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Dayara bugyal restoration model
in the alpine and subalpine region
of the Central Himalaya: a step
toward minimizing the impacts
Jagdish Chandra Kuniyal 1*, Priyanka Maiti 1*, Sandeep Kumar2, Anand Kumar1,
Nisha Bisht1, K. Chandra Sekar 1, Satish Chandra Arya1, Sumit Rai1 & Mahesha Nand 1
Eco-restoration initiative work in the high altitude Dayara pastureland (3501 m) from the Indian
Himalayan Region has been considered to be one of the successful eld demonstration against
both natural and anthropogenic degradation. The present study therefore attempts to assess the
implications of entire eco-restoration model as practiced by Department of Forest, Government of
Uttarakhand in 2019. Its assessment was done by calculating restoration success index by way of
considering three categories, viz., direct management measure (M), environmental desirability (E)
and socio-economic feasibility (SE) considering 22 individual variables. ‘M’ comprised both biotic and
abiotic pressures. Grazing and tourism were biotic, while abiotic pressure was considered mainly soil
erosion in alpine area due to topographic fragility. Above ground vegetation prole and below ground
soil nutrient prole (N, P, K, pH and water holding capacity) were analyzed in ‘E’ component. In the
last but not least, ‘SE’ was analyzed to assess the social acceptability of the local communities and
stakeholders who are supposed to be ultimate beneciary of alike interventions. Direct management
measure was found with the variable index score of 0.8 indicating the higher score as compared to
environmental desirability (0.56). Under direct management measure, grazing and tourists’ carrying
capacity of the area was analyzed with high management needs to call the region sustainable in terms
of availability of bio-resources. The ecosystem index score was evaluated for the reference (81.94),
treated (64.5) and untreated zones (52.03), wherein increasing prole of these values were found. The
outcomes like improved vegetation prole in terms of total herb density, soil nutrient prole of the
restored area along with soil pH (4.96) and water holding capacity (49.85%) were found to be restored
signicantly along with controlling 169.64 tonne year-1 soil erosion from draining. The assessment of
grazing pattern of 118 migratory Cow Unit (CU) (76 horse/mule and 18 sheep/goat, already controlled),
318 local CU (30 horse/mule and 187 sheep/goat) were calculated and recommended to be controlled.
Tourists’ carrying capacity of 274 tourists per day and manual removal of Rumex nepalensis at the
shepherd camping site were found to be worth to apply in the area. Use of biodegradable but locally
sourced material and engaging local villagers in this endeavor were also found to be in harmony with
SDG Goal 1 (no poverty). Therefore, the restoration and its evaluation model could have its future
prospects to prove as a successful restoration practice. This restoration practice could not only be
worth in high altitude degraded alpine pastures of the Indian Himalayan Region but also to other
mountain alpine and sub-alpine ecosystems.
In the present scenario, gradual degradation of high elevation mountain eco-systems and their rational ecological
management have been a matter of great concern1. Although several restoration eorts have been made in high
altitude forests, treeline zone and wetland, yet restoration in meadows especially in alpine and sub-alpine have
not been much reported so far as they are unique, complex, and fragile natural area associated with restoration
implementation diculties2–4.
OPEN
India.
*
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Land restoration in high altitude degraded pasture areas addresses diverse issues associated with Sustainable
Development Goals (SDGs). As restoration activities produce employment, thus improving the socioeconomic
conditions of the poor (SDG-1, no poverty) needs a priority. Its successful examples include use of bamboo for
land restoration in China, Ethiopia, Cameroon, Vietnam, India, Madagascar, Ghana, the Philippines and Kenya5.
Other co-benets of land restoration include increased community resilience (SDG-2, zero hunger), improved
good health and well-being (SDG-3) of the associated villages, impacts on access to quality education (SDG-4,
quality education), income generation for women villagers (SDG-5, gender equality), restores ground water and
in turn ensure future clean water availability (SDG-6, clean water and sanitation), and also have direct impact
on SDG-13 (climate action), SDG-15 (life on land) and SDG 17 (partnerships to achieve the goal) (United
Nations Environment Programme, 2020). In context to land restoration, degradation of high altitude pastureland
leading to soil erosion nowadays have become a matter of great concern. Some of the examples of such lands
include, montane grasslands of the north-eastern Italian Alps (Italy)6, Asteroussia Mountains (Greece)7, and
High Himalayas in Nepal and India8.erefore, restoration of alpine pastures is a global need. Some restoration
guidelines available for low altitude forest and degraded lands include Restoration Opportunities Assessment
Methodology (ROAM)9, International principles and standards for the practice of ecological restoration, Eco-
logical Restoration Guidelines for British Columbia10 and Assessing Landscape Restoration Opportunities for
Uttarakhand, India, etc.11.
Some examples of the restoration activities of Govind Ballabh Pant National Institute of Himalayan Envi-
ronment (GBP-NIHE), Kosi, Almora, Uttarakhand, India have been implemented in Indian Himalayan Region
include Sloping Watershed Environment Engineering Technology (SWEET) developed by GBP-NIHE in 1994,
Badrivan Restoration Programme (BRP) at Badrinath, Uttarakhand in 1993, development of an agroforestry
model at Bansbara village, Rudraprayag District Uttarakhand in 2001, forest eco-restoration programme at Kolid-
haik, Lohaghat, Uttarakhand in 2004, community wasteland (open grazing land) restoration at Arah village in
1992, Bageshwar District, Uttarakhand, silvi-pasture development in Uttarakhand, rehabilitation of Bhimtal lake,
Nainital, Restoration of Surya Kunj at Katarmal, Almora, Uttarakhand, Dhoranalla and Mohal Khad (seasonal
stream) restoration work in Mohal, Kullu, Himachal Pradesh, implementation of Contour Hedgerow Farming
System Technology (CHFST) in Sikkim in 2005, and rehabilitation of degraded community land in Gumod,
Champawat district, Uttarakhand12.
Still restoration activities in high altitude degraded grasslands have neither proper guideline nor eld exam-
ples available till date. In this regard, the present work is a eld illustration of eco-restoration in high altitude
grassland at Dayara alpine pasture (3501m) which was initiated by the Department of Forest, Govt. of Uttara-
khand. So, the present attempt aims at evaluation of its impact in terms of grazing capacity, carrying capacity
of tourists, overall land stabilization from soil erosion, vegetation prole especially plant growth, soil nutrients
availability, etc. e applied restoration approach for current work is in harmony with the “Scientic Conceptual
Framework for Land Degradation Neutrality” by the United Nations Convention to Combat Desertication
(UNCCD) Science-Policy Interface13, and also concerns restoration denitions established by the Society for
Ecological Restoration14.
