JURISDICTIONAL SUB- NATIONAL REDD+ PROGRAM FOR DISTRICT OF STATE,

Prepared by Madhya Pradesh Forest Department Under the USAID-funded Partnership for Land Use Science (Forest-PLUS) Program

October 2017 Version 1.3 Jurisdictional REDD+ Project | (Madhya Pradesh)

Table of Contents

List of Figures ...... ii List of Tables ...... iii Abbreviations ...... v 1.0 Introduction ...... 1 1.1 Background and Overview ...... 1 1.2 Overview of REDD+ Project ...... 4 2.0 Scope of the Project ...... 6 2.1 Geographical Scope ...... 6 2.2 Carbon Pools ...... 16 2.3 Baseline Sources and Project Sources of GHG ...... 17 3.0 Forest Reference Emissions Levels ...... 19 3.1 Introduction ...... 19 3.2 LULC Changes over the Historical Reference Period ...... 26 4.0 Drivers of Forest Change ...... 32 4.1 Introduction ...... 32 4.2 Agents and Drivers of Deforestation and Forest Degradation ...... 32 4.3 Pre-project Scenario ...... 37 4.4 Methodology ...... 38 4.6 Questionnaire Preparation ...... 38 4.7 Assessment of Drivers of Deforestation and Degradation ...... 42 4.8 Carbon Loss from Forests ...... 45 4.9 Validation of Results ...... 46 5.0 Driver-Intervention Matrix ...... 47 5.1 Introduction ...... 47 5.2 Interventions to Decrease Emissions from Forests ...... 47 6.0 Quantification of Emission Reductions ...... 69 6.1 Introduction ...... 69 6.2 Historical Reference Periods ...... 69 6.3 Baseline and Project Scenario ...... 71 6.4 Net Emissions Reductions ...... 72 7.0 Implementation Strategy and Monitoring Plan ...... 73

i Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

7.1 Introduction ...... 73 7.2 Implementation strategy ...... 74 8.0 REDD+ Safeguards and Benefit-Sharing Mechanism ...... 101 8.1 National REDD+ Safeguard Policy ...... 101 8.2 Compliance with Laws ...... 102 8.3 Safeguards Information System ...... 105 8.4 Benefit-Sharing Mechanism ...... 118 9.0 Other Project Details ...... 127 9.1 Start Date and Crediting Period ...... 127 9.2 Details of Project Design ...... 127 9.3 Activities and Consultations in the Program ...... 127

List of Figures Figure 1: Location of Hoshangabad District ...... 2 Figure 2: Hoshangabad District Map...... 3 Figure 3: Range Map, Hoshangabad ...... 8 Figure 4: Hydrogeological Map of Hoshangabad District ...... 11 Figure 5: Village Map of Hoshangabad District ...... 14 Figure 6: Detailed methodology for analysis of satellite imagery ...... 22 Figure 8: Canopy density map of Hoshangabad District, 2008 ...... 22 Figure 9: Canopy density map of Hoshangabad District, 2013 ...... 23 Figure 10: Land use land cover map of Hoshangabad District, 2005...... 24 Figure 11: Land use land cover map of Hoshangabad District, 2008...... 24 Figure 12: Land use land cover map of Hoshangabad District, 2013...... 25 Figure 13: Compartment boundary map of Hoshangabad District ...... 26 Figure 14: Territorial Range Map of Hoshangabad ...... 29 Figure 15: Forest Type Map of Hoshangabad, 2005 ...... 29 Figure 16: Forest Type Map of Hoshangabad, 2008 ...... 30 Figure 17: Forest Type Map of Hoshangabad, 2013 ...... 30 Figure 18: Forest Strata and Canopy Density Map of Hoshangabad (2005, 2008, 2013) ...... 31 Figure 19: Spatial Representation of Fodder Extraction in MP Landscape Study Villages (FRI Study) ...... 33 Figure 20: Spatial Representation of Grazing Intensity in MP Landscape Study Villages (FRI Study) ...... 33 Figure 21: Spatial Representation of Fuelwood Extraction in MP Landscape Study Villages (FRI study) ... 34 Figure 22: Spatial Representation of Livestock Population in MP Landscape Study Villages (FRI Study) .. 34 Figure 23: Spatial Representation of Human Populations in MP Landscape Study Villages (FRI Study) .... 35 Figure 24: Spatial Representation of Fire Intensity in MP Landscape Study Villages (FRI Study) ...... 35 Figure 25: Collective Impact of Forest Degradation and Deforestation Drivers in Madhya Pradesh Forest- PLUS Landscape (FRI study) ...... 36

ii Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 26: Deforestation and Degradation Map of Hoshangabad, 2005-2013 ...... 37 Figure 27: Steps for Assessing Degradation and Deforestation Drivers in Hoshangabad ...... 38 Figure 28: Agave plantation ...... 53 Figure 30: Implementation Structure for the Program...... 75 Figure 31: Monitoring Structure of the Program ...... 76

List of Tables Table 1: General Administrative Characteristics of Hoshangabad ...... 3 Table 2: State Missions, Policies, and Notification in force in Madhya Pradesh ...... 4 Table 3: Soil Profile of Hoshangabad ...... 6 Table 4: Temperatures and Potential Evapo-Transpiration ...... 7 Table 5: Reserved and Protected Forests Blocks of the Hoshangabad Division (2013-14)...... 8 Table 6: Sub Divisions, Ranges, Range Head Quarters, Sub Ranges, and Beats under the Hoshangabad Division (2013–2014) ...... 8 Table 7: Status of Forest Cover in Hoshangabad in 2015 (in sq km) ...... 10 Table 8: Different Categories of Forest Area in the Hoshangabad Division (2013–2014) ...... 10 Table 9: Forest Resource Survey to Determine the Age, Girth-Class, Density Wise Composition of Crop in the Division (2013–2014) ...... 10 Table 10: MP and Hoshangabad Demographic Details ...... 13 Table 11: Social Classification in Hoshangabad District ...... 14 Table 12: Livestock Details, Hoshangabad ...... 15 Table 13: Land-Use Pattern, Hoshangabad ...... 15 Table 14: Forestry Linked Statistics of Hoshangabad District ...... 16 Table 15: Carbon Pools Considered for Jurisdictional Baseline ...... 16 Table 16: Characteristics of the Satellite Imagery Used ...... 20 Table 17: Land Use Pattern in Hoshangabad District ...... 27 Table 18: Table: Classification of Land and Forests in Hoshangabad over the Reference Period ...... 27 Table 19: List of Planned and Unplanned Drivers of Deforestation and Forest Degradation ...... 32 Table 20: Major Drivers of Deforestation and Forest Degradation ...... 37 Table 21: Status of Forest Cover in Hoshangabad in 2015 (Km2) ...... 37 Table 22: List of Villages Where FGDs Were Carried Out ...... 39 Table 23: List of Villages and Households Surveyed ...... 39 Table 24: Types of Forest Product Collected by Households for Various Purposes ...... 41 Table 25: Fuelwood Extraction Pattern by Source ...... 42 Table 26: Quantification of Fuelwood Extracted from Forests ...... 43 Table 27: Fodder Collection by Source ...... 43 Table 28: Amount of Fodder Extracted in Hoshangabad ...... 43 Table 29: Grazing Sources and Pattern ...... 43 Table 30: Small Timber Extraction Pattern by Source ...... 44 Table 31: Amount of Small Timber Collected ...... 44 Table 32: Amount of Small Timber Collected ...... 44

iii Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 33: Large TIMBER QUANTIFICATION ...... 44 Table 34: Quantification of NTFP Collection ...... 45 Table 35: Consumption and Share of Products Collected from Forests ...... 45 Table 36: Estimated Carbon Loss in Hoshangabad Due to Collection of Fuelwood, Fodder, Small, and Large Timber ...... 46 Table 37: Organic Matter content in Above Ground (AGL) and Below Ground (BG) Biomass ...... 70 Table 38: Emissions Reductions from the REDD+ Project...... 72 Table 39: Summary of the Monitoring Plan ...... 74 Table 40: Steering Committee of the Project ...... 75 Table 41: Parameters to Be Measured Toward Annual Monitoring ...... 77 Table 42: Features of Benefit-Sharing Mechanisms and Their Importance ...... 119

iv Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Abbreviations AFOLU Agriculture, Forestry, and Other Land Use AGB Above Ground Biomass AGD Aboveground Dead AGL Aboveground Live ALM Agricultural Land Management ANR Assisted Natural Regeneration ARR Afforestation Reforestation and Revegetation BEF Biomass Expansion Factor BG Belowground BGB Below Ground Biomass CBD Convention on Biological Diversity CDM Clean Development Mechanism CF Carbon Fraction CFE Cookstove and Fuel Efficiency CGWB Central Ground Water Board CITES Convention on International Trade in Endangered Species of Wild Fauna and Flora COP Conference of the Parties CP-AB Carbon Pool in Trees CPT Cattle-Proof Trench CS Class or Forest Stratum DBH Diameter at Breast Height DDF Dry Deciduous Forest Df Deforestation Dg Forest Degradation DTMRB Densified Total Mixed Ration Block EDC Eco-Development Committee EE Executing Entity EF Emission Factor FAO Food and Agriculture Organization of the United Nations FDA Forest Development Agency FGD Focal Group Discussion Forest-PLUS Partnership for Land Use Science (Forest-PLUS) Program FRA Forest Rights Act

v Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

FRI Forest Research Institute of India GHG Greenhouse Gas GIS Geographic Information System GoI GPS Global Positioning System GWP Global Warming Potential Ha Hectare Ham Hectare-meter HCV High Conservation Value HH Household HoFF Head of Forest Force HRD Human Resources Department ICS Improved Cook Stoves ILO International Labor Organization IPCC Intergovernmental Panel on Climate Change IT Information Technology IUCN International Union for Conservation of Nature JFM Joint Forest Management JFMC Joint Forest Management Committee JICA Japanese International Cooperation Agency LISS Linear Imaging Self-Scanning System LPG Liquified Petroleum Gas LULC Land Use Land Cover MDDF Mix Dry Deciduous Forest MFP Minor Forest Produce MGNREGA Mahatma Gandhi National Rural Employment Guarantee Act MNRE Ministry of New and Renewable Energy MoEFCC Ministry of Environment, Forests and Climate Change MoM Minutes of the Meeting MP Madhya Pradesh MPDAH Madhya Pradesh Department of Animal Husbandry MPFD Madhya Pradesh Forest Department MPSDMA Madhya Pradesh State Disaster Management Authority MSL Mean Sea Level NAP National Afforestation Policy

vi Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

NBMMP National Biogas and Manure Management Programme NGO Nongovernmental Organization NIR Near Infrared NRSC National Remote Sensing Centre NTFP Non-Timber Forest Product OBC Other Backward Category PA Project Area PAF Protected Area (Forests) PCCF Principal Chief Conservator of Forests PCR Physical Cultural Resource PDD Project Design Document PLR Policy, Law, and Regulation PMKSY Pradhan Mantri Krishi Sinchayee Yojana PRA Participatory Rural Appraisal PRDD Panchayat and Rural Development Department QA/QC Quality Assurance RE Renewable Energy REDD+ Reducing Emissions from Deforestation and Forest Degradation RF Reserve Forest RS Remote Sensing SAPCC State Action Plan on Climate Change SBSTA Subsidiary Body of Scientific and Technological Advice SC Scheduled Castes SDG Sustainable Development Goal SFD State Forest Department SHG Self-Help Group SIS Safeguard Information System SMART Spatial Monitoring and Reporting Tool SOC Soil Organic Carbon SOM Soil Organic Matter SOP Standard Operating Procedure ST Scheduled Tribes SWIR Shortwave Infrared TCO2e Metric Tons of Carbon Dioxide Equivalents UNFCCC United Nations Framework Convention on Climate Change

vii Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

USAID United Stated Agency for International Development USGS United States Geological Society VFC Village Forest Committee VM Verified Methodology

viii Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

1.0 Introduction 1.1 Background and Overview Forests cover one-third of the earth’s total land surface1 and play a major role in the carbon cycle by acting as carbon sinks and a major carbon source. The conversion of forestland into other land use categories result in greenhouse gas (GHG) emissions into the atmosphere. Apart from causing ecological damage resulting in the negative effects on the provision of ecosystem services, deforestation and forest degradation also have negative social impacts, ranging from livelihood to cultural aspects of forest fringe communities. The critical role forests play is highlighted by the fact that they contribute toward both climate change mitigation and adaptation efforts. Reducing Emissions from Deforestation and Forest Degradation (REDD+) is an international instrument developed under the United Nations Framework Convention on Climate Change (UNFCCC) to combat climate change by mitigating emissions from forestry sector. The REDD+ approach has been explicitly recognized under Article 5 of the Paris Agreement in 2015 at the 21st Conference of Parties (COP) to the UNFCCC, which calls all member parties to initiate, implement, and support activities related to the five-pronged approach under the REDD+ mechanism: 1. Reducing emissions from deforestation; 2. Reducing emissions from forest degradation; 3. Conserving forest stock; 4. Enhancing forest stock; and 5. Conducting Sustainable Forest Management.2 India ratified the COP21 Paris Agreement on 02/10/2016.3 The State of Madhya Pradesh (MP) has a total area of 94,689 km2. Forests cover about 31 percent of this area. MP is a pioneer in making forestry people-oriented with 15,228 Joint Forest Management Committees (JFMCs) involved in protection and management of about 70 percent of the forest area. People are the real dwellers and the real caretakers of the forests and, thus, are made stakeholders of the dividends of this field. However, the forests of MP have been steadily degrading due to multiple man-made drivers, leading to environmental uncertainties. Hoshangabad district, home to the important Satpura Forest Reserve, is vulnerable to the ill effects of climate change and consequences of man-made drivers of deforestation and forest degradation. The proposed REDD+ project is initiated to mitigate impacts of climate change through actions that will reduce emissions from forests and encourage more carbon sequestration in forests. The entire district of Hoshangabad will be considered as a jurisdiction for this purpose. The project design was developed after field activities, interactions, consultations, and validation exercises in the District, and is detailed in this Project Design Document (PDD).

1 FAO Forestry Paper 163. (2010). Global Forest Resources Assessment 2010 - Main report. Rome: Food and Agriculture Organization of the United Nations. 2 United Nations Framework Convention on Climate Change: Twenty-first Session of the Conference of the Parties (2015); Adoption of the Paris Agreement. 3 United Nations Framework Convention on Climate Change. (2016). Paris Agreement - Status of Ratification. Retrieved from UNFCCC: http://unfccc.int/paris_agreement/items/9444.php

1 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

1.1.1 About Hoshangabad Hoshangabad District of MP has a geographical area of 6,703 km² (670,300 ha). It is also home to , a hill station and popular tourist spot in the in the southern part of the district. The Pachmarhi Sanctuary (461.37 km²) is part of the larger Pachmarhi Biosphere Reserve, which extends into Betul and districts. The district is bounded by the districts of Raisen to the north, to the east, Chhindwara to the southeast, Betul to the south, to the west, and to the northwest. In 1998, the western portion of Hoshangabad District was carved off to create . Hoshangabad district lies in the valley; the River forms the northern boundary of the district. The is a tributary of the Narmada, rising in the Satpura Range to the south and flowing north to meet the Narmada at the village of Bandra Bhan. The lies in the south-central region of the district. Figure 1: Location of Hoshangabad District

The geographical boundary of Hoshangabad Jurisdiction is similar to the official administrative boundaries of Hoshangabad district (Figure 2).

2 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 2: Hoshangabad District Map

Location: Hoshangabad District lies in the central Narmada Valley and on the northern fringe of the Satpura Plateau, between the latitudes 21°53” and 22° 59” N and longitudes 76° 49” and 78° 44” E. In shape, it is an irregular strip elongated along the southern banks of Narmada River. Its greatest length from southeast to northeast is 160 km. An overview of the Hoshangabad’s demographic characteristics is given in Error! Reference source not found.. Table 1: General Administrative Characteristics of Hoshangabad Attributes Value Geographical Area 6,703 km2 Developmental Blocks 7 Developmental Blocks: Bankhedi, Pipariya, , Babai, Hoshangabad, Kesla, Seoni Number of Tehsils and Name 8 Tehsils: Babai, Bankhedi, Hoshangabad, , Pipariya, , Sohagpur, Dolaria Number of Villages 961 Population (Census 2011) Total: 1,241,350, Males: 648,725, Female: 571,774 Percentage Urban Population: 31.42% Average Population Density per km2 185

3 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

1.1.2 Forests in Hoshangabad The total forest area of Hoshangabad Forest Division is 112,965.15 ha. About half of this is hilly and lies in the Satpura mountain ranges. The division has 17 forest ranges and total area of these ranges is 364,733.45 ha. These forest enclaves provide habitat to several at-risk and endangered species, including the Bengal tiger (Panthera tigris), gaur (Bos gaurus), dhole (Cuon alpinus), sloth bear (Melursus ursinus), Chousingha (Tetracerus quadricornis), and blackbuck (Antilope cervicapra). While most of the Satpura range was originally heavily forested; the area has been subject to gradual deforestation in recent decades (significant stands of forests remain). Although the amount of forest cover of the Hoshangabad district has increased slightly over the past decade, the quality of forest is degrading, resulting in increase in open forest area. The over- exploitation of natural resources in the context of an ever-growing population resulted in land degradation, vegetation loss, and pollution, among other problems. 1.2 Overview of REDD+ Project 1.2.1 Objective MP has the largest forest cover in India.4 Further, about 10 percent of world’s tiger population is in Madhya Pradesh (leading to MP being known as “Tiger State”). The Government of MP has taken several steps to protect, conserve, and to improve forest cover through its policies. The following table gives a glimpse of such polices. Table 2: State Missions, Policies, and Notification in force in Madhya Pradesh Title Objective Madhya Pradesh State The main objective of the state policy is to strengthen the forces and systems Forest Policy 20055 for the protection and management of forests and ensuring stability of the environment and ecological balance by developing government forests and private areas under forest cover through sustainable management of forests. The Wild Life This act provides protection to wildlife of MP with strict rules and regulations. (Protection) Act, 19726 This will also ensure ecological and environmental security of the state. State Action Plan on The MP SAPCC seeks to formulate strategies towards combating the impacts Climate Change of climatic changes on forests and wildlife, among other sectors, while (SAPCC)7 simultaneously strengthening existing policies and legislations concerned with the sustainable use of forest resources for development in the state. Participatory Forest State government issued a resolution in 1991 on communities’ involvement in Management forest management and development of forest resources. MP has been a pioneer in making forestry people-oriented with 15,228 JFMCs involved in protection and management of about 70 percent of the forest area8.

The proposed project is an agriculture, forestry, and land use (AFOLU) project under the REDD+ category initiated to mitigate changes in climate change through actions that will reduce emissions from forests and encourage more carbon sequestration in forests. The project aims to establish a Jurisdictional REDD+ project, with the entire district of Hoshangabad as the jurisdictional area.

4 Madhya Pradesh Forest Department. (2005). Madhya Pradesh State Forest Policy. Madhya Pradesh Forest Department. 5 Madhya Pradesh Forest Department. (2005). Madhya Pradesh State Forest Policy 2005. Retrieved from MP Forest: http://mfp.mpforest.org/eco/pdf/forestpolicy.pdf 6 Madhya Pradesh Forest Department. (n.d.). The Wild Life (Protection) Act, 1972. Retrieved from Madhya Pradesh Forest Department: http://mpforest.gov.in/img/files/WildLife_Act.pdf 7 Housing and Environment Department, Govt. of Madhya Pradesh. (2014). Madhya Pradesh State Action Plan on Climate Change. Housing and Environment Department, Govt. of Madhya Pradesh. 8 Government of Madhya Pradesh. (n.d.). Forest. Retrieved from Government of Madhya Pradesh: http://www.mp.gov.in/en/web/guest/forest;jsessionid=5CC4D12EB0ED40BE5F2799860E5D0F94.worker1

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The Madhya Pradesh Forest Department (MPFD) would be the project proponent for this project. The project seeks to meet three objectives:  Mitigate carbon emissions by reducing deforestation and forest degradation, and by reducing the pressure on forests that are already degraded and avoid further deforestation in the project area;  Contribute to biodiversity conservation including high conservation-value species; and  Strengthen community building and contribute toward livelihoods generation of communities residing in forest fringe areas. The project seeks to meet these objectives through following activities with strategic alliances with the stakeholders:  Better management of natural resources involving communities;  Foster strategic alliances with all stakeholders;  Improve market linkages; and  Capacity building programs to forest department personnel and communities. An analysis of the socio-economic study conducted in Hoshangabad District revealed that the major drivers causing deforestation and forest degradation in the district are fuelwood extraction, grazing, non-timber forest product (NTFP) extraction, encroachment, and forest fires. To minimize the impacts of the drivers of deforestation, intervention activities have been shortlisted after a multi-tiered stakeholder consultation in the district. 1.2.2 Project Executing Entity The State Forest Department of Madhya Pradesh, Government of Madhya Pradesh, is the project Executing Entity (EE). The coordination of local administrative bodies (Gram Panchayats, JFMCs, Eco-Development Committees [EDCs], and Village Forest Protection Committees) will be sought at every stage with due stakeholder consultations, along with nongovernmental organizations (NGOs) and academics. Executing Entity Information: Organization name State Forest Department, Madhya Pradesh Contact person Mr. Animesh Shukla, IFS Title Principal Chief Conservator of Forest (HoFF), Address Satpura Bhavan 1st Floor, , Madhya Pradesh Telephone Phone: 0755-2674001 and 0755-2674302 Fax: 0755-2674001 Email Email: [email protected]

5 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

2.0 Scope of the Project 2.1 Geographical Scope 2.1.1 Physical Features of Hoshangabad Topography Geomorphology and Soil Types The study area is bounded by Satpura ranges in south and by the Narmada River in the north. The area slopes northwest toward the Narmada River. The slope is generally steep at the foothills of Satpura but moderate to gentle toward the Narmada River. The area may be divided into three zones on the basis of the physiography: 1. The Satpura range in the south; 2. An alluvial plain in the middle; and 3. Badland topography zone confined to the vicinity of the Narmada River. The maximum width of the valley between Satpura and the Narmada River is about 30 km. A large number of north-westerly flowing tributaries originating from the Satpura join the Narmada along the left bank. Soils of the area are black grey, red, and yellow, often mixed with red and black alluvium and ferruginous red ravel or lateritic soils. These soils are commonly known as black soils. About 15 percent of the area is covered by sandy loam soils on the high bank of Tawa River. The remaining area is occupied by clay loam with big pockets of sandy clay loam and sandy loam. The soils have been classified as Ustocherpts/Ustorthents, Haplustalfs/Haplusterts as per pedagogical taxonomy. The rocks in the district range in age from Palaeoproterozoic to Quaternary. The Mahakoshal Group of rocks mainly comprise quartzite, slate, and phyllites. The Satpura Group comprises 18 to 21 basaltic flows, which are further classified into five formations. Numerous dykes and sills, mostly of doleritic composition intrude the Gondwana rocks and basaltic flows. The permeability of the soil is low when the clay contains montorillonite. They swell intensively when wet and shrink with deep cracks when dry. Intake of water is very rapid until the cracks disappear after complete wetting. The soil of Hoshangabad district is medium black soil, which is characterized by moderately well drained, fine soils on very gently sloping with moderate erosion. Its pH ranges between 7.2 and 8.0. This soil has medium to high potential for rice, wheat gram, linseed, and vegetable growing. The depths of soil vary from place to place. The water-holding capacity of soil is mainly controlled by the structure of soil. The clayey soil has a higher water-holding capacity than sandy soil. Historically, land and soils of Seoni Malwa, Babai, Sohagpur, and Hoshangabad blocks have been fertile and cultivated for many centuries. Many areas of Piparia, Kesla, and Bankhedi blocks have also been tilled for growing crops for many decades. Table 3: Soil Profile of Hoshangabad S. No. Block Soil type Land Slopes Major Soil Classes Area(ha) 0–3%(ha) 3–8%(ha) 8–25%(ha) >25% 1 Hoshangabad black grey, red, and 51,262 49,062 2,000 0 0 2 Kesla yellow, often mixed 96,567 70,201 6,142 20,224 0 with red and black 3 Seonimalwa alluvium and 124,314 76,045 19,575 28,694 0 4 Babai ferruginous red 58,977 42,595 16,382 0 0 5 Sohagpur ravel or lateritic 126,819 51,345 65,919 9,555 0 soils 6 Pipariya 147,344 40,345 60,503 46,496 0

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S. No. Block Soil type Land Slopes Major Soil Classes Area(ha) 0–3%(ha) 3–8%(ha) 8–25%(ha) >25% 7 Bankhedi 62,806 37,253 25,553 0 0 Total 668,089 366,846 196,074 104,969 0

Major Soils Area (‘000 ha) Percentage of total (%) Deep soil 433.2 64.6 Medium deep soil 26.8 4.0 Shallow soil 209.8 31.3 Source: NBSS & LUP, Nagpur9 Rainfall and Temperature The climate of Hoshangabad district is characterized by a hot summer and general dryness, except during the southwest monsoon season. The cold season runs from December to February and is followed by the hot season from March to the middle of June. The southwest monsoon season follows, running from the middle of June to September. Finally, October and November form the post-monsoon or transition period. The normal rainfall of Hoshangabad district is 1,225.9 mm. It receives maximum rainfall during southwest monsoon period. About 92.8 percent of the annual rainfall received during monsoon seasons and only 7.2 percent of the annual rainfalls take place from October to May. Rainfall forms the sole source of natural recharge to groundwater regime. The maximum rainfall received in district at Pachmarhi (2,122 mm) and minimum at Hoshangabad (1,302.3 mm). On an average, there are 53 rainy days in the District while in Pachmarhi there are 80 rainy days. The normal maximum temperature during May is 42.1oC and minimum during January is 11.7oC. The normal annual mean maximum and minimum temperature of Hoshangabad district is 32.8oC and 19.8oC, respectively. During the southwest monsoon season, the relative humidity generally exceeds 91 percent (in August). The rest of the year is drier. The driest part of the year is the summer season, when relative humidity is less than 33 percent. April is the driest month of the year. The wind velocity is higher during the pre-monsoon period as compared to post-monsoon period. The maximum wind velocity 7.7 km/hr observed during the month of June and is minimum 2.9 km/hr during the month of December. The average normal annual wind velocity of Hoshangabad district is 5.0 km/hr. Table 4: Temperatures and Potential Evapo-Transpiration

