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Sacred forests play a unique role in soil
conservation. Due to rapid litter decomposition rate, nutrient release into the
soil of these forests is very high. The soil itself has little nutrients to
support the large biomass of the sacred grove.

The knowledge of climatic conditions and forest soil
of any region help to understand the growth, reproduction, and composition of
forest vegetation. The innermost theory for ecology is that climate exerts the
dominant control on the spatial distribution of the major vegetation types on a
global scale, while on a smaller scale, the contribution of secondary factors
such as soil type or topography are important as well (Woodward, 1987,
Whittaker, 1975). Numerous studies have attempted to correlate climax
vegetation and soils (Daubenmire and Daubenmire 1968; Daubenmire 1979; Tisdale
and Bramble-Brodahl 1983, Sexton 1986; Neiman 1988; Jensen et al.,  1990; Celine et al., , 2017). In addition, the soil
and vegetation have a complex interrelation because they develop together over
a long period. Soil analysis shows the forest types and plant density of any
area because the different species of plants need different types of soils. The
selective absorption of nutrient elements by different plant species and their
capacity to return them to the soil brings about changes in soil properties
(Singh et al.,  1986).

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Presence of plant elements in soil would give good
information towards the knowledge of nutrient cycling and bio-chemical cycle in
the soil–plant ecosystem (Pandit and Thampan 1988, Binkley and Giardina 1998).
Moreover, different tree species can differ significantly in their influence on
soil properties as well as soil fertility (Augusto et al.,  2002). The
properties of the soil are the important factor for the growth of the plants.
Among them, the most important factor is soil fertility, i.e., the essential
nutrients available in the soil, for the growth of plants. Soil as a stable and
renewable resource is a foundation of organisms’ survival. It is considered as
a part of an ecosystem, having specific properties and varying from one region
to another. Some of these properties including the percentage of nitrogen,
phosphorus, potassium, soil acidity, soil salinity, and pH affect vegetation
cover in an ecosystem (Zarinkafsh, 1987). The sporadic successes in correlating
climate and soils with vegetation appear to be locally significant, but are not
applicable elsewhere. Johnson and Simon (1987) had some success in broad
relational correlations. The forest of Garhwal region of central Himalaya has
vast variations in the climate, topography, and soil conditions, which form a
very complex ecosystem.  Since, the
vegetation zones in the Garhwal region clearly reflect edaphic and climatic
variations (Bhatta 1981; Bhatt and Purohit 2009) and at the same time the
knowledge of physical and chemical properties of soils and climatic conditions
of different forest types of temperate region of Garhwal and Kumaun region region
of central Himalaya is meagre (Upreti et
al., , 2016). Therefore, to study adequate theoretical and practical
knowledge of climatic, various forest soils, and the complex relationship
between the lives of various plants of the forest is necessary to study.
However, the present study was undertaken to understand the effects of climatic
variables and the soil properties in relation to the forest structure in
different forest types of moist temperate Taknaur reserve forest of Uttarkashi
Forest Division of Central Himalaya, India.

7.2 Result and discussion

   7.2.1
Soil Physical properties of
sacred forest:  

The
sand percentage ranged from 14.90 to 73.49.The percentage of sand was maximum
in sacred Ratwali forest at 61-90cm depth and minimum in sacred Thal kedar
forest at 0-10 cm depth. The Silt percentage ranged 15.82 to 34.71, maximum in
sacred Betal forest at 61-90 cm depth and minimum in sacred Ratwali forest at
61-90cm depth. The sacred Thal kedar had maximum clay percentage viz. 53.16 at
0-10cm depth and sacred Ratwali forest had minimum percentage viz. 10.69 at
61-90cm depth. Sacred Thal kedar forest had maximum moisture content (37.16) at
0-10cm depth and sacred Pasupatinath nath forest had minimum moisture contend
viz. 18.29 at 31-60cm depth. Maximum Water holding capacity recorded in sacred Thal
kedar forest (68.74) at 0-10 cm depth while minimum in sacred Ratwali forest
(31.24) at 31-60 cm depth. Maximum bulk density recorded in sacred Ratwali
forest (1.34 g/cm3) at 61-90cm depth and minimum recorded in sacred
Pasupatinath forest (1.20 g/cm3) at 0-10cm depth. Sacred Thal kedar
forest had maximum porosity (54.85) at 0-10cm depth while sacred Ratwali forest
had minimum porosity (48.59) at 61-90cm depth (Table 7.1 fig 7.1-7.7).

