<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.3-30.v1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                    <subj-group>
                        <subject>Global Change Ecology</subject>
                    </subj-group>
                    <subj-group>
                        <subject>Spatial &amp; Landscape Ecology</subject>
                    </subj-group>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Post-fire nutrient availability in the sub-tropical forest ecosystem of the Koubru Hills, Manipur</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Sitlhou</surname>
                        <given-names>Alice</given-names>
                    </name>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Singh</surname>
                        <given-names>Thingbaijam Binoy</given-names>
                    </name>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Ecology Section, Department of Life Sciences, Manipur University, Imphal, 795003, India</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:alicesitlhou1982@gmail.com">alicesitlhou1982@gmail.com</email>
                </corresp>
                <fn fn-type="con">
                    <p>TBS conceived the study, suggested expertise in soil science and contributed to the preparation of the manuscript. AS carried out the research, interpreted the data and prepared the first draft of the manuscript. Both authors critically revised the draft manuscript and have agreed to the final content of the version to be published.</p>
                </fn>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>29</day>
                <month>1</month>
                <year>2014</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2014</year>
            </pub-date>
            <volume>3</volume>
            <elocation-id>30</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>23</day>
                    <month>1</month>
                    <year>2014</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2014 Sitlhou A and Singh TB</copyright-statement>
                <copyright-year>2014</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/3.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
                <license>
                    <license-p>The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/3-30/pdf"/>
            <abstract>
                <p>Forest fires are known to significantly alter soil nutrient availability. The study investigated the post-fire nutrient availability in the sub-tropical forest ecosystem of Koubru Hills, Manipur (North-East India). The forested ecosystem was disturbed by forest wildfire in January 2010. To study the fire effect, collection of burned and unburned soil samples from three soil depths (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm) was started approximately three months after the fire event and continued at monthly intervals for a period of one year. The collected soil samples were analyzed for soil organic carbon (SOC), NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N, Bray-extractable phosphorus, available potassium and micronutrients such as Fe, Cu, Mn and Zn. Results of the ANOVA test showed significant reduction in the SOC, NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N and available K contents of the surface (0&#x2013;5 cm) and sub-surface (5&#x2013;10 and 10&#x2013;15 cm) soil layers of the burned area. However, significant increases in the Bray-extractable phosphorus were observed in all the three soil depths studied. With respect to the effect of forest fire on soil micronutrient availability, results are contradictory. The available Fe depleted in all the three soil depths, whilst the available Cu declined in the 0&#x2013;5 cm but increased in the 10&#x2013;15 cm soil layer. The available Cu content of the 5&#x2013;10 cm soil layer did not vary between the burned and unburned areas. While no significant effect of fire was observed on the available Mn contents of the 0&#x2013;5 and 10&#x2013;15 cm soil layers, there was a significant post-fire decrease in the Mn availability of the 5&#x2013;10 cm soil layer of the burned area compared with the unburned area. Forest fire also resulted in a significant loss of the available Zn from the 0&#x2013;5 and 5&#x2013;10 cm soil layers of the burned area but in the 10&#x2013;15 cm soil layer, no significant variation was observed between the burned and unburned areas.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>nutrient availability</kwd>
                <kwd>soil</kwd>
                <kwd>sub-tropical</kwd>
                <kwd>ecosystem</kwd>
                <kwd>fire</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The research was funded by the University Grants Commission (UGC), New Delhi under the Rajiv Gandhi National Fellowship (RGNF) awarded to Alice Sitlhou vide Grant No. F. 14-2 (SC)/2009(SA-III). </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec sec-type="intro">
            <title>Introduction</title>
            <p>Forest fires form part of ecosystem disturbances and those provoked by human activities are a paramount environmental problem and a serious threat to biodiversity
                <sup>
                    <xref ref-type="bibr" rid="ref-1">1</xref>
                </sup>. Pickett and White
                <sup>
                    <xref ref-type="bibr" rid="ref-2">2</xref>
                </sup> defined ecosystem disturbances as &#x201c;any relatively discrete event(s) in time and space that disrupts the structure of populations, communities, and ecosystems and causes(s) change in resource availability or the physical environment&#x201d;. Fire as natural or anthropogenic disturbance can cause short- or long-term changes in ecosystem dynamics
                <sup>
                    <xref ref-type="bibr" rid="ref-3">3</xref>,
                    <xref ref-type="bibr" rid="ref-4">4</xref>
                </sup>.</p>
            <p>The effect of forest fire on forest soil is very complicated and less studied in comparison to its aboveground effect
                <sup>
                    <xref ref-type="bibr" rid="ref-5">5</xref>
                </sup>. Fire effects on soil can vary greatly among different ecosystems depending on the severity (a combination of fire line intensity and duration) according to Keeley
                <sup>
                    <xref ref-type="bibr" rid="ref-6">6</xref>
                </sup> and frequency of fires. While low severity-fires do not substantially affect soils, high severity-fires can affect a wide range of soil properties, one of which is nutrient availability
                <sup>
                    <xref ref-type="bibr" rid="ref-7">7</xref>
                </sup>. The concentrations, forms, and depth distribution of soil nutrients can be dramatically altered after fire disturbance
                <sup>
                    <xref ref-type="bibr" rid="ref-8">8</xref>
                </sup>. The productivity of burned soils can be impacted, in some cases, in an irreversible way resulting from fire-induced changes on soil properties
                <sup>
                    <xref ref-type="bibr" rid="ref-9">9</xref>
                </sup>. Post-fire nutrient losses can be accelerated through volatilization, leaching and erosion
                <sup>
                    <xref ref-type="bibr" rid="ref-7">7</xref>
                </sup>.</p>
            <p>Most studies on fire-associated alterations in soil nutrients have been focused on evaluating changes in available macro-nutrients
                <sup>
                    <xref ref-type="bibr" rid="ref-10">10</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref-12">12</xref>
                </sup>. Very few studies have evaluated post-fire effects on soil micronutrients. This paper presents information regarding the post-fire availability of nutrients which include both macro- and micro-nutrients of the burned and unburned areas in the sub-tropical forest ecosystem of Koubru Hills, Manipur (NE India). The role of fire in this region is poorly understood, therefore, the aim of this study was to investigate changes in some of the soil nutrients following forest wildfire using conventional soil analytical tools. Results from the present study would provide insight into potential fire effects on soil nutrients at this site and also give some direction for sorely needed future research.</p>
        </sec>
        <sec sec-type="materials | methods">
            <title>Materials and methods</title>
            <sec>
                <title>Site description</title>
                <p>This research was conducted between March 2010 and April 2011 in the sub-tropical forest ecosystem of the Koubru Hills, Manipur (NE India). The site under study lies at 24&#x00b0;55&#x2032;N latitude and 93&#x00b0;48&#x2032;E longitude. Average elevation of the site is approximately 1294 m above mean sea level. Mean annual precipitation is about 3.99 mm with the wet season between June and August. Average annual relative humidity is 75.99%. Average annual air temperature is 21.14&#x00b0;C. The data are based on long term records from the Indian Council of Agricultural Research (ICAR) located nearby the study site. The soil is sandy loam in texture. Vegetation at the site is dominated by 
                    <italic toggle="yes">Cinnamomum zeylanicum</italic> and some unidentified species belonging to the genus 
                    <italic toggle="yes">Litsaea</italic>.</p>
                <p>In mid January 2010, a forest wildfire occurred in the study site which had been undisturbed by fire for more than 100 years. The fire removed almost all the understory vegetation and soil surface litter.</p>
            </sec>
            <sec>
                <title>Soil sampling and sample analysis</title>
                <p>Soil sampling at monthly intervals started in April 2010 and ended in March 2011. Sampling was carried out approximately three months after the occurrence of the forest wildfire. Two representative plots (with an area of 6000 m
                    <sup>2</sup> per plot), one each in the burned and the adjacent unburned areas, were taken. Each plot was equally divided into fifteen sub-plots (with an area of 20&#x00d7;20 m
                    <sup>2</sup> per sub-plot). From amongst the fifteen sub-plots, ten sub-plots were randomly selected following the random number table method of Fisher and Yates
                    <sup>
                        <xref ref-type="bibr" rid="ref-13">13</xref>
                    </sup>. Soils were sampled from three depths (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm) in each of the randomly selected ten sub-plots of both burned and adjacent unburned areas using 5 cm &#x00d7; 5 cm soil cores. Soils collected from the similar depths in each of the ten sub-plots of the burned area were pooled into one composite sample (for instance, soils collected from the 0&#x2013;5 cm soil depth of the burned area were pooled into one composite sample representing the 0&#x2013;5 cm soil depth of the burned area). The same was repeated for soils sampled from three depths in each of the ten sub-plots of the unburned area. Thus, each composite soil sample representing a specific depth of either the burned or unburned area was composed of ten pooled sub-samples collected from the randomly selected ten sub-plots. The collected soil samples were air-dried, crushed and passed through a 2 mm mesh soil sieve (Shiva Scientific Instruments, India) for nutrient analysis.</p>
                <p>Soil organic carbon (SOC) contents were analyzed using H
                    <sub>2</sub>SO
                    <sub>4</sub>&#x2013;K
                    <sub>2</sub>Cr
                    <sub>2</sub>O
                    <sub>7</sub> oxidation method
                    <sup>
                        <xref ref-type="bibr" rid="ref-14">14</xref>
