Soil properties variation in a small-scale altitudinal gradient of an evergreen foothills forest, Ecuadorian Amazon Region

doi:10.21203/rs.3.rs-2736175/v1

The aim of this study was to evaluate variation in the soil physical and chemical properties in a small-scale elevation gradient at 601 to 1000 m above sea level (m.a.s.l) in an Evergreen Andean-Amazonian forest. The soil sampling was divided into four elevation zones, establishing five permanent monitoring plots (PMP) for each one, where soil physical and chemical properties were determined at depths of 0-10 cm and 10-30 cm. For the altitudinal soil-gradient relationship analysis, multivariate statistical methods were used. The results suggest that some soil properties - such as bulk density (BD), saturated hydraulic conductivity (K_sat), total porosity (TP), soil organic matter (SOM), total nitrogen (TN), available phosphorus (P), potassium (K⁺) and exchangeable calcium (Ca²⁺) were significantly affected by altitude. Soil pH, Al³⁺and exchangeable acidity did not follow any defined pattern with respect to the altitudinal gradients. SOM, TN, Ca²⁺, K_sat, TP and retention porosity (RP) exhibited an increase according to altitudinal gradient, whereas soil bulk density, K⁺and P showed an inverse behavior, with higher values at the lower elevation gradient. The principal components analysis (PCA) and the redundancy component analysis (RDA) also revealed a clear separation of soil properties among altitudinal gradient and confirmed that these variables were necessary in order to explain variation in the soil physical and chemical properties as an elevation gradient function.

Soil fertility

elevation gradients

soil properties

multivariate analysis

Ecuadorian Amazon Region

Ecuador’s Amazon region represents 45% of its territory and is considered one of the tropical areas with the highest concentration of biodiversity. The region has large areas of natural forest, which in turn constitutes an ecosystem of wide local and global interest (Bravo et al. 2017b; Torres et al. 2019; Bravo-Medina et al. 2021). It is characterized by very rainy weather conditions, a variety of soil orders with a predominance of Inceptisols that represent about 80% of its surface, while the other orders (including Andisols) make up a smaller proportion (Espinosa et al. 2018). Due to the humid and warm tropical climate, the soils are highly meteorized, which leads to a predominance of unalterable minerals, such as quartz and low-activity clays e.g., kaolinite, halloysite, gibbsite and iron oxides, all of which confer certain morphological characteristics and a deterioration of the soil chemical parameters (Herrera et al. 1978; Custode and Sourdat 1986; Gardi et al. 2014) .The soils normally have low fertility due to their acidic pH, high organic matter content and low content of available phosphorus and exchangeable bases (K⁺, Ca^2+, Mg²⁺ and Na⁺) (Quesada et al. 2011; Nieto and Caicedo 2012; Bravo et al. 2017a).

Cross-sectional studies in tropical forests have provided valuable information regarding the effect of changes in altitude over long distances on the availability of nutrients (Schawe et al. 2007; Wilcke et al. 2008; Unger et al. 2010; Magnani et al. 2018), which has allowed people to identify and relate the nutrients that limit plant growth as a function of elevation (Unger et al. 2010). However, studies in altitudinal gradients in short range are very scarce, so this proposed research represents an initial step towards evaluating the effect of altitude on the variability of physical and chemical properties associated with fertility and subsequently at a second stage to relate these soil parameters with the distribution and growth of vegetation. Likewise, this study allows us to understand the support function of the soil associated with plant growth and its hydric behaviour. This function is related to structural indicators, such as bulk density, saturated hydraulic conductivity and porosity distribution, and how they are affected by changes in altitude over at close range.

Several studies have indicated that soil properties are related to topographical positions in different forest ecosystems (Tsui et al. 2004; Begum et al. 2010; Unger et al. 2010; Boyden et al. 2012; Liu et al. 2020) and some researchers have related topography to soil types and their current state of soil fertility and trace elements (De Bauw et al. 2016; Tesfaye et al. 2016; Magnani et al. 2018).

Forest soil is an important source of nutrients for vegetation, including N, P, S, K, Ca, Mg, Na and some micronutrients (Tsui et al. 2004). Under natural conditions, soil nutrient availability and water availability often show high variability at small scales (Boyden et al. 2012) and topography is considered an important control factor(Behrens et al. 2014). In this sense, the terrain influences the spatial distribution of soil fertility through variables such as organic carbon, pH, cation exchange capacity (CIC) and nutrient availability (De Bauw et al. 2016). Important relationships between elevation and parameters associated with soil fertility have been indicated; for example, soil pH, available P, and exchangeable K⁺, Ca²⁺ and Mg²⁺ showed a significant decrease with respect to elevation (De Bauw et al. 2016). For Amazonian conditions, an increase in the availability of P and exchangeable bases has been reported with the increase in elevation associated with the thickness of the organic layer, which increases the nutrient reserve for the plants (Wilcke et al. 2008; Unger et al. 2010). Soil organic carbon and total nitrogen may be more influenced by soil depth than by elevation in native forests (Tesfaye et al. 2016). The interrelationship between fertility, topography and tree growth in a subtropical forest ecosystem in southeast China showed that topographic heterogeneity leads to ecological gradients across geomorphological positions. Therefore, small-scale soil-plant interactions in a young forest can serve as a driver for future vegetation development and biodiversity control over soil fertility (Scholten et al. 2017). Both the soil structure and floristic composition of the forest can undergo a dramatic change along the gradient, which in turn can lead to changes in the physical, chemical and biological properties of the soil (Chen et al. 1997; Torres et al. 2019). In some cases, soil properties, such as pH and nutrient availability, also affect the type of vegetation (Tsui et al. 2004). Moreover, the condition of development and distribution of vegetation types on different slope positions are controlled by the bioavailability of nutrients (De Bauw et al. 2016).

The soil physical properties and, in turn, plant growth are significantly controlled by variations in landscape attributes, including slope, appearance and elevation, which influence the distribution of energy, plant nutrients and vegetation (Rezaei and Gilkes 2005). The thickness of the surface layer of the soil, the bulk density, and the structure of the soil are all quite dynamic because they are sensitive to soil formation factors, and depend, to some extent, on land management factors (e.g., erosion, exploitation and conservation) (Blanco-Canqui and Ruis 2018).

