<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">JGIS</journal-id><journal-title-group><journal-title>Journal of Geographic Information System</journal-title></journal-title-group><issn pub-type="epub">2151-1950</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/jgis.2023.152013</article-id><article-id pub-id-type="publisher-id">JGIS-124409</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  An Assessment and Geostatistics of Land-Use and Selected Physico-Chemical Properties of Soils in the Mount Cameroon Area
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nchia</surname><given-names>Peter Ghong</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ngwa</surname><given-names>Martin Ngwabie</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Godswill</surname><given-names>Azinwie Asongwe</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Arnold</surname><given-names>Chi Kedia</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Cheo</surname><given-names>Emmanuel Suh</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib></contrib-group><aff id="aff4"><addr-line>Department of Geology, Faculty of Science, University of Bamenda, Bambili, North West Region, Cameroon</addr-line></aff><aff id="aff1"><addr-line>Department of Agriculture and Environmental Engineering, College of Technology, University of Bamenda, Bambili, North West Region, Cameroon</addr-line></aff><aff id="aff2"><addr-line>Department of Environmental Science, University of Buea, Buea, South West Region, Cameroon</addr-line></aff><aff id="aff3"><addr-line>School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA</addr-line></aff><pub-date pub-type="epub"><day>31</day><month>03</month><year>2023</year></pub-date><volume>15</volume><issue>02</issue><fpage>244</fpage><lpage>266</lpage><history><date date-type="received"><day>27,</day>	<month>January</month>	<year>2023</year></date><date date-type="rev-recd"><day>18,</day>	<month>April</month>	<year>2023</year>	</date><date date-type="accepted"><day>21,</day>	<month>April</month>	<year>2023</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  This work investigated the land-use/land-cover and some physico-chemical properties of the soils of Mt Cameroon and presented same in maps. ArcGIS Pro mapping software, Landsat images, Global Positioning Systems (GPS) coordinates collected from the field combined with updated shape files from competent services were used to produce the location and land-use/land-cover maps. Sixteen topsoil samples (0 - 20 cm) were collected, 4 from each land use/cover category: farmland, forest, plantation and settlement, and analysed for soil pH, cation exchange capacity (CEC), bulk density, moisture content and soil texture, in the laboratory using standard analytical procedures. This data was used to produce spatial distribution maps using ordinary kriging, in ArcGIS Pro. The main terrestrial land use/cover categories comprised of the forest (mangrove, lowland, montane and sub-montane), agroforestry, plantations, grassland, settlement, cropland, shrubby savannah, and bare lava. Bulk density showed the highest values in settlement areas and least values under forest land-use categories. Soil moisture content exhibited a reverse trend compared to that of soil bulk density. Forest soils were the sandiest while soils in plantation agricultural land were the most clayey. The soils were slightly acidic to neutral with soils from agricultural land being more acidic (pH
  <sub>(water)</sub> = 5.43). It is discernible from the results that the conversion from forest to other land use/cover classes enhances soil degradation and that soil physico-chemical properties adequately serve as indicators of soil quality in the Mt Cameroon area.
 
</p></abstract><kwd-group><kwd>Geographic Information Systems</kwd><kwd> Geostatistics</kwd><kwd> Land-Use</kwd><kwd> Mt Cameroon</kwd><kwd> Soil Quality</kwd><kwd> Thematic Maps</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The presentation of scientific findings in forms that facilitate comprehension by non-specialists is central for the sustainable management of environmental resources and by extension, the accruing benefits to mankind. The combined use of GIS tools and related technology for the visualization of data has proven to be a reliable approach for the utilization, management, and monitoring of environmental resources [<xref ref-type="bibr" rid="scirp.124409-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref3">3</xref>] .</p><p>Human interactions with the environment impact on the dynamics and functioning of ecosystems [<xref ref-type="bibr" rid="scirp.124409-ref4">4</xref>] . The management or exploitation of soil resources, for instance, may affect soil physical, chemical and biological properties and could result in a change of the land-use/land-cover (LULC) class [<xref ref-type="bibr" rid="scirp.124409-ref5">5</xref>] . LULC change, on the other hand, could lead to the alteration of soil properties [<xref ref-type="bibr" rid="scirp.124409-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref7">7</xref>] . The sustainable use of soils and other natural resources, to maximize the benefits of their ecological services to man, remains a major challenge [<xref ref-type="bibr" rid="scirp.124409-ref8">8</xref>] . Monitoring and sporadic assessment of resource characteristics are primordial for sustainability [<xref ref-type="bibr" rid="scirp.124409-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref10">10</xref>] .</p><p>A change in soil properties affects processes that take place in the soils and could compromise the productivity of the land. Soil physical properties play a decisive role in the capture, retention and transmission of water; aeration and gaseous exchange; effective rooting depth; soil heat capacity and the temperature regime [<xref ref-type="bibr" rid="scirp.124409-ref11">11</xref>] . A disruption in soil chemistry is a big threat to soil quality, productivity, as well as environmental protection; plant, animal and human health [<xref ref-type="bibr" rid="scirp.124409-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref13">13</xref>] . Management practices that preserve or enhance soil physical and chemical properties are, therefore, essential for the sustenance of environmental quality, safeguarding of biodiversity and promoting human wellbeing [<xref ref-type="bibr" rid="scirp.124409-ref14">14</xref>] . In view of these functions and challenges, land managers need information that allows them to make rational decisions.</p><p>Another challenge related to research in soil science is that data is often available on representative samples (points or lines) especially for difficult terrains and extensive study areas, but decisions are expected to be made regarding the entire land mass. Rational and far-reaching management decisions expected to enhance sustainability, require spatially continuous data. To generate such information from point or linear data calls for the use of methods that can make predictions on information at unsampled locations, using the available data. Several studies have projected geostatistics as a possible bridge between hard intermittent data obtained in the field and the continuous data required to ease scientific interpretations and the making of decisions by managers and policy makers [<xref ref-type="bibr" rid="scirp.124409-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref16">16</xref>] . Burrough [<xref ref-type="bibr" rid="scirp.124409-ref1">1</xref>] demonstrated that GIS, statistics and geostatistics were essential and complimentary partners in the capturing, storage, retrieval, digitization, analysis, and display of spatial data. The interpolation results can be rendered even much easier for visual interpretation and re-evaluation by environmental managers, by importing them on to the digital elevation model (DEM) of the study area [<xref ref-type="bibr" rid="scirp.124409-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref18">18</xref>] .</p><p>The investigation of land-use and soil physicochemical properties has been the subject of numerous research projects, elsewhere. Studies on LULC changes and their relatedness to soil quality characteristics have been carried out at different scales in space and time [<xref ref-type="bibr" rid="scirp.124409-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref23">23</xref>] . Soil physicochemical characteristics have also been extensively investigated. Fetene and Amera [<xref ref-type="bibr" rid="scirp.124409-ref24">24</xref>] , for instance, found that sand and clay particle fractions, bulk density and soil porosity were significantly affected by land-use; while Moges, Dagnachew [<xref ref-type="bibr" rid="scirp.124409-ref10">10</xref>] reported that all soil textural fractions exhibited significant variations for different land-use classes; and Shaver, Peterson [<xref ref-type="bibr" rid="scirp.124409-ref25">25</xref>] and Agbede, Ojeniyi [<xref ref-type="bibr" rid="scirp.124409-ref26">26</xref>] reported significant improvement of soil physical properties following the addition of crop residues and poultry manure respectively. Barzegar, Yousefi [<xref ref-type="bibr" rid="scirp.124409-ref27">27</xref>] reported a negative correlation between bulk density and the rate of application of organic matter to soil; and a positive correlation between the amounts of organic matter added to the soil and soil water content.