Diurnal and seasonal carbon sequestration potential ...

Atmospheric Environment 89 (2014) 827e834

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Diurnal and seasonal carbon sequestration potential of seven broadleaved species in a mixed deciduous forest in India Soumyajit Biswas a, b, Sanjay Bala a, b, Asis Mazumdar a, b, * a Regional Centre, National Afforestation & Eco-Development Board, Ministry of Environment and Forests, Govt. of India, Jadavpur University, Kolkata 700032, West Bengal, India b School of Water Resources Engineering, Jadavpur University, Kolkata 700032, West Bengal, India

h i g h l i g h t s Spontaneous CO2 exchange rate was measured with LI-6400 for seven tree species. Carbon sequestration rate was simulated to canopy level with analytical model. Comparison of gas exchange attributes of broadleaved species. Annual carbon sequestration rate of man-made mixed forest in natural condition.

a b s t r a c t Keywords: Broadleaved Canopy Carbon sequestration Leaf area index Light response curve Net assimilation rate

The objective of the study was to measure annual carbon sequestration rate of mixed deciduous forest by measuring that of seven young broadleaved tree species (6 years age) as well as selection of better carbon sequestered plant species for future plantation. The diurnal net assimilation rate of Carbon dioxide (CO2) at leaf level was measured with LI-6400 Portable Photosynthesis System at daytime on seasonal basis in a man-made forest at Budge Budge (N 22 280 E 88 080 ) of South 24 Parganas, West Bengal, INDIA. Net assimilation rate of carbon at canopy level was calculated by measuring Leaf Area Index with LAI-2200 and using analytical model with non-rectangular hyperbolic light response curve. The average net assimilation rate of CO2 at leaf level was found maximum in Albizzia lebbek (8.13 mmol m2 s1) and that of canopy level in Eucalyptus spp. (4.851 g h1). The minimum was found for Swietenia mahagoni (1.058 g h1). The annual carbon sequestration rate of the mixed forest in natural condition was estimated 6.01 t ha1 year1 by consolidating the potential of all seven species. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction There is general consensus that the increasing concentration of greenhouse gases (e.g. Carbon dioxide, Methane, Nitrous Oxide, Sulfur Hexafluoride, Per-fluorocarbons, Hydro-fluorocarbons) have led to changes in the earth’s climate and a warming of the earth’s surface. Furthermore, there is agreement that human activities such as fossil fuel combustion, land-use change and agricultural practices have contributed substantially to the rise in atmospheric greenhouse gas concentrations (IPCC, 1997). Carbon

* Corresponding author. Regional Centre, National Afforestation & EcoDevelopment Board, Ministry of Environment and Forests, Govt. of India, Jadavpur University, Kolkata 700032, West Bengal, India. E-mail addresses: [email protected] (S. Biswas), sanjayiifm@gmail. com (S. Bala), [email protected] (A. Mazumdar). http://dx.doi.org/10.1016/j.atmosenv.2014.03.015 1352-2310/Ó 2014 Elsevier Ltd. All rights reserved.

dioxide (CO2) is one of the more abundant greenhouse gases and a primary agent of global warming. It constitutes 72% of the total anthropogenic greenhouse gases, causing between 9 to 26% of the greenhouse effect (Kiehl and Trenberth, 1997). According to National Oceanic & Atmospheric Administration-Earth System Research Laboratory (NOAA-ESRL) of United States, the amount of Global CO2 concentration in the year 2011 is 391.63 ppmv, and last 10 years average annual increase is 2.01 ppmv per year (http:// www.esrl.noaa.gov). Dramatic rise of CO2 concentration is attributed largely to human activities. Over the last 20 years, majority of emission is attributed to burning of fossil fuel, while 10e30% is attributed to landuse change and deforestation (IPCC, 2001). Increase in CO2 concentration, along with other greenhouse gases (GHGs), raised concerns over global warming and climate changes. Forestry and afforestation in particular, is regarded as an important contributor to the offset of greenhouse