Average Weekly Temperature (degree Potential Evapo-Transpiration Elevation In MSL Celsius)

Period Period (season) Summer Winter Rainy Total Min Max Mean (April-May) (Oct-May) (June-Sept) Summer Winter Rainy

Min Min Min

Max Max Max

Mean Mean Mean

9 National Innovations on Climate Resilient Agriculture (NICRA), I. C. (n.d.). Agriculture Contingency Plan for District: Hoshangabad. Indian Council of Agricultural Research (ICAR), National Innovations on Climate Resilient Agriculture (NICRA). Government of India. Retrieved from http://www.nicra-icar.in/nicrarevised/images/statewiseplans/madhya%20pradesh/MP46_Hoshangabad_24.09.13.pdf

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22 43 31 11 34 22 22 37 29 115 79 90 284 270 1352 946

Distribution of Area (forest classification, climatic zonation) Out of the 6703 km2 area of the district, the total area under forest in the district is 2,575.93 km2 (i.e., 257,593 ha), 38.41 percent of the total area.10 There are 13 Reserved Forest Blocks and 120 Protected Forest Blocks in the district (Table 5). Table 5: Reserved and Protected Forests Blocks of the Hoshangabad Division (2013-14). Sl. No. Legal Status No of Forest Block Compartment included Area Notified in Ha. 1 Reserved Forest 13 276 67,462.352 2 Protected Forest 120 224 45,502.798 Total 133 500 1,12,965.150 Source: Working Plan, Hoshangabad Division 2013–2014 District forest area is under the jurisdiction of Hoshangabad Forest Circle. The total digitized area of Hoshangabad forest division, including area of 1,867.62 ha transferred to MP Forest Development Corporation, is 113,986.30 ha, meaning only 112,118.67 ha of digitized area is included for the management purpose in this district. However, the total notified forest area of Hoshangabad Division is 112,965.15 ha. There are four sub-divisions and nine ranges in the entire plan area along with Seoni Malwa and Ranges. The plan area is bounded in the north by Narmada and Dudhi Rivers, in the east by Narsinghpur division, and in the south and west by Betul and Harda districts.11 Table 6: Sub Divisions, Ranges, Range Head Quarters, Sub Ranges, and Beats under the Hoshangabad Division (2013–2014) Division Sub Division Range Range Head Quarter Sub Range Beat Hoshangabad Hoshangabad Hoshangabad Hoshangabad 1 3 Itarsi Itarsi 6 30 Sukhtawa Kala-Akhar 5 21 Sohagpur Sohagpur Sohagpur 3 18 Bagda Bagda 4 22 Pipariya Pipariya Pipariya 1 6 Bankhedi Bankhedi 3 14 Seoni Malwa Banapura Banapura 4 25 Seoni Malwa Seoni Malwa 5 25 Total 4 9 32 164

Figure 3: Range Map, Hoshangabad

10 Census of India 2011. (2011). District Census Handbook Hoshangabad. Retrieved from Census of India 2011: http://www.censusindia.gov.in/2011census/dchb/DCHB_A/23/2332_PART_A_DCHB_HOSHANGABAD.pdf 11 Hoshangabad Forest Division. (2013). Forest Working Plan, Hoshangabad Division. Retrieved from Madhya Pradesh Forest Department: http://www.mpforest.org/intranet/workingplanlibrary/ViewContent.aspx?circularid=182&DivId=10701

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Out of the total division area of 112,118.67 ha (Digital), 66,812.85 ha is under reserved forest and 45,305.81 ha under protected forest. An area of 107,535.08 ha is allotted to various working circles and 4,583.58 ha is under the boundary of forest villages. Thus the area of forest of the division that has been put under regular forest working circle is 107,535.08 ha. Out of this, 2,985.29 ha is classified as blank, 962.66 ha under encroachment, 499.01 ha under plantation and 2,445.87 ha in other categories. The remaining 100,642.23 ha has 12,634.13 ha under crops of young age, 84,393.47 ha under middle age, and 3,614.63 ha under mature age. The total area under dense forest is 90,803.29 ha, open forest is 9,838.93 ha, and 2,985.29 ha is designated blank. The extent of forests in the division is 38.5 percent of the total geographical area of the division. Two major types of forests have been identified in the division per Champion & Seth classification system. 1. 5A/C1-b Southern Tropical Dry Deciduous Dry Teak Forests; and 2. 5A/C-3 Southern Tropical Dry Deciduous Mixed Forests. The forests in the division are classified as Tropical Dry Deciduous Dry Teak Forests and Tropical Dry Deciduous Mixed Forests on the basis of species composition. The main tree species found in the plan area are Teak, Saja, Dhaoda, Haldu, Tendu, Papda, Gunja, Bahera, Bhirra, Kusum, Achar, Aonla, Khair, Dhaman, Kari, Tinsa, Amaltas, and Palas. The main bush species are Lantana, Karonda, Jharberi, Charota, and Gokharu. Dendroclamus strictus is the only Bamboo species occurring in the forests. Details of forest area in different categories are given in the tables below.

9 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 7: Status of Forest Cover in Hoshangabad in 2015 (in sq km) Total forest Very Dense Moderately Dense Open Change in forest area area (m2) forests (m2) forests (m2) forests (m2) between 2013 and 2015 (m2) 2424 274 1373 777 0 Source: State of the Forest Report in India, 201512 Table 8: Different Categories of Forest Area in the Hoshangabad Division (2013–2014) No. Forest Types Stocked/Under-Stocked Area (ha) Percentage

1 Southern Tropical Dry Deciduous Stocked 33,837.166 30.18 Dry Teak Forests Under-Stocked 4,447.948 3.97 (Dry Deciduous forests) Total Teak Forest 38,285.114 34.14 2 Southern Tropical Dry Deciduous Stocked 56,966.129 50.84 Mixed Forests Under-Stocked 5,390.989 4.80 (Mixed Moist Deciduous forests) Total Misc. Forest 62,357.118 55.63 Blank Forest 2,985.298 2.66

Figure: Area under Different Forest Category in the District

70

55.63 60

50

40 34.14 30

20

10 2.66 4.08 0.86 0.44 2.19 0 Teak forest Misc forest Blank forest Encrochment Plantation Forest Other forests Villages

Area (ha x 1000) Percentage Source: Working Plan, Hoshangabad Division 2013–2014 Per the Forest Resource Survey conducted to determine the tree population and biomass, more than 56 lac cubic meters (cmt) of total growing stock was recorded in the division (Table below). Table 9: Forest Resource Survey to Determine the Age, Girth-Class, Density Wise Composition of Crop in the Division (2013–2014) 1 Total no. trees in plan area 48,208,000 2 Total growing stock in plan area (cmt) 5,618,160

12 Forest Survey of India. (2015). India State of Forest Report 2015. Dehradun, India: Forest Survey of India. Retrieved from http://fsi.nic.in/details.php?pgID=sb_62

10 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

3 No. of trees per hectare 460.58 4 Growing stock per hectare (cmt) 51.31 5 Total notified plan area (ha) 112,965.15 6 Total digitized area for management purpose (ha) 112,118.67 Source: Working Plan, Hoshangabad Division 2013–2014 Hydrology The northern part of Hoshangabad District adjoining the Narmada River is covered with alluvium, which makes for more than 50 percent of the entire district. Deccan traps occur as lava flows in the west-central part of the district. The southern part of the district is hilly and occupied by rocks belonging to Gondwanas. The Archaeans are exposed south of Itarsi around Kesla railway station between the rocks of Gondwana in the form of inliers in very small patches and no ground water structure exists in them for hydrogeological studies. Figure 4: Hydrogeological Map of Hoshangabad District

Source: District Ground Water Information Booklet, Hoshangabad District Groundwater Resources Hoshangabad District is characterized by alluvial formations, Gondwana, Achaean, and Deccan trap basaltic lava flow. Dynamic ground water resources of the district have been estimated for base year 2008/09 on a block-wise basis. Out of 670,400 ha of geographical area, 558,352 ha (84 percent) is ground water recharge worthy area and 112,048 ha (16 percent) is hilly area. There are six assessment units (block) in the district that fall under command (43 percent) and non-command (57 percent, Bankhedi, Pipariya and Kesla) sub units. All blocks of the district are categorized as safe blocks, Bankhedi block is with highest stage of ground water development of 61 percent. According to the Central Ground Water Board (CGWB), the “stage of ground water development” is a ratio of Annual Ground Water Draft and Net Annual Ground Water Availability in percentage.

11 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

The present stage of ground water development is 58 percent.13 The net ground water availability in Hoshangabad District is 201,888 hectare-meters (ham) and ground water draft for all uses is 35,617 ham, making stage of ground water development 18 percent for the district. After making allocation for future domestic and industrial supply for next 25 years, the balance available ground water for future irrigation would be 164,889 ham at 50 percent stage of ground water development’s safe limits in the district. Ground water levels form a very important parameter of the ground water system. The groundwater balance expresses itself in the change in water levels; hence a continuous record is important and useful. CGWB has 18 National Hydrograph Monitoring wells and 1 Piezometer in Hoshangabad District.14 Pre-Monsoon Depth to Water Level (May 2012) In general, depth to water level in the area ranges from 4.14 to 17.50 m below ground level. It is observed in major part of the district (Figure 10). Post-Monsoon Depth to Water Level (November 2012) In general, during post-monsoon period, depth of water levels in the district ranges between 1.24 and 13.47 m below ground level. It is observed that the major part of the district was covered by the water levels varying between 5 to 10 m below ground level (bgl) during the period (Figure 11). Figure 10-11: Pre- and Post-Monsoon Ground Water Level

Source: District Ground Water Information Booklet, Hoshangabad District River/Lake In Hoshangabad District, the two main rivers are the Narmada and Tawa, which join each other at in Bandra Bhan village. Other small rivers are the Dudhi and Denwa. Pachmarhi has a large lake that is one of the main tourist destinations in the District. 2.1.2 Socio-Economic Profile of Hoshangabad With a population density of 185 persons/sq. km, Hoshangabad comprises 1.71 percent of the total population of Madhya Pradesh. Hoshangabad has a low sex ratio of 914 women per 1,000 men with an average literacy of 75.29 percent. Female literacy (66.45 percent) is considerably less than male literacy (83.35 percent), according to the 2011 Census.

13 Central Ground Water Board (CGWB). (n.d.). Frequently Asked Questions. Retrieved from Central Ground Water Board (CGWB): http://www.cgwb.gov.in/faq.html 14 Ministry of Water Resources, Central Ground Water Board. (2013). District Ground Water Information Booklet, Hoshangabad District. Retrieved from District Ground Water Information Booklet: http://www.cgwb.gov.in/District_Profile/MP/Hoshangabad.pdf

12 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 10: MP and Hoshangabad Demographic Details

Source: Census 2011

A survey was carried out by Forest-PLUS in 432 households of Hoshangabad District including 36 forest fringe villages where the average family size was 5.4 individuals per household with a total population of 2,538 individuals. About 99.2 percent respondents in the forest fringe villages of Hoshangabad District own dwelling units in contrast to the situations prevailing in cities. About 1 percent of the families were staying in rental houses in the sampled households. Of all households sampled, about 10.41 percent families had pucca (pucca = not made of mud) houses, 13.5 percent had semi-pucca houses, and 76 percent families lived in kaccha (kaccha = made of mud) houses. The proportion of scheduled tribe and other backward classes was 46 percent and 30 percent, respectively, and the families under general category were 12.3 percent and under Scheduled Caste were 11.5 percent of the sampled households. Forest Villages in Hoshangabad There are around 923 villages in Hoshangabad District, of which 332 villages are located within 5 km of the periphery of the forest area. Due to poor road networks in these villages, about 72 percent of the villages are cut off from the main roads during rainy season. Employment generation through forestry activities represents 15 percent of the total employment generated. Forest dwellers have low agriculture production, which is an inhibiting factor for their overall development. Biotic pressure of livestock is very high. The people living in these villages are dependent on forest for their livelihood, as they collect and sell NTFPs like Mahua, Chironji, Tendu leaves,

13 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) medicinal plants, and honey to earn their livelihood for about six months per year. The inhabitants of forest fringe villages are affected by geographical disadvantageous location of their villages. The goods and services are dearer to them both in terms of extent of availability and costs. If these are not made available in-situ, these people will migrate to alien environment where they will be subjected to further exploitation. Hence, the need for in-situ development of forests together with the forest fringe villages and their inhabitants is necessary (Development of Forest Villages through Forest Development Agencies Madhya Pradesh, Forest Department, and Government of Madhya Pradesh). Figure 5: Village Map of Hoshangabad District

Household Size The total number of households in the District has been recorded to be 255,099 (Pradhan Mantri Krishi Sinchayee Yojana [PMKSY], 2014)15, bringing the average household size to 4.85. Social Classification16 Table 11: Social Classification in Hoshangabad District SC ST General Total

15 Ministry of Agriculture & Farmers Welfare, G. o. (2014). Operational Guidelines of Pradhan Mantri Krishi Sinchayee (PMKSY). Government of India, Ministry of Agriculture & Farmers Welfare. New Delhi: Ministry of Agriculture & Farmers Welfare, Government of India. Retrieved from http://pmksy.gov.in/pdflinks/Guidelines_English.pdf 16 Department of Irrigation & CD and Department of Agriculture, Hoshangabad. (2015-2020). District Irrigation Plan, Hoshangabad. Retrieved from Pradhanmantri Krishi Sinchai Yojana (PMKSY): http://pmksy.gov.in/mis/Uploads/2016/20160721020514706- 1.pdf

14 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

No. of HH No. of No. of HH No. of No. of HH No. of No. of HH No. of Members Members Members Members 40,386 211,902 50,221 193,633 164,492 831,960 255,099 1,237,495

Livestock and Grazing Among the ruminant livestock reared by the respondents, the highest was cow (n=8,683 individuals), followed by buffalo (n=2,847). Individual goats (n= 4,955) were reared by the locals interviewed in the study villages. The interview data also suggests that majority of the locals were dependent on forests for fuelwood collection (717.51/year) followed by own land (137.29 tons/year) and community land (27.02 tons/year). However, a significant proportion of villagers were dependent on purchased fuelwood (47.5 percent). The source wise-fodder (stall feed) collection was also highest from forest (335.71 tons/year) followed by own land (108.98 tons/year). For grazing, locals were dependent mostly on forests followed by private pasture (7.45 tons/year) and road-side lands (1.40 tons/year). About 7,400 tons of fodder is grazed in forest in a year and about 335 tons/year fodder is extracted from forest for stall-fed livestock (Table 9). The data on various use of fuelwood collected from forest suggests that fuelwood in Hoshangabad is mostly used for cooking (9,45.74 tons/year) followed by heating during winter months (128.17 tons/year). Although Hoshangabad is one Madhya Pradesh’s agriculturally advanced districts, animal husbandry is not as developed. Unlike the districts of Malwa region (Shajapur and ), Hoshangabad District did not develop a synergetic relation between the agriculture and animal husbandry-based livelihoods. Dairy development did not emerge as a key livelihood of the villagers, which could be traced to the fact that the villagers from the blocks of Sohagpur, Hoshangabad, Babai and Piparia, were, on an average, 70 to 120 km. away from Bhopal city. The Bhopal Milk Union collects some milk from primary milk producers’ cooperatives located in Hoshangabad district. However, there is no milk chilling plant in the district. (PMKSY, 2014) Table 12: Livestock Details, Hoshangabad Block Small Animals (no.) Large Animals (no.) Poultry Goats Pigs Sheep Indigenous Non-descriptive Cow Buffalo Hoshangabad 2,401 7,726 281 0 36,442 13,018 Babai 2,785 9,082 8 0 47,461 15,010 Sohagpur 2,976 9,024 1,000 0 44,853 16,273 Pipariya 8,995 13,407 262 40 39,960 14,801 Bankhedi 6,676 11,756 184 12 37,876 16,775 Kesla 199,770 12,483 88 0 42,973 9,872 Seoni Malwa 6,740 17,107 144 0 74,245 27,403 Total 230,343 80,585 1,967 52 323,810 113,152

Land Use The land-use pattern of Hoshangabad District can be classified as net sown area (61.20 percent), forest area (16.37 percent), land not available for cultivation (5.34 percent), cultivable wasteland (5.07 percent), and other uncultivated land excluding both fallow land and cultivable wasteland (2.67 percent). See Table 14 below for the land-use pattern in hectares. (PMKSY, 2014) Table 13: Land-Use Pattern, Hoshangabad Geographical Area (ha) 670,300 Area under Forest (ha) 175,340 Area under Agriculture (ha) 324,025

15 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Net Sown Area (ha) 317,100 Gross Cropped Area (ha) 326,995 Net Rain-fed Area (ha) 29,910

Flora and Fauna The forests in Hoshangabad district are classified as Teak and Miscellaneous forest on the basis of species. The panther is the most predominant of the large wild animals in Hoshangabad. Tiger sightings (direct or indirect) are rarely reported in the area. Other carnivores (hyenas, wild dogs, jackals, and wildcats) can be found in the area. Herbivorous species found in the area include blue bull, chital, sambhar, barking deer, wild pig, sloth bear, and Indian gazelle. The ban on the hunting of wild animals was made effective with the enforcement of Wild Life Protection Act (1972). Table 14: Forestry Linked Statistics of Hoshangabad District Geographical area (sq. km.) 6703 Forest area (sq. km) 1753.4 Reserved forest (sq. km.) 685.37 Protected forest (sq. km.) 457. 91 Encroached forest area (ha) 56. 133 Forest type Teak forest Main forest species Teak, Bamboo Population 8,88,449 Male population 4,68,505 Female population 4,17,944 ST population 14.44 % SC population 16.05 % Income 22% Fuelwood 59% Fodder 39.29% Population below poverty line (%) 38% Land under irrigation (%) 79.18% Agricultural production 893,500 MT/year Employment (%) 22-29% Average Annual Income per family (INR) 6,000-7,000 Total no. of villages 923 No. of villages within 5 km of forest area 332 Source: Forest Department, Government of Madhya Pradesh 2.2 Carbon Pools A rigorous assessment of the carbon stock of the forests in Hoshangabad has been undertaken through spatial analysis and extensive field surveys. The carbon pools considered as part of carbon stock assessment and baseline development, along with their justification, has been given below. Table 15: Carbon Pools Considered for Jurisdictional Baseline Carbon Pools/Sources Gas Included Justification/Explanation

Aboveground tree or woody CO2 Yes Major carbon pool affected by project activities biomass Aboveground non-tree or non- CO2 No Time and resource limitations woody biomass Belowground biomass CO2 Yes Major carbon pool affected by project activities Litter CO2 Yes Carbon pool affected by Project activity

16 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Dead wood CO2 No Dead wood contribution to the Carbon pool is negligible (1% approx.)17 Soil organic carbon CO2 Yes Major carbon pool affected by project activities

2.3 Baseline Sources and Project Sources of GHG Source Gas Included? Justification/Explanation CO2 Yes Emissions are related to changes in carbon pools. CH4 Yes Included only in the case of certain intervention activities such as cook stove and fuel efficiency activities (CFE). In baseline if biomass is burnt during land preparation in the case of afforestation Baseline reforestation and revegetation (ARR), CH4 is included. Deforestation and In baseline if grazing and animal management is

Forest involved, CH4 is not counted for reasons of Degradation conservativeness. N2O Yes Included as CFE are involved. In baseline or project if

Baseline biomass is burnt, N2O is included. If baseline involves application of fertilizers N2O is not considered for reasons of conservativeness. CO2 Yes Emissions are related to changes in carbon pools. CH4 No Emissions are expected to be negligible and are hence Baseline ARR excluded. N2O No Emissions are expected to be negligible and are hence excluded. CO2 No Emissions are excluded as they are a part of the changes in carbon pools. When there is a forest fire, there is a related change in the forest stratum, which is already reflected as change in the emission factor. Biomass burning Estimation of emissions from forest fire separately will from unplanned result in double counting. large and small CH4 Yes CH4 emissions of burning woody biomass from scale fires and unplanned fires are to be accounted. If the fires are biomass burnt in catastrophic, CH4 emissions must be estimated and cook stoves demonstrated negligible or otherwise accounted for. N2O Yes N2O emissions of burning woody biomass from unplanned fires are to be accounted, If the fires are catastrophic, N2O emissions must be estimated and

Project demonstrated negligible, or otherwise accounted for. CO2 No Emissions from fossil fuel combustion is considered de Fossil fuel used minimis for REDD and ARR. Excluded. during operations CH4 No Insignificant N2O No Insignificant CO2 Yes Emissions related to changes in carbon pools are taken Removal of woody into account. Woody biomass will not be removed biomass during during assisted natural regeneration activities. assisted natural CH4 Yes CH4 emissions from removal of woody biomass are regeneration significant when fire is used in preparing the land for (Assisted Natural ANR activities. Woody biomass will not be removed Regeneration during assisted natural regeneration activities.

17 India State of Forest Report 2011. (2011). Chapter-8 Carbon Stock of India's Forests. Forest Survey of India.

17 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Source Gas Included? Justification/Explanation [ANR] and ARR) N2O No N2O emissions from burning woody biomass during activities ANR activities are assumed negligible and conservatively excluded. Fertilizer used CO2 No Assumed negligible during enrichment CH4 No Assumed negligible planting for N2O No Assumed negligible assisting natural regeneration and ARR CO2 No Not Applicable Increased fertilizer CH4 No Not Applicable use N2O No N2O emissions related to increased fertilizer use are de minimis.

18 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

3.0 Forest Reference Emissions Levels 3.1 Introduction A national forest reference emission level, or forest reference level, is one of the elements to be developed by developing countries implementing REDD+ activities (para 71 of decision 1/CP.16). The COP recognizes the importance and necessity of adequate and predictable financial and technology support for developing such reference levels. Reference levels are expressed as tons of CO2 equivalent per year for a reference period against which the emissions and removals from a period within project life are compared to estimate actual emissions savings from the project.18 Spatial analysis was done for 2005, 2008, and 2013 to estimate forest cover change under the different forest types in Hoshangabad District/Division. A land use land cover (LULC) analysis was conducted. Linear Imaging Self-Scanning System (LISS)-III images for 2013 have been used to represent the latest satellite imagery for the region. Similarly, the team used satellite imagery from 2008 and 2005 to depict the forest cover four to nine years and nine to ten years before the project start date, respectively. Hence, accurate data on past LULC and forest cover in Hoshangabad are available and have been used in the analysis for these three points in time. The selection of data sources was conducted according to Chapter 3A.2.4 of the Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines for GHG inventories, AFOLU19. The LISS-III multi-sensor satellite data was used for baseline analysis. Data was downloaded from the open source data archive and web-based gateway to Indian Earth observation, BHUVAN,20 and National Remote Sensing Centre (NRSC)/Indian Space Research Organization. Ancillary data on past LULC and forest cover in Hoshangabad was made available by the MPFD to guide the classification and validation process. The temporal resolution of satellite images for the three points are: - 2013 0–3 years before the project start date. - 2008: 4–9 years before the project start date. - 2005: 10- 15 years before the project start date.

