Carbon Sequestration Potential of Himalayan Cypress Stands of Kumaun Central Himalaya, India

doi:10.21203/rs.3.rs-4635650/v1

Forests play a substantial role in sequestering carbon and regulating the global carbon balance. Himalayan Cypress (Cupressus torulosa D. Don) from an ecological and economic stand point is a least explored evergreen conifer of Central Himalaya that often forms either pure stands or sometimes association with other tree species. However, very little information is known about the carbon sequestration potential of these Cypress stands. Therefore, the main objective of this study was to quantify carbon stocks and carbon sequestration potential of six Cypress stands distributed along the altitudinal gradients of 1600–2500 m asl in Kumaon Central Himalaya. A total of 120 circular plots of 5.65 m radius were laid systematically in six Cypress stands with 20 sample plots in each. Soil physical and chemical properties were also assessed. Results revealed that total tree density and basal area in cypress stand ranged from 440–1050 individuals ha^-1 and 30.84–60.79 m² ha^-1, respectively. The total carbon stock ranged between 151–285 Mg C ha^-1, respectively. Carbon sequestration rate across stands fluctuated between 2.42 and 4.87 Mg C ha^-1 yr^-1. Soil organic carbon (SOC), total nitrogen (TN) and available potassium (K) levels were higher in high altitude stands. Soil organic carbon (SOC) stock (for soil depth 0-60 cm) ranged from 155.58–398.80 Mg ha^-1. Altitude and soil physico-chemical factors showed no significant (p>0.05) impact on carbon stocks of Cypress stands. Overall, the carbon reserves in the soil across stands were 9-57% higher than those in the trees' biomass. These estimates indicate that the value of cypress forests lies not only in their ability to sequester biomass carbon but primarily in their extensive soil carbon reserves. This study provides useful background for future research to assess the trend of carbon sequestration in Cypress stands.

Carbon stocks

Carbon sequestration potential

Himalayan Cypress

Biomass

Forests provide vital ecosystems services and goods to the survival of human beings across the globe (Brockerhoff et al. 2017). They also play an important role in providing various benefits at the local and regional scales. Furthermore, forests actively participate in the exchange of carbon with the atmosphere, engaging in the processes of photosynthesis and respiration. This accumulation of carbon within forests makes them a significant carbon reservoir, storing substantial amounts of carbon within vegetation and soil (Rana et al. 2015). This intricate interplay contributes to the regulation of carbon levels, making forests pivotal in maintaining environmental balance on multiple levels (Bhatta et al. 2021). Forests have greater carbon in biomass and soils compared to other natural ecosystems and atmosphere (Favero et al. 2020; Yam et al. 2021; Joshi et al. 2021). The central Himalayan forests are defined by the prevalence of prominent tree species across different altitudes which play a vital role in sustaining ecosystem functions and providing essential services (Joshi et al. 2023). Therefore, exploring characteristics of these forests, including floristic diversity, structural patterns, and distribution, is imperative for the preservation of ecosystem stability. Additionally, studies on forest biomass provide critical insights into the carbon dynamics of ecosystems and play a fundamental role in assessing the overall carbon storage capacity of forests at broader geographical levels (Behera et al., 2017; Bisht et al. 2022). Although, quantitative studies on carbon in biomass and soil are well discussed at national as well as at global level, there are still a great deal of uncertainties about biomass, carbon stock and carbon sequestration of a particular forest ecosystem in Himalayan region.

The Himalayan cypress (Cupressus torulosa D. Don) is a coniferous evergreen tree of family Cupressaceae, and is native to the Himalayas and the surrounding regions, including Bhutan, northern India, and Nepal (Asif et al. 2018). It thrives in limestone-rich barren terrains across the Western and Central Himalayas, with an elevational range spanning from 1700 to 2700 meters (Pandit and Ram 2004). Spatially, it occurs either as pure stands or in association with coniferous species like Deodar, and broad-leaved species such as Quercus spp. and Acer spp (Rana et al. 2015; Negi et al. 2023). Throughout literature there is a noticeable scarcity of studies that quantify the biomass and carbon storage potential of Cypress stands along altitudinal gradient. By investigating the carbon sequestration capacity of this tree species, we can assess its contribution to carbon storage in both above-ground biomass and soil. We conducted the present study in Cypress stands of Kumaun, central Himalayas to evaluate vegetation parameters of the stands, to explore the pattern of biomass and carbon stocks along an altitudinal gradient, and to study the factors influencing carbon storage potential.

Study area

This study was carried out in Cypress stands located between 29°21'–29° 23' N and 79°26'–79°32' E of Nainital forest division of District Nainital, Uttarakhand, India (Fig. 1), and the data collection period spanned from October 2021 to October 2022. Detailed characteristics of the study area are given in Table 1. The climate of the study area is mainly ruled by monsoon pattern. On the basis of temperature and amount of rainfall, seasons were divided into following combination of months viz., summer (March-June), rainy (July-October) and winter (November-February). During the study period, area received a total annual rainfall of 1854.3 mm with maximum precipitation of 407 mm in October (Fig. 2). During the rainy season, relative humidity reached its peak, hitting 88% in the month of September (Fig. 2). The maximum mean monthly temperature fluctuated from 14.1°C (January) to 24.7°C (April), while the minimum mean temperature ranged from 4.3°C (January) to 16.5°C (September) (meteorological data was collected from the nearest meteorological station located at Nainital) (Fig. 2).

The studied Cypress stands come under lesser Himalayan range of Kumaun region. This region predominantly constitute of igneous, sedimentary and low–grade metamorphic rocks belonging to krol formations (Valdiya 1980).

Table 1

Site characteristics of the study area.
S. No	Forest site	Longitude	Latitude	Altitude (m asl)	Aspect
I	Farsauli	79°31'1.88"E	29°22'42.75"N	1682–1686	SE
II	Dankaniya	79°32'55.17"E	29°23'0.85"N	1690–1700	NE
III	Manora	79°27'48.01"E	29°21'44.99"N	1768–1837	NE
IV	Takula	79°27'29.97"E	29°21'45.77"N	1808–1895	SW
V	Oak-Park	79°26'20.34"E	29°23'44.58"N	2113–2148	W
VI	Naina- Peak	79°26'8.91"E	29°23'49.37"N	2315–2324	NW

Where, SE-south east, NE-north east, SW-south west, W-west, NW-north west

Soil sampling and analysis

The soil samples at depths 0–10 cm, 10–20 cm, 20–30 cm, 30–40 cm, 40–50 cm and 50–60 cm were collected in triplicates from each forest stand using soil corer. Samples were brought to the laboratory to determine the soil physical and chemical properties. Components of soil texture was determined using sieves of different mesh sizes: >2 mm for gravel, 0.05-2 mm for sand, 0.05 − 0.002 mm for silt and < 0.002 mm for clay. To evaluate the soil moisture content, fresh samples of soil were weighed and dried in Oven at 60 ⁰C till the constant weight was achieved. Water holding capacity was estimated following Piper (1950). Bulk density (BD) was estimated as mass of dry soil per unit volume of the corer (g cm^− 3) following Vibhuti (2019). Porosity was calculated as the percentage of void in soil volume following Kumar et al. (2020).