In this context, the objective of this study was to determine the variation of soil properties in a small-scale altitudinal gradient in an evergreen foothills forest in the Ecuadorian Amazon region. In this paper, it was hypothesized that the soil physical and chemical properties associated with the support functions (bulk density, saturated hydraulic conductivity, soil porosity, SOM, TN, available P, and exchangeable K⁺, Ca²⁺ and Mg²⁺) are directly affected by the small-scale altitudinal gradient. An additional hypothesis is that the properties are indirectly influenced by landscape attributes with microclimates that support the growth of plant species with different characteristics in the absence of management factors.

2.1 Study Area

This study was carried out in Andean-Amazonian forests in the province of Napo, Ecuador, in collaboration with the Center for Research, Postgraduate Studies and Conservation of Amazon Biodiversity (CIPCA). The forests in this region are considered part of the evergreen slow-growth forests in the northeastern Andean foothills (MAE 2012) (Figure 1) and include about 50 tree families, with the richest being Moraceae, Fabaceae, Meliaceae, Cecropiaceae, Euphorbiaceae, Arecaceae, Annonaceae, Clusiaceae, Rubiaceae and Myristicaceae (Torres et al. 2019).

The climate was similar across the altitude range, and was humid and hyper-humid (MAE, 2012), with an average annual temperature of 23ºC and average annual rainfall of 4119 mm. The lowest rainfall occurs from January to April and the highest from May to July, and the relative humidity varies from 65 to 70% throughout the year. The soils are also located in a pedogenetically homogenous zone since all the sampling plots along the different altitudinal gradients are on the Chambira formation. The latter is constituted by fluvial deposits and conglomerates with a majority of milky quartz clasts with a quartz-clay-sandy matrix (Christophoul et al. 2016). The soil in all the altitudinal gradients belongs to the Andisol order and Udands suborder, which is characteristic of volcanic soils typical of a humid climate (see Figure 1) (Espinosa et al. 2018).

The site where the study plots were established was located in a mountainous area dominated by high and medium crests and rounded hills, composed of volcanic and sedimentary rocks of recent origin (MAE, 2012). The plots were installed at four elevations in the Evergreen Andean-Amazonian Forest (EAAF) whose slope angle varied: it was between 3 and 12 % in EAAF1 (601–700 m.a.s.l) and EAAF2 (701–800 m.a.s.l.), while in EAAF3 (801–900 m.a.s.l) and EAAF4 (901–1000 m.a.s.l) the slope angle ranged between 3 and 30 % (Table 1). At each elevation, ﬁve permanent monitoring plots (PMP), each of 1000 m² (10 x 100 m), were established parallel to the slope to maintain consistency in terms of elevation (reducing micro-level variation). The selection criteria were accessibility, topographical homogeneity, elevation at four small-scale gradients (100 m in each gradient) and being apparently non-disturbed old-growth forests.

2.2 Soil Sampling

In each PMP, 3 subplots (10 x 10 m) were identified in order to cover the entire altitudinal range. In each subplot, 5 soil sub-samples were collected at 2 soil depths (0-10 and 10-30 cm), which were subsequently homogenized to obtain a representative soil sample for each soil depth.

2.3 Soil Physical Analysis

Non-altered soil samples were taken using cylinders. They were collected with an Uhland-type sample to determine bulk density (BD) by the cylinder method using cores (or volumetric rings) of well-deﬁned size (5 cm long and 5 cm in diameter). We determined pore size distribution (TP: total porosity), aeration porosity (AP: pores of >15 µm radius), and retention porosity (RP), using the saturation tension table method with -10kPa matric potential (Blake and Hartge 1986). The saturated hydraulic conductivity (K_sat) was evaluated using the variable loading method (Reynolds et al. 2002).

2.4 Soil Chemistry Analysis

Total Organic Carbon (TOC) was determined by the Walkley & Black wet digestion method (Nelson and Sommers 1982) and later the soil organic matter (SOM) was estimated from the COS multiplied by the equivalent factor 1.724 (Jackson 1964). The potentiometric method (soil-water ratio of 1: 2.5) was used to measure the soil pH. Acidity and exchangeable Al³⁺ were measured by titration (McLean 1965). The analytical methods are described by Okalebo et al., (2002).Total N was assessed by titration after Kjeldahl digestion with sulfuric acid and selenium as a catalyst. Available P and extractable cations (K⁺, Ca²⁺ and Mg²⁺) were removed using Olsen extraction solution. P was measured colorimetrically using the molybdenum blue method, while K⁺, Ca²⁺ and Mg²⁺ were determined using an atomic absorption spectrophotometer.

2.5 Data Analysis

The data analysis was carried out using the SPSS Statistics software version 22.0 ®, IBM, 2013. A one-way ANOVA was used to detect significant differences (P <0.05) between the altitudinal gradients. Prior to the ANOVA, an exploratory data set analysis was carried out using descriptive statistics, and normality was tested with the Shapiro-Wilk test. In order to display the soil-landscape relationships, redundancy (RDA) and principal component (PCA) analyses were performed using the soil physical and chemical variables and elevation data set (CANOCO software) (ter Braak and Šmilauer 2012). All the data were normalized before implementing the PCA and RDA. The degree of correlation among soil properties was assessed by means of Pearson's correlation coefficient (r) (Hervé 2020).

The nutrient stock in the soil (Ss) was calculated at the depths of 0-10 cm and 10-30 cm using the following equation (Bond 2010):

Ss (kg ha^-1) = Bulk density (kg m^-3) *[ mg kg^-1]* soil depth(m)*0.01 (1)

and then a weighted average was performed to obtain the nutrient reserve in the 0-30 cm zone.

3.1 Soil Physical and Chemical Properties as a Function of the Altitudinal Gradient

The soil physical properties evaluated through structural indices registered significant differences (P <0.05) for the different altitudinal gradients. A clear difference in soil physical properties along the altitudinal gradient was observed, showing a decrease in BD ranging from a minimum of 0.52 Mg m^-3 dry soil to a maximum of 0.89 Mg m^-3in the surface layer (Table 2). BD was signiﬁcantly lower at the highest altitudinal gradient (901-1000 m.a.s.l) compared to other altitudinal gradients at both soil depths (Table 2).

