Comparative analysis of soil from mixed forest Habitats in Southern Western Ghats

 

Nisha Thomas1, M. G. Sanal Kumar2

1Department of Zoology, St. Johns College, Anchal, 691306, Kerala, India.

2Department of Zoology, N.S.S. College, Pandalam, 689501, Kerala, India.

*Corresponding Author E-mail: nishathomas09@gmail.com

 

Abstract:

A study was conducted on the physical and chemical properties of the soil of Chittar forest station, Vadasserikkara range, in Ranni Forest Reserve, Kerala. Vadasserikkara range lies to the eastern part of Ranni, with its headquarters at Vadasserikkara. It covers an area of almost 268 square kilometres of the Ranni Forest Division. The major tributaries of the River Pamba - Kakkad and Kallar, flows through this range. The three different forest type seen in this range are-west coast tropical evergreen forests, west coast semi-evergreen forests, southern moist mixed deciduous forests. Thr three forest stations under Vadasserikkara range are Chittar, Gurunathanmannu and Thannithodu. The present study aimed to assess the physiochemical parameters of soil in various seasons in a mixed forest habitat of Chittar forest station in Vadasserikkara forest range. Soil analysis and statistical analysis were done using standard procedures. Percentage of gavel and silt was more in Moist deciduous forest and Semi Evergreen forest respectively. Nitrogen content showed significant variation between seasons and different type of forest. Nitrogen content was less in moist deciduous forest compared to other two forest types. Potassium and Calcium content was high in moist deciduous forest in all the seasons. In general soil analysis showed richness in organic carbon, nitrogen, potassium, calcium and magnesium content, but low Phosphorus content which signifies high lushness and output of forest ecosystem.

 

KEY WORDS: Chittar forest station, Physicochemical analysis, Evergreen forest, semi-evergreen forests, moist deciduous forest.

 

 

I INTRODUCTION:

Primary forests Western Ghats of peninsular India are disappearing at an alarming rate, due to anthropogenic pressure. They are being replaced by forests containing inferior species or by monoculture like rubber and pineapple plantations. Human impacts on forests date back to the distant past and even to pre-history. An understanding of forest processes is fundamental to the management of natural and disturbed vegetation. Such an understanding is necessary for assessment of potential impacts, the amelioration of effects of disturbance, optimization of productivity and rehabilitation of degraded ecosystems 1. Increase in organic carbon content of the soil increase the cation exchange capacity of the soil and decline in soil organic matter content involve significant loss in nutrients and exchangeable bases. Increase in organic carbon might increase calcium storage of the top soil through increase in exchange capacity. In most of our forest reserves the nature of the soils has not been investigated, hence the fertility status of the soils is not known hence the objective of present study was to investigate the physicochemical properties of the soils of Chittar reserve Forest

 

The Ranni Forest Division in Kerala, India, comprising the Ranni, Vadasserikkara, and Goodrical ranges, with its headquarters at Ranni covers 1,057 square kilometres. It comprises of parts of Konni reserve forest and the reserves of Ranni, Goodrical and Schettakkal. Ranni forest is divided into three ranges-Goodrical range (61.74955%), Ranni range (12.86388%) and Vadasserikkara range (25.38657%). The Goodrical forest range is situated in the eastern side of Pathanamthitta district, with an area of 654 square kilometres and three forest stations under this range. Plappally, Kochukoikkal, Pachakkanam. Here there is less human interference except during Sabarimala pilgrimage, these forests ranges are crowded with devotees. Evergreen and semi-evergreen types of forests are here. The Ranni range covers an area of 136.2 square kilometres and three forest stations under this range are: Karimkulam, Kanamala, Rajampara. Evergreen, semi-evergreen, and deciduous types of forests can be seen here. The. Vadasserikkara range is towards the eastern part of Ranni,. The objectives of the present study was to to analyze various soil edaphic factors and nutrient contents of mixed forest in Chittar forest station in Vadasserikkara forest range. These data are expected to be useful in conservation planning.

