2. Biomass Production
The highest numbers of dominant AFS were reported in southern India and the northeastern and eastern Indian regions. These regions of India receive very high rainfall and hence agrobiodiversity is high, which creates opportunities for maintaining varied plant diversity in AFS. The least number of AFS was reported in the Indo-Gangetic region. This region is the food bowl of India and is highly fertile and highly populated. Farmers prefer cash crops in this region. The main system used in the region is the short rotation
Populus deltoides and Eucalyptus spp. agrisilviculture system.
Considerable regional variability for biomass production was recorded in this entry (
Table 1). Higher total biomass (>200 Mg ha
−1) was observed in the humid tropics of India, which are prevalent in southern India and northeastern India. Coffee plantations had the highest mean biomass (279.2 Mg ha
−1), followed by block plantations/woodlots (239.8 Mg ha
−1) and plantation crop-based AF (232.38 Mg ha
−1) in southern India, or followed by block plantations/woodlots (220.2 Mg ha
−1) in the northeastern part of India. The effectiveness of agroforestry systems in biomass production and carbon storage depends on environmental and socio-economic factors, management regimes, tree growth characteristics and other factors
[26]. In a humid tropic climate, the rainfall is abundant, thus water stress does not occur. In this climatic condition, the temperature generally remains between 20–30 °C, which is conducive to plant growth. However, in other regions, such as the northern Himalayas, the temperature descends to subfreezing, while, in western India, the temperature rises above 40 °C during summer, and these conditions hamper plant growth. The higher biomass in the coffee agroforests of southern peninsular India could be a reflection of management practices. Coffee farmers in this region, through intermittent crown pruning, retain large sized trees to provide shade to under-story vegetation
[27]. Irrespective of the region, the mean AGB was lowest in boundary plantations followed by silvipasture systems (
Figure 1A), and highest in block plantation/woodlots. This is because of the intrinsic nature of AFS, whereby the number of trees per hectare varies. Boundary plantations and silvipastures contain less trees, while block plantations have densely planted trees. The root proportion (read BGB) was higher in homegardens and least in boundary plantations (
Figure 1B). Homegardens have different species in different strata (vertical stratification above ground); the roots of these species draw nutrients from different root zones and, hence, occupy a larger surface of the soil profile, resulting in higher root biomass.
Table 1. Variation in biomass components among different agroforestry systems across agro-climatic zones of India.
| Agroclimatic Region/States |
AFSs (N @) |
AGB (Mg ha−1) |
BGB (Mg ha−1) |
TB (AGB + BGB + Crop Biomass) (Mg ha−1) |
Range (Mean) |
SD |
) (
Table 2). In addition, frequent pruning of horticulture crops to enhance fruit production could lead to lower biomass carbon in these systems. Biomass carbon in agrisilviculture systems (mean = 7.95 Mg ha
−1) in Indo-Gangetic region (IGR) was also relatively lower. This is because short rotation species are maintained in the region with a rotation age of 5–7 years. The SOC was also less in IGR (mean = 15.25 Mg ha
−1) because intensive agriculture is practiced in the region with a cropping intensity of 2.5, with paddy as the main crop; the practice of paddy does not allow buildup of SOC, as, during soil puddling, soil aggregates are broken, leading to loss of SOC.
Table 2. Variation in carbon storage between AFS prevalent in different regions of the Indian subcontinent.
