Dayara bugyal restoration model in the alpine and subalpine region of the Central Himalaya: a step toward minimizing the impacts

Restoration response evaluation

Multi-criteria response analysis has been a crucial part of restoration evaluation work as a proper practical achievement which always includes multiple objectives defined by diverse stakeholders. In current work, a new framework was designed for restoration response evaluation by assessing three categories, direct management measure (M), environmental desirability (E) and socio-economic feasibility (SE). In total, 9 sub-categories and 22 individual variables were considered for evaluation of the present work⁴¹ (Table 6).

Direct management measure (M) evaluation

During the starting phase of the work, excessive grazing, uncontrolled tourism and continuous soil erosion were identified as major drivers behind the degradation of Dayara bugyal. Therefore, in the first category of the evaluation work, direct management measures to control the above-mentioned activities were analysed. The disturbances were controlled by managing both anthropogenic (M1) and natural (M2) processes. Under anthropogenic control process, grazing (A1) and tourism (A2) control activities were measured and soil erosion (B1) control activities was considered under natural control sub-category.

Livestock carrying capacity

Livestock carrying capacity of the pastureland was a measure for proper control of the estimation of grazing capacity. Forage yield of the area was calculated by considering the shoot production of 10 dominant palatable species of the area. Sample plant materials at the end of the growing season, were oven-dried at 80 (^circ)C till it reached at constant weight and then weighed in the laboratory. Thereafter, density of individual plant was measured by laying 30 quadrates of 1 × 1 m randomly placed within 50 × 50 m grid in the herb community (Eq. 1)⁴². Total 80 grids were sampled for analysis of 40 hectare degraded grazing land of the Dayara alpine pasture from the Papad Gad and Swari Gad area. Thereafter, 10 dominant palatable species covering ~ 33% of the total dry weight of the palatable and unpalatable species were considered for forage production calculation. Peak biomass was calculated by summing up the peak biomass of each individual to get the forage yield (Eq. 2). Finally, standard dry forage yield and proper rangeland carrying capacity was calculated by using Eqs. (3) and (4)⁴³ as follows.

where, Y = forage yield in a certain area (kg), Yp i = forage yield per unit area (kg/km²), A = land area of rangeland (km²) (i.e., total grazing area of the Dayara occupies 3.235 km²).

where F = yield of standard dry forage (kg), Yi = forage yield (kg), Ui = utilizable rate (%), Ci = conversion coefficient.

Utilization rate 50% and conversion coefficient 1 for meadow was considered for current work⁴³ .

where, Cc = proper livestock numbers that meadow can bear, F = yield of standard dry forage (kg), I = daily intake for an animal unit (7.5 kg/day, Table 7)*, D = Grazing days (May to September, 153 days).

*One animal consumes 3% of its body weight as dry forage⁴⁴. Animal unit conversion was done after Rawat (2020)⁴⁵.

Tourists’ Carrying Capacity (TCC)

The general formula of carrying capacity assessment for protected areas was first proposed by Cifuentes (1992), which was further applied in different fields⁴⁶. The approach is to establish the capacity of an area for maximum visits based on existing physical, biological, and management conditions through the physical carrying capacity (PCC), and real carrying capacity (RCC). TCC is divided into the following levels:

Physical Carrying Capacity (PCC)

The PCC is the maximum number of tourists that can physically accommodate into or onto a specific area, over a particular time. The PCC (Eq. 5) may be estimated as follows:

where, PCC = physical carrying capacity; A = Available area for tourists use ; 15%-18% area of the total geographical area is considered for the present work according to the expert opinion and URDPFI guidelines for hill towns⁴⁷.

Au = Area required per tourist; in general, it is considered 3 m². However in the present work, 5 m² area is considered for one person based on nature of the area is relatively more sensitive to degradation.

Rf = Daily open period / average time of visit.

Average opening time = 6 h (according to the field survey, tourists like timing for a day visit between 9 AM to 3 PM), time required by one tourist to visit the Dayara bugyal = 3 h.

Rf = 6 h/3 h = 2.

Real Carrying Capacity (RCC) (Eq. 6)

Maximum permissible number of tourists to a specific site could be determined once the Correction factors (CF) becomes possible to derive out of the particular characteristics of the site. CF is applied to the PCC as follows.

where RCC = Real Carrying Capacity, PCC = Physical Carrying Capacity, Cf = Correction factors.

Correction factors are calculated using the following formula.

where Cfx = Correction factors of variable x, Lmx = Limiting magnitude of variable x, Tmx = Total magnitude of variable x.

Tourism is dependent on nature. In the present work, number of days with heavy rain (> 250 mm per day) and snowfall (> 8 cm per day) were considered as limiting variables that control tourism for the area. The calculations were done by analyzing the rainfall and snowfall data from 2017 to 2019 considering March to November as rainfall months and December to February as snowfall months. Total numbers of days in the months were considered as total variables (Tmx) and the days with heavy rain/snow fall were considered as limiting variables (Lmx). For example, during 2017 to 2019 total number of days from March to November were 909 days (Tmx) and in 369 heavy rainfall occurred, therefore, Cf1 was 0.59 (1—Lmx/Tmx). Similarly, during this time heavy snowfall occurred for 51 days out of 186 days, and Cf2 was 0.72.

Measurement of soil erosion control

Eco-friendly bio-degradable coir geo-textile (9000 sq m) purchased from Coir Board of India, locally available pine needle (240 tonne) along with bamboo were roped in, to create a series of check dams and channels to control soil erosion, gully formation and vegetation loss. Prior to commencement, the leveling of uneven surfaces was done before laying the coir geo-textile. The open degraded sites in different patches of the bugyal, the eroded lateral sites of the gullies were then covered with geo-textile to control soil erosion. Total 38 check dams in the Swari Gad area were examined for draining soil holding capacity. After one year of the treatment, total mass of debris stored by each check dams was evaluated using core density method. The core density of bulk soil in each check dam was determined in triplicates, using an iron core of 2.5 cm radius and 30 cm height. The mass of draining soil checked by each check dam was calculated as under⁴⁸:

where, Md = The mass of debris in each check dam, V = Volume of check dam, ρb = Mean core density of bulk of soil in each check dam.