18 UNFCCC. (n.d.). Forest Reference Emission Levels. Retrieved from REDD+ Web Platform: http://redd.unfccc.int/fact- sheets/forest-reference-emission-levels.html 19 IPCC 2006, 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan. 20 Indian Space Research Organisation. (n.d.). Open Data Archive. Retrieved from Bhuvan: http://bhuvan.nrsc.gov.in/data/download/index.php

19 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 16: Characteristics of the Satellite Imagery Used Data Source Main Use of Data Information about data collected Medium resolution of 23.5 m remote sensing data of at least one image for 3-time periods 0–3 years before 4–9 years before project 10–15 years before project Time Frame project start date start date start date Year of Satellite Imagery 2013 (LISS-III) 2008 (LISS-III) 2005 (LISS-III) Received from Madhya Pradesh Forest-Information Technology (IT) Department, Wing-D Source Government of India, Bhopal – 462004 Madhya Pradesh, India Historical analysis Satellite imagery using visible (green, red) and near-infrared bands (NIR). This is Type and Resolution (Spatial of deforestation LISS-III multi-spectral data with a spatial resolution of 23.5 m operating in the visible, and Spectral) and forest NIR bands and 70.5 m resolution in the shortwave infrared (SWIR) band. degradation Coordinate system and pre- WGS 84 – UTM Zone 43N processing Layer Extent: 726684.04 803148.41 (If different sources of remote 2529003.90 2453499.54 sensing data are used, a formal Indian Remote Sensing ID LISS-III multi-spectral sensor with a spatial resolution of comparison of the sensors 23.5 m operating in the visible, NIR bands and 70.5 m resolution in the SWIR band, should be added to the with a swath of 141 hm. monitoring report to ensure Resourcesat-1 LISS-III multi-spectral sensor with a spatial resolution of 23.5 m consistency) operating in the visible, NIR bands and SWIR band, with a swath of 141 km. Minimum Mapping Unit (ha) ≥1 hectare Description of Method Used to The LULC maps for historical baseline are classified using an unsupervised approach Produce These Data Training of with the K Means classification method. classification The LULC classes or categories described are as follows: procedures Dry Deciduous Forest Descriptions of the LULC Independent Mix Dry Deciduous Forest Classes and/or LULC Change verification of the Cropland Categories analysis of Wetland historical images Other lands Settlements Grassland

20 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

An accuracy assessment of the LULC and forest cover maps revealed overall accuracy to be above 80 percent. 3.1.1 Ancillary Data Ancillary data such as validation of classification, working plans, forest circle and range boundary maps, administrative boundary maps, slope maps, elevation maps, and agro-ecological zonation maps obtained from the MPFD have been used. 3.1.2 Pre-processing of remote sensing data Pre-processing includes radiometric and geometric correction and managing image data loss due to cloud cover. Geometric correction ensures that images in a time series properly overlay one other and properly overly other geographic information system (GIS) maps used in the analysis (i.e., for post- classification stratification). The average location error between two images (RMSE) must be less than or equal to one pixel. A forest benchmark map was needed to show forest cover status in the project area. The final LULC map in the historic series was used as the forest benchmark map; however, missing values within the project area due to clouds and cloud shadow were filled with remotely sensed data acquired within three years before the start of the crediting period. Calculation of GHG benefits in the project area after the project start will include only cloud-free imagery. When clouds and cloud shadows are present, calculation of the GHG benefits from these areas will be postponed until cloud-free remote sensing data is available in subsequent monitoring periods. Temporarily halted net emission reductions may be added to those generated in the subsequent monitoring period. This is only allowed in areas for which the forest status was unambiguously demonstrated at the beginning of the crediting period. The detailed methodology for remote sensing analysis is as follows:

21 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 6: Detailed methodology for analysis of satellite imagery The satellite imagery was subjected to radiometric and geometric corrections to obtain a clear image with verified coordinates. The images and layers were maintained according to the following system: Projection Type: UTM Spheroid Name: WGS 84 Datum Name: WGS 84 A reconnaissance survey was conducted to acquaint the team with general vegetation patterns in the area, main vegetation types and variation, and tonal patterns observed on existing imagery and maps. The landscape was traversed along roads, major drainage areas, and hilltops to collect ground-truthing information. Global positioning system (GPS) readings were taken to pinpoint various land use classes and forest types. In addition, existing literature like working plans and annual reports were consulted. Classification of land cover using remotely sensed data was done using digital classification algorithms, which allow for automated grouping of spectrally similar pixels in order to classify different landscape features. The two major types of forest found in this area are dry deciduous forest (DDF) and mix dry deciduous forest (MDDF). In Hoshangabad District, it is estimated that the area of DDF in 2005 was 217,530.9 ha but this decreased to 206,514.8 ha by 2013. The area of MDDF in 2005 was 57,961.6 ha but decreased to 56,259.53 ha by 2013. Hence, the district’s DDF area decreased by 11,016 ha and the MDDF area decreased by 1,702 ha between 2005 and 2013.

Figure 7: Canopy Density Map of Hoshangabad District, 2008

22 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 8: Canopy Density Map of Hoshangabad District, 2013 Land cover: Spatial analysis was conducted to classify LULC in the district/division according to the IPCC’s seven classes: dry deciduous forest, mix dry deciduous forest, wetland, cropland, other land, settlement, and grassland. The classification results show that during the 2005–2013 period of analysis, DDF decreased by 110,016 ha, MDDF decreased by 1,702 ha, wetlands increased by 75 ha, croplands increased by 1,619.5 ha, other lands increased by 1,101.7 ha, settlements increased by 655.5 ha, and grasslands increased by 184 ha.

23 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 9: Land Use Land Cover Map of Hoshangabad District, 2005

Figure 10: Land Use Land Cover Map of Hoshangabad District, 2008

24 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 11: Land Use Land Cover Map of Hoshangabad District, 2013 Compartment boundary: A compartment is a permanent, geographically recognizable unit of forestland forming the basis for planning, prescription, implementation, monitoring, and recording of forest operations. To the extent that it is practicable, areas of forest that are to be managed for different purposes, or have clearly different functions or values, should be placed in separately defined compartments. The forest division under Hoshangabad District is divided into 1,140 compartments covering an area 288,384.3 ha.

25 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 12: Compartment boundary map of Hoshangabad District 3.2 LULC Changes over the Historical Reference Period 3.2.1 Methodology Land use involves the management and modification of the environment or wilderness into built environments, such as settlements, and semi-natural habitats, such as arable fields, pastures, and managed woods.

26 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 17: Land Use Pattern in Hoshangabad District

Area under Agriculture Area Area Number of Number of Total Area under under S. No. Block Gram Villages Geographical Area under Waste- Other Panchayat Covered Area Sown Forest Gross Net Cropping land Uses More Cropped Sown Intensity Than Area (1) Area (2) (%) Once (1-2) 1 Hoshangabad 49 103 51,262 46,080 48,575 38,316 203 0 2470 101 2 Kesla 49 128 96,567 32,475 32,475 24,338 201 20,224 6,230 155 3 Seonimalwa 95 202 124,915 76,045 76,045 66,485 205 28,694 6,480 108 4 Babai 61 107 58,977 42,595 42,595 24,338 204 0 3,835 120 5 Sohagpur 65 141 126,819 51,345 41,450 23,141 202 65,909 6,010 141 6 Pipariya 52 135 147,344 40,345 40,345 27,752 203 60,503 6,190 120 7 Bankhedi 53 120 62,806 35,615 35,615 25,183 201 0 3,125 115 Total 424 936 668,690 324,500 317,100 229,553 203 175,330 34,340 860

Table 18: Table: Classification of Land and Forests in Hoshangabad over the Reference Period Average Average Land Use Land Cover Land Use Land Cover Area in ha Magnitude in ha Change in ha Change in % (Density classes) 2005 2008 2013 2005-2008 2008-2013 Dry Deciduous 10–30 5,278 8,474 15,974 -3,196 -7,500 -5,348 -0.80 Dry Deciduous 30–50 2,439 3,795 6,536 -1,356 -2,741 -2,049 -0.31 Dry Deciduous 50–70 16,956 12,175 3,026 4,782 9,148 6,965 1.04 Dry Deciduous Above 70 10,685 8,442 5,527 2,244 2,914 2,579 0.38 Mix Dry Deciduous 10–30 87,523 64,810 77,451 22,714 -12,641 5,036 0.75 Mix Dry Deciduous 30–50 70,254 54,972 63,465 15,283 -8,493 3,395 0.51 Mix Dry Deciduous 50–70 25,618 46,989 30,135 -21,371 16,855 -2,258 -0.34

27 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Average Average Land Use Land Cover Land Use Land Cover Area in ha Magnitude in ha Change in ha Change in % (Density classes) 2005 2008 2013 2005-2008 2008-2013 Mix Dry Deciduous Above 70 30,851 43,788 36,445 -12,937 7,343 -2,797 -0.42 Wetland 31,352 23,987 17,478 7,364 6,509 6,937 1.03 Cropland 370,321 381,331 386,547 -11,011 -5,215 -8,113 -1.21 Other land 11,703 16,060 19,306 -4,358 -3,245 -3,802 -0.57 Settlement 2,313 3,176 6,159 -862 -2,983 -1,923 -0.29 Grassland 5,406 2,701 2,652 2,705 49 1,377 0.21

28 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Definition of LULC Classes and Forest Strata

Figure 13: Territorial Range Map of Hoshangabad

Figure 14: Forest Type Map of Hoshangabad, 2005

29 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 15: Forest Type Map of Hoshangabad, 2008

Figure 16: Forest Type Map of Hoshangabad, 2013

30 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 17: Forest Strata and Canopy Density Map of Hoshangabad (2005, 2008, 2013)

31 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

4.0 Drivers of Forest Change 4.1 Introduction Almost 70 percent population of Hoshangabad District is rural. There are a total of 644 villages in the district, out of which 351 are situated within a range of 5 km from a forest boundary. The economy is mainly based on agriculture and forest resources. Dependence on the fuel-wood, fodder, and small timber generated by the forest among people who live nearby is very high. A significant majority of the area’s farmers have small land holdings. In the plan area, most crops are grown during Rabi (from October to March), but there is some harvesting of crops during Kharif (from July to October). The main crops produced in the plan area are wheat, gram, soybeans, and oil seed. Cattle rearing is also common in the district. Good quality tendu leaves are produced in the division. The collection and marketing of tendu leaves is carried out by minor primary forest product cooperative societies. The villagers obtain non-nationalized NTFPs and fuelwood free of charge from the forests. 4.2 Agents and Drivers of Deforestation and Forest Degradation As part of this project for the Hoshangabad District, the agents and the activities they carry out that lead to deforestation/forest degradation have been identified. These activities include firewood collection, timber extraction, land clearing for agriculture, and unsustainable NTFP collection. Drivers of deforestation and forest degradation fall into two categories: those that are planned for in accordance with policies, legal frameworks, and management plans, and those that are unplanned and spontaneous (i.e., beyond government and management control). Planned and unplanned withdrawals of resources from forests affect the forest carbon stock (i.e., deforestation and forest degradation). Thus, proper understanding and management tools are required, including transparent governance, effective enforcement, and appropriate mitigation actions to counter these drivers. Drivers for both of these categories are listed below in Table 19, as identified in India’s submission to the UNFCCC’s Subsidiary Body of Scientific and Technological Advice (SBSTA) on REDD+. Table 19: List of Planned and Unplanned Drivers of Deforestation and Forest Degradation21 Planned Drivers Unplanned Drivers Infrastructure and other developmental Unauthorized, unplanned, or unsustainable extractions of works: forest resources not covered in official management plans: - Road and railway construction - Encroachment of forest land for agriculture and housing - Mining activities - Illegal felling of timber - Hydro-electric power - Firewood, small timber, and NTFP extraction - Irrigation projects - Livestock grazing - Industrial development - Fodder collection - Planned expansion of cities and towns - Illegal mining and quarry operations

In order to minimize the impacts of planned drivers, appropriate interventions need to be implemented. These interventions encompass policy instruments and management options such as effective legal frameworks and site-specific mitigation measures. Unplanned drivers and activities are mainly a direct outcome of local people’s dependence on the adjoining forest areas

21 Government of India. (2012). Submission by India to SBSTA, UNFCCC. UNFCCC. Retrieved from http://unfccc.int/files/land_use_and_climate_change/redd/submissions/application/pdf/india_driversdeforestationdegrdn_sbsta.p df

32 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) to meet their livelihood and subsistence needs of firewood, grazing, fodder, and food supplements. To a small extent, illegal mining activities within a forest is also an unplanned driver of forest change. Weaning the local communities away from such livelihood-related practices will require sizable investment in providing alternatives for the forest products that the communities have been deriving from the forests traditionally—but not necessarily in a sustainable manner. Many of these forest-dependent people are poor with little land and limited options for sustaining livelihoods. Geospatial mapping of different drivers of forest degradation and deforestation in Hoshangabad District is shown in the following figures from a study conducted by the Forest Research Institute of India (FRI) in 2016.

Figure 18: Spatial Representation of Fodder Extraction in MP Landscape Study Villages (FRI Study)

Figure 19: Spatial Representation of Grazing Intensity in MP Landscape Study Villages (FRI Study)

33 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 20: Spatial Representation of Fuelwood Extraction in MP Landscape Study Villages (FRI study)

Figure 21: Spatial Representation of Livestock Population in MP Landscape Study Villages (FRI Study)

34 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 22: Spatial Representation of Human Populations in MP Landscape Study Villages (FRI Study)

Figure 23: Spatial Representation of Fire Intensity in MP Landscape Study Villages (FRI Study)

35 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Figure 24: Collective Impact of Forest Degradation and Deforestation Drivers in Madhya Pradesh Forest-PLUS Landscape (FRI study) A socio-economic survey carried out by Forest-PLUS and the MPFD in 15 villages to assess forest products consumed by the local people revealed that the forest product requirements per family in the plan area are: 0.22 mt3 timber, 12.62 Bamboo sprouts, and 7.93 quintal fuelwood. There is 2.9 times more grazing pressure than the carrying capacity in the plan area. Timber is mainly exported, whereas fuelwood is utilized locally. Tendu is sold through the Minor Forest Produce (MFP) cooperative societies. Five major drivers of deforestation and forest degradation in the Hoshangabad circle of MP have been identified (see Table 20).

36 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 20: Major Drivers of Deforestation and Forest Degradation Drivers Factors that can decrease the impact of drivers Fuelwood Extraction Introduction of alternate energy sources like biogas plants, efficient cook- stoves, and solar water heaters. Alternative fuelwood species and alternate solutions for animal fodder. Animal Grazing Fodder needs of the cattle population are met from forest area. Also, rising standard of living and population pressure in MP have led to increased demand for meat, milk, and other dairy products. NTFP Extraction Sustainable harvesting methodologies for NTFPs linked to markets to ensure that fair benefits reach the collectors. Diversion and Forestland is diverted for various needs. Climate-smart agricultural, Encroachments silviculture, and agro-forestry practices in the state can aid in decreasing encroachment, as they can ensure sustainable incomes and employment. Forest Fires Implementation of forest fire reporting and response mechanisms.

Figure 25: Deforestation and Degradation Map of Hoshangabad, 2005-2013 4.3 Pre-project Scenario Table 21: Status of Forest Cover in Hoshangabad in 2015 (Km2) Total forest area Very Dense Moderately Open Change in forest area forests Dense forests forests between 2013 and 2015 2,424 274 1,373 777 0 Source: State of the Forest Report in India, 201522

22 Forest Survey of India. (2015). India State of Forest Report 2015. Dehradun, India: Forest Survey of India. Retrieved from http://fsi.nic.in/details.php?pgID=sb_62

37 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

4.4 Methodology In order to ascertain and quantify the drivers of deforestation and degradation, a survey was undertaken in the forest fringe rural villages in Hoshangabad District lying within 0 km, 3 km, and 5 km of the forest buffer zone, as historically they are the most dependent on forest products. An 11-step approach was followed. The steps are depicted in Figure 27 below.

3 1 2 Questionnaire for 4 District-level forest FGD and HH-level Validation by the change map Map validated surveys in wards forest officials prepared prepared in-house

6 7 8 5 Villages randomly Selected villges FGDs carried out Sampling set up selected as per mapped and geo- with randomly sampling criteria tagged selected villages

10 11 9 Validation meeting of HH surveys carried Data digitization & drivers conducted with out in villages analysis stakeholders

Figure 26: Steps for Assessing Degradation and Deforestation Drivers in Hoshangabad 4.6 Questionnaire Preparation Based on the initial discussions with the State forest officials, two questionnaires were prepared to understand the drivers of degradation and deforestation in the State. The questionnaires were designed to use a multi-pronged approach to ascertain a single driver through multiple questions. 4.6.1 Criteria for Wards and Households Selection Stratified random sampling of the State was undertaken based on the degradation and deforestation. Buffer zones were created at 0 km, 3 km and 5 km from the forest. The following steps were undertaken to assess and quantify forest degradation and deforestation drivers: 1. Forest change maps between 2005 and 2013 of all the ranges in the Hoshangabad District were drawn up and evaluated to identify spatial distribution of forest degradation, deforestation, reforestation, and enhancement in forest cover that has taken place between 2005 and 2013. 2. Criteria for selection of wards to be surveyed included villages located around forests that showed any amount of change in terms of deforestation and degradation. Villages were to be surveyed within the three buffer zones. 3. As per the UN guidelines,23 general purpose surveys that focus on several subjects (e.g., identifying the direct and indirect indicators of degradation and deforestation) should have a sample size such that it enables reliable measurement. The UN guidelines suggests 5–10

23 UN, 2005. Designing Household Survey Samples: Practical Guidelines. Department of Economic and Social Affairs, Statistics Division, Studies in Methods, Series F No.98, http://unstats.un.org/unsd/demographic/sources/surveys/Handbook23June05.pdf

38 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

percent samples need to be covered, but the exact percentage can be left to the discretion of the survey manager. 4. The next step was to calculate the number of HHs to be surveyed to give meaningful results. As per literature, the number of samples within a population of 10,00,000 (in this case, population refers to HHs), a maximum of 384 surveys would need to be conducted, beyond which samples get saturated.24 4.6.2 Sampling Design Field Records The survey team deployed consisted of one supervisor supported by one assistant supervisor and three surveyors. Additionally four people logged email and hard copy data. There were a total of nine people in the survey team. Focus Group Discussions Focal group discussions (FGDs) were performed with a group of 200–250 village members, with the goal of including at least one representative from each hamlet as possible. Twelve FGDs were carried out with 17 villages in Itarsi, Seoni Malwa, Pipariya, Bankhedi, and Shagpur tehsils to validate the findings from the s in general and understand socio-economic and land-use characteristics and the extent of villagers’ dependence on forests in Hoshangabad. Table 22: List of Villages Where FGDs Were Carried Out S.no. Tehsil Village 1 Itarsi Silwani 2 Seonu Malwa Lokhertali, Sota Chikhali, Nanderwada, 3 Pipariya Pisua, Pagara, Chandonpipariya, Khar, Singoda, Tekapar, Ghogri, Khar, Singhanama, Hathni Kapa 4 Bankhedi Khapa Khurd 5 Sohagpur Magariya, Gaudikhedi

Rural Household Survey A sample of 66 villages was chosen to represent the diversity of forest management and socio- economic conditions prevailing in villages within the three buffer zones. The survey was carried out from June to September 2016. Table 23: List of Villages and Households Surveyed S.No. Villages HHs S.No. Villages HHs 1. Pipaliya Kalan 20 14. Matkuli 20 2. Bankhedi 20 15. Saharanpur 20 3. Chichadhani 7 16. Panchmarhi 20 4. Silwani 20 17. Ghana 20 5. Kotmi Ryd 20 18. Singoda 20 6. Koda 17 19. Raini Pani 9 7. Dhekna 20 20. Dabka 20 8. Lokhar Talai 20 21. Tekaper 20 9. Kasda Khurd 20 22. Basaniya Kala 20 10. Jujharpur 20 23. Nibhora 20 11. Bhopda 20 24. Piplathon 20 12. Chhitapura 12 25. Mangriya 20 13. Jhapdi 9 26. Kamti 20

24 Krejcie, Robert V, and Daryle W Morgan. 1970. “Determining Sample Size for Research Activities.” Educational and Psychological Measurement 30(3): 607–10. http://journals.sagepub.com/doi/10.1177/001316447003000308.

39 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

S.No. Villages HHs S.No. Villages HHs 27. Pisua 20 47. Panari 9 28. Semri Harchand 20 48. Mongra 10 29. Bari Aam 9 49. Gram umaria 10 30. Ghogri 4 50. Samnapur 10 31. Mohgaon 12 51. Rechheda 7 32. Pagara 10 52. Raiyatwadi 5 33. Amar Katara 13 53. Rechheda 5 34. Khari 7 54. Badkchhar 2 35. Singanama 10 55. KHoshangabad 10 36. Kapar Kheda 8 56. Meghli 10 37. Hathni Khapa 10 57. Nayakheda 10 38. Dokri kheda 9 58. Borkunda 10 39. Goodi khedi 10 59. Nanderwada 10 40. Chedka 10 60. Sota chikhali 9 41. Naya kheda 10 61. Binda kheda 10 42. Sihar kheda 11 62. Chandan pipariya 10 43. Bichua 7 63. Lanjhi 10 44. Tura khapa 10 64. Amadeh 10 45. Dunda deh 10 65. Binora 10 46. Godikhedi malgujari 9 Quality Assurance/Quality Control Stringent quality assurance/quality control (QA/QC) procedures were followed to gather good quality data through field measurements. The household-level questionnaire was designed and field-tested before the actual questionnaire survey was administered. The survey team was given an orientation on the study and its objectives. Data Digitization and Analysis The data in the questionnaires were digitized. Statistical analysis was carried out to decipher the dominant driver in each of the wards. These were then added up to assess the dominant driver in each of the districts, and then in the entire State. Socio-Economic Profile of the Surveyed Areas As of the 2011 census, the population of Hoshangabad District was 1,241,350, 68.6 percent of which is rural (851,364). There are 175,529 rural households in the district.25 As per our survey, the average household size in rural areas is 5.4. Average household size in the district is much higher than the average household size in Madhya Pradesh (4.84) or that of India (4.9). Though the cropland area is high, the number of landless persons is also high. It was revealed that the majority of the respondents (53.5 percent) are landless. Of the 46.5 percent of landholders surveyed, 6.7 percent own less than 2 ha of land, and 30.8 percent own between 2 and 5 ha. The remaining landholding households own land of between 5 and more than 15 ha (see Figure 27b). Livestock holding levels are relatively low in Hoshangabad District. Each household on average has two cows, one ox, one buffalo, and one goat. The survey revealed that out of total livestock owned, the majority (50 percent) were cows, followed by ox (28 percent), goat (12 percent), and buffalo (10 percent). It was further noted that in the survey region, 28 percent of the families earn their livelihood through farming and 44 percent of the population are laborers (agricultural and otherwise).

25 Hoshangabad District Census, 2011.

40 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Significantly, the only livelihood for 24 percent of the population is NTFP collection from forests. Only 1 percent of the population is engaged in business and 3 percent of the population pursues other livelihoods.

60.0 53.5 (a) (b) 50.0 Urban 31.4% 40.0 30.8 30.0

20.0

10.0 6.7 4.3 Rural 2.0 2.7 68.6% 0.0

Others Others Agricultur (c) 6% (d) 3% NTFP e 24% 28% OBC 28% ST 47% Business 1%

SC Labour 19% 44%

Figure 27: Key Socio-economic Features: (a) Population Distribution in Hoshangabad – Urban and Rural; (b) landholding; (c) Social Profile; (d) Livelihood Pattern Source: Population data is from 2011 Census. The remainder of the data is from project survey. 4.6.3 Types of Produce Collected from Forests The respondents in the survey indicated that they source various material from forests to meet their energy demands, provide fodder for their cattle, make houses and sheds for cattle, or gather medicinal plants. These scenarios were validated by rangers and forest guards who are familiar with the situation in the field. Table 24 lists the types of produce collected from forests and their utilization. The table also notes the different species used for these purposes. Table 24: Types of Forest Product Collected by Households for Various Purposes Type of Forest Purpose Species Product Collected (Vernacular Names) Firewood Meeting energy demand Saj, Makhandi, Kahrera, Kher, Ghiriya, Mahua, Satkata, Aal, Phaphra Fodder Fodder and feed for cattle Forest litter, leaves Small timber and Fencing and housing for Neelgiri, Babul, Rinj, Sagon, Saaja, Subabul, large timber cattle Arjun, Baans (Dendroclamus Strictus) Tree bark Medicinal applications Arjun, Rohini, Beeja, Sal, Neem Seeds Oil Mahua, Neem

41 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Type of Forest Purpose Species Product Collected (Vernacular Names) Flowers Liquor Mahua Fruits Medicinal applications Chirata, Neem, Harra, Bahera, Kalmegh, Maror Phali Leaves Plates, Bidi Tendu Patta 4.7 Assessment of Drivers of Deforestation and Degradation 4.7.1 Fuelwood In Hoshangabad District, forests continue to be the main source of fuelwood. Our survey indicated that 88.84 percent of the fuelwood is collected from forests and around 5.92 percent from agricultural land. A miniscule amount is also bought from forest depots. People living in the buffer zone closest to the forest extract the maximum from forests, but as the distance from the forests increases, people source their fuelwood more frequently from forest depots. Range-wise validation with forest field staff confirmed this extraction pattern. Table 25: Fuelwood Extraction Pattern by Source Fuelwood Forest Cropland Depot (%) (%) (%) Hoshangabad District 88.84 5.92 0.76

Fuelwood in rural households is used for cooking (73 percent), heating water, heating rooms, festivals, marriages, and other occasions. Cooking includes cooking meals for the household as well as feed for the cattle. Among the cooking devices used, 80 percent of households use mud- based cooking stoves. Only 13 percent have liquid petroleum gas (LPG) connection. About 2 percent of the HHs have improved stoves. There were no reports of biogas-based cooking devices or kerosene or electric induction stoves being used. Interestingly in rural areas, it was observed that HHs tended to have biogas and LPG stoves due to various government promotion programs of the government promoting in addition to the mud stoves. Mud and stone stoves use fuelwood in conventional quantities. marriage others LPG Others water Improved 3% 1% 13% 1% heating (a) stoves (b) 8% festival 2% 4% room Mud/clay/ heating stone 11% With C Mud/clay/ 6% stone Without C Cooking 78% 73%

Figure 28: (a) Fuelwood Utilization Pattern, (b) Types of Stoves Used for Cooking

The survey results indicate that the amount of fuelwood used for various purposes is 33 kg/day/household (Table 26). In order to quantify the total amount of fuelwood used, the project extrapolated this to the total rural households within the district. As a result, it is estimated that 2,114.25 thousand tons of fuelwood is consumed annually by all rural households in Hoshangabad. As 88.84 percent of the total fuelwood consumed is extracted from forests, it is estimated that 1,878.30 thousand tons of fuelwood are extracted directly from forests annually.