                    </sup> with five replications. Ammonical nitrogen was determined by the alkaline permanganate method using an Alpkem autoanalyser (Kjeltec system 1026 Distilling unit, Sweden) with three replications. Bray-extractable phosphorus (2.85 g soil in 0.03 N NH
                    <sub>4</sub>F plus 0.025 N HCl) was analyzed using spectrophotometer 169 (Systronics, India) with three replications. Available potassium was extracted by 0.1 M ammonium acetate solution adjusted to pH 7 at a 1:5 soil solution ratio and determined by flame photometer 128 (Systronics, India) with three replications. The plant-available fractions of micronutrients (Fe, Cu, Mn and Zn) were determined by using 0.05 M DTPA (Diethylene Triamine Pentaacetic Acid) plus 0.01 M CaCl
                    <sub>2</sub> plus 0.1 M Triethanolamine, adjusted to pH 7.30 at a 1:2 soil solution ratio
                    <sup>
                        <xref ref-type="bibr" rid="ref-15">15</xref>
                    </sup>. The concentrations of the elements were assessed using atomic absorption spectrophotometry (Aanalyst 200, PerkinElmer, USA).</p>
            </sec>
            <sec>
                <title>Statistical analysis</title>
                <p>A two way ANOVA test was performed to test the effects of forest fire (burned and unburned) and sampling month (time) on the soil nutrients studied at three different soil depths (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm). A one way ANOVA test was performed to detect the differences in soil nutrient concentrations between the burned and unburned areas at a specific sampling month. P&#x2264;0.05 was considered to be significant. The data analysis was carried out using Microsoft Excel 2007.</p>
            </sec>
        </sec>
        <sec sec-type="results">
            <title>Results</title>
            <sec>
                <title>Soil organic carbon</title>
                <p>The SOC contents of the surface layer (0&#x2013;5 cm) ranged from 2.10 to 2.18% in the unburned area while in the burned area they ranged from 1.94 to 2.02% (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In the sub-surface layers (5&#x2013;10 and 10&#x2013;15 cm) the SOC contents of the unburned area were observed to vary from 1.97 to 2.04% and from 1.76 to 1.89%, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In contrast, the SOC contents of the sub-surface layers in the burned area ranged from 1.62 to 1.74% and from 1.49 to 1.58%, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <table-wrap id="T1" orientation="portrait" position="anchor">
                    <label>Table 1. </label>
                    <caption>
                        <title>The maximum and minimum soil nutrient concentrations of the burned and unburned areas at three soil depths (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="center" colspan="1" rowspan="3" valign="middle">SOIL
                                    <break/>NUTRIENTS</th>
                                <th align="center" colspan="4" rowspan="1">0&#x2013;5 cm</th>
                                <th align="center" colspan="4" rowspan="1">5&#x2013;10 cm</th>
                                <th align="center" colspan="4" rowspan="1">10&#x2013;15 cm</th>
                            </tr>
                            <tr>
                                <th align="center" colspan="2" rowspan="1">UNBURNED</th>
                                <th align="center" colspan="2" rowspan="1">BURNED</th>
                                <th align="center" colspan="2" rowspan="1">UNBURNED</th>
                                <th align="center" colspan="2" rowspan="1">BURNED</th>
                                <th align="center" colspan="2" rowspan="1">UNBURNED</th>
                                <th align="center" colspan="2" rowspan="1">BURNED</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                                <th align="left" colspan="1" rowspan="1">MAX</th>
                                <th align="left" colspan="1" rowspan="1">MIN</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td colspan="1" rowspan="1">SOC
                                    <break/>(%)</td>
                                <td colspan="1" rowspan="1">2.18</td>
                                <td colspan="1" rowspan="1">2.10</td>
                                <td colspan="1" rowspan="1">2.02</td>
                                <td colspan="1" rowspan="1">1.94</td>
                                <td colspan="1" rowspan="1">2.04</td>
                                <td colspan="1" rowspan="1">1.97</td>
                                <td colspan="1" rowspan="1">1.74</td>
                                <td colspan="1" rowspan="1">1.62</td>
                                <td colspan="1" rowspan="1">1.89</td>
                                <td colspan="1" rowspan="1">1.76</td>
                                <td colspan="1" rowspan="1">1.58</td>
                                <td colspan="1" rowspan="1">1.49</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">NH
                                    <sub>4</sub>
                                    <sup>+</sup>&#x2212;N
                                    <break/>(kg/ha)</td>
                                <td colspan="1" rowspan="1">592.10</td>
                                <td colspan="1" rowspan="1">543.47</td>
                                <td colspan="1" rowspan="1">389.57</td>
                                <td colspan="1" rowspan="1">349.12</td>
                                <td colspan="1" rowspan="1">519.99</td>
                                <td colspan="1" rowspan="1">475.86</td>
                                <td colspan="1" rowspan="1">325.38</td>
                                <td colspan="1" rowspan="1">294.15</td>
                                <td colspan="1" rowspan="1">443.47</td>
                                <td colspan="1" rowspan="1">396.27</td>
                                <td colspan="1" rowspan="1">292.25</td>
                                <td colspan="1" rowspan="1">265.25</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available P
                                    <break/>(kg/ha)</td>
                                <td colspan="1" rowspan="1">25.73</td>
                                <td colspan="1" rowspan="1">21.36</td>
                                <td colspan="1" rowspan="1">26.69</td>
                                <td colspan="1" rowspan="1">24.98</td>
                                <td colspan="1" rowspan="1">21.42</td>
                                <td colspan="1" rowspan="1">18.77</td>
                                <td colspan="1" rowspan="1">26.24</td>
                                <td colspan="1" rowspan="1">23.72</td>
                                <td colspan="1" rowspan="1">21.82</td>
                                <td colspan="1" rowspan="1">19.10</td>
                                <td colspan="1" rowspan="1">26.30</td>
                                <td colspan="1" rowspan="1">23.99</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available K
                                    <break/>(kg/ha)</td>
                                <td colspan="1" rowspan="1">852.76</td>
                                <td colspan="1" rowspan="1">697.07</td>
                                <td colspan="1" rowspan="1">623.62</td>
                                <td colspan="1" rowspan="1">484.62</td>
                                <td colspan="1" rowspan="1">579.19</td>
                                <td colspan="1" rowspan="1">482.84</td>
                                <td colspan="1" rowspan="1">368.40</td>
                                <td colspan="1" rowspan="1">306.07</td>
                                <td colspan="1" rowspan="1">457.27</td>
                                <td colspan="1" rowspan="1">369.77</td>
                                <td colspan="1" rowspan="1">288.29</td>
                                <td colspan="1" rowspan="1">241.78</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Fe
                                    <break/>(mg/kg)</td>
                                <td colspan="1" rowspan="1">98.37</td>
                                <td colspan="1" rowspan="1">87.22</td>
                                <td colspan="1" rowspan="1">84.42</td>
                                <td colspan="1" rowspan="1">73.54</td>
                                <td colspan="1" rowspan="1">83.36</td>
                                <td colspan="1" rowspan="1">77.44</td>
                                <td colspan="1" rowspan="1">72.52</td>
                                <td colspan="1" rowspan="1">64.52</td>
                                <td colspan="1" rowspan="1">78.41</td>
                                <td colspan="1" rowspan="1">68.87</td>
                                <td colspan="1" rowspan="1">67.93</td>
                                <td colspan="1" rowspan="1">58.88</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Cu
                                    <break/>(mg/kg)</td>
                                <td colspan="1" rowspan="1">0.79</td>
                                <td colspan="1" rowspan="1">0.51</td>
                                <td colspan="1" rowspan="1">0.40</td>
                                <td colspan="1" rowspan="1">0.20</td>
                                <td colspan="1" rowspan="1">0.39</td>
                                <td colspan="1" rowspan="1">0.08</td>
                                <td colspan="1" rowspan="1">0.31</td>
                                <td colspan="1" rowspan="1">0.12</td>
                                <td colspan="1" rowspan="1">0.16</td>
                                <td colspan="1" rowspan="1">0.06</td>
                                <td colspan="1" rowspan="1">0.39</td>
                                <td colspan="1" rowspan="1">0.23</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Mn
                                    <break/>(mg/kg)</td>
                                <td colspan="1" rowspan="1">79.58</td>
                                <td colspan="1" rowspan="1">61.28</td>
                                <td colspan="1" rowspan="1">74.16</td>
                                <td colspan="1" rowspan="1">60.44</td>
                                <td colspan="1" rowspan="1">61.51</td>
                                <td colspan="1" rowspan="1">45.11</td>
                                <td colspan="1" rowspan="1">48.36</td>
                                <td colspan="1" rowspan="1">39.39</td>
                                <td colspan="1" rowspan="1">48.31</td>
                                <td colspan="1" rowspan="1">35.00</td>
                                <td colspan="1" rowspan="1">41.12</td>
                                <td colspan="1" rowspan="1">34.38</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Zn
                                    <break/>(mg/kg)</td>
                                <td colspan="1" rowspan="1">4.17</td>
                                <td colspan="1" rowspan="1">2.18</td>
                                <td colspan="1" rowspan="1">2.22</td>
                                <td colspan="1" rowspan="1">1.41</td>
                                <td colspan="1" rowspan="1">2.46</td>
                                <td colspan="1" rowspan="1">1.59</td>
                                <td colspan="1" rowspan="1">2.12</td>
                                <td colspan="1" rowspan="1">1.21</td>
                                <td colspan="1" rowspan="1">2.17</td>
                                <td colspan="1" rowspan="1">1.17</td>
                                <td colspan="1" rowspan="1">2.01</td>