The soil pH was assessed by creating a mixture of soil and distilled water in a ratio of 1:5 using a digital pH meter (Systronics pH system 361). Soil Organic Carbon was estimated by Wet combustion and Dichromate oxidation method (Walkely and Black, 1947). The soil total nitrogen (TN) was estimated following Kjeldahl method. The available soil phosphorus was assessed following Olsen’s method (Olsen et al. 1954). The available potassium was determined by flame photometer using neutral normal acetate method of Black (1965).

Vegetation sampling and analysis

After intensive reconnaissance survey, 6 Cypress stands were identified along the altitudinal gradients of 1600–2500 m asl in Kumaon, Central Himalaya. The study employed systematic sampling method. From each Cypress stand, 1 ha forested area was selected randomly and was divided into 20 plots of ~ 100.29 m² each. Within each plot, circular nested plots of 5.65 m radius were laid covering 100 m² area to measure trees circumference at breast height (CBH in cm). Density and Total basal area were determined following Curtis and McIntosh (1950) and Misra (1968). Shannon's Diversity Index (H′) of trees was calculated following the methodology outlined by Shannon and Weaver (1963), Simpson's concentration of dominance (Cd) by Simpson (1949), and Evenness (E) as per Pielou's Evenness Index (1966).

The biomass for tree and saplings were estimated by using allometric equations reported by Chaturvedi and Singh (1987). Rawat and Singh (1988), Bargali et al. (1992), and Adhikari et al. (1995), as:

$$\:ln\:\text{y}=a+\text{b}\:ln\:\text{x}$$

where, a = intercept, b = slope or regression coefficient, x = CBH (cm) and y = weight of the components of tree (kg).

Carbon stock (C) was calculated following Magnussen and Reed (2004) as:

$$\:\text{C}=\text{B}\times\:0.475$$

Where, C is the Carbon stock and B is oven dry biomass

The total carbon stock (TCS) was calculated by summing up the total aboveground carbon stock (AGCS), belowground carbon stock (BGCS) and soil organic carbon (SOC).

TCS = AGCS + BGCS + SOC

For the estimation of annual biomass accumulation in each forest stand, trees were marked and CBH were measured in the year 2021, and their CBH was remeasured in each sampling plot in the subsequent year, i.e., 2022. The net change in biomass (ΔB = B₂-B₁) yielded annual biomass accumulation. Carbon sequestration rate (CSR) was calculated by multiplying ΔB with 0.475. The difference between carbon content estimated in year one versus year two was taken as the carbon sequestration rate (Tewari et al. 2008).

Statistical analysis

Two-way ANOVA (analysis of variance) was conducted to assess the impact of site, soil depth and their combined interactions on soil physical and chemical properties. Pearson’s correlation test was done to assess the relationship between environmental variables. All statistical analysis was done using SPSS software version 22.0.

Forests vegetational parameters

Highest tree species richness was documented at Naina- Peak (5) while, it was lowest at Farsauli, Dankania and Manora sites with 3 tree species each (Table 2). Maximum tree density was recorded at Takula site (1050 ha^− 1) and minimum at Dankania site (440 ha^− 1). Total basal area of the forests ranged from 30.84 m² ha^− 1 (Manora site) to 60.79 m² ha^− 1 (Oak Park site). Similar to species richness, highest tree species diversity was documented from Naina- Peak site (0.85) and lowest at Manora site (0.42) with mean tree diversity of 0.38 ± 0.12. Highest evenness was recorded at Takula (0.6) while lowest at Dankania (0.04). Concentration of dominance was recorded highest at Farsauli (0.96) and minimum at Takula (0.53) (Table 2).

Table 2

Structural characteristics of tree layer of Cypress stands in Nainital, Uttarakhand.
	Sites	Tree species	TD	TBA	H'	Cd	E
1	Farsauli	Cupressus torulosa, Pinus roxburghii, Quercus leucotrichophora	475	40.43	0.12	0.96	0.11
2	Dankania	Cupressus torulosa, Pyrus pashia, Aesculus indica	440	35.67	0.04	0.91	0.04
3	Manora	Cupressus torulosa, Cedrus deodara, Pinus roxburghii	560	30.84	0.35	0.82	0.32
4	Takula	Cupressus torulosa, Quercus leucotrichophora, Rhododendron arboreum, Cedrus deodara	1050	37.43	0.83	0.53	0.60
5	Oak- Park	Cupressus torulosa, Quercus leucotrichophora, Quercus floribunda, Acer oblongum	485	60.79	0.33	0.86	0.24
6	Naina-Peak	Cupressus torulosa, Quercus floribunda, Rhododendron arboreum, Lyonia ovalifolia, Cedrus deodara	555	48.04	0.61	0.72	0.38

Where, TD-total density (ind. ha^− 1), TBA-total basal area (m² ha^− 1), H-Shannon diversity index, Cd-concentration of dominance, E-evenness

Biomass distribution and carbon sequestration rate

Total tree biomass (TB in Mg ha^− 1) across all six sites ranged from 223.51 (Manora stand) to 434.59 (Oak Park stand) in the first year and increased to 228.61 (Manora stand) and 442.68 (Oak Park stand) in the second year (Table 3). The range of aboveground tree biomass (AGB in Mg ha^− 1) in first year varied between 181.94 (Manora stand) and 372.87 (Oak Park stand), which increased slightly by the second year and ranged between 186.42 and 380.15, respectively. The belowground biomass (BGB in Mg ha^− 1) in initial year ranged from 41.56 (Manora stand) to 83.89 (Takula stand), which increased to 42.19 and 85.40 in the second year, respectively (Table 3).

