Next Article in Journal
The Effect of Organic vs. Conventional Cropping Systems on the Yield and Chemical Composition of Three Courgette Cultivars
Previous Article in Journal
Development and Characteristics of Interspecific Hybrids between Brassica oleracea L. and B. napus L.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 10
Issue 9
10.3390/agronomy10091340
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Short-Term Effects of Pile Burn on N Dynamic and N Loss in Mediterranean Croatia

by
Domina Delač
1,
Paulo Pereira
2,
Igor Bogunović
1,* and
Ivica Kisić
1
1
Faculty of Agriculture, University of Zagreb, 10000 Zagreb, Croatia
2
Environmental Management Laboratory, Mykolas Romeris University, LT-08303 Vilnius, Lithuania
*
Author to whom correspondence should be addressed.
Agronomy 2020, 10(9), 1340; https://doi.org/10.3390/agronomy10091340
Submission received: 17 July 2020 / Revised: 31 August 2020 / Accepted: 4 September 2020 / Published: 5 September 2020
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Versions Notes

Abstract

:
There is a lack of information in the rural Mediterranean area about agricultural pile burning impacts on soil nitrogen (N) dynamic and the N loss. Therefore, this research aims to study the impacts of moderate (MS), and high (HS) severity burn on N transformation and N losses, compared to an unburned (C) during the first year. The experimental plots (10 m2) were established in Croatia (43°58′ N 15°31′ E), in a slope ~18°, with a southwest exposition. Five days after the burn, C treatment had a significantly higher total N (TN) than MS and HS. Generally, the runoff was significantly different between burned and C treatments. Sediment yield, concentrations, and TN loss were significantly higher in MS than in C treatment. The concentrations of ammonium (NH4-N) and nitrate (NO3-N) in the runoff, and their losses were higher in burn treatments than in C treatment. These values were high in the first three months after burn, although the peaks in later periods correspond to extreme rainfall events. Principal component analysis showed that sediment yield was associated with sediment concentration, runoff, and TN loss (Factor 1). In addition, rainfall amount and intensity were inversely related to NH4-N concentration and losses (Factor 2). The NO3-N concentration was positively related to NO3-N losses. Overall, MS treatment had severe effects on N loss and, sediment yield can be used as an indicator of soil degradation after pile burns.

1. Introduction

The risk of wildfires in Mediterranean areas increased with rural depopulation and the consequent accumulation of fuel in woodlands due to the lack of management [1,2], the prohibition of using fire for landscape management, and climate change [3]. However, burning agricultural residues in piles is a cost-effective alternative for reduction residues when the management of the landscape with fire is forbidden [4]. Pile burn is a widely adopted practice in the rural Mediterranean area for residues management [5,6] despite the environmental impacts (e.g., air and water pollution). Even though the environmental impacts can be relevant, the effects of this practice are poorly studied. Burning residues heat the soil (direct impacts), changing their properties depending on the severity of the burn [7]. In the period post-burning, the ash produced (indirect impacts) will affect the soil properties and the hydrological response [8]. Pile burns expose soils, increasing their vulnerability to erosion and overland flow. Nutrient losses occur mainly in the first months after burning [9,10]. The magnitude of post-burn nutrient loss is variable and depending on the interplay between burn severity, post-burn weather patterns, type of burned biomass, topography, soil properties, and land use [10,11,12] The varied Mediterranean landscape, such as abandoned terraces and intricate land-use patterns, lead to the different response of post-burn erosion at different sites and spatial scales [13].
Nitrogen (N) loss by volatilization is well documented [14], but less attention has been paid to the impacts of pile-burning on soil N chemical forms and losses in overland flow. N losses occur through the combustion of organic matter or water and sediment transport [15,16,17], contributing to water body pollution [16]. The N volatilization starts at ~200 °C, and the losses increase with temperature increasing [14,17]. The N that is not volatilized remains in the ash and can be converted to other available inorganic forms, such as ammonium (NH4-N) and nitrate (NO3-N). Conservation of ammonium (NH4-N) to nitrate (NO3-N) by nitrifying bacteria is one of the crucial steps leading to the transformation of inorganic N in the post-burn period [18,19,20]. Moreover, the process behind the increased inorganic N loss after a burn is still not well understood because of the cycle and complex nature of inorganic N transformations [21]. During burning, temperature controls the N release rate depending on the intensity [17]. Almost all N is volatilized at temperatures higher than 500 °C, and there is an increase in inorganic N [18,22]. High burn severity leads to a high N loss thought erosion or runoff [14,23,24]. After a moderate severity burn (~300 °C), substantial portions of soil organic N remain or changing its form [11].
Research about the impacts of pile burn severity on soil N and transported in sediment is lacking. This work aims to study the impacts of a pile burn in (a) soil and (b) sediments N forms according to different severities.

2. Materials and Methods

2.1. Study Site and Location

The experimental site is located in Croatia (43°58′ N 15°31′ E; 20 m a. s. l.), with a slope of ~18°, and southwest aspect. The soil type is classified as Leptosols (IUSS Working Group WRB, Vienna, Austria 2015), with 5%, 58.9%, and 29.6% of sand, silt, and clay. According to Köppen’s climate classification, the climate is Mediterranean Cfb (warm temperature with fully humid and warm summer) [25]. The mean annual temperature (1961–2019) is 15.2 °C, and the mean annual precipitation is 851 mm (Ravni Kotari meteorological station, 6 km from the experimental site, Polaca, Croatia). The location is surrounded by a mosaic of arable and permanent crops, vegetables, and vineyards. In this area, the residues’ management using fire is common, especially in late winter or early spring.