Study area
e study area of the current work is the Dayara alpine meadow (3501m) from Uttarkashi district of Uttara-
khand, India. e Dayara bugyal lies from 30°49′18.53"N to 78°32′31.20"E to 30°50′31.82"N to 78°33′24.71"E
and covers an area of 3.38 sq km (Fig.1). e entire area comprises extraordinary ecological diversity with a
large adjoining regions that helps in maintaining signicant biodiversity of both the Himalayan wildlife ora and
fauna. e pasture area is mainly dominated by three types of vegetation, namely, herbaceous meadow (Rumex
nepalensis Spreng., Anaphalis cuneifolia (DC.) Hook. f., Hackelia uncinata (Royle ex Benth.) C.E.C. Fisch.,etc.),
shrubberies (Rhododendron anthopogon D. Don—Rhododendron campanulatum D. Don) and stable boulder
(Bergenia strachyei (Hook. f. & omson) Engl., Arnebia benthamii (Wall. ex G. Don) I.M. Johnst., etc.)15. Faunal
diversity of the area consists of the Himalayan wildlife species like Musk dear (Moschus leucogaster, Hodgson,
1839), Brown bear (Ursus arctos isabellinus Horseld, 1826), Himalayan ar (Hemitragus jemlahicus C.H. Smith,
1826), Monal Pheasant (Lophophorus impejanus Latham, 1790), etc. It is the origin site of two important tribu-
taries of River Bhagirathi, locally known as Papad Gad (local stream) and Swari Gad. Both the streams not only
provide drinking and irrigation water to the downstream villages of Raithal, Kyark and Barsu but also maintain
the geo-hydrological system of the entire area. e place is also famous for its natural beauty and a favourable
tourist spot which have led to a variety of adverse impacts like increase in solid waste, trampling due to night
camps and other anthropogenic activities. Apart from these, the ecosystem has experienced the adversities of
climate change as heavy rainfall, ash oods, cloudbursts, etc. leading to disasters in the lower catchment of the
Bhagirathi valley. Along with this, the nomadic tribe known as Gujjars seasonally migrate to this pastureland
for grazing with the onset of spring and stay there till autumn. e unattended cattle of the adjacent villages
also occupy the area in spring and summers resulting in habitat degradation16. Gradual increase in mean annual
temperature and decrease in mean annual precipitation was also reected from the climatic prole of the area
with gridded resolution 0.5 x 0.5° (CRU TS 4.04, land) (Supplementary TableS1, S2).
Results
Direct management measure (M). Grazing capacity of the Dayara bugyal was calculated by evaluating
the standard forage production and daily demand of the livestock population. Total 70 species were found in
the sampled grazing areas dominated by Anaphalis cuneifolia, Taraxacum ocinale W.W. Weber ex F.H. Wigg.,
Iris kemaonensis Wall. ex Royle, Sibbaldia parviora Willd., Kobresia nepalensis (Nees) Kk., Trifolium repens L.,
Danthonia cachemyriana Jaub. & Spach, Carex nubigena D. Don, etc. Among the studied vegetation, 37 domi-
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nant palatable species recorded with the 52% of the total number of studied species (palatable & unpalatable)
were selected for calculation of forage production (Supplementary TableS3). Total dr y forage yield of the Dayara
bugyal was calculated 10,003 quintal per year (Table1) and yield of standard dry forage was 5001 quintal per
year which was 50% of the total yield for 4.23 sq km area. Only suitable area for grazing was considered for the
present work. Intake of one Cow Unit (CU) was calculated 7.5kg dry matter per day and 153 (May–September)
days grazing time was taken into account. e grazing capacity of the area was calculated as 436 cow unit per
year. Total migratory animal data for Taknor range and livestock census data for the village livestock were found
increasing in last 10years (Supplementary TableS4). As a part of management measure, grazing camps of Barsu
villagers were then shied away from Dayara to Lambidhar. Migratory animals were also found to be reduced
reasonably in the Tanknor range. According to the migratory animal record of Forest Department Uttarkashi
(2020) and livestock census data, total 881 CU were found to be grazed in the area in the year 2019. is value
exceeds the grazing capacity but the numbers of migratory animals (Gujjars) were found to be continuously
decreasing at a rate of 20 CU per year (Fig.2).
Figure1. (a, b, c) Geographical extent, and (d) climatic prole of the study area. {Source: CRU TS 4.04 (land),
0.5°}.
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During the last 5years, the tourists’ ow in the Dayara bugyalwas found to be increased by 186%. Nearly 2850
tourists are found to be increasing every year. According to the linear regression predictive model, the tourists’
number may be projected to be 30,999 per year by 2025, which indicates an expected increase of 343% tourists
(Supplementary TableS5). e tourists’ carrying capacity of the area was calculated to be 80,093–100,116 tour-
ists per year (Table2), taking into account the correction factors like rainfall, snowfall, tourists’ infrastructure,
ecological parameters and socio-economic parameters. e tourists’ inux of the Dayara bugyal in 2019 was
nearly 54 tourists per day. While based on our estimation, 275 tourists may be allowed for the place which reects
the necessity to promote tourism in the area.
For the measurement of tourism activity, Hon’ble High Court Uttarakhand, Nainital, in WPPIL No.123 of
2014 order, 200 tourists per day for bugyal areas need to be followed. Aer analysing tourists’ data of the area,
it was found under control and are not exceeding more than 200 tourists per day.
In view of controlling soil erosion, 170 tonne of soil was found to be arrested by the 38 check dams created
among three gullies (Supplementary TableS6). e horizontal sheet erosion in highly steep sloped areas near
the gullies also found to be controlled using the eco-friendly geo textile matting (Fig.3).
Environmental desirability (E). Environmental desirability was measured by considering both above and
below ground ecological parameters in the area. e negative inuence of degradation in alpine meadow on
Table 1. Standard forage production in the Dayara alpine pastureland. *Mean values are considered.
Plant name Density (individual/m2)* Above ground biomass (g/m2)* Forage yield (quintal /year)
Aconogonum tortuosum (D. Don) Hara 0.4 4.2 177.86
Anemone obtusiloba D.Don 0.23 2.68 113.49
Arnebia benthamii (Wall. ex G. Don) I.M.
Johnst. 0.06 12.8 542.04
Bistorta vivipara (L.) Gray 9.8 16.8 711.43
Bupleurum longicaule Wall. ex DC 0.2 1.3 55.05
Carex nubigena D. Don 4.42 1.5 63.52
Carex setigera D. Don 0.82 7.2 304.90
Cyananthus lobatus Wall. ex Benth. 0.57 6.1 258.32
Dactylorhiza hatagirea (D.Don) Soo 0.23 1.3 55.05
Danthonia cachemyriana Jaub. &Spach 0.33 60.2 2549.30
Epilobium latifolium L. 0.24 1.1 46.58
Eritrichium canum (Benth.) Kitam. 0.62 1.2 50.82
Euphorbia stracheyi Boiss. 0.2 1.4 59.29
Galium rotundifolium L. 0.23 0.2 8.47
Gentiana argentea (D.Don) Griseb. 0.23 0.8 33.88
Geranium wallichianum D.Don ex Sweet 0.3 0.9 38.11
Geum elatum Wall. ex G. Don 0.2 1.2 50.82
Impatiens scabrida DC. 0.31 1.3 55.05
Origanum vulgare L. 1.22 4.3 182.09
Oxygraphis polypetala (D.Don) Hook.f. &
omson 0.02 1.4 59.29
Parnassia nubicola Wall. ex Royle 0.27 3.4 143.98
Picrorhiza kurrooa Royle ex Benth 0.08 1.2 50.82
Poa alpina L. 0.23 1.1 46.58
Polygonum polystachyum Wall. ex Meisn. 0.4 1.8 76.22
Potentilla argyrophylla Wall. ex Lehm. 0.5 2.2 93.16
Potentilla atrosanguinea G.Lodd. ex D. Don 0.3 2.1 88.93
Potentilla fulgens Wall. ex Hook 0.13 1.7 71.99
Primula denticulata Sm. 0.4 2.9 122.81
Prunella vulgaris L. 4.43 6.3 266.79
Ranunculus hyperboreus Rottb. 0.4 6.1 258.32
Rumex nepalensis Spreng. 1.19 10.8 457.35
Salix lindleyana Wall. ex Andersson 0.01 22.6 957.04
Taraxacum ocinale F.H. Wigg 9.79 15.04 636.90
Trachydium roylei Lindl. 19.33 22.2 940.11
Trifolium repens L. 0.53 4.2 177.86
Valeriana hardwickii Wall. 0.04 0.5 21.17
Viola biora L. 4.24 4.2 177.86
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regeneration of herbs and soil water availability has considerable impacts. e entire area was evaluated in terms
of three zones, viz., geo-coir treated zone (GTZ), untreated degraded zone (UTZ) and untreated undegraded
zone (R). Both soil and vegetation analyses were done in all the three respective zones to minimize the ecological
eects of the restoration work. In case of above ground parameters, herbs diversity of the treated zone was found
to be increased when compared with the untreated zones. e total herb density per metre square was analysed
for vegetation diversity within geo-coir treated zone (GTZ), untreated degraded zone (UTZ) and untreated
undegraded zone (R), respectively. Dominating plant species existing at the time of eld study of the respective
zone are given in Table3. In the untreated undisturbed reference zone, dominated community was Danthonia
cachemyriana—Sibbaldia parviora-Anemone obtusiloba D. Don—Achillea millefolium community. Whereas,
geo-coir treated zone was found to be dominated by Sibbaldia parviora—Taraxacum ocinale—Achillea mille-
folium—Artemisia vestita community. Dominance of Danthonia cachemyriana—Rumex nepalensis—Achillea
millefolium community was found in untreated degraded zone.Colonization of Rumex nepalensis was found in
high frequencies in dierent places where anthropogenic disturbance was reasonably found (Fig.4).