Table 3

Aboveground biomass (AGB Mg ha^− 1), belowground biomass (BGB Mg ha^− 1), total biomass (TB Mg ha^− 1), and net increment in biomass (ΔB) in Mg ha^− 1 of Cypress forests
		First year			Second year			ΔB
Site	Species	AGB	BGB	TB	AGB	BGB	TB	ΔB
Farsauli	Cupressus torulosa	243.15	46.43	289.58	247.96	47.01	294.97	5.38
	Quercus leucotrichophora	0.96	0.42	1.37	1.03	0.44	1.46	0.09
	Pinus roxburghii	1.89	0.42	2.32	2.01	0.45	2.46	0.14
	Total	246.00	47.27	293.27	251	47.9	298.89	5.61
Dankania	Cupressus torulosa	214.95	41.41	256.36	220.43	41.92	262.35	5.98
	Pyrus pashia	1.43	0.35	1.78	1.55	0.37	1.92	0.14
	Aesculus indica	7.07	2.58	9.65	7.13	2.6	9.73	0.08
	Total	223.46	44.33	267.79	229.11	44.89	274	6.2
Manora	Cupressus torulosa	169.21	38.84	208.05	173.31	39.4	212.71	4.65
	Cedrus deodara	11.50	2.44	13.94	11.78	2.49	14.27	0.32
	Pinus roxburghii	1.23	0.28	1.51	1.33	0.3	1.63	0.12
	Total	181.94	41.56	223.51	186.42	42.19	228.61	5.09
Takula	Cupressus torulosa	166.97	45.23	212.20	171.78	45.79	217.57	5.37
	Cedrus deodara	12.15	2.14	14.29	12.35	2.15	14.5	0.21
	Quercus leucotrichophora	101.08	34.89	135.97	104.77	35.82	140.59	4.62
	Rhododendron arboreum	5.99	1.63	7.62	6.03	1.64	7.68	0.05
	Total	286.19	83.89	370.08	294.93	85.4	380.34	10.25
Oak Park	Cupressus torulosa	361.43	57.93	419.36	368.32	58.67	426.98	7.63
	Quercus floribunda	4.31	1.31	5.62	4.44	1.33	5.76	0.15
	Quercus leucotrichophora	6.59	2.42	9.02	6.83	2.48	9.31	0.29
	Ilex dipyrena	0.53	0.07	0.60	0.56	0.07	0.63	0.03
	Total	372.87	61.73	434.59	380.15	62.55	442.68	8.1
Naina-Peak	Cupressus torulosa	246.79	46.84	293.63	253.44	47.48	300.92	7.29
	Quercus floribunda	45.17	10.52	55.69	45.6	10.59	56.19	0.5
	Rhododendron arboreum	1.22	0.42	1.64	1.26	0.43	1.68	0.04
	Lyonia ovalifolia	4.25	0.37	4.62	4.29	0.37	4.65	0.04
	Cedrus deodara	6.88	0.87	7.75	6.98	0.88	7.86	0.11
	Total	304.31	59.02	363.33	311.57	59.75	371.3	7.98

Where, AGB-aboveground biomass, BGB-belowground biomass, TB-total biomass, ΔB-difference between biomass of first year and second year

In the first year, total tree carbon stock (TCS) ranged from 106.17 Mg C ha^− 1 in the Manora stand to 206.43 Mg C ha^− 1 in the Oak Park stand. By the second year, TCS range shifted from 108.59 Mg C ha^− 1 in the Manora stand to 210.27 Mg C ha^− 1 in the Oak Park stand (Table 4). The aboveground carbon stock (AGCS) in the first year varied from 108.59 Mg C ha^− 1 in the Manora stand to 210.27 Mg C ha^− 1 in the Oak Park stand which increased to 186.42 Mg C ha^− 1 and 380.15 Mg C ha^− 1 in second year, respectively. Belowground biomass (BGCS), in the first year, ranged from 19.74 Mg C ha^− 1 in the Manora stand to 39.85 Mg C ha^− 1 in the Takula stand. By the second year, this range shifted slightly to 20.04 Mg C ha^− 1 and 40.57 Mg C ha^− 1, respectively (Table 4). The carbon sequestration rate (in Mg C ha^− 1yr^− 1) across six sites ranged from 2.42 (at Manora stand) to 4.87 (at Takula stand).

Tables 4. Aboveground carbon stock (AGCS in Mg C ha^− 1), belowground carbon stock (BGCS in Mg C ha^− 1), total carbon stock (TCS in Mg C ha^− 1), and carbon sequestration rate (CSR) in Mg C ha^− 1yr^− 1 of Cypress forests.

Site	Species	First year			Second year			CSR
		AGCS	BGCS	TCS	AGCS	BGCS	TCS	CSR
Farsauli	Cupressus torulosa	115.50	22.05	137.55	117.78	22.33	140.11	2.56
	Quercus leucotrichophora	0.45	0.20	0.65	0.49	0.21	0.69	0.04
	Pinus roxburghii	0.90	0.20	1.10	0.95	0.21	1.17	0.07
	Total	116.85	22.45	139.30	119.23	22.75	141.97	2.67
Dankania	Cupressus torulosa	102.10	19.67	121.77	104.7	19.91	124.62	2.84
	Pyrus pashia	0.68	0.16	0.85	0.74	0.18	0.91	0.06
	Aesculus indica	3.36	1.23	4.58	3.39	1.24	4.62	0.04
	Total	106.14	21.06	127.20	108.83	21.32	130.15	2.94
Manora	Cupressus torulosa	80.37	18.45	98.82	82.32	18.72	101.04	2.21
	Cedrus deodara	5.46	1.16	6.62	5.6	1.18	6.78	0.15
	Pinus roxburghii	0.58	0.13	0.72	0.63	0.14	0.77	0.06
	Total	86.42	19.74	106.17	88.55	20.04	108.59	2.42
Takula	Cupressus torulosa	79.31	21.48	100.80	81.6	21.75	103.35	2.55
	Cedrus deodara	5.77	1.02	6.79	5.87	1.02	6.89	0.1
	Quercus leucotrichophora	48.01	16.57	64.59	49.77	17.01	66.78	2.19
	Rhododendron arboreum	2.85	0.77	3.62	2.86	0.78	3.65	0.03
	Total	135.94	39.85	175.79	140.09	40.57	180.66	4.87
Oak Park	Cupressus torulosa	171.68	27.52	199.19	174.95	27.87	202.82	3.62
	Quercus floribunda	2.05	0.62	2.67	2.11	0.63	2.74	0.07
	Quercus leucotrichophora	3.13	1.15	4.28	3.24	1.18	4.42	0.14
	Ilex dipyrena	0.25	0.03	0.29	0.27	0.03	0.3	0.01
	Total	177.11	29.32	206.43	180.57	29.71	210.27	3.84
Naina-Peak	Cupressus torulosa	117.23	22.25	139.47	120.38	22.55	142.94	3.47
	Quercus floribunda	21.46	5.00	26.45	21.66	5.03	26.69	0.24
	Rhododendron arboreum	0.58	0.20	0.78	0.6	0.2	0.8	0.02
	Lyonia ovalifolia	2.02	0.18	2.19	2.04	0.18	2.21	0.02
	Cedrus deodara	3.27	0.41	3.68	3.32	0.42	3.73	0.05
	Total	144.55	28.03	172.58	148	28.38	176.37	3.8

Where, AGCS-aboveground carbon stock, BGCS-belowground carbon stock, TCS-total carbon stock, CSR-carbon sequestration rate

Soil physico-chemical properties

Soil physico-chemical parameters differed significantly across forest stands and depths (p < 0.05), except for sand, silt and pH between depths. Site and depth combined interactions also showed significant variation in water holding capacity and all chemical parameters (Supplementary Table 1). Depth-wise detailed descriptions of soil physico-chemical properties are given in (Table 5a-b).

Across all forest sites and soil depths, the soil texture ranged from loam, clay loam to clay. Irrespective of soil depth, the soil moisture ranged from 1.08 (Farsauli site) to 17.68% (Dankaniya) across sites. The minimum and maximum bulk density ranged from 0.67 g cm^− 3 at 0–10 cm depth (Farsuali) to 1.90 g cm^− 3 at 40–50 cm depth (Dankaniya), whereas, porosity varied between 26.83% at 40–50 cm depth (Dankaniya) to 74.10% at 0–10 cm depth (Farsuali) across cypress forests. The average water holding capacity was highest at 0–10 cm depth in Dankaniya stand (61.33%) while, lowest at 50–60 cm depth in Manora stand (14.60%).