                                <td colspan="1" rowspan="1">1.05</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>A two way ANOVA test showed that fire reduced the SOC of the surface layer (0&#x2013;5 cm) varying significantly (P=0.00005) between the burned and unburned areas (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f1">Figure 1A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while it did not vary significantly over the sampling months (P=0.480). The SOC of the 5&#x2013;10 cm soil layer was also significantly affected (P&lt;0.001) by fire (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f1">Figure 1B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while there were no significant variation (P=0.090) among the sampling months. The SOC also varied significantly (P&lt;0.001) between the burned and unburned areas in the 10&#x2013;15 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f1">Figure 1C</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while it did not vary significantly (P=0.324) among the sampling months.</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <p>Soil organic carbon % at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.001) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=5).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure1.gif"/>
                </fig>
                <table-wrap id="T2" orientation="portrait" position="anchor">
                    <label>Table 2. </label>
                    <caption>
                        <title>Results of F tests based on two way ANOVA for SOC, NH
                            <sub>4</sub>
                            <sup>+</sup>&#x2013;N, Bray-extractable P, available K and DTPA-extractable (available) micronutrients (Fe, Cu, Mn &amp; Zn) at the 0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm soil layers.</title>
                        <p>Fire effect (F) and sampling month effect (E); *, ** and *** statistically significant at P&lt;0.05, 0.01, 0.001 respectively.</p>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="center" colspan="1" rowspan="2" valign="middle">Soil nutrients</th>
                                <th align="center" colspan="2" rowspan="1">0&#x2013;5 cm</th>
                                <th align="center" colspan="2" rowspan="1">5&#x2013;10 cm</th>
                                <th align="center" colspan="2" rowspan="1">10&#x2013;15 cm</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1">F</th>
                                <th align="left" colspan="1" rowspan="1">E</th>
                                <th align="left" colspan="1" rowspan="1">F</th>
                                <th align="left" colspan="1" rowspan="1">E</th>
                                <th align="left" colspan="1" rowspan="1">F</th>
                                <th align="left" colspan="1" rowspan="1">E</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td colspan="1" rowspan="1">SOC</td>
                                <td colspan="1" rowspan="1">40.83***</td>
                                <td colspan="1" rowspan="1">1.03</td>
                                <td colspan="1" rowspan="1">189.0***</td>
                                <td colspan="1" rowspan="1">2.31</td>
                                <td colspan="1" rowspan="1">73.22***</td>
                                <td colspan="1" rowspan="1">1.32</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">NH
                                    <sub>4</sub>
                                    <sup>+</sup>-N</td>
                                <td colspan="1" rowspan="1">281.07***</td>
                                <td colspan="1" rowspan="1">1.94</td>
                                <td colspan="1" rowspan="1">408.09***</td>
                                <td colspan="1" rowspan="1">2.47</td>
                                <td colspan="1" rowspan="1">151.99***</td>
                                <td colspan="1" rowspan="1">1.32</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available P</td>
                                <td colspan="1" rowspan="1">6.97*</td>
                                <td colspan="1" rowspan="1">2.01</td>
                                <td colspan="1" rowspan="1">44.52***</td>
                                <td colspan="1" rowspan="1">1.57</td>
                                <td colspan="1" rowspan="1">25.37***</td>
                                <td colspan="1" rowspan="1">0.52</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available K</td>
                                <td colspan="1" rowspan="1">103.85***</td>
                                <td colspan="1" rowspan="1">8.64***</td>
                                <td colspan="1" rowspan="1">150.86***</td>
                                <td colspan="1" rowspan="1">4.46*</td>
                                <td colspan="1" rowspan="1">70.79***</td>
                                <td colspan="1" rowspan="1">2.25</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Fe</td>
                                <td colspan="1" rowspan="1">16.61**</td>
                                <td colspan="1" rowspan="1">1.18</td>
                                <td colspan="1" rowspan="1">27.78***</td>
                                <td colspan="1" rowspan="1">1.01</td>
                                <td colspan="1" rowspan="1">18.01**</td>
                                <td colspan="1" rowspan="1">2.07</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Cu</td>
                                <td colspan="1" rowspan="1">33.98***</td>
                                <td colspan="1" rowspan="1">1.04</td>
                                <td colspan="1" rowspan="1">0.05</td>
                                <td colspan="1" rowspan="1">0.24</td>
                                <td colspan="1" rowspan="1">18.15**</td>
                                <td colspan="1" rowspan="1">0.76</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Mn</td>
                                <td colspan="1" rowspan="1">1.09</td>
                                <td colspan="1" rowspan="1">5.00**</td>
                                <td colspan="1" rowspan="1">15.72**</td>
                                <td colspan="1" rowspan="1">5.36**</td>
                                <td colspan="1" rowspan="1">3.55</td>
                                <td colspan="1" rowspan="1">4.34*</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1">Available Zn</td>
                                <td colspan="1" rowspan="1">12.97**</td>
                                <td colspan="1" rowspan="1">2.32</td>
                                <td colspan="1" rowspan="1">7.38</td>
                                <td colspan="1" rowspan="1">8.40***</td>
                                <td colspan="1" rowspan="1">1.68</td>
                                <td colspan="1" rowspan="1">16.80***</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec>
                <title>Ammonium nitrogen</title>
                <p>Soil NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N contents in the surface layer (0&#x2013;5 cm) ranged from 543.47 to 592.10 kg/ha in the unburned area while in the burned area, they ranged from 349.12 to 389.57 kg/ha (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In the sub-surface layers (5&#x2013;10 and 10&#x2013;15 cm) of the unburned area, soil NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N contents ranged from 475.86 to 519.99 kg/ha and from 396.27 to 443.47 kg/ha, respectively while in the burned area, they ranged from 294.15 to 325.38 kg/ha and from 265.25 to 292.25 kg/ha, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>A two way ANOVA test indicated that fire caused a significant reduction (P&lt;0.001) of soil NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N in the surface (0&#x2013;5 cm) layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f2">Figure 2A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while sampling date did not significantly (P=0.141) affect the soil NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N. NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N of the 5&#x2013;10 cm soil layer was also significantly lower (P&lt;0.001) in the burned area compared to the adjacent unburned area (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f2">Figure 2B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while it showed no significant variation (P=0.073) over the sampling months. Fire also affected the NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N content of the 10&#x2013;15 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f2">Figure 2C</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) varying significantly (P&lt;0.001) between the burned and unburned areas while no significant effect (P=0.322) of sampling month was observed.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>Figure 2. </label>
                    <caption>
                        <p>NH
                            <sub>4</sub>
                            <sup>+</sup>&#x2013;N (kg/ha) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.001) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=3).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure2.gif"/>
                </fig>
            </sec>
            <sec>
                <title>Bray-extractable (available) phosphorus</title>
                <p>The available P of the 0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm soil layers in the unburned area varied from 21.36 to 25.73 kg/ha, 18.77 to 21.42 kg/ha and from 19.10 to 21.82 kg/ha, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In contrast, the available P of the burned area in the three different soil layers ranged from 24.98 to 26.69 kg/ha, 23.72 to 26.24 kg/ha and from 23.99 to 26.30 kg/ha, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>A two way ANOVA test showed that fire resulted in a significant rise (P=0.022) of the available P in the upper 5 cm of the burned area (Unburned &lt; Burned, 
                    <xref ref-type="fig" rid="f3">Figure 3A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while it did not vary significantly (P=0.131) over the sampling months. In the 5&#x2013;10 cm soil layer, fire also significantly increased (P&lt;0.001) the available P, the concentration being higher in the burned area than the adjacent unburned area (Unburned &lt; Burned, 
                    <xref ref-type="fig" rid="f3">Figure 3B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while sampling month had no significant effect (P=0.231) on the available P. The available P of the 10&#x2013;15 cm soil layer also showed significant variation (P&lt;0.001) between the burned and unburned areas (Unburned &lt; Burned, 
                    <xref ref-type="fig" rid="f3">Figure 3C</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while no significant variation (P=0.850) was observed over the sampling months.</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>Figure 3. </label>
                    <caption>
                        <p>Available phosphorus (kg/ha) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=3).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure3.gif"/>
                </fig>
            </sec>
            <sec>
                <title>Available potassium</title>
