CO₂ Mitigation Potential of Traditional Agroforestry Systems along Elevations in Tehri District of North West Himalaya, India

1. Introduction

Climate change is now impacting agricultural production, food stability and nutritional security across the world. Agricultural systems, such as agroforestry, that integrate trees with livestock and crops on the same land has been adopted in developing countries to strengthen the climate change resilience of small stakeholders who have limited resources. In tropical countries such as Kenya, Brazil and Indonesia, government programs are run to cultivate trees plus crops on farmland to reduce the effect of climate change [1]. India became the first country in the world to adopt an agroforestry policy (10 February 2014). The “Trees Outside Forests in India” programme has been launched as a joint initiative of the Ministry of Environment, Forest and Climate Change, Government of India and the United States Agency for International Development (USAID). The initiative is mainly to expand the area under trees outside of forests and to mitigate climate change [2]. The current area under agroforestry is estimated from LISS III satellite data to be 13.75 M ha of the total geographical area of the country using by the Central Agroforestry Research Institute (CAFRI) [3]. Increasing temperature is mainly due to rising CO₂ levels in the atmosphere and there is need to take necessary action to reduce the effect of climate change. Agroforestry can play a significant role to sequester atmospheric CO₂ which may help to mitigate climate change. A proposal has been approved by the Cabinet Committee on Economic Affairs as a National Mission for a green India as a centrally sponsored scheme. The main objective of the mission includes increased forest/tree cover and improved quality of forest cover across in two to eight million hectares, along with improved ecosystem services including biodiversity, hydrological services, and an increased forest-based livelihood income for households that live in and around the forests, and enhanced annual CO₂ sequestration [4]. India is the third highest country in the world for in green house gas emissions after China and the United States. India promises to reduce green house gas emission intensity by 33 to 35 percent by 2030 [5]. If the agroforestry technique is to be used for climate change mitigation through carbon sequestration, then accurate data is required on living biomass [6]. Therefore, the main objective of the study was to examine the CO₂ mitigation efficiency of agroforestry systems across different elevations in North Western Himalaya, in the Tehri District, Uttarakhand, India.

2. Materials and methods

2.1. Study area

The present study was carried out from 2014-2018 in the Tehri Garhwal district of Uttarakhand (Figure 1) which is the part of North Western Himalayan region . The district lies between latitude of 30⁰03' and 30⁰ 53' North l and longitudes 77⁰ 56' and 79⁰ 04' East and has an area of 3,642 km² [7]. The area under forest cover is 2236 km² and 1142.42 km² is under cultivation [7] .The Tehri district has been divided into three agro-climatic zones viz: sub-tropical zone (300-1200m), sub-temperate zone (1200-2000m) and temperate zone (2000-2800 m) on the basis of topography, elevation and temperature condition [8].