</p><p>The veracity and dependence of results of studies on the interactions between LULC and soil parameters have been established elsewhere but such studies are rare for the study area. Mount Cameroon is a biodiversity hotspot harbouring a protected area, the Mount Cameroon National Park, with a host of other features of importance and activities on its foot slopes. It is commonly described as Cameroon in miniature, comprising of land-use/land cover classes characteristic of the different ecological zones of Cameroon. The fertile lands attract huge agricultural activities; both (industrialized) plantation and peasant agriculture, as well as a rapidly growing population that leads to the expansion of settlement area. The Mountain is an active volcano where materials are constantly added to the surface, thereby modifying the soils. The type of human activities in the area and their trends points to imminent land degradation if the situation is not adequately managed. It is within the context of the fact that the availability of scientific information in easily exploitable formats is a necessary condition for rational, sound and well-informed decision making, that this study sets out to investigate the land-use, soil physical properties, acidity, the cation exchange capacity in the area and to present same geospatially, in the form of maps which can easily be exploited by policy makers.</p></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Description of Study Area</title><p>Mount Cameroon, a stratovolcano, is part of the Cameroon Volcanic Line (CVL) (<xref ref-type="fig" rid="fig1">Figure 1</xref>). The peak of the mountain (~4100 m) is approximately 25 km inland from the coastline. The base of the massif, approximately elliptical in shape,</p><p>is estimated to extend between 4˚00' - 4˚28'N and 9˚00' - 9˚30'E. It is an active volcano, with a record of eight eruptions in the 20<sup>th</sup> Century [<xref ref-type="bibr" rid="scirp.124409-ref28">28</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref29">29</xref>] . The study was carried out on the southern slopes of Mt Cameroon (<xref ref-type="fig" rid="fig2">Figure 2</xref>).</p><p>The combined effect of the height of the mountain, its proximity to the Atlantic Ocean, and positions of the various spots relative to the South-westerly and Northeasterly winds, during different periods of the year instil slight changes in the microclimate of the area. For instance, West Coast, in the south west area of the Mountain has abundance of rainfall with a mean annual of c. 9000 mm at Debundscha but Buea has much less, c. 5000 mm, annual mean rainfall. To minimize the disparity in climatic conditions, the study was limited to the southern part and lower flanks of the mountain. The variations of climatic patterns around the Mountain notwithstanding, the Mt Cameroon area, generally speaking, has a tropical seasonal climate with a short dry season (December to February) and a longer rainy season (March to November). The mean annual temperature at sea level is 27˚C and about 0˚C at the summit while the relative humidity, however, remains relatively high c. 75% - 80% (at sea level) [<xref ref-type="bibr" rid="scirp.124409-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref31">31</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref32">32</xref>] .</p></sec><sec id="s2_2"><title>2.2. Parent Material and Soils of the Study Area</title><p>The rocks of Mt Cameroon have been variously described as products of different volcanic events but geochemically similar; comprising of basalts, basanites and hawaiites; and are reportedly covered in some areas by subsidiary fall-out tephra deposits [<xref ref-type="bibr" rid="scirp.124409-ref28">28</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref34">34</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref35">35</xref>] . Like the soil parent material, the soils of the area are of varying ages, accounting for the contrasting weathering degrees. The soils in the upper slopes of the mountain, formed from lava flows, deposits of pyroclastics and volcanic ash have been described to be well drained. Soil profiles range from being very shallow and stony on basaltic ridge crests, with parent material at times exposed on the surface, to deep and sometimes stone-free soil on more gently sloping depressions. At the lower parts of the mountain, the soils are an admixture of relict primary material, secondary minerals from heavily weathered lava and scoriaceous material, and alluvium. The soil thickness on the plains at the foot of Mt Cameroon runs up to c. 10 m in some places [<xref ref-type="bibr" rid="scirp.124409-ref31">31</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref36">36</xref>] .</p><p>Payton [<xref ref-type="bibr" rid="scirp.124409-ref37">37</xref>] describes the soils around Mount Cameroon as being varieties of Andosols, derived from alkaline basaltic material. Hasselo [<xref ref-type="bibr" rid="scirp.124409-ref36">36</xref>] identified volcanic and alluvial as the two sources of the parent material of the soils. The volcanic soils are said to be either products of the weathering of basement rocks (lava flows), the direct deposition of aeolian volcanic ash, the deposition of mudflows (comprising of volcanic ash and other loose material in valleys and low-lying plains) washed down from the slopes, or a combination of these. Patches of alluvial soils considered to be of marine origin and believed to have been deposited at high sea levels are also reported in the low lying land below the 100 m contour line [<xref ref-type="bibr" rid="scirp.124409-ref36">36</xref>] . The soil colour reflects the age, degree of laterization and organic matter content. For the mineral soils on the upper slopes of the area, the younger soils are generally darker and get more reddish with age and degree of weathering [<xref ref-type="bibr" rid="scirp.124409-ref37">37</xref>] .</p></sec><sec id="s2_3"><title>2.3. Collection of Soil Samples, Processing, Data Analysis and Map Production</title><p>Desk work before sample collection comprised of using Landsat and Google Earth images to have an overview of the LULC pattern and the pre-selection of areas to be sampled. A provisional LULC map was produced and used in the extensive field work that followed. Land-use categories were identified, and GPS coordinates recorded for “ground truthing”. This information, combined with updated shape files from the Cameroonian Ministry of Scientific Research and Innovation and the Ministry of Forestry and Wild Life, respectively were used in the production of the location map and the current LULC map of the study area. In May 2021, during the on-set of the rainy season, four composite soil samples were collected from each of the 4 major LULC classes—farmland, forest, plantation agriculture and settlement. Following, are the characteristics of the LULC categories.</p><p>- Farmland: characterized by the cultivation at small holder scale and mix cropping with the major crops being cassava, cocoyam, plantain, maize, egusi and vegetables.</p><p>- Forest: the equatorial rainforest and montane forests, of more than 0.5 hectares, with a tree canopy cover of more than 10 percent, which are not primarily under agricultural or urban land uses [<xref ref-type="bibr" rid="scirp.124409-ref38">38</xref>] .</p><p>- Plantation: mono-cropping at industrial scales (of either banana, tea, oil palm or rubber).</p><p>- Settlement: the built-up area with a high intensity of engineering activities, sometimes characterized by the removal or transported top soil.</p><p>Specifically, the samples for the commercial agricultural plantations were collected one each from tea, oil palm, rubber, and banana plantations; and those for the settlement land-use class were collected from around major road junctions in built-up areas. For each sample site, 2 sets of samples were collected. One set was used for the determination of bulk density and moisture content and the other set was used for the determination of soil separates, soil pH and CEC. The latter set of samples was collected using a randomized complete block research design. For each preselected sample site, representative plots of 10 m &#215; 10 m were mapped out. After clearing the debris, top soil (0 - 20 cm) samples were collected from the four corners of the plot and the centre and bulked together to form a composite sample which was later air-dried and sieved to obtain the ≤2 mm faction. The set of samples for the determination of bulk density and moisture content were collected using a metal cylinder (6 cm diameter and 6 cm height) within the plot. After clearing the debris, the metallic cylinder was carefully driven into the ground as to fill the entire cylinder without compressing the soil in it. The soil around the cylinder was excavated and the cylinder with the core in place was carefully removed by sliding a trowel under it. The mass of the core (wet soil) was determined in the field and parcelled in plastic papers, for oven drying in the laboratory.