Among soil chemical properties, pH fluctuated between 5.83 (Dankaniya) and 7.60 (Oak Park). Soil organic carbon (SOC), total nitrogen (TN) and available potassium (K) levels were higher at high attitude cypress stands (Oak Park and Naina Peak stands), whereas lower at low altitude stands (Farsauli and Manora stands). SOC levels were minimum at 50–60 cm depth in Manora (1.24%), while, maximum at 0-10cm depth in Naina Peak (5.94%). TN levels

Table 5

a. Soil physical properties across different cypress stands
Sites	Depth	Gravel (%)	Sand (%)	Silt (%)	Clay (%)	Texture	SMC (%)	pH	BD (g cm^− 3)	Porosity (%)	WHC (%)
Dankaniya	0–10	24.61 ± 6.96	29.18 ± 0.58	35.52 ± 1.10	35.30 ± 1.58	Clay loam	9.17 ± 1.26	6.03 ± 0.07	0.67 ± 0.14	74.10 ± 5.38	61.33 ± 2.03
	10–20	35.40 ± 10.34	27.05 ± 3.28	33.57 ± 1.75	39.39 ± 3.13	Clay loam	11.44 ± 1.15	5.93 ± 0.07	0.85 ± 0.14	67.51 ± 5.36	48.63 ± 1.84
	20–30	44.35 ± 3.38	25.73 ± 2.73	30.14 ± 2.01	44.73 ± 1.69	Clay	15.05 ± 2.09	5.83 ± 0.07	0.96 ± 0.13	62.96 ± 4.97	50.00 ± 2.65
	30–40	30.85 ± 2.38	26.61 ± 3.14	33.41 ± 2.98	39.98 ± 6.02	Clay loam	17.09 ± 3.10	5.90 ± 0.10	0.84 ± 0.14	67.79 ± 5.34	45.90 ± 1.07
	40–50	43.43 ± 15.43	32.21 ± 3.25	32.58 ± 0.49	35.21 ± 3.73	Clay loam	17.68 ± 2.53	5.83 ± 0.03	1.03 ± 0.20	60.41 ± 7.65	45.00 ± 2.52
	50–60	42.65 ± 5.57	28.58 ± 2.47	32.77 ± 2.06	38.66 ± 4.53	Clay loam	16.43 ± 2.61	5.83 ± 0.07	1.01 ± 0.19	60.99 ± 7.30	43.67 ± 1.67
Farsuli	0–10	69.30 ± 5.21	33.34 ± 6.43	33.34 ± 5.59	33.33 ± 5.29	Clay loam	1.08 ± 0.51	6.67 ± 0.03	1.11 ± 0.03	57.37 ± 1.06	44.57 ± 1.55
	10–20	95.73 ± 6.41	33.33 ± 5.89	33.34 ± 5.47	33.33 ± 6.00	Clay loam	2.47 ± 0.27	6.77 ± 0.03	1.68 ± 0.03	35.39 ± 1.06	36.17 ± 2.14
	20–30	83.91 ± 2.05	33.33 ± 4.75	33.33 ± 5.46	33.33 ± 4.29	Clay loam	2.97 ± 0.15	6.87 ± 0.03	1.41 ± 0.02	45.80 ± 0.71	31.07 ± 1.95
	30–40	74.59 ± 2.83	33.33 ± 5.18	33.33 ± 5.74	33.33 ± 4.11	Clay loam	2.17 ± 0.62	6.67 ± 0.03	1.47 ± 0.02	43.24 ± 0.68	25.33 ± 1.54
	40–50	81.91 ± 0.96	33.33 ± 5.16	33.33 ± 4.41	33.33 ± 3.65	Clay loam	1.59 ± 0.39	6.77 ± 0.03	1.31 ± 0.06	49.57 ± 2.18	20.67 ± 2.01
	50–60	84.15 ± 2.44	33.33 ± 5.13	33.33 ± 5.29	33.33 ± 5.48	Clay loam	1.30 ± 0.21	6.67 ± 0.03	1.35 ± 0.01	48.05 ± 0.38	15.90 ± 0.78
Manora	0–10	59.68 ± 10.93	38.11 ± 1.48	38.61 ± 0.10	24.86 ± 1.57	Clay loam	4.30 ± 0.45	6.93 ± 0.03	1.22 ± 0.21	53.12 ± 7.87	24.53 ± 1.43
	10–20	61.43 ± 2.69	33.84 ± 0.47	38.88 ± 0.28	28.02 ± 0.74	Clay loam	2.35 ± 0.54	7.10 ± 0.10	1.20 ± 0.01	53.64 ± 0.40	20.47 ± 1.56
	20–30	85.31 ± 4.36	33.58 ± 0.26	38.99 ± 0.08	27.78 ± 0.35	Clay loam	3.70 ± 0.03	7.20 ± 0.10	1.43 ± 0.07	45.10 ± 2.74	16.17 ± 0.28
	30–40	51.08 ± 14.94	32.58 ± 0.64	38.22 ± 0.83	29.00 ± 0.19	Clay loam	3.78 ± 0.82	7.27 ± 0.03	1.02 ± 0.35	60.65 ± 13.68	15.77 ± 0.58