2.2. Experimental Designs and Laboratory Analyses

The experiment included moderate severity (MS), high severity (HS), and unburned treatment–control (C). MS treatment represented the burning of 10 kg m−2 barley straw, and HS treatment 10 kg m−2 barley straw, and 15 kg m−2 vine stem. One treatment covered an area of ~10 m2. The meadow plants (Foeniculum vulgare Mill., Elymus repens (L.) Gould, Digitaria sanguinalis (L.) Scop.) and the Maquis shrubland are the dominant vegetation in the study area and C treatment. The experiment was set up on the agriculture sloped terrain, abandoned 40 years ago. Fifteen metal rings (5 per treatment) with 0.2 m2 area were set before biomass deposition. Biomass was staggered equally on burn treatments to obtain similar burn effects on each ring. Piles were burned on 18 March 2019 in 26- and 40-min duration on MS and HS plots, respectively. Burn severities were assessed by observing ash color, using the Munsell color chart [26]. After the burn, on the side of the rings facing downstream, a plastic tube was mounted to 5 L collectors to monitor runoff and soil loss. The first runoff was collected 5 days after the burn (DAB), and then approximately every 25 days in a period of 247 days, after rainfall events.
Additionally, soil samples (0–3 cm) were collected in the vicinity of each plot 5, 122, and 247 DAB, and ash samples immediately after burn (IAB) for total N (TN) determination. Soil and ash samples (ash only in the burned plots) were collected in 5 repetitions along each ring, stored in plastic bags, and taken to the laboratory for analysis. Sediment yield was determined by filtering (2 µm filter paper) after air-drying at room temperature and weighting of the filter paper. TN loss was determined after the calculation of TN concentrations with the mass of sediment yield. Additionally, the runoff was filtrated through active carbon and 0.45 µm filter paper to determine runoff NH4-N and NO3-N concentrations with a Dionex ICS-1000 system. TN content was obtained by a dry-combustion method with a vario MACRO CHNS analyzer.

2.3. Statistical Analyses

Before statistical analysis, data were checked for normality with the Kolmogorov–Smirnov test. Data were considered normal at p > 0.05 level. Only of ash and soil TN followed the Gaussian distribution. One-way ANOVA was applied to test whether ash TN varied significantly between MS and HS treatments, and two-way ANOVA was applied to observe differences between sampling dates and treatments for soil data. The data of runoff, sediment yield, sediment concentration, N concentrations, and N loss were tested with several data transformation methods, such as logarithm, square root, and Box-Cox to see which one normalized most data distribution. The transformed data did not correspond to raw scale data (i.e., means), so a two-way ANOVA was applied to raw data to identify differences among treatments and dates. All comparisons were carried out with the Fisher post-hoc test to identified significant differences at p < 0.05 level. Original data were presented in graphics and tables. A principal component analysis (PCA) was carried out (using the original data), based on the correlation matrix to identify the relations among all variables. All analyses were performed using Statistica 12.0 for windows.

3. Results

3.1. Post-Burn Rainfall

Figure 1 shows total rainfall between sampling dates and the maximum 30-min rainfall intensities (I30). In the period between experiment setup and 5 DAB, there was a total of 20 mm rainfall. Approximately every 25 days, between 5 and 85, a similar amount of rainfall was observed (50 mm), and then decreased between 85 and 122 DAB (35 mm). A higher amount of rainfall occurred in the period from 122 to 155 (72 mm), and then a decrease in rainfall amount (20 mm) was noted until 180 DAB. The major rainfall occurred between 208 and 247 DAB (188 mm). The maximum 30-min rainfall intensity (I30) was noted at 247 DAB, followed by 85 and 155 DAB.

3.2. Ash and Surface TN Content

Pile burn severity did not affect (p > 0.05) the ash TN content. The content of soil TN was not significantly different between treatments and sampling dates (Table 1). Treatment × sampling date interaction (p < 0.05) indicate a significant effect on soil TN. At 5 DAB, the soil TN content was significantly higher in C treatment than at MS and HS treatments. Seasonal dynamic at C treatment shows significantly higher TN at 5 than at 122 and 247 DAB.

3.3. Runoff and Sediment Characteristic

Runoff was significantly different among treatments (F = 22.3, p < 0.0001), sampling dates (F = 11.2, p < 0.0001), and in the treatments × sampling dates interaction (F = 1.9, p < 0.05). At 25, 52, 65, 85, 155, and 247 DAB, runoff was significantly higher in MS and HS than in C treatments. In the C treatment runoff, no significant differences were observed among dates. In MS treatment, the runoff was significantly higher at 52, 65, 155, and 247 than at 5, 85, 122, 180, and 208 DAB. In HS treatment, runoff was significantly higher at 247 than at 5, 65, 85, 122, 155, 180, and 208 DAB. Likewise, at 25, 52, 65, and 155, runoff was significantly higher than at 5, 85, 122, 180, and 208 DAB (Figure 2).
Sediment yield was significantly different among treatments (F = 11.2, p < 0.001), sampling dates (F = 2.92, p < 0.05), and the treatments × sampling dates interaction (F = 1.88, p < 0.05). At 25, 52, and 155 DAB, significantly higher sediment yield was observed in MS compared C treatments. No differences were identified between C and HS treatments among sampling dates for sediment yield. At MS treatment, a significantly higher sediment yield was observed at 155 and 52 than at 5, 65, 85, 122, 180, 208, and 247 DAB. Likewise, at 25 DAB, sediment yield was significantly higher than at 5, 122, 180, and 208 DAB (Figure 3).
Sediment concentration was significantly different among treatments (F = 17.6, p < 0.0001), and sampling dates (F = 3.6, p < 0.001). Significant differences were not observed in the treatments × sampling dates interaction (F = 1.43, p > 0.05). At 25, 85, 155, 180, and 208 DAB, a significantly higher sediment concentration was observed in MS compared to C and HS treatments. In C treatment, no significant differences in sediment concentration were observed among sampling dates. In MS treatment, significantly higher sediment concentration was identified at 25 and 52 DAB compared to all other sampling dates. Likewise, at 85, and 155 sediment concentration was significantly higher than at 5, 65, 122, 180, and 247 DAB. In HS treatment, significantly higher sediment concentration was observed at 52 than at 5, 85, 122, 180, and 208 DAB (Figure 4).