42 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 26: Quantification of Fuelwood Extracted from Forests District Fuelwood per HH Total Annual Fuelwood Consumption (kg/day) (‘000 tons/year) Total 33 2,114.25 Extracted from forest 29.32 1,878.30

4.7.2 Fodder Fodder collection is another identified driver of forest degradation. As per the socio-economic survey, 18.76 percent of households collect fodder from forests, 37.26 percent collect fodder from cropland, and 43.98 percent purchase fodder (Table 27). Table 27: Fodder Collection by Source Fodder Forest Cropland Purchased (%) (%) (%) Hoshangabad 18.76 37.26 43.98

It was ascertained from the validation that cattle consume approximately 20–25 kg of fodder per day and goats consume 3–4 kg of fodder per day. Using this information and the number of livestock owned by the households surveyed, it is estimated that the amount of fodder required per household is 65.34 kg/HH/day. Further, the survey has revealed that fodder is consumed only for four months when cattle are not able to graze outside. Extrapolating per household number to all rural households in Hoshangabad, it is estimated that 1,398.37 thousand tons of fodder is consumed annually. Based on the number of households sourcing their fodder from forests, it can be estimated that 262.33 thousand tons of fodder are extracted from forests in Hoshangabad each year (Table 28). Table 28: Amount of Fodder Extracted in Hoshangabad

Fodder collected Fodder Consumed per HH Annually District (kg/day) (‘000 tons/year) Total 65.34 1,398.37 Forest 12.25 262.33

4.7.3 Grazing In the surveyed villages, 78.3 percent of the households let out their livestock graze in forests. About 19.4 percent of households graze their livestock in fallow croplands and in common grazing land in the villages. Only 2.3 percent of the households have indicated that their cattle are stall- fed. For about eight months in a year, cattle graze outside and no extra fodder is provided to them during this time. Rampant grazing has adverse impacts on growing stock and the regeneration capacity of forests. Table 29: Grazing Sources and Pattern Grazing Forest Cropland Others

Hoshangabad 78.3% 19.4% 2.3%

4.7.4 Small Timber Small timber species extracted from forests include Neelgiri, Babul, Rinj, Sagon, Saaja, Subabul, Arjun, and Baans. These are used for housing repair and maintenance, fencing, and making furniture, agricultural equipment, and tools. Households surveyed indicated that due to

43 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) mechanization, wood-based agriculture tools are sparsely used. Of all small timber, 72.4 percent comes from forests, 14.15 percent comes from cropland, and the rest comes from other sources. As per the survey, about 762.85 kg of small timber is used per year per household. If extended to the entire rural population, this amount is 134.16 thousand tons per year. Further, about 78.3 percent of the small timber consumed in rural households comes directly from forests. This amounts to 97.13 thousand tons of small timber (Table 30). Table 30: Small Timber Extraction Pattern by Source District Forest Cropland Plantation Purchased Trees Outside Forest Others Hoshangabad 72.4% 14.15% 0.73% 6.51% 5.82% 0.39%

Table 31: Amount of Small Timber Collected Small Timber Total Collection Collected (Kg/year) (‘000 tons/year) Total 762.85 134.16 From Forest 554.8 97.13

4.7.5 Large Timber The survey indicates that 72.53 percent of all large timber used by households is extracted from forests. About 11.44 percent comes from private plantations and 13.33 percent comes from trees outside forests. The remaining very small amount is purchased from forest depot. Each household consumes 226.30 kg of large timber annually. When extended to all households in the district, total consumption is estimated to be 39.21 thousand tons annually in rural Hoshangabad. As 72.53 percent of large timber is sourced from forests, it ca be estimated that each household in the district consumes 160.60 kg/year; when extended to all rural households in Hoshangabad, the total consumption is 28.44 thousand tons/year. Table 32: Amount of Small Timber Collected Large Timber Forest Plantation Trees Outside Forest Forest Depot Hoshangabad 72.53% 11.44% 13.33% 2.7%

Table 33: Large TIMBER QUANTIFICATION Small Timber Collected (Kg/Year) Total collection (‘000 tons/year) Total 226.30 39.21 From Forest 160.60 28.44

4.7.6 Non-Timber Forest Products Mahua flowers, Tendu patta, Chironjee, Mahua seeds, Harra, Bahera, Chirata, Kalmegh, Barks of Arjun, Rohini, Beejasal, Neem, and Aonla are the NTFPs that are collected from the forests in Hoshangabad. As per our survey, only 24 percent of the population collects NTFPs. About 50 kg/HH/day of Mahua flowers are collected during the 15-to-20-day season in Hoshangabad. In 2017 the Forest Department bought Mahua flowers for the first time at the rate of Rs. 30/kg on dry weight basis. The rate of Tendu patta collection is 250 bundles per household per season (which also lasts 15-20 days). Chironjee is collected at the rate 1.25 kg/HH/day for the same length of time. Mahua seeds can only be collected for 5–6 days a year, at a rate of 41.9 kg/HH/day. Harra collection is at the rate 0.63 kg/HH/day and Bahera fruits are collected at the rate of 0.88 kg/HH/day in rural areas in Hoshangabad, both for a 15-to-20-day season. The Chirata collection rate is 1.25 kg/HH/day in the survey area. Barks of Arjun, Rohini, Beejasaal,

44 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) and Neem are collected at the rate of 0.38 kg/HH/day and can be collected for three months a year. Further, aonla collection is at the rate of 17.5 kg/HH/day for a 15-to-20-day period each year. The collection rate for Kalmegh is 1.5 kg/HH/day. Table 34: Quantification of NTFP Collection NTFPs NTFP collection across district ‘000 tons Mahua Flower 15.80 Chironjee 0.79 Mahua seeds 26.46 Harra 0.39 Bahera 0.55 Chirota 0.95 Kalmegh 0.95 Barks of Trees 1.44 Aonla 11.06 Tendu patta 158* *Tendu patta is gathered in bundles of 1,000,000. 4.8 Carbon Loss from Forests Based on the household level survey, the team estimated consumption of various NTFPs in rural households in Hoshangabad. Table 35 details the annual consumption of fuelwood, fodder, small timber, and large timber. Forests clearly emerge as the dominant source of all these products collected by the villagers surveyed. Fuelwood and fodder emerge as the main drivers of degradation and deforestation in forests. Grazing is another driver, but it has not been quantified, as thus it is not possible to indicate clearly what is being consuming in addition to forest litter and grass. Table 35: Consumption and Share of Products Collected from Forests

Total Annual Share Collected from Consumption Forest (‘000 tons/year) (‘000 tons/year) Fuelwood 2,114.25 1,878.3 Fodder 1,398.37 262.33 Small timber 134.16 97.13 Large Timber 39.21 28.44

NTFPs such as Mahua flowers, Mahua seeds, Tendu patta, Chirata, Harra, Bahera, Kalmegh, Chiraunjee, Aonla, Barks of Arjun, Rohini, Beejasaal, and Neem are all collected from the forests in Hoshangabad. However, collection of Mahua flowers and Tendu patta dominates. These now have minimum reserve prices (MRPs) set by the government, and therefore are not subjected to market shocks, securing livelihoods of the people who depend on these NTFPs. The carbon calculations have been done using the following formula (based on IPCC 2006 guidelines and default values of emission coefficients). Carbon loss has also been estimated due to extraction of fuelwood, fiber, small timber, and large timber directly from forests

퐶푎푟푏표푛 푙표푠푠 = ∑ 퐴푛푛푢푎푙 퐶표푛푠푢푚푝푡푖표푛 ∗ 푐푎푟푏표푛 푓푟푎푐푡푖표푛 표푓 푑푟푦 푚푎푡푡푒푟 푙,푗푘 ∗ 푐푎푟푏표푛 푒푚푖푠푠푖표푛 푓푎푐푡표푟 Where I, j, and k represent the various drivers.

45 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Based on this, it is estimated that the annual carbon loss from forests due to extraction of fuelwood, fodder, large timber, and small timber is 407.92 thousand tons/yr. Table 36: Estimated Carbon Loss in Hoshangabad Due to Collection of Fuelwood, Fodder, Small, and Large Timber Source Fuelwood Fodder Small Timber Large Timber TOTAL (‘000 (‘000 (‘0000 (‘000 (‘000 Tons/year) Tons/year) Tons/year) Tons/year) Tons/year) Directly From 338.09 47.22 17.48 5.12 407.92 Forest

4.9 Validation of Results The results of the survey were presented for validation to Range Officers in Hoshangabad. The overarching goal of this activity is to design possible interventions to address deforestation and degradation in Hoshangabad District. This is incorporated into this Project Design Document prepared for developing a jurisdictional REDD+ project for the district. Feedback was taken on the driver source allocation and the potential interventions that can be propagated to address deforestation and degradation through discussions and in writing from each participant. Some of the key points that emerged from the validation are as follows: 1. Respondents in general agreed with the unplanned drivers identified through the survey. 2. LPG is being used to prepare meals for festive occasions by villages beyond 3 km from the forest; however, villages within that buffer continue to use wood for festivities. 3. LPG penetration is reported to be high in Itarsi and Sukhtawa and supply is stable. This is contrary to our survey results. 4. The livestock population in the region is depleting. Ten years ago, the average household households could have a maximum of 12 livestock; now they may have 3 or 4. This is in sync with survey findings. 5. People burn their crop residue, but this could be a source of fodder. 6. Lantana and wild basil have infested forests, leading to reductions in fodder. However, lantana can be used for making briquette and furniture. Many people are now being trained on this aspect. 7. Leopard and tiger attacks against livestock are frequent. The Forest Department compensates affected families at the rate of Rs 30,000 for mature cattle and Rs 3000 for goats. Crop loss due to attacks are also compensated by the Forest Department. 8. Grazing is done mainly in forest and in fallow cropland. 9. Women generally collect fuelwood from forests. They go in groups and cut the branches. Additionally, they pick up litter to sell. 10. The “Krishi Vaniki se Krishi Samridhhi” program to promote agroforestry has been launched by the State government.

46 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

5.0 Driver-Intervention Matrix 5.1 Introduction Based on primary and secondary studies as well as consultations held with the stakeholders in the district, a number of potential interventions were identified as a part of this project. In the following tables, all the intervention activities have been detailed out to describe the problems, solutions, and their implementation plans. 5.2 Interventions to Decrease Emissions from Forests Each intervention activity to address deforestation and degradation has specific objectives associated with it. The objectives could be better forest management, capacity building, governance, clean energy solutions (e.g., solar), improved cook stoves (ICS), etc. Intervention activities have been classified into different categories and details of the same are given below. S. No. Name of Intervention Drivers Addressed 1. Assisted natural regeneration in forests to stop Deforestation and forest degradation degradation due to extraction of 1 2. Afforestation/reforestation in non-forest lands fuelwood, NTFPs, 3. Agro-forestry activities encroachment, etc. 2 Creation and maintenance of fire lines in forests Community-based firefighting 3 Forest Fires 4 Permanent fire-camps and fire watchtowers Promoting sustainable extraction of NTFPs (Mahua flowers and seeds, tendu patta, etc.) through capacity building, 5 creating proper storage facilities and enterprises to NTFP extraction facilitate trade. Bio-fencing to reduce encroachment, illegal felling and 6 man-animal conflicts Encroachment, unplanned Smart patrolling to check unplanned extraction of forest felling 7 resources and unplanned mining within forest land Fuelwood plantations: Small timber and Large timber in private lands. Over-exploitation of timber for 8 Promotion of schemes like Krishi Vaniki and Krishi fuelwood procurement Samriddhi Alternate energy technologies for cooking in households, 9 community events Improved Cook Stoves for cooking in household and 9.1 community cooking during festivals and other social events Over-extraction of fuelwood from forests for cooking and 9.2 Improved cook stoves for cooking and cattle food preparation in households heating purposes Promotion of small and medium sized Biogas plants using 9.3 bio-degradable household waste like kitchen, agricultural,

livestock waste, etc. Construction of watchtowers, cattle-proof trenches (CPTs) Overgrazing, intrusion by wild 10 and installation of ultrasonic pest control system animals, man-animal conflict Fodder plantations (fallow lands, community lands, 11 agricultural field bunds) Overgrazing in forest lands 12 Fodder Densification and stall feeding

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Detailed Intervention Plans 1) Afforestation/Reforestation and ANR Activities 1. ANR in forests to stop degradation Name of the 2. Afforestation/reforestation in non-forest lands Intervention 3. Agro-forestry activities Code FM-ANR-MPFD Recent studies have concluded that due to anthropogenic pressure forests of Description of the Hoshangabad District are degrading further and there deforested. Through GIS problem analysis of satellite images revealed that, the rate of degradation over the past 15 years has been accounted. Plantation activities in identified degraded pockets through assisted natural Description of the regeneration (ANR) and gap plantation and identified non-forest pockets prone solution to deforestation (afforestation and reforestation) will help in enhancement of forest stock and increase forest and tree cover. Afforestation and reforestation both refer to establishment of trees on lands not currently having trees. Reforestation refers to establishment of forest on land that had recent tree cover, whereas afforestation refers to land that has been without forest for much longer. For such activities, it is stipulated that the identified land at the time of commencement of plantation is not a forest, and woody vegetation on the land is below the forest threshold as decided for the national GHG inventory; which is a crown cover of 10%. ANR is a method for enhancing the establishment of secondary forest from Detailed description degraded grassland and shrub vegetation by protecting and nurturing the mother of the technology trees and their wildlings inherently present in the area. ANR activities are focused on lands currently classified as forests (and which meet the minimum eligibility criteria for forests mentioned above), but which may not remain one in the future due to anthropogenic pressures from the drivers of forest change identified in the socio-economic surveys conducted in the landscape. Depending on the existing condition and canopy cover of the identified area, appropriate techniques and methods for plantations and development of the degraded landscape will be employed towards regenerating forest cover through selection of appropriate tree species, forest management, protection and monitoring. Institutional JFMCs/EDCs Partners 1. Non-availability of degraded areas on a suitable scale. 2. Lack of sufficient funds to undertake plantation activities across Identified Barriers Hoshangabad. 3. Lack of technology-driven cost effective monitoring of these plantations. 1. Training of forest department personnel and JFMCs on undertaking best land regeneration practices through trainings planned under REDD+. 2. Undertaking communication campaigns focusing on the benefits of forest conservation and enhancement. How will these be 3. Distribution of native tree species’ seeds and saplings for plantation to overcome through JFMCs and EDCs under an appropriate scheme. REDD+ project 4. Convergence of funds and schemes for better regeneration of degraded forest and non-forest land 5. Use the tools and techniques developed under the Forest-PLUS program for better monitoring of the forests where plantation activities have taken place. 1. Identification of degraded lands with clear boundary demarcation. 2. Selection of suitable native species to be used for regeneration of forest Implementation through consultations within the department Plan 3. Convergence of schemes and funds for implementing the plantation activities on the degraded lands.

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4. Expert consultations to identify, and attempt to overcome, expected challenges (environmental, ecological, and financial) for carrying out the regeneration of the degraded land. 5. Development of an Action Plan for administration and monitoring of the intervention with JFMCs and MPFD. 6. Year 3 onwards, further ANR to increase the forest stocks. This will be done in a phased manner. Socio economic surveys and consultations with the forest department has resulted in agreeing on Subabul, Khamer, Nilgiri, Katanga bamboo to be promoted for small timber and Sagon, Saja, Saal, Shishum for large timber. Along with these species Mango, Jackfruit, Jamoon species will be promoted as agro species crops. Progressive farmers in the district will be identified and trained on the sustainable farming and harvesting practices. These trained farmers will be used as trainers and they in turn train other farmers. Access to timber, fuelwood and fodder, increase the forest cover and health, and Co-benefits provide labor to people in plantation and site preparation activities, decrease incidents of landslides. All existing schemes and programs on afforestation, reforestation in the sites  National Afforestation Policy (NAP), National Afforestation and Eco- Development Board (Ministry of Environment, Forest and Climate Change [MoEFCC]) Potential schemes  State Compensatory Afforestation Fund Management and Planning Authority  Forestry and Environment Mission,  State Green Mission  Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)

2) Development of Fire Lines Name of the Creation and maintenance of fire lines in forests intervention: Code: FM-FIRE-FL Fire has long been integral part of the forest environment and has played an important role in shaping the flora and fauna. In MP, forest floors are burnt by the local people to collect mahua flowers in the month of March. Some fires are Description of the caused to promote better growth of tendu leaves as well as for better grass problem growth. Some fires are caused by negligence. Wildlife managers in MP use fires generally to keep grasslands free of weeds and woody growth, as well as to prevent more devastating fires (controlled burning). Fire protection is one of the most difficult tasks in MP as the season is extremely hot and dry. Development of ‘fire lines’ before the onset of the summer season to check the advance the forest fires. A fire line, also called a fire-break, is the traditional Description of the practice of burning a strip of vegetation and clearing the land so that if there is solution a fire, the flames don’t spread. Geo tagging of each fire line will be done to monitor forest fires. This will help in mapping the existing lines and also establish new ones if required fire lines. Fire lines ensure that in the event of a fire, it is confined to that particular area and does not spread. The bald patch of land helps cut off further combustion. Detailed description Fire lines are demarcated around a swathe of forest land covering a given area, of the technology usually a Beat or less, and the vegetation is normally burnt during the onset of winter as the moisture, including early morning mist, helps in controlled

49 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

burning.26 This geo tagged mapping will be monitored using satellites. Whenever forest fires occur satellite will trigger a warning message to forest fire controlling center to take further action on a real-time basis. 1. Local JFMCs/EDCs Partner institutions 2. Madhya Pradesh State Disaster Management Authority (MPSDMA) 1. Identification of forest areas vulnerable to fires in Hoshangabad district. 2. Training and capacity building of MPFD personnel and JFMC/EDC members to carry out controlled burning at selected sites in RFs. 3. Establishment of fire lines: Take up fire lines in Hoshangabad, by marking Implementation the most vulnerable and fire prone areas using latest technology and ground plan reconnaissance, and study of fuel availability and physio-geographic and other social angles. 4. Development of standard operating procedure (SOP) for maintaining the fire lines. 5. Create JFMC groups to help in creation and maintenance of the fire lines. 1. Lack of training and capacity of local community members to carry out Identified barriers controlled burning, maintain fire lines. 1. Undertaking communication campaigns to sensitize local communities on the ill-effects of forest fires, the common do’s and don’ts and the relevant How will these be precautions to be taken in forests overcome through 2. Supporting the capacity building of local MPFD personnel and local REDD+ project? communities towards forest fire management 3. Dissemination of best practices of fire management and preventing fire outbreaks Co-benefits Potential

convergence

3) Community-based Firefighting Name of the intervention: Community-based firefighting Code: FM-FIRE-COMM Description of the The problem of forest fire has been explained in the intervention given above. problem Apart from creation of fire lines, fire management activities undertaken in Description of the coordination with local JFMCs/EDCs to reduce the instances of fires in solution forestlands across the state are found to be very effective in controlling fire. Community involvement in forest fire management techniques and methods undertaken by the MPSDMA. This would include coordination in maintenance of fire lines and regulating access to forests among a suite of activities as per a Detailed description jointly-developed Action Plan. of the technology JFMCs and EDCs, along with already-present ones, will be strengthened through capacity building to assist the MPFD in carrying out its fire management activities. 1. JFMCs/EDCs Partner institutions 2. MPSDMA 1. Identification of forest areas vulnerable to fires in each district. Implementation 2. Identification of active JFMCs and EDCs in identified areas. plan 3. Training and capacity building of MPFD personnel and JFMC/EDC members to carry out specified forest fire management activities.

26 The Hindu. (2016, October 23). Forest officials bracing up for fire lines ahead of schedule. The Hindu. Retrieved from http://www.thehindu.com/news/national/karnataka/Forest-officials-bracing-up-for-fire-lines-ahead-of- schedule/article16079227.ece

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1. Lack of interest among local communities to participate in fire management Identified barriers 2. Irregular monitoring of vulnerable forest areas, making it susceptible to further fire attacks 1. Undertaking communication campaigns to sensitize local communities on How will these be the ill-effects of forest fires, the common do’s and don’ts and the need to overcome through take certain precautions when in forestlands. REDD+ project? 2. Supporting the capacity building of local MPFD personnel and local personnel towards forest fire management

4) Fire Camps and Fire Watchtowers Name of the Establishment of fire-camps and fire watchtowers intervention: Code: FM-FIRE-TOW Description of the The problem of forest fires is explained in the description of the intervention problem above. Establishing permanent fire camps and fire watchtowers in vulnerable forest Description of the areas in Hoshangabad for constant monitoring to avoid the initiation and spread solution of forest fires. Fire camps are campsites for firefighters and support personnel setup to monitor fires in areas which require large work force, logistics and organization. Detailed description Permanent fire camps setup in the identified vulnerable forest patches help in of the technology round-the-clock monitoring of the landscape to avoid the development of forest fires. Similarly, fire watchtowers ensure regular monitoring of forest fires in vulnerable areas by providing a panoramic view of the forestlands. 1. MPSDMA Partner institutions 2. Local JFMCs/EDCs 1. Identification of forest patches vulnerable to fires in each district. 2. Construction of fire camps and fire watchtowers from fire management funds earmarked under the annual budget of the MPFD in selected sites. Implementation 3. Training and capacity building of MPFD personnel to carry out specified plan forest fire management activities. 4. Development of an Action Plan for constant monitoring of sites to ensure no fire outbreak occurs. Identified barriers 1. Lack of funding for construction of fire camps and watchtowers. 1. Making available sustainable sources of funding for the development and How will these be maintenance of fire camps and watchtowers overcome through 2. Supporting the capacity building of local MPFD personnel and local REDD+ project? personnel towards forest fire management

5) Sustainable Harvesting of Mahua Name of the Promoting sustainable extraction of Mahua through capacity building, creating Intervention proper storage facilities and enterprises to facilitate Mahua trade. Code FM-MAH-PROM 30% of the Mahua collected is spoiled due to lack of proper storage facilities Description of the among the collectors. This leads them to sell Mahua at cheap rates only to problem procure it later at higher prices, thus inducing “distress selling.” Construction of Mahua storage facilities. Community storage needs to be done Description of the as one tribal cannot hold more than 5 kg Mahua flowers as per government solution rules. Promoting food products made from Mahua (kishmish, jam) and creating a market linkage for the same. Detailed description Storage of kernels at about 8% moisture level or better at 5 to 6% moisture level of the technology in Gunny bags with aluminum phosphide, would preserve the kernels well. Identified Barriers 1. Storage problem

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2. Markets not developed for Mahua products 3. Distress selling How will these be 1. Setting up storage units overcome through 2. Establishing market access for Mahua products REDD+ project 3. Creating awareness regarding distress selling and its prevention 1. Identifying farmers dependent on Mahua collection and sale 2. Identifying sites where kernel storing units can be constructed. 3. Exploring ideas on varied products from Mahua based on their market value Implementation 4. Creating self-help groups (SHGs) and producer companies for Mahua Plan products and other NTFPs 5. Creating market linkage between farmers and the consumer 6. Awareness creation and promotion of sustainable NTFP harvesting practices.

6) Bio-fencing to Counter Encroachment Name of the Bio-fencing to reduce encroachment, illegal felling and man-animal conflicts intervention: Code: FM-BRDR-PLANT Encroachment and illegal felling are some of the many causes of deforestation Description of the and forest degradation. Further, in areas where agricultural fields are situated problem adjacent to forestlands, there are frequent man-animal conflicts. Development of biological barriers such as agave plantation can stop the felling and transport of local timber out of Hoshangabad, while also acting as a barricade against animal incursion. These natural barriers would supplement Description of the existing efforts undertaken by the MPFD, like surveillance through watchtowers solution and procurement of night-vision glasses, to check these illegal activities. In addition, such vegetative barriers restrict animals from foraging on agricultural produce and causing crop damages. Agave plantations have been used across various states in India for live fencing due to its low maintenance requirements, growth of marginal lands and its soil binding properties. Agave leaves are thick and fleshy, and its tips are full of Description of spines.27 Rows of agave plantations would help check illegal encroachment, technology felling and transport of timber, as well as man-animal conflicts, by acting as a natural barrier. Other types of vegetation can also be explored to act as bio-fencing towards restricting these activities. 1. Lack of protection and maintenance of these bio-fencing techniques 2. Lack of capacity and training of local MPFFD personnel and communities Identified barriers towards bio-fencing 3. Destruction of such fences by encroachers 1. Undertaking communication campaigns on the benefits of natural barriers to restrict these activities. How will these be 2. Training and capacity building of JFMCs and local communities, in addition overcome through to convergence of central and state funds and schemes, on the plantation REDD+ project? and maintenance of these bio-fences 3. Distribution of saplings (e.g., agave or other thorny species) of plants which can be used for live fences 1. Training of MPFD personnel, JFMCs and local communities on the Implementation construction and maintenance of live fences plan 2. Identification of areas which are priority plantations to take up agave plantation, geo-tagging them.

27 Sarkar, M., & Sarcar A B. (n.d.). Agave, a multipurpose dryland plant. (D. M. A, Ed.) Retrieved from BioGov.in: http://biogov.in/article/agave-a-multipurose-dryland-plant/

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3. Ground reconnaissance, raising agave, planting them in the prescribed manner. 4. Development of strategies to converge the objectives of this intervention with other MPFD initiatives to check illegal felling and transport.