In case of below ground in the GTZ parameters, like water holding capacity of soil was found to be 50%
which is 3% higher than the untreated degraded site (UTZ), i.e., 47%, within a span of one year aer treatment.
e water holding capacity of undisturbed soil was 57% which is expected to be increased in successive years.
Increase in water holding capacity will increase soil moisture content (SMC) which will help plants to grow more
and during later stages it may overcome negative soil water potential (SWP). SWP is a fundamental hydrological
variable that indicates soil water status and is linked with plant physiology. e growth of vegetation in alpine
Figure2. Anthropogenic interference at Dayara bugyal: (a) total cow unit of the area from 2007 to 2019, (b)
return of animals from the Dayara bugyal before upcoming winter season, (c) time series analysis of tourists’
inux in the Dayara (2015–2025), and (d) tourists’ inux and their camping in the Dayara before the restoration
period (2d-Photo credit: Mr.Santosh Saklani, Uttarakashi).
Table 2. Estimation of tourists’ carrying capacity for the Dayara Bugyal (A = Available area for tourists
use, Au = Area required per tourist, Rf = Daily open period / average time of visit, Cf 1 = Correction factor
1(rainfall), Cf2 = Correction factors 2 (snowfall), RCC = Real Carrying Capacity).
Total geographical
area (km2)Total geographical
area (m2) (I)
Ecologically
fragile area (m2)
(II) Available area
(m2) (I-II) Available area for
tourism (m2) (A) A/AU
(A/5) (A/AU)*Rf
(Rf = 2) Cf1 Cf2 RCC per year RCC per day
3.94 3,940,000 12,000 3,928,000
471,360 (12% of
available area) 94,272 188,544 0.59 0.72 80,093 219
589,200
(15% of available
area) 117,840 235,680 0.59 0.72 100,117 274
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regions is generally impeded by rigorous hydrothermal conditions and limitations in soil nutrient. Rise in nitro-
gen, total potassium, and total phosphorus was also examined in the GTZ comparing with the UTZ (Table4).
Socio-economic feasibility (SE). Socio-economic feasibility of the work was evaluated by village sur-
vey conducted in two adjacent villages within a periphery of the Dayara bugyal, Barsu (2258m) and Raithal
(2180m). e detailed outline of the respondents regarding the selected socioeconomic parameters are depicted
in Fig.5 (Supplementary TableS7, S8). Locally available materials like pine needles, bamboo and involving vil-
lagers as workers in view of generating local employment have not only resulted in reduction of cost by about
20% but also has generated direct and alternate livelihood opportunities for 700 households. During restoration
planning, Biodiversity Management Committees (BMCs) of nearest these two villages were involved for ensur-
ing sustainability in alpine and sub-alpine meadows and their downslope located villages. Regular meetings con-
ducted with the villagers since 2018 have shown that there is a signicant reduction in the number of unattended
cattle. Innovative techniques using biodegradable coir-geotextile, locally available pine needles and bamboo
have thus emerged out as an economical and sustainable alternative to treat degraded meadows and has resulted
in more eective regeneration of vegetation. Being labour intensive, this has not only generated livelihood alter-
natives to the local people but also has reduced the re incidences due to Pine forests in the lower altitude of the
district. Being technically simple, the treatment works were carried out by the villagers without any inherited
knowledge and experience according to Divisional Forest Ocer (DFO), Uttarkashi. e technique therefore
has emerged as one of the most suitable method of treatment of degraded alpine meadows in the Himalayan
region which was degraded more naturally due to gully erosion than anthropogenic pressures.
Index score. All individual variables of the rst two categories were indexed according to the dened scale
formulated on the basis of available literature and expert opinion (Table5). In case of the last category, scaling
was done directly by considering individual opinion for scoring information. e restoration evolution index
of the entire work was calculated as 69.31 (Supplementary TableS9). Among the three categories of the index,
changes governed by management measures (0.8) used in the work were found to be more eective than the envi-
ronmental changes (0.56). Ecosystem index scores were determined among references, degraded and restored
zones applying one way ANOVA analysis wherein two categories viz., direct management measure (M) and
Figure3. Soil erosion control techniques in the Dayara alpine pasture: (a) eroded gully side areas due to biotic
and abiotic factors in 2018, (b) restoration planning details in 2019, (c) eld implementation of the plan initiated
in 2019, and (d) implications of one year outcome of the restoration activity since 13th October, 2020.
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Table 3. Dominant herbs (density/m2) frequency (%) and abundance among comparison in Untreated
Undisturbed Zone (R), Geo-Coir Treated Zone (GTZ), and Untreated Degraded Zone (UTZ) of the Dayara
bugyal.
Name of plants Density (individual/m2) (mean) Frequency (%) Abundance
Untreated Undisturbed Zone (R)
Achillea millefolium L. 1.40 73.33 1.91
Allium humile Kunth 0.70 36.67 1.91
Anaphalis contorta (D. Don) Hook. f. 0.77 43.33 1.77
Anemone obtusiloba D. Don 1.47 70.00 2.10
Arctium lappa L. 0.40 26.67 1.50
Artemisia vestita Wall. ex Besser 1.13 63.33 1.79
Bistorta anis (D. Don) Greene 0.60 40.00 1.50
Cyananthus lobatus Wall. ex Royle 0.87 50.00 1.73
Danthonia cachemyriana Jaub. & Spach 1.70 90.00 1.89
Epilobium laxum Roy le 0.67 43.33 1.54
Geranium wallichianum D. Don ex Sweet 0.37 23.33 1.57
Kobresia nepalensis (Nees) Kk. 0.90 33.33 2.70
Morina longifolia Wall. ex DC. 0.43 23.33 1.86
Poa alpina L. 0.80 46.67 1.71
Potentilla argyrophylla Wall. ex Lehm. 0.80 46.67 1.71
Potentilla atrosanguinea G. Lodd. ex D. Don 1.13 63.33 1.79
Prunella vulgaris L. 1.27 53.33 2.38
Sibbaldia parviora Willd. 1.93 83.33 2.32
Tanacetum longifolium Wall. ex DC. 0.73 43.33 1.69
Taraxacum ocinale F.H. Wigg 1.23 53.33 2.31
Viola biora L. 0.47 36.67 1.27
Geo- Coir Treated Zone (GTZ)
Achillea millefolium L. 0.97 56.67 1.71
Allium humile Kunth 0.23 23.33 1.00
Anemone obtusiloba D. Don 0.50 40.00 1.25
Artemisia vestita Wall. ex Besser 0.93 53.33 1.75
Danthonia cachemyriana Jaub. & Spach 0.80 60.00 1.33
Epilobium laxum Roy le 0.60 46.67 1.29
Impatiens sulcata Wall. 0.30 23.33 1.29
Morina longifolia Wall. ex DC. 0.13 13.33 1.00
Poa alpina L. 0.43 30.00 1.44
Polygonum polystachyum Wall. ex Meisn. 0.50 36.67 1.36
Potentilla argyrophylla Wall. ex Lehm. 0.57 40.00 1.42
Potentilla atrosanguinea G. Lodd. ex D. Don 0.60 40.00 1.50
Prunella vulgaris L. 0.77 40.00 1.92
Senecio chrysanthemoides DC. 0.60 40.00 1.50
Sibbaldia parviora Willd. 1.23 73.33 1.68
Tanacetum longifolium Wall. ex DC. 0.27 20.00 1.33
Taraxacum ocinale F.H. Wigg 1.13 56.67 2.00
Untreated Degraded Zone (UTZ)
Achillea millefolium L. 0.43 30.00 1.44
Anemone obtusiloba D. Don 0.30 20.00 1.50
Artemisia vestita Wall. ex Besser 0.40 33.33 1.20
Danthonia cachemyriana Jaub. & Spach 0.63 33.33 1.90
Epilobium laxum Roy le 0.27 20.00 1.33
Potentilla argyrophylla Wall. ex Lehm. 0.40 23.33 1.71
Rumex nepalensis Spreng. 0.57 33.33 1.70
Taraxacum ocinale F.H. Wigg 0.40 30.00 1.33
Polygonum polystachyum Wall. ex Meisn. 0.30 23.33 1.29
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environmental desirability (E) were used. e average ecosystem index score for treated zones was 72% (± 3.78
standard error [SE]) which was signicantly higher than the average score of degraded zones 55.61% (± 4.79) but
lower than the average score of reference zones 88% (± 3.17) (one way ANOVA test, p = 0.003, Fig.6b). e high-
est variation was observed in a degraded zone (68%), followed by treated zone (42%) and reference zone (30%).