                <p>The available potassium contents in the surface soil layer (0&#x2013;5 cm) of the unburned and burned areas ranged from 697.07 to 852.76 kg/ha and from 484.62 to 623.62 kg/ha, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In the sub-surface soil layers (5&#x2013;10 and 10&#x2013;15 cm) of the unburned area the available potassium contents respectively ranged from 482.84 to 579.19 kg/ha and from 369.77 to 457.27 kg/ha while they ranged from 306.07 to 368.40 kg/ha in the 5&#x2013;10 and from 241.78 to 288.29 kg/ha in the 10&#x2013;15 cm sub-surface soil layers of the burned area (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>A two way ANOVA test showed a significant fire induced loss (P&lt;0.001) of the available potassium from the 0&#x2013;5 cm soil layer of the burned area (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f4">Figure 4A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) and there was also significant variation among the sampling months (P&lt;0.0006). Fire also caused a significant reduction (P&lt;0.001) of the available potassium in the 5&#x2013;10 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f4">Figure 4B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) and it varied significantly among the sampling months (P=0.010). A significant difference (P&lt;0.001) in the potassium availability between the burned and unburned areas was also observed in the 10&#x2013;15 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f4">Figure 4C</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while there was no significant variation (P=0.096) among the sampling months.</p>
                <fig fig-type="figure" id="f4" orientation="portrait" position="float">
                    <label>Figure 4. </label>
                    <caption>
                        <p>Available potassium (kg/ha) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&#x2264;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=3).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure4.gif"/>
                </fig>
            </sec>
            <sec>
                <title>DTPA-extractable (available) micronutrients (Fe, Cu, Mn and Zn)</title>
                <p>The DTPA-extractable Fe of the unburned area ranged from 87.22 to 98.37 mg/kg in the 0&#x2013;5, 77.44 to 83.36 mg/kg in the 5&#x2013;10 and 68.87 to 78.41 mg/kg in the 10&#x2013;15 cm soil layers while in the burned area, it ranged from 73.54 to 84.42 mg/kg, 64.52 to 72.52 mg/kg and from 58.88 to 67.93 mg/kg in the 0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm soil layers, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>). Thus, the unburned area had a higher Fe availability compared to the burned area in all the three soil layers.</p>
                <p>A two way ANOVA test indicated a significant effect (P=0.001) of fire on the DTPA-extractable Fe which showed a decrease in the surface 0&#x2013;5 cm soil layer of the burned area (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f5">Figure 5A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while no significant effect (P=0.393) of sampling month was observed. In the subsurface layer (5&#x2013;10 cm), the DTPA-extractable Fe showed a significant variation (P&lt;0.001) between the burned and unburned areas (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f5">Figure 5B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while no significant difference (P=0.490) was found among the sampling months. The 10&#x2013;15 cm soil layer also showed a significant (P=0.001) fire-induced loss of the DTPA-extractable Fe which was found to be lower in the burned area than the adjacent unburned area (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f5">Figure 5C</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while there was no significant difference (P=0.121) among the sampling months as confirmed by the two way ANOVA test.</p>
                <fig fig-type="figure" id="f5" orientation="portrait" position="float">
                    <label>Figure 5. </label>
                    <caption>
                        <p>Available iron (mg/kg) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=4).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure5.gif"/>
                </fig>
                <p>The DTPA-extractable Cu contents of the 0&#x2013;5 cm soil layer ranged from 0.51 to 0.79 mg/kg in the unburned area while in the burned area, they ranged from 0.20 to 0.40 mg/kg (
                    <xref ref-type="table" rid="T1">Table 1</xref>). The DTPA-extractable Cu contents of the sub-surface layers (5&#x2013;10 and 10&#x2013;15 cm) respectively ranged from 0.08 to 0.39 mg/kg and from 0.06 to 0.16 mg/kg in the unburned area while in the burned area they ranged from 0.12 to 0.3 mg/kg and from 0.23 to 0.39 mg/kg, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>As confirmed by the two way ANOVA test, fire caused a significant decline (P&lt;0.001) of the DTPA-extractable Cu contents in the 0&#x2013;5 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f6">Figure 6A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) but there was a significant post-fire increase (P=0.001) in the 10&#x2013;15 cm soil layer. The 5&#x2013;10 cm soil layer showed no significant variation (P=0.820) between the burned and unburned areas with respect to the post-fire Cu availability. No significant variation was observed among the sampling months in the DTPA-extractable Cu contents of the 0&#x2013;5 (P=0.470), 5&#x2013;10 (P=0.984) and 10&#x2013;15 cm (P=0.668) soil layers.</p>
                <fig fig-type="figure" id="f6" orientation="portrait" position="float">
                    <label>Figure 6. </label>
                    <caption>
                        <p>Available copper (mg/kg) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=4).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure6.gif"/>
                </fig>
                <p>In the unburned area, the DTPA-extractable Mn of the 0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm soil layers varied from 61.28 to 79.58 mg/kg, 45.11 to 61.51 mg/kg and from 35.00 to 48.3 mg/kg, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>). In contrast, the DTPA-extractable Mn of the three different soil layers respectively ranged from 60.44 to 74.16 mg/kg, 39.39 to 48.36 mg/kg and from 34.38 to 41.12 mg/kg (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>A two way ANOVA test indicated that fire had no significant effect on the DTPA-extractable Mn contents of the 0&#x2013;5 (P=0.318) and 10&#x2013;15 cm (P=0.085) soil layers. However, a significant post-fire decrease (P=0.002) in the Mn availability was noticed in the 5&#x2013;10 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f7">Figure 7B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>). The DTPA-extractable Mn also varied significantly among the sampling months in the 0&#x2013;5 (P=0.006), 5&#x2013;10 (P=0.004) and 10&#x2013;15 cm (P=0.011) soil layers.</p>
                <fig fig-type="figure" id="f7" orientation="portrait" position="float">
                    <label>Figure 7. </label>
                    <caption>
                        <p>Available manganese (mg/kg) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=4).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure7.gif"/>
                </fig>
                <p>In the surface layer (0&#x2013;5 cm), the DTPA-extractable Zn of the unburned area ranged from 2.18 to 4.17 mg/kg while in the burned area, it ranged from 1.41 to 2.22 mg/kg (
                    <xref ref-type="table" rid="T1">Table 1</xref>). The DTPA-extractable Zn contents of the sub-surface layers (5&#x2013;10 and 10&#x2013;15 cm) in the unburned area respectively ranged from 1.59 to 2.46 mg/kg and from 1.17 to 2.17 mg/kg while in the burned area, they ranged from 1.21 to 2.12 mg/kg and from 1.05 to 2.01 mg/kg, respectively (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <p>The results of the two way ANOVA test showed that fire reduced the DTPA-extractable Zn contents of the 0&#x2013;5 cm soil layer varying significantly (P=0.004) between the burned and unburned areas (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f8">Figure 8A</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>) while it did not show significant variation (P=0.08) among the sampling months. A significant decline (P=0.020) was also observed in the 5&#x2013;10 cm soil layer (Unburned &gt; Burned, 
                    <xref ref-type="fig" rid="f8">Figure 8B</xref>, 
                    <xref ref-type="table" rid="T2">Table 2</xref>). The DTPA-extractable Zn of the 5&#x2013;10 cm soil layer also varied significantly (P&lt;0.001) among the sampling months. The 10&#x2013;15 cm soil layer showed no significant variation (P=0.220) in terms of the Zn availability between the burned and unburned areas. However, it showed significant variation (P&lt;0.001) among the sampling months.</p>
                <fig fig-type="figure" id="f8" orientation="portrait" position="float">
                    <label>Figure 8. </label>
                    <caption>
                        <p>Available zinc (mg/kg) at 0&#x2013;5 (
                            <bold>A</bold>), 5&#x2013;10 (
                            <bold>B</bold>) and 10&#x2013;15 cm (
                            <bold>C</bold>) soil layers. Significant differences (P&lt;0.05) between unburned and burned areas on specific sampling months are indicated by different letters above histogram bars. Data show mean &#x00b1; SE (n=4).</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/3273/205564cb-e399-4fa2-a52c-7036906c5503_figure8.gif"/>
                </fig>
                <media content-type="figshare" orientation="portrait" position="float" xlink:href="http://dx.doi.org/10.6084/m9.figshare.903706"/>
            </sec>
        </sec>
        <sec sec-type="discussion">
            <title>Discussion</title>
            <sec>
                <title>Soil organic carbon</title>
                <p>SOC contents decreased in all the three soil layers of the burned area as confirmed by the two way ANOVA test and the decrease persisted throughout the sampling period. The persistence of this condition throughout the study reflects the high severity of the forest fire and the fact that we found a significant decrease of SOC in the 5&#x2013;10 and 10&#x2013;15 cm soil layers is further evidence of the high severity of the forest fire. The fire-induced reduction in SOC in this study is consistent with the results from studies conducted elsewhere
                    <sup>
                        <xref ref-type="bibr" rid="ref-16">16</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-20">20</xref>
                    </sup>. However, contrasting results have also been obtained by other researchers
                    <sup>
                        <xref ref-type="bibr" rid="ref-21">21</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-23">23</xref>
                    </sup> who reported increased SOC after fire disturbance. The decrease in SOC content of the burned area may be attributed to the volatilization of organic carbon and conversion of organic matter to ash
                    <sup>
                        <xref ref-type="bibr" rid="ref-24">24</xref>,
                        <xref ref-type="bibr" rid="ref-25">25</xref>
                    </sup>. In a laboratory experiment, Terefe 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-26">26</xref>
                    </sup> observed a significant reduction in SOC content from A horizons after heating at 200 and 300&#x00b0;C with the complete loss of SOC at 500&#x00b0;C.</p>
            </sec>
            <sec>
                <title>NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N and available potassium</title>
                <p>As confirmed by the two way ANOVA test, forest wildfire resulted in a significant loss of NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N and available K from the burned area. Most studies
                    <sup>
                        <xref ref-type="bibr" rid="ref-17">17</xref>,
                        <xref ref-type="bibr" rid="ref-27">27</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-29">29</xref>
                    </sup> show an initial increase in inorganic forms of nitrogen such as NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N after fire followed by a decline with time. In the present study, however, we found a decrease in NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N concentration of the burned area and the decrease persisted until the study ended. This finding agreed with the results obtained by Shaoqing 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-30">30</xref>