 

II. MATERIALS AND METHODS:

Study Area: Chittar Forest station is located in Vadaserrikara forest. It lies between Lat 9.3311° N to 9.3225° N and Long76.9222° E to 76.9709° E. The villages surrounding this forest station area includes: Seethathode, Thannithodu, Perunadu and Anghamoozhy. Soil samples were randomly collected from different layers of soil pit. Samples were air dried, passed through 2mm sieve. The particles >2mm(gravel) were separated for analysis of percentage of gravel. The sand, slit, clay, pH, OC, exchangeable acids, exchangeable bases, Nitrogen, Phosphorous, Potassium, Calcium and Magnesium were found out according to the procedure of Jackson (1958). Data was analyzed using mean, standard deviation and ANOVA.

 

III. RESULT AND DISCUSSION:

Analysis of vegetation has revealed three types of forests in Chittar forest station, west coast tropical evergreen forests, west coast semi-evergreen forests, southern moist mixed deciduous forests. The evergreen forests is green throughout the year and has cycas, pteridophytes and less thick trees with top canopy. Tree species like Terminalia paniculata, Dalbergia latifolia, predominates in the moist deciduous forest2. The semi evergreen predominant species as Lagerstroemia lanceolata, Lagerstroemia reginae3. Moist deciduous habitat has soil gravel content ranging between 7 – 20 %. Generally the soil is sandy loam . The soil has high Nitrogen, Potassium and Calcium content. Magnesium content was generally low. Forest management can stimulate the decomposition of the forest floor and can modify its quality by the tree species selection (quantity and chemical quality of litter, rooting depth) and the thinning regime (microclimate).4

 

In evergreen forest soil gravel content ranges between 10 – 17 %. The soil was sandy loam and strongly acidic. Very high organic carbon content was present. Sand content varies between 70–85%. Exchangeable acidity was generally low which exchangeable base was high. This soil has high Nitrogen, Potassium, Calcium content but low Phosphorous and Magnesium content (table 9). These results indicate high fertility and productivity of forest ecosystem. Mean and standard deviation of each parameter were determined by using Microsoft Excel software. Graphical representation is carried out by Microsoft Excel software. Anova was carried out to find the significant difference between the different types of forest habitat and between the seasons.

 

Table 1: Comparative analysis of soil parameters in Vadaserrikara Reserve Forest (Mean ± SE) during various seasons

Parameters

Seasons

Evergreen habitat

Semi Evergreen habitat

Moist deciduous habitat

 

 

 

Temperature C

Pre monsoon

28.13±0.164

29.56±0.181

28.835±0.1346

Monsoon

21.39±0.175

24.34±0.190

23.025±0.170

Post monsoon

24.36±0.18

26.08±0.21

24.99±0.14

Summer

25.11±0.26

28.93±0.215

25.91±0.215

 

 

 

pH

Pre monsoon

4.794±0.0154

4.718±0.0189

4.779±0.0078

Monsoon

3.7875±0.024

4.335±0.029

5.698±0.007

Post monsoon

4.9±0.02

4.48±0.01

4.7± 0.01

Summer

4.65± 0.012

4.25±0.051

4.48±0.035

 

 

 

OC%

Pre monsoon

4.905±0.022

4.602±0.0507

5.0735±0.005

Monsoon

4.59±0.053

4.58±0.050

4.79±0.0218

Post monsoon

4.69±0.01

4.33±0.003

3.39±0.025

Summer

4.049±0.01

4.7±0.051

3.66±0.032

 

 

 

Sand %

Pre monsoon

48.1825±0.244

45.95±0.568

73.5±0.420

Monsoon

73.189±0.825

58.999±0.781

78.4±0.425

Post monsoon

75.51±0.46

76.933±0.51

84.395±0.43

Summer

65.32 ± 0.21

64.6±0.449

83.95±0.58

 

 

 

Silt%

Pre monsoon

6.6235±0.0579

12.4615±0.0578

8.2515±0.088

Monsoon

12.70±0.095

13.70.107

7.98±0.109

Post monsoon

13.8±0.39

12±0.33

7.15±0.19

Summer

12.365 ±0.10

12.9±0.176

7.345±0.11

 

