INDICATOR CODE: Forest Plantation
SIMPLIFIED NAME OF INDICATOR: Areas in ha of State Forest(SF) land brought under plantation
TYPE OF INDICATOR: Output
INDICATOR DESCRIPTION: Areas in ha of SF land brought under plantation. This will help to increase forest cover which in turn will sequester carbon and carbon stock enhancement in face of climate change
RATIONALE FOR INDICATOR:
Plantation forestry is planting of trees or plants in barren, eroded, degraded, and logged government forest lands or in registered private or institutional lands to increase the production capacity by planting suitable species to fulfill increasing local and industrial demands; biodiversity conservation, carbon sequestration, protection of soil, water catchment and environment conservation.
With current developmental trend, peoples’ demand for forest produce is escalating over the years exerting huge pressure on the forest and the environment. The Department has over the years worked towards maintaining a balance between its conservation efforts without undermining peoples’ demand for forest produce.
This is where Plantation forestry comes in. It also plays a vital role in maintaining a minimum of 60 % forest cover for all times to come as mandated by the Constitution of Bhutan, especially at a time when the country is developing at a rapid phase.
Recognizing the vital role plantation program plays, the program has also been given great weightage in the 11th FYP with a target of about 24858 hacteres, which counts to about 400 ha annually.
Through this program, areas such as land slide prone areas, degraded and barren forest lands brought under plantations will enhance forest product and ecosystem services and further contribute to rural livelihood through employment opportunities.
INDICATOR HISTORICAL TRENDS AND FUTURE PROJECTIONS:
Historical and Projected Trends for Forest Plantation Areas in Ha
|
Historical Performance Achievement (before start-of 11th FYP)
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Future projection for 11th FYP
|
Fiscal year
|
1946-2013
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2013 - 14
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2014 -15
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2015-16
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2016-17
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2017-18
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Actual achieved
DoFPS records
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22858
|
23258
|
23658
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24058
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24458
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24858
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Fiscal year target
|
|
400
|
400
|
400
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400
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400
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Note : The targets set are cumulative of all types of plantation including in Community Forest, Lease Land and SF
ANALYSIS OF INDICATOR BEHAVIOUR: The history of recorded forest plantation dates back to 1947 long before the establishment of the Forest Department in 1952. The first recorded plantation was carried out by civil authority at Gelephu under Sarpang Dzongkhag. Since then, Plantation has come a long way totaling to about 22858 hacteres of plantation recorded in 2013.
From the total of 22858 ha plantation carried out so far most of the plantations are recorded in southern Bhutan which has been undertaken under the project aimed at greening the southern belt in late 1970s. On an average 350 ha plantations have been carried out annually till 2013.
Currently, planted forests have success immensely in recouping the logged and barren forest areas in Bhutan. Thinning from plantation forests has also contributed to meet timber demand; mainly poles size timber requirement.
OTHER RELATED INDICATORS:
-
Area in acres of plantation carried out.
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Number of plantations carried out in Dzongkhag, Territorial Forest Division, NRDCL and Public Corporation Agencies.
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Percentage of forest cover increased
INSTITUTION RESPONSIBLE FOR INDICATOR OVERSIGHT:
Social Forestry and Extension Division, Department of Forests and Park Services, Ministry of Agriculture and Forests, Thimphu, Bhutan
KEY PERSON RESPONSIBLE FOR INDICATOR MANAGEMENT:
Gyeltshen Drukpa, Chief Forestry Officer, Social Forestry and Extension Division, Department of Forests and Park Services, Ministry of Agriculture & Forests
Phone: +975 2 323138; Fax: +975 328394
E-mail: gyeltshendrukpa@gmail.com
METHODOLOGY FOR INDICATOR MANAGEMENT:
Stage in Data Management
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Description
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Data type selection (what is data to be collected and its level of aggregation)
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Primary datum needed for this indicator is areas in hectares of plantation carried out. This indicator can also be expressed in terms of acres of plantation.
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Data sources (what is the collection instrument)
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Plantation data is collected using GPS, which is mainly used for identifying the boundaries and calculating areas. Data are maintained at Dzongkhag, Division and NRDCL offices that are periodically sent to SFED for nationwide compilation in prescribed format form.
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Data collection (who is responsible for collecting)
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Dzongkhag, Territorial Division and NRDCL offices are responsible for collecting plantation data, which are then sent to SFED for record
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Data processing (who carries out data entry and data processing and how)
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Plantation data are collected by Dzongkhag, Division and NRDCL. Data entry and compilation are done in prescribed format by respective implementing agencies as no processing is required.