Figure 27: Agave plantation Co-benefits Decrease man-animal conflict, encroachment, and smuggling. Potential schemes Existing MPFD schemes

7) Spatial Monitoring and Reporting Tool (SMART) Patrolling to Check Unplanned Extraction of Forest Resources and Unplanned Mining within Forest Land Name of the SMART patrolling to check unplanned extraction of forest resources and intervention: unplanned mining within forest land Code: FML-PAT-MIN Description of the There are some instances of extraction of small rocks from the forests and break problem them into small pieces (gravel) and are sold in the market. Over a period of time, this practice affects the forest soil and leads to forest degradation. In the same way there are minor forest products, NTFPs, bamboos, etc., which are extracted in an unplanned manner. Smart patrolling can also check encroachment and forest fires. Description of the SMART is a combination of software, training materials and patrolling standards solution to help conservation managers monitor animals, identify threats such as poaching or disease and make patrols more effective. Regular patrolling by forest personnel will discourage encroachers to illegally retrieve rocks from forests. This will include: 1. GPS trackers in vehicles. 2. Night vision goggles. 3. Watch towers in certain RFs. 4. Tents. 5. Smart phones and apps

53 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Description of SMART provides rapid access to accurate conservation information for technology managers. Data is standardized and can be used to create maps, analyses and produce reports to help managers decide on the appropriate actions to take, and how to prioritize limited financial or staffing resources, and track changes in activity over time.

The SMART approach combines a cutting-edge, site-based management tool with capacity building and a set of protection standards. SMART supports truly adaptive management of a site—training and equipping rangers and protected area managers, gathering data on wildlife and threats, using the SMART software to store and analyze these data and critically using these reports and debriefs to better plan and target protection efforts. Institutional Forest Department partners JFMCs Identified barriers  Lack of willingness to utilize latest technology for patrolling purposes.  Lack of awareness on latest gadgets and apps for patrolling. How will these be  Capacity building workshops for training rangers and forest department overcome through personnel on SMART patrolling. REDD+ project? Implementation 1) Identification of target JFMCs and training them on SMART patrolling plan approach. 2) Capacity building across all ranges of forest personnel. 3) Training shall be provided on the following activities:  Define and manage patrolling schedules  Inform personnel about their Rota and send reminder through mobile app.  Track and record adherence to patrolling schedule  Maintain historical records of adherence through images/videos  Generate analytics for planning and reporting

8) Fuelwood Plantations: Small and Large Timber Name of the Small and Large Timber plantations intervention: Code: ALM-TIM-PLT A considerable population across the district depends on forests for fuelwood. Of the fuelwood used in Hoshangabad, it has been found that 89% is sourced directly from forests on average causing pressure on the district’s forests. Such extraction over time has led to the depletion of forest carbon stocks in Description of the Hoshangabad. problem Results from the socio-economic survey indicate that each rural household in Hoshangabad utilizes about 33 kg of fuelwood per day, part of which is used for fodder preparation. Also, it has been estimated that about 262 thousand tons of fodder is collected from the forests in Hoshangabad every year. Plantation of timber species in private forest and wasteland which can be used to meet the fuelwood and fodder demand of local communities for their bona- Description of the fide use. Successful plantation activities in private lands will help mitigate the solution pressure on forests, prevent encroachment of forests and help in reducing deforestation and forest degradation. Plantations carried out on private lands will help meet fuelwood demands of Detailed description local communities. Identification of suitable lands will be carried out in of technology consultation with the MPFD. Institutional mechanisms will be developed to enable the Department to provide the saplings of suitable fuelwood species.

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1. MPFD Institutional 2. Madhya Pradesh Department of Animal Husbandry (MPDAH) partners 3. Local JFMCs and EDCs 1. Lack of awareness about the ill-effects of fuelwood combustion. 2. Lack of incentives for private landowners to take up the plantation activities. Identified barriers 3. Restricted access to plantations for some vulnerable groups. 4. Lack of inter-departmental coordination to provide saplings and raw materials for plantation. 1. Undertaking communication campaigns on benefits of forest protection and enhancement. How will these be 2. Distribution of tree seeds and saplings for plantation to private land holders, overcome through where the land holders have to pay a subsidized amount for each sapling. REDD+ project? 3. Providing technical assistance to private landholders through the approaches developed under the Forest-PLUS Program. 4. Convergence of the programs and schemes to support private plantation. 1. Demarcation of private lands available to take up the plantation activity. 2. Assessment of the inclination and incentives available for plantation in private lands. 3. Preparation of plantation plans – selection of species, provision of inputs, etc. Implementation 4. Designing communication campaign for awareness of plantation and plan conserving forests in Hoshangabad 5. Calculation of benefits (in CO2 eq.) and costs (in INR), and presentation to the MPFD and Government of Madhya Pradesh 6. Development of an Action Plan for administration and monitoring of the intervention with the MPFD and Gram Panchayats, overseen by the REDD+ Cell Co-benefits Extra source of income for people, source of NTFP, fuelwood, timber, etc. Agro-forestry promotion schemes in Hoshangabad  Accelerated Fodder Development Programme, Department of Agriculture (Government of India [GoI]) Potential schemes  Sub-Mission on Agroforestry, National Mission for Sustainable Agriculture, GoI  MGNREGA  Krishi Samruddhi Yojana 9) Alternate Energy Technologies for Cooking in Households

8.1) Improved cook stoves (ICS) Name of the Improved Cook Stoves for cooking in household and community cooking during Intervention festivals and other social events Code ENE-ICS-HH/COMM In Hoshangabad, fuelwood continues to be mainly extracted from forests. Socio- economic survey indicates that about 78% of the fuelwood is collected from forests and around 21% from agricultural land. Rest is bought from Forest Description of the Depots. People living just next to the buffer zone extract maximum from forests, problem but as distance from forests increase, people source their fuelwood also from forest depot. The people to meet their energy demand remove forest resources illegally. Fuelwood is mainly used for cooking, heating water and cattle food preparation. Deployment of ICS as alternative cook stove for rural households and Description of the community establishments such as hostels to decrease fuelwood consumption solution and ease pressures on forests. ICS with better thermal efficiency, not less than 25%, will reduce the fuelwood consumption.

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The Ministry of New and Renewable Energy (MNRE) has approved some improved biomass cook stoves for widespread use across the country, as part of the Central Government-sponsored Unnat Chulha Abhiyan. As a part of pilot project a project was implemented to demonstrate the usefulness of the ICS at community level. Evaluation study conducted in Madhya Pradesh indicated reduction in fuel consumption in the range 40-60%, emission reduction in the rage 60-70% and saving cooking time in the range 10-30% compared to traditional chulha.28 Therefore, there is a potential for ICS in the region to promote ICS as an alternative cook stove in place of traditional stoves.

ICS with a minimum thermal efficiency of 25%29 can, on an average, save 3.5 tons of fuelwood annually over a lifetime of 5 years.30

Example: Greenway ICS at household level

Detailed description of the technology

Technical Specifications • Size: 9.8” x 7.6” x 11.6” • Materials: Steel and Aluminum with Bakelite Handles • Loading Capacity: 25 kg • Secondary Air Induction Mechanism: Yes • Warranty: 1 year • Fuel Savings: 65% • Smoke Reduction: 70% • Ergonomic front loading design 1. Social Forestry Department 2. Panchayat and Rural Development Department Institutional 3. Food, Civil Supplies and Consumer Affairs Department Partners 4. Planning and Development Department 5. Science and Technology Department 6. Gram Panchayats and Village Forest Committees (VFCs)/JFMCs 1. Lack of awareness about deleterious effects of fuelwood combustion and Identified Barriers resultant indoor pollution, 2. Lack of awareness about alternate efficient ways of cooking.

28 Ministry of New and Renewable Energy. (n.d.). National Biomass Cookstoves Programme. Retrieved from Ministry of New and Renewable Energy: http://www.mnre.gov.in/schemes/decentralized-systems/national-biomass-cookstoves-initiative/ 29 Minimum requirement as per MNRE. 30 Panwar, N.L.; Kurchania, A.K.; Rathore, N.S.; “Mitig Adapt Strateg Glob Change (2009) 14:569–578” (https://www.researchgate.net/profile/Nl_Panwar2/publication/225756958_Mitigation_of_greenhouse_gases_by_adoption_of_im proved_biomass_cookstoves/links/560a24ac08ae840a08d533e7.pdf)

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3. Cultural barriers to accepting new systems, and change in the “smoky” flavor. 1. Undertaking communication campaigns to sensitize communities towards alternative cooking systems and the ill-effects of fuelwood combustion. How will these be 2. Assisting in delivery mechanisms for uptake and installation and overcome through maintenance of ICS, by convergence under government schemes. REDD+ project 3. A centralized monitoring system on the efficacy of the cooking systems, and their uptake. 1. Using a scientific and objective decision support system to identify locations of maximum benefit for rollout of these activities through funding from other convergence activities. Implementation 2. Development of an Action Plan for the administration and monitoring of Plan these interventions, together with the identified institutional partners and the forest department 3. Facilitating distribution of ICS through existing schemes and co-financing.  Contribution to Sustainable Development Goal (SDGs), - Goal 1 – No poverty: Time saved in collection of fuelwood can now be utilized for livelihood generation activities; savings in cost accrued on illness of women and children due to indoor pollution; improved access to micro-finance; skill development; pollution-free kitchens will lead to better standard of living - Goal 2 – Zero Hunger: Efficient cooking devices and saved time from collecting fuelwood will result in better food for women and children tackling the issue of malnutrition/hunger. - Goal 3 – Good health and well-being: decreased indoor air pollution, Co-benefits decreased burden on travelling distances and collecting fuelwood - Goal 4 – Quality Education: Not having to collect as much fuelwood will free time for children, especially adolescent girls, to invest in education. - Goal 5 – Gender Equality: Access to better cooking will ultimately lead to women empowerment - Goal 7 – Affordable and clean energy - Goal 13 – Climate Action: Reduced GHG emissions due to efficient fuel consumption - Goal 15 – Life on land: reduce emissions due to deforestation and degradation; and to conserve forests and terrestrial ecosystems. Potential schemes Unnat Chulha Abhiyan

8.2) ICS for Fodder Preparation in Households Name of the Improved Cook Stoves for cooking and cattle food preparation in households intervention: Code ENE-ICS-FODD Households in Hoshangabad typically own several animals – cows, buffaloes, ox and goats – due to which the district has a sizeable livestock and poultry population.

Description of the For preparation of animal feed, fuelwood is utilized for preparation on problem conventional stoves. These activities result in a sustained fuelwood demand and significant amounts of thermal energy loss. Results from the socio-economic survey indicate that each rural household in Hoshangabad utilizes about 33 kg of fuelwood per day, part of which is used for cattle food preparation. Improved Cook Stoves distributed to beneficiaries for preparation of animal feed Description of the in households and community establishments. The provision and use of these solution ICS would significantly bring down the pressure on forests for fuelwood provision and help maintain forest carbon stocks in Hoshangabad. Analysis of

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the effects of these measures to inform subsequent scaling up of the intervention. The MNRE has approved some large improved biomass cookstoves for widespread use across the country, as part of the Central Government- sponsored Unnat Chulha Abhiyan. These ICS can also be utilized for fodder preparation at the individual/community levels. Some of these are31: Power Thermal Model Manufacturer output efficiency (kW) (%) XXXL Plus Alpha Renewable Energy Pvt 3.78 35.52 Stove Ltd, Anand () Sacks Right Energy Detailed description Ojas-M06 Innovations, Bengaluru 5.43 35.11 of the technology (Karnataka) Vikram Stoves and Vikram Jumbo Fabricators, Osmanabad 3.64 28.1 Bio Super () Digvijay Digvijay Sales and Community Engineering, Beed 4.2 30.28 Chulha (Maharashtra)

Appropriate large ICS will be chosen for identified villages to regulate fuelwood demand towards cattle food preparation. 1. Panchayat and Rural Development Department (PRDD) Institutional 2. MPDAH partners 3. Gram Panchayats and local JFMCs/EDCs 1. Lack of awareness about deleterious effects of fuelwood combustion Identified barriers 2. Lack of awareness about alternate efficient sources. 3. Cultural barriers towards take-up of new technologies 1. Undertaking communication campaigns to sensitize livestock and poultry owners about the ill-effects of fuelwood combustion. How will these be 2. Assisting in delivery mechanisms for uptake of these ICS through overcome through convergence with the PRDD and MPDAH. REDD+ project? 3. Monitoring of distributed ICS with coordination from Gram Panchayats and local MPDAH personnel. Each village in Hoshangabad to be provided with one community cook stove each under the project. This community cook stove will demonstrate the Implementation efficiency of large cook stoves for preparation of food for livestock. An active plan communication will describe the advantages of such an improved cook stove. Interested people can then purchase them from the market. 100% of the cost of the devise is through co-financing and not from the project. Better health of women and children, decrease in indoor pollution, contribution to SDGs, decrease drudgery in collection of fuelwood, economical benefit as Co-benefits more time will be available for any income generation activity, skill development, better education as children will be freed from collection of fuelwood, improved standard of living. Potential Pradhan Mantri Ujjwala Yojana, Unnat Chulha Abhiyan convergence

31 Approved Models of Portable Improved Biomass Cookstoves, Ministry of New and Renewable Energy.

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8.3) Promotion of Biogas Plants Name of the Promotion of small and medium sized Biogas plants using bio-degradable Intervention household waste like kitchen, agricultural, livestock waste, etc. Code ENE-BIO-HH In Hoshangabad, fuelwood continues to be mainly extracted from forests. Socio economic survey indicates that about 78% of the fuelwood is collected from forests and around 21% from agricultural land. Rest is bought from Forest Description of the Depots. People living just next to the buffer zone extract maximum from forests, problem but as distance from forests increase, people source their fuelwood also from forest depot. The people to meet their energy demand remove forest resources illegally. Fuelwood is mainly used for cooking, heating water and cattle food preparation. Biogas is a renewable energy source. A typical family type biogas plant generates biogas from organic substances such as cattle –dung, and other biodegradable materials such as biomass from farms, gardens, kitchens, etc. Description of the The process of biogas generation is called anaerobic digestion. Biogas plants solution are ideal for households with livestock towards, community hostels with enough kitchen waste becoming self-dependent for the provision of cooking gas and enriched bio-manure. Biogas mainly composed of 60% of methane (CH4) and is generated by fermentation of cellulose-rich organic matter under anaerobic conditions. The optimum utilization depends upon the successful physical installations, which in turn depend upon plant design and its selection. The basic conversion principle is that when a non-ligneous biomass is kept in a closed chamber for a few days, it ferments and produces an inflammable gas (methane). The anaerobic digestion consists of three stages: Hydrolysis; Acid Formation and Methane Fermentation. Under the National Biogas and Manure Management Programme (NBMMP), the MNRE promoting biogas and provides subsidies for biogas installation at household level. One such biogas model promoted under the scheme is Detailed description Dheenabandhu model. The model is well known in India and is known for of the technology effective methane recovery and combustion32. Its technical specifications are as follows.33

Specification Value Capacity 2 m3 Mixing Proportion (Water: 1:1 Dung) Feed Material Cattle Dung or organic waste Flow rate 0.47 m3/hr Number and size of burners 2 burners of 4” size

32 National Biogas and Manure Management Programme (NBMMP), Section 3, Technology. http://www.mnre.gov.in/schemes/decentralized-systems/schems-2 33 Nijaguna, B. (2007). Biogas Technology. New Age International Pvt Ltd Publisher

59 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

60 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

1. Panchayat and Rural Development Department 2. Horticulture department Institutional 3. Food, Civil Supplies and Consumer Affairs Department Partners 4. Planning and Development Department 5. Science and Technology Department 6. Gram Panchayats and VFCs 1. Lack of awareness about deleterious effects of fuelwood combustion and resultant indoor pollution, 2. Lack of awareness about biogas and it uses Identified Barriers 3. Cultural barriers to accepting new systems, and change in the “smoky” flavor. 4. Lack of capacity towards installation and maintenance of biogas plants. 1. Undertaking communication campaigns to sensitize communities towards alternative cooking systems and the ill-effects of fuelwood combustion. How will these be 2. Assisting in delivery mechanisms for uptake, installation, and maintenance overcome through biogas plants by convergence under government schemes. REDD+ project 3. A centralized monitoring system on the efficacy of the cooking systems, and their uptake. 1. Using a scientific and objective decision support system to identify locations of maximum benefit for rollout of these activities through funding from other projects. Implementation 2. Development of an Action Plan for the administration and monitoring of Plan these interventions, together with the identified institutional partners. 3. Facilitating distribution of biogas through existing schemes and co- financing. Contribution to SDGs, - Goal 1 – No poverty: Time saved in collection of fuelwood can now be utilized for livelihood generation activities; savings in cost accrued on illness of women and children due to indoor pollution; improved access to micro-finance; skill development; pollution-free kitchens will lead to better standard of living - Goal 2 – Zero Hunger: Efficient cooking devices and saved time from Co-benefits collecting fuelwood will result in better food for women and children tackling the issue of malnutrition/hunger. - Goal 3 – Good health and well-being: decreased indoor air pollution, decreased burden on travelling distances and collecting fuelwood - Goal 4 – Quality Education: Not having to collect as much fuelwood will free time for children, especially adolescent girls, to invest in education. - Goal 5 – Gender Equality: Access to better cooking will ultimately lead to women empowerment

61 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

- Goal 7 – Affordable and clean energy - Goal 13 – Climate Action: Reduced GHG emissions due to efficient fuel consumption - Goal 15 – Life on land: reduce emissions due to deforestation and degradation; and to conserve forests and terrestrial ecosystems. Potential schemes NBMMP

10) Construction of watchtowers, CPTs and installation of ultrasonic pest control system Name of the Construction of watchtowers, CPTs and installation of ultrasonic pest control intervention: system Code: FML-DBN-ENC The lack of artificial boundaries of a number of reserve forests leads to encroachment and regular felling and extraction of resources from the forest reserves. Ecological and social surveys conducted in the landscape indicate that Description of the Reserved Forests in Hoshangabad suffer from illegal encroachments due to lack problem of proper demarcation, unauthorized cattle grazing and lack of soil conservation leading to riverine and gully formations. Crop raiding and livestock damage by the wild animals has been observed in the region. There is a need for strict vigilance through watchtowers to manage the boundary line of the reserve forests and proper demarcation with fixing of pillars in the division.

Construction of CPTs, as well as other relevant measures like installation of acoustic devices like the ultrasonic pest control system, to counter the multi- faceted challenges that RFs face in the Hoshangabad.

CPTs are multi-purpose and useful towards forest management, utilizing least Description of the amount of resources for maintenance and construction. These can be solution constructed under MGNREGA funds through convergence with other state government departments by looking at various models practiced in different landscapes across India.

Acoustic devices are used to repel wild pests from entering into the crop fields, ensuring crop protection. This ultrasonic pest control system has been successfully pilot-tested in Chandaney area located in East Sikkim, which is another landscape under the Forest-PLUS Program. The device that was installed is called Grus Q-3 Harmony and it produces sounds of 17-18 wild animals. This device is environmental friendly and uses solar energy.

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Figure 10.1: Solar powered acoustic device

Figure 10.2: Acoustic device being installed under a mitigation pilot program in Sikkim, which can be replicated in MP. A watchtower is simply a structure with a platform a few meters high that can support one or two people and from which the surrounding area can be observed. It can be either on a tree or as a stand-alone structure.

Description of the For CPTs: technology Common dimensions of such trenches are 3m wide at the top, 1m wide at the bottom and 2m deep. The design of the CPTs may also depend on the challenge that needs to be addressed : - For cattle grazing, trench size of at least 4ft deep and 4ft wide. - For encroachment, trench size of 3ft high and 3ft wide.

63 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

- For erosion control, trench size of 3ft high and 3ft wide. These trenches are constructed after identification of vulnerable areas on the forest fringes where encroachment activities, man-animal conflicts and other issues have been repeatedly observed.

Other relevant measures that can be considered include the utilization of used rail tracks sourced from the Indian Railways for fencing purposes. This has already been tried on an experimental basis in Assam.

An acoustic device is an ultrasonic pest controlling system which works on multi- frequency modulated sound. Devised to produce sounds of multiple animals, the acoustic device is able to repel pest and wild animals which are responsible for crop raiding as well as man-animal conflicts. Institutional MPFD, JFMCs partners  Lack of properly defined boundaries in reserve forests.  Lack of awareness among communities regarding reserve forests.  Lack of capacity among the JFMCs.  There are reports that animals get injured in tea garden areas after falling Identified barriers into the deep tranches, dug within the garden areas for drainage of water.  Lack of funding towards construction of trenches  Lack of participation of local communities and VFCs towards construction  Defective construction and lack of maintenance  Regular surveillance will check encroachment. How will these be  Training campaign among communities regarding the importance of reserve overcome through forests. REDD+ project?  CPTs will make sure animals are not injured and man-animal conflicts are reduced. 1) Proper demarcation of reserve forests with help of the Forest Dept. 2) Creating awareness among JFMCs and concerned forest communities regarding management of reserve forests. 3) Construction of watch towers & posting of staff on 24 hours duty during most vulnerable periods. 4) Vaccination of cattle near the fringe villages needs to done regularly and awareness camp & animal health camps needs to be conducted with the Implementation help of veterinary doctors regularly. plan 5) JFMCs (or EDCs) need to be activated & awareness to be given on protection to wildlife. 6) Provision of funds to public for construction of stone wall/solar electric fencing around agricultural fields. 7) Construction of watchtowers & posting of staff on 24 hours duty during most vulnerable periods. 8) Training of JFMCs and local population on using acoustic devices 9) Exploring various models of trench construction

11) Fodder Plantations Name of the Fodder Plantations in fallow lands, community lands, and agricultural field bunds intervention: Code: FM-FUE-FODD It is estimated that there are 770,135 livestock in the district, which require a constant supply of fodder and pasturelands. The raising of poultry, ducks, goats, Description of and pigs are major backyard activities of the rural households for food and nutrition. the problem There are 175,529 rural households in Hoshangabad (Census 2011), with average of 4 livestock per household. From the socio-economic survey conducted in the

64 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

landscape, it was found that 78.3% of the cattle goes for open grazing. Around 19% of the surveyed households revealed they collect fodder from forests. This leads to pressures on existing lands to provide fodder and pastures. Description of Development of silvipastoral models to meet the pasture demands of local livestock the solution and to provide for the cultivation of trees for fuelwood purposes. Silvipastoral systems advocate the cultivation of trees simultaneously with the cultivation of grasses and forage. In this system, the space between individual tree specimens in silvipastoral and hortipastoral systems will be utilized for cultivation of grasses and forage for livestock. In-situ grazing will be provided for livestock Detailed throughout the year (in silvipastoral systems) and for a period of 3-4 months during description of the fruiting season (in hortipastoral systems). In addition, foliage to be made available technology for livestock consumption.

Institutional mechanisms will be developed to enable the MPDAH to provide saplings for suitable fodder species. 1. MPFD Partner 2. JFMCs/EDCs/SHGs and Gram Panchayats institutions 3. Horticulture Mission, Agriculture Department 1. Lack of awareness and knowledge of silvipastoral and hortipastoral practices and their benefits 2. Lack of resources and capacity of local communities towards the development Identified barriers and monitoring of silvipastoral landscapes. 3. Lack of coordination among institutions for the deployment of this intervention, along with other financial and technical towards adoption of these modern techniques 1. Undertaking communication campaigns on benefit of forest conservation, importance of silvipastoral and hortipastoral practices How will these be 2. Training and capacity building on silvipastoral and hortipastoral practices overcome 3. Distribution of ecologically adaptive and agro-climatically suitable tree species through REDD+ seeds and saplings for silvipastoral and hortipastoral plantations project? 4. Financial, technical and institutional support to overcome the barriers of silvipastoral and hortipastoral practices 1. Identification and selection of suitable lands for adoption of silvipastoral activities 2. Designing of silvipastoral and hortipastoral activities in consultation with experts and institutions and agencies like local NGOs, SHGs and others. 3. Training, capacity-building and promotion of silvipastoral and hortipastoral Implementation activities plan 4. Facilitating distribution of seeds of ecologically adaptive and agro-climatically suitable species 5. Convergence of public funds and schemes for promoting and implementing silvipastoral and hortipastoral practices 6. Development of an Action Plan for administration and monitoring of the intervention with Gram Panchayats, JFMCs, and DoEF. Co-benefits Source of fodder and decrease in soil erosion. Potential  Sub-Mission on Fodder and Feed Development, National Livestock Mission schemes (Government of India)  Accelerated Fodder Development Programme, Department of Agriculture (Government of India)

12) Fodder Densification and Stall Feeding Name of the Fodder densification and stall feeding intervention: Code: ALM-FODD-FD

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Due to climate variations, sustenance of livestock production is at threat due to scarcity of fodder during drought periods. Also, for a majority of illiterate and semi- Description of literate farmers to compute a balanced feed for animals. Crop residues, which are the problem otherwise suitable for animal feeding are quite often burnt in the paddy fields or destroyed gradually without in utility.

Densification of roughages and waste crop residues in compact blocks is an effective solution for livestock feed management. The digestibility of crop residues and other low quality forages can be increased through the action of rumen microbes by strategically mixing nitrogen and minerals that are deficient in these feed resources.

The increase in digestibility of crop residues and low quality forages, in turn also increases their intake. Both these phenomena enhance the efficiency of nutrient utilization from these feed resources in animal food chains. Fodder densification machines are based on the formation of a complete diet in the form of densified feed blocks or pellets from straws mixed with minerals, oil seed cakes and other agro-industrial by-products.

Description of This technology will enhance income of farmers, decrease environmental pollution the solution and help alleviate shortage of good quality seeds in tropical countries. In addition, the feed produced in the densified form as blocks or pellets could also provide complete feed to livestock in emergency situations. This will also enable efficient and cost-effective transport of fodder upon its densification into fodder blocks where up to 10 tons of feed block can be easily transported in a truck as against 4 ton loose fodder.

Fodder Cultivation Scheme for production of oat grass was not very popular, hence it was discontinued 2 years earlier. It can be started on a pilot basis in one or two villages.