</p><p>In the laboratory, samples for the determination of bulk density and moisture content were oven dried at 105˚C to constant weight and weighed. Bulk density was determined as per Hao, Ball [<xref ref-type="bibr" rid="scirp.124409-ref39">39</xref>] and moisture content determined using the procedure described by Clarke Topp, Parkin [<xref ref-type="bibr" rid="scirp.124409-ref40">40</xref>] . With the other set of samples, particle size analysis was carried out using the hydrometer method as outlined by Kroetsch and Wang [<xref ref-type="bibr" rid="scirp.124409-ref41">41</xref>] . Soil textural classes were determined using the designation of the United State Department of Agriculture (USDA). The soil samples were also analyzed for pH and CEC. Soil pH was determined in both water (pH<sub>(</sub><sub>water)</sub>) and KCl (pH<sub>(KCl)</sub>) [<xref ref-type="bibr" rid="scirp.124409-ref42">42</xref>] using a glass electrode Thermo-Russel pH meter and CEC was determined using the 1N ammonium acetate (NH<sub>4</sub>OAc), pH 7.0 method extraction [<xref ref-type="bibr" rid="scirp.124409-ref43">43</xref>] .</p><p>The digital elevation model (DEM) was obtained from the website of the United States Geological Survey (USGS, https://earthexplorer.usgs.gov/). The DEM, complemented by data from the fieldwork of the researchers was used in the production of maps. These data and images were processed using ArcGIS Pro 2.7.2 and WGS 84/UTM Zone 32N was used to harmonize the data. The spatial distribution maps of the selected soil physico-chemical properties were produced using ordinary kriging interpolation [<xref ref-type="bibr" rid="scirp.124409-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref3">3</xref>] .</p></sec></sec><sec id="s3"><title>3. Results and Discussions</title><sec id="s3_1"><title>3.1. Land-Use/Land-Cover Distribution</title><p>The spatial patterns and magnitudes of the LULC classes of the study area are shown in <xref ref-type="fig" rid="fig3">Figure 3</xref> and <xref ref-type="fig" rid="fig4">Figure 4</xref>, respectively. Thirteen LULC classes were identified and classified. These included: agroforestry mosaic (24.27%), mangrove (13.41%), lowland forest (&lt;900 m) (10.31%), sub-mountain forest (&gt;900 - &lt;1.500 m) (9.69%), orchard or plantation forest (8.60), palm plantation (7.63%), grassland (7.07%), mountain forest (&gt;1.500 m) (5.57%), settlement (4.56%), water (2.96%), elephant bush (1.77%), shrubby savanna (1.68%), bare lava fields (1.37%) and cropland/bare soil (1.03%). Working on the entire Mount Cameroon area, Maschler [<xref ref-type="bibr" rid="scirp.124409-ref19">19</xref>] identified and classified similar LULC classes, namely: montane forest, sub-montane forest, shrubby savannah, agroforestry mosaic, open agroforestry mosaic, palm plantation, tree plantation, banana plantation, tea plantation, grassland/bare soil, grassland savannah/lava and settlement. The LULC classes of the study are, therefore, reminiscent of those of the entire Mt Cameroon area. The differences in the identified and classified categories in the two studies might have arisen from subjectivity in interpretation, inexplicit definition of thematic classes, inaccuracies in reference samples, the edge pixels effect and geolocation errors [<xref ref-type="bibr" rid="scirp.124409-ref44">44</xref>] .</p><p>The water LULC category comprised of the Atlantic Ocean plus the rivers and streams in the area. Mangroves were found along the shore mostly at estuaries. The lowland comprised mostly of the following LULC categories: lowland forest (&lt;900 m asl), plantations and orchards (&lt;900 m above sea level (asl)) and settlement (&lt;1200 m asl). The other categories were predominantly within the following corresponding ranges of attitude: sub-montane forest (&gt;900 - &lt;1500 m asl), cropland and agroforestry (&lt;1500 m asl), montane forest (~1500 - 1900 m asl), elephant bush (intersperse within lowland, sub-montane forests and montane forest), shrubby savanna (~900 - 2700 m asl), savanna (~2000 - 3500 m asl) and bare lava fields (at around the summit and along lava outcrops of previous eruption events, down to about 100 m asl at Bakingili).</p><p>These results revealed that the Mt Cameroon region is Cameroon in miniature; having LULC categories that are typical of the agro-ecological zones of the country. These range from the mono-modal rainforest zone, through the bimodal rainforest zone, highland zone, guinea savanna to the sudano-sahelian zone [<xref ref-type="bibr" rid="scirp.124409-ref45">45</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref46">46</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref47">47</xref>] . The LULC distribution pattern approximately followed an attitudinal gradation. This is consistent with findings by Proctor, Edwards [<xref ref-type="bibr" rid="scirp.124409-ref31">31</xref>] and Hall [<xref ref-type="bibr" rid="scirp.124409-ref48">48</xref>] who reported that there exists a reduction in tree species richness with attitude and vegetation zonation, on Mt Cameroon, respectively. The variety in the LULC classes is the combined effect of the relief of the mountain (~4100 m asl) that orchestrates temperature variation with attitude and influences the effect of the Southwesterly and Northeasterly winds on different positions of the mountain in conjunction with its proximity to the Atlantic Ocean.</p><p>The fertile soils and abundance of rainfall in the study area have endowed it with varied forms of life. It has been variedly described as one of the richest biodiversity hot spots, having rare, endangered and endermic species [<xref ref-type="bibr" rid="scirp.124409-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref48">48</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref49">49</xref>] . These characteristics have encouraged agricultural activities for both subsistence and industrial purposes and has attracted high immigration into the area [<xref ref-type="bibr" rid="scirp.124409-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref50">50</xref>] with a corresponding negative impact on the forest cover. Fonge, Bechem [<xref ref-type="bibr" rid="scirp.124409-ref51">51</xref>] reported the yearly clearing of large expands of forest in favour of agricultural expansion, illegal logging, and the collection of fuel wood.</p><p>The distribution and expanse of LULC categories of an area have far-reaching implications, to different extends, on food security, the economy and ecology at local, regional, and global levels. They determine the type and quality of ecosystem services offered. Subsistence agriculture goes a long way to improve food security and the livelihood of rural communities and industrial agriculture increases employment and foreign exchange [<xref ref-type="bibr" rid="scirp.124409-ref22">22</xref>] . Vegetation, especially forest cover, serves as a carbon sink thereby attenuating the propensity of climate change and provide several other ecosystem services [<xref ref-type="bibr" rid="scirp.124409-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref52">52</xref>] . These benefits notwithstanding, certain LULC changes could jeopardize sustainable development through biodiversity loss, land degradation, change in micro-climate, decrease in crop yield, soil erosion and rural exodus [<xref ref-type="bibr" rid="scirp.124409-ref53">53</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref54">54</xref>] . To promote the conservation and judicious use of natural resources on Mt Cameroon, the government of Cameroon created a protected area, the Mt Cameroon National Park in 2009 [<xref ref-type="bibr" rid="scirp.124409-ref55">55</xref>] .</p></sec><sec id="s3_2"><title>3.2. Soil Physical Properties</title><p>The results of variation of the selected soil physical properties of the study area are summarized in <xref ref-type="table" rid="table1">Table 1</xref> and depicted in <xref ref-type="fig" rid="fig5">Figure 5</xref>. Soil bulk density ranged between 0.33 - 1.24 g/cm<sup>3</sup> with the highest densities registered in settlements with high human habitation followed by areas in plantations, farmland and least in forest areas. This is consistent with the findings of earlier similar studies. For instance, Fetene and Amera [<xref ref-type="bibr" rid="scirp.124409-ref24">24</xref>] reported higher bulk densities for grazing land, followed by cultivated land than for adjacent forest land. Chandel, Hadda [<xref ref-type="bibr" rid="scirp.124409-ref56">56</xref>] reported the following relationship for bulk density: bare &gt; horticulture &gt; grasses &gt; forest &gt; cultivated land. While Bizuhoraho, Kayiranga [<xref ref-type="bibr" rid="scirp.124409-ref57">57</xref>] and Moges, Dagnachew [<xref ref-type="bibr" rid="scirp.124409-ref10">10</xref>] did not find a significant difference in bulk density for the different land-use types they, however, reported a similar sequence in the variation of bulk density: cultivated &gt; farmland &gt; forest, and open grassland &gt; grazing land &gt; forest &gt; farmland, respectively.