	40–50	51.14 ± 11.46	32.41 ± 0.76	40.79 ± 0.28	27.29 ± 0.49	Clay loam	5.19 ± 0.25	7.27 ± 0.07	1.90 ± 0.00	26.83 ± 0.00	15.43 ± 0.34
	50–60	51.57 ± 14.46	31.40 ± 0.65	38.23 ± 1.24	29.77 ± 0.60	Clay loam	4.28 ± 0.84	7.10 ± 0.06	1.03 ± 0.34	60.46 ± 13.03	14.60 ± 0.50
Takula	0–10	60.46 ± 6.84	34.36 ± 2.44	35.86 ± 3.78	28.99 ± 2.00	Clay loam	2.89 ± 0.73	6.43 ± 0.07	0.96 ± 0.01	62.98 ± 0.22	41.17 ± 1.09
	10–20	63.40 ± 9.74	30.31 ± 1.28	31.92 ± 3.46	37.77 ± 2.56	Clay loam	4.70 ± 0.82	6.40 ± 0.10	1.16 ± 0.13	55.26 ± 5.15	36.87 ± 0.72
	20–30	81.19 ± 14.62	32.31 ± 0.67	32.89 ± 0.89	34.81 ± 1.22	Clay loam	4.93 ± 0.79	6.33 ± 0.03	1.24 ± 0.21	52.22 ± 8.03	34.13 ± 0.61
	30–40	76.32 ± 18.40	31.61 ± 0.68	36.07 ± 1.23	32.32 ± 1.12	Clay loam	5.15 ± 0.87	6.17 ± 0.07	1.46 ± 0.37	44.02 ± 14.07	33.60 ± 0.26
	40–50	92.70 ± 28.02	31.70 ± 2.62	36.71 ± 1.03	31.59 ± 1.80	Clay loam	6.16 ± 0.86	6.20 ± 0.10	1.48 ± 0.21	42.94 ± 8.04	32.73 ± 0.27
	50–60	88.36 ± 13.99	31.05 ± 2.41	36.13 ± 0.92	32.82 ± 1.56	Clay loam	6.14 ± 0.43	5.93 ± 0.03	1.47 ± 0.15	43.34 ± 5.58	31.97 ± 0.55
Oak Park	0–10	49.47 ± 22.51	39.14 ± 3.27	36.87 ± 1.49	23.99 ± 1.85	Loam	6.50 ± 2.48	7.20 ± 0.10	0.72 ± 0.22	72.51 ± 8.49	51.80 ± 1.70
	10–20	62.74 ± 8.32	37.75 ± 0.27	36.21 ± 0.78	26.04 ± 1.01	Loam	7.34 ± 1.30	7.33 ± 0.09	1.08 ± 0.20	58.63 ± 7.49	46.83 ± 1.13
	20–30	51.87 ± 9.70	37.98 ± 2.46	36.95 ± 1.08	25.07 ± 2.42	Loam	7.22 ± 1.58	7.30 ± 0.00	0.90 ± 0.17	65.35 ± 6.29	43.83 ± 1.17
	30–40	84.77 ± 25.20	35.24 ± 1.59	36.33 ± 0.42	28.42 ± 1.36	Clay loam	7.47 ± 0.82	7.50 ± 0.00	1.41 ± 0.40	45.82 ± 15.27	40.83 ± 0.44
	40–50	57.34 ± 6.49	35.55 ± 1.81	36.77 ± 1.55	27.68 ± 1.02	Clay loam	6.94 ± 1.81	7.40 ± 0.00	0.94 ± 0.13	63.88 ± 4.94	38.23 ± 0.88
	50–60	85.64 ± 32.84	35.26 ± 0.94	35.92 ± 1.71	28.82 ± 0.88	Clay loam	7.44 ± 1.47	7.60 ± 0.00	1.39 ± 0.57	46.40 ± 21.73	35.53 ± 0.24
Naina peak	0–10	44.69 ± 1.77	36.12 ± 2.18	36.59 ± 2.67	27.30 ± 1.40	Clay loam	6.37 ± 0.67	6.73 ± 0.03	0.99 ± 0.02	62.04 ± 0.75	44.53 ± 1.05
	10–20	65.60 ± 21.06	28.58 ± 0.69	34.07 ± 2.57	37.36 ± 2.79	Clay loam	7.39 ± 0.59	6.47 ± 0.03	1.24 ± 0.27	52.37 ± 10.57	39.60 ± 1.21
	20–30	61.94 ± 20.11	24.63 ± 2.12	32.39 ± 1.32	42.98 ± 3.29	Clay	8.09 ± 0.56	6.37 ± 0.03	1.23 ± 0.13	52.55 ± 4.93	35.17 ± 1.65
	30–40	56.56 ± 3.67	27.04 ± 0.72	33.70 ± 1.45	39.26 ± 1.39	Clay loam	8.45 ± 1.13	6.57 ± 0.07	1.11 ± 0.18	57.51 ± 7.13	31.93 ± 0.67
	40–50	65.89 ± 10.18	28.98 ± 1.86	33.25 ± 3.95	37.77 ± 4.81	Clay loam	9.63 ± 1.77	6.67 ± 0.07	1.39 ± 0.14	46.74 ± 5.38	29.73 ± 0.32
	50–60	90.74 ± 13.42	27.82 ± 2.44	32.78 ± 2.47	39.40 ± 4.20	Clay loam	9.01 ± 1.39	6.43 ± 0.07	1.61 ± 0.26	37.92 ± 10.05	28.70 ± 1.11