Absence of feed mill in the district the main cause of lack of quality feed for cattle which is the main obstacle for promoting stall feeding. Quality fodder and feed production can be promoted in some of the fringe villages of forest villages. Detailed description of the The Densified Total Mixed Ration Block (DTMRB) technology has mostly been technology developed in India, through the collaborative efforts of animal nutritionists and feed technologists. It is different from the green forages or silage based complete feeds (Schroeder and Park, 199734). Since the fibrous crop residues are low density feeds, apart from difficulties in its handling and transportation, making a densified block from this loose and lighter stuff is challenging. A different approach and machinery are required for making such blocks from these residues and other dried roughages such as tree leaves and forest grasses.

The first step in the process of making straw based feed blocks is the grinding of concentrate ingredients, followed by their mixing and addition of the feed additives. This is then followed by mixing of these ingredients and straw in proper proportions along with addition of molasses in a specifically designed TMR mixer, taking care that mixing is uniform and ingredients are not separated due to gravity. Finally, the weighed quantity of the mixed stuff is transferred into a hydraulic press to get the final product – the DTMRB.

Machinery Needed

34 Schroeder, J.W. & Park, C.S. 1997. Using a total mixed ration for dairy cows. Available at http:// www.ag.ndsu.edu/pubs/ansci/dairy/as769.pdf

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 A grinder (hammer mill) and a mixer is required for making a normal concentrate mixture.  A specially designed total mixed ration mixer is required for mixing weighed quantities of low density crop residue (straws, bagasse, dried forest grasses, dried tree leaves, etc.) and the high density concentrate. Molasses and any other liquid feed additive are also added at this stage. The mixing is done through vertical motion, so that there is no separation due to gravity  Weighed quantity of the mixed ingredients is transferred into densification machine (works on the principle of hydraulic compression) which compresses the forage and concentrate mixture into densified complete feed block.

Machines of different capacities and different efficiencies are available in India. Installed capacity can vary from 0.5 to 3 tons per hour, which requires a motor of 20–40 horse power having a power consumption of 12–16 KW per ton. These machines can produce feed blocks weighing from 7 kg to 30 kg. Partner institutes MPFD, Food and Agriculture Organization of the United Nations (FAO), MP Department of Animal Husbandry  Insufficient nutrient provision to livestock  Lack of technical know-how to make densified fodder blocks in the region. Identified barriers (technical barrier)  Lack of financial resources (financial barrier) How will these be  Efficient nutrients delivery system – less feed wastage overcome  Provision of training and setting up of required machinery through REDD+ project?  Easy credit facilities Implementation  Fodder densification through establishing of fodder banks and promotion of plan fodder grasses and legumes.  DTMRB can be effectively utilized as a combined source of protein, energy and minerals during drought situations. They also help in preventing loss of fertility in case of prolonged drought.  Establishment of fodder banks for storing and distribution of dry fodder.  The existing Gaushalas in the region should be made use of for storing and distribution of dry fodder/ feed blocks.  Fodder grasses and legumes of Cenchrus ciliaris, Chloris gayana, Dichanthium, Stylosanthes, Clitori needs to be propagated especially in the common grazing lands

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Co-benefits Fodder availability throughout the year for livestock. Better health of livestock because of optimum nutrient intake. Increased productivity of livestock. Potential  Sub-Mission on Fodder and Feed Development, National Livestock Mission convergence (Government of India)  Accelerated Fodder Development Programme, Department of Agriculture (Government of India)

Additional ideas  Introduction of biomass briquettes using waste biomass and invasive species will help reduce fuelwood consumption. In addition, they will lead to the following benefits: - Check the breakout of invasive species causing deterioration of forest health - Provide an outlet for disposal of agricultural and animal feed wastes - Make available organic fertilizer and opportunities for non-farm-based livelihoods - Reduce health hazards from smoke and high emissions from burning fuelwood and biomass  High resolution mapping of forestland and reconciliation of land records, with annual monitoring of forestland using high-resolution data.  Capacity development of front-line staff to deal with encroachment cases.

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6.0 Quantification of Emission Reductions 6.1 Introduction The jurisdictional baseline start date and timeline has been described in Chapter 2. The baseline will be aligned every 10 years. The six IPCC LULC classes (forestland, cropland, grassland, wetland, settlement and other land) have been distinguished and the area under each classification has been detailed. The LULC classes have been further sub-divided into forest strata to achieve the goal of defining classes that are homogeneous in forest carbon stock density. Predominantly, two forest types have been found in the forestlands in Hoshangabad. These forests have been further sub-divided based on canopy densities, so as to accurately pinpoint forest degradation. Land transitions within the same forest types have been mapped between different density classes and between forest classes and non-forest classes, so as to estimate rates of degradation and deforestation. 6.2 Historical Reference Periods The land transitions from 2002 to 2009 and from 2009 to 2013 were analyzed. The average of these two transitions was used to create the baseline transitions. The mean rate of LULC transition over the historical period has been calculated and is represented in the emissions reductions spreadsheet. 6.2.1 Organic Matter Content For the aboveground live (AGL), aboveground dead (AGD), belowground (BG), and soil organic matter (SOM) pools, the average stock densities of stratum 풊 and associated statistics are calculated as per the equation:

OMo(i) = average (OMo,plot−wise(i, p))

Stratum-specific average organic matter can be estimated by summing organic matter in different carbon pools. Subsequently, the average total carbon stock is calculated by applying the carbon fraction. Summation of average carbon stock densities of LULC stratum i, pool o (Mg C ha-1) shall give the average carbon content of that specific stratum. Equations 23, 24 and 25 of the applied methodology have been used to arrive at these figures.

OM(i) = ∑ OMo (i) o

Co(i) = CF. OMo(i)

C(i) = ∑ Co (i) o Where: Average plant-derived organic matter of LULC class or forest 푂푀(푖) = stratum 푖. [MG DM ha-1] Plant-derived organic matter of LULC class or forest stratum 푖 in 푂푀 (푖) = 표 pool 표. [Mg DM ha-1] Average carbon stock density of LULC class or forest stratum 푖 퐶표(푖) = in pool 표. [MT C ha-1] 퐶퐹 = Carbon fraction of dry matter in wood (default = 0.5). [Mg C (Mg DM)-1]

69 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

퐶(푖) = Average carbon stock density of LULC class or forest stratum 푖. [MT C ha-1]

Table 37: Organic Matter content in Above Ground (AGL) and Below Ground (BG) Biomass Class/Stratum Stratum (i) C (i) (tC/ha) Dry Deciduous 10-30 DD 10-30 80.5 Dry Deciduous 30-50 DD 30-50 114.5 Dry Deciduous 50-70 DD 50-70 124.8 Dry Deciduous Above 70 DD Above 70 115.1 Mix Dry Deciduous 10-30 MMD 10-30 91.0 Mix Dry Deciduous 30-50 MMD 30-50 95.4 Mix Dry Deciduous 50-70 MMD 50-70 147.3 Mix Dry Deciduous Above 70 MMD Above 70 160.9 6.2.2 Emissions Factors The Emission Factor for AGB has been calculated as: ퟒퟒ 퐄퐅 (퐂퐒ퟏ → 퐂퐒ퟐ) = . (퐂 (퐂퐒ퟐ) − 퐂 (퐂퐒ퟏ)) 퐀퐆퐋 ퟏퟐ 퐀퐆퐋 퐀퐆퐋 Where:

퐸퐹퐴퐺퐿(퐶푆1→퐶푆2) = Emission factor for change in aboveground live plant organic matter from an LULC class or forest stratum (CS) 1 to 2. [tCO2e ha-1] 퐶푆1→퐶푆2 = Land transition from LULC class or forest stratum 1 to 2. 퐶퐴퐺퐿(푖) = Carbon density of aboveground plant organic matter of classes or forest stratum 푖. [MT C ha-1]

The Emission Factor for Below Ground Biomass (BGB) must also be must be gradually spread over time. The project proponent may propose their own temporal component (e.g., an exponential equation) if the conservative nature of the temporal component can be demonstrated using peer-reviewed literature or measurements conducted by the project proponent. Here, the default temporal component has been calculated from: For t < 10: ퟒퟒ (푪 (푪푺ퟐ) − 푪 (푪푺ퟏ)) 푬푭 (푪푺ퟏ → 푪푺ퟐ, 풕) = . 푩푮 푩푮 푩푮 ퟏퟐ ퟏퟎ For t > 10:

푬푭푩푮(푪푺ퟏ → 푪푺ퟐ, 풕) = ퟎ Where:

퐸퐹퐵퐺(퐶푆1→퐶푆2,푡) = Emission factor for change in belowground plant organic matter from an LULC class or forest stratum (CS) 1 to 2 at 푡 years after transition. [tCO2e ha-1] 퐶푆1→퐶푆2 = Land transition from LULC class or forest stratum 1 to 2. 퐶퐵퐺(푖) = Carbon density of belowground plant organic matter of classes or forest stratum 푖. [MT C ha-1]

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For this project, the default value has been chosen for the temporal component for BGB, which is 10 years. The emission factor have been calculated and is represented in the emissions reductions spreadsheet attached with the PDD.

From

AG+BG L Carbon To content tC(ha)

Dry Deciduous 10-30 Deciduous Dry 30-50 Deciduous Dry 50-70 Deciduous Dry 70Above Deciduous Dry 10-30 Deciduous Dry Mix 30-50 Deciduous Dry Mix 50-70 Deciduous Dry Mix 70Above Deciduous Dry Mix Cropland Waterbodies Grassland Otherland Settlement

80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 Dry Deciduous 10-30 80.55 0.00 33.96 44.22 34.57 10.47 14.81 66.77 80.34 -80.55 -80.55 -80.55 -80.55 -80.55 Dry Deciduous 30-50 114.51 -33.96 0.00 10.26 0.61 -23.49 -19.15 32.81 46.38 -114.51 -114.51 -114.51 -114.51 -114.51 Dry Deciduous 50-70 124.77 -44.22 -10.26 0.00 -9.65 -33.75 -29.41 22.54 36.12 -124.77 -124.77 -124.77 -124.77 -124.77 Dry Deciduous Above 70 115.12 -34.57 -0.61 9.65 0.00 -24.10 -19.76 32.19 45.77 -115.12 -115.12 -115.12 -115.12 -115.12 Mix Dry Deciduous 10-30 91.02 -10.47 23.49 33.75 24.10 0.00 4.34 56.30 69.87 -91.02 -91.02 -91.02 -91.02 -91.02 Mix Dry Deciduous 30-50 95.36 -14.81 19.15 29.41 19.76 -4.34 0.00 51.96 65.53 -95.36 -95.36 -95.36 -95.36 -95.36 Mix Dry Deciduous 50-70 147.32 -66.77 -32.81 -22.54 -32.19 -56.30 -51.96 0.00 13.58 -147.32 -147.32 -147.32 -147.32 -147.32 Mix Dry Deciduous Above 70 160.89 -80.34 -46.38 -36.12 -45.77 -69.87 -65.53 -13.58 0.00 -160.89 -160.89 -160.89 -160.89 -160.89 Cropland 0.00 80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 Waterbodies 0.00 80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 Grassland 0.00 80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 Otherland 0.00 80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 Settlement 0.00 80.55 114.51 124.77 115.12 91.02 95.36 147.32 160.89 0.00 0.00 0.00 0.00 0.00 6.3 Baseline and Project Scenario From the ecological and spatial analyses conducted across Hoshangabad District, the REDD+ baseline developed for Hoshangabad depicts patterns of LULC changes per year (in ha/year). Similarly, LULC changes in the project scenario have been estimated, where no transitions are expected across LULC categories and land area under each category remains constant. These scenarios have been represented in the emissions reductions spreadsheet in annexure.

Area 2013

LULC (ha) 10-30 Deciduous Dry 30-50 Deciduous Dry 50-70 Deciduous Dry 70Above Deciduous Dry 10-30 Deciduous Dry Mix 30-50 Deciduous Dry Mix 50-70 Deciduous Dry Mix 70Above Deciduous Dry Mix Cropland Waterbodies Grassland Otherland Settlement DD 10-30 3493.8 0 -10364 -4743 -127 0 0 0 0 150 5385 558 49 2322 DD 30-50 24055.3 26060 0 -18360 -31 0 0 0 0 1239 19145 1500 223 9375 DD 50-70 95402.1 29383 51657 0 12029 0 0 0 0 3965 22251 2258 351 11324 DD Above 70 1647.7 96 11 -2400 0 0 0 0 0 41 70 18 1 106 MMD 10-30 2275.6 0 0 0 0 0 -619 -4486 242 607 7002 1545 51 1617 MMD 30-50 12260.3 0 0 0 0 1161 0 -60522 1915 225 3038 579 41 1639 MMD 50-70 92882.7 0 0 0 0 18588 199344 0 151651 1590 7446 2036 248 3800 MMD Above 70 6587.2 0 0 0 0 -222 -2079 -86903 0 26 39 48 2 34 WATERBODIES 17743.2 0 0 0 0 0 0 0 0 0 0 0 0 0 CROPLAND 386256.8 0 0 0 0 0 0 0 0 0 0 0 0 0 OTHERLAND 19346.4 0 0 0 0 0 0 0 0 0 0 0 0 0 SETTLEMENT 6137.2 0 0 0 0 0 0 0 0 0 0 0 0 0 GRASSLAND 2611.5 -1 0 0 0 -1 0 0 0 0 0 0 0 0

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6.4 Net Emissions Reductions Emissions reductions from the project are given below: Table 38: Emissions Reductions from the REDD+ Project Year Emission Reductions (tCO2e) Cumulative reductions (tCO2e) Year 1 - - Year 2 151,517 151,517 Year 3 227,276 378,793 Year 4 303,035 681,828 Year 5 378,793 1,060,621 Year 6 454,552 1,515,173 Year 7 530,310 2,045,483 Year 8 681,828 2,727,311 Year 9 833,345 3,560,656 Year 10 984,862 4,545,518 Year 11 1,060,621 5,606,139 Year 12 1,136,380 6,742,518 Year 13 1,212,138 7,954,657 Year 14 1,212,138 9,166,795 Year 15 1,212,138 10,378,933 Year 16 1,212,138 11,591,071 Year 17 1,212,138 12,803,209 Year 18 1,212,138 14,015,347 Year 19 1,212,138 15,227,485 Year 20 1,212,138 16,439,624 Total 16,439,624 Average 821,981

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7.0 Implementation Strategy and Monitoring Plan 7.1 Introduction The monitoring plan developed for the project will enable the MPFD to monitor project performance based estimations of achievement of given monitoring targets. The indicators measured as part of monitoring will also help to validate the carbon benefits accrued to the project and assess the extent of community involvement in project activities. Evaluation of the following indicators will also be made possible:  Effectiveness of project activities to mitigate drivers of deforestation and forest degradation;  Uptake of proposed intervention activities by the local communities;  Environmental impacts of the projects, including shifts in forest fire frequency and extent; and  Socio-economic impacts of the project, including successes in the alternative livelihoods for local youth. Baselines were established at the start of the project, including (a) forest cover and (b) carbon stock based on remote sensing imagery and field surveys, and (c) socio-economic indicators based on surveys in the landscape. The project proposes two stages of monitoring and assessment to be undertaken by the MPFD:  Annual Monitoring: Measurement of indicators and monitoring of activities supported by the project. This shall be documented in the Annual Progress Report.  Five-year Monitoring: Assessment of impacts accruing due to proposed interventions, including social and environmental impacts. This shall be documented as part of the Project Verification Report. Photographic evidence shall be collected during collection of ecological data for a representation of the forest structure, regrowth, and other characteristics of the sample plots. The survey may be performed over the summer months (April–June) and will be facilitated by the MPFD along with the help of members of the forest-related institutions trained in forest inventory techniques. The REDD+ Cell at the MPFD may facilitate resources required for the survey (equipment, logistics, etc.). Results of the survey will be detailed in the Annual Report published in December in the same year/March in the following year. This analysis will also inform the Project Verification Report to reflect changes in the forest carbon stock and shifts in density classes observed, if any. Although annual changes in forest cover have been consistently low, it is expected that project activities will result in the enhancement of forest carbon stock in Hoshangabad. Estimated project benefits and technical specifications may be modified contingent on the assessment of forest carbon stock detailed in the Verification Report to reflect local circumstances and capabilities. In addition to the collection and assessment of ecological data, given socio-economic and environmental indicators shall be evaluated on an annual basis. An extensive socio-economic survey, including household surveys and FGDs, has already been undertaken as part of the baseline analysis for the drivers of deforestation and forest degradation. This will be followed up annually using appropriate indicators. The assessment of these indicators will help to assess the prevalence of the proposed project interventions. These indicators have been developed in consultation with the MPFD and other stakeholders, and reflect actions undertaken toward mitigating the drivers of deforestation and forest degradation, including mitigation of grazing, forest fires, and fuelwood and NTFP extraction. Going forward, since analysis of the indicators shall also be able to assess community capacity toward undertaking project activities,

73 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) interventions can be readjusted appropriately. Field data collection (household surveys, FGDs, key informant interviews) of these indicators may be undertaken in the summer, in sync with the collection of ecological data. Table 39: Summary of the Monitoring Plan Annual Monitoring No. of JFMC meetings in the current year and attendance No. of people attending JFMC meetings, % of men and women Community indicators No. of trainings imparted and no. of people trained for community monitoring of forests Funding of community groups – JFMCs, VFCs, EDCs Methodology of site selection and preparation Planting area (ha) Afforestation and Species planted and planting density (tree ha-1) reforestation activities Planting date indicators Survival rate (measured the following year) in % Information on climatic extremes which may affect stand growth Amount of forestlands diverted for non-forest activities Amount of forestland damaged due to fire, pests, grazing Environmental indicators Carbon stock analysis of sample plots Information on general forest management techniques carried out No. of improved cook stoves/bio-briquettes/biogas plants installed Details of fodder management techniques advanced Intervention activities Details of alternative livelihoods – No. of families impacted, government indicators schemes involved, etc. Area under medicinal gardens (Ha) Five-year Monitoring Changes in forest cover from remotely sensed data Changes in forest carbon stock from remote sensing (RS) data and field surveys Institutional Support REDD+ Cell for overall guidance of the monitoring program Community facilitator (a member of the local JFMC) for coordinating data collection in that area Monitoring Officer (a Ranger from the MPFD) for each Forest Range Coordinator at the Range Level – RFO Project Coordinator for Remote Sensing analysis – an official nominated from the RS/GIS Wing of the MPFD

7.2 Implementation strategy The implementation structure further builds on the management structure, and includes Forest Divisions and Ranges of the MPFD and village-level JFMCs to oversee a community-based implementation and monitoring program. Led by the Steering Committee and REDD+ Cell at the State level, the structure mandates that the implementation of program activities and interventions involve local JFMCs and EDCs. This will ensure that no new implementation arrangement is required and the department can deploy the interventions through the established and tested delivery routes.

74 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

REDD+ Steering Committee

REDD+ Cell

Forest Divisions

Range Offices within Each Division

JFMCs/EDCs

Figure 28: Implementation Structure for the Program 7.2.1 Monitoring Plan: Institutional Arrangement The state government constituted its first State-level Steering Committee in the Forest Department to review the progress of the REDD+ project in Hoshangabad Circle vide Order No. 77 dated 16/06/2015. The Steering Committee includes Forest Department officials. This Steering Committee will review the REDD+ project quarterly and guide it to a successful completion. This committee will be responsible for major strategic decisions for this REDD+ project in Madhya Pradesh. Table 40: REDD+ Steering Committee 1 Principal Chief Conservator of Forest & HoFF Chairman 2 Principal Chief Conservator of Forests (RE & LV and JFM/FDA) Member 3 Addl. Principal Chief Conservator of Forests (Development) Member 4 Addl. Principal Chief Conservator of Forests (HRD) Member 5 Addl. Principal Chief Conservator of Forests (IT) Member 6 Addl. Principal Chief Conservator of Forests (JFM/FDA) (State Nodal Member- Officer) Secretary 7 Chief Conservator of Forests, Hoshangabad Circle (Project Nodal Member Officer)

75 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Reporting of results to REDD+ Consolidation Steering and archiving at Committee Second REDD+ Cell validation of under the forest Validation of information at department information at divisional level JFMC/ range level community- based monitoring

Figure 29: Monitoring Structure of the Program 7.2.2 Monitoring Plan The Monitoring Plan developed for the program will enable the MPFD to monitor the performance of the REDD+ interventions advanced under the project, based on estimation of the achievement of given targets. The indicators measured as part of monitoring will also help in validation of the carbon (in the form of emissions reductions) and non-carbon benefits accrued to the project and assess the extent of community involvement in project activities. In addition, the monitoring plan will make evaluation of the following indicators possible:  Effectiveness of project activities to mitigate drivers of deforestation and forest degradation;  Uptake of proposed intervention activities by the local communities;  Deployment of alternative energy technologies, grazing techniques, and land use management initiatives;  Environmental impacts of the projects; and  Socio-economic impacts of the project and participation of local communities toward monitoring. The project has already established baselines at the start of the program, including (a) forest types and forest cover, (b) forest carbon stock based on remote sensing imagery and field surveys, and (c) socio-economic surveys to evaluate forest dependency of the rural population. The project proposes two stages of monitoring and assessment to be undertaken by the MPFD:  Annual Monitoring: Measurement of indicators and monitoring of activities supported by the project. This shall be documented in the Annual Progress Report.  Baseline Re-evaluation at 10 Years: Re-development of the baseline to be considered for estimating emissions reductions accrued from the project activities. The components under annual monitoring carried out by the MPFD are summarized below.

76 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Table 41: Parameters to Be Measured Toward Annual Monitoring No. of JFMC meetings in the current year and attendance No. of people attending JFMC meetings, % of men and women Community No. of trainings imparted and no. of people trained for community monitoring indicators of forests Funding and audit of community groups – JFMCs, VFCs, EDCs Community involvement in forest management Methodology of site selection for plantation activities Planting area (Ha) for fuelwood and fodder plantations Land use Species planted and planting density (tree ha-1) management indicators Survival rate (measured the following year) in % Information on climatic extremes which may affect stand growth Lands cleared to make grazing areas (Ha) Amount of forestlands diverted for non-forest activities (Ha) Environmental Amount of forestlands damaged due to fire, pests, grazing (Ha) indicators Information on general forest management techniques carried out – fire prevention, pest management No. of ICS/induction plates distributed bio-briquettes/biogas plants installed No. of LPG connections installed No. of briquette-making equipment distributed Intervention Details of fodder management techniques advanced activities indicators Details of alternative livelihoods – No. of families impacted, schemes introduced, inter-departmental convergences No. of induction devices and ICS distributed and installed No. of organic certifications supplied for horticultural crops The baseline estimated for calculating emissions reductions across the landscape will be re- evaluated at an interval of 10 years from the project start date to reflect changing environmental and socio-economic scenarios in Hoshangabad District. This will enable an accurate and up-to- date estimation of the forest carbon stocks, emissions from the forestlands, and characteristics of the forest dependency of the local rural population. Baseline re-evaluation will include:  Estimation of the changes in Hoshangabad’s forest strata through spatial analysis to reflect shifts in density classes;  Calculation of the forest carbon stock in each strata through spatial and field analysis; and  Assessment of the forest dependency of local communities, the provenance of the drivers of forest change in the landscape, and the success of the REDD+ interventions. For this activity, spatial analysis techniques shall remain consistent across baseline re-evaluation; although data sources may be updated if new and improved sources are found, provided there exist reasonable consistency and overlap. At the same time, consistency and compatibility with a future national carbon accounting system (as and when developed and ratified) will be explored. For the calculation of forest carbon stock, biomass plots have been laid in every forest strata in Hoshangabad as per standard methodologies detailed in the National Working Plan Code 201435. These will be adhered to for future baseline re-evaluation, until newer versions of the National

35 Ministry of Environment and Forests Government of India. 2014. 2014 National Working Plan Code -2014 (For Sustainable Management of Forests and Biodiversity in India). Dehradun: Forest Research Institute. http://envfor.nic.in/sites/default/files/National Working Plan Code 2014.pdf.

77 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Working Plan Code are introduced by the MoEFCC. The REDD+ Cell at the MPFD may facilitate resources required for the survey (equipment, logistics, etc.). Permanent plots that have been established in Hoshangabad will act as random control plots to validate the baseline, and effects of the interventions on the emissions from forests. 7.2.3 Quality Assurance and Quality Control (QA/QC) In addition to the manual for the monitoring plan, a QA/QC plan, including protocols for field measurements, data collection and verification, data entry, and archiving, will be developed and circulated to ensure the integrity of data collected and improve the monitoring efficiency for subsequent monitoring cycles shall be established. For all activities, SOPs shall be developed by the MPFD. These shall be adhered to at all times during monitoring. This will include:  Training of field team members on field data collection and analysis;  Deployment of alternative energy interventions;  Monitoring and assessment of lands identified for fodder and fuelwood plantations on both government and private lands; and  Monitoring of forest management techniques applied towards fire prevention and patrolling. 7.2.4 Parameters (Fixed) Parameters available at the development stage and that are fixed during monitoring are known as “parameters (fixed).” These do not change during the monitoring unless a more conservative value is applied based on scientifically accepted practices. These parameters are detailed below.