The BD values were inversely related to the total porosity, retention porosity and saturated hydraulic conductivity (K_sat) of the soil since a lower BD resulted in higher values of these variables as a function of the altitudinal gradient and for both depths evaluated (Table 2)

In the surface layer, the saturated hydraulic conductivity only showed significant differences (P < 0.05) in the higher altitudinal gradient (901-1000 m.a.s.l). In the first three gradients, the values ranged from 16 to 21 cm h^-1(Table 2), while the highest gradient showed values close to 60 cm h^-1. Within the 10-30 cm soil layer, the first altitudinal gradient (600-900 m.a.s.l) presented values between 6 and 7 cm h^-1 and for the second altitudinal gradient, the values were around 37 cm h^-1. Regardless of the altitudinal gradient, K_sat decreased with depth (Table 2).

The highest proportion of pores was represented by retention pores (RP) as opposed to aeration porosity (AP) (Table 2). In general, for both depths, the RP increased gradually following a pattern according to the altitudinal gradient. Specifically, in the surface layer, the values ranged from 52 to 58% at 601 to 900 m.a.s.l, while at 901 to 1000 m.a.s.l, the value was around 65%. For the subsurface layer, the values showed ranges from 53 to 58% (601 to 900 m.a.s.l) and 63% at the highest floor (901 to 100 m.a.s.l). AP did not follow a defined pattern based on the altitudinal floor and it decreased with depth regardless of the altitude. The surface layer showed values that ranged from 15 to 19%, while in the subsurface layer, the values ranged from 9 to 11%.

Soil bulk density and soil microporosity values increased with soil depth, whereas K_sat, TP and AP showed an inverse behavior, decreasing with soil depth. The behavior of structural indices is closely related to the variation in SOM content (Table 2).

The soil chemical properties associated with soil fertility showed significant differences (P <0.05) for soil organic matter, total nitrogen, available phosphorus, potassium and exchangeable calcium at both soil depths of sampling points (Table 3).

At both soil depths, the pH values were very acidic and this did not change along the altitudinal gradient. The exchangeable acidity and Al³⁺ showed high values without differences between the altitudes. The soil organic matter (SOM) and total nitrogen (TN) concentrations increased as elevation increased. In particular, at both soil depths, the SOM content obeyed the following trend: EAAF1 = EAAF2 < EAAF3 = EAAF4 and so on for TN was: EAAF1 = EAAF2 < EAAF3 < EAAF4.

The available P content was slightly higher at the lower elevation areas for both soil depths with medium to low contents. Furthermore, at both soil depths, this nutrient followed the trend of EAAF1 = EAAF2 > EAAF3 = EAAF4.

The levels of exchangeable bases are affected by leaching processes throughout the altitudinal gradients; however, the K⁺concentrationat both soil depthsfollowed a downward trend according to the altitudinal gradients, with values that ranged from high to low. In contrast, the exchangeable Ca²⁺ exhibited an increasing pattern, with higher values at the higher altitudinal gradients, which are categorized as medium to low. The exchangeable Mg²⁺did not show significant differences and did not follow any definite pattern with respect to the altitudinal gradient.

3.2 Soil Parameter Variation as a Function of the Altitudinal Gradient

The analysis of main components, using the graphical representation method of the data matrix, showed the interaction of the soil physical and chemical variables associated with soil fertility in the two evaluated soil depths according to the altitudinal gradient (Figures 2a and 2b).

The results of Figure 2 show that 82% of the data variance could be explained by the first two principal components. For the surface layer (Figure 2a) along the first axis, it can be observed that the plots with higher altitudes (EAAPF3 and EAAPF4; see Table 2) presented higher values of SOC, TN, K_sat, exchangeable Ca²⁺, TP and RP, while the available P, exchangeable K⁺ and BD were higher in the plots located at medium altitudinal gradients (EAAPF1 and EAAPF2; see Table 2). The soil pH, acidity, exchangeable aluminum and aeration porosity were not related to the plot nor were they influenced by the altitudinal gradients.

3.3 Correlations Among Soil Properties and Altitude

The correlation matrices for soils at 0-10 and 10-30 cm in depth show several sets of significant relationships (Table 4 and 5). Within the 0-10 cm soil layer, K_sat, TP, SOM, TN and Ca²⁺ were positively correlated with altitude. In contrast, BD, exchangeable K⁺ and Mg²⁺, and available P were negatively related to altitude (Table 4). For the subsurface layer (10-30 cm), altitude was negatively related to the soil bulk density (r=-0.80**) and the exchangeable potassium content (r=-0.63**), while it was positively related to SOM (r=0.63**), TN (r=0.84**) and Ca²⁺(r=0.74**) (Table 5).

The following variables presented relationships with altitudinal gradient: BD, K_sat, SOM, TN and exchangeable Ca²⁺ for depths of 0-10 cm and 10-30 cm. Soil bulk density (Figure 3a and 3b) showed a linear and inverse behavior, decreasing with altitude. It had a determination coefficient of R² that ranged from 0.60 (0-10 cm) to 0.83 (10-30 cm), considered moderate to high, respectively.

The saturated hydraulic conductivity (Figure 3c and 3d) for the surface layer exhibited an exponential adjustment with altitude and a high determination coefficient (0.90), while for the subsurface layer, the correlations were very low.

The correlation of the SOM content and TN with altitudinal gradient showed a similar behavior with a linear adjustment. For SOM, the correlation value ranged from 0.76 to 0.63 (Tables 4 and 5), which is categorized as high to moderate for the surface and subsurface soil layer, respectively (Figure 4a and 4b), while for TN, the value ranged from 0.84 to 0.90 (Tables 4 and 5), which is considered a high correlation (Figure 4c and 4d).

Exchangeable Ca²⁺ (Figure 4e and 4f) exhibited an exponential behavior with a moderate correlation that ranged from 0.47 to 0.34 in the surface and subsurface soil depths, respectively, indicating higher values in the higher elevation areas.