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gas emissions (Miehle et al., 2006). It stores about 80% of all above-ground and 40% of all below-ground terrestrial organic carbon (IPCC, 2001). During productive season, CO2 from the atmosphere is taken up by vegetation (Losi et al., 2003; Phat et al., 2004) and stored as plant biomass. In 1997, during the Third Conference of Parties (COP-3) of the UNFCCC, the Kyoto Protocol was drafted which is the first international agreement that places legally binding limits on GHG emissions from developed countries. The Kyoto Protocol proposed that C reduction could take place by decreasing fossil fuel emissions, or by accumulating C in vegetation and in the soil of terrestrial ecosystems. Tropical forests have the largest potential to mitigate climate change amongst the world’s forests through conservation of existing C pools (e.g. reduced impact logging), expansion of C sinks (e.g. reforestation, agroforestry), and substitution of wood products for fossil fuels (Nath and Das, 2012). The forest and landuse sector has received significant attention globally in addressing the climate change problem. However, as evidenced by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2007), mitigation potential assessment in the landuse change and forest sector has been limited by availability of information at the globallevel, and by the lack of disaggregation of mitigation potential at the national and sub-national level. This is particularly true for India since very few forest mitigation assessment studies have been published (Murthy et al., 2012). Projects that increase the area of plantations have been suggested for inclusion under the Clean Development Mechanism (CDM) as defined in Article 12 of the Kyoto Protocol. However, significant uncertainties in the reliability of carbon pool and flux measurements make it difficult to determine the (net) carbon benefits of afforestation or forest management practices. As a result, further investment in and development of, the plantation industry is threatened (Van Vliet et al., 2003). The net carbon gain of a terrestrial ecosystem is composed from complex consequences of leaf area, CO2 exchange capacity, activity of photosynthetic (leaves) and nonphotosynthetic (stems and roots) organs, canopy architecture, stand biomass of plant species involved, and meteorological conditions including light incidence, air temperature, air humidity, wind speed and air CO2 concentration (Ehleringer and Field, 1993; Baldocchi and Meyers, 1998; Baldocchi and Wilson, 2001; Baldocchi et al., 2002). As well as these instantaneous consequences of plants and their environments, spatial and temporal variations of both biotic and abiotic factors throughout the growing season control the ecosystem behavior. Due to these multiple relationships of factors governing the ecosystem function, the ecophysiological mechanisms underlying the functional role of the vegetation are always fundamental knowledge since they provide mechanistic explanations and/or parameters to the meteorological observation, satellite remote sensing and modeling prediction of the ecosystem carbon cycling which enable us to evaluate larger scale behavior of the ecosystems (Ehleringer and Field, 1993; Baldocchi and Meyers, 1998; Wilson et al., 2001; Muraoka and Koizumi, 2005). Most of the earlier carbon sequestration researches were based on the concept of static biomass carbon with a longer time scale where diurnal carbon sequestration rate (minute scale) has not been considered. Earlier works have only considered a concept of linear (proportionate) carbon sequestration as well as biomass, which is practically not feasible in the natural system. The objective of the study was to measure diurnal and annual carbon sequestration rate of young (6 years) mixed deciduous forests composed of Acacia auriculiformis, Albizzia lebbek, Dalbergia sissoo, Eucalyptus spp., Swietenia mahagoni, Tectona grandis, Terminalia arjuna as well as selection of better carbon sequestered plant species for future plantation.