7.2.2 Soil Physical
properties of Non- sacred forest:  

The
sand percentage ranged from 30.73 to 56.20.The percentage of sand was maximum
in Non- sacred Betal forest at 61-90cm depth and minimum in Non- sacred Kalika
forest at 61-90 cm depth. The Silt percentage ranged 22.2 to 39.51, maximum in non-sacred
Kalika forest at 61-90 cm depth and minimum in non-sacred Thal kedar forest at
31-60cm depth. The Non- sacred Chamunda forest had maximum clay percentage viz.
39.3 at 0-10cm depth and Non- sacred Pasupatinath forest had minimum percentage
viz. 14.68 at 31-60cm depth. Non- sacred Ratwali forest had maximum moisture
content (18.72) at 61-90 cm depth and Non- sacred Ratwali forest had minimum
moisture contend viz. 7.51 at 0-10cm depth. Maximum Water holding capacity
recorded in non-sacred Kalika forest (54.34) at 0-10 cm depth while minimum in non-sacred
Pasupatinath forest (22.0) at 31-60 cm depth. Maximum bulk density recorded in Non-
sacred Ratwali forest (1.43 g/cm3) at 61-90cm depth and minimum
recorded in Non- sacred Pasupatinath forest (1.30 g/cm3) at 0-10cm
depth. Non- sacred Thal kedar forest had maximum porosity (50.63) at 0-10cm
depth while Non- sacred forest Ratwali had minimum porosity (44.80) at 61-90cm
depth. (Table 7.2, Fig 7.1-7.7).

7.2.3 Soil Chemical
properties of sacred forest:  

The
pH ranged from 5.4 to 7.4 recorded maximum in sacred Ratwali forest at 0-10cm
depth and minimum in sacred Betal forest at 61-90cm depth. The organic matter
percentage ranged 1.8 to 3.86, maximum in sacred Kalika forest at 0-10 cm depth
and minimum in sacred Pasupatinath forest at 61-90cm depth. The sacred Kalika
forest had maximum carbon percentage (2.24%) at 0-10cm depth and sacred Pasupatinath
forest had minimum percentage (1.05%) at 61-90cm depth. Sacred Pasupatinath
forest had maximum available nitrogen (326kg/h) at 0-10cm depth and minimum
(200kg/h) at 31-60cm depth. Maximum potassium recorded in sacred Kalika forest
(0.025) at 0-10 cm depth while minimum in sacred Thal kedar forest (0.001) at
61-90 cm depth. Maximum phosphorus recorded in Sacred Ratwali forest (0.014) at
0-10cm depth and minimum recorded in Sacred Thal kedar forest (0.003) at
61-90cm depth. (Table 7.3, Fig 7.8-7.13).

7.2.4 Soil Chemical
properties of Non- sacred forest:  

The
pH ranged from 4.8 to 7.5 recorded maximum in Non- sacred Kalika forest at
31-60cm depth and minimum in Non- sacred Chamunda forest at 11-30cm depth. The
organic matter percentage ranged 1.14 to 3.76, maximum in non-sacred Betal
forest at 0-10 cm depth and minimum in non-sacred Ratwali forest at 61-90cm
depth. The Non- sacred Betal forest had maximum carbon percentage (2.19%) at
0-10cm depth and Non- sacred Ratwali forest had minimum percentage (0.66%) at
61-90cm depth. Non- sacred Pasupatinath forest had maximum available nitrogen
(250.8 kg/h) at 0-10cm depth and minimum in Non- sacred Thal kedar forest
(134.4kg/h) at 31-60cm depth. Maximum potassium recorded in non-sacred Betal
forest (0.009) at 0-10 cm depth while minimum in non-sacred Pasupatinath forest
(0.001) at 61-90 cm depth. Maximum phosphorus recorded in Non- sacred Kalika
forest (0.014) at 11-30cm depth and minimum recorded in Non- sacred Ratwali
forest (0.001) at 31-60cm depth (Table 7.4, Fig 7.8-7.13).

