Assesing Infiltration Rate and Soil Physical Properties at Different Vegetation Densities in the Jasinga Silviculture Teaching Industry (JSTI) Area

The Jasinga Silviculture Teaching Industry (JSTI) area is a research forest with ecosystem conditions that have yet to be widely known. Research on the local ecosystem is needed, especially regarding vegetation, soil, and the hydrological cycle. Vegetation densities in the JSTI area are uneven, which affects groundwater absorption (infiltration rate). This study aimed to identify the infiltration rate and soil physical properties at different vegetation densities. The research plot was determined through purposive sampling techniques based on the level of vegetation density. The research methods carried out were analysis of vegetation density and composition, identification of soil physical properties (such as organic matter content, bulk density, porosity, and moisture content), measuring field infiltration rates using a double-ring infiltrometer, and analyzed the Spearman correlation. The results showed that dense vegetation has the highest score of organic matter content (> 4%), the bulk density is moderate, the porous category dominates the porosity, and the water content and infiltration rate were greater than sparse vegetation plots. Therefore, it is recommended to carry out planting activities at sparse vegetation density in the JSTI area.


Introduction
Forests are natural resources that have an important role in maintaining ecosystem balance.The presence of vegetation in a forest ecosystem is one factor that greatly affects the infiltration rate and the soil's physical properties.Infiltration is vertically entering the water through the soil surface into the inner soil.The amount of water per unit of time entering through the ground surface is expressed in mm/hour or cm/hour, called the infiltration rate [4].[18] stated that the forest canopy will have a significant impact on the solar radiation reaching the ground surface.The sunlight that eventually reaches the ground surface will be greatly reduced.High light intensity results in greater evaporation of groundwater [38].Canopy strata can also block rainwater blows against the soil surface, which can damage soil structure [18].[12] suggest that soil's physical properties in moisture content, porosity, bulk density, and soil organic matter content formed in forest ecosystems are closely related to vegetation density.High quality of infiltration rates and soil properties will optimize groundwater availability, minimize the rate of erosion and surface runoff, and streamline irrigation and drainage [31].
Jasinga Silviculture Teaching Industry (JSTI) is an area for research and development in forestry.The condition of the JSTI ecosystem still needs to be widely known, so research related to vegetation IOP Publishing doi:10.1088/1755-1315/1315/1/012036 2 and its effects on the ecosystem is considered necessary as the initial stage of area development.JSTI areas have land cover areas with different vegetation types, so the canopy density will also be different.This is considered to affect the soil physical properties and the amount of water infiltration that enters the soil [17].Low infiltration rate and poor soil physical properties will cause runoff water and erosion rates that tend to be high.This will certainly damage the existing ecosystem.Further handling of these adverse impacts can be done if the the infiltration rate and physical properties of the soil are known.Therefore, the JSTI area was chosen as the research location.

Method
The study consisted of five implementation stages, wich is determining the research plot, measuring crown density and stand composition, soil sampling, soil infiltration rate, and data analysis.

Determination of the research plot
The location of the research plot was determined using purposive sampling techniques, namely selecting plots based on certain criteria and objectives [6].Plots were selected based on two crown density criteria.The criteria consist of vegetation with dense and sparse canopies.Both canopy criteria are suspected to have a strong influence on infiltration rate and soil physical properties.Vegetation with a moderate canopy is not chosen as a measurement criterion, because according to [1], the influence of infiltration rate and soil physical properties on vegetation with a moderate canopy does not differ significantly from the criteria for dense canopy vegetation.The sampling intensity used is 6% of the total area of JSTI.This is according to the calculation of representation of [26], which states that forests with an area of less than 1,000 ha can use a sampling intensity of more than 5%.Based on the predetermined sampling intensity, the plots in each vegetation density are 25 m x 40 m, with the number of dense and sparse vegetation plots as many as three plots each (Figure 1).The land cover map in Figure 1 was created using ArcGIS software to classify two types of vegetation crown density through the Normalized Difference Vegetation Index (NDVI) method.[27] suggest that NDVI can accurately reflect surface vegetation crown conditions by reflecting different types of light waves.Landsat-8 band 4 and 5 imagery is used as reflectance data for electromagnetic radiation at specific wavelengths.

Measurement of crown density and stand composition
Crown density measurement using the CanopyApp application on plots pre-classified through a delineation map.This application uses a digital densitometer method with built-in processing capabilities to monitor forest canopy cover in the field.A photo of the vegetation crown density was taken from under the stand and marked the area containing the crown vegetation for the masking process.The accelerometer feature will calculate the percentage of crown density if the masking process has been recorded [7; 32].Crown density measurements were made at three points in each plot and then averaged.
The composition of stands was analyzed on the growth rate of saplings (saplings with a height of 1.5 m and a diameter of <10 cm), poles (saplings 10-20 cm in diameter), and trees (mature trees with a diameter of >20 cm) [15].Each plot of 25 m x 40 m is divided into two subplots to analyze vegetation composition.The size of the subplot is determined based on the species-area curve (KSA), which is 8 m x 16 m for the pile level and 25 m x 40 m for the pole and tree level (Figure 2).Measurements of the diameter of stakes, poles, and trees were carried out on diameter at breast height (dbh), which is 1.3 m, using phibands.