                    </sup> and Longo 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-19">19</xref>
                    </sup>. The burned area also had lower available potassium than the adjacent unburned area. Yinghua 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-31">31</xref>
                    </sup> reported short-term increase in available potassium after fire which then declined and was lower than the unburned area at later sampling times. The decrease in NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N and available potassium of the burned area may be attributed to the individual or combined effect of several factors such as volatilization, slow mineralization rate, increased uptake by newly sprouted vegetation
                    <sup>
                        <xref ref-type="bibr" rid="ref-32">32</xref>
                    </sup>, dry ravel erosion
                    <sup>
                        <xref ref-type="bibr" rid="ref-33">33</xref>
                    </sup>, surface run-off and leaching. In addition to the above mentioned factors, the loss of NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N from the burned area may also be due to the nitrification of NH
                    <sub>4</sub>
                    <sup>+</sup> to NO
                    <sub>3</sub>
                    <sup>&#x2013;</sup> as heat-sensitive nitrifying bacteria recolonized the area
                    <sup>
                        <xref ref-type="bibr" rid="ref-34">34</xref>,
                        <xref ref-type="bibr" rid="ref-35">35</xref>
                    </sup>. Among all nutrients vital for plant growth, N is the most sensitive to volatilization. Half of the N in organic matter can be volatilized at 500&#x00b0;C
                    <sup>
                        <xref ref-type="bibr" rid="ref-35">35</xref>,
                        <xref ref-type="bibr" rid="ref-36">36</xref>
                    </sup>. The volatilization temperature of K is 760&#x00b0;C. Because the forest fire consumed the entire understory vegetation and the litter layer, it is possible that the temperature was sufficiently high during the fire to volatilize significant quantities of NH
                    <sub>4</sub>
                    <sup>+</sup>&#x2013;N and available potassium. The rate of nutrient mineralization may have been slowed down probably due to fire-induced reduction in soil decomposer organisms which include microbes and invertebrates. High severity-fires sterilize the soil or delay the recovery of soil microbes and consequently reduce their activity
                    <sup>
                        <xref ref-type="bibr" rid="ref-37">37</xref>,
                        <xref ref-type="bibr" rid="ref-38">38</xref>
                    </sup>. The litter loss and microclimatic changes resulting from fire can indirectly decrease the total mass and species numbers of soil and litter dwelling invertebrates
                    <sup>
                        <xref ref-type="bibr" rid="ref-39">39</xref>,
                        <xref ref-type="bibr" rid="ref-40">40</xref>
                    </sup>. Choromanska and DeLuca
                    <sup>
                        <xref ref-type="bibr" rid="ref-41">41</xref>
                    </sup> reported that N mineralization decreased after fire and did not recover after nine months of the study period.</p>
                <p>Soil that has been protected from erosional processes for decades by vegetation or litter cover is particularly vulnerable when the cover is removed
                    <sup>
                        <xref ref-type="bibr" rid="ref-42">42</xref>
                    </sup>. When the vegetation and litter layer is destroyed by fire, the soil is susceptible to dry ravel
                    <sup>
                        <xref ref-type="bibr" rid="ref-43">43</xref>,
                        <xref ref-type="bibr" rid="ref-44">44</xref>
                    </sup>, which can be defined as the movement of particles by rolling, sliding and bouncing down slope under the influence of gravity
                    <sup>
                        <xref ref-type="bibr" rid="ref-45">45</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-47">47</xref>
                    </sup> and to water erosion during the first major rain event
                    <sup>
                        <xref ref-type="bibr" rid="ref-48">48</xref>,
                        <xref ref-type="bibr" rid="ref-49">49</xref>
                    </sup>. Following fire, surface run-off and erosion can be increased by several orders of magnitude
                    <sup>
                        <xref ref-type="bibr" rid="ref-50">50</xref>,
                        <xref ref-type="bibr" rid="ref-51">51</xref>
                    </sup>, mainly during the first months when the soil is bare, if intense rainfall events are frequent
                    <sup>
                        <xref ref-type="bibr" rid="ref-52">52</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-54">54</xref>
                    </sup>.</p>
            </sec>
            <sec>
                <title>Available (Bray-extractable) phosphorus</title>
                <p>In this study, the available P was higher in the burned area than the adjacent unburned area in all the three soil layers and the increase was significant as proved by the two way ANOVA test. This finding is in agreement with the findings of several other workers who have reported increased post-fire available P levels
                    <sup>
                        <xref ref-type="bibr" rid="ref-55">55</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-59">59</xref>
                    </sup>. Though post-fire increase in the available P level is a common trend in most research findings, decreases have also been noted
                    <sup>
                        <xref ref-type="bibr" rid="ref-19">19</xref>,
                        <xref ref-type="bibr" rid="ref-60">60</xref>
                    </sup>. The significant post-fire increase in the available P may be attributed to a number of factors such as fire-induced conversion of organic forms of soil phosphorus to inorganic forms, lack of orthophosphate leaching and lack of plants that utilize this nutrient in the study site. P loss through volatilization generally does not take place
                    <sup>
                        <xref ref-type="bibr" rid="ref-61">61</xref>
                    </sup>. However, burning converts the soil organic P to orthophosphate
                    <sup>
                        <xref ref-type="bibr" rid="ref-62">62</xref>,
                        <xref ref-type="bibr" rid="ref-63">63</xref>
                    </sup>, the sole form of soil P available to biota. The time in which the positive effect on P bioavailability runs short is highly variable depending on numerous factors. Romanya 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-64">64</xref>
                    </sup> found increased post-fire soil concentrations of available P (NaHCO
                    <sub>3</sub>-extractable) and labile P (NH
                    <sub>4</sub>F HCl-extractable) even at seven months after clear felling and slash burning, in a 
                    <italic toggle="yes">Eucalyptus</italic> forest. In a Picea dominated forest, Macadam
                    <sup>
                        <xref ref-type="bibr" rid="ref-65">65</xref>
                    </sup> found that the available P in the upper 30 cm mineral soil had increased by up to 50%, nine months after slash burning, and this increase persisted, although somewhat diminished, twenty months after the fire event. In this research, sampling at monthly intervals started approximately three months after the fire event and continued for a period of one year, so it may have been within the fire-associated P enrichment period.</p>
            </sec>
            <sec>
                <title>Available (DTPA-extractable) micronutrients (Fe, Cu, Mn and Zn)</title>
                <p>The available Fe levels depleted in all the three soil layers (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm) of the burned area and the depletion was significant as confirmed by the two way ANOVA test. Some recent studies have also reported a decline in the Fe availability of burned soils
                    <sup>
                        <xref ref-type="bibr" rid="ref-18">18</xref>,
                        <xref ref-type="bibr" rid="ref-29">29</xref>,
                        <xref ref-type="bibr" rid="ref-66">66</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-68">68</xref>
                    </sup>. The fire induced depletion of the available Fe in the burned area could be associated with losses (by convection in smoke columns, transport by wind, erosion and leaching) and/or conversion to insoluble oxidized forms in soils as have been reported for several other nutrients
                    <sup>
                        <xref ref-type="bibr" rid="ref-25">25</xref>,
                        <xref ref-type="bibr" rid="ref-69">69</xref>
                    </sup>.</p>
                <p>Contradictory results were obtained in terms of fire-induced effects on the soil available Cu contents of the three soil layers studied. While the available Cu content of the 0&#x2013;5 cm soil layer declined significantly, it showed no noticeable variation between the burned and unburned areas in the 5&#x2013;10 cm soil layer. The 10&#x2013;15 cm soil layer showed an increase in the Cu availability after the fire event, the available Cu being higher in the burned area than the adjacent unburned area. Other authors
                    <sup>
                        <xref ref-type="bibr" rid="ref-68">68</xref>,
                        <xref ref-type="bibr" rid="ref-70">70</xref>
                    </sup> have also observed fire-induced increases in the soil available Cu. The fire induced-loss of the available Cu from the 0&#x2013;5 cm soil layer of the burned area may be due to the singular or combination effects of several factors such as erosion, leaching, transport by wind, 
                    <italic toggle="yes">etc</italic>. Solute losses increased during the first rain events following fire according to one study
                    <sup>
                        <xref ref-type="bibr" rid="ref-71">71</xref>
                    </sup>. Thus, it is possible that during rains some amounts of the available Cu in the ash resulting from fire leached into the deeper soil layers causing higher Cu availability in the 10&#x2013;15 cm soil layer.</p>
                <p>As confirmed by the two way ANOVA test, fire had no significant effect on the available Mn contents of the 0&#x2013;5 and 10&#x2013;15 cm soil layers, although Gomez-Rey 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-29">29</xref>
                    </sup> reported higher post-fire Mn availability in the 0&#x2013;5 cm soil layer, attributed to Mn supplied by ashes from the burned vegetation. In contrast to the lack of difference in terms of the Mn availability between the burned and unburned areas in the 0&#x2013;5 and 10&#x2013;15 cm soil layers, the 5&#x2013;10 cm soil layer showed a significant post-fire decrease in the available Mn compared with the unburned areas. Research findings from several studies have been mixed in terms of post-fire Mn availability. Brye
                    <sup>
                        <xref ref-type="bibr" rid="ref-72">72</xref>
                    </sup> observed a significant decline in the soil available Mn (extracted with Mehlich 3) as a consequence of 12 years of annual burning on a tall-grass prairie. However, other authors
                    <sup>
                        <xref ref-type="bibr" rid="ref-66">66</xref>,
                        <xref ref-type="bibr" rid="ref-68">68</xref>,