</p><p>Many studies have attributed the variation of soil bulk density with land-use type to differences in soil organic matter content, vegetal cover and the soil management history. Fetene and Amera [<xref ref-type="bibr" rid="scirp.124409-ref24">24</xref>] reported a negative significant correlation (r = −0.82, p &lt; 0.01) between bulk density and soil organic matter content. The authors equally reported higher values of soil organic matter in soils under forests than for cultivated land. Though soil organic matter was not investigated</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Summary of selected physical properties of soils of the southern slopes of Mt Cameroon</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >LULC</th><th align="center" valign="middle" >Quantity</th><th align="center" valign="middle" >Bulk density (g/cm<sup>3</sup>)</th><th align="center" valign="middle" >Moisture content (%)</th><th align="center" valign="middle" >Clay (%)</th><th align="center" valign="middle" >Silt (%)</th><th align="center" valign="middle" >Sand (%)</th></tr></thead><tr><td align="center" valign="middle"  rowspan="4"  >Farmland</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >18.53</td><td align="center" valign="middle" >4.60</td><td align="center" valign="middle" >12.00</td><td align="center" valign="middle" >59.40</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >0.88</td><td align="center" valign="middle" >39.86</td><td align="center" valign="middle" >7.60</td><td align="center" valign="middle" >35.00</td><td align="center" valign="middle" >83.40</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >0.64</td><td align="center" valign="middle" >30.91</td><td align="center" valign="middle" >5.85</td><td align="center" valign="middle" >21.75</td><td align="center" valign="middle" >72.40</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.17</td><td align="center" valign="middle" >9.32</td><td align="center" valign="middle" >1.26</td><td align="center" valign="middle" >9.64</td><td align="center" valign="middle" >9.87</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Forest</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >0.33</td><td align="center" valign="middle" >25.56</td><td align="center" valign="middle" >3.60</td><td align="center" valign="middle" >7.00</td><td align="center" valign="middle" >81.40</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >0.67</td><td align="center" valign="middle" >50.47</td><td align="center" valign="middle" >10.60</td><td align="center" valign="middle" >8.00</td><td align="center" valign="middle" >89.40</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >0.50</td><td align="center" valign="middle" >35.62</td><td align="center" valign="middle" >5.60</td><td align="center" valign="middle" >7.50</td><td align="center" valign="middle" >86.90</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.17</td><td align="center" valign="middle" >11.70</td><td align="center" valign="middle" >3.37</td><td align="center" valign="middle" >0.58</td><td align="center" valign="middle" >3.79</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Plantation</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >0.51</td><td align="center" valign="middle" >22.23</td><td align="center" valign="middle" >4.60</td><td align="center" valign="middle" >16.00</td><td align="center" valign="middle" >52.40</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >1.05</td><td align="center" valign="middle" >38.71</td><td align="center" valign="middle" >24.60</td><td align="center" valign="middle" >26.00</td><td align="center" valign="middle" >79.40</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >0.79</td><td align="center" valign="middle" >27.11</td><td align="center" valign="middle" >15.60</td><td align="center" valign="middle" >20.25</td><td align="center" valign="middle" >64.15</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.25</td><td align="center" valign="middle" >7.82</td><td align="center" valign="middle" >8.87</td><td align="center" valign="middle" >5.06</td><td align="center" valign="middle" >13.40</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Settlement</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >0.73</td><td align="center" valign="middle" >18.26</td><td align="center" valign="middle" >8.60</td><td align="center" valign="middle" >12.00</td><td align="center" valign="middle" >69.40</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >1.24</td><td align="center" valign="middle" >27.20</td><td align="center" valign="middle" >12.60</td><td align="center" valign="middle" >20.00</td><td align="center" valign="middle" >79.40</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >0.98</td><td align="center" valign="middle" >22.08</td><td align="center" valign="middle" >10.10</td><td align="center" valign="middle" >14.00</td><td align="center" valign="middle" >75.90</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.28</td><td align="center" valign="middle" >4.10</td><td align="center" valign="middle" >1.91</td><td align="center" valign="middle" >4.00</td><td align="center" valign="middle" >4.73</td></tr></tbody></table></table-wrap><p>in this study, results partly suggest the same trend. The effect of soil organic matter on bulk density is due to the improvement of soil structure with higher contents of organic matter, through the formation of macro aggregates which leads to an increase in the total pore space and a reduction of the potential of soil crusting [<xref ref-type="bibr" rid="scirp.124409-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.124409-ref58">58</xref>] . Soil vegetal cover and the management history of the soils affect soil bulk density through the influence of activities or processes that impact on soil surface crusting and compaction. The use of machinery; for deforestation, cultivation or urban development, for instance, could also be a contributory factor to explain the trend in bulk density variation with land-use [<xref ref-type="bibr" rid="scirp.124409-ref5">5</xref>] .</p><p>The trend obtained in this study for bulk density variation was to be expected. Heavy machinery that tends to compact the soil is used for different engineering purposes within the urban centres and occasionally in the plantations for field preparation and harvesting. In addition, irrigation is used in the banana plantations. Farmland is cultivated yearly and the soils of natural forest experience little or no human activity. Forest soils are rich in organic matter owing to fallen litter and limited activities that can lead to the loss of organic matter. Though soil organic matter is lost in farmland facilitated by tilling activities, some organic matter is regained through the ploughing back of crop residue. The return of soil organic matter in the plantations, through falling leaves, is limited while it is mostly constantly being depleted in urban centers.</p><p>Moisture content, on the other hand, which ranged between 18.26% and 50.47%, with a mean value of 28.93% was highest in the forested areas, followed by areas in farmland, plantations and least in areas with high human settlement (<xref ref-type="table" rid="table1">Table 1</xref>). This pattern of variation was to be expected, as soil compaction or the collapse of the soil aggregate structure reduces the total pore space in the soil, and hence, it’s water retention capacity. This is similar to the results obtained by Chandel, Hadda [<xref ref-type="bibr" rid="scirp.124409-ref56">56</xref>] who found the highest water holding capacity for forest soils, followed by those of horticulture, grasses, cultivated land, and least for bare land land-use. Anderson, Gantzer [<xref ref-type="bibr" rid="scirp.124409-ref58">58</xref>] suggested that soils with higher soil organic matter content have higher water retention capacities.</p><p>The proportion of clay was greatest in plantation and least in the forest land-use (plantation &gt; settlement &gt; farmland &gt; forest); while that of silt was greatest in the farmland and least in the forest land-use (farmland &gt; plantation &gt; settlement &gt; forest). The forest land-use class was the sandiest while the plantation LULC class was the least sandy (forest &gt; settlement &gt; farmland &gt; plantation). Using the United States Department of Agriculture (USDA) soil classification scheme, the soils could be classified as sandy, loamy sand, sandy loam and loamy clay sand (<xref ref-type="fig" rid="fig6">Figure 6</xref>). Moges, Dagnachew [<xref ref-type="bibr" rid="scirp.124409-ref10">10</xref>] reported similar results: the highest proportion of sand in the protected forest land-use class and a relatively higher proportion of clay in the farmland LULC type. They suggested that the relatively higher clay fraction in the farmland could be accounted for by an increased weathering rate, enhanced by farming activities and a change in both the water and temperature regimes of soils in farmland. Tellen and Yerima [<xref ref-type="bibr" rid="scirp.124409-ref59">59</xref>] found the highest percentage of sand at mid-attitudes in an afforested area and the least in a farmland and equally attributed the lower sand content in farmland to the effects of tillage activities.</p></sec><sec id="s3_3"><title>3.3. Soil chemical Properties</title><p>The results of the variation of soil acidity and cation exchange capacity (CEC) are summarized in <xref ref-type="table" rid="table2">Table 2</xref> and illustrated in <xref ref-type="fig" rid="fig7">Figure 7</xref>. Soil acidity was measured both as pH in water and pH in KCl. pH<sub>(</sub><sub>water)</sub> with a mean of 5.9 and standard deviation 0.86 varied between 4.0 and 7.4 while pH<sub>(KCl)</sub> with a mean of 5.15 and standard deviation 0.74 ranged between 3.8 and 7.1. CEC registered a mean of 14.39, standard deviation of 2.14 and range 10.4 - 17.87.