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Data presentation (how)
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Currently the data is stored in temporary excel database format.
The data stored and validated at SFED is sent to the Forest Information Management Section (FIMS), DoFPS. The data are then maintained in the Forest Information Database (FID) and used for publishing annual forestry statistics and other technical reports which is used for policy formulations.
However, the FID still need to be upgraded and once proper database system is developed within the ministry, the plantation record will be used to work out carbon stock in planted forests.
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Data reporting (by whom to whom)
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On completion of data compilation in SFED, data will be reported annually to the Ministry through FIMS, Department of Forests and Park Services for reference and record.
Compiled data can be given to other agencies to serve as statistical information for reference and record and copy to the funding agencies for the plantation carried through donors funding agencies.
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Inputs required for data management (when and by whom)
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The most important input required is to have enough incentives for the field offices to carry out plantations in terms of fund for Travel and Daily allowance. Basic infrastructures like computers and printers are also required to maintain record of plantations.
Funds are require to support Travel and Daily Allowances being paid to the SFED staff, vehicles expenses to monitor and verify the plantation data submitted by the implementing agencies like Dzongkhag, Division and NRDCL.
A reliable and upgraded database and storage facilities is required in SFED and the Department to store the compiled plantation data And for further processing.
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Cost of verification
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Data verification may be needed if the information submitted by the agencies (NRDCL, Dzongkhag Forestry Sector and Divisions) deviates from the technical sanction approved by DoFPS. However the additional cost is not required beside travel allowance and vehicle expenses.
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Data quality and risk assessment (who and how)
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SFED not only initiate funding source for the plantations and CF development for the implementing agencies, but also render technical support for plantation. Timely monitoring and assessing of plantation data collected are verified and examined for correct data quality and accuracy. The survival percentages of each plantation area examined annually to assure success of the plantations. Further the compiled plantation records are crosschecked by SFED for reliable and accurate information to avoid compromising the quality of data.
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ANY SUPPLEMENTARY INFORMATION:
On compilation of plantation data, these data will be used to work for the calculation of carbon stock available in the planted forests.
To help forest the degraded land and to maintain existing plantation, adequate fund is required. Apart from the usual RGoB funding, additional funds will be seeked frorn reliable funding agencies like UNFCCC and REDD+. The funds secured shall prove of great help to achieve the Departments mandate and also to continue maintaining the constitutional mandate of atleast 60 % forest cover for all times to come
INDICATOR CODE: Watershed Assessment &Planning
SIMPLIFIED NAME OF INDICATOR: No. of Watershed assessed and Management plans for degraded/critical watershed within major river basins developed & implemented (Punatsangchhu, Wangchhu, Mangdechhu & Kurichhu)
TYPE OF INDICATOR: Output
INDICATOR DESCRIPTION: No. of watershed assessment carried out and management
plans for selected watersheds developed for undertaking interventions to address watershed related issues given adverse impacts if climate change on water resources.
RATIONALE FOR INDICATOR:
Well managed watersheds play a pivotal role in supplying a wide range of goods and services both on-site and downstream. They are the basis for sustainable agricultural, forestry and pastoral pursuits, sustaining biodiversity and for providing other environmental benefits as well as water for local and downstream use. Sound watershed management also aids in mitigating potential disaster risks, such as landslides and flash flooding.
The production of hydro-power for local use and export, contributes about 24% to Bhutan's GDP and this is expected to rise further with the planned construction of more hydro-plants, making electricity generation the single biggest contributor to the economy. Consequently, a reliable supply of good quality water is the most valuable commercial product derived from watersheds. Therefore, the maintenance and improvement of the country's watersheds is a high management priority, not only for hydro-power, but also for domestic use, irrigation and disaster mitigation.
This program will work towards maintaining environmentally and economically healthy watersheds.
Sustainable management and rehabilitation of degraded watersheds has been an implicit and explicit part of various policy frameworks in Bhutan for many years, and watershed management appears in most of the country’s policy documents. The Department of Forests and Park Services (DoFPS) has the primary responsibility for planning and coordination of Watershed Management, although responsibilities for specific land management aspects are spread across many agencies.
The implementation of the program shall pursue a two-pronged approach that will distinguish activities to be carried out on their own at a strategic level; and those activities that must be integrated, incorporated and harmonized into the implementation plans of other area-based development, conservation and management programs within and outside the Ministry. These include the regular development plans of the Dzongkhags and Geogs as well as the land-use specific planning frameworks such as those that apply to FMUs, PAs, CFs.