                        <xref ref-type="bibr" rid="ref-73">73</xref>
                    </sup> have reported a significant increase in the soil available Mn after fire.</p>
                <p>With respect to the post-fire Zn availability, we found that the available Zn decreased in the 0&#x2013;5 and 5&#x2013;10 cm soil layers showing significant variations between the burned and unburned areas as indicated by the two way ANOVA tests. No fire effect was seen in the 10&#x2013;15 cm soil layer as regards the available Zn which did not differ between the burned and unburned areas. The post-fire decline in the available Zn of the 0&#x2013;5 and 5&#x2013;10 cm soil layers is consistent with the observation of Marafa and Chau
                    <sup>
                        <xref ref-type="bibr" rid="ref-74">74</xref>
                    </sup> who have also reported a post-fire reduction in the amount of Zn. Other researchers have obtained contradictory results. For example, Garcia-Marco and Gonzalez Prieto
                    <sup>
                        <xref ref-type="bibr" rid="ref-66">66</xref>
                    </sup> observed an initial rise in the available Zn after fire disturbance followed by a decline one year after the fire. However, Close 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-68">68</xref>
                    </sup> and Stankov Jovanovic 
                    <italic toggle="yes">et al.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-69">69</xref>
                    </sup> have reported enhanced Zn availability in burned soils due to the release of Zn by ashes from burned vegetation. The available Zn depletion in the 0&#x2013;5 and 5&#x2013;10 cm soil layers of the burned area may be attributed to leaching and erosional losses as this element could be quickly leached
                    <sup>
                        <xref ref-type="bibr" rid="ref-75">75</xref>
                    </sup> or lost in eroded sediments
                    <sup>
                        <xref ref-type="bibr" rid="ref-29">29</xref>
                    </sup>.</p>
            </sec>
        </sec>
        <sec sec-type="conclusions">
            <title>Conclusion</title>
            <p>The SOC was significantly reduced following fire in all the three soil layers (0&#x2013;5, 5&#x2013;10 and 10&#x2013;15 cm) and the significant reduction of the SOC even in the sub-surface layers (5&#x2013;10 and 10&#x2013;15 cm) is an indication of the high severity of the forest wildfire. The forest wildfire also had a significant effect on the available macronutrient concentrations, decreasing NH
                <sub>4</sub>
                <sup>+</sup>&#x2013;N and available K and increasing that of available P in all the three soil layers. Contradictory results were obtained with respect to the soil micronutrient availability. While the available Fe declined in all the three soil layers, the available Cu declined only in the 0&#x2013;5 cm soil layer. However, in the 10&#x2013;15 cm soil layer, the available Cu showed an increase, the concentration being higher in the burned area compared to the unburned area. The available Cu contents of the 5&#x2013;10 cm soil layer did not vary significantly between the burned and unburned areas. The Mn availability declined in the 5&#x2013;10 cm soil layer but no fire-induced effect was found on the available Mn contents of the 0&#x2013;5 and 10&#x2013;15 cm soil layers. Fire significantly reduced the available Zn contents of the 0&#x2013;5 and 5&#x2013;10 cm soil layers. The available Zn content of the 10&#x2013;15 cm soil layer did not show significant variation between the burned and unburned areas. Thus, the forest wildfire resulted in a significant loss of most soil nutrients at this site. Taking into account the post-fire decline of most soil nutrients in one or all of the three soil layers studied, it can be concluded that forest wildfire had detrimental impacts on soil nutrients at this site and the ecologically most significant effect was the loss of N and K from the burned soil.</p>
        </sec>
        <sec>
            <title>Data availability</title>
            <p>The data referenced by this article are under copyright with the following copyright statement: Copyright: &#x00ef;&#x00bf;&#x00bd; 2014 Sitlhou A and Singh TB</p>
            <p>Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
                <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/"/>
            </p>
            <p>Figshare. Post forest fire soil nutrient levels in burned and unburned areas of the Koubru Hills, Manipur, 
                <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.6084/m9.figshare.903706">http://dx.doi.org/10.6084/m9.figshare.903706</ext-link>
                <sup>
                    <xref ref-type="bibr" rid="ref-76">76</xref>
                </sup>
            </p>
        </sec>
    </body>
    <back>
        <ack>
            <title>Acknowledgements</title>
            <p>Takhellambam Bikramsen Singh is greatly acknowledged for his timely help during the selection of the study site. The authors are indebted to the village elders, Seitinhen Vaiphei and Dirinamei Dirangbou, for unrestricted access to the study site and their friendly attitude. Dr.Athokpam Herojit Singh deserves special mention for fruitful discussions of the soil analytical methods. The authors would also like to thank the technical staff at the Department of Soil Science, Central Agricultural University, for their great help and patience during the long days of soil analysis in the laboratory. Thanks also go to Hechong Sitlhou and Samson Sitlhou for their support and encouragement of this research. Ningthoujam Ranbir Singh, Khumbongmayum Rakesh Singh and Donga Mizo are also highly appreciated for their assistance in soil sampling during field work. The authors would also like to gratefully acknowledge Kshetrimayum Radheshyam Singh for his advice on statistical analysis.</p>
        </ack>
        <sec sec-type="supplementary-material">
            <title>Supplementary materials</title>
            <table-wrap id="ST1" orientation="portrait" position="anchor">
                <label>Supplementary Table 1. </label>
                <caption>
                    <title>The individual P values (both significant and non-significant) determined by the one way ANOVA test for all the soil nutrients studied at 0&#x2013;5 cm soil depths in each sampling month.</title>
                    <p>The significant P values are followed by the letters (ab) on the right.</p>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1">Months</th>
                            <th align="left" colspan="1" rowspan="1">SOC %</th>
                            <th align="left" colspan="1" rowspan="1">NH
                                <sub>4</sub>
                                <sup>+</sup>&#x2212;N</th>
                            <th align="left" colspan="1" rowspan="1">Available P</th>
                            <th align="left" colspan="1" rowspan="1">Available K</th>
                            <th align="left" colspan="1" rowspan="1">Available Fe</th>
                            <th align="left" colspan="1" rowspan="1">Available Cu</th>
                            <th align="left" colspan="1" rowspan="1">Available Mn</th>
                            <th align="left" colspan="1" rowspan="1">Available Zn</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td colspan="1" rowspan="1">APRIL</td>
                            <td colspan="1" rowspan="1">0.013732ab</td>
                            <td colspan="1" rowspan="1">0.00000115ab</td>
                            <td colspan="1" rowspan="1">0.092399</td>
                            <td colspan="1" rowspan="1">0.000488ab</td>
                            <td colspan="1" rowspan="1">0.024384ab</td>
                            <td colspan="1" rowspan="1">0.0000408ab</td>
                            <td colspan="1" rowspan="1">0.01729ab</td>
                            <td colspan="1" rowspan="1">0.000438ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MAY</td>
                            <td colspan="1" rowspan="1">0.0000436ab</td>
                            <td colspan="1" rowspan="1">0.00000025ab</td>
                            <td colspan="1" rowspan="1">0.788271</td>
                            <td colspan="1" rowspan="1">0.0000327ab</td>
                            <td colspan="1" rowspan="1">0.00000562ab</td>
                            <td colspan="1" rowspan="1">0.013035ab</td>
                            <td colspan="1" rowspan="1">0.005514ab</td>
                            <td colspan="1" rowspan="1">0.00768ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JUNE</td>
                            <td colspan="1" rowspan="1">0.000298ab</td>
                            <td colspan="1" rowspan="1">0.0000014ab</td>
                            <td colspan="1" rowspan="1">0.003423ab</td>
                            <td colspan="1" rowspan="1">0.00036ab</td>
                            <td colspan="1" rowspan="1">0.031598ab</td>
                            <td colspan="1" rowspan="1">0.0000341ab</td>
                            <td colspan="1" rowspan="1">0.114677</td>
                            <td colspan="1" rowspan="1">0.00692ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JULY</td>
                            <td colspan="1" rowspan="1">0.000395ab</td>
                            <td colspan="1" rowspan="1">0.00000053ab</td>
                            <td colspan="1" rowspan="1">0.794072</td>
                            <td colspan="1" rowspan="1">0.001494ab</td>
                            <td colspan="1" rowspan="1">0.643206</td>
                            <td colspan="1" rowspan="1">0.000121ab</td>
                            <td colspan="1" rowspan="1">0.059718</td>
                            <td colspan="1" rowspan="1">0.214843</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">AUG</td>
                            <td colspan="1" rowspan="1">0.014326ab</td>
                            <td colspan="1" rowspan="1">0.00000152ab</td>
                            <td colspan="1" rowspan="1">0.024494ab</td>
                            <td colspan="1" rowspan="1">0.00105ab</td>
                            <td colspan="1" rowspan="1">0.000201ab</td>
                            <td colspan="1" rowspan="1">0.00000008ab</td>
                            <td colspan="1" rowspan="1">0.243871</td>
                            <td colspan="1" rowspan="1">0.006771ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">SEPT</td>
                            <td colspan="1" rowspan="1">0.000863ab</td>
                            <td colspan="1" rowspan="1">0.0000011ab</td>
                            <td colspan="1" rowspan="1">0.011319ab</td>
                            <td colspan="1" rowspan="1">0.000102ab</td>
                            <td colspan="1" rowspan="1">0.001058ab</td>
                            <td colspan="1" rowspan="1">0.00000717ab</td>
                            <td colspan="1" rowspan="1">0.001556ab</td>
                            <td colspan="1" rowspan="1">0.000325ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">OCT</td>
                            <td colspan="1" rowspan="1">0.000972ab</td>
                            <td colspan="1" rowspan="1">0.00000272ab</td>
                            <td colspan="1" rowspan="1">0.033226ab</td>
                            <td colspan="1" rowspan="1">0.0000868ab</td>
                            <td colspan="1" rowspan="1">0.000357ab</td>
                            <td colspan="1" rowspan="1">0.014517ab</td>
                            <td colspan="1" rowspan="1">0.002495ab</td>
                            <td colspan="1" rowspan="1">0.000144ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">NOV</td>
                            <td colspan="1" rowspan="1">0.033615ab</td>