2.2. Methodology

Stratified random sampling techniques were used for this study. Out of nine blocks, six blocks on three elevations i.e. 286-1200m, 1200-2000m and 2000-2800m were selected in the district for first stage sampling. Thirty two villages were selected randomly from six blocks, seven villages from Deoparayag block, six villages each from Kirtinagar & Chamba blocks, five villages from Pratapnagar block and four villages each from Thauldhar & Jakhnidhar blocks. Considering the elevations, 14 villages were situated in lower elevation (286-1200m), 13 villages were in middle elevation (1200-2000m) and five villages were in upper elevation (2000-2800m). In the second stage of sampling, list of farmers of each villages were prepared on the basis of concerned block office records. Total, 540 farmers were selected randomly. Most of agroforestry systems have been identified at each elevation of each block. On the basis of structure and function of different land use systems, most important components were identified. Ten sample plots of 100 m² size were randomly marked in each village. All individual trees, shrubs and fruits species were recorded within 100 m² size plot and crops, grasses and weeds species were recorded in 1m² size nested plot and density was estimated by formula given by Muller-Dombios and Ellenberg (1974) [9]. Tree height was determined by Haga altimeter and DBH was measured by tree caliper. Collected data was in unequal replication and analyzed by analysis of variance (ANOVA) and least significant difference (LSD) statistical tools. Stem volume was measured using the Pressler 1985 [10] and Bitterlich 1984 [11] formula V=f × h × g (where V is volume, f is form factor, h is total height and g is basal area). Stem biomass was estimated by multiplying the stem volume with wood specific gravity [12] using the maximum moisture content method [13]. Branch and leaf biomass was estimated using the fresh and dry weight ratio [14]. Factor of 0.25 for broad-leaved species and 0.20 for coniferous species were multiplied with above ground biomass for below ground biomass [15]. 0.45 Factor was multiplied with biomass for value of carbon stock [16]. Destructive method was used for crop and grass biomass using 1m² quadrate. Fresh weight was converted into dry weight on the basis of plant samples kept in the oven for drying at 80oC for 24 hours. Total carbon was converted in to CO₂ mitigation by multiplied carbon stock value with the factor of 3.67 [17]. One tone of sequestrated CO₂ in the form of living biomass is equal to one C credit. One carbon credit is equal to €3.00 [18]. Soil carbon in same agroforestry sites was also estimated. 10 pre-existing sample plots of 100m² were also selected for soil carbon estimation. Composite samples were obtained for three soil layers, 0-10, 10-20 and 20-30 cm. Weighing bottle method were used for determining bulk density [19]. Walkley and Black (1934) method [20] were used for estimating soil organic carbon percentage. Soil carbon stock (Mg ha^-1) was calculated by using the Pearson et al. (2007) [17] equation.

3. Results

The three common agroforestry systems were identified in Tehri district which are agrisilviculture system-AS (includes trees and agriculture crops), agrihorticulture system-AH (includes edible fruit trees and agriculture crops), and agrihortisilviculture system-AHS (trees including edible fruit trees, forest trees and agriculture crops) (Table 1). In different agroforestry systems, predominant forestry species were Grewia oppositifoila, Celtis australis, Melia azedarach, Bauhinia variegata, Ficus roxburghii, Boehmeria regulosa, Quercus leucotrichophora, Myrica esulenta, whereas, Mangifera indica, Musa pradisica, Citrus sinensis, Prunus persica, Pyrus cuminis, Malus domestica, Psidium guajava, Punica grantum and Emblica officinalis were the common fruit species (Table 1). Predominant annual crops were Triticum aestivum (Wheat), Oryza sativa (Rice), Ehinochloa frumentacea (Barnyard millet), Eleusine coracana (Finger millet), Hordeum vulagare (Barley), Zea mays (Maize), Cajanus spp. (Pigeon pea), Glycine max (Soyabean), Amarnathus blitum (Chaulai), Pisum sativum (Pea), Allium cepa (Onion), Solanum tuberosum (Potato), Vigna mungo (Urd) and Brassica compestris (Sarson). Considering the agroforestry systems across elevations, G. oppositifolia, C. australis, M. azedarach, B. variegata, F. roxburghii and T. ciliata were the most common tree species present across two elevations (286-1200 & 1200-2000m) in AS and AHS, whereas, Q. leucotrichophora also common tree species present across two altitiudes (1200-2000 & 2000-2800m) in AS and AHS. However, Grewia oppositifolia was one of the species thriving in the diverse altitudinal range in AS and AHS. The most common fruit tree species Citrus limon, C. sinensis, C. aurentium, Mangifera indica, Musa prasdisica, Psidium guajava and Emblica officinalis were present across two elevations (286-1200 & 1200-2000m) in AHS and AH, while Malus domestica, Juglans regia, C. limon and C. sinensis were also common fruit tree species present across two elevations (1200-2000 & 2000-2800m) in AHS and AH. Triticum aestivum, Echinochloa frumentacea, and Eleusine coracana were the most common annual crops grown by the farmers across the three elevations under agroforestry systems (Table 1). The vegetables, oil and pulses crops viz. Solanum tuberosum, Allium cepa, Brassica compestris, Glycine max, Cajnus spp. and Vigna mungo were also grown by most of the farmers across the elevations.