Soil sampling
Soil samples consist of non-destructive soil samples to analyze bulk density, porosity, moisture content, and destructive soil samples to analyze soil organic matter content.Non-destructive soil is soil that has not been disturbed by external factors and has the same aggregate, particles, and size distribution as the place of origin, while the destructive soil is instead [23].Sampling soil in each plot was carried out diagonally three times (Figure 3).The total samples were 12 samples each.Non-destructive soil samples were taken using ring samples.Trenches are needed to take intact soil so that soil aggregates are not damaged while facilitating ring removal.The ring sample is pressed using auxiliary rings, machetes, and hammerheads.Destructive soil is taken at a depth of 10 cm to 20 cm using a soil drill [1].

Measurement of soil infiltration rate
The infiltration rate was measured using a double-ring infiltrometer [3].Measurements were made in each plot.The ring is installed slowly to prevent damage to the soil aggregate.According to [1], the ring is pressed into the ground up to 3-5 cm with tools in the form of hammers and blocks to balance the placement.The ruler is placed perpendicular to the inner ring.Water is fed into the outer ring hole and then the inside in a balanced manner.The decrease in water level is recorded at predetermined intervals until the infiltration rate is constant.
The infiltration rate is determined by measuring the water level's decrease every 2 minutes in the first 30 minutes, 5 minutes in the 30 to 60 minute, and every 15 minutes until a constant rate is obtained.The measurement is stopped when the decrease in water level has been constant at least four times in a row [8].The already constant decrease in water level is used to determine the infiltration rate.Data obtained in the field is processed using Microsoft Excel 2019.The following equation is used to determine the value of the infiltration rate capacity: FT : Infiltration rate (cm/h) Δh : height of water drop (cm) The results of the calculation of infiltration rate capacity are classified according to the interval class in Table 1.Very fast >25

Analysis of the soil physical properties 2.5.1. Soil organic matter content
Determination of soil organic matter levels using destructive soil samples.The soil is weighed at 200 g per sample, set as the total mass, and then fed into aluminium foil.Soil samples were opened at a temperature of 105 o C for 24 hours, which they were weighed and obtained a solid mass.The second oven process was carried out on the same soil sample with a temperature of 200 o C for 24 hours, which it was weighed (MK).The soil organic matter content in each sample is calculated using the formula:

Porosity
The porosity value can be known through the calculation method from the results of bulk density analysis using the formula: (5) Description: BI = weight of soil content/bulk density (cm 3 ) BP = weight of soil particles (g cm -3 ) = 2.65 g cm -3   The calculated values are classified according to the soil porosity class described in Table 2. Very bad <30

Water content
Soil samples in ring samples without lids are watered to maximum capacity (saturated), then allowed to dry the air for two days.The weighing of soil samples in an air-dried ring (BK1) was carried out.Soil samples that have been weighed are then opened at 105 o C for 24 hours and weighed (BK2).The moisture content of field capacity (KL) can be calculated using the formula:

Spearman correlation test
The Spearman correlation test was carried out between the parameters of vegetation density, soil physical properties, and field infiltration rate values through correlation coefficients and scatterplots in RStudio software.According to [21], this analysis was carried out to see the level of strength (closeness), the direction of the relationship, and the significance between parameters.The Spearman correlation coefficient is calculated using the following equation [35]: = amount of data The Spearman correlation test was chosen to make the resulting coefficient more accurate because the repeat data used was less than 30 samples [22].

Overview of the research site
The research location is in the Jasinga Silviculture Teaching Industry (JSTI) area, Jasinga District, Bogor Regency, West Java.The area of JSTI is ±9.3 ha (6.1 ha densely vegetated and 3.2 ha sparsely vegetated) with an altitude of ±250 meters above sea level and an average rainfall of 4,267 mm/year [20].JSTI areas have an undulating topography with a dominant slope of 26%-45%.
Field data were collected on six plots selected based on vegetation crown density criteria.There are the first dense vegetation plot (R1), the second dense vegetation plot (R2), the third dense vegetation plot (R3), the first sparse vegetation plot (J1), the second sparse vegetation plot (J2), and the third sparse vegetation plot (J3).