Data/parameter Ajur Data unit Km2 Description Area of the jurisdiction (in Ha) Data source Official national and state records Value applied 6,707 km2 Justification of choice of data or description of measurement methods The value has been used from official government source. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project sequestrations Comments None

Data/parameter CF Data unit t C t d.m-1 Description Carbon fraction of dry matter in t C t d.m-1 Values from the literature (e.g., IPCC 2006 INV GLs AFOLU Data source Chapter 4 Table 4.3) shall be used if available (otherwise default value of 0.47 t C t-1 d.m). Value applied 0.47 Justification of choice of data or Calculated as a ratio of AGB, based on 2006 IPCC Guidelines description of measurement methods to Prepare National GHG Inventory and procedures applied Calculate carbon content in biomass, to be used in baseline Purpose of data and project sequestration calculations Comments None

Data/parameter fj (X,Y)

78 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data unit t d.m. tree-1 Allometric equation for species j linking measured tree Description variable(s) to aboveground biomass of living trees, expressed as t d.m. tree-1 Equations derived using a range of measured variables like diameter at breast height (DBH) and tree height based on datasets that comprise at least 30 trees. Equations must be based on statistically significant regressions and must have an r2 that is ≥ 0.8.

The source of equation(s) shall be chosen with priority from higher to lower preference, as available, as follows: (a) National species-, genus-, family-specific; (b) Species-, genus-, family-specific from neighboring countries with similar conditions (i.e., broad continental regions); (c) National forest-type specific; (d) Forest-type specific from neighboring countries with similar conditions (i.e. broad continental regions); (e) Pan-tropical forest type-specific. Data source

Those provided Tables 4.A.1 to 4.A.3 of the GPG-LULUCF (IPCC, 2003), or in Pearson et al. (2005); Sourcebook for Land Use, Land-Use Change and Forestry Projects. Available at: http://www.winrock.org/Ecosystems/files/Winrock- BioCarbon_Fund_Sourcebook-compressed.pdf or in Chave et al. (2005); Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145: 87-99.

Species-, genus- and family-specific allometric equations may not always be available, and may be difficult to apply with certainty, hence it is acceptable practice to use equations developed for regional or pantropical forest types, provided that their accuracy has been validated with direct site-specific data. If a forest-type specific equation is used, it should not be used in combination with species-specific equation(s). Refer the emission reduction spreadsheet for the volume Value applied equations which have been applied. Justification of choice of data or description of measurement methods Peer-reviewed literature and procedures applied Purpose of data Calculation of baseline and project sequestration Volume equations can be changed during the life of the Comments project based on the CDM guidance.

Data/parameter fj (vegetation parameters) Data unit t. d.m. individual-1 Allometric equation for non-tree species, linking parameters Description such as stem count, diameter of crown, height, etc. to AGB of an individual Use of allometric equations that are species-specific or group of species-specific wherever available, provided the equations Data source have been derived using a wide range of diameters and heights, based on datasets that comprise at least 30 individuals.

79 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Project participants may create project location specific equation where appropriate. Value applied Not used for the current baseline, and hence not applicable. Justification of choice of data or description of measurement methods None and procedures applied Purpose of data Baseline and project emission reductions Comments May be included in revised baselines in the future.

Data/parameter R Data unit t root d.m. t-1 shoot d.m. Root to shoot ratio appropriate to species or forest type. Here, Description this ratio is given by belowground biomass per unit area: aboveground biomass per unit area. From Table 4.4 in IPCC GL AFOLU, based on ecological Data source domain and AGB. Value applied 0.24 Justification of choice of data or Based on GPG LULUCF in the absence of country specific description of measurement methods data. and procedures applied Calculate carbon content in biomass, to be used in baseline Purpose of data and project sequestration calculations. Comments None

Data/parameter Risk Maps Data unit Metric Describes the risk of deforestation for each pixel in project Description area as a numerical scale. Data source Satellite imagery Value applied NA (NRSC/USGS) Justification of choice of data or description of measurement methods Government validated data and procedures applied Purpose of data For mapping LULC change and baseline Comments None

Data/parameter Baseline deforestation maps Data unit Metric Maps showing location of deforested areas in the project area Description in the last 10 years Data source Satellite imagery Value applied NA (NRSC/USGS) Justification of choice of data or description of measurement methods Government validated data and procedures applied Purpose of data For mapping LULC change and baseline Comments None

Data/parameter AAu Data unit % Accuracy assessment of the classification of LULC for each Description map  Existing maps and models Data source  Literature and expert consultations

80 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Value applied More than 80% Justification of choice of data or description of measurement methods Based on actual classification data and procedures applied Purpose of data Uncertainty due to classification errors Comments Will be updated during every revision of the baseline

Data/parameter Thrp Data unit Years Description Duration of the historical reference period in years  Expert consultations Data source  Secondary data review Value applied 15 years The historical time period that has been chosen for analyzing Justification of choice of data or change in forests is 12 years. Such analyses can choose a description of measurement methods time horizon of more than 10 years to map changes. Further and procedures applied images are free of cloud cover, and takes into consideration seasonal consistency across the time horizon. Purpose of data To map LULC change for the baseline Comments None Data/parameter WD Data unit g/cm3 Description Mean wood density of species Chosen from: (a) Averaged national and commercial species-specific inventories, or from such estimates in neighboring countries. (b) Averaged regional commercial species-specific (e.g., Table Data source 4.13 IPCC National Guidance for Greenhouse Gas Inventories AFOLU Section). (c) Regional averages (0.58 for tropical Africa, 0.60 for tropical America; 0.57 for tropical Asia). Taken from Brown, 1997; Estimating Biomass and Biomass Change of Tropical Forests: a Primer (FAO Forestry Paper - 134). Specific to the species of trees. Refer the base volume Value applied calculation spreadsheets associated with the emission reductions spreadsheet. Justification of choice of data or description of measurement methods Based on peer-reviewed literature and procedures applied Purpose of data Calculation of baseline and project emission reductions Comments None

Data/parameter VFW Data unit m3/year/household Description Mean annual consumption of fuelwood in the baseline period  Interviews/participatory rural appraisals (PRAs) Data source  Field measurements and expert appraisals Value applied As given in the emission reduction spreadsheet Justification of choice of data or description of measurement methods Based on peer reviewed literature or surveys and procedures applied Purpose of data Calculation of baseline and project emission reductions Comments None

Data/parameter GWPg

81 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data unit Dimensionless Description Global warming potential for gas g Data source IPCC Assessment Report 5 Value applied As given in the emission reduction spreadsheet Justification of choice of data or description of measurement methods Based on peer reviewed literature and procedures applied Purpose of data Calculation of baseline and project emission reductions Comments None

Data/parameter Ai Data unit Ha Description Area of baseline stratum i  GIS coverage and remote imagery Data source  Ground survey data Value applied As given in the emission reduction spreadsheet Land Use Land Cover classification follows IPCC guidelines. Justification of choice of data or Forest strata has been based on the Champion and Seth description of measurement methods classification. Forests have been further divided into strata and procedures applied based on the canopy density. Purpose of data Calculation of baseline emissions Comments None

Data/parameter UBSL Data unit % Percentage uncertainty (expressed as 95% confidence interval as a percentage of the mean where appropriate) for Description carbon stocks and greenhouse gas sources in the baseline case Data source Field measurements and calculations Value applied 0.8 and 0.9 Justification of choice of data or description of measurement methods Based on approved REDD+ methodology VM0006 version 2.1 and procedures applied Purpose of data Calculation of uncertainty Comments None

Data/parameter BDs Data unit g/cm3 Description Bulk density of soil in soil stratum ‘s’ Data source Field measurements and literature study Value applied -- Justification of choice of data or description of measurement methods The value has been sourced from peer reviewed literature. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emissions Comments None

Data/parameter FBE

82 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data unit Dimensionless Description Biomass Expansion Factor Values from IPCC Good Practice Guidance for LULUCF Data source (2003) Table 3A.1.10. Default values of biomass expansion factors (BEFs) Value applied IPCC GPG Default value BEF must be sourced from data on local ecological systems. Justification of choice of data or In case of unavailability of this data, regional, national and description of measurement methods international data must be used, in that order. Since no other and procedures applied data was available, IPCC value has been used.  Calculation of baseline emissions Purpose of data  Calculation of project emissions Comments None

Data/parameter ROCNF Data unit ha/yr. Rate of conversion of forest land stratum ‘í’ into non-forest Description land stratum ‘í’ where I is denoted by 1.2…etc. Data source Literature study and expert appraisals Value applied Please refer the emission reduction calculation spread sheet. Justification of choice of data or Latest RS/GIS techniques have been used to map the LULC description of measurement methods changes. and procedures applied Purpose of data Calculation of baseline emissions Comments None

Data/parameter ROCOF Data unit ha/yr. Rate of conversion of forest land stratum ‘í’ into another forest Description land stratum ‘í’ where I is denoted by 1.2…etc. Data source Literature study and expert appraisals

Value applied Please refer the emission reduction calculation spread sheet.

Justification of choice of data or Latest RS/GIs techniques have been used to map the LULC description of measurement methods changes. and procedures applied Purpose of data Calculation of baseline emissions Comments None

Data/parameter NTS Data unit Dimensionless Description Thermal efficiency of traditional stoves Data source Expert appraisal, market information 10% default value based on IPCC/CDM approved Value applied methodology AMS-II.G Justification of choice of data or This is considered as default value based on IPCC/CDM description of measurement methods approved methodology. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emissions Comments None

83 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data/parameter NFES Data unit Dimensionless Description Thermal efficiency of fuel-efficient stoves Data source MNRE information for the public Value applied As per the model of the stove Justification of choice of data or The MNRE has compiled information of all stoves that are description of measurement methods efficient and have been empaneled. and procedures applied Purpose of data Calculation of project emissions reductions Comments None

Data/parameter EFf Data unit Dimensionless Description Emission factor of fossil fuel ‘f’ Data source IPCC 2006 Value applied Based on the fuel used (e.g., LPG) Justification of choice of data or description of measurement methods IPCC 2006 lists all default values and procedures applied Purpose of data Calculation of project emissions Comments None

Data/parameter ROCA_i Data unit Ha/yr. Description Rate of change in area of a stratum ‘I’ Data source RS/GIS analysis and field data Value applied Refer spreadsheets Justification of choice of data or Latest RS/GIS techniques have been used to map the LULC description of measurement methods changes. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emissions Comments

Data/parameter DFd Data unit % Description Proportion of driver ‘d’ in causing deforestation. Data source Based on socio-economic surveys Value applied Refer to spreadsheets Justification of choice of data or description of measurement methods Based on key informant interviews. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emission reductions Comments None

Data/parameter DGd Data unit % Description Proportion of driver ‘d’ in causing forest degradation Data source Based on socio-economic surveys Value applied Refer spreadsheets Justification of choice of data or description of measurement methods Same as DFd and procedures applied

84 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

 Calculation of baseline emissions Purpose of data  Calculation of project emission reductions Comments

Data/parameter SRint-d Data unit % Efficacy or success rate of an intervention activity planned on Description driver ‘d’ in completely eliminating emissions due to driver ‘d’ Data source Based on socio-economic surveys Value applied Refer spreadsheets Justification of choice of data or description of measurement methods Based on expert opinions and key informant interviews. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emission reductions Applicable in case more than one intervention activities are Comments planned

Data/parameter RB Data unit Mg/year Description Demonstrably renewable biomass within the state Data source PRAs, expert appraisals and literature study Value applied -- Justification of choice of data or Not used in this phase, but may be used in the latter stages of description of measurement methods the project. and procedures applied  Calculation of baseline emissions Purpose of data  Calculation of project emissions Estimation to be made of proportion of fuelwood that is Comments demonstrably renewable

Data / Parameter CFTree Data unit t C td.m. -1 Description Carbon fraction of dry matter for species of type j Methodological tool: “Estimation of carbon stocks and change in carbon stocks of trees and shrubs in A/R CDM project Data source activities” Latest version. Referred in equation number 13.

Value applied A default value of 0.47 is used following the AR CDM methodological tool. Justification of choice of data or To convert the dry biomass into carbon weight description of measurement methods and procedures applied Purpose of Data Project emission and project sequestration Comments None

Data / Parameter Dj Data unit t d.m. m-3 Description Density overbark of tree stem for tree species j. Source of data Good Practices IPCC Guidelines, 1996 and Published literature

85 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Value applied Please refer to the C-calculation spreadsheet associated with the ER calculations Justification of choice of data or Dj must be sourced from data on local ecological systems. In description of measurement methods case of unavailability of this data, regional, national and and procedures applied international data must be used, in that order. Purpose of Data Project emission and project sequestration Comments

Data / Parameter R j Data unit Dimensionless Description Root-shoot ratio appropriate for biomass stock, for species j Source of data A default value given in the methodology or, Values from IPCC Good Practice Guidance for LULUCF (2003) Table 3A.1.8 “Average belowground to aboveground biomass ratio (root- shoot ratio, r) in natural regeneration by broad category (tons dry matter/ton dry matter)”. Value applied A default value given in the methodology Justification of choice of data or Rj must be sourced from data on local ecological systems. In description of measurement methods case of unavailability of this data, regional, national and and procedures applied international data must be used, in that order. Purpose of Data Project emission and project sequestration Comments None

Parameters to be monitored

Data / Parameter Ai Data unit Ha Description Area of stratum i Source of data RS/GIS analysis by the EE Description of measurement methods Standard land use land cover classification techniques. and procedures to be applied: Frequency of monitoring/recording Minimum every 10 years prior to baseline renewal. Value applied -- Monitoring equipment -- QA/QC procedures to be applied All RS/GIs related SOPs to be followed including validation of classification and accuracy assessment. Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method None Comments None

Data / Parameter Aunplanned_hrp Data unit Ha Description Total area deforested during the historical reference period in the jurisdiction. Source of data Remote sensing and GIS analysis imagery Description of measurement methods Same as above and procedures to be applied: Frequency of monitoring/recording Minimum 10 years prior to baseline renewal Value applied -- Monitoring equipment -- QA/QC procedures to be applied Same as above

86 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method None Comments Monitored for the purpose of baseline revisions also.

Data / Parameter Adeg Data unit Ha Description Area potentially impacted by forest degradation processes Source of data GIS delineation and ground-truthing Description of measurement methods Adeg shall be composed of a buffer from all access points like and procedures to be applied: roads, rivers and previously cleared areas. Extent of this buffer determined by PRA results. Frequency of monitoring/recording Repeated each time requested by a PRA request. Value applied Same as above Monitoring equipment Same as above QA/QC procedures to be applied Same as above Purpose of data Calculation of program emissions Calculation method Same as above Comments Same as above

Data / Parameter APi Data unit Ha Description Total area of degradation sample plots in stratum i Source of data Ground measurements Description of measurement methods Plots systematically placed over the buffer zone such that they and procedures to be applied: cover a reasonable area of the buffer zone. Frequency of monitoring/recording At least every 5 years. If verification occurs on a frequency of less than every 5 years, then before any verification event. Value applied None Monitoring equipment None QA/QC procedures to be applied Standard SOPs to be followed. Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method None Comments None

Data / Parameter Cdeg Data unit t CO2 eq Description Biomass of trees cut and removed through fuelwood and charcoal extraction from plots in the given strata at time t Source of data Field measurement Description of measurement methods The diameter of all tree stumps in the designated plots will be and procedures to be applied: measured and conservatively assumed to be the same as the DBH. If the stump is a large buttress, identify several individuals of the same species nearby and determine a ratio of the diameter at DBH to the diameter of buttress at the same height above ground as the measured stumps. This ratio will be applied to the measured stumps to estimate the likely DBH of the cut tree. The above and below ground carbon stock of each harvested tree must be estimated using the same allometric regression equation and root to shoot ratio used in the module for estimating the carbon pool in trees (CP-AB) in the baseline scenario.

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Frequency of monitoring/recording At least every 5 years. If verification occurs on a frequency of less than every 5 years, then before any verification event. Value applied None Monitoring equipment None QA/QC procedures to be applied SOPs if any to be followed. Purpose of data Calculation of program emissions Calculation method Please refer to relevant sections in this PDD. Comments Ex-ante, an estimation shall be made of likely degradation in the with-project case. Such an estimation shall be based on rates of degradation in surrounding areas and the degree of protection that will be in place (e.g., forest guards) in the with- project case.

Data / Parameter FLU, FMG and FL Data unit Dimensionless Description Land use Factor, Management Factor and Input Factor before and after conversion respectively Source of data Stock Change Factors are provided in Tables 5.5, 5.10, and 6.2 of the IPCC 2006GL Volume 4 Description of measurement methods Stock Change Factors as defined in IPCC 2006GL are equal to and procedures to be applied: the carbon stock in the altered condition as a proportion of the reference carbon stock. Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data Calculation of program emissions Calculation method -- Comments --

Data / Parameter ADF_PA Data unit Ha Description Area of unplanned deforestation in the given year

Source of data -- Description of measurement methods -- and procedures to be applied: Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter ADG_PA Data unit Ha Description Area of unplanned forest degradation in the given year Source of data -- Description of measurement methods -- and procedures to be applied: Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied --

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Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter CPA_t Data unit t CO2 eq. Description Carbon stock in all pools in given stratum Source of data Field measurement Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter Df% Data unit % Description % of land deforested in the given stratum at the present monitoring period Source of data -- Description of measurement methods -- and procedures to be applied: Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of program emissions Calculation method Comments

Data / Parameter Ebiomass_burn (M-MON) Data unit t CO2 eq. Description Non-CO2 emissions due to biomass burning in given stratum Source of data -- Description of measurement methods -- and procedures to be applied: Frequency of monitoring/recording Every monitoring cycle (5/10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of program emissions Calculation method Comments

Data / Parameter Asp (CP-AB) Data unit Ha

89 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Description Area of sample plots Source of data Recording of number and size of sample plots Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Every 10 years for baseline renewal. If C stock enhancement is included, it may be done once every 5 years Value applied 0.1 ha Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method Comments Ex-ante, number and size of sample plots may be estimated based on projected effort relative to scale of emissions and growth.

Data / Parameter N Data unit Dimensionless Description Number of sample points Source of data Recording of sample points during field activities

Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Every 10 years for baseline renewal. If C stock enhancement is included, it may be done once every 5 years Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of program emissions  Calculation of leakage Calculation method Comments Ex-ante, number and size of sample plots may be estimated based on projected effort relative to scale of emissions and growth.

Data / Parameter DBH Data unit cm Description Diameter at breast height of an individual in centimeters. Source of data Field measurements in sample plots Description of measurement methods Typically measured 1.3m aboveground. Measure all trees and procedures to be applied: above a minimum DBH of 10cm in the sample plots. Minimum DBH employed in inventories is held constant for the duration of the project. Frequency of monitoring/recording Every 10 years for baseline renewal. If C stock enhancement is included, it may be done once every 5 years Value applied -- Monitoring equipment -- QA/QC procedures to be applied Use or adaptation of QA/QCs already applied in national forest monitoring, or available from published handbooks, or form the IPCC GPG LULUCF 2003, is recommended. Purpose of data Calculation of program emissions Calculation method

90 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Comments Ex-ante, number and size of sample plots may be estimated based on projected effort relative to scale of emissions and growth.

Data / Parameter H Data unit m Description Height of individual in meters Source of data Field measurements in sample plots Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Every 10 years for baseline renewal. If C stock enhancement is included, it may be done once every 5 years Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of program emissions Calculation method Comments Ex-ante, height shall be estimated based on projections of growth.

Data / Parameter Pop Data unit Description Number of individuals per census Source of data National and state records/representative surveys Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Updated every 10 years Value applied -- Monitoring equipment -- QA/QC procedures to be applied Census data to ensure adequate representation of both urban and rural households. Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter Df Data unit Ha Description Forest area cleared in Hoshangabad in last 10 years Source of data Official national and state records/representative surveys Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Updated once every 10 years Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

91 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data / Parameter Any spatial feature subject to change over time – Risk Maps, Deforestation Maps Data unit Description Risk Map depicts the potential for deforestation for each pixel location on a numerical scale. Deforestation Maps shows the location of deforested hectares. Source of data -- Description of measurement methods -- and procedures to be applied: Frequency of monitoring/recording Updated each time the baseline is re-evaluated (at least once every 10 years). Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method Comments

Data / Parameter AAU Data unit % Description Accuracy assessment of the rate of unplanned deforestation Source of data Existing maps/models, expert consultation and literature Description of measurement methods Multi-criteria analysis performed in a Geographical Information and procedures to be applied: System Frequency of monitoring/recording Updated every time a baseline is re-evaluated (at least once every 10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method Comments

Data / Parameter PAF Data unit Ha Description Area of forest available for fuelwood and charcoal extraction located within jurisdiction Source of data Determination of maximum distance of travel from communities for fuelwood collection/charcoal production and assessment of available forest within project boundaries Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Updated every time a baseline is re-evaluated (at least once every 10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage

92 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Calculation method -- Comments --

Data / Parameter VFW Data unit m3/year Description Mean annual per capita consumption of fuelwood and charcoal within state boundaries Source of data Interviews, PRAs, field measurements and literature study. Verifiable information from anecdotal evidences may be used in some cases. Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Updated every time a baseline is re-evaluated (at least once every 10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter UCpool Data unit % Description Percentage uncertainty (expressed as 95% confidence interval as a percentage of the mean where appropriate) for carbon stocks and greenhouse gas sources in the (1) baseline case and (2) project case Source of data Calculations from field measurements Description of measurement methods Uncertainty in pools derived from field measurement with 95% and procedures to be applied: confidence interval calculated as the standard error of the averaged plot measurements in each stratum multiplied by the t-value for the 95% confidence level. Frequency of monitoring/recording Updated every time a baseline is re-evaluated (at least once every 10 years) Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter FGPA Data unit m3/year Description Volume of fuelwood gathered within the given strata in project area in the given year Source of data Interviews, PRAs, field measurements and literature study. Monitoring should be conducted in communities within the project boundary as well as in communities outside the boundary but potentially collecting fuelwood or producing charcoal from within the project boundaries.

93 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years, examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter GHGDG Data unit t CO2 eq. Description Greenhouse gas emissions as a result of degradation activities within the project boundaries Source of data Field measurements, expert appraisals Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years, examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter GHGDF Data unit t CO2 eq. Description Greenhouse gas emissions as a result of deforestation activities within the project boundaries Source of data Field measurements, expert appraisals Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years, examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter FOR Data unit Ha

94 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Description Total area of forest cover available nationally and within the Hoshangabad district, which is under active management as a protected forest, National Park, Wildlife Sanctuary, Biosphere Reserve, etc. Source of data Official data, peer reviewed publications and other verifiable sources Description of measurement methods A demonstration is required that areas will be protected against and procedures to be applied: deforestation. Such a demonstration may include the existence of forest guards in sufficient numbers to prevent illegal colonization and an active management plan detailing harvest plans and return intervals, and/or evidence that the concession owner has previously evicted illegal colonists/squatters from the forest areas. Ex-ante, it can be assumed that FOR remains constant. Frequency of monitoring/recording Must be monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of baseline emissions  Calculation of program emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter CJUR_GHG Data unit t CO2 eq. Description Net emissions in the jurisdiction in the given year Source of data Field measurements Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data Calculation of program emissions Calculation method -- Comments --

Data / Parameter CPA_unplanned Data unit tCO2 eq. Description Net GHG emissions due to activity shifting for projects preventing forest degradation and unplanned deforestation Source of data Calculations from field measurements Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment --

95 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

QA/QC procedures to be applied Purpose of data Calculation of leakage Calculation method -- Comments --

Data / Parameter Cactual Data unit t CO2 eq. Description Net GHG emissions by sinks, in the given year Source of data Calculations from field measurements Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data Calculation of project emissions Calculation method -- Comments --

Data / Parameter ALU Data unit Ha Description Total area of a specific land use that has shifted from the last monitoring (forest to non-forest). Source of data RS/GIS based analysis and ground validation Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data Calculation of project emissions Calculation method -- Comments --

Data / Parameter AF-LU Data unit Ha Description Total area of forest land that has shifted from one strata to another from the last monitoring Source of data RS/GIS based analysis and ground validation Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data Calculation of project emissions Calculation method -- Comments --

96 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Data / Parameter CAGB-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in aboveground biomass in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter CBGB-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in belowground biomass in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable, Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter CDW-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in deadwood in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable,

97 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment QA/QC procedures to be applied Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter CLI-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in litter biomass in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable, Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter CSOC-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in the soil organic matter in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable, Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment --

98 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

QA/QC procedures to be applied -- Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter C-i Data unit t CO2 eq./Ha Description Carbon stock per hectare in total in given stratum i Source of data Estimation through data collected from field studies and sample plots. Please refer to the attached worksheet. Description of measurement methods Most accurate estimation is based on Tier-3 data collected. and procedures to be applied: Appropriate methodology has been applied. Where applicable, Tier-3 data has been used. Tier-2 or Tier-1 data has been applied in the order based on availability. Allometric equations are based on Forest Survey of India estimates and applicable for Hoshangabad. Summation of all carbon pools considered in the study – AGB + BGB + DW + SOC + LI Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied Refer to attached spreadsheet Monitoring equipment -- QA/QC procedures to be applied -- Purpose of data  Calculation of project emissions  Calculation of emissions credits Calculation method -- Comments --

Data / Parameter AUDF Data unit Ha Description Projected area for unplanned deforestation within jurisdiction Source of data Field investigations and remote sensing data Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of project emissions Calculation method -- Comments --

Data / Parameter AUDg Data unit Ha Description Projected area for unplanned forest degradation within jurisdiction Source of data Field investigations and remote sensing data Description of measurement methods and procedures to be applied:

99 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of project emissions Calculation method -- Comments --

Data / Parameter LB Data unit Ha Description Area of leakage belt for the jurisdiction Source of data Field investigation and remote sensing data Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data  Calculation of project emissions  Calculation of leakage Calculation method -- Comments --