2. Materials and methods 2.1. Study area The study was conducted in a man-made forest of Budge Budge (N 22 280 E 88 080 ) in South 24 Parganas district of West Bengal, INDIA. The mean annual air temperature (Kolkata) for past two decades was 26.66 C, with highest in May (30.5 C) and lowest in January (19 C). Mean annual precipitation during the same period was 170.3 cm (http://www.myweather2.com /City-Town/India/ Kolkata/climate-profile.aspx). The study area was mainly composed of seven broadleaved deciduous species of 6 years age. Soil at the study area was silt/sandy loam in texture with a pH and bulk density of 8.25 and 1.43 g/cm3 respectively. The soil organic carbon was found 7.6 g/kg through testing of soil sample. 2.2. Measurement of net assimilation rate of CO2 The net assimilation rate of CO2 (A) was measured with undamaged matured leaves (n ¼ 30e35 per species) under natural condition i.e., under natural Photosynthetic Active Radiation (PAR), air temperature, humidity and CO2 concentration. Leaves were clamped by the cuvette of LI-6400 Portable Photosynthesis System (LICOR INC., USA) with the position and direction of the blade fixed as they had been in the crown and exposed to solar radiation incident on the leaf through a transparent window at the top of the chamber (Biswas et al., 2013). A was measured at 1e2 h interval from morning to evening with the leaves of selected seven plant species in monsoon (September, 2010), winter (December, 2011) and summer (June, 2011) to get the diurnal variation of net assimilation rate of CO2 with an air flow rate of 500 mmol s1. Ambient PAR was recorded by the LI-6400 simultaneously at the time of measurement. Leaf temperatures were 36.13 C in September, 25.97 C in December, and 37.45 C in June. The average ambient CO2 concentration was 371 ppmv in monsoon, 399 ppmv in winter and 382 ppmv in summer as measured with LI6400. The seasonal variation of the ambient CO2 concentration may be due to the presence of a major CO2 source (Chimney of a thermal power plant) in the northern side of the sampling area which influences concentration of CO2 in the ambient air due to wind flow direction. The direction of wind flow normally remains North to South in the winter, and South to North in summer and monsoon. The vapor pressure deficit (VPD, kPa) inside the cuvette was 1.854, 2.552 and 5.235 in monsoon, winter and summer respectively. Dark respiration (RD) was measured with the sampled leaves (n ¼ 20e25 per species) in the absence of sunlight to calculate the respiration at night. Net assimilation rate of CO2 at different values of PAR (mmol m2 s1) was also measured by using artificial light source (LED-6400-02B) of LI-6400 at leaves of selected plant species to determine the net assimilation rate of CO2 at light saturation point by drawing the light response curve (net assimilation rate of CO2 vs. PAR) of the species. The gas exchange rate has been measured with varying PAR (0 to 2000 mmol m2 s1) at 21 irradiance levels at 100 unit intervals. 2.3. Measurement of leaf area Leaf area index (LAI) is the total one-sided area of leaf tissue per unit ground surface area (Watson, 1947). According to this definition, LAI is a dimensionless quantity characterizing the canopy of an ecosystem. It is a key parameter in eco-physiology, especially for scaling up the gas exchange from leaf to canopy level. It characterizes the canopy-atmosphere interface, where most of the energy fluxes exchange (Breada Nathalie, 2003). LAI has been measured with LAI-2200 (LICOR INC., USA) plant canopy analyzer to estimate the total leaf area of the individual plant species by multiplying


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with surface area of the individual trees to calculate the net assimilation rate of CO2 at canopy level.

can be adequately described by a simple exponential relationship with accumulated leaf area. This is analogous to Beer’s law for attenuation along a single beam i.e.

2.4. Calculation of net assimilation rate of CO2 at canopy level

IðzÞ ¼ I0 ekLðzÞ

Scaling from the leaf to the canopy level can be achieved by making assumption that allow the general expression for canopy photosynthesis to be integrated analytically, leading to explicit formulae for whole canopy photosynthesis, either at a given time (e.g. Thornley, 2002), or for a day (Sands, 1995). The basic mathematical problem is to perform the integrations in the expression for daily whole-canopy assimilation, AC (mmol m2 day1) i.e.

where I0 and I(z) are respectively the irradiances in horizontal surfaces above the canopy and at some level z within the canopy, L(z) is accumulated leaf area index of the canopy at that level, and k is called the extinction coefficient (Landsberg and Sands, 2011). Therefore, it is assumed that, at any level in the canopy irradiance Il is determined by Beer’s law and hence driving photosynthesis quantum is

Zh ZL AC ¼

I1 ¼

AðAmax ; Il dLdt 0

0

I ¼

where L is the canopy leaf area index, h (s day ) is the day length, A and Amax (mmol m2 s1) are the instantaneous and light saturated leaf level photosynthesis rates, and Il (mmol m2 s1), is the irradiance incident upon the leaf. The leaf level assimilation rate A is represented by a nonrectangular hyperbolic light response:

2aIl =Amax ffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 þ aIl =Amax þ ð1 þ aIl =Amax Þ2 4qaIl =Amax

2.5. Calculation of total CO2 assimilation in a year After getting the actual leaf level assimilation rate (A,

where, Amax (mmol m2 s1) is the average of maximum net assimilation rate of CO2 in a day, a (mol mol1) is the quantum efficiency, and q is the shape parameter. A has been denoted as a function of the average of maximum photosynthesis rate (Amax) in a day and irradiance Il incident upon the leaf which depends on accumulated leaf area (L). The use of equation above rather than a detailed biochemical model is modified by its simplicity, and is justified the fact that it accurately represents observed leaf level assimilation rates. Its three parameter can be determined as a function of leaf temperature and ambient CO2 concentration by gas exchange experiment (Landsberg and Sands, 2011). Despite canopy heterogeneity, and variations in sun angle and radiation characteristics, many empirical observations have shown that, when the profiles of radiation in a horizontal plane, and of leaf area density, are measured at different levels in a canopy, the transmittance of direct and diffuse radiation through the canopy

mmol m2 s1) in three different seasons (monsoon, winter, sum-

mer) total net assimilation of CO2 was calculated in the year from the mean daily sunshine hours (Solar Radiation Hand Book, 2008). The following equation is the general expression for the calculation:

