Relationship in Tree outside Forests of Terai, Nepal Ram Asheshwar Mandal
1*, Bijay K. Yadav
2, Sujit K. Jha
3and Ramesh K. Giri
4Abstract
Tree outside forests (ToFs) is major source of timber and firewood for farmers living distant from the forests in Tarai (plain), Nepal. Importantly, the ToFs can also reduce the pressure on natural forests which may be the potential candidate under Reducing Deforestation and Forest Degradation (REDD+) mechanism so carbon stock assessment is essential. Equally, biodiversity conservation is other significant global concern but no any study was done yet to assess the relationship between carbon stock and plant biodiversity especially in ToFs. Thus this research has main objective to assess the relationship between carbon stock and plant biodiversity. Altogether, 161 sample plots of 10m*10m quadrates were established using Global Positioning System (GPS) coordinates and collected from ToFs of Pipara and Sahodawa villages of Mahottari district maintaining 1% sample intensity applying multistage random sampling. Height and diameter at breast height (DBH) of plants were measured, soil samples were collected from 0-0.1, 0.1-0.3 and 0.3- 0.6m depths and species were counted. Biomass was calculated using equation of Chave et al and converted into carbon. The soil carbon was analyzed in laboratory. After estimating the biodiversity indices, the relationship between carbon and biodiversity was developed.
The estimated carbon stock of ToFs was the highest 65.57 t ha-1 in rich households in Pipara village while it was the lowest 43.30 t ha-1 in poor households in Sahodawa village.
The values of Shannon-Weiner Biodiversity Index ranged 1.66-2.08 and no any significant relationship existed between carbon stock and biodiversity. Thus, the REDD+ mechanism should emphasize on biodiversity conservation.
Key words: tree outside forests, biodiversity, carbon, REDD+
1 Ph D candidate Trichandra College, Kathmandu.
2 Assistant Forest officer, department of forests.
3 Department of Forests, Babarmahal, Kathmandu.
4 Assistant Forest Officer Department of Forests
* Corresponding Author : Email- [email protected]
Introduction
Trees outside forests (ToFs) mean the trees available on trees outside the forests which are generally detached with the contiguous forest block like trees on alley, orchard, park, bank of the pond, canal, lake and river, along roadside, home garden, office compound, agricultural land and parks. FAO defined ToF as trees available on lands which is not defined as ‘forests’ or ‘other wooded land’
(FAO 2005). In India, ToF is defined as all those trees, which have attained 10 cm or more diameters at breast height, available on land, which is not notified as forests (FSI 2011). Though, there is no any legal definition of ToF in Nepal, it includes the tree in other wooded land than the forest (DFRS/FRA, 2014).
Tree outside forests (ToF) is the major source of timber and firewood for farmers (Longi et al, 1999, Singh et al, 2012) living distant from the forests in Tarai (plain) Nepal, because they have not enough and easy alternatives to meet their demand of forest products. The consequences are reducing the pressure on natural forest in one way and carbon enhancement and species diversity in other way (Singh et al, 2009, Thompson, et al, 2009). This can meet the important goal of Reducing Emission from Deforestation and Forest Degradation (REDD+) mechanism.
Record of carbon is the main threat to carbon stock and biodiversity. Annually, there was -5.2 million ha of forest loss in the world between 2000 and 2010. It was more than 0.9 million ha forest area shrink in Southeast Asia in the last 10 years (FAO, 2010). The estimated annual deforestation was 16,500 ha in Terai forest in between 2001 to 2010. Meanwhile, the recorded forest cover loss was 32,000 ha between1991 to 2010. Thus, the annual deforestation rate was 0.44% and 0.40%
between 2001 to 2010 and 1991 to 2010 respectively (FRA/DFRS, 2014). Infact, the depletion in forest affects negatively on carbon stocks and biodiversity together (Sedjo, 2001).
Plantation in trees outside forest has been playing positive roles in carbon enhancement and biodiversity conservation (Leah, et al, 2010). Globally, estimated total plantation area was 264 million ha in 2010 which has capacity to store about 1.5 gigatonnes of carbon annually. Specifically, almost half of the agricultural land has trees cover more than 10% in the world (more than 1 billion ha), they are ToF. Net gain of forest was reported more than 2.2 million ha per year in Asia between 2000 to 2010 because of large scale of afforestation in China (FAO, 2010). Though, there was no clear record of ToF in Nepal, mostly the private plantation is considered as ToF. Estimated record of ToF was 10,240 ha in the country (DoF, 2005). These all plantations offer to store and capture the carbon and ultimately support to ease the people's pressure on national forests
(Gibbs et al, 2007), this concept is aligned with the main purpose of REDD+
mechanism (Skutsch et al, 2009, Corbera, 2010). But, it is fact that the choice of species for plantation clearly depends up on the farmer's preference and value of the products. The consequence may be monoculture species which is the major threat to biodiversity.
The over exploitation of forest and impacts of climate change are creating a great threat to plant species. Approximately 8000 tree species, or 9% of the total number of tree species worldwide are under threat of extinction (Singh et al, 2005). The continuous deforestation is the high threat for the biodiversity in the tropics (FAO, 2010). Though, the land surface area of Nepal is only 0.1 % of the world’s area, she harbors 136 ecosystems, about 2 % of the flowering plants, 3 % of the pteridophytes, and 6 % of bryophytes of the world’s flora. Unfortunately, 8 species are suspected to be extinct, 1 species is endangered, 7 species are vulnerable and 31 species fall under the IUCN rare species category in Nepal (MFSC, 2000).
Infact, the REDD+ mechanism has primarily focus on the carbon enhancement but biodiversity is considered as co-benefit. It may mislead the understanding of valuing the biodiversity compared to carbon while they have parallel importance under United Nations Framework Convention on Climate Change (UNFCCC). In addition, establishment of monitoring reporting and verification (MRV) and reference emission level and assessing the strategy of social and environmental impacts assessment (SESA) need robust and intensive data of forest carbon and biodiversity (Corbera et al, 2010). Besides, biophysical characteristics of forest are generally correlated to the forest carbon stock. Hence, a remarkable question is raised that, whether there is any relationship between the carbon stock and biodiversity in ToF? This research tries to answer this question because such research has not been done yet in ToF especially in Tarai (plain), Nepal.
Therefore, the objective of the research is to assess the carbon stock and biodiversity of ToF and relationship between them.
Materials and Methods
Research site: Pipara and Sahodawa villages were selected for the study sites (Figure 1) which are situated far from the forest in Mahottari district, Nepal. This district lies in 26o 36' to 28o10' N and 85o41' to 85o 57' E. It has tropical and subtropical climate. The record of minimum temperature shows 200C and maximum 450Cand the average annual rainfall has been recorded between 1100- 3500 mm however they are not common every year.
There were about 28 tree species in ToF in both villages. The most dominant species were Mangifera indica, Eucalyptus camaldulensis, Dalbergia sissoo, Tectona grandis while other species were Psidium guajava, Syzygium cumini, Gmelina arborea, Dalbergia latifolia.
Figure 7 : Map of research site of ToF in Sahodawa and Pipara villages Data collection: Basically, socioeconomic and biophysical data were collected for this research work.
Socio- economic data: Due to diverse nature of ToF area, total households were categorized into three main groups: rich, medium and poor. Generally, large sizes (areas > 0.17 ha) of ToF owned by rich family while home garden belonged to poor family semi orchard (areas < 0.17 ha and home orchard too) were with medium family. Thus, after collecting the record of total households of Pipara and Sahodawa villages, they were categorized into rich, medium and poor family applying participatory well being ranking process. The criteria for dividing household category were types of house, employment, land holding, cattle keeping, education, income source (business) and food security (Chapagain and Banjade, 2009). If household has annual income about US$ 1000- 2000, Khapada (roofing burnt clay tile), 1 employee, 1 ox and 1 cow and educational qualification at least class 10 pass are categorized under medium family while having more than that grouped under rich and less than that are kept under poor household
(HH). There were 454, 576 and 605 HHs in rich, medium and poor respectively in Pipara village while they were 420, 540 and 540 correspondingly in Sahodawa village. The purpose of this is to conduct design the experiment and carry out the representative sampling.
Next, list of ToF holding farmers were prepared and their ToF areas were recorded. Then considering the ToF areas as a sample unit or one block, 1%
sample area of ToF from each household category were sampled applying multistage random sampling. Thus the randomized block design (RBD) was set.
About 31, 29 and 23 samples were collected from ToF of rich, medium and poor HHs respectively of Pipara village. Similarly, 27, 27 and 24 samples were collected from that of rich, medium and poor HHs correspondingly of Sahodawa village. Total area of ToF was 66.00 ha, in Pipara village, Out of this 23, 15, 8 ha were with rich, medium and poor HHs correspondingly in this village while total it was 66 ha in Sahodawa village out of this 38, 21 and 7 ha were with rich, medium and poor HHs correspondingly.
Biophysical data : The centre point coordinates of selected ToF areas were located on the map for samples and their coordinates were uploaded to GPS reciever.
Then, rectangular sample plots for tree, pole and sapling (dbh>5cm) of 10m*10m and sapling (dbh<5cm) and seedling, herbs and grasses of 5m*5m were established. The height and diameter at breast height were measured and recorded. Then, sapling (5cm >dbh >1cm), seedlings, herbs and shrubs were counted and fresh weights of their samples were recorded (Mandal et al., 2013).
Simultaneously, soil samples were also collected from three different depths 0- 0.1, 0.10-0.3 and 0.3-0.6m in order to determine the soil carbon (Eggleston, 2006).
Meanwhile, the list of tree species was prepared to assess the biodiversity.
Data Analysis:
Calculation of carbon: It is prerequisite to estimate the forest biomass for calculation of the carbon except soil. Therefore, the Above Ground Tree dry Biomass (AGTB in kg) was determined by using
(Chave et al, 2005)
where D is the diameter at breast height (cm), H is the height of the tree (m) and ρ is wood density (g/cc).
Moreover, the biomass of dbh<5cm was quantified applying equation developed by Tamrakar's (2000) but this equation gives only the fresh weight so collected
related samples were dried in the laboratory at 105 0C until they showed the constant weight.
Where AGSB represents the above ground sapling biomass (kg), Ln is natural log, a & b are constants, DBH (cm) is diameter at breast height.
Similarly, dry weight of samples of seedling, leaf litter, herbs and grass (LHG) were recorded. Additionally, the root shoot ratio 0.125 was used to calculate the root biomass (MacDicken, 1997). The multiplying factor 0.47 was used to convert the biomass into carbon (Chabbra, 2002)
Soil carbon was estimated by applying the Walkley Black Method (Walkley et al., 1958).
Bulk Density (BD g/cc) = (oven dry weight of soil)/ (volume of soil in the core) SOC= Organic Carbon Content % * Soil Bulk Density (Kg/cc) * thickens of horizon.
Total Carbon= Total Biomass carbon + Soil carbon (Mini, 2011)
Biodiversity calculation: biodiversity indices were calculated using following formulae.
Species richness S: is the number of species in the community or sample
Simpson's evenness , Where D is the Simpson's diversity index, S is the species richness
Shannon-Weiner Biodiversity Index, , where pi is the total individuals in a species community (Barlow et al, 2007).
Relationship between carbon (biomass) and biodiversity: Regression analysis was carried out to determine the correlation between carbon stock and biodiversity.
For this, only biomass carbon was used. So, the relationship between carbon stock and species richness as well as carbon stock and Simpson evenness was developed so that REDD+ policy implication may be worthwhile.
Statistical analysis: Likewise, only total carbon stock was used for statistical analysis. The variation in carbon of ToF belonging to different household categories were tested applying one way ANOVA, Tukey’s test and t-test by using software EBM SPSS 21 (Rocky et al, 2012).