3.4. Nitrogen Concentrations in Runoff

NH4-N concentration was significantly different among treatments (F = 3.6, p > 0.05). Significant difference was not observed among sampling dates (F = 1.38, p > 0.05), and in the treatments × sampling dates interaction (F = 1.4, p > 0.05). At 180 and 247 DAB, NH4-N concentrations were significantly higher in C treatment than MS and HS treatments. In C treatment, NH4-N concentration was significantly higher at 180 and 247 DAB than at all other dates. In MS and HS treatments, NH4-N concentration was not significantly different (Figure 5).
NO3-N concentration was significantly different among treatments (F = 16.9, p < 0.0001), sampling dates (F = 4.31, p < 0.0001), and the treatments × sampling dates interaction (F = 3.19, p < 0.0001). At 85, 122, and 155, DAB NO3-N concentration was significantly higher in MS than in C treatments. In C and MS treatments, NO3-N concentration was significantly different among sampling dates. In HS treatment, NO3-N concentration was significantly higher at 122 DAB than at all other sampling dates. Likewise, at 155, NO3-N concentration was significantly higher than at 5, 25, 52, 65, 180, 208, and 247 DAB (Figure 6).

3.5. Nitrogen Loss in Sediment

NH4-N loss was not significantly different among treatments (F = 1.74, p > 0.05), and in the treatments × sampling dates interaction (F = 1.66, p < 0.05), but was among sampling dates (F = 1.98, p < 0.05). At 247 DAB, significantly higher NH4-N loss was observed in C treatment compared to MS and HS treatments. In C treatment, significantly higher NH4-N loss was observed at 247 DAB than in all other sampling dates. No significant differences in MS and HS treatments were observed in NH4-N loss among sampling dates (Figure 7).
NO3-N loss was significantly different among treatments (F = 21.1, p < 0.0001), sampling dates (F = 7.23, p < 0.0001), and the treatments × sampling dates interaction (F = 3.34, p < 0.0001). At 25, 52, 65, 85, 122, 155, and 247 DAB, significantly higher NO3-N loss was observed at MS and HS than at C treatments. At 122 DAB, significantly higher NO3-N loss was identified at HS than at MS and C treatments. In C treatment, no significant differences were observed for NO3−-N loss. In MS treatment, significantly higher NO3-N loss was identified at 52 and 65 DAB than at all other sampling dates. In HS treatment, significantly higher NO3-N loss was observed at 52, 65, 122, 155, and 247 than at 5, 25, 85, 180, and 208 DAB (Figure 8).
TN loss was significantly different among treatment (F = 12.1, p < 0.0001), sampling dates (F = 2.92, p < 0.05), and treatments × sampling dates interaction (F = 2.1, p < 0.05). In C and HS treatments, no significant differences among sampling dates were observed. At 25, 52, 85, 155, and 247 DAB, TN loss was significantly higher in MS treatment than on other dates. Likewise, TN loss in MS treatment was significantly higher at 25 and 52 than at 5, 25, 65, 85, 122, 180, 208, and 247 DAB (Figure 9).

3.6. Principal Component Analysis

The first three factors explained 72.7% of the total variance (Table S1 in Supplementary Material). Factor 1 explained 33.2%, and Factors 2 and 3 explained 23%, and 16.5%, respectively. The PCA identified three groups:
Sediment concentration, sediment yield, TN loss, and runoff;
Rainfall amount and intensity, NH4-N concentration and NH4-N losses;
Runoff, NO3-N concentrations, and NO3-N losses.
Factor 1 had high negative loadings in sediment yield, TN loss, sediment concentration, and runoff. Factor 2 had high negative loadings in rainfall amount, rain intensity, NH4-N loss, and concentration. Finally, Factor 3 had positive loadings in NO3-N concentration and loss. The intersection between Factor 1 and Factor 2 shows that sediment yield, TN loss, sediment concentration, and runoff are inversely related to most other variables, especially to rainfall amount and intensity (Figure 10A). The impact of all treatments is noticeably different. The variability is noted in all treatments, although MS can be singled out as the most variable (Figure 10B).

4. Discussion

4.1. Ash and Soil TN Dynamics

Five DAB, soil TN content in C treatment was significantly higher than in burn treatments. This was attributed to the fact that topsoil TN decreased in burned soils due to volatilization [14,27,28]. However, soils did not recover TN in the period post-burn. Usually, topsoil TN response in the post-burn period varies among burn severities and due to possible different extent of ash incorporation into the soil [14,29]. In this research, ash TN was similar at MS and HS treatment, although ash color varied between MS (black to dark grey, 10 YR 2/1, 10 YR 3/1) and HS (dark grey to light grey, 10 YR 4/1, 10 YR 7/1) treatments. Previous works observed that medium to high severity burn may produce a similar effect on the burned biomass and, consequently, surface soil [30]. In a study by Francos et al. [31], soil TN content was not significantly different among low, high severity burn, and unburned plots. Moreover, other works also confirmed similar TN contents in burned and unburned soils in the first years after burn [32,33].