</p><p>pH<sub>(</sub><sub>water)</sub> and pH<sub>(KCl)</sub> exhibited similar trends across the study area. The average values were highest for settlements and least for the agricultural areas. These results tie with the findings of Tellen and Yerima [<xref ref-type="bibr" rid="scirp.124409-ref59">59</xref>] who found the lowest pH averages for farmland and higher values for grassland and grazing land. Fetene and Amera [<xref ref-type="bibr" rid="scirp.124409-ref24">24</xref>] recorded the highest mean value of pH for forest, followed by grazing land and cultivated land. The results, however, contradict those of Sebhatleab [<xref ref-type="bibr" rid="scirp.124409-ref60">60</xref>] who reported low pH values for forest land and grassland compared to bare land. Lake [<xref ref-type="bibr" rid="scirp.124409-ref61">61</xref>] identified parent material, weathering and agricultural practices as the main factors that influence soil pH.</p><p>The low pH values for agricultural land-use classes could be attributed to the predominant use of agro-chemicals, especially ammonium fertilizers. The relatively low pH values for forest could be as a result of the formation of (weak) organic acids following the decomposition of SOM and nitrogen mineralization by soil microbes. The settlement LULC class generally has little organic carbon</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Summary of selected chemical properties of soils of the southern slopes of Mt Cameroon</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >LULC</th><th align="center" valign="middle" >Quantity</th><th align="center" valign="middle" >pH<sub>(H2O)</sub></th><th align="center" valign="middle" >pH<sub>(KCl)</sub></th><th align="center" valign="middle" >CEC</th></tr></thead><tr><td align="center" valign="middle"  rowspan="4"  >Farmland</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >4.00</td><td align="center" valign="middle" >4.40</td><td align="center" valign="middle" >10.40</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >6.10</td><td align="center" valign="middle" >5.20</td><td align="center" valign="middle" >17.87</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >5.43</td><td align="center" valign="middle" >4.80</td><td align="center" valign="middle" >13.94</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.97</td><td align="center" valign="middle" >0.33</td><td align="center" valign="middle" >3.06</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Forest</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >5.50</td><td align="center" valign="middle" >4.90</td><td align="center" valign="middle" >12.80</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >6.50</td><td align="center" valign="middle" >5.60</td><td align="center" valign="middle" >17.60</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >5.78</td><td align="center" valign="middle" >5.13</td><td align="center" valign="middle" >15.33</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.49</td><td align="center" valign="middle" >0.33</td><td align="center" valign="middle" >1.98</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Plantation</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >4.50</td><td align="center" valign="middle" >3.80</td><td align="center" valign="middle" >12.00</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >6.40</td><td align="center" valign="middle" >5.00</td><td align="center" valign="middle" >17.20</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >5.60</td><td align="center" valign="middle" >4.63</td><td align="center" valign="middle" >14.03</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.88</td><td align="center" valign="middle" >0.57</td><td align="center" valign="middle" >2.52</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Settlement</td><td align="center" valign="middle" >min</td><td align="center" valign="middle" >6.50</td><td align="center" valign="middle" >5.30</td><td align="center" valign="middle" >13.07</td></tr><tr><td align="center" valign="middle" >max</td><td align="center" valign="middle" >7.40</td><td align="center" valign="middle" >7.10</td><td align="center" valign="middle" >15.93</td></tr><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >6.83</td><td align="center" valign="middle" >6.08</td><td align="center" valign="middle" >14.25</td></tr><tr><td align="center" valign="middle" >SD</td><td align="center" valign="middle" >0.40</td><td align="center" valign="middle" >0.75</td><td align="center" valign="middle" >1.25</td></tr></tbody></table></table-wrap><p>and experience minimal use of chemicals. The acidity of soils in the settlement land-use is, consequently, dominated by the chemistry of the soil parent material which is mostly basic rocks, basalts, basanites and hawaiites [<xref ref-type="bibr" rid="scirp.124409-ref29">29</xref>] . This certainly accounts for the high mean pH values (low acidity) for soils of the settlement land-use areas.</p><p>The difference between the 2 pH values for each sample (pH<sub>(</sub><sub>water)</sub> - pH<sub>(KCl)</sub>) gives the net charge. The average net charge for the study area is positive, highest in areas dominated by plantations followed by those for settlement, forest, and farmland, respectively. The acidity of the soil was greater when measured in KCl most probably due to the mobilization of reserved acidity on the soil colloids whereby Al cations in the colloids are displaced by K cations from the KCl. The positive net charge of the soils is an indication of the fact that the rate of cation exchange is higher than that of anions [<xref ref-type="bibr" rid="scirp.124409-ref62">62</xref>] .</p><p>CEC did not reveal any clear pattern of variation. The mean values of CEC for the various LULC classes, however, were in the following order: forest &gt; settlement &gt; plantation &gt; farmland. According to the rating proposed by Hazelton and Murphy [<xref ref-type="bibr" rid="scirp.124409-ref63">63</xref>] , the mean values of CEC for all LULC classes of the study area were moderate (12 - 25 cmol (+)/kg). This implies moderate resistance to changes in soil chemistry and reasonable availability of plant nutrients to the root system (fertility of the soil) [<xref ref-type="bibr" rid="scirp.124409-ref64">64</xref>] . There was neither a clear match in the trend of CEC means exhibited in the study and those of other studies nor was there any consistency in the trends for similar studies in the literature. Fetene and Amera [<xref ref-type="bibr" rid="scirp.124409-ref24">24</xref>] , for instance, associated the variation of CEC in soils with the types and relative amounts of clays and soil organic matter. This may account for the inconsistencies.</p></sec></sec><sec id="s4"><title>4. Conclusions</title><p>The major LULC categories of the southern slopes of Mount Cameroon were forest, agroforestry, settlement, and orchards/plantation. It is discernible from the results that subsistence agriculture was a key source of livelihood, as the agroforestry LULC was the largest in surface area extent. The variation of the mean values of the selected soil properties with LULC exhibited the following trends: bulk density (settlement &gt; plantation &gt; farmland &gt; forest); moisture content (forest &gt; farmland &gt; plantation &gt; settlement); clay (plantation &gt; settlement &gt; farmland &gt; forest); silt (farmland &gt; plantation &gt; settlement &gt; forest); sand (forest &gt; settlement &gt; farmland &gt; plantation); pH<sub>(H2O)</sub> (settlement &gt; forest &gt; plantation &gt; farmland); pH<sub>(KCl)</sub> (settlement &gt; forest &gt; farmland &gt; plantation) and CEC (forest &gt; settlement &gt; plantation &gt; farmland).</p><p>The soils were moderately acidic to neutral (pH: 4.00 - 7.04) and the soil texture was sandy to loamy clay sand. From the geostatistics, land management, reflected by LULC, impacted on soil acidity, bulk density, moisture content, soil texture and CEC. Conversion from forest to other LULC categories, therefore, leads to a decrease in CEC, soil moisture content and pH, while there is an increase in bulk density and clay. Consequently, changes in these soil physico-chemical properties are a pointer to possible soil degradation. Hence, soil physico-chemical properties can be considered as indicators of soil quality and on the other hand, a change in these properties could serve as a proxy for LULC change.</p><p>The major limitation of the study included the inaccessibility of some areas due to the nature of the terrain and security threats posed by wild animals and the civil strife in the region. Future studies could consider increasing the sample density and increasing the number of soil chemical parameters.</p></sec><sec id="s5"><title>Acknowledgements</title><p>The authors are grateful to Mr. Tamungang Richard of the South West Regional Delegation of the Ministry of Forestry and Wildlife, Cameroon, for his contributions to the production of the maps. They are equally thankful to Dr. Kum Marius Kebei, Dr. Kum Christian Tegha and Miss Kum Mirabel Bih, for their assistance in field work.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>Authors have declared that no competing interests exist.</p></sec><sec id="s7"><title>Cite this paper</title><p>Ghong, N.P., Ngwabie, N.M., Asongwe, G.A., Kedia, A.C. and Suh, C.E. (2023) An Assessment and Geostatistics of Land-Use and Selected Physico-Chemical Properties of Soils in the Mount Cameroon Area. Journal of Geographic Information System, 15, 244-266. https://doi.org/10.4236/jgis.2023.152013</p></sec></body><back><ref-list><title>References</title><ref id="scirp.124409-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Burrough, P. (2001) GIS and Geostatistics: Essential Partners for Spatial Analysis. Environmental and Ecological Statistics, 8, 361-377.  