ATot ¼

12 X

Ai Ti Di

i¼1

365 X

RDj

j¼1

where, ATot is the annual net leaf level assimilation rate of carbon, i represents months in a year, Ai represent actual net assimilation rate of CO2 in a day of three different seasons, Ti represent mean daily sunshine hours in a month, Di represent no. of days in a month; and RD is dark respiration in the night period in a day, j represents number of days in a year. It has been assumed that the non-sunshine hours in daytime photosynthesis neutralize the

Irradiance at leaf level

1200

k I ekL 1m 0

where, m is the average leaf transmittance. The irradiances I0 in horizontal surfaces above the canopy, had been calculated from the mean monthly solar radiant exposure (MJ m2 day1) of Kolkata (nearest place of the study area) as given in the Solar Radiation Hand Book, 2008. The shape parameter (q) which is an empirical factor has been determined by curve fitting (Lieth and Reynolds, 1987). The value of q has derived by calculating the slope of the tangent at light saturation point of the light response curve.

1

AðAmax ; Il Þ ¼ Amax

k 1m

Irradiance above canopy level

Irradiance (μ mole m-2 sec-1)

1000

800

600

400

200

0 J

F

M

A

M

J

J

A

S

Calendar month Fig. 1. Average value of solar irradiances in each month of a year.

O

N

D

830


Fig. 2. Diurnal changes of net assimilation rate of CO2 among the different species (a) Acacia auriculiformis, (b) Albizzia lebbek, (c) Dalbergia sissoo, (d) Eucalyptus spp., (e) Swietenia mahagoni, (f) Tectona grandis and (g) Terminalia arjuna (The vertical bars are showing the Standard Deviation).


831

Fig. 2. (continued).

Table 1 Diurnal course of net assimilation rate of CO2 (mmol m2 s1) in summer, monsoon and winter seasons. Sl no. Species

Season Summer

1. 2. 3. 4. 5. 6. 7.

respiration rate during that time as there is little bit of photosynthesis in daytime even the absence of direct sunlight.

Mean Monsoon

3. Results and discussions

Winter

Acacia auriculiformis 10.48 2.277 6.18 1.230 1.67 0.664 Albizzia lebbek 9.43 2.966 11.61 1.544 3.34 0.631 Dalbergia sishoo 8.06 1.068 6.76 1.281 6.34 1.630 Eucalyptus spp. 9.20 2.132 5.90 2.028 6.98 1.488 Swietenia mahagoni 6.03 1.118 4.14 1.183 1.76 0.686 Tectona grandis 7.01 2.059 4.91 1.130 1.37 0.662 Terminalia arjuna 5.43 1.065 5.73 1.250 5.20 1.892

6.11 8.13 7.05 7.36 3.98 4.43 5.45

The average solar irradiances variation was measured from sunrise to sunset in horizontal surfaces above the canopy and as well as at leaf level within the canopy during the measurement of net assimilation rate of CO2 of the sampled species (Fig. 1). Significant variation of irradiance Il was observed in all three seasons e winter, summer and monsoon. The diurnal changes of net assimilation rate of CO2 (Ad) were monitored from 07.00 to 17.00 h in three seasons at 1e2 h interval. Maximum rate was observed in morning

Table 2 Average values (SD) of the parameters of Photosynthesis-PAR. Sl. No.

Species

Season

q (shape parameter)

1.

Acacia auriculiformis

2.

Albizzia lebbek

3.

Dalbergia sissoo

4.

Eucalyptus spp.

5.

Swietenia mahagoni

6.

Tectona grandis

7.