4.2. Hydrological Response to Pile Burns

Five, 25, 122, and 247 DAB, a significantly higher runoff was identified in HS treatment, while higher runoff on MS treatment was noted 52, 65, 85, and 155 DAB, compared to other dates. A significantly higher runoff in burn treatments was identified at 25, 52, 65, 155, and 247 DAB than in C treatment (Figure 2). The highest sediment yield was observed in MS treatment at 155 DAB, followed by 25 and 52 DAB (Figure 3). Both burned treatments showed several orders of magnitude higher sediment yields than the unburned, which agrees with previous studies [34,35], although HS treatment did not show significant high values. Moreover, previous studies found that high severity burn did not have significant differences in runoff rate compared to moderate severity burn, even to low severity burn [36,37]. Gimeno-Garcia et al. [38] found that in the first months after an experimental burn, high severity burn increased runoff and soil loss compared to moderate burn, although the differences between them were not statistically significant. The variability of runoff and sediment loss on MS and HS treatments is very likely due to differences in small scale variability in ash thickness [39] or soil. The soil type in our study was classified as Leptosols, that are known for their low susceptibility to water repellency [40]. Ash might alter soil hydrological properties, increasing water retention and reducing sediment loss [41]. However, ash can also clog soil pores and increase surface erosion [42]. The direct comparison of runoff and sediment losses with other studies is almost impossible considering the large variability in reported post-burn runoff and erosion rates, mostly due to the type of burn-event (pile burn, prescribed, or wildfire), vast ranges of landscapes and climates where burns occur. Sediment concentrations were variable between measurement dates. However, they were notably highest in MS. In MS treatment, higher sediment concentration was observed on first dates then in later dates post-burn. Considering both erosion rates, in MS treatment at 85 DAB, sediment concentration was not significantly different from 52 and 155 DAB (Figure 4), unlike sediment yield observed at 85 DAB (Figure 3). It seems that high rainfall intensity, which occurred at 85 DAB (Figure 1), was responsible for the increase in sediment concentration in MS. The highest amount and rainfall intensity, which was observed at 247 DAB, did not significantly influence the overland flow and erosion rate. This was very likely due to sediment exhaustion as a consequence of the previous rainfall events. Our results agree with previous studies that showed decreasing erosion rate in the later post-burn period [13,34,38].

4.3. The N losses in the Post-Burn Period

The two distinct NH4-N concentrations in C treatment at 180 and 247 DAB can be explained due to rainfall patterns and related soil saturation (Figure 5) [43]. In the C treatment, the organic matter includes a diverse composition of flora population, so it was assumed that these contributed to higher soil saturation and related increased NH4-N concentrations [14,43]. Regarding the burn treatments, the major NH4-N concentrations in MS treatment were observed at 208 DAB, and in HS treatment at 65 DAB, although not significantly different. According to our results, precipitation intensity did not influence the hydrological response and related NH4-N concentrations in all treatments. Several authors confirmed a high NH4-N concentration in overland flow immediately after a high severity burn [14,15,16,44]. In this work, this was not the case. However, NO3-N is not produced directly by heating but is formed during subsequent nitrification of NH4-N as a result of the burning [10,11,45]. These results indicate that HS treatment had a severe effect on NO3-N concentrations in runoff, as the significantly higher values were observed in HS treatment. A more significant NO3-N availability and movement are frequent when the nitrifying population recovers [19]. According to Koyama et al. [21], high severity burn led to higher NO3-N concentrations compared to low severity burn, which was the case in our experiment. In this context, microbial population after burn become functionally more diverse, and certain nitrifying bacteria increase 10 times more than levels in unburned areas, thereby increasing NO3-N concentration, which is assumed to be the reason for high NO3-N concentration in HS compared to C treatment [45]. The NH4-N and NO3-N loss (Figure 7 and Figure 8) follow the patterns of N concentrations in runoff as the loss is mainly influenced by N-form concentration behavior [23,46]. However, differences in N losses between treatments were more apparent than the differences in the N concentrations. Our results showed high variability in the loss of NO3-N than in the loss of NH4-N. This phenomenon occurs due to post-burn transformation of NH4-N to NO3-N by nitrifying bacteria, increasing the transport of inorganic N [20]. NH4-N is in the N soluble form, and it is adsorbed on the negatively charged soil cation exchange site, and thus is less mobile than anions. NO3-N cannot bind to soil adsorption complexes and, therefore, is more vulnerable to leaching [14,19]. In MS treatment highest NO3-N loss was observed at 52 and 65 DAB, unlike NH4-N concentrations on the same dates. NO3-N losses follow the patterns of erosion. According to Thomas et al. [9], the amount of sediment yield is the main factor controlling the N loss rather than any N concentration change in the sediment or runoff.
The TN loss was highest 155 DAB, followed by first sampling dates at 25 and 52 DAB in MS treatment. The highest peaks of TN losses were a consequence of extreme rainfall events, as is noted by Field et al. [46], Ferreira et al. [23], or Hosseini et al. [47]. After the first months, peak losses are restricted to extreme rainfall, which can mobilize ash and soil [30]. High runoff and erosion events in MS treatment are responsible for the increments of TN and NO3-N loss at 52, 65, and 85 DAB [23]. Regarding the NO3-N loss 122 and 155 DAB, this may be attributed to the burn severity, rather than erosion, since HS treatment’s highest losses occurred when low sediment yield was observed. The sediment yield and runoff rate increase with rainfall amount as confirmed in other works in fire-affected areas [23,38]. In the study by Hosseini et al. [47], the N loss was mainly due to rainfall patterns and runoff. In this research, maximum rainfall intensity was noted at 247 DAB but did not influence sediment yield, TN, and NO3-N loss at 155 DAB. This could be attributed to sediment and nutrient exhaustion and plant consumption [13,38]. The second highest rainfall event with high intensity was observed at 155 DAB and increased sediment yield and, consequently, N loss. In our work, sediment yield has more effects on N loss rather than sediment concentrations. The sediment concentration was more influenced by firsts runoff events, at 25 and 52 DAB, and did not have the same patterns as sediment yield (Figure 4), as was found in previous research [36].