Now, considering the individual variables, the score of water holding capacity and soil pH of treated land were
found to be in most comfortable zone comparing with the non-degraded zone as a reference. Tourism activity
was not found to be responsible for the degradation as the scores were almost equal in reference and degraded
zones. From the hit map analysis of the variables, it was made clear that soil chemical properties like OC, N and
K were not found to be in good agreement in case of the treated land (Fig.6). Direct eld values of the variables
considered under ecological category were further evaluated in three respective zones by discriminate function
analysis. e results revealed two signicant functions, factor 1 accounted for 97% of the explained variance, and
factor 2 accounted for 2% of the explained variance. All individual variables of soil were found to be strongly
correlated across the three zones with little low values in case of P and K (Fig.7).
Discussion
e alpine pastures in the Himalaya provide a wide range of ecosystem services such as carbon sequestration,
water storage and provisioning, maintaining biodiversity, food security and livelihoods. But current days, these
ecological treasure houses are facing degradation threats like upcoming invasive species, inappropriate manage-
ment and development policies, soil erosion, extraction of medicinal plants, overgrazing and climate change23.
erefore, these areas require not only the protection of native vegetation but also its restoration wherever neces-
sary. Eco-restoration is an attractive strategy in this regard that will provide the ecological and socioeconomic
benets like expanding coverage and connectivity of the remaining native vegetation; increasing the ow of
ecosystem goods and services (e.g., water, food, biological control, pollination, grazing livestock products, timber
and non-timber forest products, climate regulation, control and mitigation of erosion and oods); and creation
of social and economic development opportunities for rural community24. On the other hand, implementing
eco-restoration is a challenging work for these regions. e outcomes of the present work, depicts a clear eco-
restoration and its evaluation framework for degraded high altitude alpine pastures of the Himalayan region. e
degradation parameters considered for the present work was found in harmony with other aected areas of the
Figure4. Colonization of Rumex nepalensis distributedin the Dayara bugyal.
Table 4. Chemical characteristics of the dierent soil zones (upto 30cm depth) from R, GTZ and UTZ in the
Dayara bugyal (n = 3 per investigation zone; 50 random soil cores per replicate for soil analysis ; 30 randomly
placed quadrates of 1 × 1m in 5-50m in triplicate per investigation zone). *(mean ± standard error).
Variables
Investigation zone
Untreated Un degraded zone (R) * Geo-coir Treated Zone (GTZ)* Untreated Degraded Zone (UTZ)*
Vegetation prole
Total herb density / m219.77 ± 0.04 10.56 ± 0.02 3.7 ± 0.05
Soil chemical prole
pH 5.15 ± 0.24 4.96 ± 0.28 4.69 ± 0.21
OC (%) 6.64 ± 0.26 4.83 ± 0.04 3.76 ± 0.14
N (%) 0.133 ± 0.01 0.09 ± 0.03 0.047 ± 0.02
P (%) 0.35 ± 0.04 0.29 ± 0.03 0.14 ± 0.01
K (%) 0.81 ± 0.02 0.78 ± 0.04 0.26 ± 0.02
WHC (%) 56.96 ± 0.13 49.85 ± 0.13 47.76 ± 0.59
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Himalayan Region. Like, overgrazing is reported for the areas of high altitude grasslands of Kashmir, Tungnath,
Garhwal in the Indian Himalaya, Sagarmatha (Mt. Everest) National Park, Nepal and China25–28, and other places
of the Himalaya. In case of the Dayara bugyal, local livestock populations were found to be increased at a rate of
33 CU per year and also evaluated to be more responsible for overgrazing. Migratory livestock unit was found
to be controlled aer the restoration phase. Overgrazing is strongly associated with soil cracking and vegetation
disturbance, important processes and features of degradation in alpine ecosystems29. Shiing of grazing land from
Dayara towards Lambidhar was an excellent management measure in this aspect, where more control measures
are needed. According to our calculations, if 445 CU will be deducted from the local livestock from Dayara,
grazing will be under carrying capacity. erefore, the grazing pattern of 118 migratory CU (76 horse/mule and
18 sheep/goat, already controlled) and 318 local CU (30 horse/mule and 187 sheep/goat, need to be controlled)
is recommended for the area. Rest of the animals may be shied to some other areas like Lambidhar, Devkund,
and Suriyatop. One check post for checking the livestock should be made in this regard.
Further, in alpine region, tourism is also reported to reect impacts like reduction in litter biomass, soil
nutrient supply and soil enzyme activities, generation of solid waste, thus adversely aect the whole plant-soil
system30. On the other hand, tourism sector is considered as growth engine for the future development of the
Indian Himalayan Region31. In Uttarakhand, due to lack of attentive strategies, and the existing policy framework,
incongruous practice of tourism, unplanned developmental activities, and the massive inow of visitors are
Figure5. Socio-economic responses by the local stakeholders regarding feasibility assessment criteria related to
the Dayara bugyal restoration.
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some of the key factors adversely aecting the sustainable tourism development32. e results of tourist carrying
capacity inow of 274 tourists per day for the area was also in compliance with Hon’ble High court, Uttarakhand
(WPPIL No.123 of 2014) where 200 tourists per day are allowed to visit on alike locations.
Tourism activity of the study area was found to be below carrying capacity and further eco-tourism may
be promoted in the area which will also have socioeconomic impact for the two adjacent villages. Promotion
of homestays for tourists, training of local people as tour guides and bird watching are suggested for the same.
Some base framework suggested for a community-based rural tourism development include activities followed
in Darap and Pastanga villages in Sikkim and Dhanolti Eco-park in Uttarakhand33,34. A village level committee
like Dayara Ecotourism Development Committee (DEDC) may be formed in the upcoming phases, consistingof
20 members (10 from Raithal, 10 from Barsu villages) representing50% women members. e main role of the
Figure6. Evaluation of dierent components under restoration evaluation index; (a) category comparison
between dierent zones, (b) ecosystem index score comparison between restore, reference and degraded zones,
(c) evaluation of individual variables for their eectiveness in dierent zones, and (d) ecological prole of
dierent zones (R_S = satisfactory for reference zone, R_A = average for reference zone, R_NS = not satisfactory
for reference zone, similarly T = treated zone, D = degraded zone).