The results of the redundancy analysis (RDA) for soil properties at both soil depths (0-10 and 10-30 cm) showed a clear separation of some soil physical and chemical variables associated with soil fertility as a function of the altitudinal microgradient (Figure 8). In both studied soil layers (Figures 5a and 5b), the Monte Carlos test indicated the variation of some soil properties to be significantly related to altitude (P <0.001). The variables K_sat, AP, TP, SOM, TN and Ca showed a positive relationship with altitude, while BD, P and K presented an inverse behavior, reaching lower values in higher elevation areas.

The soil nutrients stock as TN, P available, K, Ca and exchangeable Mg at 0-30 cm deep showed significant differences (P < 0.05) as a function of altitude gradient (Figure 6). The total nitrogen and exchangeable Ca²⁺ reserve values increased with altitude, while the rest of the nutrients, such as exchangeable P, K⁺ and Mg²⁺, exhibited an inverse behavior, with higher reserves at lower altitudes (Figure 6). TN ranged from 2847.34 to 3929.50 kg ha^-1, available P from 10.51 to 19.44 kg ha^-1, K⁺ from 18.61 to 1126,79 kg ha^-1, Ca²⁺ from 17.50 to 661.64 and Mg²⁺ from 38.43 to 333.37 kg ha^-1. Overall, our plot cation status categorization (viz. “medium” vs. “low”) reﬂects differences in overall soil nutrient status reasonably well

4.1 Effect of Altitudinal Gradient on Soil Physical Properties

This study addressed the effect of altitude on soil properties within an evergreen foothills forest in the Ecuadorian Amazon region (EAR). The study area presents similar climatic conditions, characterized by high precipitation and high temperatures along the altitudinal gradient (Torres et al. 2019). The soils are also located in a pedogenically homogeneous zone since all the sampling plots in the different altitudinal gradients were located within the Chambira formation. The latter is constituted by fluvial deposits and conglomerates with a majority of milky quartz clasts with a dominant quartz-sandy-clay matrix (Chritophoul et al. 2004). Also, the soils at all altitudinal gradients were taxonomically classified within the Andisol order and the Udands suborder (Figure 1), which are characteristic of volcanic soils typical of humid climates (Espinosa et al. 2018). All this is of great relevance due to the impact it has on certain physical properties of the soil, especially those related to the soil’s hydric behavior, such as saturated hydraulic conductivity and porosity (Pla 2010; Blanco-Canqui and Ruis 2018). The soil physical properties are recognised for their important role as a support function for plant growth. When evaluated in the evergreen forest along altitudinal gradients at short range (Table 2), the behavior of these properties indicates a structural condition as a function of soil support, typical for Amazonian soils (Bravo-Medina et al. 2017), where low values of BD, high K_sat and adequate pore size distribution (PSD) are present.

Despite that, significant differences were observed (P <0.05) in the physical properties which are closely related to the changes in the organic matter content of the soil along the altitudinal gradient, whose values increase with altitude (Table 3). The increase in soil organic matter has been pointed out as an important factor in improving the physical properties associated with the structure (BD, K_sat, porosity), as well as the infiltration and water retention rates(Bravo et al. 2017a; Blanco-Canqui and Ruis 2018). The relationship between organic matter, certain physical properties and altitude was confirmed through the PCA (Figure 2) and correlation values (Tables 4 and 5) at both depths (Figure 3). The two depths showed highly significant Pearson's correlation coefficients (P < 0.001) for BD (r=-0.73 to -0.80), K_sat (r=0.60 to 0.59) and TP (r=0.64 to 0.56). The physical properties of the soil and, in turn, plant growth are significantly controlled by the variation in landscape attributes, including appearance, slope, and altitude, which influence the distribution of energy, plant nutrients, and vegetation affecting the availability of the organic component of the soil (Rezaei and Gilkes 2005). In this research, the dynamic nature of the physical properties assessed (Da, Ksat, Pt, Pa) could be affected by the altitudinal gradient or other landscape attributes (e.g., shape and growth density) with indirect influences by providing different microclimates that support the growth of plant species with different characteristics in the absence of management factors. In our research project, the small-scale altitudinal gradient also showed a pattern of the spatial distribution of soil organic matter (SOM), whose value increases with altitude (Figure 2). These results are consistent with those obtained by Unger et al., (2010) in a forest ecosystem in that they reported a higher humus content for the surface horizon in areas of higher elevation, thus lower values of soil BD. In our investigation, SOM was significantly related (P <0.001) to BD (r = -0.78 to 0.92), K_sat (r = 0.61 to 0.67), TP (r = 0.71 to 0.75), and RP (r = 0.61 to 0.63) at both depths (Tables 4 and 5). The negative correlation between soil bulk density, soil organic matter and altitude could be associated with an increase in tree density and basal area, which caused an increase in the entry of roots and leaf litter biomass (Viana et al. 2014). A study at the same site and plots suggests that at the microlevel, species diversity can vary widely because no different species were found at the four altitudinal ranges (Torres et al. 2019). In this context, Torres et al.,(2019) indicated that average tree species richness increases with increasing altitude, although significant differences were only detected (P <0.01) between 600-700 and 901-1000 m.a.s.l. Tree biomass (TBM) along the short-range altitudinal gradient varied between 246.8 and 320.9 Mg ha^-1, which led to differences in biomass and root supply.

The soil bulk density (BD) is a property of great environmental and agricultural significance because it influences the soil’s hydric and pore behavior, as well as the root penetration and development of the crop (Pla 2010; Blanco-Canqui and Ruis 2018). Its values can be interpreted according to the soil’s texture; in the case of a fine texture, for instance clay, BD >1.40 Mg m^-3 should be the threshold value (USDA-NRCS 1996). Based on this, in all the altitudinal gradients, the soil texture classes in the plots studied varied from clayey loam (CL) to clayey (C), which are categorized as fine. Meanwhile, the BD values were below the indicated threshold, which confirms the adequate physical conditions of the soil regardless of the altitude (Table 2). The results obtained are consistent with studies within forest ecosystems in the Ecuadorian Amazon region. Those studies suggest a high accumulation of organic matter on the surface horizon, contributing to a structural formation of granular-type soil that in turn generates adequate physical conditions for plant growth (Bravo et al. 2017a). The bulk density values along the altitudinal gradient reflect an adequate distribution of pore size and a high speed of water penetration in the profile, which shows that the soil has adequate physical functionality (Table 2).