4.4. Interrelations between Hydrological Variables

Factor 1 of PCA grouped most of the erosion variables, i.e., sediment yield, concentration, runoff, and TN losses, respectively. The erosion was higher in MS compared to C and HS treatments. The sediment yield and concentration, runoff, and TN loss are the best indicators to assess the impacts of pile burn effects, rather than NH4-N concentration and loss and NO3-N concentration and loss, respectively. The erosion parameters are well documented in other studies as the main features for the identification of soil degradation in the post-burn period [13,34]. Factor 2 grouped the precipitation parameters (amount and intensity), and NH4-N concentration and loss. This can be attributed to the lack of significant differences in burn treatments, with the highest in C treatment for the NH4-N variables. The highest NH4-N values were observed at 247 DAB in C treatment when the highest rainfall amount and intensity were identified. NH4-N loss and concentration patterns differed considerably from those of NO3-N, which were identified in Factor 3. The NO3-N concentration had positive values. For NO3-N values, diverse concentration and loss in both burn treatments were observed, and it was not recognized as the main factor for validation of the pile burn effects. Pile burn leaves only localized soil impact and nutrient effects. However, the effects are substantial.

4.5. Implications for Land Management

The accumulation of organic feedstock material in Mediterranean rural areas has become an environmental problem. There has been a need to manage unwanted harvest to avoid large wildfires and minimize their impact at all levels [48]. Pile burn is recognized as an economical treatment for disposing of harvested residues [5], but the critical question in terms of the sustainability of their practice is to what extent will it alter soil functions and cause soil degradation? Should soils before burning be protected somehow, or do the benefits of pile burning outweigh the possible impact on soil? A fundamental guideline in discussing the effects of pile burning is the knowledge that soil is not renewable in our lifetime, which comes to the fore in the Mediterranean’s endangered area. The post-burn N dynamic and N losses are useful indicators to rank pile burn effects in terms of consequences to soil fertility and soil degradation [10]. Relatively small and localized burned areas give preference to these practices. Pile burning can be used as a conservative approach that protects natural resources, which should be a priority in land management, but do not neglect their soil [49]. Different experiment designs focused on more closely controlling fuel characteristics (amount, type, and moisture), the season of burning, weather variables, and possible slope gradient are necessary to more clearly understand the period in which these practices are best to conduct [50].

5. Conclusions

The short-term effect showed a substantial impact on N loss in both burn treatments. However, severe impact on N loss was noted at MS treatment. The C treatment had peak NH4-N concentrations, which may be attributed to the natural biological process and soil saturation. This work’s outcomes showed that rainfall amount and intensity in the first months of post-burn had a major effect on N loss compared to more severe rainfall patterns in later months. Therefore, pile burning has significant effects in a short-term study on N loss by runoff and erosion process. MS had the strongest effects on N loss in the post-burn period. Sediment yield can be used as an important indicator for the determination of soil degradation in the post-burn period. The future work with included analyses of physical and chemical soil and water parameters is obligatory for deeper insights into the effects of pile burn practice on the environment.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4395/10/9/1340/s1, Table S1: Loadings matrix with first three factors extracted from the PCA analysis.

Author Contributions

Conceptualization, D.D. and P.P.; methodology, D.D.; validation, I.B. and P.P.; formal analysis, D.D.; investigation, D.D., I.K., and I.B.; resources, I.K.; data curation, D.D. and I.B.; writing—original draft preparation, D.D.; writing—review and editing, D.D., I.B., and P.P.; visualization, D.D., I.B., and P.P.; supervision, P.P. and I.K.; project administration, I.K.; funding acquisition, I.K. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the Croatian science foundation under the project “Influence of Summer Fire on Soil and Water Quality” (IP-2018-01-1645).