| Agroclimatic Region/States |
AFSs (N @) |
TBC (Tree + Crop Biomass Carbon) (Mg ha−1) |
SOC (Mg ha−1) |
| Range |
| (Mean) |
SD * |
Range (Mean) |
SD |
Range (Mean) |
SD |
Range (Mean) |
SD * |
| Northern Himalayas (Himachal Pradesh, Jammu and Kashmir and Uttrakhand) |
Agrisilvicuture (31) |
6.7–159.41 (54.93) |
42.21 |
1.58–71.55 (14.87) |
14.60 |
15.94–202.59 (64.67) |
43.01 |
| Northern Himalayas (Himachal Pradesh, Jammu and Kashmir and Uttrakhand) |
Agrisilviculture (31) |
2.16–116.29 (32.61) |
34.02 |
22.28–142.9 (58.07) |
33.60 |
| Agri-horticulture (13) |
15.79–137.56 (40.00) |
32.90 |
2.40–34.39 (13.23) |
11.20 |
| Agrihorticulture (13) |
8.05–81.68 | 18.19–171.95 |
| (57.56) |
50.81 |
| (29.61) |
19.77 |
43.67–151.7 (64.34) |
33.33 |
Silvipasture (4) |
34.49–53.20 (43.85) |
13.23 |
9.01–34.42 (19.47) |
10.85 |
43.51–136.42 |
| Silvipasture (4) |
| (87.52) |
41.08 |
| 21.75–68.4 | (44.59) |
17.6 |
16.2–109.7 (47.63) |
34.69 |
Indo-Gangetic region (Punjab, Haryana, Uttar Pradesh, Bihar) |
Agrisilviculture (14) |
17.16–62.8 (33.82) |
20.25 |
3.62–3.84 (3.76) |
0.10 |
| Indo-Gangetic region (Punjab, Haryana, Uttar Pradesh, Bihar) |
Agrisilviculture (14) |
2.24–19.9 | 4.96–137.3 |
| (23.85) |
30.64 |
| (7.95) |
4.96 |
4.25–48.98 | (15.25) |
12.52 |
Silvipasture (17) |
13.57–60.20 (38.41) |
13.52 |
1.17–17.00 (9.32) |
4.08 |
| Eastern and northeastern India (West Bengal, Odisha, Assam, Sikkam, Meghalaya, Nagaland, Manipur, Mizorum) | 14.74–77.20 |
| (50.72) |
16.67 |
| Home gardens (11) |
30.76–140.0 | (55.18) |
27.74 |
42.8–119.5 (52.15) |
22.27 |
Eastern and northeastern India (West Bengal, Odisha, Assam, Sikkam, Meghalaya, Manipur) |
Agri-horticulture (14) |
0.81–22.50 (5.57) |
7.28 |
1.52–6.28 (3.63) |
1.81 |
2.33–11.79
|
| Plantation crop-based Agroforestry (18) | (6.41) |
0.08–76.16 (26.42) |
26.64 | 3.57 |
| 30.56–176.74 |
| (96.53) |
71.57 |
Home gardens (11) |
4.72–199.00 (52.54) |
75.53 |
30.60–39.90 (34.69) |
4.21 |
92.58–150.75 (121.67) |
41.13 |
| Boundary plantation (24) |
1.24–59.93 (9.74) |
12.25 |
48.18–55.73 (51.95) |
3.28 |
Plantation-based agroforestry (18) |
0.10–141.10 (40.46) |
46.96 |
0.12–38.47 (13.36) |
13.53 |
0.86–245.64 (87.16) |
82.55 |
| Block plantation (13) |
11.41–362.27 (98.99) |
Boundary plantation (24) |
2.15–104.72 (16.96) |
21.39 |
0.32–15.14 (2.52) |
3.11 |
2.47–119.86 (19.48) |
24.50 |
| Block plantation (13) |
23.24–642.32 (186.20) |
158.31 |
2.33–128.46 (25.33) |
35.28 |
25.56–770.78 (220.20) |
205.92 |
| Western and central India (Rajasthan, Gujarat, Maharashtra and Madhya Pradesh) |
Agrisilviculture (7) |
5.63–19.24 (11.91) |
6.28 |
- |
- |
3.20–89.8 (33.63) |
38.38 |
| 97.34 |
Agrihorticulture (19) |
0.6–200.5 (81.05) |
68.3 |
0.5–75.2 (24.60) |
21.77 |
1.2–252.6 (78.95) |
88.39 |
| Block plantation (71) |
1.11–261.4 (79.24) |
77.19 |
0.96–82.5 (21.84) |
23.07 |
0.1–713.3 (120.09) |
168.11 |
| Southern India (Karnataka, Andhra Pradesh, Tamil Nadu, Kerala) |
Agrisilviculture (6) |
14.42–59.75 (37.37) |
19.91 |
2.85–20.25 (11.87) |
5.92 |
3.90–76.87 (35.96) |
27.89 |
| Plantation crop-based agroforestry (10) |
59.96–302.43 (174.96) |
90.15 |
22.14–63.29 (41.29) |
17.34 |
104.14–365.72 (232.38) |
105.85 |
| Block plantation (5) |
120.9–233.4 (170.9) |
41.4 |
37.24–104.5 (69.49) |
25.8 |
158.1–332.77 (239.8) |
65.25 |
| Coffee plantation (11) |
187.7–252.5 (221.5) |
26.84 |
50.68–68.18 (59.38) |
6.57 |
238.3–320.7 (279.2) |
30.91 |
Irrespective of the region, the highest total biomass was recorded in plantation crop-based AFS, followed by boundary plantations and homegardens (
Figure 12C). This could be attributed to higher tree density and difference in management regimes; for example, in coffee plantations in the western Ghats region, farmers retain native trees in large numbers to provide shade for under-story coffee, and
Grevillea robusta trees serve as standards for pepper vines. In the homegardens of northeastern and western Ghats, smallholder farmers maintain diverse trees to meet an array of demands. A study in the western Ghats region of peninsular India found that coffee agroforests resembled natural forest and mixed species plantations in terms of tree diversity and biomass production, suggesting that traditional coffee farms can help to protect tree species, sustain smallholder production and offer opportunities for conservation of biodiversity and climate change mitigation
[27]. Similarly, another study revealed that coffee agroforests and mixed species plantations were more effective compared to monocultures for conserving biodiversity and storing more biomass
[28].