 

 

Clay%

Pre monsoon

13.0345±0.110

15.0445±0.094

15.0365±0.176

Monsoon

12.03±0.164

13.16±0.095

11.44±0.290

Post monsoon

11.71 ± 0.15

12.98±0.47

9.93±0.140

Summer

14.5 ±0.18

13.5±0.144

13±0.316

 

 

 

EA%

Pre monsoon

3.658±0.007

4.8985±0.013

3.495±0.082

Monsoon

3.705±0.031

4.687±0.0159

3.1890.062

Post monsoon

1.43±0.025

2.56±0.028

2.519±0.039

Summer

3.46±0.156

3.62±0.016

2.85±0.01

 

 

EB%

Pre monsoon

5.777±0.025

15.3005±0.088

5.9395±0.01024

Monsoon

5.35±0.088

13.83±0.160

5.87±0.004

Post monsoon

3.4±0.02

11.78±0.11

5.2±0.14

Summer

4.49±0.068

14.182±0.101

5.78±0.041

 

 

 

N(ppm)

Pre monsoon

5646.4±0.666

5834.25±0.714

2765.25±0.547

Monsoon

4675.05±0.670

4563.8±0.605

2433±0.4230

Post monsoon

3755±0.74

3283±0.69

2255±0.48

Summer

4765 ±0.627

4464±0.678

2701±0.478

 

 

 

P(ppm)

Pre monsoon

8.83±0.0376

6.6585±0.0512

5.7145±0.0430

Monsoon

6.60±0.343

6.0±0.132

5.25±0.104

Post monsoon

4.726±0.018

4.82±0.010

5.871±0.01

Summer

6.136±0.29

7.63±0.058

7.068±0.16

 

 

K(ppm)

 

Pre monsoon

267.975±0.639

235.9055±0.668

345.84±0.227

Monsoon

292.69±0.584

342.12±0.947

505.5±0.674

Post monsoon

152.43±0.28

162.8±0.80

244±0.54

Summer

190.36±0.88

187.7±0.912

265.85±0.477

 

 

 

Ca(ppm)

Pre monsoon

436.633±0.191

587.28±0.769

609.095±0.215

Monsoon

514.16±0.642

565.01±0.576

545.92±0.475

Post monsoon

143.08±0.39

347.2±0.85

376±0.52

Summer

218.38±0.20

238.25±1.053

444.6±0.472

 

 

 

Mg(ppm)

Pre monsoon

35.6025±0.161

77.093±0.3404

36.38±0.232

Monsoon

67.49±0.232

47.79±0.851

64.3±0.684

Post monsoon

48.301±0.18

73.95±0.42

30.1±0.57

Summer

56.82±0.40

39.7±0.830

42.4±0.701

 

Table 2 :Two way anova showing the significance of observed variation in primary data of soil parameters during different seasons in different types of forest habitat in Vadaserrikara forest .

Parameters

Comparison

F -value

P-value

F -critical value

Temperature C

Between habitats

15.12284

0.004536

5.143253

Between seasons

45.01435

0.000166

4.757063

pH

Between habitats

0.899054

0.455498

5.143253

Between seasons

0.190129

0.899392

4.757063

OC%

Between habitats

0.653218

0.55378

5.143253

Between seasons

1.666915

0.271805

4.757063

Gravel%

Between habitats

22.39993

0.001648

5.143253

Between seasons

0.703266

0.583865

4.757063

Sand %

Between habitats

11.24127

0.009348

5.143253

Between seasons

8.276435

0.014899

4.757063

Silt%

Between habitats

6.807329

0.028623

5.143253

Between seasons

0.791083

0.541641

4.757063

Clay%

Between habitats

1.661244

0.266599

5.143253

Between seasons

4.669169

0.051904

4.757063

EA%

Between habitats

5.021411

0.052313

5.143253

Between seasons

9.645292

0.010341

4.757063

EB%

Between habitats

238.2083

1.92E-06

5.143253

Between seasons

6.034913

0.030411

4.757063

N(ppm)