4.2 Effect of the altitudinal gradient on the soil chemical properties

In forest ecosystems, the chemical properties of the soil are influenced by the composition of the vegetation cover and topographical factors (Tsui et al. 2004). In this study, we hypothesized that the small-scale altitudinal gradient may affect soil chemical properties. In our study, several soil chemical properties (namely SOM, TN, available P, K⁺ and exchangeable Ca²⁺) showed statistically significant differences (P <0.05) at both depths with respect to altitude (Table 3). Several studies have shown that differences along an altitudinal gradient can affect changes in the balance of inputs and losses of C, which in turn are potentially related to changes in abiotic and biotic factors (litter quality) (Egli et al. 2008; De Bauw et al. 2016; Magnani et al. 2018). In our paper, the SOM and TN contents showed a similar pattern of spatial distribution with respect to altitude (Figure 2), presenting a linear adjustment that varied from high to moderate for the soil surface and the subsurface horizon respectively (Figure 4). These results were evidenced by Pearson's correlation coefficient with highly significant (P < 0.001) relationships between altitude and SOM (r = 0.76 to 0.63) and NT (r= 0.90 to 0.84) (Tables 4 and 5), confirming the role of SOM as the main source of nitrogen (McGrath et al. 2014). Due to higher N concentrations, organic material in the upper soil layer generally has higher N mineralization rates than the subsurface horizon (Unger et al. 2010). Another factor that could influence N availability for plants in tropical montane forests is the depth of organic layers, which typically increases with altitude (Unger et al. 2010). It has also been noted that in central and northern Ecuador, many summits are volcanoes that develop Andosols in higher altitude areas with relatively high nitrogen concentrations as the soil ages (Unger et al. 2012).

In this study, a higher amount of SOM in higher altitude areas was also associated with a higher concentration of exchangeable Ca²⁺, which was confirmed by the degree of association between both variables with Pearson's correlation coefficients (r = 0.79 to 0.74). The availability of N and exchangeable Ca²⁺ is directly related to the accumulation of organic matter in the soil, which in turn is influenced by the amount of leaf litter that falls on the forest floor (Tsui et al. 2004). In our study site, a greater presence of tree species of the leguminous family such as Fabaceas (Inga spp and Dusia spp) has been reported at the highest elevation floor (901-1000 m.a.s.l), which could contribute to an increase in SOM, TN and Ca²⁺ values (Torres et al. 2019).

The redundancy analysis (RDA) (Figure 5) showed that the altitudinal gradient can affect the behavior of some physical and chemical soil parameters associated with fertility (SOM, TN, available P, K⁺ and Ca²⁺); however, to complement these results it is necessary to carry out studies into the composition and structure of the vegetation in order to help explain the variation of the soil parameters (Chen et al. 1997; Tsui et al. 2004).

Our results show that available P had a negative relationship with altitude with Pearson's correlation coefficients varying from r = -0.41 to -0.66 (Tables 4 and 5), with higher average available P values at lower altitudes (Table 3). Opposite results have been reported for the area by Unger et al., (2010), who found that available P increased with altitude, whereby the rise was associated with a substantial increase in the thickness of the organic horizon. However, it was observed that available P was higher in the surface horizon (0-10 cm) than the second layer (10-30 cm), which indicates a vertical gradient in P availability in the soil, emphasizing the role of organic matter as an important source of P in these soils. We could point out that, in our study, the low quantities of phosphorus available at both depths confirm that this nutrient is a limiting factor and that part of the P released by the decomposition of organic matter is used by the plants, which does not allow it to accumulate in the soil in greater quantities. The renewal of organic P and the rapid recycling of P from waste are the main processes for providing P to plants in natural ecosystems (Johnson et al. 2003).

The P values available from this study coincide with previous work regarding different Amazonian landscapes (forests and other land uses), where it is highlighted that the low P content in Amazonian conditions could be a limiting factor in the productivity of the ecosystem (Cuevas and Medina 1986; Bravo et al. 2017b). Phosphorus (P) is the main limiting macronutrient for ecosystem productivity in highly weathered tropical soils (Elser et al. 2007; Hamer et al. 2013). These soils have high amounts of iron (Fe) and aluminum (Al) sesquioxides that bind geochemically to P and make it unavailable for plant absorption (Custode and Sourdat 1986; Soltangheisi et al. 2019). Understanding soil phosphorus (P) transformation pathways and determining factors related to soil P nutritional status when land-use changes occur is critical in order to develop better management practices, especially in the Amazon region (Soltangheisi et al. 2019). Given that phosphorus is stored in various forms in the soil and P availability varies among plants (depending on their rooting strategies) and soils (depending on their properties), some researchers suggest using total P rather than available P measurements because many plants in natural ecosystems can access more P forms in the soil than crops(Bond 2010). Further study is essential in order to discuss the relevant processes that control the stock of available P in the soil, and its decline with altitude, as well as its potential impact on tree growth, tree species composition and nutrient cycling in tropical forests at altitude.

Soil pH is an important factor, as it directly affects other parameters associated with soil fertility and the capacity of plants to absorb nutrients (McGrath et al. 2014). Based on this, the acidification process evaluated through soil pH, acidity and exchangeable aluminium was similar across the entire altitudinal gradient and without significant differences. The very acidic (<5) soil pH levels, acidity and exchangeable Al³⁺ at both soil depths did not follow any defined pattern with respect to the altitudinal gradient. High acidity and interchangeable aluminium values contributed to the low soil pH levels, reflecting a wide adaptation of the plants to the oligotrophic environment characteristic of the Amazon region(Cuevas and Medina 1988; Bravo et al. 2017a). Other studies have reported a strong relationship between soil pH and the altitudinal gradient, where a linear decrease with altitude was observed. This can be explained by more intense leaching and acidification in higher altitude areas, traditionally following the orographic rain gradient and leading to a lower value of Ca²⁺, Mg²⁺, K⁺ and available P (Vitousek and Chadwick 2013; De Bauw et al. 2016). However, since edaphogenesis in the Amazon region is very marked by climatic conditions (high rainfall and temperature), there is a generalized leaching of the interchangeable bases (K⁺, Ca²⁺ and Mg²⁺) due to their weak adsorption force on the tropical soil colloids which leads to soil acidification (Custode and Sourdat 1986; Viana et al. 2014). This alteration induces a predominance of not-very-altered minerals such as quartz and simple clays e.g. kaolinite, halloysite, gibbsite and iron oxides, conferring certain morphological characteristics and a decrease in the parameters, mainly soil pH and the interchangeable bases (Gardi et al. 2014; De Souza et al. 2018).

