138715 (2020) GRAPHICAL ABSTRACT *Graphical Abstract HIGHLIGHTS  Analytical pyrolysis revealed differences among burnt, restored and unburnt areas  The fine fractions were more altered than the coarse and composition differed between scenarios  Fire induced defunctionalization of lignin phenols and the formation of recalcitrant compounds  Demethoxylation, dealkylation and dehydration were the main fire-mediated processes in SOM *Highlights (for review : 3 to 5 bullet points (maximum 85 characters including spaces per bullet point) 2 Abstract 20 The impact of wildfires and of restoration actions on soil organic matter (SOM) content and 21 structure was studied in a soil under pine (Pinus pinea) from Doñana National Park (SW 22 Spain). Samples were collected from burnt areas before (B) and after post-fire restoration 23 (BR) and compared with an unburnt (UB) site. Analytical pyrolysis (Py-GC/MS) was used 24 to investigate SOM molecular composition in whole soil samples and in coarse (CF) and 25 fine (FF) fractions. The results were interpreted using a van Krevelen graphical-statistical 26 method. Highest total organic carbon (TOC) was found in UB soil and no differences were 27 found between B and BR soils. The CF had the highest TOC values and FF presented 28 differences among the three scenarios. Respect to SOM structure, the B soil was depleted in 29 lignin and enriched in unspecific aromatics and polycyclic aromatic hydrocarbons, and in all 30 scenarios, CF SOM consisted mainly of lignocellulose derived compounds and fatty acids. 31 In general, FF SOM was found more altered than CF. High contribution of unspecific 32 aromatic compounds and polycyclic aromatic hydrocarbons was observed in B-FF whereas 33 BR-FF samples comprised considerable proportions of compounds from labile biomass, 34 possibly due to soil mixing during rehabilitation actions. The fire caused a 35 defunctionalisation of lignin-derived phenolics and the formation of pyrogenic compounds. 36 The van Krevelen diagram was found useful to—at first sight—differentiate between 37 chemical processes caused by fire and of the rehabilitation actions. Fire exerted SOM 38 demethoxylation, dealkylation and dehydration. Our results indicate that soil management 39 actions after the fire lead to an increase in aromaticity corresponding to the accumulation of 40 lignin and polycyclic aromatic compounds. This suggests additional inputs from charred 41 lignocellulosic biomass, including black carbon, that was incorporated into the soil during 42 rehabilitation practices. 43 3 Keywords: Wildfires, soil organic matter, soil rehabilitation, analytical pyrolysis, 44 chemometrics 45 1. Introduction 46 Fire is considered one of the main environmental disturbing factors (Neary et al., 2005). In 47 fact, it is estimated that over 8-billion Mg of biomass is burnt globally every year (Levine, 48 2000). Up to 18% global biomass burning occurs in European forests and mainly in 49 Mediterranean areas where the largest number of fire events (≈50.000 per year) are 50 recorded. Only during 2018, over 7 thousand fire events occurred in Spain that affected 51 more than 29.000 ha of forest (MAPA Spain, 2019). Wildfires may have negative impacts 52 on soil fertility, biodiversity, land resources, global warming and human assets, but also 53 positive environmental effects can occur such as enhanced forest regeneration and nutrient 54 recycling (Stephens et al., 2009). Nonetheless, the positive or negative impact of fire on a 55 particular ecosystem will depend on many factors i.e., fire severity, weather conditions, soil 56 type, topographic constraints vegetation type, fuel characteristics and soil moisture, etc. 57 (Certini et al., 2005; De la Rosa et al., 2008a). 58 In general, the effect of an average wildfire on the soil profile is restricted to the surface and 59 shallowest layers (< 5 cm depth) (Aznar et al., 2016, Badía et al., 2014). However, is in this 60 uppermost layer where most of the SOM is located and affected to a greater extent by the 61 impact of fire. Therefore, fire may affect primarily topsoil SOM exerting thermal removal 62 (combustion) of all or part of this organic layer, leading to a transformation of the original 63 SOM and the emergence of newly-formed structures, or even in the short time after the fire, 64 a build-up of biogenic partially charred biomass in the form of additions from the fire-65 affected standing vegetation. So, fire-affected SOM may ultimately consist of a complex 66 mixture of more or less transformed materials with different origin (pyrogenic or biogenic) 67 (González-Pérez et al., 2004, 2008; Jiménez-Morillo et al., 2016a; Miller et al., 2020). 