Tree density both forest and fruit trees varied from 61 tree ha^-1 in AHS system to 233 tree ha^-1 in AH system across the elevations (Table 2). The tree densities including fruit trees at lower elevation of AS, AHS and AH systems were 227, 230 and 181 ha^-1, respectively, whereas at middle elevation of AS, AHS and AH systems were 216, 243 and 233 ha^-1, respectively. At upper elevation tree densities of AS, AHS and AH systems were 152, 206 and 148 ha^-1, respectively. The density was higher at middle elevation as compared to lower and upper elevation, whereas, density value was higher in AHS system as compared to AS and AH systems across the elevations. Grewia oppositifolia was dominant forest tree species having maximum density (90 trees ha^-1) in AHS system (77 trees ha^-1) in AS system as compared to AH system at middle elevation followed by Ficus roxburghii (45 trees ha^-1) in AS system at middle elevation and Celtis australis (41 trees ha^-1) in AHS system at lower elevation. Whereas, dominant fruit trees are Mangifera indica with maximum density (37 trees ha^-1) and (35 trees ha^-1) respectively at lower and middle elevation in AH system as compared to AHS system followed by Citrus sinensis (35 trees ha^-1) in AH system at middle elevation and Musa paradisiaca (34 trees ha^-1) in same system at lower elevation (Table 2). Similarly, Quercus leucotrichophora was dominant forest tree having maximum density (58 trees ha^-1) in AS system and (51 trees ha^-1) in AHS system followed by Grewia oppositifolia (40 trees ha^-1) in AS system at upper elevation, while dominant fruit trees species were Citrus sinensis and Malus domestica have maximum density (32 trees ha^-1) respectively in AH system as compared to AHS system at upper elevation (Table 2). Across the elevations, AHS system contained maximum density followed by AS system, while, higher density were recorded at middle and lower elevations.

The total biomass and carbon stock was found comparatively higher at lower elevation than middle and upper elevations across the systems. Whereas, across the elevations AHS system contained higher biomass accumulation and carbon stock than AS and AH systems (Table 3). CO₂ mitigation showed significant difference (P ≤ 0.05) at lower elevation across the system. Whereas, across the elevations AHS system showed significant difference (P ≤ 0.05) and estimated higher CO₂ mitigation than AS and AH system (Table 3).

The Net carbon stock of different agroforestry land systems, including soil organic carbon and plant biomass carbon is given in Table 4. Carbon pools compared with plant and soil indicated that soil organic carbon was significantly higher (P ≤ 0.05) than that of plant C pools across the elevations. Total C pools including plant and soil recorded significantly higher (P ≤ 0.05) in AH system as compared to AHS and AS system across the elevations. Statistically lowest C pool was recorded in AS system across the elevations. In general, total C pools were recorded statistically higher at upper elevation than middle and lower elevations. In the soil layer (0–30 cm, AS system exhibited, statistically the highest total C pool (46.53 Mg ha^-1) at upper elevation followed by AHS system (27.71 Mg ha^-1), however, statistically alike at lower elevation.

At upper elevation, plant soil carbon ratio was found statistically higher than middle and lower elevations, irrespective of agroforestry systems, whereas in AH system plant soil carbon ratio was statistically higher than AHS and AS systems across the elevations (Figure 2). Plant soil carbon pool ratio was also recorded maximum (56.44) in AH system followed by (21.62) in AS system at upper elevation.

C mitigation differs significantly (P ≤ 0.05) with changing elevations. It was estimated that the total agroforestry land use area contributed mostly biomass C mitigation (5894.13Mg) at middle elevation followed by (4574.08 Mg) at lower elevation (Table 5).

It shows that the C mitigation reduces approximately at the rate of 38% at upper elevation from lower elevation. C mitigation capacity followed the order Middle >lower > upper elevations. The total C mitigated by agroforestry systems was 11714.59 Mg in the district (Table 5). Moreover, rate of C mitigation was more at mid elevation with AHS system. Total C credits of agroforestry of Tehri district were estimated at 42992.53 in which highest number (21631.45) was from the middle elevation and lowest number (4574.21) was from the upper elevation of Tehri district. Whereas, the C credits per ha produced greatest number (7.52 ha^-1) at lower elevation, while upper elevation produced the lowest (5.83 ha^-1) C credit. Total calculated values of carbon credit were 128977.59 € (Table 5).