Terminalia arjuna

Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer

0.73 0.85 0.69 0.38 0.62 0.42 0.55 0.68 0.44 0.62 0.69 0.54 0.41 0.5 0.32 0.82 0.89 0.77 0.78 0.82 0.70

0.967 0.044 0.120 0.142 0.099 0.069 0.098 0.06 0.026 0.131 0.097 0.087 0.08 0.036 0.028 0.11 0.041 0.088 0.125 0.025 0.083

a (mol mol1) 0.14 0.128 0.148 0.122 0.087 0.101 0.045 0.042 0.065 0.136 0.159 0.166 0.025 0.013 0.038 0.109 0.077 0.110 0.154 0.119 0.146

0.0089 0.0048 0.0057 0.0075 0.0023 0.0041 0.0051 0.0033 0.0022 0.0099 0.0018 0.0069 0.0069 0.0044 0.0018 0.0095 0.0025 0.0069 0.0122 0.0068 0.0098

ATOT (g m2 year1) 425.7007 233.1134 73.34918 342.0358 342.9239 138.703 269.4994 111.1807 219.7797 377.1712 220.4263 288.6118 185.8556 86.15414 53.82686 279.9217 175.0447 59.90108 232.9291 218.1345 217.5374

832


Respiration rate (μmol m-2 s-1)

3.5

Average respiraƟon rate

3 2.5 2 1.5 1 0.5 0 Acacia

Albizzia

Dalbergia

Eucalyptus

Swietenia

Tectona

Terminalia

Species Fig. 3. Species wise dark respiration rate (mmol m2 s1).

carbon sequestration rate from the ambient air is found for Eucalyptus tereticornis and Gmelina arborea in an agroforestry system is 20.4 mmol m2 s1 and 17.09 mmol m2 s1 respectively (Biswas et al., 2013). Lee et al. (2006) showed that Saturation PPFD of A. auriculiformis and Acacia mangium approached 15e 18 mmol m2 s1 CO2 under 800e1500 mmol m2 s1 PPFD. Marenco Ricardo et al. (2001) obtained maximum light saturated photosynthesis rate of Swietenia macrophylla was 10.20 mmol m2 s1 at 380 mmol mol1 CO2. The mean diurnal course of net photosynthetic rate for Terminalia arjuna was 8.65 mg CO2 dm2 s1 (Naidu and Swamy, 2000). The above findings are more or less similar to our estimate. The little difference may be due to different species, different age groups and different agro-climatic conditions. The convexity of Photosynthesis-PAR curves (q) was significantly greater in winter season than in summer and monsoon. The quantum efficiency (a) was significantly lower in winter than in summer and monsoon (Table 2). The average dark respiration rate (RD) is found maximum for Eucalyptus spp. (2.50 mmol m2 s1) and minimum for S. mahagoni (0.81 mmol m2 s1) (Fig. 3). Annual net leaf level assimilation rate of carbon (ATot g m2 year1) is maximum for Eucalyptus spp. and minimum for S. mahagoni. This could be observed from Fig. 4 that the net assimilation rate of carbon differed among the species and significantly lower in the winter season. The net assimilation rate of carbon of the species reached maximum in the summer season. This may be

hours and decreased towards the evening in all the tree species sampled. Different tree species reached maximum peak levels of net assimilation rate of CO2 at different hours starting from morning 8e12 h (except for A. auriculiformis) in growing season of summer and monsoon and 9e12 h in the winter season (Fig. 2). Among the seven tree species studied maximum average net assimilation rate of CO2 was found in A. lebbek and least in S. mahagoni for all the three seasons starting from morning to evening hours of a day (Table 1). The rate decreased gradually from morning to evening in all the three seasons. Ad differed among different species and was significantly lower in winter than that of during the growing seasons of monsoon and summer. This may occur due to increasing photosynthetic active radiation revealing their efficiency to grow and utilize maximal light at high light intensities (Naidu and Swamy, 2000). The decreased rate during low light period might be attributed to the combination of factors such as less numbers of sunshine hours, increased leaf resistance and increased leaf temperature besides photosynthetic active radiation (Beedle et al., 1985; Liang and Maruyama, 1994). The net assimilation rate of CO2 of the tree species was compared with the works of different scientists and researchers. Rawat and Singh (2000) measured the rate of photosynthesis for A. lebbek, D. sissoo and Eucalyptus camaldulensis at 600 mmol m2 s1 photosynthesis photon flux density (PPFD) at the age of eight months. The photosynthesis rate was 3.80, 8.70 and 3.72 mmol m2 s1 for A. lebbek, D. sissoo and E. camaldulensis respectively. The average

Net assimilation rate of carbon (gm m-2 y-1)

700

Summer

Monsoon

Winter

Total assimilation of carbon in year

600 500 400 300 200 100 0 Acacia

Albizzia

Dalbergia

Eucalyptus

Swietenia

Tectona

Species Fig. 4. Species wise net assimilation rate of carbon (g m2 year1).