Between habitats

31.09866

0.000681

5.143253

Between seasons

7.296071

0.019943

4.757063

P(ppm)

Between habitats

0.296061

0.754011

5.143253

Between seasons

2.019309

0.212777

4.757063

K(ppm)

Between habitats

14.08171

0.005417

5.143253

Between seasons

18.95922

0.001831

4.757063

Ca(ppm)

Between habitats

6.487153

0.03162

5.143253

Between seasons

14.19574

0.003924

4.757063

Mg(ppm)

Between habitats

0.820587

0.484143

5.143253

Between seasons

0.308618

0.818829

4.757063

Temperature in mixed forest habitat is highest during pre monsoon season in semi evergreen forest and least in evergreen forest during monsoon season (Table.1). The two way Anova result showed that there was significant variation in temperature between seasons (F=45.01435, F crit =4.757063; P<0.05) and different types of forest (F=15.12284, F crit=5.143253; P<0.05) (Table.2)

 

pH in mixed forest Habitat is acidic during monsoon season in evergreen forest and slightly acidic during monsoon in evergreen forest (Table.1). The two way Anova result showed that there was no significant variation in pH between seasons (F=0.190129, F crit =4.757063; P>0.05) and different types of forest (F=0.899054, F crit=5.143253; P>0.05) (Table.2)

 

Orgaic carbon content in mixed forest habitat is high during pre-monsoon season in moist deciduous forest and less during post monsoon in moist deciduous forest (Table.1). The two way Anova result showed that there was no significant variation in Orgaic carbon content between seasons (F=1.666915, F crit =4.757063; P>0.05) and different types of forest (F=0.653218, F crit=5.143253; P>0.05) (Table.2)

 

Percentage of gravel in mixed forest habitat is more during pre-monsoon season in moist deciduous forest and less during post monsoon in semievergreen forest (Table.1). The two way Anova result showed that there was no significant variation in Percentage of gravel between seasons (F=0.703266, F crit =4.757063; P>0.05) and but gravel percentage shows significant variation in different types of forest (F=22.39993, F crit=5.143253; P<0.05) (Table.2)

 

Percentage of sand in mixed forest habitat is more during post-monsoon season in moist deciduous forest and less during pre monsoon in semi evergreen forest (Table.1). The two way Anova result showed that there was significant variation in Percentage of sand between seasons (F=8.276435, F crit =4.757063; P<0.05) and in different types of forest (F=11.24127, F crit=5.143253; P<0.05) (Table.2)

 

Percentage of silt in mixed forest habitat is more during post-monsoon season in evergreen forest and less during pre monsoon in evergreen forest (Table.1). The two way Anova result showed that there was no significant variation in percentage of silt between seasons (F=0.791083, F crit =4.757063; P>0.05) but there is significant difference in different types of forest (F=6.807329, F crit=5.143253; P<0.05) (Table.2)

 

Percentage of clay in mixed forest habitat is more during pre-monsoon season in semi evergreen forest and less during post monsoon moist deciduous (Table.1). The two way Anova result showed that there was no significant variation in percentage of silt between seasons (F=4.669169, F crit =4.757063; P>0.05) and different types of forest (F=1.661244, F crit=5.143253; P>0.05) (Table.2)

 

Percentage of exchangeable acid in mixed forest habitat is more during pre-monsoon season in semi evergreen forest and less during post monsoon season in evergreen forest (Table.1). The two way Anova result showed that there was significant variation in percentage of exchangeable acid between seasons (F=9.645292, F crit =4.757063; P<0.05) but threre was no significant difference in exchangeable acid in different types of forest (F=5.021411, F crit=5.143253; P>0.05) (Table.2)

 