7.2.5 Correlation

7.2.5.1 Kalika sacred and Non- sacred forest: In Kalika sacred and Non- sacred forest moisture
content and organic matter showed maximum correlation (at significant level
0.01) .Organic matter showed maximum positive correlation with six
physicochemical properties i.e., Clay, Porosity, Moisture content, Carbon,
Potassium and Nitrogen while negatively correlate with Silt and Bulk density
(Table 7.5).

7.2.5.2 Chamunda sacred and Non- sacred forest:  In Chamunda Devi
sacred and Non- sacred forest Porosity, Carbon, Organic matter and Nitrogen showed
maximum correlation (at significant level 0.01) with physicochemical
properties. Porosity is positively correlate with eight properties (Moisture
content, pH, Carbon, Potassium, organic matter Nitrogen and Phosphorus) while
negatively correlate with two properties (Silt and bulk density).Carbon is
positively correlated with eight properties (Clay, porosity, Moisture content,
pH, Potassium, Organic matter, Nitrogen and Phosphorus) and negatively
correlated with two properties (Silt and Bulk density). Organic matter
positively correlated with eight properties (Clay, Porosity, Moisture content,
pH, Carbon, Potassium, Nitrogen, and Phosphorus) and negatively correlates with
silt and Bulk density. Nitrogen is positively correlates with eight properties
(Clay, Porosity, Moisture content, pH, carbon, Potassium, organic matter, and
Phosphorus) and negatively correlates with silt and Bulk density (Table 7.6).

7.2.5.3 Kanalichina sacred and non-sacred forest: In Kanalichina sacred and non-sacred forest, Sand,
and porosity showed maximum correlation (at significant level 0.01) with
physicochemical properties. Sand positively correlate with two properties (Bulk
density and pH) while negatively correlate with ten properties (Silt, Clay,
Porosity, Moisture content, Water holding capacity, Carbon, Potassium, Organic
matter, Nitrogen and phosphorus). Porosity showed positive correlation with
eight properties (Silt, Clay, Moisture content, Water holding capacity, Carbon,
Potassium, Nitrogen and Phosphorus) and negatively correlate with sand and Bulk
density (Table 7.7).

7.2.5.4 Pasupatinath sacred and Non- sacred forest: In Pasupatinath sacred and Non- sacred forest Clay showed
maximum positive correlation (at significant level 0.01) with eight properties
(Porosity, Moisture content, pH, Carbon, Potassium, Organic matter, Nitrogen
and phosphorus) and negatively correlate with three properties (Sand, Silt and
Clay) (Table 7.8).

7.2.5.5  Ratwali
sacred and Non- sacred forests: In Ratwali sacred and Non- sacred forest Porosity showed maximum positive
correlation (at significant level 0.01) with eight properties (Clay, Moisture
content, pH, Carbon, Potassium, Organic matter, Nitrogen and phosphorus) and
negative correlation with Bulk density and Silt. Nitrogen positively correlated
with eight properties (Clay, Porosity, Moisture content, pH, Carbon, potassium,
Organic matter and phosphorus) and negatively correlated with Silt and Bulk
density (Table 7.9).

7.2.5.6 Thal kedar sacred and Non- sacred forest: In Thal kedar sacred and Non- sacred forest
Phosphorus showed maximum positive correlation (at significant level 0.01) with
seven physicochemical properties (Silt, Porosity, Moisture content, carbon,
Potassium, Organic matter and Nitrogen) and negatively correlate with Sand and
Bulk density (Table 7.10).