INDICATOR HISTORICAL TRENDS AND FUTURE PROJECTIONS:
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Historical performance achievement (before start of 11 FYP
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Projections for indicators (targets) under 11 FYP
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Fiscal Year
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2011
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2012
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2013-14
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2014-15
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2015-16
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2016-17
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2017-18
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Targets related to 11 FYP
|
|
71
|
79
|
87
|
95
|
103
|
111
|
ANALYSIS OF INDICATOR BEHAVIOUR:
Before the creation of the Watershed Management Division in 2009, the watershed-related program was managed by one of the sections under the Social Forestry Division of DoFPS. Under this arrangement, one of the achievements was successful completion Wang Chhu Watershed ManagementPlan. The then EU-funded Wang Watershed Management Project, various integrated activities were implemented in the Wang watersheds. Although the importance of watershed management was recognized at that time, noticeable progress could not be made due to a lack of capacity and dedicated division.
However after creation of a separate division (the Watershed Management Division), which has primary mandates to carry out watershed assessment and develop watershed plans amongst others, tremendous progress has been made. The Watershed Management Division has, for practical implementation purposes, delineated all the watersheds across the country using a threshold of 5000 ha (50 km2) and has assigned unique identify numbers for each of these. Based on the above delineation, there are 186 watersheds in Bhutan. During the 10th FYP, two major river basins (Wang Chhu and Punatsang Chhu) comprising 71 watersheds were assessedand identified 2 critical/degraded watershed each from 2 major basins. The division also published Road Map for Watershed Management in Bhutan, 2011 which guide watershed management and planning in the country.
OTHER RELATED INDICATORS:
-
Areas (in hectares) covered by watershed assessment activities
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No. of geogs or villages within the watershed area where watershed assessment activities are implemented
INSTITUTION RESPONSIBLE FOR INDICATOR OVERSIGHT:
Watershed Management Division (WMD) under the Department of Forests and Park Services (DoFPS), Ministry of Agriculture and Forests (MoAF)
KEY PERSON RESPONSIBLE FOR INDICATOR MANAGEMENT:
The Chief Forestry Officer, Watershed Management Division, Department of Forests and Park Services, Ministry of Agriculture & Forests
Phone: +975 2 323568
E-mail: pemaparop@gmail.com
METHODOLOGY FOR INDICATOR MANAGEMENT:
Stage in Data Management
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Description
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Data type selection (what is the data to be collected and its level of aggregation)
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Primary data needed for this indicator is the number of watersheds for which assessment has been completed. This indicator can also be expressed in terms of area in hectares for which watershed assessments have been carried out.
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Data sources
(what is the collection instrument)
|
Watershed assessments are undertaken using the approved Watershed Classification Guideline which classifies each tributaries into 3 categories (Pristine, Normal and degraded/critical) according to 22 criteria. For each assessed watershed, hard copies of the assessment forms are retained on file and the raw data is stored in an Excel spreadsheet. Maps showing the number of watersheds in a particular river basin are also stored on file.
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Data collection
(who is responsible for collecting the data)
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Under the coordination of the WMD, the GIS officer is entrusted with the responsibility of keeping records (both in hard & soft copy format) of all assessed watersheds.
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Data processing
(who carries out data entry & data processing and how)
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The data collected for each watershed is compiled according to the criteria used during the assessment process.
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Data presentation (how is the data presented)
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Once the relevant data is compiled, each watershed is classified as either Pristine, Normal or Degraded/Critical.
The watershed assessed by the concerned extension agents in the geogs are verified by the technical team from WMD in collaboration with other relevant division of DoFPS.
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Data reporting (by whom to whom)
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On completion of the river basin classification, the results are presented to all relevant stakeholders at Dzongkhag and Geog level. As for the degraded/critical watersheds, results are presented right down to the Chiwog level for subsequent planning and implementation of watershed activities. Initially watershed assessment has to be done using the criteria from the guideline for classification of watersheds. A team from WMD assess the watershed in collaboration with the RNR extension officers and at the same time using the GPS for the mapping. In addition to the scoring of the criteria, flow discharge is also measured using the velocity-area method.