https://doi.org/10.1023/A:1012734519752</mixed-citation></ref><ref id="scirp.124409-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Aksoy, E. and Dirim, M.S. (2009) Soil Mapping Approach in GIS Using Landsat Satellite Imagery and DEM Data. African Journal of Agricultural Research, 4, 1295-1302.</mixed-citation></ref><ref id="scirp.124409-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Aliou, N. and Lamine, N.M. (2022) Evaluation of the Physical and Chemical Fertility of Soils in the Sylvopastoral Zone: Case of the Pilot Site of the National Institute of Pedology in the Commune of Kelle Gueye (Louga/Senegal). Journal of Geographic Information System, 14, 503-515. https://doi.org/10.4236/jgis.2022.145028</mixed-citation></ref><ref id="scirp.124409-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Costanza, R., et al. (1997) The Value of the World’s Ecosystem Services and Natural Capital. Nature, 387, 253-260. https://doi.org/10.1038/387253a0</mixed-citation></ref><ref id="scirp.124409-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Hajabbasi, M.A., Jalalian, A. and Karimzadeh, H.R. (1997) Deforestation Effects on Soil Physical and Chemical Properties, Lordegan, Iran. Plant and Soil, 190, 301-308.  
https://doi.org/10.1023/A:1004243702208</mixed-citation></ref><ref id="scirp.124409-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Purswani, E. and Pathak, B. (2018) Assessment of Soil Characteristics in Different Land-Use Systems in Gandhinagar, Gujarat. International Academy of Ecology and Environmental Sciences, Hong Kong.</mixed-citation></ref><ref id="scirp.124409-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Paz-Kagan, T., et al. (2014) A Spectral Soil Quality Index (SSQI) for Characterizing Soil Function in Areas of Changed Land Use. Geoderma, 230-231, 171-184.  
https://doi.org/10.1016/j.geoderma.2014.04.003</mixed-citation></ref><ref id="scirp.124409-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Hurni, H., et al. (2015) Soils, Agriculture and Food Security: The Interplay between Ecosystem Functioning and Human Well-Being. Current Opinion in Environmental Sustainability, 15, 25-34. https://doi.org/10.1016/j.cosust.2015.07.009</mixed-citation></ref><ref id="scirp.124409-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Nath, B., Ni-Meister, W. and Choudhury, R. (2021) Impact of Urbanization on Land Use and Land Cover Change in Guwahati City, India and Its Implication on Declining Groundwater Level. Groundwater for Sustainable Development, 12, Article ID: 100500. https://doi.org/10.1016/j.gsd.2020.100500</mixed-citation></ref><ref id="scirp.124409-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Moges, A., Dagnachew, M. and Yimer, F. (2013) Land Use Effects on Soil Quality Indicators: A Case Study of Abo-Wonsho Southern Ethiopia. Applied and Environmental Soil Science, 2013, Article ID: 784989.  
https://doi.org/10.1155/2013/784989</mixed-citation></ref><ref id="scirp.124409-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Lal, R. (2015) Restoring Soil Quality to Mitigate Soil Degradation. Sustainability, 7, 5875-5895. https://doi.org/10.3390/su7055875</mixed-citation></ref><ref id="scirp.124409-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Lal, R. (2012) Climate Change and Soil Degradation Mitigation by Sustainable Management of Soils and Other Natural Resources. Agricultural Research, 1, 199-212.  
https://doi.org/10.1007/s40003-012-0031-9</mixed-citation></ref><ref id="scirp.124409-ref13"><label>13</label><mixed-citation publication-type="book" xlink:type="simple">de la Rosa, D. and Sobral, R. (2008) Soil Quality and Methods for Its Assessment. In: Braimoh, A.K. and Vlek, P.L.G., Eds., Land Use and Soil Resources, Springer, Dordrecht, 167-200. https://doi.org/10.1007/978-1-4020-6778-5_9</mixed-citation></ref><ref id="scirp.124409-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">FAO and ITPS (2015) Status of the World’s Soil Resources—Main Report. Rome.</mixed-citation></ref><ref id="scirp.124409-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Nkwunonwo, U. and Okeke, F. (2013) GIS-Based Production of Digital Soil Map for Nigeria. Ethiopian Journal of Environmental Studies and Management, 6, 498-506.  
https://doi.org/10.4314/ejesm.v6i5.7</mixed-citation></ref><ref id="scirp.124409-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Fang, X., et al. (2012) Soil Organic Carbon Distribution in Relation to Land Use and Its Storage in a Small Watershed of the Loes Plateau, China. Catena, 88, 6-13.  
https://doi.org/10.1016/j.catena.2011.07.012</mixed-citation></ref><ref id="scirp.124409-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Szypula, B. (2017) Digital Elevation Models in Geomorphology. In: Hydro Geomorphology Models and Trends, IntechOpen, London, 81-112.  
https://doi.org/10.5772/intechopen.68447</mixed-citation></ref><ref id="scirp.124409-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Mukherjee, S., et al. (2013) Evaluation of Vertical Accuracy of Open Source Digital Elevation Model (DEM). International Journal of Applied Earth Observation and Geoinformation, 21, 205-217. https://doi.org/10.1016/j.jag.2012.09.004</mixed-citation></ref><ref id="scirp.124409-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Maschler, T. (2011) Benchmark Map and Assessment of Deforestation/Forest Degradation Trends in the Mount Cameroon REDD+ Project Area. B. Krause Information Systems, Freiburg.</mixed-citation></ref><ref id="scirp.124409-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Vadrevu, K., Ohara, T. and Justice, C. (2017) Land Cover, Land Use Changes and Air Pollution in Asia: A Synthesis. Environmental Research Letters, 12, Article ID: 120201. https://doi.org/10.1088/1748-9326/aa9c5d</mixed-citation></ref><ref id="scirp.124409-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Wubie, M.A., Assen, M. and Nicolau, M.D. (2016) Patterns, Causes and Consequences of Land Use/Cover Dynamics in the Gumara Watershed of Lake Tana Basin, Northwestern Ethiopia. Environmental Systems Research, 5, 1-12.  
https://doi.org/10.1186/s40068-016-0058-1</mixed-citation></ref><ref id="scirp.124409-ref22"><label>22</label><mixed-citation publication-type="other" xlink:type="simple">Yaron, G. (2001) Forest, Plantation Crops or Small-Scale Agriculture? An Economic Analysis of Alternative Land Use Options in the Mount Cameroon Area. Journal of Environmental Planning and Management, 44, 85-108.  