68 4 It is known that the effect of fire on SOM chemical composition leads to a loss of 69 lignocellulosic material that dominates in plant biomass, and to a concomitant increase in 70 recalcitrant carbon compounds (De la Rosa et al., 2008b; González-Pérez et al., 2004; 71 Tinoco et al., 2006) made up mainly of condensed structures produced by dehydration and 72 cyclization reactions of raw material (Baldock and Smernik, 2002). Such carbon combustion 73 products, collectively referred to as black carbon, have not a defined structure, ranging from 74 residual charcoal to highly graphitized soot (Goldberd, 1985). 75 After a wildfire event, Governmental environmental agencies and responsible bodies—in an 76 attempt to revert the effects of fire—invest many resources in rehabilitation actions. Such 77 actions include a wide spectrum of management activities, ultimately motivated by aspects 78 other than environmental health rehabilitation, and that usually include economic, cultural 79 and even aesthetic components (Castro et al., 2010; Lindenmayer and Noss, 2006; McIver 80 and Starr, 2000). 81 Amongst the most frequently used actions are: i) removing the burnt trees, also known as 82 “salvage logging” (McIver and Starr, 2000); ii) remove and plough the land; and iii) 83 reforestation with native or alien vegetation. Nevertheless, some of these practices may be 84 harmful to soil, sometimes producing more damage than the fire itself. For instance, salvage 85 logging can degrade ecosystem functions and vegetation regeneration, animal and plant 86 diversity, watershed runoff and erosion and nutrient cycling (Castro et al., 2010; Karr et al., 87 2004; Lindenmayer et al., 2008). For this reason, a body of research has focused in the study 88 of rehabilitation activities, that far from ameliorating post-fire conditions often introduce 89 further disturbances that delay the natural ecosystem recovery (Beschta et al. 2004, 90 Lindenmayer et al. 2008; Pereira et al 2018; Shakesby et al., 1996). By contrast, there is a 91 knowledge gap in the study of both, the direct and indirect effects caused by post-fire 92 rehabilitation activities on the quality of SOM. Furthermore, it is expected that changes 93 5 produced by rehabilitation activities on the vegetation, soil microbiota and even carbon and 94 nitrogen storage should also play a relevant influence on SOM chemical composition and 95 properties. Analytical pyrolysis (Py-GC/MS) is a fast, direct and reproducible technique 96 increasingly used to explore the chemical composition of complex organic materials and 97 specifically of fire-affected SOM and their fractions (e.g. Almendros et al., 2018; De la Rosa 98 et al, 2018, 2019; Jiménez-González et al., 2016; Jiménez-Morillo et al., 2016a). Pyrolysis is 99 defined as the thermochemical decomposition of organic materials at high temperatures in 100 the absence of oxygen (Irwin, 1982). It is an analytical degradation technique that converts 101 macromolecules into small fragments, which can be further separated and identified by gas 102 chromatography-mass spectrometry (GC/MS). The pyrolytic fragments are considered to be 103 representative of the original larger macromolecules (González-Vila et al., 2009; Leinweber 104 and Schulten, 1993; Martin et al., 1979). 105 Recently the pyrolysis characteristics of soil humic substances (HS) have been investigated 106 using TG-FTIR-MS and kinetic models and the results effectively associated to the thermal 107 degradation of various functional groups and compounds in HS (Li et al., 2020). The authors 108 found that most of the gas species from HS pyrolysis evolved at a temperature range of 250–109 500 °C and forecasted that findings for the pyrolysis of soil HS will be critical for predicting 110 changes of the global carbon cycle and soil ecosystems as affected by future climate and fire 111 regimes. 