Terminalia


833

12

Net assimilation rate of carbon (gm hr -1)

Summer

Monsoon

Winter

Average

10

8

6

4

2

0 Acacia

Albizzia

Dalbergia

Eucalyptus

Swietenia

Tectona

Terminalia

Species Fig. 5. Species wise net assimilation rate of carbon (g h1) at canopy level.

because of daily mean sunshine hours variation in different seasons which is maximum in the summer season. It is observed that ATot is maximum for A. lebbek (555.05 g m2 year1), followed by Eucalyptus spp. (413.97 g m2 year1), A. auriculiformis (409.07 g m2 year1), Dalbergia sishoo (344.93 g m2 year1), T. arjuna (268.93 g m2 year1), T. grandis (206.48 g m2 year1) and S. mahagoni (171.71 g m2 year1). Total net assimilation does not depend only a or spontaneous net assimilation rate. It also depends on other factors like dark respiration, effective leaf area, soil quality, availability of water, proximity of other trees. Based on the leaf area index (LAI) and surface area or canopy cover of the sampled species the average net assimilation rate of carbon (g h1) at canopy level has been calculated. The average net assimilation rate of carbon at canopy level (Fig. 5) is maximum for Eucalyptus spp. (4.851 g h1) and minimum for S. mahagoni (1.085 g h1). This may be due to variation of LAI, canopy cover, net assimilation rate of different species. In summer season, Eucalyptus spp. shows the maximum assimilation rate followed by T. grandis, A. auriculiformis, A. lebbek, T. arjuna, D. sissoo, S. mahagoni. In summer season the net assimilation rate of

Table 3 Leaf area index and total leaf area of different species. Sl. No.

Species

Season

LAI

Total leaf area (m2)

1.

Acacia auriculiformis

2.

Albizzia lebbek

3.

Dalbergia sissoo

4.

Eucalyptus spp.

5.

Swietenia mahagoni

6.

Tectona grandis

7.

Terminalia arjuna

Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer Monsoon Winter Summer

2.10 1.45 1.95 1.96 1.38 1.81 2.05 1.22 1.91 1.8 1.52 1.68 2.51 1.83 2.28 3.26 1.36 2.8 2.55 1.89 2.14

30.324 20.938 28.158 20.305 14.296 18.751 18.347 10.919 17.094 39.330 33.212 36.708 20.582 15.006 18.696 55.289 23.065 47.488 30.931 22.925 25.958

carbon is maximum than the other two seasons (Table 1) for all the species (except for A. lebbek). This may be due to increasing photosynthetic active radiation revealing their efficiency to grow and utilize maximal light at high light intensity in summer. The net assimilation rate of carbon for Eucalyptus spp. did not differ significantly in three different seasons. It may be because of the total number of leaves more or less similar in all the seasons comparison to other species. Another reason may be the average leaf level assimilation rate is also in the higher side for Eucalyptus spp. among the sampled species. LAI also does not show significant variation in all the seasons for Eucalyptus spp. A. lebbek exhibited maximum net assimilation rate of carbon in consistent to the highest LAI in the monsoon (Table 3) because its maximum leaf level assimilation rate in monsoon which is maximum in summer for other species. The annual carbon sequestration rate per hectare from ambient air has been estimated for 79 sampled trees within a 30 m 30 m quadrate in the study area. The total annual carbon sequestration rate as estimated for all the sampled species from our study was 6.01 t ha1 year1 (Table 4). Among the total sampled species annual carbon sequestration rate from ambient air the maximum yield has been shown by A. lebbek (1.79 t ha1 year1) and minimum by T. arjuna (0.12 t ha1 year1). Bala et al., 2012 estimated carbon sequestration potential by the Eucalyptus coppice forest was 13.07 t ha1 in 6 years, with an average annual increment of 2.18 t ha1 whereas our estimated value was 1.19 t ha1 year1 for Eucalyptus spp. Walsh et al., 2008 predicted carbon sequestration potential at age 10 year for a range of Eucalyptus species based on mean dominant height, mean top-basal area, and stem

Table 4 No. of trees in quadrate and annual carbon sequestration rate. Species

No. of trees in quadrate

Annual carbon sequestration rate (t ha1 year1)

Acacia auriculiformis Albizzia lebbek Dalbergia sissoo Eucalyptus spp. Swietenia mahagoni Tectona grandis Terminalia arjuna Total

10 19 20 9 8 9 2 77a

1.04 1.79 0.90 1.19 0.23 0.72 0.12 6.01

a The total no. of trees in the quadrate was actually 79 nos. among them two trees being other species, were excluded.