https://doi.org/10.1080/09640560123194</mixed-citation></ref><ref id="scirp.124409-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Lambin, E.F., Geist, H.J. and Lepers, E. (2003) Dynamics of Land-Use and Land-Cover Change in Tropical Regions. Annual Review of Environment and Resources, 28, 205-241. https://doi.org/10.1146/annurev.energy.28.050302.105459</mixed-citation></ref><ref id="scirp.124409-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">Fetene, E.M. and Amera, M.Y. (2018) The Effects of Land Use Types and Soil Depth on Soil Properties of Agedit Watershed, Northwest Ethiopia. Ethiopian Journal of Science and Technology, 11, 39-56. https://doi.org/10.4314/ejst.v11i1.4</mixed-citation></ref><ref id="scirp.124409-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">Shaver, T.M., Peterson, G.A. and Sherrod, L.A. (2003) Cropping Intensification in Dryland Systems Improves Soil Physical Properties: Regression Relations. Geoderma, 116, 149-164. https://doi.org/10.1016/S0016-7061(03)00099-5</mixed-citation></ref><ref id="scirp.124409-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">Agbede, T., Ojeniyi, S. and Adeyemo, A. (2008) Effect of Poultry Manure on Soil Physical and Chemical Properties, Growth and Grain Yield of Sorghum in Southwest, Nigeria. American-Eurasian Journal of Sustainable Agriculture, 2, 72-77.</mixed-citation></ref><ref id="scirp.124409-ref27"><label>27</label><mixed-citation publication-type="other" xlink:type="simple">Barzegar, A., Yousefi, A. and Daryashenas, A. (2002) The Effect of Addition of Different Amounts and Types of Organic Materials on Soil Physical Properties and Yield of Wheat. Plant and Soil, 247, 295-301.  
https://doi.org/10.1023/A:1021561628045</mixed-citation></ref><ref id="scirp.124409-ref28"><label>28</label><mixed-citation publication-type="other" xlink:type="simple">Wandji, P., et al. (2009) Xenoliths of Dunites, Wehrlites and Clinopyroxenites in the Basanites from Batoke Volcanic Cone (Mount Cameroon, Central Africa): Petrogenetic Implications. Mineralogy and Petrology, 96, 81-98.  
https://doi.org/10.1007/s00710-008-0040-3</mixed-citation></ref><ref id="scirp.124409-ref29"><label>29</label><mixed-citation publication-type="other" xlink:type="simple">Suh, C.E., Luhr, J.F. and Njome, M. (2008) Olivine-Hosted Glass Inclusions from Scoriae Erupted in 1954-2000 at Mount Cameroon Volcano, West Africa. Journal of Volcanology and Geothermal Research, 169, 1-33.  
https://doi.org/10.1016/j.jvolgeores.2007.07.004</mixed-citation></ref><ref id="scirp.124409-ref30"><label>30</label><mixed-citation publication-type="other" xlink:type="simple">Forboseh, P.F., et al. (2011) Tree Population Dynamics of Three Altitudinal Vegetation Communities on Mount Cameroon (1989-2004). Journal of Mountain Science, 8, 495-504. https://doi.org/10.1007/s11629-011-2031-9</mixed-citation></ref><ref id="scirp.124409-ref31"><label>31</label><mixed-citation publication-type="other" xlink:type="simple">Proctor, J.K., et al. (2007) Zonation of Forest Vegetation and Soils of Mount Cameroon, West Africa. Plant Ecology, 192, 251-269.  
https://doi.org/10.1007/s11258-007-9326-5</mixed-citation></ref><ref id="scirp.124409-ref32"><label>32</label><mixed-citation publication-type="other" xlink:type="simple">Fraser, P.J., Hall, J.B. and Healey, J.R. (1998) Climate of the Mount Cameroon Region: Long and Medium Term Rainfall, Temperature and Sunshine Data. University of Wales, Mount Cameroon Project and Cameroon Development Corporation, Bangor.</mixed-citation></ref><ref id="scirp.124409-ref33"><label>33</label><mixed-citation publication-type="other" xlink:type="simple">Djukem, W.D.L., et al. (2020) Effect of Soil Geomechanical Properties and Geo-Environmental Factors on Landslide Predisposition at Mount Oku, Cameroon. International Journal of Environmental Research and Public Health, 17, 6795.  
https://doi.org/10.3390/ijerph17186795</mixed-citation></ref><ref id="scirp.124409-ref34"><label>34</label><mixed-citation publication-type="other" xlink:type="simple">Suh, C.E., et al. (2011) Morphology and Structure of the 1999 Lava Flows at Mount Cameroon Volcano (West Africa) and Their Bearing on the Emplacement Dynamics of Volume-Limited Flows. Geological Magazine, 148, 22-34.  
https://doi.org/10.1017/S0016756810000312</mixed-citation></ref><ref id="scirp.124409-ref35"><label>35</label><mixed-citation publication-type="other" xlink:type="simple">Tsafack, J.-P.F., et al. (2009) The Mount Cameroon Stratovolcano (Cameroon Volcanic Line, Central Africa): Petrology, Geochemistry, Isotope and Age Data. Geochemistry, Mineralogy and Petrology, 47, 65-78.  
https://doi.org/10.1097/00010694-196205000-00026</mixed-citation></ref><ref id="scirp.124409-ref36"><label>36</label><mixed-citation publication-type="other" xlink:type="simple">Hasselo, H.N. (1961) The Soils of the Lower Eastern Slopes of the Cameroon Mountain and Their Suitability for Various Perennial Crops. Veenman, Wageningen.</mixed-citation></ref><ref id="scirp.124409-ref37"><label>37</label><mixed-citation publication-type="other" xlink:type="simple">Payton, R.W. (1993) Ecology, Altitudinal Zonation and Conservation of Tropical Rain Forests of Mount Cameroon. Final Project Report R4600.</mixed-citation></ref><ref id="scirp.124409-ref38"><label>38</label><mixed-citation publication-type="other" xlink:type="simple">FAO. Definitions of Forest, Other Land Uses, and Trees outside Forests.  
https://www.fao.org/3/ad665e/ad665e03.htm</mixed-citation></ref><ref id="scirp.124409-ref39"><label>39</label><mixed-citation publication-type="book" xlink:type="simple">Hao, X., et al. (2008) Soil Density and Porosity. In: Carter, M.R. and Gregorich, E.G., Eds., Soil Sampling and Methods of Analysis, Taylor &amp; Francis Group, Boca Raton, 743-759.</mixed-citation></ref><ref id="scirp.124409-ref40"><label>40</label><mixed-citation publication-type="book" xlink:type="simple">Clarke Topp, G., Parkin, G.W. and Ferre, T.P.A. (2008) Soil Water Content. In: Carter, M.R. and Gregorich, E.G., Eds., Soil Sampling and Methods of Analysis, Taylor &amp; Francis Group, Boca Raton, 939-961.</mixed-citation></ref><ref id="scirp.124409-ref41"><label>41</label><mixed-citation publication-type="book" xlink:type="simple">Kroetsch, D. and Wang, C. (2008) Particle Size Distribution. In: Carter, M.R. and Gregorich, E.G., Eds., Soil Sampling and Methods of Analysis, Taylor &amp; Francis Group, Boca Raton, 713-725. https://doi.org/10.1201/9781420005271.ch55</mixed-citation></ref><ref id="scirp.124409-ref42"><label>42</label><mixed-citation publication-type="book" xlink:type="simple">Hendershot, W.H., Lalande, H. and Duquette, M. (2008) Soil Reaction and Exchangeable Acidity. In: Carter, M.R. and Gregorich, E.G., Eds., Soil Sampling and Methods of Analysis, Taylor &amp; Francis Group, Boca Raton, 173-178.  
https://doi.org/10.1201/9781420005271.ch16</mixed-citation></ref><ref id="scirp.124409-ref43"><label>43</label><mixed-citation publication-type="other" xlink:type="simple">FAO (2022) Standard Operating Procedure for Cation Exchange Capacity and Exchangeable Bases 1N Ammonium Acetate, pH 7.0 Method.  