Table 5. Scoring criteria for calculation of restoration evaluation index.
Satisfactory Average Not Satisfactory References
Soil chemical properties
pH 4.7–5.3 4–4.7 < 4.0
17, 18, 19
OC (%) > 7.5 5.0–7.5 < 5.0
N (%) > 0.75 0.50–0.75 < 0.50
P (%) > 0.50 0.25–0.50 < 0.25
K (%) > 2 2–1 < 1
Water holding capacity (%) 50–60 40–50 < 40
Vegetation index
Vegetation cover (%) > 60 30–60 < 30 Based on eld observation
Management measures
Grazing control < 285 285 -857 > 857 Based on eld observation, experts’ opinion and survey,
Order of Hon’ble High court, Uttarakhand (WPPIL No.123
of 2014 ), 21, 22
Tourists’ control < 65 65–200 > 200
Erosion control
(t h-1y-1) < 5 5–35 > 35
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committee will be to manage the tourists’ inux, conserve forest and ecosystem, dispose of and recycle garbage,
and collect fees for various amenities as provided to the tourists. A small nature interpretation and learning
centre may be also established in Barsu village, by engaging localities in Eco-huts. e role of the centre will be
conducting amusement facilities like ying fox and burma bridge, plantation of memory saplings, and nature
trails with yoga for the tourists. Localities may be made aware of the activities, by way of nature learning and
interpretation training provided by GBP-NIHE, Kosi-Katarmal, Almora, Uttarakhand, India. Further, practices
like packaging with less waste prone materials such as decomposable wrappers, establishment of a waste dealer
centre (Could one earn 25 paise per bottle upon submission, if sold to a dealer) are also adopted in the area for
the management of solid waste35.
Soil erosion of the area was found to be controlled at the rate of 0.5 tonne per hectare per year. e newly
introduced geo-coir matting approach was found to be successful in this aspect. e geo-coir matting technique
was successful for controlling soil erosion in the Amachal watershed in Trivandrum District in the Western Ghat
region of Kerala, India36. But its use in such a high-altitude alpine in the present work is rst time found to be
successful. Further, use of dry pine needles (Piruls) in the construction of cheek-dams was also found to be an
eective strategy as these are highly inammable because of presence of turpentine oil in them and cause hunting
forest re incidences in the north western Himalaya during summer37.
ereaer, environmental desirability in the treated area was found to have improved vegetation and soil
prole. e total herb density in per metre square of the treated area indicates good values. But colonization of
Rumex nepalensis was found in dierent places where anthropogenic disturbance was frequently found. is
species has good forage value, higher crude protein (CP) and digestibility for cattle. On the other hand, it has
become dominant and outcompete desirable pasture species and degrade pasture quality. It regenerates from
tap roots and establishes quickly as seedlings. Once established, tough tap roots become dicult to remove and
are not readily damaged by tillage38. erefore, manual removal of Rumex nepalensis at the shepherd camping
(30°50′3.48"N, 78°34′2.21"E to 30°50′0.49"N, 78°34′2.76"E, 3348m) is recommended to stop the future spread
of this dicult weed in the pasture area. Small plots of 10 m2 can be considered for this purpose stating from
the camping sites. Simultaneously, plantation activity should be done to stop the surface soil erosion. Herbs like
Trifolium repens, Carex setosa and Dolomiaea macrocephala are recommended for this purpose. In below ground,
water holding property of soiland soil nutrients were also found to increase in the treated area. Soil pH of the
treated area was also found to be undisturbed. Pine needles are a matter of concern as these were introduced in
the bugyal area during the restoration work. Soil ‘C’ and ‘N’ storage and other physiochemical components were
found to be increased in the treated zone comparing with the untreated zone. is will ultimately increase the
above ground biomass of the area39. Reduction of the grazing activity could be one of the reasons behind it. On
the other hand, during upcoming 10years, exclusion of the grazing activity may reduce the vegetation diversity
of the area and may allow the vegetation to be dominated by a few species with strong colonization abilities40.
e socio-economic parameters used in the present study was the eld implementation of the conceptual
framework designed by Pandit etal. (2020) for land degradation and restoration responses for improved planning
and decision-making considering 141 current articles in this context. Although the framework was for forest land
degradation assessment, but the parameters also strongly correlate with the pasture area of the current work. e
results of the present work revealed good success rate and popularity of the work among the localities as well as
in Government departments. Community involvement is a vital parameter behind the success of any work. Like
Community Forest User Groups in Nepal beneted nearly 2.908 million households by 2018 and also managed
total of 2.238 million ha of forests41. e ecological index of the treated zones was found to be increased in com-
parison with the degraded zone which indicated improving ecological prole of the area. Direct management
measures like control in grazing and tourism activity along with geo-textile matting and check dams for erosion
control are found to have more impact in this aspect.
Figure7. Discriminant function analysis of (a) direct eld evaluated values, and (b) their covariance matrix.
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erefore, the eco-restoration strategies and their evaluation model of the present work, could have its future
avenue for successful restoration practice. e planning of geo-coir mats and pirul check dams for the soil erosion
control may be further used for restoration of other high-altitude regions prone to erosion. e grazing pattern
and herbs colonization controlling strategies, tourism management strategies as suggested in the work are also
useful for other degraded pasture lands facing the same problem in high altitude degraded alpine pastures of the
Indian Himalayan Region as well as in other mountain alpine and sub-alpine ecosystems.
Methods
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 dened 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
(Table6).
Direct management measure (M) evaluation. During the starting phase of the work, excessive graz-
ing, uncontrolled tourism and continuous soil erosion were identied as major drivers behind the degradation
of Dayara bugyal. erefore, in the rst category of the evaluation work, direct management measures to control
the above-mentioned activities were analysed. e disturbances were controlled by managing both anthropo-
genic (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
◦
C till it reached at constant weight and then weighed in the laboratory. ereaer, density
of individual plant was measured by laying 30 quadrates of 1 × 1m randomly placed within 50 × 50m 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. ereaer, 10 dominant palatable species cover-
ing ~ 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
coecient.
Utilization rate 50% and conversion coecient 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 (7.5kg/day, Table7)*, D = Grazing days (May to September, 153days).
*One animal consumes 3% of its body weight as dry forage44. Animal unit conversion was done aer Rawat
(2020)45.
Tourists’ Carrying Capacity(TCC). e general formula of carrying capacity assessment for protected areas
was rst proposed by Cifuentes (1992), which was further applied in dierent elds46. e approach is to estab-
lish the capacity of an area for maximum visits based on existing physical, biological, and management condi-
tions through the physical carrying capacity (PCC), and real carrying capacity (RCC). TCC is divided into the
following levels:
Physical Carrying Capacity (PCC). e PCC is the maximum number of tourists that can physically accom-
modate into or onto a specic area, over a particular time. e PCC (Eq.5) may be estimated as follows:
(1)
Density
=
Total number of individuals of a species in all quadrates
Total number of quadrates laid
(2)
Y
=
Yp
×
A
(3)
F
=
n
i=1
Yi×Ui×C
i
(4)
Cc
=
F
I×D
(5)
PCC
=
A/Au
×
Rf
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where, PCC = physical carrying capacity; A = Available area for tourists use ; 15%-18% area of the total geo-
graphical 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 = 6h (according to the eld survey, tourists like timing for a day visit between 9 AM
to 3 PM), time required by one tourist to visit the Dayara bugyal = 3h.