4.3 Nutrient reserve according to altitudinal gradient

The available nutrient reserve was calculated from the nutrient concentrations in the soil and adjusted to the bulk density and weighted at the first 0.30 m depth within the tree root zone. The soil analysis generally extracts a part of the total amount of the element present and the amount extracted is proportional to the amount available for plant absorption. The results in our study indicate that the nutrient reserves (N, P, K, Ca and Mg) followed the same trend along the altitudinal gradient and according to the variation in the concentration of each element; therefore, the TN and Ca²⁺ reserves increased significantly with altitude (Figure 6, P < 0.001), while the P and K⁺ reserves were higher in the lower altitude zones. For nitrogen and Ca²⁺, it was clear that these reserves are associated with soil organic matter; however, their importance in the productivity of these ecosystems is evident, not only with respect to TN and Ca²⁺ but also to available P and Mg²⁺ (Wilcke et al. 2008; Unger et al. 2012).

These results suggest that even in dystrophic environments, such as those in the Ecuadorian Amazon region with medium to low levels of nutrient concentration, there is a nutrient reserve that plays an important role in the productivity of natural ecosystems through soil fertility and with potential input for plants, especially of nitrogen and calcium. Most of the weathered soils in humid regions act as weak acidic systems, where the total acidity is much higher than the active acidity and, therefore, the potential acidity is high (Lira-Martins et al. 2019). In our study, the nitrogen stock was higher than the exchangeable bases (K+, Ca²⁺ and Mg²⁺) and the available phosphorus (P). Available P is the most limiting nutrient, which is common in the tropical forests of the Amazon, and represents a forest that grows on nutrient-poor soils (Johnson et al. 2003; Bravo et al. 2017b). Organic P mineralization and dissolution (or weathering) of stable P minerals are natural processes that provide labile P to crops. However, in soils that have low to medium available P values, this means that the supply for plants only covers 15 to 50% of the crop requirement (McGrath et al. 2014). It is important to note that laboratory assessment methods designed to evaluate nutrient availability for crops underestimate the nutrients available in natural ecosystems because plants in forests often access more nutrients than agricultural crops, appealing to a highly diverse nutrient conservation mechanism (Cuevas and Medina 1988). Correlations of vegetation patterns with soil nutrients, particularly P, suggest that soil chemistry is an important factor influencing vegetation properties (Lloyd et al. 2008). Although soil nutrient concentration represents an important reserve for biomass production, it has been estimated that in some forests, 90% of the total reserve of the Ca, K, P and N ecosystem may be trapped in aerial biomass reserves, whereby this proportion is lower if deeper soil layers are considered (Bond 2010). It should be noted that the nutrient reserves in our study were obtained from available P and exchangeable fractions (K+, Ca²⁺ and Mg²⁺). However, some studies recommend that the analysis should focus on the total nutrient stock rather than the fraction of the stock that is available to natural vegetation or the rate at which nutrients are available in decomposition processes (Johnson et al. 2003; Bond 2010; Paul et al. 2010). From this perspective, Bond, (2010) estimated that, as a general guideline, the nutrient stocks (kg ha^-1) needed to build a forest would be > = P: 20-30, K: 200-350, Ca: 300-600 and Mg: 55-65. Therefore, when comparing the potential woody biomass requirements with the nutrient reserves obtained in our study, we could indicate that they do not limit the development of the forest as it is possible to satisfy these demands, especially in plots located at higher elevations. This is confirmed by the production reported in our study area, where aerial biomass varied between 246.8 and 320.9 Mg ha^-1(Torres et al. 2019).

We hypothesized that soil physical and chemical properties (BD, K_sat, soil porosity, SOM, TN, available P, and exchangeable K⁺, Ca²⁺ and Mg²⁺) could be directly affected by a small-scale altitudinal gradient. Along the microgradient, the soil physical and chemical parameters related to fertility varied with elevation and consequently soil fertility, but are not homogeneous in this area. These varying soil properties inﬂuence the availability of plant nutrients and hence their uptake by aboveground vegetation in the rainforest. Overall, it can be stated that soils are generally more fertile at higher elevations. The soil type, pedogenetic processes and weather conditions along the altitudinal microgradient of the evergreen foothills forest in the Amazon region were relatively homogeneous (Figure 1). Hence, the variation found in most of the soil physical and chemical properties in accordance with the altitudinal gradient can be interpreted as possible changes in plant cover, causing a greater biomass and litter contribution, which in turn results in high soil organic matter and nitrogen contents at a higher altitude. SOM, TN, exchangeable Ca²⁺, K_sat, TP and RP increased according to the altitudinal gradient, with higher values at higher elevations, while the soil bulk density, exchangeable K⁺ and available P showed an inverse behavior, with higher values at lower elevations. The soil pH, Al³⁺and exchangeable acidity did not follow any defined pattern with respect to the altitudinal gradient, which is related to the influence of the soil formative factors, especially the high rainfall. The higher SOM content at higher elevation areas favored better physical conditions of the soil, which were reflected in better structural conditions. As indicated, the diﬀering patterns of variations in nutrient stock in relation to the altitudinal gradient suggest that some factors, such as vegetation associated with altitude, may inﬂuence the concentrations of various nutrients, especially TN, P, Ca and K. Additional studies are required in order to contemplate the analysis of the floristic composition by altitudinal gradient to establish relationships between plant cover, soil, microclimate and altitudinal components.