Acknowledgments

Željka Zgorelec and Aleksandra Perčin are acknowledged for their cooperation during the laboratory work.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Moreira, F.; Viedma, O.; Arianoutsou, M.; Curt, T.; Koutsias, N.; Rigolot, E.; Barbati, A.; Corona, P.; Vaz, P.; Xanthopoulos, G.; et al. Landscape—Wildfire interactions in southern Europe: Implications for landscape management. J. Environ. Manag. 2011, 92, 2389–2402. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Lasanta, T.; Khorchani, M.; Pérez-Cabello, F.; Errea, P.; Sáenz-Blanco, R.; Nadal-Romero, E. Clearing shrubland and extensive livestock farming: Active prevention to control wildfires in the Mediterranean mountains. J. Environ. Manag. 2018, 227, 256–266. [Google Scholar] [CrossRef] [PubMed]
  3. Curt, T.; Frejaville, T. Wildfire Policy in Mediterranean France: How Far is it Efficient and Sustainable? Risk Anal. 2018, 38, 472–488. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Busse, M.D.; Shestak, C.J.; Hubbert, K.R. Soil heating during burning of forest slash piles and wood piles. Int. J. Wildland Fire 2013, 22, 786–796. [Google Scholar] [CrossRef]
  5. Pastor, E.; Pérez, Y.; Agueda, A.; Miralles, M.; Planas, E. Pile burning of cutting debris in stands of hazel (Corylus avellana): An experimental study of smouldering combustion towards the validation of a burning protocol. Fire Saf. J. 2010, 45, 69–81. [Google Scholar] [CrossRef]
  6. Kostenidou, E.; Kaltsonoudis, C.; Tsiflikiotou, M.; Louvaris, E.; Russell, L.M.; Pandis, S.N. Burning of olive tree branches: A major organic aerosol source in the Mediterranean. Atmos. Chem. Phys. Discuss. 2013, 13, 7223–7266. [Google Scholar] [CrossRef]
  7. Francos, M.; Úbeda, X.; Pereira, P. Impact of bonfires on soil properties in an urban park in Vilnius (Lithuania). Environ. Res. 2020, 181, 108895. [Google Scholar] [CrossRef]
  8. Pereira, P.; Francos, M.; Brevik, E.C.; Ubeda, X.; Bogunovic, I. Post-fire soil management. Curr. Opin. Environ. Sci. Health 2018, 5, 26–32. [Google Scholar] [CrossRef]
  9. Thomas, A.D.; Walsh, R.P.D.; Shakesby, R.A. Nutrient losses in eroded sediment after fire in eucalyptus and pine forests in the wet Mediterranean environment of northern Portugal. Catena 1999, 36, 283–302. [Google Scholar] [CrossRef]
  10. Caon, L.; Vallejo, V.R.; Coen, R.J.; Geissen, V. Effects of wildfire on soil nutrients in Mediterranean ecosystems. Earth Sci. Rev. 2014, 139, 47–58. [Google Scholar] [CrossRef]
  11. Certini, G. Effects of fire on properties of forest soils: A review. Oecologia 2005, 143, 1–10. [Google Scholar] [CrossRef] [PubMed]
  12. Bodí, M.B.; Martin, D.A.; Balfour, V.N.; Santín, C.; Doerr, S.H.; Pereira, P.; Cerdà, A.; Mataix-Solera, J. Wildland fire ash: Production, composition and eco-hydro-geomorphic effects. Earth Sci. Rev. 2014, 130, 103–127. [Google Scholar] [CrossRef]
  13. Shakesby, R.A. Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth Sci. Rev. 2011, 105, 71–100. [Google Scholar] [CrossRef]
  14. Neary, D.G.; Ryan, K.C.; DeBano, L.F. Wildland Fire in Ecosystems: Effects of Fire on Soils and Water; Gen. Tech. Rep. RMRS-GTR-42-vol.4; CreateSpace Independent Publishing Platform: Scotts Valley, CA, USA, 2005. [Google Scholar]
  15. Wan, S.; Hui, D.; Luo, Y. Fire effects on nitrogen pools and dynamics in terrestrial ecosystems: A meta-analysis. Ecological 2001, 11, 711–730. [Google Scholar] [CrossRef]
  16. Smith, H.G.; Sheridan, G.J.; Lane, P.N.J.; Nyman, P.; Haydon, S. Wildfire effects on water quality in forest catchments: A review with implications for water supply. J. Hydrol. 2011, 396, 170–192. [Google Scholar] [CrossRef]
  17. Pereira, P.; Brevik, E.; Bogunović, I.; Ferran, E.-S. Ash and soils: A Close Relationship in Fire-Affected Areas. In Fire Effects on Soil Properties; Pereira, P., Mataix-Solera, J., Úbeda, X., Rein, G., Cerdà, A., Eds.; CSIRO Publishing: Clayton, Australia, 2019; ISBN 9781486308149. [Google Scholar]
  18. Certini, G.; Nocentini, C.; Knicker, H.; Arfaioli, P.; Rumpel, C. Wildfire effects on soil organic matter quantity and quality in two fire-prone Mediterranean pine forests. Geoderma 2011, 167, 148–155. [Google Scholar] [CrossRef]
  19. Johnson, B.G.; Johnson, D.W.; Miller, W.W.; Carroll-Moore, E.M.; Board, D.I. The effects of slash pile burning on soil and water macronutrients. Soil Sci. 2011, 176, 413–425. [Google Scholar] [CrossRef]
  20. Hubbert, K.R.; Busse, M.; Overby, S.; Shestak, C.; Gerrard, R. Pile burning effects on soil water repellency, infiltration, and downslope water chemistry in the lake tahoe basin, USA. Fire Ecol. 2015, 11, 100–118. [Google Scholar] [CrossRef]
  21. Koyama, A.; Stephan, K.; Kavanagh, K.L. Fire effects on gross inorganic N transformation in riparian soils in coniferous forests of central Idaho, USA: Wildfires v. prescribed fires. Int. J. Wildland Fire 2012, 21, 69. [Google Scholar] [CrossRef]
  22. Stephan, K.; Kavanagh, K.L.; Koyama, A. Comparing the Influence of Wildfire and Prescribed Burns on Watershed Nitrogen Biogeochemistry Using 15N Natural Abundance in Terrestrial and Aquatic Ecosystem Components. PLoS ONE 2015, 10, e0119560. [Google Scholar] [CrossRef]
  23. Ferreira, R.V.; Serpa, D.; Machado, A.I.; Rodríguez-Blanco, M.L.; Santos, L.F.; Taboada-Castro, M.T.; Cerqueira, M.A.; Keizer, J.J. Short-term nitrogen losses by overland flow in a recently burnt forest area in north-central Portugal: A study at micro-plot scale. Sci. Total Environ. 2016, 572, 1281–1288. [Google Scholar] [CrossRef] [PubMed]
  24. Sharma, U.; Sharma, J.; Devi, M.; Uday Sharma, C. Effect of Forest fire on soil nitrogen mineralization and microbial biomass: A review. J. Pharmacogn. Phytochem. 2017, 6, 682–685. [Google Scholar]