Vegetation density and vegetation composition
The highest percentage of crown density was found in plot R3 (60.31%), followed by plot R1 (56.10%) and R2 (50.96%).The J2 plot has the lowest crown density percentage of 9.28%, followed by the J1 plot (13.27%) and the J3 plot (20.46%).The diversity of individuals in the growth rate of stakes, poles, and trees greatly affects the density of the vegetation canopy.The three growth rates have clear qualitative differences in vegetation composition.The composition of vegetation growth rates in each plot is shown in Figure 4.The composition of the growth rate in each plot (Figure 4) shows that the large number of individuals in the vegetation composition tends to align with the crown density in each plot.R3 plots have the highest vegetation composition at stakes (36 individuals) and poles (13 individuals) compared to plots R1 and R2.The J2 plot has the lowest vegetation composition because only nine individual stake-level vegetation exists.The J1 plot has a vegetation composition that tends to be high, but the canopy density is low (13.27%)due to the steep slope factor.[14] explained that differences in succession processes cause variations in the number of types found in each plot.The success of the succession process is influenced by the genetic factors of each type and the environment in which it grows.

Soil organic matter content
Soil organic matter is the remains of plant parts or other living things that have died and decomposed in the soil.The addition of soil organic matter levels has an effect on decreasing the weight of soil contents, increasing total pore space, and increasing drainage pore space [16].[30] examined the role of organic matter as an adhesive for soil particles, which can increase soil aggregation and pore space and reduce soil bulk density.This is due to the porous nature of organic matter, which will create pore space when it enters the soil.

Figure 5. Soil organic matter levels of each plot
The results of the analysis of soil organic matter levels on each plot are shown in Figure 5.It was found that the soil organic matter rate in each plot was high (>4%) [12].The lowest average value of soil organic matter levels was found in plot J2 (14.47%), while levels in other plots were not significantly different (Figure 5).Soil organic matter levels are closely related to vegetation above ground.J2 plots have the lowest soil organic matter levels due to the lowest vegetation density compared to other plots.This is following the research of [9], it is known that the denser the vegetation, the vegetation composition will be higher which causes the soil organic matter content to be greater.The amount of litter will be more, so the greater the decomposition process by microorganisms will increase the level of soil organic matter.

Porosity
According to [33], soil porosity is the percentage of soil volume not occupied by solid grains and consists of space between sand, dust, and klei particles and space between soil aggregates.Soil porosity is closely related to vegetation density [29].Figure 6 shows the soil porosity analysis results on each plot.Based on Figure 6, soil porosity tends to be constant and have values that fall into the class of porous.The highest porosity mean value was found in plot R1 (71.12%), while the lowest in plot J2 (58.88%).Soil porosity is influenced by the content of organic material derived from vegetation above the soil and the root system in the soil.Dense vegetation has a higher organic matter content, so the soil structure is more crumb/granular [10].Crumbly soil will have a high porosity value.The roots of vegetation growth rate poles and trees can reach deeper soil, so there will be more space in the ground [36].The porosity value of the soil will be higher when there is much space in the soil [30].

Bulk density
The parameter of soil density through the ratio of the dry weight of soil to units of soil volume is called bulk density or weight of soil content [28].The higher the bulk density value, the denser the soil.Increasingly porous soil will decrease the value of bulk density.Figure 7 shows the dynamics of bulk density on each plot.According to the [34] classification, the average value of bulk density in each plot produced is classified as medium category (0.6-1.2 g cm -3 ).Root growth will be hampered if the bulk density value is classified as a very heavy category (>1.65 g cm -3 ).The J2 plot had the highest average bulk density value (1.09 g cm -3 ), while the lowest mean value was found in the R1 plot (0.77 g cm -3 ).[12] stated that dense vegetation will minimize soil compaction caused by rainwater.The influence of organic matter levels can also maintain soil temperature and moisture and increase moisture content and soil microorganism activity so that the soil tends to be loose.

Soil moisture content
Soil water content is a comparison of groundwater weight to wet and dry weight of soil [12].The moisture content in the soil can increase depending on the water supply.According to [4], the soil water Bulk Density (g cm -3 ) content will increase when there is rain.The value of soil moisture content at different densities can be seen in Figure 8.

Figure 8. Soil moisture content of each plot
Soil moisture content in Figure 8 is considered quite significant.The highest soil moisture content was found in plot R1 (56.12%).Dense plots (R1, R2, and R3) have soil moisture content values that tend to be high >50%, compared to sparse density plots.This is because denser vegetation cover increases soil moisture, so soil water content tends to be large because groundwater loss can be minimized [25].
The J2 plot has the lowest soil moisture content value of 37.65%.Land cover with vegetation rarely has low groundwater content due to the lack of vegetation cover in minimizing high evaporation by sun exposure.J3 plot has a fairly high moisture content value (55.92%) because the stand composition of the existing density makes the soil porosity value (69.67%) and soil organic matter content (27.72%) tend to be high.This is supported by [4], who stated that the ability of the soil to escape and store water is greater if the porosity and soil organic matter levels tend to be high.