112 The combination of graphical-statistical methods, such as van Krevelen diagrams (van 113 Krevelen, 1950), with other data i.e. proportions of compounds released by analytical 114 degradation methods, has experienced a noticeable development to monitor chemical 115 changes on SOM produced by natural or anthropogenic impacts (Almendros et al., 2018; 116 Jiménez-Morillo et al., 2018). Recently, the combination between van Krevelen diagrams 117 done from the chemical molecular formulas of Py-GC/MS released compounds has been 118 6 used to evaluate the chemical alteration produced by a wildfire event on SOM and sieved 119 fractions (Jiménez-Morillo et al., 2016a). 120 We hypothesize that, after a forest fire in particularly vulnerable ecosystems, restoration 121 rehabilitation management techniques involving mechanical disruption of the topsoil, may 122 cause additional impacts on soils leading to more severe effect than that directly caused by 123 fire. Consequently, this work describes the effects of fire on the chemical composition of 124 SOM and main size fractions, before and after rehabilitation actions. For this purpose, we 125 use a novel perceptual approach combining analytical pyrolysis and a van Krevelen 126 graphical-statistical method, to detect and characterize main chemical changes exerted by a 127 forest fire in SOM from bulk and sieved soil fractions (coarse and fine) under pine (Pinus 128 pinea) forest in Doñana National Park (SW Spain). 129 130 2. Materials and Methods 131 2.1. Sampling area 132 A sandy soil classified as Arenosol (FAO, 2015) with a 99.2% of aeolian sand (Holocene) 133 covering gravel and other sandy sediments (Pliocene-Pleistocene), neutral pH (6.8) and C 134 and N contents of 8.52 % and N 0.96 % respectively was chosen for this study. The area 135 under study is located at “Las Madres” site within the Doñana National Park (SW Spain) 136 premises, one of the most important Mediterranean environmental reserve in Europe. The 137 morphology and vegetation cover in the study area have intimately been associated with 138 frequent and recurrent wildfire episodes ranging from low to medium-high severity. The 139 study area is covered with Mediterranean vegetation dominated by pine (Pinus pinea) and an 140 understory of bushes of Halimium halimifolium, Daphne gnidium, Ulex europaeus, 141 Rosmarinus officinalis, Lavandula angustifolia, Genista pseudopilosa and Erica arborea. 142 7 This area is influenced by a Mediterranean climate, where wildfires occur during the 143 warmest, dry season with extreme temperatures. Rainfall is episodic (average 550 mm year144 1) and highly variable ranging from 200 mm and 1100 mm in a unique rainfall regime and an 145 almost total absence of rain events during the summer (Siljeström and Clemente, 1990). 146 The sampling area was affected by a wildfire episode in August 2013, burning 80 ha of the 147 pine forest. Two months after the wildfire event, forest managers commenced the restoration 148 actions, which consisted of salvage logging, removing burnt trees, tillage (plough) and 149 reforestation with nursery pine species. The sampling was carried out after the wildfire event 150 and one year after the restoration actions (October 2014). Three composite samples were 151 collected; two in a burnt area, before (Burnt “B”: 37° 4'13.27"N, 6°37'18.71"W) and after its 152 restoration (Burnt and restored “BR”: 37° 4'11.10"N; 6°37'17.86"W). Also, a control soil 153 sample was collected in a neighbour area not affected by fire (Unburnt “UB”: 37° 4'9.00"N; 154 6°37'16.54"W). All samples were collected in duplicate in nearby points under the same 155 vegetation cover, soil type, physiographic and climatic characteristics. The UB sampling 156 place has a known history of more than 10 years without being affected by fire. Each 157 composite sample was prepared by combining six sub-samples taken within a circular area 158 of c. 20 m2 under a well-developed vegetation cover. After the removal of the litter layer, the 159 top 3 cm of soil was sampled and transported to the laboratory in glass containers to avoid 160 contamination by plasticizers and other alien substances. The soil samples were air-dried at 161 laboratory conditions (at 25 °C and approximately 50% relative humidity) during 1 week 162 and sieved (< 2 mm, fine earth) to remove gravel and litter fragments. Each combined fine 163 earth sample (total or whole sample) was further divided by dry sieving into two fractions 164 (1–2 mm “coarse (CF)” and <0.05 mm “fine (FF)”). 