3. Carbon Capture
Total mean biomass carbon (TMBC) was in the range of 7.95–81.2 Mg C ha
−1, while average SOC varied in the range of 13.3–69.39 Mg C ha
−1 across different regions. The highest TMBC (81.2 Mg C ha
−1) and SOC (69.39 Mg C ha
−1) were recorded from the southern peninsular region followed by the eastern and northeastern Indian region, with a TMBC value of 47.58 Mg C ha
−1 and SOC of 66.88 Mg C ha
−1, indicating the higher carbon sequestration potential of AFS from these regions in India. AF systems, such as coffee plantations, plantation crop-based AFS in the southern peninsular region, homegardens in northeastern India and silivipastoral systems in the northern Himalayas were found to have greater potential to sequester carbon in both biomass and soil. When the same AFS were compared between different agroclimatic regions, researchers found that the agrisilviculture and agrihorticulture systems of the northern Himalayas had greater carbon sequestration potential compared to the Indo-Gangetic and western and central Indian regions. These differences in biomass carbon and SOC across the regions and AFS were observed as the carbon storage capacity of agroforestry systems is dependent upon many biophysical and socio-economic characteristic of the system
[29]. Further, the carbon storage potential of AF systems are strongly governed by the structure and functioning of different components within the system. The lowest biomass carbon was observed in agrihorticulture systems in western India (mean = 1.84 Mg ha
−1), probably due to the extremely dry and hot climatic conditions. This was also reflected in low SOC, ranging from 12.26 to 14.55 Mg ha
−1
| - |
| - |
| Western and central India (Rajasthan, Gujarat, Maharashtra and Madhya Pradesh) |
| Agrisilviculture (7) |
| 1.5–42.9 |
| (10.24) |
11.54 |
4.28–24.13 (12.26) |
7.08 |
| Agrihorticulture (19) |
0.82–5 (1.84) |
1.77 |
- |
|
| Block plantation (71) |
0.05–353.2 (38.12) |
69.07 |
0.1–63.80 (14.55) |
19.57 |
| Southern India (Karnataka, Andhra Pradesh, Tamil Nadu, Kerala) |
Agrisilviculture (6) |
1.57–39.31 (11.93) |
10.50 |
1.23–77.56 (17.08) |
26.33 |
| Plantation crop-based agroforestry (10) |
48.95–169.24 (107.95) |
49.51 |
61.26–71.39 (65.82) |
3.65 |
| Block plantation (5) |
14.75–152.16 (73.56) |
41.13 |
- |
- |
| Coffee plantation (6) |
112.04–150.74 (131.27) |
14.53 |
78.70–170.43 (125.29) |
34.66 |
The south Indian AFS had the highest mean SOC stock in the range of 17.08–125.29 Mg ha
−1, followed by eastern Indian AFS, with a mean SOC stock of 51.95–96.53 Mg ha
−1. AFS in southern peninsular India showed considerable variation in SOC stock compared to AFS in eastern and northeastern India. The prominent agroforestry systems in the south Indian region were found to be plantation-based systems, in the form of either commercial coffee or forest tree species plantations, which are crucial from the perspective of long-term carbon storage. SOC in AFS other than vegetation, particularly woody species composition, is also influenced by litter quality, age and locality (e.g., climate, soil conditions, topography), geographic position, land use and management systems. Older and relatively undisturbed land use systems generally accumulate higher organic carbon content
[30][31][32]. Relatively, the eastern and northeastern Indian region receives higher rainfall compared to other regions of India with an average annual rainfall of more than 2000 mm; thus, soils are generally acidic and have higher SOC
[31][33].