7.2.6 CLUSTER ANALYSIS

7.2.6.1 Kalika
sacred and non-sacred forest: Based on cluster analysis site 1 is divided into V clusters. Cluster
I (2 sites viz. Sk4, NsK3), Cluster II (2 sites viz. NsK1, NsK2), Cluster
III (1 site viz. NsK4), Cluster IV (2 sites viz. sK2, sK3) and Cluster
V (1 site viz. sK1) (Fig 7.14).

7.2.6.2 Chamunda
sacred and Non- sacred forest: Cluster analysis divided sites in V clusters. Cluster I (2 sites
viz. NsC2, NsC3), Cluster II (2 sites viz. NsC1, sC4), Cluster III (1
site viz. NsC4), Cluster IV (2 sites viz. sC2, sC3) and Cluster V
(1 site viz. sC1) (Fig 7.15).

7.2.6.3 Ratwali
sacred and Non- sacred forest: Cluster analysis divided sites in IV clusters. Cluster I (3
sites viz. NsR2, NsR3, NsR4), Cluster II (2 sites viz. sR4, NsR1), Cluster
III (2 site viz. sR2, sR3), Cluster IV (1 sites viz. sR1) (Fig 7.16)

7.2.6.4. Pasupatinath sacred and Non- sacred forest: Cluster analysis
divided sites in IV clusters. Cluster I (3 sites viz. NsP2, NsP3 and
NsP4), Cluster II (2 sites viz. sP3, sP4), Cluster III (2 site viz.
sP2, NsP1), Cluster IV (1 sites viz. sP1) (Fig 7.17).

7.2.6.5 Betal
sacred and Non- sacred forest: Cluster analysis divided sites in IV clusters. Cluster I (3 sites)
Cluster II (one site) Cluster III (two sites) Cluster IV (two sites). Cluster
I:    sB2, NsB1, sB3, Cluster II: sB1,
Cluster III: NsB3, NsB4, Cluster IV: sB4, NsB2 (Fig 7.18).

7.2.6.6 Thal
Kedar sacred and non-sacred forest: Cluster analysis divided sites in V clusters. Cluster I (2 sites viz.
sT2, sT3), Cluster II (1 sites viz. sT1), Cluster III (2 site viz.
NsT3, NsT4), Cluster IV (2 sites viz. NsT1, NsT2), Cluster V (1
site viz. sT4) (Fig 7.19).

7.2.6.7 Cluster dendrogram within six
Sacred forests Pithoragarh: Cluster analysis showed VII
clusters. Cluster I (5 sites viz. sC1, sC3, sK4, sB4, sT4), Cluster II (3 sites viz. sC4, sP3, sP4), Cluster III (6 sites viz. sB2, sT2, sP2, sB3, sC1, sT3), Cluster IV (3 sites viz. sK2, sK3, sR3), Cluster V (1 site viz. sR4), Cluster VI (2 sites viz. sR1,
sP1) and Cluster VII (4 sites viz. sk1, sB1, sR2, sT1) (Fig 7.20).

7.2.6.8 Cluster dendrogram within six Non-
sacred forests Pithoragarh: Cluster analysis showed VI
clusters. Cluster I (5 sites viz. NsK2, NsB2, NsK3, NsK1, NsR2), Cluster II (3 sites viz. NsP1, NsB1,NsR1), Cluster III (2 sites viz. NsT3, NsT4), Cluster IV (3 sites viz. NsC4, NsP4, NsP3), Cluster V (5
site viz. NsR4, NsB2, NsR3, NsB3, NsT1)
and Cluster VI (6 sites viz. NsC2, NsC3, NsT2, NsP2, NsK4, NsC1) (Fig 7.21).