(Where, SMC-soil moisture content, BD-bulk density, Po-porosity, WHC-water holding capacity)

Table 5

b. Soil chemical properties across different cypress stands
Sites	Depth (cm)	TN (%)	SOC (%)	SOC (Mg ha^− 1)	N (kg ha^− 1)	P (%)	K (%)	C:N
Dankaniya	0–10	0.41 ± 0.01	3.96 ± 0.02	26.70 ± 5.64	642.10 ± 1.71	0.0027 ± 0.0001	0.0132 ± 0.0006	9.65 ± 0.13
	10–20	0.39 ± 0.01	3.78 ± 0.03	31.87 ± 5.06	619.43 ± 2.44	0.0026 ± 0.0001	0.0097 ± 0.0002	9.78 ± 0.16
	20–30	0.35 ± 0.01	3.45 ± 0.01	33.23 ± 4.36	616.23 ± 1.25	0.0023 ± 0.0001	0.0055 ± 0.0004	9.87 ± 0.19
	30–40	0.32 ± 0.01	3.17 ± 0.09	26.38 ± 4.14	603.00 ± 3.06	0.0020 ± 0.0000	0.0048 ± 0.0002	9.86 ± 0.70
	40–50	0.28 ± 0.01	2.83 ± 0.05	29.25 ± 6.12	588.67 ± 2.36	0.0018 ± 0.0001	0.0039 ± 0.0001	9.99 ± 0.26
	50–60	0.22 ± 0.01	2.56 ± 0.03	26.05 ± 5.02	492.57 ± 2.06	0.0013 ± 0.0001	0.0036 ± 0.0001	11.54 ± 0.59
Farsuli	0–10	0.43 ± 0.00	3.68 ± 0.02	40.78 ± 0.83	649.20 ± 2.08	0.0022 ± 0.0001	0.0141 ± 0.0002	8.49 ± 0.10
	10–20	0.40 ± 0.01	3.48 ± 0.03	58.47 ± 1.42	483.47 ± 3.65	0.0024 ± 0.0000	0.0121 ± 0.0002	8.70 ± 0.11
	20–30	0.35 ± 0.01	2.77 ± 0.03	39.04 ± 0.63	473.70 ± 2.29	0.0024 ± 0.0001	0.0099 ± 0.0002	7.93 ± 0.24
	30–40	0.31 ± 0.01	2.37 ± 0.03	34.99 ± 0.70	463.07 ± 3.77	0.0025 ± 0.0001	0.0077 ± 0.0004	7.58 ± 0.23
	40–50	0.26 ± 0.01	2.18 ± 0.02	28.56 ± 1.03	407.23 ± 3.00	0.0018 ± 0.0001	0.0066 ± 0.0002	8.53 ± 0.43
	50–60	0.18 ± 0.01	1.95 ± 0.00	26.38 ± 0.23	400.10 ± 0.75	0.0013 ± 0.0001	0.0050 ± 0.0003	10.70 ± 0.49
Manora	0–10	0.46 ± 0.01	3.38 ± 0.08	41.20 ± 7.12	253.30 ± 1.34	0.0019 ± 0.0002	0.0078 ± 0.0002	7.35 ± 0.25
	10–20	0.33 ± 0.01	2.51 ± 0.01	30.21 ± 0.12	248.30 ± 1.64	0.0023 ± 0.0001	0.0063 ± 0.0003	7.69 ± 0.26
	20–30	0.30 ± 0.01	1.85 ± 0.03	26.37 ± 1.50	244.77 ± 3.07	0.0025 ± 0.0001	0.0052 ± 0.0002	6.23 ± 0.17
	30–40	0.26 ± 0.01	1.71 ± 0.01	17.55 ± 6.14	209.47 ± 4.46	0.0025 ± 0.0001	0.0038 ± 0.0002	6.69 ± 0.19
	40–50	0.20 ± 0.00	1.45 ± 0.01	27.65 ± 0.13	191.67 ± 1.83	0.0016 ± 0.0002	0.0022 ± 0.0002	7.15 ± 0.10
	50–60	0.17 ± 0.01	1.24 ± 0.01	12.78 ± 4.27	151.63 ± 2.10	0.0015 ± 0.0001	0.0019 ± 0.0001	7.20 ± 0.41
Takula	0–10	0.40 ± 0.00	3.49 ± 0.01	33.59 ± 0.29	400.50 ± 3.29	0.0018 ± 0.0000	0.0122 ± 0.0002	8.65 ± 0.05
	10–20	0.37 ± 0.01	2.68 ± 0.02	31.16 ± 3.72	369.27 ± 3.01	0.0015 ± 0.0000	0.0077 ± 0.0004	7.31 ± 0.13
	20–30	0.33 ± 0.01	2.56 ± 0.01	31.88 ± 5.47	356.70 ± 3.82	0.0013 ± 0.0000	0.0050 ± 0.0002	7.71 ± 0.33
	30–40	0.30 ± 0.01	2.51 ± 0.01	36.67 ± 9.42	342.23 ± 2.02	0.0011 ± 0.0000	0.0031 ± 0.0002	8.40 ± 0.30
	40–50	0.27 ± 0.00	2.48 ± 0.01	36.90 ± 5.41	301.93 ± 3.23	0.0011 ± 0.0001	0.0022 ± 0.0001	9.32 ± 0.17
	50–60	0.22 ± 0.01	2.40 ± 0.01	35.43 ± 3.60	257.40 ± 4.42	0.0009 ± 0.0001	0.0018 ± 0.0001	11.13 ± 0.41
Oak Park	0–10	0.50 ± 0.01	5.08 ± 0.04	36.33 ± 11.31	381.43 ± 2.75	0.0014 ± 0.0001	0.0162 ± 0.0003	10.11 ± 0.35
	10–20	0.43 ± 0.01	4.19 ± 0.04	45.01 ± 8.08	372.43 ± 2.38	0.0013 ± 0.0001	0.0150 ± 0.0002	9.67 ± 0.24
	20–30	0.39 ± 0.01	3.61 ± 0.05	32.40 ± 5.63	342.10 ± 2.09	0.0015 ± 0.0001	0.0139 ± 0.0001	9.35 ± 0.30
	30–40	0.33 ± 0.01	3.15 ± 0.02	44.21 ± 12.25	319.70 ± 3.27	0.0014 ± 0.0001	0.0149 ± 0.0001	9.65 ± 0.30
	40–50	0.29 ± 0.01	3.09 ± 0.03	29.03 ± 4.02	253.77 ± 1.51	0.0012 ± 0.0000	0.0156 ± 0.0003	10.54 ± 0.25
	50–60	0.25 ± 0.01	2.83 ± 0.09	40.47 ± 17.59	273.33 ± 6.05	0.0011 ± 0.0000	0.0150 ± 0.0001	11.19 ± 0.04
	0–10	0.61 ± 0.02	5.94 ± 0.04	58.62 ± 1.03	420.90 ± 3.10	0.0021 ± 0.0001	0.0146 ± 0.0003	9.75 ± 0.31
	10–20	0.60 ± 0.00	5.88 ± 0.02	72.88 ± 16.40	374.37 ± 5.98	0.0018 ± 0.0000	0.0126 ± 0.0003	9.85 ± 0.06
Naina peak	20–30	0.59 ± 0.01	5.75 ± 0.03	71.04 ± 7.69	359.30 ± 2.44	0.0021 ± 0.0001	0.0127 ± 0.0012	9.81 ± 0.14
	30–40	0.56 ± 0.01	5.30 ± 0.02	58.50 ± 9.82	278.03 ± 3.14	0.0019 ± 0.0001	0.0088 ± 0.0002	9.53 ± 0.24
	40–50	0.49 ± 0.01	5.18 ± 0.02	71.66 ± 7.09	246.40 ± 2.34	0.0025 ± 0.0001	0.0083 ± 0.0002	10.66 ± 0.31
	50–60	0.43 ± 0.01	4.07 ± 0.08	65.26 ± 9.45	220.27 ± 3.92	0.0014 ± 0.0001	0.0069 ± 0.0002	9.46 ± 0.20
(where, TN-total nitrogen (%), SOC-soil organic carbon (%), TOC-total organic carbon (%), N-available nitrogen, P-available phosphorous (%), K- available potassium (%), C:N-carbon to nitrogen ratio

were maximum at Naina Peak stand (5.35%, 9.20% and 0.54%, respectively), while minimum at Manora stand (2.02%, 3.48% and 0.29%, respectively). On the other hand, SOC stock level was highest at 10-20 cm depth at Naina Peak stand (72.88 Mg ha^-1) while, lowest at 50-60 cm depth at Manora stand (12.78 Mg ha^-1). Available nitrogen (N) content was highest at 0-10 depth (649.2 kg ha^-1) in Manora stand, while, lowest at 50-60 cm depth (151.63 kg ha^-1) in Farsauli stand. Available phosphorous (P) levels were highest at 0-10 cm depth (0.0027%) in Dankaniya stand, while, in Takula stand lowest levels were evaluated at 50-60 cm depth (0.0009%). Available potassium (K) levels were lowest at 50-60 cm depth in Takula stand (0.0018%), while, highest in Oak Park stand (0.0162%). C: N ratio ranged between 6.23 (at 20-30 cm depth in Manora stand) and 11.54 (at 50-60 cm depth in Dankaniya stand).

Correlation analysis revealed that with increase in elevation, soil pH, total nitrogen, organic and total carbon and, potassium content significantly (p < 0.05) increased except for the available nitrogen and phosphorous. Depth-wise all soil nutrient stocks significantly declined while, gravel, clay, bulk density and C:N ratio significantly increased (Table 6).

The floristic composition of a plant community provides an overall understanding of the structure and functioning of any ecosystem and has frequently been the subject of ecological studies (Singh et al. 2016). In the present study, tree species diversity ranged between 0.42 and 0.85. Generally, monospecific forest types are unable to sustain high floral diversity in contrast to mixed forests which provide heterogenous environment allowing co-existence of various species (Tiwari et al. 2019). Species richness observed in the present study (3–5) are comparable to earlier reported values from temperate forest of Kumaun, Central Himalaya (Bargali et al. 2013; Rana et al. 2015), as well as from temperate forest of Garhwal Himalaya (Singh et al. 2014) and Western Himalaya (Joshi et al. 2021).