Infiltration rate
Infiltration is the vertically entering water into the soil, reaching a saturated layer of water, and becoming a groundwater flow [4].According to [2], the infiltration rate has a complex interaction with the rain intensity (water supply rate).The infiltration rate will be equal to the intensity of rain if the intensity is less than the infiltration capacity.However, waterlogging and surface flow will occur when the rain intensity exceeds the infiltration capacity due to saturated soil.

Figure 9. Field infiltration rate on each plot
High vegetation composition will increase the infiltration rate due to growth activities that require water in the process.In addition, the rate of erosion and flooding due to surface flow (runoff) will be minimized if the soil infiltration rate is high.The results of measuring the infiltration rate in the field can be seen in Figure 9, while the infiltration rate and its class capacity are in Table 5. [8] suggest that the capacity of the infiltration rate can be determined when the rate of water decline becomes constant.This indicates that the soil is already in a saturated condition.Figure 9 shows that the infiltration rate on plot R1 is constant as it enters the 0.13 hour (8 minute); constant plot R2 in the 0.23 hour (14 minute); constant plots R3, J1 and J2 in the 0.17 hour (10 minute); as well as a constant J3 plot in the 0.07 hour (4 minute).4, plot R1 has the highest field infiltration rate capacity (30 cm/h) with a very fast class.The lowest infiltration rate capacity was found in plots J1 and J2 (1.5 cm/h) with a rather slow class.Dense vegetation plots (R1, R2, and R3) tend to have a larger infiltration capacity than sparse plots.The difference in infiltration rates is due to vegetation factors and the physical properties of the soil.Dense plots have a more varied vegetation composition at both stake, pole, and tree levels with a high crown density.According to [11], the presence of the roots of vegetation will create space that can be filled by water and strengthen soil aggregates.[5] said that organic matter levels will increase if the closure of the crown is tighter.This will encourage the activity of organisms on the soil surface, such as ants, worms, ureters, and other insects that form soil macropores.Hence, the infiltration rate capacity tends to be high.Dense plots have high soil moisture content but low bulk density values and high porosity.Thus, the infiltration rate on dense plots tends to be faster than on sparsely vegetated plots.Figure 10 shows the correlation between the analyzed parameters.The results of the Spearman correlation test between vegetation density, soil physical properties, and infiltration rate are tabulated in Table 5.Based on Table 6, vegetation density has been shown to affect soil physical properties parameters and infiltration rates through formed correlations.The stronger the correlation indicates that the resulting influence will be more visible.It can be seen from the correlation value that higher vegetation density will reduce bulk density and increase porosity, moisture content, soil organic matter, and infiltration rate.The lowest correlation value was found in the density parameter with soil organic matter (0.26).According to [19], this can be caused by too few test samples or other influence factors that have yet to be analyzed.Other possible influencing factors are slope and soil permeability [24].

Conclusions
Different vegetation densities in the Jasinga Silviculture Teaching Industry (JSTI) area greatly affect the soil's physical properties and the infiltration rate.Dense vegetation forms good soil physical properties with low bulk density values and high porosity, moisture content, and organic matter values.The infiltration rate produced by dense vegetation has been shown to be higher than that of sparse vege tation.Planting activities with dominant types and according to forest management objectives must be carried out, especially in sparse vegetation density.This is one of the efforts to conserve soil and water so that the physical properties of the soil and the resulting infiltration rate are getting better.Thus, the forest ecosystem formed will be more stable and minimize the occurrence of disasters such as runoff and erosion.

Figure 1 .
Figure 1.Location of research plots based on vegetation density in the JSTI area.

Figure 3 .
Figure 3. Subplot of soil sampling and infiltration rate measurement.
2) Description: SOM = soil organic matter content (%) MS = solid mass (g) MK = dry mass (g) MT = total mass (g) 2.5.2.Bulk density Soil samples in rings without lids are weighed to determine the weight of the field soil (BB).Oven process is carried out for 24 hours at a temperature of 105 o C, then weighed to determine the weight of the dry soil (BK1).The soil sample in the ring is discarded, and the weight of the ring sample is weighed (BR).The dry weight value of the soil sample without (BK) is found through the equation BK = BK1 -BR.The value of bulk density is set using the formula: = bulk density (g cm -3 ) BK = dry weight (g) Vt = volume of soil in the sample ring (cm -3 ) d = inner diameter of the ring (cm) t = sample ring height (cm) 1315 (2024) 012036 IOP Publishing doi:10.1088/1755-1315/1315/1/0120365

Figure 4 .
Figure 4. Composition of vegetation growth rate in each study plot.

Figure 7 .
Figure 7. Bulk density of each plot.

Table 4 .
Field infiltration rate capacity on each plot.

Table 5 .
Tabulation of Spearman correlation test result data.