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volume. According to them total above-ground biomass ranged from 12.5 to 105.8 t ha1 at the age 10 year. Annual carbon sequestration rate for Shorea robusta, A. lebbek, T. grandis and Artocarpus integrifolia was 8.97 t ha1 year1, 11.97 t ha1 year1, 2.07 t ha1 year1 and 3.33 t ha1 year1 (Jana et al., 2009). In India, the potential of short rotation forestry species in sequestering carbon has been reported for Poplar, Eucalyptus, Sal, Teak, Leucaena, Albizzia and Acacia species. The annual rate of accumulation of carbon in these tree species ranged from 1 t ha1 year1 in sal (S. robusta) to 11.8 t ha1 year1 in poplar in the Indo Gangetic regions under irrigated conditions (Prasad et al., 2012). 4. Conclusion This study illustrates field measurement and estimation of diurnal carbon sequestration rate of seven young broadleaved plant species (A. auriculiformis, A. lebbek, D. sissoo, Eucalyptus spp, S. mahagoni, T. grandis, T. arjuna) of 6 years of age. The study concludes the average leaf level net assimilation rate of CO2 by the abovementioned species at Budge Budge of South 24 Parganas for summer, monsoon and winter in 2010e11 were 6.11 mmol m2 s1, 8.13 mmol m2 s1, 7.05 mmol m2 s1, 7.36 mmol m2 s1, 3.98 mmol m2 s1, 4.43 mmol m2 s1 and 5.45 mmol m2 s1 respectively. The average net assimilation rate of carbon at canopy level as obtained by us for the above-mentioned species were 6.78 g h1, 5.11 g h1, 2.95 g h1, 10.55 g h1, 1.98 g h1, 8.04 g h1 and 5.91 g h1 respectively. Thus, it may be concluded that net assimilation rate at canopy level is maximum for Eucalyptus spp. and minimum for S. mahagoni. Among the total sampled trees annual carbon sequestration rate from ambient air the maximum yield has been shown by A. lebbek (1.79 t ha1 year1) and minimum by T. arjuna (0.12 t ha1 year1). The overall annual carbon sequestration rate of the created forests of mixed species was estimated as 6.01 t ha1 year1. Acknowledgments Authors are thankful to the Department of Science and technology, Govt. of India (DST/IS-STAC/CO2-SR-49/08) for financial support of this study. We also like to acknowledge the authority, all the officials and ground staffs of Budge Budge Generating Station of CESC for their kind assistance and cooperation to conduct the study in a smooth manner. References Bala, S., Biswas, S., Mazumdar, A., 2012. Potential of carbon benefits from Eucalyptus hybrid in dry-deciduous coppice forest of Jharkhand. ARPN Journal of Engineering and Applied Sciences 7 (12), 1614e1622. Baldocchi, D.D., Meyers, T., 1998. On using eco-physiological, micrometeorological and biogeochemical theory to evaluate carbon dioxide, water vapor and trace gas fluxes over vegetation: a perspective. Agriculture and Forest Meteorology 90, 1e25. Baldocchi, D.D., Wilson, K.B., 2001. Modeling CO2 and water vapor exchange of a temperate boradleaved forest across hourly to decadal time scales. Ecological Modeling 142, 155e184. Baldocchi, D.D., Wilson, K.B., Gu, L., 2002. How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad-leaved deciduous forest and assessment with the biophysical model CANOAK. Tree Physiology 22, 1065e1077. Beedle, C.L., Neilson, R.E., Talbot, H., Jarvis, P.G., 1985. Stomatal conductance and photosynthesis in a mature Scots pine forest. I. Diurnal, seasonal and spatial variation in shoots. Journal of Applied Ecology 22, 557e571. Biswas, S., Bala, S., Mazumdar, A., 2013. Carbon sequestration potential of agroforestry species in red and laterite zone of West Bengal towards sustainable development. Indian Journal of Environmental Protection 33 (2), 109e118. Breada Nathalie, J.J., 2003. Review Article: field techniques ground-based measurements of leaf area index: a review of methods, instruments and current controversies. Journal of Experimental Botany 54 (392), 2403e2417.

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