  25. Kottek, M.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006, 15, 259–263. [Google Scholar] [CrossRef]
  26. USDA. Soil Conservation Service. In Munsell Soil Color Book; Agricultural Handbook No. 18; U.S. Government Printing Office: Washington, DC, USA, 2009. [Google Scholar]
  27. DeBano, L.F.; Neary, D.G.; Ffolliott, P. Fire Effects on Ecosystems; John Wiley & Sons: Hoboken, NJ, USA, 1998; ISBN 978-0-471-16356-5. [Google Scholar]
  28. Rau, B.M.; Tausch, R.; Reiner, A.; Johnson, D.W.; Chambers, J.C.; Blank, R.R.; Lucchesi, A. Influence of prescribed fire on ecosystem biomass, carbon, and nitrogen in a pinyon juniper woodland. Rangel. Ecol. Manag. 2010, 63, 197–202. [Google Scholar] [CrossRef] [Green Version]
  29. Johnson, B.G.; Johnson, D.W.; Miller, W.W.; Board, D.I. The effects of ash influx on burned and unburned soil water-extractable nutrients using a mechanical vacuum extractor. Soil Sci. 2012, 177, 338–344. [Google Scholar] [CrossRef]
  30. Dinis Ferrira, A.J.; Leitao, I.A.; Boulet, A.K.; Santos Ferreira, C.S. Nutrient Processes. In Fire Effects on Soil Properties; Pereira, P., Mataix-Solera, J., Úbeda, X., Rein, G., Cerdà, A., Eds.; CSIRO Publishing: Clayton, Australia, 2019; pp. 129–142. [Google Scholar]
  31. Francos, M.; Úbeda, X.; Pereira, P.; Alcañiz, M. Long-term impact of wildfire on soils exposed to different fire severities. A case study in Cadiretes Massif (NE Iberian Peninsula). Sci. Total Environ. 2018, 615, 664–671. [Google Scholar] [CrossRef]
  32. Boerner, R.E.J.; Huang, J.; Hart, S.C. Impacts of Fire and Fire Surrogate treatments on forest soil properties: A meta-analytical approach. Ecol. Appl. 2009, 19, 338–358. [Google Scholar] [CrossRef]
  33. Zavala, L.M.; de celis, R.; Jordán, A. How wildfires affect soil properties. A brief review. Cuad. Investig. Geogr. 2014, 40, 311–331. [Google Scholar] [CrossRef] [Green Version]
  34. Shakesby, R.A.; Doerr, S.H. Wildfire as a hydrological and geomorphological agent. Earth Sci. Rev. 2006, 74, 269–307. [Google Scholar] [CrossRef]
  35. Moody, J.A.; Martin, D.A.; Haire, S.L.; Kinner, D.A. Linking runoff response to burn severity after a wildfire. Hydrol. Process. 2008, 22, 2063–2074. [Google Scholar] [CrossRef]
  36. Benavides-Solorio, J.; MacDonald, L.H. Post-fire runoff and erosion from simulated rainfall on small plots, Colorado Front Range. Hydrol. Process. 2001, 15, 2931–2952. [Google Scholar] [CrossRef]
  37. Soto, B.; Diaz-Fierros, F. Interactions between plant ash leachates and soil. Int. J. Wildland Fire 1993, 3, 207–216. [Google Scholar] [CrossRef]
  38. Gimeno-García, E.; Andreu, V.; Rubio, J.L. Influence of vegetation recovery on water erosion at short and medium-term after experimental fires in a Mediterranean shrubland. Catena 2007, 69, 150–160. [Google Scholar] [CrossRef] [Green Version]
  39. Pereira, P.; Cerdà, A.; Úbeda, X.; Mataix-Solera, J.; Arcenegui, V.; Zavala, L.M. Modelling the Impacts of Wildfire on Ash Thickness in a Short-Term Period. Land Degrad. Dev. 2015, 26, 180–192. [Google Scholar] [CrossRef]
  40. Mataix-Solera, J.; Arcenegui, V.; Guerrero, C.; Jordán, M.M.; Dlapa, P.; Tessler, N.; Wittenberg, L. Can terra rossa become water repellent by burning? A laboratory approach. Geoderma 2008, 147, 178–184. [Google Scholar] [CrossRef]
  41. Cerdà, A.; Doerr, S.H. The effect of ash and needle cover on surface runoff and erosion in the immediate post-fire period. Catena 2008, 74, 256–263. [Google Scholar] [CrossRef]
  42. Onda, Y.; Dietrich, W.E.; Booker, F. Evolution of overland flow after a severe forest fire, Point Reyes, California. Catena 2008, 72, 13–20. [Google Scholar] [CrossRef]
  43. Zheng, F.L.; Zhang, Y.B.; Cao, N. Effect of saturated near surface on nitrate and ammonia nitrogen losses in surface runoff at the loess soil hillslope. Int. J. Chem. Eng. 2010, 2010. [Google Scholar] [CrossRef]
  44. Riggan, P.J.; Lockwood, R.N.; Jacks, P.M.; Colver, C.G.; Weirich, F.; DeBano, L.F.; Brass, J.A. Effects of Fire Severity on Nitrate Mobilization in Watersheds Subject to Chronic Atmospheric Deposition. Environ. Sci. Technol. 1994, 28, 369–375. [Google Scholar] [CrossRef]
  45. Hart, S.C.; DeLuca, T.H.; Newman, G.S.; MacKenzie, M.D.; Boyle, S.I. Post-fire vegetative dynamics as drivers of microbial community structure and function in forest soils. For. Ecol. Manag. 2005, 220, 166–184. [Google Scholar] [CrossRef]
  46. Field, J.P.; Farrish, K.W.; Carter, E.A. Soil and nutrient losses following site preparation burning in a harvested loblolly pine site. Trans. Am. Soc. Agric. Eng. 2003, 46, 1697–1703. [Google Scholar] [CrossRef] [Green Version]
  47. Hosseini, M.; Geissen, V.; González-Pelayo, O.; Serpa, D.; Machado, A.I.; Ritsema, C.; Keizer, J.J. Effects of fire occurrence and recurrence on nitrogen and phosphorus losses by overland flow in maritime pine plantations in north-central Portugal. Geoderma 2017, 289, 97–106. [Google Scholar] [CrossRef]
  48. Pausas, J.G.; Fernández-Muñoz, S. Fire regime changes in the Western Mediterranean Basin: From fuel-limited to drought-driven fire regime. Clim. Chang. 2012, 110, 215–226. [Google Scholar] [CrossRef] [Green Version]
  49. Busse, M.D.; Hubbert, K.R.; Moghaddas, E.E.Y. Fuel reduction practices and their effects on soil quality. Gen. Tech. Rep. 2014, 156, 241. [Google Scholar]
  50. Wright, C.S.; Evans, A.M.; Grove, S.; Haubensak, K.A. Pile age and burn season influence fuelbed properties, combustion dynamics, fuel consumption, and charcoal formation when burning hand piles. For. Ecol. Manag. 2019, 439, 146–158. [Google Scholar] [CrossRef]