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Cost of verification
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As WMD is the coordinating office for watershed classification in all major river basins and developing river basin management plans, frequent field monitoring and technical supervisory being carried out by the division to ensure watershed activities are incorporated into geog and dzongkhag plans and accordingly implemented. Thus, till date there was no additional cost involved for verification as the cost was internalized in forms of normal TADA being paid to officials from WMD. However, in future for monitoring and technical backstopping of watershed program in the country, an additional cost will be involved for transport and officials travel allowance.
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Data quality and risk assessment (who and how)
|
The rapid classification of watersheds was done using the guideline for classification of watershed. The forms for classification of watersheds were filled-in after visual assessment of the given watershed using transect-walks. Most of the criteria were filled-in using “expert judgment” and mostly mean figures were used (for example, steepness of the slope, distance of human activities from the stream, presence of mass movements, etc). In order to remove/minimize personal bias in scoring of the criteria and to be able to compare the conditions of the watersheds at different point of time, normalization of the scores of each criterion was done using the standard normalization equation:
|
|
Normalization of score = a + (X-A) (b-a) / (B-A) (1)
Where a = minimum value of the new data set = 0
b = maximum value of the new data set = 100
X = value to be normalized
A = minimum value of the original data set
B = maximum value of the original data set
Substituting the values of a and b in equation (1), equation (1) becomes:
Normalization of score = (X-A) x 100 (2)
(B-A)
Using equation (2), all the scores for each criterion were normalized. The normalized scores of the criteria used were added up and divided by the number of criteria used to get the mean normalized score of each sub-watershed. The mean normalized score determines the class of watershed as follows: critical (≤ 33%); normal (34-66%); and pristine (≥ 67%) as per the guideline.
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|
The discharges of the streams were determined using the Velocity-area method. This method requires determining the average velocity of the stream and cross-sectional area of the stream. The average velocities of the streams were determined using various floaters (orange buds, plastic bottles filled with water; pieces of wood). A suitable, straight reach with a minimum amount of turbulence was chosen, and an interval selected, measured and marked on the bank at each end by pegs, or rocks. Ideally, the marks should be far enough apart to allow a travel time of at least 20 seconds but in reality, such suitable stretch were difficult to find. The interval should also overlap one or more surveyed cross sections to determine the cross-sectional area. The discharges of the streams are taken once when the assessment is done.
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Score %
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Class of watershed
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≤ 33
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Critical Watershed - Need Immediate Actions
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33 – 66
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Normal – Need Periodical Monitoring
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≥ 67
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Pristine - No Action Required
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Inputs required for data management (when and by whom)
|
Initially watershed assessment has to be done using the criteria from the guideline for classification of watersheds. A team from WMD assess the watershed in collaboration with the RNR extension officers and at the same time using the GPS for the mapping. In addition to the scoring of the criteria, flow discharge is also measured using the velocity-area method.
|
ANY SUPPLEMENTARY INFORMATION:
Undertaking watershed assessment and classification has been a challenging task given the lack of expertise (eg; hydrologist)besides challenges posed by difficult and unforgiving geographical terrain. Once the assessment and classification of river basins are completed with its management plans, assured funds for implementation of programs would be vital to maintain the healthy watersheds for sustainable water use for drinking, irrigation and hydro power etc. and same time enhance livelihood of the communities living within the watershed. Watershed Management is also a sound approach in disaster risk mitigation (mainly landslides and local floods).
INDICATOR CODE: CCA-VT-5
SIMPLIFIED NAME OF INDICATOR: Area covered by National Forest Inventory
TYPE OF INDICATOR: Output
INDICATOR DESCRIPTION:
Areas in km2 for which National Forest Inventory (NFI) data collection is completed in Bhutan
RATIONALE FOR INDICATOR:
While forests are one of the largest terrestrial sinks of carbon, they are also one of the sources (from deforestation and forest degradation) of CO2, which is a significant cause of global warming and climate change. This statement underpins the role of forests in climate change mitigation and adaptation vis-à-vis the impacts of climate change on forests are so intricately intertwined. Forests, therefore, are important components in strategies for adapting to climate change. The National Forest Inventory (NFI) was due to be completed during the 10th FYP; however, it will now be completed by end of the 11th FYP. The RNR-CCAP is funding the NFI in four target Dzongkhags; it is one of the activities being supported within the framework of the Global Climate Change Alliance (GCCA) support to Bhutan.
The NFI is one of the most important forest programmes, not only from the climate change perspective, but it is important for its contribution to formulation and framing of policy and legislation which will contribute towards sustainable management of forest resources in the country. Therefore, NFI is a prioritized activity in the 11th Five Year Plan, especially as it is only through NFI that the required baseline data on forest resources can be generated and established.