                            <td colspan="1" rowspan="1">0.00000281ab</td>
                            <td colspan="1" rowspan="1">0.027905ab</td>
                            <td colspan="1" rowspan="1">0.00000602ab</td>
                            <td colspan="1" rowspan="1">0.000322ab</td>
                            <td colspan="1" rowspan="1">0.00000114ab</td>
                            <td colspan="1" rowspan="1">0.0005ab</td>
                            <td colspan="1" rowspan="1">1</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">DEC</td>
                            <td colspan="1" rowspan="1">0.000518ab</td>
                            <td colspan="1" rowspan="1">0.0000013ab</td>
                            <td colspan="1" rowspan="1">1</td>
                            <td colspan="1" rowspan="1">0.0000596ab</td>
                            <td colspan="1" rowspan="1">0.051249</td>
                            <td colspan="1" rowspan="1">0.031933ab</td>
                            <td colspan="1" rowspan="1">0.000194ab</td>
                            <td colspan="1" rowspan="1">0.00000004ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JAN</td>
                            <td colspan="1" rowspan="1">0.006283ab</td>
                            <td colspan="1" rowspan="1">0.00000487ab</td>
                            <td colspan="1" rowspan="1">0.144604</td>
                            <td colspan="1" rowspan="1">0.001808ab</td>
                            <td colspan="1" rowspan="1">0.013683ab</td>
                            <td colspan="1" rowspan="1">0.00000004ab</td>
                            <td colspan="1" rowspan="1">0.003687ab</td>
                            <td colspan="1" rowspan="1">0.0000157ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">FEB</td>
                            <td colspan="1" rowspan="1">0.005026ab</td>
                            <td colspan="1" rowspan="1">0.0000412ab</td>
                            <td colspan="1" rowspan="1">0.40357</td>
                            <td colspan="1" rowspan="1">0.0000306ab</td>
                            <td colspan="1" rowspan="1">0.280835</td>
                            <td colspan="1" rowspan="1">0.00000016ab</td>
                            <td colspan="1" rowspan="1">0.24263</td>
                            <td colspan="1" rowspan="1">0.00000323ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MARCH</td>
                            <td colspan="1" rowspan="1">0.000102ab</td>
                            <td colspan="1" rowspan="1">0.00000367ab</td>
                            <td colspan="1" rowspan="1">0.411553</td>
                            <td colspan="1" rowspan="1">0.000126ab</td>
                            <td colspan="1" rowspan="1">0.345353</td>
                            <td colspan="1" rowspan="1">0.0000001ab</td>
                            <td colspan="1" rowspan="1">0.0000107ab</td>
                            <td colspan="1" rowspan="1">0.00000033ab</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="ST2" orientation="portrait" position="anchor">
                <label>Supplementary Table 2. </label>
                <caption>
                    <title>The individual P values (both significant and non-significant) determined by the one way ANOVA test for all the soil nutrients studied at 5&#x2013;10 cm soil depths in each sampling month.</title>
                    <p>The significant P values are followed by the letters (ab) on the right.</p>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1">Months</th>
                            <th align="left" colspan="1" rowspan="1">SOC %</th>
                            <th align="left" colspan="1" rowspan="1">NH
                                <sub>4</sub>
                                <sup>+</sup>&#x2212;N</th>
                            <th align="left" colspan="1" rowspan="1">Available P</th>
                            <th align="left" colspan="1" rowspan="1">Available K</th>
                            <th align="left" colspan="1" rowspan="1">Available Fe</th>
                            <th align="left" colspan="1" rowspan="1">Available Cu</th>
                            <th align="left" colspan="1" rowspan="1">Available Mn</th>
                            <th align="left" colspan="1" rowspan="1">Available Zn</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td colspan="1" rowspan="1">APRIL</td>
                            <td colspan="1" rowspan="1">0.0000668ab</td>
                            <td colspan="1" rowspan="1">0.00000646ab</td>
                            <td colspan="1" rowspan="1">0.001899ab</td>
                            <td colspan="1" rowspan="1">0.000556ab</td>
                            <td colspan="1" rowspan="1">0.000462ab</td>
                            <td colspan="1" rowspan="1">0.008833ab</td>
                            <td colspan="1" rowspan="1">0.0000248ab</td>
                            <td colspan="1" rowspan="1">0.09716</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MAY</td>
                            <td colspan="1" rowspan="1">0.0000001ab</td>
                            <td colspan="1" rowspan="1">0.00000019ab</td>
                            <td colspan="1" rowspan="1">0.002151ab</td>
                            <td colspan="1" rowspan="1">0.000418ab</td>
                            <td colspan="1" rowspan="1">0.000846ab</td>
                            <td colspan="1" rowspan="1">0.00000119ab</td>
                            <td colspan="1" rowspan="1">0.00000001ab</td>
                            <td colspan="1" rowspan="1">0.000363ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JUNE</td>
                            <td colspan="1" rowspan="1">0.00000401ab</td>
                            <td colspan="1" rowspan="1">0.00000065ab</td>
                            <td colspan="1" rowspan="1">0.009753ab</td>
                            <td colspan="1" rowspan="1">0.0000491ab</td>
                            <td colspan="1" rowspan="1">0.007329ab</td>
                            <td colspan="1" rowspan="1">0.003581ab</td>
                            <td colspan="1" rowspan="1">0.0000273ab</td>
                            <td colspan="1" rowspan="1">0.113956</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JULY</td>
                            <td colspan="1" rowspan="1">0.00000187ab</td>
                            <td colspan="1" rowspan="1">0.00000209ab</td>
                            <td colspan="1" rowspan="1">0.10013</td>
                            <td colspan="1" rowspan="1">0.000231ab</td>
                            <td colspan="1" rowspan="1">0.0000721ab</td>
                            <td colspan="1" rowspan="1">0.000608ab</td>
                            <td colspan="1" rowspan="1">0.000925ab</td>
                            <td colspan="1" rowspan="1">0.000433ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">AUG</td>
                            <td colspan="1" rowspan="1">0.00000066ab</td>
                            <td colspan="1" rowspan="1">0.0000194ab</td>
                            <td colspan="1" rowspan="1">0.00312ab</td>
                            <td colspan="1" rowspan="1">0.000937ab</td>
                            <td colspan="1" rowspan="1">0.0000302ab</td>
                            <td colspan="1" rowspan="1">0.000108ab</td>
                            <td colspan="1" rowspan="1">0.0000412ab</td>
                            <td colspan="1" rowspan="1">0.000161ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">SEPT</td>
                            <td colspan="1" rowspan="1">0.0000584ab</td>
                            <td colspan="1" rowspan="1">0.00000082ab</td>
                            <td colspan="1" rowspan="1">0.015419ab</td>
                            <td colspan="1" rowspan="1">0.000561ab</td>
                            <td colspan="1" rowspan="1">0.04445ab</td>
                            <td colspan="1" rowspan="1">0.00000059ab</td>
                            <td colspan="1" rowspan="1">0.0000775ab</td>
                            <td colspan="1" rowspan="1">0.03002ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">OCT</td>
                            <td colspan="1" rowspan="1">0.00000279ab</td>
                            <td colspan="1" rowspan="1">0.0000083ab</td>
                            <td colspan="1" rowspan="1">0.002957ab</td>
                            <td colspan="1" rowspan="1">0.00000804ab</td>
                            <td colspan="1" rowspan="1">0.010212ab</td>
                            <td colspan="1" rowspan="1">0.0000984ab</td>
                            <td colspan="1" rowspan="1">0.000168ab</td>
                            <td colspan="1" rowspan="1">0.445416</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">NOV</td>
                            <td colspan="1" rowspan="1">0.00000083ab</td>
                            <td colspan="1" rowspan="1">0.00000426ab</td>
                            <td colspan="1" rowspan="1">0.002128ab</td>
                            <td colspan="1" rowspan="1">0.0000177ab</td>
                            <td colspan="1" rowspan="1">0.018233ab</td>
                            <td colspan="1" rowspan="1">0.00000043ab</td>
                            <td colspan="1" rowspan="1">0.001414ab</td>
                            <td colspan="1" rowspan="1">0.398956</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">DEC</td>
                            <td colspan="1" rowspan="1">0.0000233ab</td>
                            <td colspan="1" rowspan="1">0.0000033ab</td>
                            <td colspan="1" rowspan="1">0.071242</td>
                            <td colspan="1" rowspan="1">0.000434ab</td>
                            <td colspan="1" rowspan="1">0.754006</td>
                            <td colspan="1" rowspan="1">0.00000425ab</td>
                            <td colspan="1" rowspan="1">0.887478</td>
                            <td colspan="1" rowspan="1">0.000595ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JAN</td>
                            <td colspan="1" rowspan="1">0.00000961ab</td>
                            <td colspan="1" rowspan="1">0.00000112ab</td>
                            <td colspan="1" rowspan="1">0.911763</td>
                            <td colspan="1" rowspan="1">0.00061ab</td>
                            <td colspan="1" rowspan="1">0.0000144ab</td>
                            <td colspan="1" rowspan="1">0.0000008ab</td>
                            <td colspan="1" rowspan="1">0.330956</td>
                            <td colspan="1" rowspan="1">0.022487ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">FEB</td>
                            <td colspan="1" rowspan="1">0.0000296ab</td>
                            <td colspan="1" rowspan="1">0.00000233ab</td>
                            <td colspan="1" rowspan="1">0.32646</td>
                            <td colspan="1" rowspan="1">0.000356ab</td>
                            <td colspan="1" rowspan="1">0.422327</td>
                            <td colspan="1" rowspan="1">0.00000001ab</td>
                            <td colspan="1" rowspan="1">0.001609ab</td>
                            <td colspan="1" rowspan="1">0.001269ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MARCH</td>
                            <td colspan="1" rowspan="1">0.00000301ab</td>
                            <td colspan="1" rowspan="1">0.00000169ab</td>
                            <td colspan="1" rowspan="1">0.839951</td>
                            <td colspan="1" rowspan="1">0.0000777ab</td>
                            <td colspan="1" rowspan="1">0.011502ab</td>
                            <td colspan="1" rowspan="1">0.00000003ab</td>
                            <td colspan="1" rowspan="1">0.01477ab</td>