6. Discussion:

Dadhwal et al. (1989) [20] and Toky et al. (1989) [21] have also observed similar agroforestry systems across the elevations in North Western Himalayan region.Value of tree density was higher than the value reported by Goswami et al. (2014) [22] at mid-hill region of the Himachal Pradesh of India. . In the present study, Grewia oppositifolia occupied in highest density across agroforestry systems of Tehri district as compared to other forest species. Grewia oppositifolia occupied 0.64% area followed by 0.40% area by Celtis australis through Remote Sensing in Tehri district [23]. Grewia oppositifolia is a multipurpose tree which is most adopted by local farmers [20]. Total biomass and carbon stock in AHS was statistically alike but differed significantly from AS and AH systems. The higher biomass and carbon stock from the fruit and tree based system can be attributed to the presence of vegetable crops and trees as the dominant component in the system along with fruit trees. Biomass carbon has been found maximum at lower elevation because of abundance of tree species such as, Grewia oppositifolia, Celtis australis, Ficus roxbughii, Morus alba, Citrus spp, Malus domestica and Psidium guajava which were planted at high density. Agrihortisilviculture land management systems have good dominance of species with diverse growth habits, better root systems and good mineral requirements, which enable them to optimize available space & resources and lesser intensity of weeds as compared to other systems [21]. It was also indicated that total tree biomass was decreased with increasing elevations across systems. This variation can mainly be due to difference in the nature of the agro-climatic region. The comparison of three agroforestry land use systems showed the maximum CO₂ mitigation potential in AHS system followed by AS system. Higher CO₂ mitigation in horticulture and tree based system can be attributed to the maximum removal of harvesting biomass of fruits, fodder, fuel wood and vegetables. CO₂ mitigation depends on total carbon storage level which is positively correlated with elevations. However, higher CO₂ mitigation was found in lower elevation due to the adequate management of tree component. Results suggested that soil C pool is exploited in agrisilviculture systems due to regular tilling of soil for crop production and also attributed to the uptake of nutrients by annual crops [24]. Higher C pool were found in under fruit tree-based system (AH and AHS) which may be due to regular addition of litter biomass in the soils [25]. Soil carbon stock exceeds by a factor of 5 from Plant carbon stock [26]. As per LISS IV satellite data, area under agroforestry estimated as 7029.06 ha of total geographical area of Tehri district. Highest area under agroforestry was found in 1200-2000 m elevation i.e. 3707.36 ha followed by 288- 1200 m elevation i.e. 2231.26 ha [23]. Considering agroforestry systems, C mitigation differs significantly (P ≤ 0.01) with respect to systems which was estimated maximum (7.98 Mg ha^-1) in AHS system followed by (5.42 Mg ha^-1) in AS system it is nearly 30% less [27]. Mid elevation/subtropical zone consists maximum number of trees biomass and carbon stock, this variation is mainly due to difference in the nature of agroclimatic region. C mitigation depends on biomass and carbon stock level which increases with elevations. Age, structure and management of the system are an important factor for C variability in plant biomass [28]. In mountain agroforestry, farmers collect the fodder and fuelwood for livelihood by lopping the trees. Requirement of timber has been fulfilled by sometimes harvesting after rotation period. Commercial felling is totally banned.

7. Conclusion

The traditional agroforestry system in Himalayan region is an alternative choice towards carbon storage for atmospheric CO₂ sequestration and carbon credit. Middle elevation/sub-temperate zone with AHS system has the capacity for maximum CO₂ mitigation and carbon credit. However, lower elevation contained maximum number of carbon credit per ha^-1. Plant: Soil carbon pool ratio was observed highest at upper elevation in AH system. Traditional agroforestry system should be promoted for environment and economic benefit as a carbon credit for improving the livelihood of rural people in Tehri district of Uttrakhand due to ban of green felling in Himalayan region.