NFI data provide the baseline figures for forest resources such as: (i) type, extent and quality of forest ecosystems, (ii) number of trees per hectare, (iii) volume and basal area per hectare, (iv) canopy cover, (v) pests and diseases affecting forest health and vitality. The data will provide information on carbon sequestration (total carbon stored within Bhutan’s forests). The NFI will generate data on biodiversity, ecological disturbances (incidences of forest fires, human disturbances, and wildlife data).
Climate change models can be developed to assess the resilience of forest ecosystems to climate change and its impact using NFI data. In order to carry out the modelling, the DOFPS will need support in the form of technical assistance, capacity building, and funding to carry out this work. RNR-CCAP and FAO could form a partnership to carry out this work.
INDICATOR HISTORICAL TRENDS AND FUTURE PROJECTIONS:
|
Historical Performance Achievement
(Before start-up of RNR-CCAP)
|
Projections for indicator (targets)
With RNR-CCAP support
|
Projections for indicator (targets) under remainder of 11th FYP but currently outside RNR-CCAP funding
|
Calendar Year +
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2008
|
2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
|
2018
|
RNR-CCAP Year
|
|
|
|
|
T
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T+1
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T+2
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T+3
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T+4
|
|
|
Targets related to 11th FYP++
|
|
|
|
|
0
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8448
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18896*
|
25680**
|
38394
|
38394
|
38394
|
Actual achieved
|
|
|
|
|
0
|
|
|
|
|
|
|
+ CY is the year for which performance data are collected for budget release eligibility in July of the following year; in the case of process indicators under RNR-CCAP performance may be delayed as late as June
++ Targets are cumulative and relate to total area in km2 covered by NFI (Including those in the four target RNR-CCAP Dzongkhags). There are 16 Cluster Plots per km2 surveyed under NFI.
T is baseline year
T+1 is first year with a budget release in July
* Performance achievement used to trigger release of 25% of Variable Tranche for FY 2015-16
** Performance achievement used to trigger release of 20% of Variable Tranche for FY 2016-17
ANALYSIS OF INDICATOR BEHAVIOUR:
The first field based forest inventory in Bhutan was carried out back in 1976-81 and was called the Pre-Investment Survey (PIS). Available forest resource data are therefore more than 30 years old. The objective of the PIS was limited to timber resource assessment, and the data from PIS were not available in a digital format. Data from that time are in the form of published reports and are not easy to use for further analysis.
However, a number of remote sensing exercises such as Land Use Planning Project (LUPP, 1995), Land Cover Mapping Project (LCMP, 2010) have been carried out after PIS, but no field based exercise has been carried out so far. Therefore, the current NFI will be the first field-based exercise after PIS to assess forest resources in Bhutan. Unlike PIS, the current NFI is more comprehensive and it will generate and establish most of the baseline data required for comprehensive forest and biodiversity resource management.
NFI has completed a total of 528 cluster plots covering 8448 km2 by end 2013. The remaining areas (cluster plots) will be completed within the 11th FYP period. Currently there are committed funds for 8 Dzongkhags (4 from EU GCCA supported RNR-CCAP, 2 from BTFEC, and 2 from EU-RNRSP), the target is set a:;
-
10448 km2 (653 CPs) to be completed by end 2014
-
6784 km2 (424 CPs) to be completed by end 2015
However, the remaining 13104 km2 (819 CPs) will be completed by end 2016, if further funding becomes available.
OTHER RELATED INDICATORS:
Areas in Km2 for which NFI data collection is completed
Number of Cluster Plots for which NFI data collection is completed
Number of Dzongkhags for which NFI data collection is completed
Number of Gewogs for which NFI data collection is completed
Number of Dzongkhags with carbon stock assessment
Number of Dzongkhags with ecosystem resilience assessments for climate change
INSTITUTION RESPONSIBLE FOR INDICATOR OVERSIGHT:
Policy and Planning Division, Ministry of Agriculture and Forests, Thimphu, Bhutan
KEY PERSON RESPONSIBLE FOR INDICATOR MANAGEMENT:
Kinley Tshering, Chief Forestry Officer, Forest Resources Management Division, Department of Forests and Park Services, Ministry of Agriculture & Forests
Phone: +975 2 327723; 324653; 330016
E-mail: kinleytshering@gmail.com
METHODOLOGY FOR INDICATOR MANAGEMENT:
Stage in Data Management
|
Description
|
Data type selection (what is data to be collected and its level of aggregation)
|
Primary datum needed for this indicator is areas in km2 for which NFI data collection is completed. This indicator can also be expressed in terms of number of cluster plots.