Environmental desirability (E) assessment

In this part, environmental desirability, the direct ecological outputs of the work were considered under this category, as habitat enhancement is the most crucial component of the activity. The sub-component considered under the category included vegetation structure (vegetation diversity, vegetation cover) and ecological progress (soil chemical properties)²⁰. Vegetation sampling was done by considering 30 randomly placed quadrates of 1 × 1 m inside 9 sample plots of 5-50 m along three different zones of the treated water channel areas using vertical belt transact method⁴⁹. The zones were: (i) geo-coir treated area, (ii) untreated degraded area, (iii) reference untreated non-degraded area along with both sides of the water channels wherein total vegetation density (Eq. 1) was analysed following the methodology of Misra (1968) and Mueller-Dombois & Ellenberg (1974)^50,51.

Soil sampling

Soil samples (30 cm depth) were collected from the experimental site in triplicates using random sampling method from all the three investigation zones, namely, Untreated undegraded zone (R), Geo-coir Treated Zone (GTZ) and Untreated Degraded Zone (UTZ). Fresh samples were taken from each plot (50 random soil cores per replicate per investigation zones) and were mixed thoroughly as one composite sample for further study. Here, it is to mention that utmost care was taken to collect each replicate as composite soil sample to appropriately represent the investigation zones of varied topography. Hence, total 9 soil samples (3 samples per investigation zones) were collected to determine its physico-chemical characteristics. After collection, the soil samples were preserved in a portable storage box and transported to the lab immediately. After air drying and grinding, it was passed through 2-mm sieve, and selected soil properties viz. soil organic carbon (SOC) (%), soil pH, total nitrogen (N), phosphorus (P), potassium (K) contents (%), and water holding capacity (WHC) (%) were determined.

Soil physico-chemical analysis

The SOC content in soil was determined by wet oxidation method using K₂Cr₂O₇⁵². The soil pH was measured with a suspension of soil in water at a 1:2.5 (soil : water) soil-to-solution ratio using a glass electrode. Calibration of the pH meter was done with the help of two buffer solutions of pH 7.0 and 9.2⁵³. The WHC of the soil was determined by measuring the ratio of total water in the wet soil to the weight of the air-dried soil using a Keen– Rackzowski box⁵⁴. Total N was analysed following the micro Kjeldahl method⁵⁵. Total phosphorous (TP) was determined using the HClO₄-H₂SO₄ method⁵⁶ and total potassium (TK) was measured by Flame Photometer (NaOH melting)⁵⁷.

Socio-economic feasibility (SE) assessment

To investigate the opinion of local residents about the restoration initiative, village survey was conducted in two adjacent villages of the Dayara bugyal, Barsu (2232 m) and Raithal (2258 m). Participants had to indicate the degree of the work in above mentioned three scales (M, E and SE). The questionnaire comprising of questions covered perception about the above discussed six categories (Supplementary S10). Total 60 respondents from different households were randomly selected from each village. The sample consisted of villagers as well as administrative staff. The informants were randomly chosen across 3 different age groups, 20–40, 40–60 and > 60 year⁵⁸. Economic feasibility was the first class and parameters considered under this category included cost-effectiveness of the material used, economic efficiency, i.e., benefit–cost ratio and economic impact of the generated income. In addition, social acceptability is the next category, where two sub-parameters were considered, procedural equity (inclusivity and participatory) in response to planning and designing and social preference that covers over current practices, access to resources and services. In the fourth category, technical feasibility was considered which included three subcategories. Adoption lag means waiting period required to adopt the response, replicability of the response and technical sophistication associated with response. In sixth category, cultural acceptability was considered to deal with alignment of the work with cultural, spiritual and aesthetic heritage values, beliefs and social norms and use of traditional (indigenous and local) knowledge and practices. In the last category, political feasibility was considered, where existing policy/legislation and governance mechanism (clarity on roles/responsibilities of stakeholders) was analysed. Each restoration response is ranked using a relative effectiveness or performance rating scale of low (L), moderate (M), or high (H). These effectiveness response ratings for each sub-criterion also reflect no (or minimal), some (or moderate) and major (or substantial) improvement, respectively, relative to the initial condition (pre-response).

Index score calculation

Restoration success index was calculated, by considering three categories, viz., direct management measure (M), environmental desirability (E), and socio-economic feasibility (SE). In the first scoring part, all the 22 individual variables were evaluated for calculation of “variable index”, by assigning index score between 0 and 3, where 0 rated for ‘not satisfactory’ and 3 rated for ‘satisfactory’. For first two categories, i.e., direct management measure (M), environmental desirability (E), and direct field values were considered. The last category, socio-economic feasibility was indexed depending on village questionnaire survey. The second score “category index” was calculated by adding all variable index and divided by number of independent variables within that category. Finally, the “restoration evaluation index” was evaluated by summing all category scores, dividing by the maximum possible score (16) and multiplying by 100⁵⁹ (Fig. 8). Ecosystem differences between reference, degraded and restored sites category and ecosystem index scores were determined using unpaired one way ANOVA by using categories viz., direct management measure (M) and environmental desirability (E). To estimate the most affected variable between references, degraded and restored sites, discriminant function analysis (DFA) was carried out, using the field values of all measured independent variables under second category.

Source: Ecology - nature.com