165 2.2. Total Organic Carbon (TOC) 166 14 Our results showed that SOM from coarse fractions from unaffected (UB) and fire-affected 313 (B and BR) soils consists of fresh material (i.e., mainly composed of carbohydrates and 314 lignin-like compounds) (Table 1, Figs 2 and 3). Jiménez-Morillo et al. (2018), using ultra-315 high resolution mass spectrometry, observed this fact in a nearby area but under cork oak 316 canopy. Nevertheless, the fire effect is perceptible in B and BR coarse fractions and 317 reflected in an increase of UAC and a decrease of lignin and alkyl compounds (Fig. 2). This 318 may be caused by two main mechanisms: i) the incorporation of new pyrogenic material 319 characterized by a condensed structure and ii) the chemical alteration of lipid compounds in 320 both charred litter and oldest SOM in the soil surface. In fact, fire may produce either a 321 cycloaddition of alkene compounds by the Diels-Alder pathway (Jiménez-Morillo et al., 322 2018), followed of an aromatization reaction or as González-Pérez et al. (2008) found, 323 thermal evaporation of free lipids together with a thermal cracking process. This trend is 324 also observed in the case of coarse fractions, in particular the decrease in the content of alkyl 325 products, however the samples retain in all cases an appreciable lignin content, which may 326 correspond to the predominance of partially-decomposed plant remains in the coarse 327 fractions. In the case of the coarse fraction of B and BR soil, a greater similarity is observed 328 concerning the original soil; in fact, a significant proportion of carbohydrate and lignin has 329 been re-established and the loss of aliphatic compounds both alkanes and fatty acids is not 330 noticeable. On the other hand, the BR coarse fraction showed a high relative amount of 331 lignin-like and polysaccharide compounds. This may be due to a further input of wood 332 material during logging activity from the sawed branches and stems, adding an uncommon 333 amount of lignocellulose compounds to the soil. 334 On the opposing side, SOM in the fine fraction showed a more pronounced humic character, 335 with a remarkably high proportion of UAC, alkyl and protein-like compounds and a low 336 proportion of polysaccharides and lignin-like compounds. This may be attributed to 337 enhanced biological activity. Kellner et al. (2014) observed that some fungal species can 338 15 defunctionalize lignocellulosic material producing UAC. Concerning the presence of alkyl 339 compounds, lignin oxidation by enzymatic hydroxyl radicals involves ring hydroxylation 340 and ring-opening to produce unsaturated aliphatic compounds (Higuchi, 2004). In this 341 research, it is observed that fire, directly or indirectly, may affect the chemical composition 342 of SOM in soil fine fractions. Recently, Jiménez-Morillo et al. (2018) observed that burnt 343 SOM in fine soil fractions consists of two differentiated C pools; one from the microbial 344 alteration of SOM and other from inputs of pyrogenic material. The van Krevelen density 345 map of B-FF (Fig. 2H), as well as its position in the PCA biplot (Fig. 3), points again to the 346 fact that SOM in this soil shows two well-differentiated C pools. After the wildfire, fine 347 fractions contain a relatively high proportion of lignin-like compounds that suggest 348 additional input of partially charred wood particles. On the other hand, the large proportion 349 of carbohydrate and fatty acids in BR-FF (Fig. 2I) may indicate that restoration activities 350 have produced a mixing of the newer and older SOM. 351 4.3. Chemical reactions produced by the fire. 352 The two-dimension contour van Krevelen plot diagrams obtained by subtracting the 353 compound abundances from pairs of samples corresponding to the different scenarios (Fig. 354 4) is auto-explicative and summarizes the selective effects of fire and restoration in the soil 355 physical fractions. In these graphs, the proportion of compounds that predominate in the 356 burnt samples with respect to the unburnt or restored presents positive values and are 357 depicted in red colour (it would indicate both, a