In the present study, tree density ranged from 440 to 1050 ha^− 1 which is comparable with the values reported for Cypress forests in the previous studies, such as 270–510 ha^− 1 by Adhikari et al. (1998) and 460–600 ha^− 1 by Rana et al. (2015) from the Central Himalayan forests (Table 7). The variation in tree basal area, ranging from 30.84 to 60.79 m² ha^− 1, suggests diverse age structures across sites, where higher values indicate the dominance of mature trees with lower density, while lower values signify denser stands with a younger demographic composition (Negi et al. 2023).

The values of biomass obtained in the present study are in the range of 223.51–434.6 Mg ha^− 1 with highest values recorded from Takula stand whereas, lowest across Dankaniya stand. Differences among stands could be most likely due to vegetation type, species composition, girth class of individual trees, temperature, rainfall pattern and altitude, as these variables have a profound effect on biomass (Pant and Tewari 2020). The biomass values evaluated in the present study are comparable to those reported by Adhikari et al. (1998) for cypress forests in the Nainital region of Central Himalayas, ranging from 239 to 433 Mg ha^− 1. When compared with other coniferous species such as Pines, the biomass values of Cypress forests in present study were higher; however, they were lower than those observed for Cedrus deodara and Abies pindrow forests (Table 7). Our study indicates that the density of individual tree species affects total biomass and carbon storage.

The carbon stock trend paralleled that of biomass since carbon content is directly proportional to biomass. Our estimates of carbon stock values (106.2-206.4 Mg C ha^− 1) are within the range given by Verma and Garkoti (2019), Lal and Lodhyal (2016), Joshi et al. (2021) for central Himalayan broad leaf forests. While, higher than Pine forests reported by Singh (2019), Gusain et al. (2015), Lal and Lodhyal (2016), Pant and Tiwari (2020), Bisht (2023), and lower than Cedrus and Abies forests (Sharma et al. 2013; Kumar et al. 2024). The reported range of biomass carbon stock at a global scale varies widely across different regions and forest types. For example, in temperate rainforests of USA, it ranges from 506 to 627 Mg C ha^− 1 (Smithwick et al., 2002), while in Northeast China temperate and boreal forests, it ranges from 58.9 to 386.5 Mg C ha^− 1 (Wei et al., 2013). In Panama, across tropical forests, the range is even broader, from 12.96 to 856.50 Mg C ha^− 1 (Ruiz-Jaen and Potvin, 2011). These variations highlight the diverse carbon storage capacities of forests worldwide, influenced by factors such as climate, vegetation type, and land management practices (Singh and Verma 2018).

Table 7

Comparisons of tree density, biomass and carbon stock of present and previous studies in the Central Himalayan forests.
Forests	Region	Location	Altitude (m)	Tree density (ind. ha^− 1)	Biomass (Mg ha^− 1)	C-stock (Mg C ha^− 1)	Reference
Cypress forest	India	Nainital	1684-2319.5	440–955	223.51–434.6	106.2-206.4	Present study
Oak forest		Almora	1790–1930	390–1500	145–503	68.29–247.61	Verma and Garkoti(2019)
Mixed oak forest		Nainital	1500–2100	910–1100	481.05- 568.99	228.5- 270.3	Lal and Lodhyal (2016)
Oak forest		Nainital	1750–1950	652	230.12	230.12	Joshi et al. 2021
Mixed-Oak Forest		Nainital	2000–2250	884	227.23	107.94	Joshi et al. 2021
Pine forest		Nainital	1600	300–300	175.5–245.6	83.36–116.6	Singh (2019)
Pine forest		Almora	1780–2120	1254	117.17 ± 10.81	55.66 ± 5.13	Gusain et al. (2015)
Pine forest		Nainital	1600	1040–1260	154–301	73–143	Lal and Lodhyal (2016)
Pine forest		Nainital	1750–1850	390–3050	97.87–158.97	46.48–74.66	Pant and Tiwari (2020)
Pine forest		Nainital	1750–1950	650	285.27	135.5	Bisht 2023
Pine forest		Garhwal Himalaya		250–300	203.02-230.84		Shiekh et al. 2012
Cypress forest		Nainital	2100–2325	270–510	239–433	–	Adhikari et al. (1998)
Cypress forest		Nainital	2120–2325	460–600	178–431	89.07–206	Rana et al. (2015)
Himalayan Cupressus torulosa Don.		Jhandidhar, Garhwal	2100–2500	810.0 ± 82.5	336.56 ± 62.80	154.82 ± 28.89	Sharma et al. 2013
Moist Cedrus deodara Loud.		Binsar, Tarkeshwar, Garhwal	2200–2500	447.5 ± 36.3	533.28 ± 39.61	245.31 ± 18.22
Abies pindrow		Dudhatoli, Garhwal	2600–3100	507.5 ± 21.7	377.65 ± 38.64	173.72 ± 17.77
Siwalik Pinus roxburghii		Fatehpur, Dabrad, Deogaddi, Garhwal	750–1250	685.0 ± 108.0	298.04 ± 56.03	137.10 ± 25.78
Himalayan Pinus roxburghii Sarg		Thalisain, Garhwal	1500–1800	525.0 ± 41.7(	159.36 ± 15.80	73.30 ± 7.27
Cedrus deodara pure stand (CDP)		Chail, Solan	2080	303.3 ± 20.8	782.6 ± 107.9	360 ± 49.7	Kumar et al. 2024
Abies pindrow dominated stand (APD		Churdhar, Sirmaur	2965	546.6 ± 90.7	700.2 ± 334	322.1 ± 154.1
Abies spectabilis pure stand (ASP)		Churdhar, Sirmaur	3235	370 ± 72.1	515.5 ± 29.5	249.4 ± 18.7
Cypress forest		Northwest Patagonia	650–1500	-	112.2	73.2	Laclau 2002

Further, our study showed that biomass and carbon stock peaked at mid altitude followed by high altitude stands. However, our findings didn’t fully support the findings of few previous studies which reported that forest biomass and carbon stocks increase with increasing altitude in the Himalayan region. Most of the forest types studied in this study were mature, fully stocked, old growth forests and had C stocks on the higher end of the values recorded for the forests of the India and elsewhere in the world (Table 7), which infers that these forests have higher amount of C stock. The proportion of above and below ground biomass was observed 83% and 17%, correspondingly, which is consistent to the value reported for Indian forest i.e., 79% and 21% (Chhabra et al. 2002).