Rf = 6h/3h = 2.
Real Carrying Capacity (RCC) (Eq.6)
Maximum permissible number of tourists to a specic site could be determined once the Correction fac-
tors (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 (> 250mm per day)
and snowfall (> 8cm per day) were considered as limiting variables that control tourism for the area. e calcula-
tions were done by analyzing the rainfall and snowfall data from 2017 to 2019 considering March to November
(6)
RCC
=
PCC
×
(Cf1
×
Cf2
×
Cf3
×
Cf4
×···
Cfn)
Cfx
=
1
−
Lmx /Tmx
Table 6. Response evaluation parameters.
Categories Sub- categories Individual variable
Direct management measure (M) M1: Anthropogenic (A) A1: Grazing
A2: Tourism
M2: Natural (B) B1: Soil erosion
Environmental desirability (E)
E1: Above ground (C) C1: Vegetation diversity
C2: Vegetation cover
E2: Below ground (D)
D1: E4: Soil pH
D2: Organic carbon (OC)
D3: Total Nitrogen (N)
D4: Total Phosphorus (P)
D5: Total Potassium (K)
D6: Water holding capacity
Socio-economic feasibility (SE)
SE1: Economic feasibility (E) E1: Cost-eectiveness
E2: Economic eciency
SE2: Social acceptability (F) F1: Procedural equity
F2: Social preference
SE3: Technical feasibility (G)
G1: Adoption lag
G2: Replicability of the response
G3: Technical sophistication
SE4: Cultural acceptability (H) H1: Cultural values
H2: Social norms
SE5: Political feasibility (I) I1: Policy/legislation
I2: Governance mechanism
Table 7. Animal unit and forage requirement.
Animals Avg. body weight (kg) Forage requirement (dry matter in kg/day) Animal Unit
Adult milking cow 250 7.5 1
Horse / mule 312.5 9.38 1.18
Goat 35.78 1.07 0.23
Sheep 32.74 0.98 0.22
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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 909days (Tmx)
and in 369 heavy rainfall occurred, therefore, Cf1 was 0.59 (1—Lmx/Tmx). Similarly, during this time heavy
snowfall occurred for 51days out of 186days, and Cf2 was 0.72.
Measurement of soil erosion control. Eco-friendly bio-degradable coir geo-textile (9000 sq m) pur-
chased 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. e open degraded
sites in dierent 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.
Aer one year of the treatment, total mass of debris stored by each check dams was evaluated using core density
method. e core density of bulk soil in each check dam was determined in triplicates, using an iron core of
2.5cm radius and 30cm height. e mass of draining soil checked by each check dam was calculated as under48:
where, Md = e 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 ecologi-
cal outputs of the work were considered under this category, as habitat enhancement is the most crucial compo-
nent of the activity. e 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 × 1m inside 9 sample plots of 5-50m along three dierent
zones of the treated water channel areas using vertical belt transact method49. e zones were: (i) geo-coir treated
area, (ii)untreated degraded area, (iii)reference untreated non-degraded area along withboth sides of the water
channels whereintotal vegetationdensity (Eq.1) was analysedfollowing the methodology of Misra (1968) and
Mueller-Dombois & Ellenberg (1974)50,51.
Soil sampling. Soil samples (30cm 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. Aer collection, the
soil samples were preserved in a portable storage box and transported to the lab immediately. Aer 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. e SOC content in soil was determined by wet oxidation method using
K2Cr2O752. e 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 buer solutions of pH
7.0 and 9.253. e 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 (2232m)
and Raithal (2258m). Participants had to indicate the degree of the work in above mentioned three scales
(M, E and SE). e questionnaire comprising of questions covered perception about the above discussed six
categories (Supplementary S10). Total 60 respondents from dierent households were randomly selected from
each village. e sample consisted of villagers as well as administrative sta. e informants were randomly
chosen across 3 dierent age groups, 20–40, 40–60 and > 60 year58. Economic feasibility was the rst class and
parameters considered under this category included cost-eectiveness of the material used, economic eciency,
i.e., benet–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 consid-
ered, where existing policy/legislation and governance mechanism (clarity on roles/responsibilities of stakehold-
Md
=
V
×
ρb
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ers) was analysed. Each restoration response is ranked using a relative eectiveness or performance rating scale
of low (L), moderate (M), or high (H). ese eectiveness response ratings for each sub-criterion also reect 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 rst
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 rst two categories,
i.e., direct management measure (M), environmental desirability (E), and direct eld values were considered.
e last category, socio-economic feasibility was indexed depending on village questionnaire survey. e sec-
ond 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 dierences
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 desir-
ability (E). To estimate the most aected variable between references, degraded and restored sites, discriminant
function analysis (DFA) was carried out, using the eld values of all measured independent variables under
second category.
Data availability
Initially, the digital elevation model data used in the study area map which is available in ALOS PALSAR – Radio-
metric Terrain Correction section of NASA earth science data (https:// search. a sf. alaska. ed u/). e shape le data
used for Uttarakhand map is available at DIVA-GIS (http:// www. diva- gis. org/). Datasets used from dierent
climatic analysis are available at CRU (https:// sites. uea. ac. uk/ cru/ data). All other data are available either in the
main text or as supplementary materials. Nomenclatures of the plants were validated from the book, ‘Flora of
Gangotri National Park, Western Himalaya’, Botanical Survey of India60.
Received: 23 March 2021; Accepted: 26 July 2021
Figure8. Detailed outline of the scoring process applied for restoration evaluation index calculation for the
Dayara bugyal.
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References
1. Trant, A., Higgs, E. & Starzomski, B. M. A century of high elevation ecosystem change in the Canadian Rocky Mountains. Sci. Rep.
10, 9698. https:// doi. org/ 10. 1038/ s41598- 020- 66277-2 (2020).
2. Kricsfalusy, V. etal. Biodiversity Restoration of the Treeline in Mountain Ecosystems: A Case Study in the East Carpathians (within
the Ukraine). 16th International Conference, Society for Ecological Restoration at Victoria, Canadain, 1–2. https:// www. resea rchga
te. net/ publi cation/ 25772 1339 (2004).
3. Mohandass, D. Biodiversity recovery and sustainable land management of a montane rain forest (shola) ecosystem of the Upper
Nilgiri Hills Sout India, Edhkwehlynawd Botanical Refuge, Technical Report. 1–49. https:// doi. org/ 10. 13140/ RG.2. 1. 2828. 7208
(2008).
4. Kumar, R. Rehabilitation of degraded mountain forests with an integrated eco restoration model- A case study of the Attappady
Hills, Kerala, India. SARRC For. J. https:// www. resea rchga te. net/ publi cation/ 28720 0083 (2015).
5. Bamboo for land restoration, International Bamboo and Rattan Organization (INBAR), Policy Synthesis Report, Headquarters
Beijing, China, New report. https:// www. inbar. int/ bambo oforl andre stora tion (2018).
6. Torresani, L., Wu, J., Masin, R., Penasa, M. & Tarolli, P. Estimating soil degradation in montane grasslands of North-eastern Italian
Alps (Italy). Heliyon 5, 1825. https:// doi. org/ 10. 1016/j. heliy on. 2019. e01825 (2019).
7. Kosmas, C. et al. Exploring long-term impact of grazing management on land degradation in the socio-ecological system of
Asteroussia Mountains, Greece. Land 4, 541–559. https:// doi. org/ 10. 3390/ land4 030541 (2015).
8. Chalise, D., Kumar, L. & Kristiansen, P. Land degradation by soil erosion in Nepal: A review. Soil Syst. 3, 12. https:// doi. org/ 10.
3390/ soils ystem s3010 012 (2019).