|
Data sources (what is the collection instrument)
|
The NFI data from cluster plots are being collected using state of the art technology called Trimble Juno SC Global Positioning System (GPS), which the 12 NFI crews comprising 5 forestry personnel are provided with. These 60 foresters visit 2424 cluster plots laid on a 4 km x 4 km grid to collect data. The data parameters being collected range from tree related data such as height, diameter at breast height, crown cover; to wildlife and other biodiversity related data including ecological disturbances.
|
Data collection (who is responsible for collecting)
|
Under the coordination of FRMD, 12 NFI crews are entrusted with the responsibility for collecting NFI data from cluster plots.
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Data processing (who carries out data entry and data processing and how)
|
The data collected by NFI crew using GPS are transferred to laptop computers at the end of the day. The data collected in the GPS comes in .SSF format files. These data are then transferred to FRMD at the end of completion of fieldwork for the assigned plots. Currently, given lack of a proper database system capable of storing, processing and analysing large amounts of NFI data, the raw data are being stored in Excel databases, which is a temporary database. Very soon the database system will be developed and all the NFI data will be migrated to a proper centralised database system.
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Data presentation (how)
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Currently the data is stored in temporary Excel database format. Once the proper database system is developed, it will be capable of generating most of the data related to forest resources such as growing stock, volume per hectare, number of trees per hectare and also biodiversity related data besides ecological disturbances data.
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Data reporting (by whom to whom)
|
Should we get the required funds, the targeted time frame for completion of NFI fieldwork is December 2015. Once fieldwork is completed, the results of the NFI will be published and reports of NFI will be submitted by the DOFPS to the National Government. Currently, as support for NFI field work come in smaller funding packages from several donor agencies (BTFEC, EU), semi-annual and /or annual progress reports are being submitted to donors by the implementing agency (FRMD, DoFPS) on the progress of the works.
|
Inputs required for data management (when and by whom)
|
Given that NFI is in the field enumeration phase wherein the NFI crew are sent into the field to collect data from 2424 cluster plots, the inputs required are mostly in the form of funds to support Travel and Daily Allowances being paid to the crew and the payments for labourers and vehicles being hired while conducting field works. Expenditure is also incurred for other miscellaneous but complementary activities such as meetings with stakeholders like local government officials (given that the support of local government is critical for the success of NFI fieldwork) and printing of the maps, etc.
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Cost of verification
|
As FRMD is the coordinating office for NFI, frequent monitoring and supervision is being carried out by NFI Coordinators and this forms an integral part of the verification process. Thus, till date there was no additional cost involved for verification as the cost was internalized in forms of normal TADA being paid to officials from FRMD. However, very soon a Quality Assurance and Quality Control (QA/QC) team will be formed to cross check and verify the data being collected by NFI crew, for which an additional cost will be involved.
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Data quality and risk assessment (who and how)
|
There are different layers of quality control measure adopted for NFI. Firstly, the use of Trimble Juno SC GPS itself is one of the means to ensure quality data. Besides its capability to collect and store data, it also collects time and date of data collection and the location (coordinates) of particular places. Therefore, the crews have no room to submit fake data and/or data from a wrong place without visiting sample plots. Secondly, within the data collection form (uploaded in GPS), certain mandatory conditions are included (such as plot numbers) without which the field crew cannot close the data form or move to the next data collection process. Such arrangements ensure that data collection is comprehensive.
Most importantly, as indicated above, very soon a QA/QC team will be formed that will visit some of the plots for which data collection is completed to re-collect the data, which will be cross-checked and verified against data collected by NFI crews. This arrangement will ensure that the data collected is of the required quality besides providing variance of NFI data, which is very important from the statistical standpoint.
Finally, field crews submit the data to the FRMD, where further comprehensive quality assurance measures, such as cleaning, verification, and correction of coordinates will take place.
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ANY SUPPLEMENTARY INFORMATION:
Once completed, the NFI will not only establish baseline forest resource data, it will also benefit Bhutan in terms of fulfilment and/or verifying a number of international commitments that Bhutan has, such as Carbon Neutrality commitment made at the 15th Conference of Parties (COP-15) of UNFCCC.
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