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Table 1. Coding of altitudinal gradients and soil sampling plots.

Code	Altitude (m.a.s.l.)	Plot	Slope (%)	Coordinates
EAAPF1(1)	601 to 700	P1, P2, P3, P4, P5	3-12	18M 0175256 9864554
EAAPF2(2)	701 to 800	P6, P7, P8, P9, P10	3-12	18M 0175453 9865823
EAAPF3(3)	801 to 900	P11, P12, P13, P14, P15	3-30	18M 0175884 9865952
EAAPF4(4)	901 to 1000	P16, P17, P18, P19, P20	3-30	18M 0174994 9866501

Table 2. Means and standard deviation (n=5) of the soil physical properties as a function of altitude and soil depth.

	Altitudinal gradient (m.a.s.l.)
	600-700	701-800	801-900	901-1000
	Soil depth 0-10 cm				F value	P
BD	0.89 ± 0.17^a	0.87 ± 0.18^a	0.71 ± 0.28^a	0.52 ± 0.10^b	9.560	0.000
K_sat	15.74 ± 4.96^b	17.45 ± 6.54^b	20.61 ± 6.87^b	59.75 ± 11.37^a	6.873	0.001
TP	70.31 ± 9.34^b	73.56 ± 7.72^a	75.00 ± 9.42^a	80.57 ± 3.41^a	4.445	0.007
AP	18.63 ± 4.31^a	16.73 ± 6.63^a	17.22 ± 4.85^a	15.07 ± 3.92^a	0.703	0.554
RP	51.68 ± 11.31^b	56.83 ± 6.73^b	57.77 ± 7.47^b	65.50 ± 10.39^a	5.795	0.002
	Soil depth 10-30 cm
BD	1.27 ± 0.14^a	1.21 ± 0.27^a	1.01 ± 0.30^a	0.76 ± 0.19^b	11.957	0.000
Ksat	7.04 ± 3.12^b	6.36 ± 2.91^b	5.79 ± 1.87^b	37.47 ± 7.76^a	10.374	0.000
TP	64.74 ± 8.78^b	63.71 ± 7.30^b	67.02 ± 10.75^a	72.99 ± 4.63a	3.361	0.025
AP	10.88 ± 4.12^a	10.02 ± 3.08^a	9.25 ± 2.75^a	9.84 ± 3.55^a	0.335	0.800
RP	54.06 ± 7.33^b	53.70 ± 8.14^b	57.77 ± 9.08^a	63.15 ± 7.86^a	3.526	0.021

BD: Bulk density (Mg m^-3); K_sat: Saturated hydraulic conductivity (cm h^-1); TP: Total porosity (%); AP: Aeration porosity (%); RP: Retention porosity (%). ANOVA of one Factor, Tukey P<0.05. Different letters in the same row indicate significant differences among elevations ranged from 601 to 1000 m.a.s.l.

Table 3. Means and standard deviation of the soil chemical properties as a function of altitude and soil depth.

Altitudinal gradient (m.a.s.l)
	600-700	701-800	801-900	901-1000
Variable	Soil depth 0-10 cm				F value	P
pH	4,42 ± 0,17^a	4,53 ± 0,25^a	4,57 ± 0,18^a	4,51 ± 0,20^a	1,368	0,262
Al³⁺ + H⁺	4,45 ± 1,51^a	2,97 ± 1,53^a	3,55 ± 1,80^a	3,61 ± 1,62^a	2,055	0,117
Al³⁺	1,41 ± 0,5^a	0,99 ± 0,37^a	1,47 ± 0,31^a	1,29 ± 0,29^a	0,742	0,531
TN	0,25 ± 0,04^c	0,30 ± 0,03^c	0,38 ± 0,11^b	0,50 ± 0,10^a	25,918	0,000
SOM	3,53 ± 0,39^b	4,65 ± 0,83^b	6,33 ± 1,02^a	6,41 ± 1,04^a	8,527	0,000
P	12,93 ± 2,56^a	12,00 ± 1,51^a	9,11 ± 1,02^b	10,51 ± 0,92^b	15,798	0,000
K⁺	1,99 ± 0,09^a	3,15 ± 0,46^a	0,09 ± 0,01^b	0,07 ± 0,01^b	20,518	0,000
Ca²⁺	0,12 ± 0,04^b	0,09 ± 0,01^b	3,15 ± 0,50^a	2,54 ± 0,30^a	37,570	0,000
Mg²⁺	1,34 ± 0,53^a	1,36 ± 0,62^a	1,47 ± 0,58^a	1,06 ± 0,50^a	0,813	0,492
Soil depth 10-30 cm
pH	4,65 ± 0,12^a	4,75 ± 0,19^a	4,70 ± 0,17^a	4,67 ± 0,18^a	0,906	0,444
Al³⁺ + H⁺	5,81 ± 1,18^a	4,93 ± 1,54^a	4,59 ± 1,63^a	3,26 ± 1,22^b	3,184	0,031
Al³⁺	1,51 ± 0,76^a	2,05 ± 1,06^a	1,46± 0,30^a	1,02± 0,50^a	2,177	0,101
TN	0,13 ± 0,03^c	0,14 ± 0,04^c	0,23 ± 0,10^b	0,31 ± 0,08^a	24,820	0,000
SOM	1,84 ± 0,3^b	2,29 ± 0,5^b	3,05 ± 0,76^a	3,95 ± 0,74^a	5,334	0,003
P	9,19 ± 1,67^a	9,43 ± 1,66^a	6,95 ± 0,62^b	8,55 ± 0,91^a	11,172	0,000
K⁺	1,35 ± 0,55^a	1,94 ± 0,60^a	0,06 ± 0,02^b	0,03 ± 0,01^b	24,180	0,000
Ca²⁺	0,06 ± 0,02^b	0,04 ± 0,01^b	2,07 ± 0,96^a	1,61 ± 0,54^a	27,429	0,000
Mg²⁺	1,40 ± 0,40^a	1,06 ± 0,35^a	1,28 ± 0,28^a	0,86 ± 0,12^a	1,162	0,332

Al³⁺ + H⁺:Exchangeable soil acidity (meq 100 g^-1); Al³⁺: Exchangeable aluminum (meq 100 g^-1); TN: Total Nitrogen (%); SOM: Soil organic matter (%); P: Phosphorus available (mg kg^-1); K⁺: Exchangeable potassium (meq 100 g^-1); Ca²⁺: Exchangeable calcium (meq 100 g^-1); Mg²⁺: Exchangeable magnesium (meq 100 g^-1); unidirectional ANOVA Tukey P<0.05. Different letters in the same row indicate significant differences among elevations ranged from 601 to 1000 m.a.s.l.