Percentage of exchangeable base in mixed forest habitat is more during pre-monsoon season in semi evergreen forest and less during post monsoon in evergreen forest (Table.1). The two way Anova result showed that there was significant variation in percentage of exchangeable base between seasons (F=6.034913, F crit =4.757063; P<0.05) and in different types of forest (F=238.2083, F crit=5.143253; P<0.05) (Table.2).Nitrogen content in ppm was more during pre-monsoon season in semi evergreen forest and less during post monsoon in moist deciduous forest (Table.1). The two way Anova result showed that there was significant variation in nitrogen content between seasons (F=7.296071, F crit =4.757063; P<0.05) and in different types of forest (F=31.09866, F crit=5.143253; P<0.05) (Table.2)

 

Phosphorous in mixed forest habitat is more during pre-monsoon season in evergreen forest and less during post monsoon evergreen forest (Table.1). The two way Anova result showed that there was no significant variation in Phosphorous between seasons (F=2.019309, F crit =4.757063; P>0.05) and different types of forest (F=0.296061, F crit=5.143253; P>0.05) (Table.2).Potassium content in ppm was more during monsoon season in moist deciduous forest and less during post monsoon in evergreen forest(Table.1). The two way Anova result showed that there was significant variation in Potassium content between seasons (F=18.95922, F crit =4.757063; P<0.05) and in different types of forest (F=14.08171, F crit=5.143253; P<0.05) (Table.2)

Calcium content in ppm was more during pre monsoon season in moist deciduous forest and less during post monsoon in evergreen forest (Table.1). The two way Anova result showed that there was significant variation in Calcium content between seasons (F=14.19574, F crit =4.757063; P<0.05) and in different types of forest (F=6.487153, F crit=5.143253; P<0.05) (Table.2).Magnesium in mixed forest habitat is more during pre-monsoon season in semi evergreen forest and less during post monsoon moist deciduous forest (Table.1). The two way Anova result showed that there was no significant variation in Magnesium content between seasons (F=0.308618, F crit =4.757063; P>0.05) and different types of forest (F=0.820587, F crit=5.143253; P>0.05) (Table.2).

 

IV. CONCLUSION:

Forest ecosystems store more than 80% of all terrestrial aboveground C and more than 70% of all soil organic C (5–7). Forest soils are considered to have a considerable potential as C sinks 8–10. Outside the tracts of irrigated agriculture, large areas of rain fed cultivation have increasingly encroached on marginal lands with poor rainfall or on steep hill slopes. Forest and grazing lands have suffered badly in this process11. In regions where exploitative historic land-use practices have reduced the soil C pool, one option is to foster the restoration of the previous forest type. This can be achieved by ameliorations, such as under planting, liming, and fertilizer application, or through a natural aggradations process, which is supported by anthropogenic N deposition and climatic change12. The annual CO2 exchange between forests and the atmosphere via photosynthesis and respiration is 50 Pg C/yr, i.e. 7 times the anthropogenic C emission. An increase in soil respiration would increase the CO2 emissions from forest ecosystems. In order to mitigate climate change, more C should be sequestered in forest ecosystems and strategies for an adapted forest management are sought13 The result obtained from the current study can be used as documentation and can be used to determine the soil poperties of Vadaserikkara reserve forest. The effects of forest management on soil carbon (C) and nitrogen (N) are important to understand because these are frequently master variables influenencing soil fertility and also the soil is a source or sink for C on a global scale 14. Forest management can stimulate the decomposition of the forest floor and can modify its quality by the tree species selection(quantity and chemical quality of litter, rooting depth)and the thinning regime (microclimate)4.The study also revealed different properties of the soils in the forest reserve as it highlighted in the relationship between the soils and forest trees in the study area. The study therefore recommends that more research should be carried out on the study area so as to clearly link the physico-chemical nature of the soils of the forest reserve and the performance of the trees. Due to the extremely unplanned development of agriculture in the high lands, the natural forest vegetation has been fragmented in many places there by losing the continuity. Forest is facing all these degradational pressures. Proper management and public awareness is needed for the proper conservation of this ecosystem.

 

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Received on 24.09.2019       Modified on 15.10.2019

Accepted on 31.10.2019      ©A&V Publications All right reserved

Research J. Science and Tech. 2019; 11(4):287-291.

DOI: 10.5958/2349-2988.2019.00041.X