https://www.fao.org/3/cc1200en/cc1200en.pdf</mixed-citation></ref><ref id="scirp.124409-ref44"><label>44</label><mixed-citation publication-type="other" xlink:type="simple">Powell, R., et al. (2004) Sources of Error in Accuracy Assessment of Thematic Land-Cover Maps in the Brazilian Amazon. Remote Sensing of Environment, 90, 221-234. https://doi.org/10.1016/j.rse.2003.12.007</mixed-citation></ref><ref id="scirp.124409-ref45"><label>45</label><mixed-citation publication-type="other" xlink:type="simple">MINADER (2015) The State of Biodiversity for Food and Agriculture in the Republic of Cameroon. Ministry of Agriculture and Rural Development, Yaounde.</mixed-citation></ref><ref id="scirp.124409-ref46"><label>46</label><mixed-citation publication-type="other" xlink:type="simple">Bele, M.Y., et al. (2013) Exploring Vulnerability and Adaptation to Climate Change of Communities in the Forest Zone of Cameroon. Climatic Change, 119, 875-889.  
https://doi.org/10.1007/s10584-013-0738-z</mixed-citation></ref><ref id="scirp.124409-ref47"><label>47</label><mixed-citation publication-type="other" xlink:type="simple">NOCC (2021) Agricultural Calendar for the Five Agro-Ecological Zones of Cameroon. National Observatory on Climate Change, Yaounde.</mixed-citation></ref><ref id="scirp.124409-ref48"><label>48</label><mixed-citation publication-type="other" xlink:type="simple">Hall, J.B. (1973) Vegetational Zones on the Southern Slopes of Mount Cameroon. Vegetatio, 27, 49-69. https://doi.org/10.1007/BF02389340</mixed-citation></ref><ref id="scirp.124409-ref49"><label>49</label><mixed-citation publication-type="other" xlink:type="simple">Watts, J. and Akogo, G.M. (1994) Biodiversity Assessment and Developments towards Participatory Forest Management on Mount Cameroon. Commonwealth Forestry Review, 73, 221-230.</mixed-citation></ref><ref id="scirp.124409-ref50"><label>50</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Bederman</surname><given-names> S.H. </given-names></name>,<etal>et al</etal>. (<year>1966</year>)<article-title>Plantation Agriculture in Victoria Division, West Cameroon: An Historical Introduction</article-title><source> Geography</source><volume> 51</volume>,<fpage> 349</fpage>-<lpage>360</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.124409-ref51"><label>51</label><mixed-citation publication-type="other" xlink:type="simple">Fonge, B., Bechem, E. and Juru, V. (2015) Agriculture Practice and Its Impact on Forest Cover and Individual Trees in the Mount Cameroon Region. Current Journal of Applied Science and Technology, 6, 123-137.  
https://doi.org/10.9734/BJAST/2015/12906</mixed-citation></ref><ref id="scirp.124409-ref52"><label>52</label><mixed-citation publication-type="other" xlink:type="simple">Hanacek, K. and Rodríguez-Labajos, B. (2018) Impacts of Land-Use and Management Changes on Cultural Agroecosystem Services and Environmental Conflicts—A Global Review. Global Environmental Change, 50, 41-59.  
https://doi.org/10.1016/j.gloenvcha.2018.02.016</mixed-citation></ref><ref id="scirp.124409-ref53"><label>53</label><mixed-citation publication-type="other" xlink:type="simple">Agidew, A.-M.A. and Singh, K. (2017) The Implications of Land Use and Land Cover Changes for Rural Household Food Insecurity in the Northeastern Highlands of Ethiopia: The Case of the Teleyayen Sub-Watershed. Agriculture &amp; Food Security, 6, Article No. 56. https://doi.org/10.1186/s40066-017-0134-4</mixed-citation></ref><ref id="scirp.124409-ref54"><label>54</label><mixed-citation publication-type="other" xlink:type="simple">Eskandari Damaneh, H., et al. (2022) The Impact of Land Use and Land Cover Changes on Soil Erosion in Western Iran. Natural Hazards, 110, 2185-2205.  
https://doi.org/10.1007/s11069-021-05032-w</mixed-citation></ref><ref id="scirp.124409-ref55"><label>55</label><mixed-citation publication-type="other" xlink:type="simple">MINFOF, Ministry of Forestry and Wildlife, Cameron (2014) The Management Plan of the Mount Cameroon National Park and Its Peripheral Zone.</mixed-citation></ref><ref id="scirp.124409-ref56"><label>56</label><mixed-citation publication-type="other" xlink:type="simple">Chandel, S., Hadda, M. and Mahal, A. (2018) Soil Quality Assessment through Minimum Data Set under Different Land Uses of Submontane Punjab. Communications in Soil Science and Plant Analysis, 49, 658-674.  
https://doi.org/10.1080/00103624.2018.1425424</mixed-citation></ref><ref id="scirp.124409-ref57"><label>57</label><mixed-citation publication-type="other" xlink:type="simple">Bizuhoraho, T., et al. (2018) The Effect of Land Use Systems on Soil Properties; a Case Study from Rwanda. Sustainable Agriculture Research, 7, 30-40.  
https://doi.org/10.5539/sar.v7n2p30</mixed-citation></ref><ref id="scirp.124409-ref58"><label>58</label><mixed-citation publication-type="other" xlink:type="simple">Anderson, S., Gantzer, C. and Brown, J. (1990) Soil Physical Properties after 100 Years of Continuous Cultivation. Journal of Soil and Water Conservation, 45, 117-121.</mixed-citation></ref><ref id="scirp.124409-ref59"><label>59</label><mixed-citation publication-type="other" xlink:type="simple">Tellen, V.A. and Yerima, B.P. (2018) Effects of Land Use Change on Soil Physicochemical Properties in Selected Areas in the North West Region of Cameroon. Environmental Systems Research, 7, Article No. 3.  
https://doi.org/10.1186/s40068-018-0106-0</mixed-citation></ref><ref id="scirp.124409-ref60"><label>60</label><mixed-citation publication-type="other" xlink:type="simple">Sebhatleab, M. (2014) Impact of Land Use and Land Cover Change on Soil Physical and Chemical Properties: A Case Study of Era-Hayelom Tabias, Northern Ethiopia. United Nations University Land Restoration Training Programme.  
http://www.unulrt.is/static/fellows/document/Mulugeta2014.pdf</mixed-citation></ref><ref id="scirp.124409-ref61"><label>61</label><mixed-citation publication-type="other" xlink:type="simple">Lake, B. (2000) Understanding Soil pH. NSW Agriculture Acid Soil Action Leaflet.</mixed-citation></ref><ref id="scirp.124409-ref62"><label>62</label><mixed-citation publication-type="other" xlink:type="simple">Pansu, M. and Gautheyrou, J. (2006) Handbook of Soil Analysis: Mineralogical, Organic and Inorganic Methods. Springer, Berlin.  
https://doi.org/10.1007/978-3-540-31211-6</mixed-citation></ref><ref id="scirp.124409-ref63"><label>63</label><mixed-citation publication-type="other" xlink:type="simple">Hazelton, P. and Murphy, B. (2016) Interpreting Soil Test Results: What Do All the Numbers Mean? CSIRO Publishing, Clayton.  
https://doi.org/10.1071/9781486303977</mixed-citation></ref><ref id="scirp.124409-ref64"><label>64</label><mixed-citation publication-type="other" xlink:type="simple">Rippy, J.F. and Nelson, P.V. (2007) Cation Exchange Capacity and Base Saturation Variation among Alberta, Canada, Moss Peats. HortScience, 42, 349-352.  
https://doi.org/10.21273/HORTSCI.42.2.349</mixed-citation></ref></ref-list></back></article>