The tree carbon sequestration rates ranged between 2.42 to 4.87 Mg ha^− 1 yr^− 1 across the study sites. Singh et al. (1985) reported a range of carbon sequestration rate of 5–9 Mg ha^− 1 yr^− 1 in better managed forests and 1.5 to 3 Mg ha^− 1 yr^− 1 in the medium-quality forests for Uttarakhand forests. When compared with coniferous forests across the world, the carbon sequestration range were within the reported range (Table 8). Stand wise, the Takula stand exhibited highest carbon sequestration rates, likely due to its high tree density and low basal area indicating the predominance of younger trees. Since younger trees grow rapidly, they absorb significant amounts of carbon dioxide from the atmosphere to fuel their growth, leading to higher rates of carbon sequestration (Terakunpisut et al. 2007). It can be concluded that the forest is not yet fully mature, but has the potential to continue sequestering carbon as these trees grow and mature further.

Table 8

Carbon sequestration rate of different forest species in Himalaya and world forests.
Forest	Region	Carbon sequestration rate (Mg ha^− 1 yr^− 1)	References
Cypress forest	Kumaun Himalaya, India	2.42–4.87	Present study
P. roxburghii forest		3.1–6.07	Pant and Tewari 2013
P. roxburghii forest		0.2–3.96	Pant and Tewari 2020
Oak forests		2.64 ± 0.27	Gosain et al. 2015
Pine forests		3.96 ± 0.65	Gosain et al. 2015
Cunninghamia lanceolata	China	2.15 to 4.20	Zhang et al. (2007),
Pinus massoniana	China	2.15 to 4.28	Zhang et al. (2007),
Pinus banksiana and Picea mariana	Cannada	2.1–3.7	Hunt et al. (2010)
Coniferous forests	Pakistan	1.65	Adnan et al. (2015)
Cunninghamia lanceolata, Cryptomeria japonica, Taiwania cryptomerioides, Chamaecyparis formosensis (plantation forests)	Taiwan	1.79–4.03	Yen et al. 2020
Temperate forests		4.19	Press et al. 2000
Boreal forests		1.4	Press et al. 2000

In the present study, carbon reserves in soils across cypress stands were higher (9–57%) than those in the trees' biomass (Fig. 3). Soil organic carbon is considered to be one of the largest carbon reservoirs of the terrestrial ecosystems and also plays an important role in the global carbon cycle (Dar and Sundarapandian 2013). The soil organic carbon stocks have been reported to increase with an increase in forest age (Zhu et al. 2010), which was evident across high altitude Naina Peak stands, in our study. The soil carbon stock values in our study were higher than those reported in various studies by Chaturvedi and Melkania (2013), Gosain et al. (2015), Dar and Sundarapandian (2013), Laclau (2000), Zhang et al. (2020), and Zhu et al. (2010), across different coniferous stands worldwide (Table 9). However, they were lower than those reported for boreal forests by IPCC (2007).

Table 9

Soil carbon stock of different forest type in Himalaya and world forests
Forest	Area	SOC (Mg ha^− 1)	References
Cypress forest	Kumaun Himalaya	173.42–398.80	Present study
Mixed Oak Forest	Kumaun Himalaya	43.81 to 53.47	Chaturvedi and Melkania 2013
Mixed Pine Forest		110.37 to 125.03	Chaturvedi and Melkania 2013
Oak forests		171.8	Gosain et al. 2015
Pine forests		73.7	Gosain et al. 2015
Pinus wallichiana and Abies pindrow forests	Western Kashmir Himalayas	50.37 to 55.38	Dar and Sundarapandian 2013
Boreal forest		338.8	IPCC 2007
Cypress forest	Andean range, Northwest Patagonia	109.8	Laclau 2000
Temperate forest	China	93.7-220.1	Zhang et al. 2020
Temperate mix old growth forest	China	62.7–88.7	Zhu et al. 2010

In Himalayas, bioclimatic conditions change rapidly and may vary within short distances resulting in a pronounced heterogeneity of soil types and their chemical and physical properties (Bargali et al. 2018). Our study highlighted highest levels of soil organic carbon (SOC), total nitrogen (TN) and potassium (K) across high altitude C. torulosa stands as indicated by positive correlation between elevation and soil nutrient content. High altitude soils have more soil organic carbon and nitrogen because low temperature causes hyper aridity of soil and suppresses microbial and enzymatic activities which results in slight and slow soil organic matter mineralization and decomposition, thereby affecting the process of nutrient cycling (Charan et al. 2013). The decline in soil nutrient stocks with increasing depth could be attributed to the fact that decomposition of organic matter takes place in the uppermost layers of the soil (Hong, Gan and Chen 2019). In the present study, high C:N ratio at higher altitudes indicate higher availability of N in the forest floor material, whereas, lower ratio in low altitudes stands indicates faster nitrogen release to the soil (Kewlani et al. 2021).

Relationship between carbon storage in both above and below ground component and sequestration rate was negative with available nitrogen and phosphorous levels although observed differences were not significant in most cases. This negative relationship can indicate that nitrogen and phosphorus is being utilized by trees for growth, leading to a depletion in their levels in the soil. Supporting this several studies have shown soils with higher tree biomass tended to have lower available nitrogen and phosphorus levels (Alvarez-Clare et al. 2013; Sun et al. 2013; Hu et al. 2024).

Cypress stands with high tree density have the great potential to sequester more carbon. Carbon sequestration was higher in younger to older forests of Cupressus. The findings suggest that the Cypress stands are moderately effective in sequestering carbon, with potential for further improvement through appropriate management practices. Soil nutrient stocks appears to decrease with increasing depth while, increase with increasing altitude. Results in the present study indicate variation in biomass and carbon pool across Cypress stands. The carbon reserves in soils across cypress stands were higher than those in the trees biomass. This study highlights the importance of cypress forests, emphasizing not just their capacity for sequestering biomass carbon but particularly their substantial soil carbon reserves. Additionally, this study provides useful background for future research to assess the trend of carbon sequestration in Cypress stands.

Funding

declaration: R.K.C. thanks NSFC (Grant No. 31750110466).

Author Contribution

"D.U. , L.M.T., A.T., N.C.P., and R.K.C. wrote the main manuscript text and D.U. and A.T. prepared figures 1-3. All authors reviewed the manuscript.

Acknowledgement

The authors are thankful to the Forest Department of district Nainital, Uttarakhand for granting permission to conduct this study. The authors also acknowledge Head, Department of Botany, D.S.B. Campus, Kumaun University, Nainital. RKC thanks the Central Laboratory, Xishuangbanna Tropical Botanical Garden, Menglun, China.

Data Availability

Data is provided within the manuscript

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Table 6 is available in the Supplementary Files section

No competing interests reported.

Carbon Sequestration Potential of Himalayan Cypress Stands of Kumaun Central Himalaya, India

Status:

Version 1

Abstract

Figures

Introduction

Material and Methods

Study area

Soil sampling and analysis

Vegetation sampling and analysis

TCS = AGCS + BGCS + SOC

Statistical analysis

Results

Forests vegetational parameters

Biomass distribution and carbon sequestration rate

Soil physico-chemical properties

Discussion

Conclusion

Declarations

Funding

Author Contribution

Acknowledgement

Data Availability

References

Table

Additional Declarations

Supplementary Files

Status:

Version 1