generation of pyrogenic products or the 358 selective accumulation of heat-resistant structures or both). Conversely, compounds that are 359 more abundant in soils not affected by fire, or in soils subjected to rehabilitation practices 360 present negative values and are shown in blue. Then, positive and negative values (red, blue 361 respectively) illustrate accumulation or depletion of pyrolytic compounds characteristic for 362 each compared scenario, then simplifying the visual identification of the balance between 363 16 compound groups which reflect with its abundances the impact of fire in the whole soil and 364 its different soil particle fractions. 365 Therefore, in the whole bulk soil fire produced two different reactions depending on if it was 366 restored or not. A reduction chemical reaction in the B bulk soil sample is evidenced by the 367 elimination of carbohydrates and lignin-like compounds. Within particle size fractions, there 368 were differences between coarse and fine, but there were no major differences between 369 sample before and after restoration. The B and BR coarse fraction suffered an oxidation 370 reaction, which could be well linked with an input of new litter (rich in lignocellulosic 371 compounds). On the other hand, a hydration reaction (rising O/C and H/C) observed in the 372 fine fraction may be attributed to the relative increase of alkyl, carbohydrate and lignin-like 373 compounds. This result is in agreement and confirms previous findings by Jiménez-Morillo 374 et al. (2016a). 375 376 5. Conclusions 377 The results obtained suggest that fire and restoration are factors with a significant effect on 378 the quantity and quality of the SOM. The fire leads to a depletion of organic matter in the 379 whole soil and its coarse fraction, resulting from losses of volatile compounds. On the 380 contrary, the concentration of organic matter in the fine soil fraction increased to some 381 extent, at expenses of pyrogenic material from the combustion of the organic matter in 382 coarser fractions. The restoration, produces a general decrease in soil organic matter levels, 383 to a large extent attributed to the mixing and turning of topsoil materials with deeper soil 384 layers, with lower organic carbon content. Concerning SOM quality, the combined use of 385 statistical techniques, such as PCA and the representation of the pyrolytic results as surface 386 density plots in the space defined by the atomic ratios of the pyrolysis compounds, 387 suggested independent changes in SOM either produced by fire or by the subsequent 388 17 restoration. The non-restored soil samples consist of three different types of organic matter: 389 i) extensively transformed organic matter, with a large influence of alkyl compounds from a 390 possible microbial activity, the same occurs in the unburned sample, ii) organic matter from 391 the partial combustion of plant residues in coarsest particle fractions, mainly thermally 392 altered lignin and iii) heavily condensed, aromatic organic matter of pyrogenic origin. On 393 the opposing side, the organic matter contained in the restored fine fraction shows a 394 remarkable proportion of fresh material (lignin, carbohydrates and fatty acids). 395 To the best of our knowledge, this is the first attempt to explain the effect of post-fire 396 rehabilitation in SOM composition at a molecular level. A better knowledge of the effect of 397 fire and of rehabilitation practices in SOM and its evolution with time using appropriate and 398 easy to interpret graphical statistical approaches may help decision-makers in choosing the 399 best practices to optimize soil post-fire management and rehabilitation strategies. 400 401 Acknowledgements. 402 To projects INTERCARBON, CARBOSOIL, and POSTFIRE Projects (CGL2016-78937-R, 403 CGL2013-43845-P and CGL2013-47862-C2-1-R, respectively) funded by the Spanish 404 Ministry for Economy and Competitiveness. The authors also thank project EROFIRE 405 (PCIF/RPG/0079/2018) funded by Fundação para a Ciência e a Tecnologia (FCT, Portugal). 406 N.T. Jiménez-Morillo was funded by an FPI research grant (BES-2013-062573). Alba 407 Carmona Navarro and Desire Monis Carrere are thanked for their technical assistance in 408 Py/GC–MS analysis. 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