Mean TBC among different AFS varied between 25.24 to 52.98 Mg ha−1. The highest mean TBC was in homegardens and the lowest in boundary plantations (Figure 2A). From a comparative point of view, SOC assessment in AFS irrespective of region, indicated that block plantations/woodlots had least SOC (15.54 Mg ha
−1), closely followed by agrisilviculture (26.59 Mg ha
−1) (
Figure 2B). Soil management and soil amendments in woodlots/block plantations are seldom performed in India. These plantations are maintained for a short duration for commercial purposes and, hence, resilience for SOC buildup does not occur. Soil carbon increases during the tree-growing phase; however, crop cultivation after tree harvesting or burning soil carbon stocks is likely to decrease it again
[34]. This interpretation is consistent with the observed reduced SOC in agrisilviculture. The IPCC recommends a minimum 20-year period for soil carbon sequestration accounting in national greenhouse gas inventories
[35]. The higher SOC in plantation-based AFS (81.17 Mg ha
−1) is due to a resilience time of more than 40 years, as coffee, tea, or cocoa plantations have durations of more than 50 years.
Figure 2. TBC (A) and SOC (B) in different AFS in India. (A) Total biomass carbon (Mg ha−1); (B) Soil Organic Carbon (Mg ha−1).
The mean biomass, biomass carbon and SOC in India reported in the literature are less compared to that of other countries. For example, ref.
[15] reported agrisilviculture systems storing 12–228 Mg C ha
−1 in the humid tropics and 68–81 Mg C ha
−1 in the dry lowlands of southeast Asia, whereas in their study, researchers found a mean of 55.69 Mg ha
−1 (both TBC + SOC) in agrisilviculture systems. AFS are complex and heterogeneous and, the more the heterogeneity, the more efficiently the carbon is sequestered compared to simpler systems
[31][33]. However, the efficiency of AFS as carbon sinks is governed by their size, natural site qualities, choice of species and management practices followed, i.e., carbon sequestered by an AFS depends on its structure and composition modified by environmental and socio-economic factors
[36][37]. Moreover, inter- and intra-specific variation in tree diameter, stand age, stand structure and diversity of the system also affect variation in biomass and its carbon
[38][39].
Homegardens and block plantation agroforestry systems were reported to have higher carbon contents than other land uses in an agricultural landscape with higher net gains in carbon stocks
[40][41][42][43][44]. Developing countries are now adopting agroforestry systems to achieve climate change mitigation as REDD+ strategic options
[45][46][47] due to their financial feasibility, avoidance of deforestation, enhanced soil productivity and permanency of carbon sequestration in agricultural landscapes, along with sustaining the growers
[48][49][50][51].
Uncertainties in estimates of carbon stocks in different AFS would be expected as each system varies according to site factors, tree species, the density and productivity of shade trees, as well as their longevity and subsequent use in processing systems, the production of litter, the rate of decomposition and its incorporation in the soil matrix as soil carbon, nutrient cycling and soil respiration. In addition, the management regime of each system is also critical as it largely determines the carbon additions and removal from the system. Perhaps more important over the longer term is the resilience of the system in terms of its ability to withstand climatic or other shocks, and, thereby, to retain carbon despite such perturbations. The resilience of agroforestry systems is a function of the diversity and complexity of the agroforest management unit, and the nature of the landscape matrix within which agroforestry systems lie. Indeed, a functional landscape system, as viewed from the perspective of resilience and carbon storage, must be considered as an integrated landscape that includes flows of materials and services across system boundaries, from agroforests to natural forest patches, and more intensive land uses, including plantations and annual crops. Agroforestry plantations require a clear understanding of their tree life history strategies, i.e., the driving mechanisms and magnitudes of biomass allocation and partitioning
[52][53]. Unfortunately, this driving mechanism and magnitude remain uncertain
[54]. There are also significant uncertainties concerning the quantification of carbon fluxes in and out of systems due to an absence of information on land use and land cover change
[55][56].