9. Restoration Opportunities Assessment Methodology (ROAM). International Union for Conservation of Nature (IUCN), Head-
quarters, Rue Mauverney 28, CH-1196 Gland, Switzerland. https:// www. iucn. org (2016).
10. Gann, G. et al. International principles and standards for the practice of ecological restoration. Restor. Ecol. 27, 1–46. https:// doi.
org/ 10. 1111/ rec. 13035 (2019).
11. G.B. Pant National Institute of Himalayan Environment. Assessing Landscape Restoration Opportunities for Uttarakhand, India.
International Union for Conservation of Nature (IUCN), 1–108. https:// www. iucn. org (2018).
12. Bhatt, I. D., Negi, V. S. & Rawal, R. S. Promoting Nature-Based Solution rough Restoration of Degraded Landscapes in the
Indian Himalayan Region. in Nature-based Solutions for Resilient Ecosystems and Societies. Disaster Resilience and Green Growth,
197–211. https:// doi. org/ 10. 1007/ 978- 981- 15- 4712-6_ 12 (2020).
13. Orr, B. J. & Cowie, A. L. Scientic conceptual framework for land degradation neutrality: a report of the science-policy interface.
United Nations Convention to Combat Desertication, (UNCCD) Publications, 1–105, https:// www. unccd. int (2017).
14. Mc Donald, T., Gann, G. D., Jonson, J. & Dixon, K. W. International standards for the practice of ecological restoration – including
principles and key concepts, 1–48. http:// www. SER. org (Society for Ecological Restoration, Washington, D.C., 2016).
15. Singh, G., Rai, I. D. & Rawat, G. S. Alpine meadows of Uttarkashi, Plant Species Diversity, Grazing Pressure and Conservation Status
(2012).
16. Anonymous, Ecorestoration of Dayara alpine meadow in Uttarakashi, Namami Gange Newsletter, National Mission on clean Ganga
under Ministry of Jal Shakti, 24–25. https:// nmcg. nic. in/ Newsl etter/ sept2 020/ index. html (2020).
17. Saha, S., Rajwar, G. S. & Kumar, M. Soil properties along altitudinal gradient in Himalayan temperate forest of Garhwal region.
Acta Ecol. Sin. 38, 1–8. https:// doi. org/ 10. 1016/j. chnaes. 2017. 02. 003 (2018).
18. Rawat, G. S. Alpine vegetation of the western Himalaya: species diversity, community structure, dynamics and aspects of conserva-
tion. esis Doctor of Science in Botany, 1–239. https:// doi. org/ 10. 13140/2. 1. 3230. 1765 (2008).
19. Poulenard, J. & Podwojewski, P. Encyclopedia of Soil Science. Ch. Alpine Soils, 75–79. https:// doi. org/ 10. 1081/e- ess3 (Taylor &
Francis, 2006).
20. Kaur, R., Joshi, V. & Joshi, S. P. Impact of degradation on biodiversity status and management of an alpine meadow within Govind
Wildlife Sanctuary and National Park, Uttarkashi, India. Int. J. Biodivers. Sci. Ecosyst. Serv. Manag. 6, 146–156. https:// doi. org/ 10.
1080/ 21513 732. 2011. 568972 (2010).
21. Hon’ble High Court Uttarakhand, WPPIL No.123 of 2014, Aali-Bedini Bagzi Bugyal Sanrakshan Samiti vs. State of Uttarakhand,
1–60, https:// india nkano on. org (2018).
22. Mandal, D. & Sharda, V. N. Appraisal of soil erosion risk in the eastern Himalayan region of India for soil conservation planning:
Soil erosion risk in the eastern Himalayan region of india. Land Degrad. Dev. 4, 430–437. https:// doi. org/ 10. 1002/ ldr. 1139 (2013).
23. Ingty, T. Pastoralism in the highest peaks: Role of the traditional grazing systems in maintaining biodiversity and ecosystem func-
tion in the alpine Himalaya. PLoS ONE 1, 1–19. https:// doi. org/ 10. 1371/ journ al. pone. 02452 21 (2011).
24. Bustamante, M. M. C. et al. Ecological restoration as a strategy for mitigating and adapting to climate change: Lessons and chal-
lenges from Brazil. Mitigat. Adapt. Strateg. Glob. Chang. 24, 1249–1270. https:// doi. org/ 10. 1007/ s11027- 018- 9837-5 (2019).
25. Khan, R. W. A., Shaheen, H., Mehmood, A. & Awan, S. N. Grazing intensity impacts on soil carbon stocks of Western Himalayan
Alpine paddocks. Carbon Manag. 10, 533–540. https:// doi. org/ 10. 1080/ 17583 004. 2019. 16677 01 (2019).
26. Nautiyal, M. C., Nautiyal, B. P. & Prakash, V. Eect of grazing and climatic changes on alpine vegetation of Tungnath, Garhwal
Himalaya, India. Environmentalist 24, 125–134. https:// doi. org/ 10. 1007/ s10669- 004- 4803-z (2004).
27. Byers, A. Contemporary Human Impacts on Alpine Ecosystems in the Sagarmatha (Mt Everest) National Park, Khumbu, Nepal.
. Ann. Assoc. Am. Geogr. 95, 112–140. https:// doi. org/ 10. 1111/j. 1467- 8306. 2005. 00452.x (2005).
28. Cao, J.,Yeh, E. T., Holden, N. M., Qin, Y., & Ren, Z. e roles of overgrazing, climate change and policy as drivers of degradation
of China’s Grasslands. Nomadic Peoples 17, 82–101. https:// doi. org/ 10. 3167/ np. 2013. 170207 (2013).
29. Vu, Q. M., Le, Q. B., Frossard, E. & Vlek, P. L. G. Socio-economic and biophysical determinants of land degradation in Vietnam:
An integrated causal analysis at the national level. Land Use Policy 36, 605–617. https:// doi. org/ 10. 1016/j. landu sepol. 2013. 10. 012
(2014).
30. Niu, Y. et al. Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau.
Land Degrad. Dev. 30, 1243–1257 (2019).
31. Gaur, V. S, & Kotru, R. Sustainable tourism in the Indian Himalayan region. Report of working group II. 1–87. https:// www. niti.
gov. in (NITI Aayog, Government of India, 2019).
32. Chandra, P. & Kumar, J. Strategies for developing sustainable tourism business in the Indian Himalayan Region: Insights from
Uttarakhand, the Northern Himalayan State of India. J. Destin. Mark. Manag. 19, 100546. https:// doi. org/ 10. 1016/j. jdmm. 2020.
100546 (2021).
33. Prakash Kala, C. Ecotourism and Sustainable Development of Mountain Communities: A Study of Dhanolti Ecopark in Uttara-
khand State of India. AEES 1, 98–103 (2013).
34. Chaudhary, M. & Lama, R. Community Based Tourism Development in Sikkim of India-A Study of Darap and Pastanga Villages.
Transnational Corporations Review 6, 228–237. https:// doi. org/ 10. 5148/ tncr. 2014. 6302 (2014).
35. Kuniyal, J. C., Jain, A. P. & Shannigrahi, A. S. Solid waste management in Indian Himalayan tourists’ treks: A case study in and
around the Valley of Flowers and Hemkund Sahib. Waste Manag. 23, 807–816. https:// doi. org/ 10. 1016/ S0956- 053X(03) 00027-8
(2003).
36. Vishnudas, S., Savenije, H. H. G., Van der Zaag, P., Anil, K. R. & Balan, K. e protective and attractive covering of a vegetated
embankment using coir geotextiles. Hydrol. Earth Syst. Sci. 10, 565–574. https:// doi. org/ 10. 5194/ hess- 10- 565- 2006 (2006).
