Study area

This research was conducted at the Botana Experimental Farm (BEF), which belongs to University of Nariño (Colombia; Fig. 1). The farm is located at 77º18’58” W and 1º10’11.4” N and 2820 m above sea level.

The average annual total rainfall is 796 mm, with a f irst rainy season from October, to December, and a second from March to May. The dry season goes from June to August. The average temperature is 12.8 ºC, with a maximum temperature up to 20°C and a minimum temperature around 9.5 ºC. The relative humidity ranges from 74 to 80%, being higher in the rainy season from October to December. (IDEAM, 2014).

The life zone of BEF belongs to a lower montane humid forest (Cabrera & Muñoz, 2013). The geological record shows undifferentiated volcanic deposits from intercalations of lavas, pyroclastic, fluvio-glacial deposits and lahars in different proportions, with a high degree of fracturing (Colombian Geological Service, 2015). BEF is surrounded by landscapes such as plateaus, hills and mountains (IGAC, 2004).

According to IGAC (2004) there are two andosol types in BEF (Fig. 1B), Vitric Haplustands, and Acrudoxic Hapludands (Table S1 [suppl.]), both very close in physical-chemical configuration. Vitric Haplustands are characterized by deep horizons, good drainage, moderately thick textures, strong acidity, low fertility, high aluminum saturation, and high organic matter contents, whilst Acrudoxic Hapludands are characterized by deep horizons, moderately thick textures, well drained, very strongly acidic, low fertility, high aluminum saturation and high organic matter contents.

 

Study design and sampling

The study area is divided in six soil uses (SU; Fig. 1) because of the historical farm managements during the last 20 years. These SU’s are:

1. Potato crop (POCR) (Solanum tuberosum L.), with a total area of 0.23 ha and a slope ranging from 12 to 25% in S-N direction. Soil under POCR has been subject to chemical fertilizers and pesticides since year 2005.

2. Pasture (PAST) Pennisetum clandestinum Hochst. ex Chiov., with a total area of 1.0 ha, a loading capacity of 3.0 AU ha-1 (Holstein cattle) and a slope higher than 50% in E-W direction. This system has been kept invariant during the last 10 years.

3. Alley cropping of Alder Trees (ACAL), stablished since year 2002. This AFS has a total area of 0.46 ha and 172 trees arranged in rows of six trees in NW-SE orientation (equivalent tree density: 374 trees ha-1). Distance between rows is 5 m and between trees 3 m. The slope ranges from 25 to 50% in S-N direction.

4. Scattered Alder Trees (SCAL) (Alnus acuminata Kunth) stablished since year 2000. This AFS has a total area of 0.72 ha and 57 trees (equivalent tree density: 79 trees ha-1) associated with P. clandestinum. This system has a loading capacity of 4.5 AU ha-1 (Holstein cattle) and a slope ranging from 12-25% in SE-NW direction.

5. Alley cropping of Wax Laurel (ACWL) (Morella pubescens (Humb. & Bonpl.) Wilbur), stablished since year 2000 (Ramírez et al., 2002). This AFS has a total area of 0.3 ha, 83 trees (equivalent tree density: 277 trees ha-1) with a planting distance of 6.0 m, and a slope ranging from 12-25% in SE-NW direction.

6. Secondary Forest (SEFO), under conservation since year 1953, composed by 34 plant species but dominated by M. pubescens, Myrisine coriaceae (Sw.) Roem and Schult, Viburnum triphyllum Benth. and Vallea stipularis Mutis ex. L.F. (Argotty & Collazos, 2001). SEFO has a total area of 40 ha and a slope ranging from 25-50% in S-N direction. SEFO was considered in this study as a reference to compare with the rest of SU’s. This was because the soil under this SU has experimented nearly 60 yr of natural soil restoration and currently is under strict protection from any kind of anthropogenic perturbation. Thus, we assumed that SEFO would reflect the best physical and chemical soil conditions.

SU’s were divided in three plots (high, mid, and low, according to the slope; Fig. 1). Ten soil samples were randomly taken from each plot, following a zig-zag-pattern that covered the whole SU (IGAC, 2014; FAO, 2018). Soil samples from each plot were mixed and homogenized to obtain two representative samples. Only five random samples were taken from POCR and PAST plots, following the same zig-zag pattern as mentioned above. These were mixed and homogenized to obtain one representative soil sample from each plot.

Only the low part of SEFO was sampled because the mid and high parts belong to a different soil type from the rest of SU’s (Fig. 1). This resulted in only one plot stablished at SEFO and hence, only one value for each soil variable was available at this SU for further data analyzes.

 

Figure 1.  A) Map of the Botana Experimental Farm showing the studied Soil Uses. Black dots represent the sampling sites within each SU. Alley cropping of Wax Laurel (ACWL), Scattered Alder Trees (SCAL), Alley cropping of Alder Trees (ACAL), Potato crop (POCR), Pasture (PAST), Secondary Forest (SEFO). B) Map of soil types in the study area.

 

 

Measurement of physical and chemical soil variables

After extraction, soil samples were labeled and transported to University of Nariño (Colombia) to be immediately analyzed. A total of 12 physical and chemical soil variables were measured in each soil sample directly in the laboratory, and 3 variables were computed later using equations and previously measured variables. Six of the variables measured at the laboratory were not directly included in subsequent statistical analysis, but indirectly as parameters in equations for computed variables. Therefore, nine final variables were used for further statistical analysis. Table S2 [suppl.] lists these variables and the methods followed for their measurements. Previous soil data from SEFO (Enríquez & Goyes 2018) was used as reference values to allow for additional comparisons against the rest of SU’s.