Table 4. Pearson correlations coefficients between soil properties in 0-10 cm depth and altitude

	Altitude	BD	Ksat	TP	AP	RP	pH	Al³⁺ + H⁺	Al³⁺	SOM	TN	P	K⁺	Ca²⁺	Mg²⁺
Altitude	1.00
BD	-0.73**	1.00
K_sat	0.60**	-0.60**	1.00
TP	0.64**	-0.09**	0.62**	1.00
AP	-0.27	0.04	-0.38	-0.09	1.00
RP	0.63**	-0.68**	0.68**	0.77**	-0.70**	1.00
pH	0.29	0.01	0.06	0.07	-0.06	0.09	1.00
Al³⁺ + H⁺	-0.15	-0.16	0.07	0.08	-0.15	0.15	-0.69**	1.00
Al³⁺	0.05	-0.26	0.12	0.19	-0.12	0.21	-0.30	0.79**	1.00
SOM	0.76**	-0.73**	0.40	0.71**	0.04	0.49*	0.29	-0.20	0.04	1.00
TN	0.90**	-0.78**	0.61**	0.75**	-0.21	0.67**	0.23	-0.19	0.01	0.81**	1.00
P	-0.66**	0.48*	-0.16	-0.41	-0.10	-0.23	-0.48*	0.33	0.02	-0.67**	-0.53*	1.00
K⁺	-0.57**	0.55*	-0.34	-0.35	0.04	-0.27	0.40	-0.44	-0.42	-0.41	-0.44	0.52*	1.00
Ca²⁺	0.79**	-0.71**	0.34	0.55*	-0.05	0.43	0.28	0.03	0.31	0.70**	0.70**	-0.80**	-0.66**	1.00
Mg²⁺	-0.14	-0.06	-0.12	0.09	0.14	-0.02	0.59**	-0.22	0.00	-0.03	-0.10	-0.09	0.48*	0.19	1.00

BD: Bulk density (Mg m^-3); K_sat: Saturated hydraulic conductivity (cm h^-1); TP: Total porosity (%); AP: Aeration porosity (%); RP: Retention porosity (%); Al³⁺ + H⁺:Exchangeable soil acidity (meq 100 g^-1); Al³⁺: Exchangeable aluminum (meq 100 g^-1); TN: Total Nitrogen (%); SOM: Soil organic matter (%); P: Phosphorus available (mg kg^-1); K⁺: Exchangeable potassium (meq 100 g^-1); Ca²⁺: Exchangeable calcium (meq 100 g^-1); Mg²⁺: Exchangeable magnesium (meq 100 g^-1).

* P<0.05; ** P<0.01

Table 5. Pearson correlations coefficients between soil properties in 10-30 cm depth and altitude

	Altitude	BD	Ksat	TP	AP	RP	pH	Al³⁺+ H⁺	Al³⁺	SOM	TN	P	K⁺	Ca²⁺	Mg²⁺
Altitude	1,00
BD	-0.80**	1,00
K_sat	0.59**	-0.63**	1,00
TP	0.56*	-0.89**	0.42	1,00
AP	-0.18	-0.04	0.25	-0.04	1,00
RP	0.55*	-0.72**	0.227	0.86**	-0.55*	1,00
pH	-0.05	0.22	-0.23	-0.21	0.21	-0.29	1,00
Al³⁺+ H⁺	-0.52*	0.50*	-0.40	-0.36	-0.15	-0.22	-0.22	1,00
Al³⁺	-0.31	0.41	-0.32	-0.38	-0.10	-0.26	-0.05	0.71**	1,00
SOM	0.63**	-0.82**	0.60**	0.67**	0.21	0.46*	-0.23	-0.28	-0.09	1,00
TN	0.84**	-0.92**	0.67**	0.75**	-0.01	0.63**	-0.19	-0.44	-0.30	0.85**	1,00
P	-0.41	0.19	-0.07	-0.06	0.08	-0.03	0.09	0.09	0.04	-0.153	-0.28	1,00
K⁺	-0.63**	0.54*	-0.37	-0.38	0.02	-0.33	0.49*	0.11	0.13	-0.40	-0.57**	0.73**	1,00
Ca²⁺	0.74**	-0.67**	0.21	0.50*	-0.12	0.51*	0.01	-0.24	-0.31	0.50*	0.67**	-0.62**	-0.68**	1,00
Mg²⁺	-0.24	0.08	-0.40	0.12	-0.08	0.15	0.32	0.30	-0.03	-0.01	-0.18	0.14	0.32	0.25	1,00

BD: Bulk density (Mg m^-3); K_sat: Saturated hydraulic conductivity (cm h^-1); TP: Total porosity (%); AP: Aeration porosity (%); RP: Retention porosity (%); Al³⁺ + H⁺:Exchangeable soil acidity (meq 100 g^-1); Al³⁺: Exchangeable aluminum (meq 100 g^-1); TN: Total Nitrogen (%); SOM: Soil organic matter (%); P: Phosphorus available (mg kg^-1); K⁺: Exchangeable potassium (meq 100 g^-1); Ca²⁺: Exchangeable calcium (meq 100 g^-1); Mg²⁺: Exchangeable magnesium (meq 100 g^-1).

P<0.05; ** P<0.01

No competing interests reported.

Soil properties variation in a small-scale altitudinal gradient of an evergreen foothills forest, Ecuadorian Amazon Region

Status:

Journal Publication

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Abstract

Figures

1. Introduction

2. Material And Methods

3. Results

4. Discussion

5. Conclusions

References

tables

Additional Declarations

Status:

Journal Publication

Version 1