7.2.6.9 Cluster dendrogram within Sacred
and Non- sacred forests Pithoragarh: Cluster analysis showed
VI clusters. Cluster I (13 sites viz. NsK2, NsB2, sK4 NsK3, sC2 , sC3, sB4,
NsR2, NsR4, NsB4, NsR3, NsB3, NsT1,), Cluster II (9 sites viz. sP4,
NsT2, NsC2, NsC3, NsP2, sC4, sP3, NsK4, NsC1), Cluster III (5 sites viz. NsT3,
NsT4, NsC4, NsP4,  NsP3), Cluster IV (6 sites viz. sR1, sP1, sk1, sB1, sR2, sT1), Cluster V (3 site viz. sK2, sR3, sR4), Cluster VI (12 sites viz. NsK1, sP2, sC1, sB3, sT3, sT4, sB2,
sT2,  NsP1,  NsB1, 
NsR1, sK3) (Fig 7.22).

7.2.7
Factor analysis and observation plot: Principal component
analysis for sand depict that sites viz. sR, NsR, sP, NsP, sB, NsB and sT were
positively significant at lower most depth 61-90 cm, while other sites and
depths were weakly significant. For silt four sites ( sK, NsK, sC and NsC) were
positivly significant at 61-90 cm depth, 
and for clay nine sites (sK, sC, NsC, sR, sP, NsP, sB, NsB and sT) were
positively significant at 0-10 cm depth while for soil moisture content and
water holding capacity four sites(sK, NsC, NsT, sT and NsK, sC, sP, sT
respectively) were strongly influenced at 0-10 cm depth.(Fig 7.24-27)

     PCA for
pH showed positive significance of six sites (sR, sC, sP, NsP, sB and NsT) at
0-10cm and 11-30 cm depth while for potassium and phosphorous nine sites (NsR,
NsP, NsB, NsT, sT, sC, sK, sB and sR) and seven sites (sC, sR, NsP, sB, sT, NsT
and NsK) showed positive significance at 0-10 and 11-30 cm depth respectively (Fig
7.28-30).

7.2.8
Correspondence analysis: Correspondence analysis showed
dispersal of physiochemical properties and sites in asymmetric and symmetric
plots. Based on asymmetric plot sacred and non-sacred sites are separated on
both sides of plot while physicochemical parameters are clustered at centre of
plot.

      On the
basis of symmetric plot sacred and Non- sacred sites were separated, while Non-
sacred sites viz. NsC1,NsB1, NsK1 and NsR1 shoed clustering with sacred sites
and sacred sites viz. sP4, sC4, sC3, sB4, sP3 and sK4 showed clustering with Non-
sacred sites. Physicochemical properties such as sand, silt, BD, and porosity
showed correlation with non-sacred sites while clay, MC, WHC, OM, K, and P
showed correlation with sacred sites. (Fig 7.31 a, b)   

7.2.9  Agglomerative hierarchical cluster (AHC): On
the basis of Physicochemical properties sites were differentiated in three
classes viz. Class 1 (sK1,  sR1, 
sR2,  sP1,  sB1 and 
sT1), Class 2 (sK2, sK3,
NsK1, SC1, sR3, sR4, NsR1, sP2, NsP1, sB2, sB3, 
NsB1,  sT2,  sT3 and 
sT4) and Class 3 (sK4 NsK2
NsK3 NsK4 SC2 SC3 SC4 NsC1, NsC2, NsC3, NsC4, NsR2, NsR3, NsR4, sP3, sP4, NsP2,
NsP3, NsP4, sB4, NsB2, NsB3, NsB4, NsT1, NsT2, NsT3 and NsT4). Observation
depict that class 1 had six sacred sites only while in class 2 total fifteen
sites were included out of which four sites were Non- sacred rest were sacred
sites and  in class 3 total twenty seven
sites were included out of which seven were sacred sites rest were Non- sacred
sites.(Fig 7.32)

7.2.10
K-mean clustering: On the basis of  K -mean cluster for sacred forests physicochemical
properties classified in five classes viz. Class
1: pH, OM, C, K, P and BD,  Class 2: N,  Class 3
Sand, Silt and MC, Class 4: Clay and
Class 5: WHC and Porosity, While for
Non- sacred forests  K- mean cluster showed
five classes viz. Class 1: pH, OM
and MC, Class 2: C, K, P and BD, Class 3: N, Class 4: Sand and Porosity,  Class 5: Silt, Clay and WHC.(Fig 7.33
a,b)

 

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