                            <td colspan="1" rowspan="1">1</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="ST3" orientation="portrait" position="anchor">
                <label>Supplementary Table 3. </label>
                <caption>
                    <title>The individual P values (both significant and non-significant) determined by the one way ANOVA test for all the soil nutrients studied at 10&#x2013;15 cm soil depths in each sampling month.</title>
                    <p>The significant P values are followed by the letters (ab) on the right.</p>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1">Months</th>
                            <th align="left" colspan="1" rowspan="1">SOC %</th>
                            <th align="left" colspan="1" rowspan="1">NH
                                <sub>4</sub>
                                <sup>+</sup>&#x2212;N</th>
                            <th align="left" colspan="1" rowspan="1">Available P</th>
                            <th align="left" colspan="1" rowspan="1">Available K</th>
                            <th align="left" colspan="1" rowspan="1">Available Fe</th>
                            <th align="left" colspan="1" rowspan="1">Available Cu</th>
                            <th align="left" colspan="1" rowspan="1">Available Mn</th>
                            <th align="left" colspan="1" rowspan="1">Available Zn</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td colspan="1" rowspan="1">APRIL</td>
                            <td colspan="1" rowspan="1">0.00000108ab</td>
                            <td colspan="1" rowspan="1">0.00000581ab</td>
                            <td colspan="1" rowspan="1">0.004729ab</td>
                            <td colspan="1" rowspan="1">0.059703ab</td>
                            <td colspan="1" rowspan="1">0.00012ab</td>
                            <td colspan="1" rowspan="1">0.00000053ab</td>
                            <td colspan="1" rowspan="1">0.058366</td>
                            <td colspan="1" rowspan="1">0.000401ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MAY</td>
                            <td colspan="1" rowspan="1">0.00000021ab</td>
                            <td colspan="1" rowspan="1">0.00000249ab</td>
                            <td colspan="1" rowspan="1">0.036467ab</td>
                            <td colspan="1" rowspan="1">0.008756ab</td>
                            <td colspan="1" rowspan="1">0.012965ab</td>
                            <td colspan="1" rowspan="1">0.00000016ab</td>
                            <td colspan="1" rowspan="1">0.0000159ab</td>
                            <td colspan="1" rowspan="1">0.001884ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JUNE</td>
                            <td colspan="1" rowspan="1">0.012776ab</td>
                            <td colspan="1" rowspan="1">0.00000176ab</td>
                            <td colspan="1" rowspan="1">0.146323</td>
                            <td colspan="1" rowspan="1">0.010478ab</td>
                            <td colspan="1" rowspan="1">0.388751</td>
                            <td colspan="1" rowspan="1">0.00011ab</td>
                            <td colspan="1" rowspan="1">0.0000002ab</td>
                            <td colspan="1" rowspan="1">0.670412</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JULY</td>
                            <td colspan="1" rowspan="1">0.020453ab</td>
                            <td colspan="1" rowspan="1">0.00000173ab</td>
                            <td colspan="1" rowspan="1">0.100267</td>
                            <td colspan="1" rowspan="1">0.000127ab</td>
                            <td colspan="1" rowspan="1">0.226362</td>
                            <td colspan="1" rowspan="1">0.030766ab</td>
                            <td colspan="1" rowspan="1">0.002672ab</td>
                            <td colspan="1" rowspan="1">0.112669</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">AUG</td>
                            <td colspan="1" rowspan="1">0.00000326ab</td>
                            <td colspan="1" rowspan="1">0.00000336ab</td>
                            <td colspan="1" rowspan="1">0.001433ab</td>
                            <td colspan="1" rowspan="1">0.0000612ab</td>
                            <td colspan="1" rowspan="1">0.046472ab</td>
                            <td colspan="1" rowspan="1">0.002253ab</td>
                            <td colspan="1" rowspan="1">0.000118ab</td>
                            <td colspan="1" rowspan="1">0.467994</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">SEPT</td>
                            <td colspan="1" rowspan="1">0.00000086ab</td>
                            <td colspan="1" rowspan="1">0.00000688ab</td>
                            <td colspan="1" rowspan="1">0.001989ab</td>
                            <td colspan="1" rowspan="1">0.0000153ab</td>
                            <td colspan="1" rowspan="1">0.03155ab</td>
                            <td colspan="1" rowspan="1">0.000379ab</td>
                            <td colspan="1" rowspan="1">0.00132ab</td>
                            <td colspan="1" rowspan="1">0.0000651ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">OCT</td>
                            <td colspan="1" rowspan="1">0.0000421ab</td>
                            <td colspan="1" rowspan="1">0.00000645ab</td>
                            <td colspan="1" rowspan="1">0.00128ab</td>
                            <td colspan="1" rowspan="1">0.000469ab</td>
                            <td colspan="1" rowspan="1">0.000522ab</td>
                            <td colspan="1" rowspan="1">0.0000123ab</td>
                            <td colspan="1" rowspan="1">0.0000891ab</td>
                            <td colspan="1" rowspan="1">0.199622</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">NOV</td>
                            <td colspan="1" rowspan="1">0.000233ab</td>
                            <td colspan="1" rowspan="1">0.000394ab</td>
                            <td colspan="1" rowspan="1">0.002893ab</td>
                            <td colspan="1" rowspan="1">0.000152ab</td>
                            <td colspan="1" rowspan="1">0.001832ab</td>
                            <td colspan="1" rowspan="1">0.906289</td>
                            <td colspan="1" rowspan="1">0.000154ab</td>
                            <td colspan="1" rowspan="1">0.50188</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">DEC</td>
                            <td colspan="1" rowspan="1">0.00000268ab</td>
                            <td colspan="1" rowspan="1">0.0000273ab</td>
                            <td colspan="1" rowspan="1">0.536106</td>
                            <td colspan="1" rowspan="1">0.001558ab</td>
                            <td colspan="1" rowspan="1">0.003051ab</td>
                            <td colspan="1" rowspan="1">0.00000943ab</td>
                            <td colspan="1" rowspan="1">0.122436</td>
                            <td colspan="1" rowspan="1">0.016703ab</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">JAN</td>
                            <td colspan="1" rowspan="1">0.000001ab</td>
                            <td colspan="1" rowspan="1">0.0000366ab</td>
                            <td colspan="1" rowspan="1">0.217319</td>
                            <td colspan="1" rowspan="1">0.0000711ab</td>
                            <td colspan="1" rowspan="1">0.008413ab</td>
                            <td colspan="1" rowspan="1">0.0000444ab</td>
                            <td colspan="1" rowspan="1">0.582289</td>
                            <td colspan="1" rowspan="1">0.536963</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">FEB</td>
                            <td colspan="1" rowspan="1">0.000227ab</td>
                            <td colspan="1" rowspan="1">0.0000316ab</td>
                            <td colspan="1" rowspan="1">0.2242323</td>
                            <td colspan="1" rowspan="1">0.0000375ab</td>
                            <td colspan="1" rowspan="1">0.476041</td>
                            <td colspan="1" rowspan="1">0.00000005ab</td>
                            <td colspan="1" rowspan="1">0.291113</td>
                            <td colspan="1" rowspan="1">0.570456</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1">MARCH</td>
                            <td colspan="1" rowspan="1">0.00000031ab</td>
                            <td colspan="1" rowspan="1">0.00000499ab</td>
                            <td colspan="1" rowspan="1">0.429647</td>
                            <td colspan="1" rowspan="1">0.002118ab</td>
                            <td colspan="1" rowspan="1">0.306916</td>
                            <td colspan="1" rowspan="1">0.00000173ab</td>
                            <td colspan="1" rowspan="1">0.000455ab</td>
                            <td colspan="1" rowspan="1">0.207031</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
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    <sub-article article-type="reviewer-report" id="report39546">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.3273.r39546</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Lu</surname>
                        <given-names>Xiankai</given-names>
                    </name>
                    <xref ref-type="aff" rid="r39546a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r39546a1">
                    <label>1</label>South China Botanical Garden, Chinese Academy of Sciences (CAS), Guangzhou, China</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>12</day>
                <month>11</month>
                <year>2018</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2018 Lu X</copyright-statement>
                <copyright-year>2018</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport39546" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.3-30.v1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The authors addressed post-fire nutrient availability in a subtropical forest. They found that the forest wildfire resulted in a significant loss of most soil nutrients. Throughout the whole manuscript, however, the authors mainly described the results rather than mechanisms. In fact, there was lack of direct evidence to explain their findings. They pointed out that very few studies have evaluated post-fire effects on soil micro-nutrients, but did not show why they did this work. "very few" may mean that this work is not important, or it has been very clear. Hence, the major concerns are related to the novelty and the mechanism explanations.</p>
            <p> </p>
            <p> Others: 
                <list list-type="order">
                    <list-item>
                        <p>I am a little curious that the abstract mainly described the results without conclusion.</p>
                    </list-item>
                    <list-item>
                        <p>In the "site description", 3.99 mm for mean annual precipitation?</p>
                    </list-item>
                    <list-item>
                        <p>Table 1, please show the sampling time, and better to unify the unit (e.g. N and P).</p>
                    </list-item>
                    <list-item>
                        <p>The authors mentioned element contents (such as SOC),the term "content" means stock. So it is better to show the responses of total soil nutrient stocks to fire for the whole soil layers.</p>
                    </list-item>
                    <list-item>
                        <p>Repeated-measure ANOVA can be used to examine the overall fire effects on soil nutrient dynamics over the study period.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>No</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>No</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>NA</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
    </sub-article>
</article>