Agronomy 10 01340 g001 550
Figure 1. Temporal precipitation (mm) and maximum rainfall intensity (I30, mm h−1) in the period between 5 and 247 days after pile burning.
Figure 1. Temporal precipitation (mm) and maximum rainfall intensity (I30, mm h−1) in the period between 5 and 247 days after pile burning.
Agronomy 10 01340 g001
Agronomy 10 01340 g002 550
Figure 2. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on runoff (L m−2) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 2. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on runoff (L m−2) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g002
Agronomy 10 01340 g003 550
Figure 3. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on sediment yield (g m−2) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show significantly different within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 3. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on sediment yield (g m−2) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show significantly different within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g003
Agronomy 10 01340 g004 550
Figure 4. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on sediment concentration (g L−1) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show significantly different within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 4. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on sediment concentration (g L−1) between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show significantly different within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g004
Agronomy 10 01340 g005 550
Figure 5. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on ammonium (NH4-N) (mg L−1) concentration between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 5. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on ammonium (NH4-N) (mg L−1) concentration between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g005
Agronomy 10 01340 g006 550
Figure 6. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on nitrate (NO3-N) (mg L−1) concentration between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 6. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on nitrate (NO3-N) (mg L−1) concentration between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g006
Agronomy 10 01340 g007 550
Figure 7. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on NH4-N loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 7. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on NH4-N loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g007
Agronomy 10 01340 g008 550
Figure 8. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on NO3-N loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters are statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 8. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on NO3-N loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters are statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g008
Agronomy 10 01340 g009 550
Figure 9. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on total Nitrogen (TN) loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Figure 9. Treatment effect under control (C), moderate severity (MS), and high severity (HS) burn on total Nitrogen (TN) loss between 5 and 247 days after pile burning. Mean values followed by the different lowercase letters show statistically significant differences within the same date. Mean values followed by the different uppercase letters show statistically significant differences within the same treatment. Significant differences were observed at p < 0.05. Hanging bars represent the standard error (n = 5).
Agronomy 10 01340 g009
Agronomy 10 01340 g010a 550Agronomy 10 01340 g010b 550
Figure 10. The relation between Factors 1 and 2, (A) Variables, and (B) Cases. TN, total nitrogen; C, control; MS, moderate severity; HS, high severity.
Figure 10. The relation between Factors 1 and 2, (A) Variables, and (B) Cases. TN, total nitrogen; C, control; MS, moderate severity; HS, high severity.
Agronomy 10 01340 g010aAgronomy 10 01340 g010b
Table
Table 1. Content of total nitrogen (TN) in ash and soil (n = 5).
Table 1. Content of total nitrogen (TN) in ash and soil (n = 5).
Ash TN (%)Soil TN (%)
Time after BurnIAB5 DAB122 DAB247 DABp Value
C/0.50aA0.45bA0.46bA*
MS0.27A0.46aB0.44aA0.45aAn.s.
HS0.25A0.45aB0.45aA0.48aAn.s.
Mean TN concentration followed by the different lowercase letters is statistically significant differences within the treatment. Mean TN concentration followed by the different uppercase letters is statistically significant differences within the same date. (IAB; immediately after burn, DAB; days after burning, TN; total nitrogen, C; control, MS; moderate severity, HS; high severity, n.s.; no significant, * significant difference at p < 0.05 level).

Share and Cite

MDPI and ACS Style

Delač, D.; Pereira, P.; Bogunović, I.; Kisić, I. Short-Term Effects of Pile Burn on N Dynamic and N Loss in Mediterranean Croatia. Agronomy 2020, 10, 1340. https://doi.org/10.3390/agronomy10091340

AMA Style

Delač D, Pereira P, Bogunović I, Kisić I. Short-Term Effects of Pile Burn on N Dynamic and N Loss in Mediterranean Croatia. Agronomy. 2020; 10(9):1340. https://doi.org/10.3390/agronomy10091340

Chicago/Turabian Style

Delač, Domina, Paulo Pereira, Igor Bogunović, and Ivica Kisić. 2020. "Short-Term Effects of Pile Burn on N Dynamic and N Loss in Mediterranean Croatia" Agronomy 10, no. 9: 1340. https://doi.org/10.3390/agronomy10091340

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop