Comprehensive Assessment of Meta-Analysis and Contingent Valuation Technique for Sustainable Management of Wetland of Middle Ganga Plain

Table 7 shows the specific monetary value of fishing in Suraha Tal Wetland. It is rich in fisheries and is able to supply plenty of fish every season. The main source of fish is the Ganga River, and the surrounding dwellers, particularly fishermen, depend on this resource for their daily livelihood. But the fishermen have not started pisciculture in this wetland. The major species of fish available are Rohu (Labeorohita), Katala (Catlacatla), Bhakur (Catlacatla), Nainee (Cirrhinusmrigala), Singhi (Heteropneustesfossilis) and Saur (Cololabissaira) and their production in the monsoon is about 5,000 kg at a market price of about INR 250–300 × kg⁻¹. The total production and its total market price in the year 2015 are shown in Table 7. So, in terms of fish production, Suraha Tal Wetland is a valuable resource.

Suraha Tal Wetland is famous for aquaculture. One of the most important aquacultures is cultivation of the lotus plant. The lotus flower is produced in the pre-monsoon period, and most of the produce is exported to other states or countries. In 2014, INR 23 lacs were earned by selling only the lotus flower. Other than this, the petals, stamen and roots of lotus are also produced and sold in the pre-monsoon. The market values of these products are given in Table 8. It is observed that lotus is very profitable for aquaculture and due to the natural wetland environment, the stakeholders do not need to invest much. The total calculated value of lotus in Suraha Tal Wetland in the pre-monsoon was about INR 2,320,445 in 2014.

In 2014, approximately 500 kg of water lily was produced in Suraha Tal Wetland. The market price of water lily flower was INR 20–30 × kg⁻¹ (Table 7). The root of the water lily was sold at INR 20–30 × kg⁻¹ (Table 9). The total market price of water lily was about INR 24,685.

Suraha Tal Wetland covers about 9,450 acres, but in the pre-monsoon and winter seasons the wetland gets dry and covers an area of only 2,774 acres (Pandey et al. 2010). The remaining area of 6,676 acres is cultivated during the dry spell of winter and summer (Pandey et al. 2010). The soil of the wetland bed is very fertile due to the accumulation of humus. The main crops in this area include wheat, legumes like peas, gram, arahar and rice. Most of the people cultivate on a small scale and use the cultivated products for their own needs. Some of them sell the crops on the market. Another valuable resource that Suraha Tal Wetland provides is fertile soil, which makes the surrounding people take part in cultivation. The total profit for agricultural production is given in Table 10.

The villagers around the wetland use it for their daily needs, for example, bathing, washing and so on. Besides this, the wetland provides them with a number of benefits and services. They ask how much compensation they should pay if they cannot avail the facilities for their daily life. Most of the villagers are poor and depend only on fishing and cultivation. Fig. 2 depicts the willingness to pay of the surrounding villages of Suraha Tal Wetland. About 47% villagers have WTP of up to INR 20 (Fig. 2). According to Fig. 2, about 33% of people have WTP of up to INR 20–40 and only 8% people wanted to pay more than INR 60. The average calculated willingness to pay for Suraha Tal Wetland is about INR 54,820. The contingent valuation thus proves that Suraha Tal Wetland is important for daily use and also has a high indirect value.

The relation between WTP and other financial parameters is shown in this study. The seven important financial indicators of lifestyle are chosen and the relationship between WTP and these indicators are calculated.

It is observed that the seven indicators are positively related to WTP. But education, total annual income and the landholding size of a household are related in a strongly positive manner. In Table 11, it is observed that age and education are negatively related to family size. Another noticeable trend is that people who live near Suraha Tal Wetland are members of the eco-development community. But again, there is a weakly positive relation between education and the number of members of the eco-development community. It is observed that less educated people are mostly prone to be members of the eco-development community (Table 11).

The environmental value is classified as fish biodiversity, faunal biodiversity, water quality and cultural value. The environmental value is assessed through the literature review. CMA is used to figure out the weightage and relevance of previous studies.

Suraha Tal Wetland is famous for different types of fish and helps to sustain not only aquatic creatures but also those people who depend on fish for their daily livelihood. About six studies are found on fish diversity in Suraha Tal Wetland. Singh et al. (2009) found 42 fish species in Suraha Tal Wetland, whereas 59 species were found by Pandey et al. (2010). In 1976, Lakshman Ram found 48 fish species but in 2012, 56 species were found by Singh et al. (2012). The review of the literature suggests that the fish diversity in Suraha Tal Wetland has increased and the wetland is rich in fish diversity.

Suraha Tal Wetland is also rich in other faunal diversity, which has been proved by three studies. According to Sharma and Agarwal (2012), 29 types of species of insects are found in this wetland; 20 types of molluscan fauna species were found by Sharma and Agarwal in 2012, while Srivastava and Srivastava in 2012 found 92 types of bird species or avifaunal diversity in Suraha Tal Wetland. It is visited by migratory birds as well.

The water quality of a wetland is an important criterion of environmental value. The water quality of Suraha Tal Wetland has been tested by five studies previously. Shukla et al. in 2015 analysed the water through 20 water samples based on 12 water quality parameters. Most of the studies were conducted in 2015. In 2010, Sharma and Sony tested 96 water samples based on 20 water quality parameters. These studies showed that the water quality of Suraha Tal Wetland was good for different floral and faunal diversity.

Surah Tal helped to grow a group of fishermen called ‘Nishad’, who depend solely on fishing for their daily life. The wetland and associated fish diversity are their main resource. The wetland not only serves them as a resource, but also helps to cultivate a unique culture of fishermen. It sustains the culture and fishing practice of the surrounding villages. In 2012, Srivastava and Srivastava found that the fisherman of Suraha Tal Wetland used seven types of fishing gear which are indigenous. These fishing gears were inheritable. These indigenous processes do not harm the biodiversity of the wetland and that makes it one of the valuable resources of Suraha Tal Wetland.

The null hypothesis is that each study and its referred literature have shown the same results. Based on this hypothesis the mean and standard deviation of the particular study and of the referring literature is calculated. The CMA runs an analysis to get the effect size of the sample. This analysis shows the relevance of the previous study, which is reviewed for environmental value (Fig. 3). The fixed effect model is only analysed in this study. Hedges’ g is selected as a displayed effect size index. The Hedges’ g index and forest plot in Fig. 3 suggest that the effect size of fish diversity, faunal diversity and water quality studies fall on the positive size of zero ranging from 0.5 to 2.0. Only the study of cultural aspects falls on the negative side of zero because of its small effect size (Fig. 3). The combined effect is 0.329 with a 95% confidence interval (CI) 0.500–2.000. CMA first calculates the standardised mean difference (d) and then multiplies (d) by a correction factor (J) to compute Hedges’ g. So first, the pooled standardised deviation is calculated as follows: (1) Raw difference=Mean1−Mean2 SDpooled=σ12(N1−1)+σ22(N2−1)(N1−1)+(N2−1)(Mangal 2012) \matrix{ {{\rm{Raw}}\;{\rm{difference}} = {\rm{Mea}}{{\rm{n}}^1} - {\rm{Mea}}{{\rm{n}}^2}} \hfill \cr {\;\;\;\;\;\;\;\;\;\matrix{ {{\rm{S}}{{\rm{D}}_{{\rm{pooled}}}}} \hfill & = \hfill & {\sqrt {{{\sigma _1^2\left( {{N_1} - 1} \right) + \sigma _2^2\left( {{N_2} - 1} \right)} \over {\left( {{N_1} - 1} \right) + \left( {{N_2} - 1} \right)}}} } \hfill \cr {} \hfill & {} \hfill & {\left( {{\rm{Mangal}}\,2012} \right)} \hfill \cr } } \hfill \cr } where σ12(N1−1) \sigma _1^2\left( {{N_1} - 1} \right) is deviation of scores of the first samples from its mean, σ22(N2−1) \sigma _2^2\left( {{N_2} - 1} \right) deviation of scores of second sample from its mean; N₁ is the first sample size and N₂ is the second sample size (Mangal 2012). After this, standardised mean difference (d) is also calculated as (2) Standard difference = raw difference/SDpooledStandardised mean difference(d)=1N1+2N2+Stddiff22×(N1+N2)(Borenstein et al. 2007). \matrix{ {{\rm{Standard}}\,{\rm{difference}}\, = \,{\rm{raw}}\,{\rm{difference}}/{\rm{S}}{{\rm{D}}_{{\rm{pooled}}}}} \cr {\matrix{ {{\rm{Standardised}}\,{\rm{mean}}\,{\rm{difference}}\left( d \right)} \hfill & = \hfill & {\sqrt {{1 \over {{N_1}}} + {2 \over {{N_2}}} + {{{Stddiff^2}} \over {2 \times \left( {{N_1} + {N_2}} \right)}}} } \hfill \cr {} \hfill & {} \hfill & {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right).} \hfill \cr } } \cr }

Fig. 3

After this, the standardised mean difference is multiplied by a correction factor (J) to find the G value.

Correction factor JCorrection factor J (3) J=1−(3/(4×df−2)(Borenstein et al. 2007) \matrix{ {J = 1 - \left( {3/\left( {4 \times df - 2} \right)} \right.} \cr {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right)} \cr } where df is a degree of freedom and total sample size (N) <2, that is {(N1 + N2) − 2}.

Computation of Hedges’ g helps to understand the measurement of effect size. Effect size is a measurement of difference between an experimental and control group (Borenstein et al. 2007). (4) G=d ×J(Borenstein et al. 2007) \matrix{ {G = d\, \times J} \cr {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right)} \cr } where d is the standardised mean difference and J is the correction factor. (5) Variance (g)=(g2)(Borenstein et al. 2007) \matrix{ {{\rm{Variance}}\,\left( g \right) = \left( {{g^2}} \right)} \cr {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right)} \cr }

According to Fig. 3, the most weighted study is fish diversity and water quality, and cultural aspects study have nearly the same weightage. The study on faunal diversity is recorded as the least weighted study (Fig. 3). The higher p-value (Fig. 3) is acquired through the z-value, which suggests that the results of this particular study and its referred literature have different results. Thus, the above-mentioned null hypothesis is rejected.

Calculation of z-value is as follows: (6) Z=point estimate/standard error(Borenstein et al. 2007) \matrix{ {{\rm{Z}} = {\rm{point}}\,{\rm{estimate}}/{\rm{standard}}\,{\rm{error}}} \cr {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right)} \cr }

Computation of p-value is as (7) p=2[1−{ϕ(|z value|)}](Borenstein et al. 2007) \matrix{ {p = 2\left[ {1 - \left\{ {\phi \left( {\left| {{\rm{z}}\,{\rm{value}}} \right|} \right)} \right\}} \right]} \cr {\left( {{\rm{Borenstein}}\,{\rm{et}}\,{\rm{al}}.\,\,2007} \right)} \cr }

Using CMA, it is found that the literature on Suraha Tal Wetland is relevant and many studies are conducted on the environmental value of this wetland. Each study has different results and significantly differs from the studies prior to it. The study on fish diversity and water quality are more frequent rather than other studies. The research on the cultural aspects of fisherman by Srivastava and Srivastava (2012) is a unique and very significant study. The review of the literature through CMA proves that Suraha Tal Wetland is not just environmentally rich with biodiversity, but also enriched with unique cultural resources.