 

Statistical analysis of data

A Principal Component Analysis (PCA) with a correlation matrix was performed in order to first explore the variability of physical-chemical soil variables among SU’s. Later, simple Analyzes of Variance (ANOVA) were performed taking every soil variable as response, and SU as a fixed factor. Since only one mean value was available for SEFO, the statistical significance of the differences between SEFO and each SU was tested using the Dunnet’s test for multiple comparisons against a single reference value, followed by Bonferroni adjustments of p-values to control for family-wise error rate (FWER) (R-package ‘multcomp’) (Hothorn et al. 2021). The difference among SU’s excluding SEFO, was assessed by visually inspecting their 95% confidence intervals (CI) (Cumming et al. 2007). All the analyzes were performed in R-studio version 3.4.1 (R-studio Team, 2019), and α = 0.05 was used as the significance threshold.

 

ResultsTop

The two first Principal Components (PC1 and PC2) explained 64.5% of the original variance in the physical and chemical soil variables (PC1 = 47.3%, PC2 = 16.7%) (Fig. 2). This percentage of variance was considered satisfactory as the result of the reduction in data dimensionality, and hence, these two components were kept and used to interpret the variability among SU’s. By inspecting the correlation coefficients (r) between PC’s and the original soil variables, it was observed that PC1 was mainly correlated with OC (-0.42), CEC (-0.41), CLA (0.37), BD (0.39) and BS (0.39), whilst PC2 was with pH (0.36), POR (0.40), INF (-0.56), and AWC (-0.49) (Table 1). The scatter plot of Fig. 2 show that SEFO is located far to the left of graph in the first quartile of PC1. By examining PCA loadings (arrows), this position is characterized by the highest levels of OC and CEC, and the lowest levels of CLA, BS and BD. Next to SEFO to the right, ACWL plots are grouped within the second quartile of PC1, showing the second highest levels of OC and CEC, and the second lowest levels of CLA, BS and BD. Next to the right between the second and third quartile, most of the SCAL, PAST, POCR and ACAL plots are mixed, and finally, a few samples from POCR and ACAL are found within the fourth quartile, showing the lowest levels of CEC and OC, and the higher levels of CLA, BS and BD.

The variability of SU’s throughout PC2 was not so clear as for PC1, however two interesting observations are the highest pH for two plots from PAST and the lowest INF for a plot from POCR. For the rest of soil variables, no further among-SU differentiation was observed in PC2.

Fig. 3 show the statistical comparison of mean values among SU’s for each soil variable, and for SEFO against the each of the other SU’s. Mean OC in SEFO (10%) was the highest, and was significantly different from all SU’s. Mean OC in ACWL (5.66%) was the most similar to SEFO, and also, the most similar to the mean OC value from Enriquez & Goyes (2018) (6.7%). CI of mean OC in AWCL did not overlap with the CI’s from the rest of SU’s, indicating significant differences. CI’s from SCAL, POCR, PAST and ACAL did overlap, pointing to significantly lower mean OC values compared to SEFO and ACAL. Results for CEC similar. SEFO showed the highest mean CEC for both our data (45.2 cmol+‧kg-1) and the data from Enriquez & Goyes (2018) (36.3 cmol+‧kg-1), and AWCL showed the second highest mean value (29.8 cmol+‧kg-1). Means of SCAL, POCR, PAST and ACAL were significantly lower, with values below 25 cmol+‧kg-1.

For CLA, SEFO showed the lowest mean value (7%) both in our data and in the data from Enriquez & Goyes (2018) (7.1%), but significant differences were detected only for POCR and ACAL (28.5 and 36.4 % of CLA percentage respectively). Again, for this variable, ACWL showed the most similar mean value to SEFO.

BD did not differ significantly among SU’s, however, ACWL and SEFO showed the lowest values both in our data and in the data from Enriquez & Goyes (2018) (0.73, 0.77 and 0.70 Mg/m3 respectively). POR did not show significant differences among SU’s, although SEFO had the highest mean values both in our data (69.6%) and in the data from Enriquez & Goyes (2018) (70%). For BS, only POCR and ACAL showed significantly higher means compared to SEFO, which had the lowest value (19%). For INF, only PAST were significantly lower than SEFO, and for pH and AWC, there were no significant differences among SU’s. No data was available for BS, INF and AWC from Enríquez & Goyes (2018).

 

 

Figure 2.  Scatterplot of scores from Principal Component Analysis performed to soil variables in plots under different soil uses in the study area. Dotted vertical gray lines represents the limits of quartiles for PC1. Alley cropping of Wax Laurel (ACWL), Scattered Alder Trees (SCAL), Alley cropping of Alder Trees (ACAL), Potato crop (POCR), Pasture (PAST), Secondary Forest (SEFO).

 

Table 1. Loadings of every physical and chemical soil variable on PC1 and PC2. Only variables with the higher loadings are shown

OC: Soil Organic Carbon; CEC: Cation Exchange Capacity; CLA: Clay; BD: Bulk Density; BS: Base saturation; pH; POR: Soil Porosity; INF: Infiltration; AWC: Available water capacity.

 

 

Figure 3. Comparison of mean values of soil variables among soil uses in the study area. Horizontal red line represent the mean value from SEFO and horizontal blue line the mean value from Enríquez & Goyes (2018). Vertical black bars represent 95% confidence intervals, and asterisks the significance of the difference between SEFO and each of the SU’s according to Dunnet’s test with bonferroni adjustments. * p<0.05; ** p<0.01; *** p<0.001. Dunnet’s test were performed only for the red line. Alley cropping of Wax Laurel (ACWL), Scattered Alder Trees (SCAL), Alley cropping of Alder Trees (ACAL), Potato crop (POCR), Pasture (PAST), Secondary Forest (SEFO).