Content courtesy of Springer Nature, terms of use apply. Rights reserved
Vol.:(0123456789)
Scientic Reports | (2021) 11:16547 |
www.nature.com/scientificreports/
37. Sengar, A. et al. Prioritization of barriers to energy generation using pine needles to mitigate climate change: Evidence from India.
J. Clean. Prod. https:// doi. org/ 10. 1016/j. jclep ro. 2020. 123840 (2020).
38. Pan, T. et al. Inuence of degradation on soil water availability in an alpine swamp meadow on the eastern edge of the Tibetan
Plateau. Sci. Total Environ. 722, 137677. https:// doi. org/ 10. 1016/j. scito tenv. 2020. 137677 (2020).
39. Hu, Z. et al. A synthesis of the eect of grazing exclusion on carbon dynamics in grasslands in China. Glob. Chang. Biol. 22,
1385–1393. https:// doi. org/ 10. 1111/ gcb. 13133(2016).
40. Li, W., Liu, Y., Wang, J., Shi, S. & Cao, W. Six years of grazing exclusion is the optimum duration in the alpine meadow-steppe of
the north-eastern Qinghai-Tibetan Plateau. Sci. Rep. 8, 17269. https:// doi. org/ 10. 1038/ s41598- 018- 35273-y (2018).
41. Pandit, R. et al. A framework to evaluate land degradation and restoration responses for improved planning and decision-making.
Ecosyst. People 16, 1–18. https:// doi. org/ 10. 1080/ 26395 916. 2019. 16977 56 (2020).
42. Negi, G. C. S., Rikhari, H. C. & Singh, S. P. Plant Regrowth Following Selective Horse and Sheep Grazing and Clipping in an Indian
Central Himalayan Alpine Meadow. Arct. Alp. Res. 25, 211–215. https:// doi. org/ 10. 1080/ 00040 851. 1993. 12003 007 (1993).
43. Cheng, D. et al. e Rangeland Livestock Carrying Capacity and Stocking Rate in the Kailash Sacred Landscape in China. J. Resour.
Ecol. 8, 551–558. https:// doi. org/ 10. 5814/j. issn. 1674- 764x. 2017. 06. 001 (2017).
44. Hocking, D. & Mattick, A. Dynamic Carrying Capacity Analysis As Tool for Conceptualising and Planning Range Management
Improvements, with A Case Study From India.1–28. https:// www. odi. org (Overseas Development Institute, 1993).
45. Rawat, A. S. Forest Management in Kumaon Himalaya: Struggle of the Marginalised People. Indus Publishing, 1–291. https:// www.
cabdi rect. org (1999).
46. Sari, C. P. & Rahayu, S. Carrying capacity of Gancik Hill top for ecotourism development in Boyolali district. E3S Web Conf. 73,
02008. https:// doi. org/ 10. 1051/ e3sco nf/ 20187 302008 (2018).
47. Urban and Regional development plan formation and implementation (URDPFI) Guidelines IIA-IIB, Appendices to URDPFI
guidelines, Ministry of Urban Development, Govt. of India, 1–153. http:// mohua. gov. in (2015).
48. Gong, X. L. et al. Characteristics of a debris ow disaster and its mitigation counter measures in Zechawa Gully, Jiuzhaigou Valley,
China. Water 12, 1256. https:// doi. org/ 10. 3390/ w1205 1256 (2020).
49. Pradhan, B. K. & Badola, H. K. Swertia chirayta, a reatened High-Value Medicinal Herb: Microhabitats and Conservation Chal-
lenges in Sikkim Himalaya, India. Mt Res Dev35, 374–381. https:// doi. org/ 10. 1659/ MRD- JOURN AL-D- 14- 00034.1 (2015).
50. Misra, R. Ecology Work Book, 1–238. https:// www. scirp. org (Oxford and IBH Publishing Co., Calcutta, 1968).
51. Mueller D. D. & Ellenberg, H. Aims and Methods of Vegetation Ecology, 1–22, https:// www. scirp. org (Wiley and Sons, New York,
1974).
52. Nelson, D. W. & Sommers, L. E. Total carbon, organic carbon, and organic matter. In Methods of Soil Analysis, Part 2-Chemical
and Microbiological Properties (Eds Page, A.L. et al.) 539–577. www. sciep ub. com/ refer ence/ 116039 (ASA-SSSA, Madison, 1982).
53. Richards, L. A. (eds) Diagnosis and improvement of saline and alkali soils. in Soil and Water Conservation Research Branch Agri-
cultural Research Service, Washington, DC, USA 1–166. https:// scien ce. scien cemag. org (1954).
54. Viji, R. & Rajesh, P. P. Assessment of water holding capacity of major soil series of Lalgudi, Trichy, India. J. Environ. Res. Dev. 7,
393–398. https:// jerad. org (2012)
55. Okalebo J. R., Gathua K. W. & Woomer P. L. Laboratory methods of soil and plant analysis: A working manual, 2nd ed. 1–31.
https:// www. resea rchga te. net (Tropical Soil Biology and Fertility Institute of the International Centre for Tropical Agriculture,
Nairobi, Kenya, 2002).
56. Kisand, A. Distribution of sediment phosphorus fractions in hypertrophic strongly stratied Lake Verevi. in Lake Verevi, Estonia - A
Highly Stratied Hypertrophic Lake, vol 182 (eds Ott, I. & Koiv, T.) 33–39. https:// doi. org/ 10. 1007/1- 4020- 4363-5_3 (Developments
in Hydrobiology, Springer, Dordrecht, 2005).
57. Hanway, J. J. & Heidel, H. Soil analysis methods as used in the iowa state college soil testing laboratory. Iowa State College of
Agriculture Bulletin, vol 57, 1–31. www. sciep ub. com/ refer ence/ 279466 (1952).
58. Joshi, B. Ch., Rawal, R. S., Chandra S. K. & Pandey, A. Quantitative ethnobotanical assessment of woody species in a representative
watershed of west Himalaya, India. Energ. Ecol. Environ. 4, 56–64. https:// doi. org/ 10. 1007/ s40974- 019- 00114-9 (2019).
59. Staszak, L. A. & Armitage, A. R. Evaluating Salt Marsh Restoration Success with an Index of Ecosystem Integrity. J. Coast. Res.
287, 410–418. https:// doi. org/ 10. 2112/ JCOAS TRES-D- 12- 00075.1 (2013).
60. Pusalkar, P. K. & Singh, D. K. Flora of Gangotri National Park, Western Himalaya, India, 1–708. (Botanical Survey of India, Kolkata,
2012).
Acknowledgements
e authors heartily thank to the Director, G.B. Pant National Institute of Himalayan Environment, Kosi-Katar-
mal, Almora, Uttarakhand, India-for providing facilities in the Institute which could make the present work
possible.Financial assistance provided by UNDP is highly acknowledged. State Forest Department, Govt. of
Uttarakhand, Dehradun is acknowledged for helping during the eld survey.We are also thankful to Dr. G.C.S.
Negi, Scientist-G, GBP-NIHE, Kosi-Katarmal, Almora, India and Dr. Suheel Ahmad, Scientist, ICAR-Indian
Grassland and Fodder Research Institute, Temperate Regional Research Station, Srinagar, Jammu & Kashmir,
India for their scientic suggestions during the work.
Author contributions
J.C.K. formulated the manuscript, critically reviewed it and nalised the entire manuscript; P.M. designed the
restoration evaluation framework and wrote the dra manuscript, S.K. helped in providing information regard-
ing eld implementation. Field data collection was done by A.K., N.B., P.M., S.R. and J.C.K. Phytosociological
and soil analysis were done by K.C.S. and S.R., respectively. S.C.A. helped in collecting information regarding
restoration planning and statistical analysis was done by M.N.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 021- 95472-y.
Correspondence and requests for materials should be addressed to J.C.K.orP.M.
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