Data / Parameter FWD Data unit Kilometers Description Distance travelled to collect fuelwood Source of data PRAs, FGDs, socio-economic surveys Description of measurement methods and procedures to be applied: Frequency of monitoring/recording Monitored at least every 5 years or if verification occurs on a frequency of less than every 5 years examination must occur prior to any verification event Value applied -- Monitoring equipment -- QA/QC procedures to be applied Purpose of data Calculation of project emissions Calculation method -- Comments --

100 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

8.0 REDD+ Safeguards and Benefit-Sharing Mechanism The safeguard mechanism is an important aspect of REDD+. Safeguards are procedures and approaches that can help to ensure that REDD+ activities do no harm to people or the environment, mitigate the risk of adverse environmental and social impacts of REDD+ activities, and promote benefits beyond carbon emission reductions. Parties to the UNFCCC adopted broad guidance and safeguards for REDD+ activities in Cancun in 2010 (Paragraph 2 in Appendix I) at the 16th COP to the United Nations Framework Convention on Climate Change. Paragraph 72, decision 1/ CP.16 requests that developing country parties, when developing and implementing their national REDD+ strategies, address the safeguards detailed, ensuring the full and effective participation of relevant stakeholders—inter alia indigenous peoples and local communities. A set of seven safeguards agreed to under the UNFCCC that should be promoted and supported when undertaking REDD+ activities are known as the Cancun Safeguards. Safeguard Information Systems (SIS) provide a systematic approach for collecting and providing information on how REDD+ safeguards are being addressed and respected throughout REDD+ implementation. This system provides information on how all Cancun safeguards are addressed. Effective systems to share information will help promote transparency, guard against unintended negative social and environmental effects, and provide information on the impact of REDD+ actions. In consonance with the Cancun safeguards, and the Indian policies, a SIS has been developed for the jurisdictional REDD+ project in Sikkim. This includes the parameters to be monitored periodically. This will help the Executive Entity to avoid any risk arising out of project activity to communities and/or environment. To develop safeguard standards for information collection and monitoring, the following important REDD+ measures were considered:  Environmental factors—biodiversity, forest ecosystem services  Socioeconomic factors—poverty reduction, job creation, improved well-being  Social factors—impacts on indigenous peoples and marginalized groups; gender impacts  Economic—distribution of costs and benefit  Governance—law implementation, law enforcement, legal situation of land, land, and resource tenure  Benefits sharing  Drivers of deforestation and forest degradation  Eco-tourism  Sustainable production of goods and services  Capacity building. The sections below explains the safeguards system that has been developed for this project. 8.1 National REDD+ Safeguard Policy As India is a party to the UNFCCC, the GoI has developed a reference document to facilitate REDD+ implementation in the country.36 The GoI also formulated a National REDD+ Policy and

36 Ministry of Environment, Forests and Climate Change . (2014, December). Reference Document for REDD+ in India. Retrieved from Ministry of Environment, Forests and Climate Change : http://envfor.nic.in/sites/default/files/press- releases/Reference%20Document%20For%20REDD+%20in%20India.pdf

101 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

Strategy where a National REDD+ Authority will be established in the MoEFCC under a national steering committee on REDD+. The policy also aims to develop a mechanism for the fund flow to the communities and to put in placer safeguards against all the risks and for protecting rights and livelihoods of communities.37 8.2 Compliance with Laws The following are the laws or conventions where India has ratified and will be a part of safeguard mechanism of the project activity. 8.2.1 National Acts and Laws The Wildlife (Protection) Act, 1972, Amendment 1991 The Wildlife Protection Act, 1972, is for protection of the listed species of flora and fauna and establishes a network of ecologically-important protected areas. The proposed project is in compliance with the Act as it aims to protect the wildlife and biodiversity of the proposed project area. The Forest (Conservation) Act, 1980 (Amended 1988) The act is aimed for protection of forest and its resources. The act restricts the power of the state in conversion or use of forestland into non-forest purpose. The proposed project is in compliance with the Act and will assist India in achieving its goals of forest conservation. There is no conversion or use of forest land for non-forest purposes. Environment (Protection) Act, 1986 The act protects and improves the environment condition by setting standards and regulating emissions and discharges; management of hazardous waste and public health and welfare protection. The project complies with requirements of the Act and promotes sustainable use and management of natural resources of the proposed project area. 8.2.2 International Agreements Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), 1973 The aim of CITES is to control or prevent international commercial trade in endangered species or products derived from them. The project complies with this convention and aims to promote faunal conservation in the proposed project area. UN Framework Convention on Climate Change (UNFCCC), 1992 The primary goal of the UNFCCC is to stabilize GHG emissions at levels that would prevent dangerous anthropogenic interference with the global climate. The main objective of the proposed project is to reduce GHG emission via implementing the REDD+. Convention on Biological Diversity (CBD), 1992 The CBD aim is conservation of biodiversity sustainable use of biological resources and equitable sharing of benefits arising from their sustainable use.

37 Ministry of Environment, Forests and Climate Change. (2014). National REDD+ Policy & Strategy - Zero Draft. Ministry of Environment, Forests and Climate Change.

102 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh)

The project complies with this convention by promoting sustainable management of forest, conservation of forest and its resources and improving the livelihood of the dependent communities. Convention on Wetlands of International Importance (Ramsar), 1971 Convention is to conserve wetlands and waterfowl habitat. The Convention encourages training of personnel in the field of wetland research, management along with research. The proposed project complies with this convention, evidenced via conservation of the wetland sites within the project area. Stockholm Declaration of the United Nations Conference in Human Environment, 1972 The Stockholm Declaration talks about the person’s right to freedom, adequate condition of life; responsibilities towards environment and sustainable future of the planet. The proposed project provides a framework whereby the project proponent, local communities and the other relevant stakeholders can protect the proposed project area’s ecosystems & environment and sustainably manage the resources available therein, and lead to an improvement in the socio-economic conditions of the community. Human Rights India has signed the Universal Declaration of Human Rights. There are no risks that the project will breach the safeguarding principles. United Nations Declaration on the Rights of Indigenous Peoples India has voted in the favor of the declaration on rights of indigenous people38. Therefore, there will be protection to the rights of indigenous people in the project area. Convention for the Safeguarding of the Intangible Cultural Heritage The Government of India is a party to UNESCO’s “The States Parties to the Convention for the Safeguarding of the Intangible Cultural Heritage” (2003)39 which aims at protection of cultural heritage and safeguards any violation of the safeguarding principle. Hence, this project does not involve and is not complicit in the alteration, damage or removal of any critical cultural heritage. International Labor Organization (ILO) Convention India has signed the International Labor Standard Convention and is a member of ILO.40 The Indian Government has not ratified the ILO Convention 87 and 98.41 The project activity does not involve production, trade or other commercial activity requiring large labor force. The project activity does not deal with setting up a factory and recruiting employees and hence not complicit in restrictions of these freedoms and rights. India has ratified ILO convention 29 and 105 on elimination of forced and compulsory labour. The project is owned by Karnataka Forest Department, a government agency. This project activity

38 United Nations. (2007, September 13). General Assembly Adopts Declaration On Rights Of Indigenous Peoples; ‘Major Step Forward’ Towards Human Rights For All, Says President. Retrieved from Meetings Coverage and Press Releases: http://www.un.org/press/en/2007/ga10612.doc.htm 39 UNESCO-ICH. (n.d.). The States Parties to the Convention for the Safeguarding of the Intangible Cultural Heritage (2003). Retrieved from UNESCO-ICH: https://ich.unesco.org/en/states-parties-00024 40 NORMLEX Information System on International Labour Standards. (n.d.). India. Retrieved from International Labour Organization: http://www.ilo.org/dyn/normlex/en/f?p=NORMLEXPUB:11110:0::NO::P11110_COUNTRY_ID:102691 41 NORMLEX Information System on International Labour Standards. (n.d.). Up-to-date Conventions and Protocols not ratified by India. Retrieved from International Labour Organization: http://www.ilo.org/dyn/normlex/en/f?p=NORMLEXPUB:11210:0::NO::P11210_COUNTRY_ID:102691

103 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) involve communities thorough VFC/JFPMs who will assist in overall management of the project activity. Monitoring personal will be adults and will be involved in monitoring voluntarily and does not involve and is not complicit in any form of forced or compulsory labor. India has ratified ILO Convention 100 (equal remuneration) and Convention 111 (discrimination in employment/occupation). The project does not involve and is not complicit in any form of discrimination based on gender, race, religion, sexual orientation or any other basis. Child Labor India is not ratified ILO convention 138 (minimum age) and convention 182 (worst form of child labor).42 But India has its own Child Labor (Prohibition & Regulation) Act, which prohibits employment of children in certain specified hazardous occupations and processes and regulates the working conditions in others.43 Currently, in the absence of a National REDD+ Strategy, states like Madhya Pradesh are free to develop their own suitable mechanisms towards REDD+ programs. These state-level initiatives would be integrated nationally in the light of future directives from the central government and the subsequent finalization of a National REDD+ Strategy. MPFD is the government department with jurisdiction over the forests of Hoshangabad. The activities of the Department are in consonance with the laws, policies and regulations evolved under the Government of Madhya Pradesh and MoEFCC, Government of India. Currently, this program is not rewarded under any other GHG emissions reductions mechanism. Registration of the program (or any parts thereof) under any other mechanism in the future shall be communicated to the concerned authority. Specifically, the environmental or ecosystem services under the program are:  Sequestration, maintenance and enhancement of forest carbon stock, and decreasing carbon flux.  Conservation of biodiversity in the state.  Climate regulation.  Conservation of hydrological systems and other related ecosystem services. Towards these ends, the MP Government would be supported by a series of guiding principles, including:  Responsible use of natural resources  Respect for the knowledge and rights of local communities  Promoting cooperation and best practices across similar programs in the rest of the country  Just and equitable sharing of benefits with stakeholders  Transparency in the administration of financial resources. Combining the legal objectives of the program with the guidelines that it would be governed by, it can be said that the project proponent, MPFD, is responsible for the valuation and management

42 NORMLEX Information System on International Labour Standards. (n.d.). Up-to-date Conventions and Protocols not ratified by India. Retrieved from International Labour Organization: http://www.ilo.org/dyn/normlex/en/f?p=NORMLEXPUB:11210:0::NO::P11210_COUNTRY_ID:102691 43 Ministry of Labour and Employment. (1987). The Policy of the Government on the issue of Child Labour. Ministry of Labour and Employment, Government of India. Retrieved from http://labour.gov.in/childlabour/child-labour-policies

104 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) of the environmental services generated within the state so that they are protected and preserved and become a source of sustainable funds towards furthering low emissions development in the state. This REDD+ program is not a part of any other GHG program, and no credits shall be issued from non-forestry projects. 8.3 Safeguards Information System SIS provide a systematic approach for collecting and providing information on how REDD+ safeguards are being addressed and respected throughout REDD+ implementation. Conceptualizing an SIS:  SIS can be understood as “the set of institutions and processes through which information is collected, verified, assessed, published and fed back to relevant institutions.”44  The systems should be developed in a way that strikes a balance between: ‒ Flexible and country-driven approaches: Useful and effective for stakeholders at the country level, respecting sovereignty, but also compatible with any international standards; and, ‒ Financial viability: Builds confidence to trigger substantial financial investment in REDD+ while not placing undue burden or transaction costs on the country/project implementers. Objectives of SIS The Safeguards Information Systems can serve multiple objectives at different levels including reporting internationally for results-based financing, and providing information within the country to improve the REDD+ strategy (adaptive management) and to build and maintain stakeholder and political support for REDD+. The objectives for the SIS and the uses of the information need to be defined early in the development process, since they will affect the design. Safeguards and SIS in the context of the UNFCCC Process

44 Boyle, J., & Murphy, D. (2012). Designing Effective REDD+ Safeguard Information Systems: Building on existing systems and country experiences. International Institute for Sustainable Development.

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SIS elements Consistency  Be consistent with Cancun guidance Accessibility & Periodic  Provide transparent and consistent information that is Reporting accessible by all relevant stakeholders and updated on a regular basis Improvement over Time  Be transparent and flexible to allow for improvements over time Comprehensiveness  Provide information on how all of Cancun safeguard elements are being addressed and respected Country Driven  Be country-driven and implemented at the national level; Utilizing Existing Systems  Build upon existing systems, as appropriate Gender  Respect gender consideration National Sovereignty  Recognize national sovereignty and legislation, as well as relevant international obligations and agreements Durban Outcome (COP17, 2011)45 Developing SIS Ideally, the development of SIS will follow the objective-setting exercise and the policy, law and regulation (PLR) gap analysis. This is because it is necessary to know, at least in outline, what the safeguards are, in order to collect information on how they are addressed and respected.

45 United Nations Framework Convention on Climate Change (UNFCCC). (2011, November). Durban Climate Change Conference - November/December 2011. Retrieved from United Nations Framework Convention on Climate Change (UNFCCC): http://unfccc.int/meetings/durban_nov_2011/meeting/6245.php

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Consistent with the PLR component, a crucial first step for the SIS will likely involve conducting an assessment of existing information sources, and existing systems for provision of information that are relevant to the safeguards. Based on this, an assessment can be made regarding what types of new processes or procedures and institutions, among other structures, might be needed. In order to collect information on whether safeguards are being addressed and respected, some form of indicators will be needed. These could be process indicators (e.g., to illustrate whether or not an output has been achieved) or impact indicators (e.g., linked to actual social or environmental impacts). Based on experiences from countries participating in the REDD+ SES Initiative, approaches to developing and implementing SIS generally comprise the six key elements.

1. Defining the Scopes and Objecives

2. Building on existing information system (institutional based information system)

3. Establishing institutional arrangements and processes for stakeholder participation (MPFD, Panchayat, and JFM community institution)

4. Identifying the specific information needed

5. Collection, compiling and analyzing information

6. Reviewing, reporting and using information

(REDD+ SES) Operationalizing and reporting information on Safeguards Stepwise approach for safeguards operationalization and the setup of SIS: 1. Risk assessment to identify priority areas in country specific REDD+ design 2. Developing safeguard criteria and indicators through analysis of available data:  Review of REDD+ discourses to identify country-specific  Objectives for REDD+ SES  Review of legal frameworks and identification of gaps  Analysis of existing SES practices and lessons  Identification of existing information sharing systems. It will be key to improve assessment and reporting of safeguards through establishment of robust datasets and inclusion of feedback loops, including continuous review of risk areas, as these may change over time. Information collection methodologies and approaches should define:  What data is to be collected (e.g., income data)

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 Methodologies to be used (e.g., household surveys; participatory approaches, such as participatory biodiversity monitoring)  Who collects the data  Frequency of data collection  The scale at which data is collected (e.g., at the country, local or project level) SAFEGUARDS INFORMATION SYSTEMS An important element of REDD+ safeguards, which is being negotiated under the UNFCCC, is systems for providing information on how safeguards are addressed and respected. A decision at the climate change meetings in the 17th Conference of the Parties held at Durban (2011) agreed on broad for provisions for guidance, including that SIS “build upon existing systems, as appropriate” (UNFCCC, 2012).46 Operationalizing and reporting information on safeguards: Stepwise approach for safeguards operationalization and the setup of SIS: 1. Conduct risk assessment to identify priority areas in country specific REDD+ design 2. Develop safeguard criteria and indicators through analysis of available data:  Review of REDD+ discourses to identify country-specific  objectives for REDD+ SES  Review of legal frameworks and identification of gaps  Analysis of existing SES practices and lessons  Identification of existing information sharing systems It will be key to improve assessment and reporting of safeguards through establishment of robust datasets and inclusion of feedback loops, including continuous review of risk areas, as these may change over time. Developing Safeguards Information Systems: For developing Safeguard standards for information collection and monitoring following important REDD+ measures were considered:  Environmental factors—biodiversity, Forest ecosystem services  Socioeconomic factors—poverty reduction, job creation, improved well-being  Social factors—impacts on indigenous peoples and marginalized groups; gender impacts  Economic—distribution of costs and benefit  Governance—law implementation, law enforcement, legal situation of land, land and resource tenure  Benefits sharing  Drivers of deforestation and forest degradation  Eco-tourism  Sustainable production of goods and services

46 Boyle J and Murphy D (2012). Designing Effective REDD+ Safeguard Information Systems: Building on existing systems and country experiences. IISD, Canada.

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 Capacity building. In order to collect information on whether safeguards are being addressed and respected, some form of indicators will be needed. These could be process indicators (e.g., to illustrate whether or not an output has been achieved) or impact indicators (e.g., linked to actual social or environmental impacts). Criteria and Indicators for Safeguards monitoring and SIS: Criteria are the standards that defines high performance of REDD+ to be met including conditions related to processes, impacts and policies in order to deliver the objectives. The REDD+ processes, impacts and policies for India is divided into four different criteria is explained below. Procedural safeguards Procedural Criteria Procedural criteria are governance issues that relate to the proper functioning of national level, sub-national level and forest sector decision making and management. This criteria is focused to address the issues related to the integration of REDD+ into PLRs, transparency, stakeholder participation, and grievance mechanisms, which can be referred to either as “safeguards” or as procedural standards depending on the initiative. Seven indicators are designed to address procedural criteria of Jurisdictional REDD+ in Forest- PLUS landscapes. Indicators define quantitative or qualitative information needed to show progress achieving a criterion. 1. Name of the Indicator Safeguards synergy with the existing PLRs Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 1 Parameter No of actions divergent to existing PLRs Description of parameters REDD+ actions taken and ensured that these are not in conflict. It will be that ensured REDD+ actions do not conflict with national law or international agreements. Unit of measurement Number Source of data Existing PLRs- state portals Project- Implementation reports, published literatures Methodology of collection of data Through literature survey for PLRs and implementation report Measuring/recording frequency Shall be reported for compliance at the formulation stage and reported at every monitoring. Calculation/analysis method NA where applicable Additional comments Nil 2. Name of the Indicator Transparent and effective forest governance structure Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 2 Parameter Village committees formed in the project area for effective REDD+ implementation Description of parameters Transparency is an important component for ensuring accountability in governance. It will helps to ensure transparency and access to information, and effectiveness and efficiency of systems for feedback, oversight and accountability. By requiring that information on REDD+ policies, programs and projects be available to the public, identified delivery partners and government stakeholders are held responsible for finance as well as successes and failures of a program or project.

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It will address transparency in implementation, execution, benefit sharing, information sharing, gender equality, implementation of PLRs, monitoring, etc. Unit of measurement Percentage Source of data Government reports Methodology of collection of data Through consultation and field monitoring as well from secondary sources Measuring/recording frequency Annually Calculation/analysis method Number of committee formed to the total villages in the project where applicable area Additional comments Uploading information on online portals or databases should be encouraged to make information easily available and up to date. Availability of information in local languages can help increase accessibility. 3. Name of the Indicator Participatory mode of actions Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 4 Parameter Extent of participation of relevant stakeholders, in particular indigenous peoples and local communities in 1. Committee meetings for REDD+ activities 2. Implementation and other project activities Description of parameters This indicator has potential to strengthen recognition of the rights of indigenous peoples, including the right to free, prior and informed consent. It will ensure active participation of all the stakeholders in REDD+ activities. Unit of measurement Percentage participation Source of data Record books/Ledger Methodology of collection of data Through record books, ledger, and MoMs with participation List. Measuring/recording frequency Annually Calculation/analysis method Enumeration of total participation where applicable Additional comments Full and effective participation of relevant stakeholders at all stages of REDD+ and project development is a critical component of good governance and important in strengthening public institutions, transparency and promoting democratic processes.47 4. Name of the Indicator Respect of knowledge of indigenous and local communities Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 3 Parameters  Number of Microplans in the REDD+ area  In the absence of Microplan, No. of PRAs, focal group discussions, resource mapping Description of parameter Total number of microplan prepared by communities in the REDD+ Jurisdiction will be evaluated. In the absence of microplan, total number of PRA exercise, FGDs and resource mapping carried out will be evaluated. Unit of measurement Number Source of data Microplans, meeting minutes Methodology of collection of data Review of microplans and/or reports/ peer reviewed papers

47 Mackenzie, C. (2013). REDD+ Social Safeguards and Standards Review. Burlington: Forest Carbon, Markets and Communities Program (FCMC).

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Measuring/recording frequency Review and reports, conduct of participatory methods as and when required. Calculation/analysis method NA where applicable Additional comments Nil 5. Name of the Indicator Availability of monitoring and reporting system Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 2 Parameters To monitor progress and device compliance Description of parameter Information on how information is stored and shared and how safeguards are being addressed and respected has to be collected and reported in a systematic way throughout the REDD+ process Unit of measurement Qualitative (Yes/No) Source of data Annual report and consultation/ meetings Methodology of collection of data Information on how safeguards are being addressed and respected has to be collected and reported in a systematic way throughout the REDD+ process. Measuring/recording frequency Annually Calculation/analysis method NA where applicable Additional comments Uploading information on online portals or databases should be encouraged to make information easily available and up to date. Availability of information in local languages can help increase accessibility. 6. Name of the Indicator Established grievance mechanism to address concerns and conflicts Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 2 Parameters To address concerns in cases where REDD+ projects cause conflicts or when safeguards are not applied. Description of parameter It involved verifying the existing grievance and redress mechanism and comparing with the international standards. Parameters like conflict resolution mechanism available, number of grievance recorded and solved, availability of redressal mechanism, etc. to be evaluated. This mechanism will provide a way for local communities to have a voice and a channel for resolution and redress Unit of measurement Yes/No Source of data Annual report, conflict register, grievance redressal cells, complain register, etc. Methodology of collection of data Verification of reports and records including annual report, conflict register, grievance redressal cells, complain register, etc. Measuring/recording frequency Every five years Calculation/analysis method N/A where applicable Additional comments Nil 7. Name of the Indicator Leakage management Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 6 and 7 Parameters To monitor shift in impacts on non-project areas

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Description of parameter A procedural requirement to identify possible leakage displacement from the project in the jurisdiction. Unit of measurement Quantitative (tons) Source of data Annual report Methodology of collection of data Data will be collected from published report Measuring/recording frequency Every five years Calculation/analysis method Amount of CO2 equivalent in tons. where applicable Additional comments Analyze the CO2 leakage, Random checks/site audits/interviews of key personnel, etc. to validate the quantity of leakage.

Environmental Safeguards Environmental Criteria Environmental criteria mandate that biodiversity and ecosystem services possibly affected by the REDD+ program are identified, prioritized and mapped, and that the REDD+ program maintains and enhances the identified biodiversity and ecosystem service urgencies. Further, the REDD+ program should not lead to the conversion or degradation of natural forests or other areas that are important for maintaining and enhancing the identified biodiversity and ecosystem service priorities. Five (5) indicators are designed to address procedural criteria of Jurisdictional REDD+ in Forest- PLUS landscapes. 1. The mapping of current policies, laws and regulations Name of the indicator related to forest conservation and biodiversity protection Synergy with Cancun Safeguards 1/CP.16 Safeguard 1 Parameters To monitor implementation of PLRs These policies have been developed after extensive consultations with stakeholders over the years. It will be Description of the indicator evaluated how these PLRs have been implemented and operationalized in the jurisdiction. Unit of measurement Qualitative Policy documents at state and national level, including:  Gazette of India Source of Data  Human Development Reports  Other relevant documents Methodology of data collection Desk study of relevant policy documents Measuring/Recording Frequency Annual Calculation/analysis method (where N/A applicable) This will help to ensure REDD+ actions do not conflict with Additional Comments national law or international agreements. 2. Initiatives and actions for biodiversity conservation and Name of the indicator wildlife protection at the National and State level Synergy with Cancun Safeguards 1/CP.16 Safeguard 5 Parameters To analysis impacts of conservation initiatives undertaken. Evaluation of the success of these initiatives on the ground. Description of the indicator There will be assessment of factors like:  No. of poachers arrested/no. of weapons seized

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 Mode of surveillance and spatial distribution of surveillance instruments  Information from field surveys/camera trapping studies/tagging (if any)  No. of ex-situ and in-situ conservation measures for rare, endangered and endemic species. This will help to incentivize protection and conservation of natural forests and biodiversity, and their services and other benefits. Unit of measurement Contingent on information presented.  Desk-based studies Source of Data  Field studies  Information from other state departments Data collection will be based on the reconciling of results from desk-based studies, periodic reports of field studies Methodology of data collection and the procurement of relevant information from other state departments wherever applicable. Measuring/Recording Frequency Annual Calculation/analysis method (where Total number of activities/incidence took place per annum. applicable) Additional Comments Nil 3. Small and large infrastructure projects, including the Name of the indicator construction of hydro projects, dams and roads. Synergy with Cancun Safeguards 1/CP.16 Safeguard 6 Parameters Loss of forest cover due to infrastructure projects An assessment of the small and large infrastructure projects currently under development in state, which have a Description of parameter potential for reversing benefits through the loss of forest carbon biomass. This will help ensure REDD+ activities result in long-lasting positive changes. Unit of measurement Nos.  Minutes of Cabinet meetings and State Assembly Source of Data  Annual Reports of state government departments, including Agriculture, Water Resources, Rural Development, Home Affairs, Horticulture, Finance. Methodology of data collection Government annual reports and other records. Measuring/Recording Frequency Annual Calculation of the benefits lost through the loss of forest Calculation/analysis method (where carbon biomass in terms of emissions, based on extent of applicable) forest and tree cover lost to given developmental activity. Additional Comments Nil 4. Name of the indicator Initiatives towards Pest and Fire Management Synergy with Cancun Safeguards 1/CP.16 Safeguard 6 Parameters Incidence of fire and pest attack Ensuring that the environmental risks associated with pests and forest fires are minimized, and that safe and Description of the indicator environmentally-sound pest and forest fire management techniques are promoted. This will help ensure REDD+ activities result in long-lasting positive changes. Unit of measurement Total land area affected due to fire and paste attack Source of Data Working Plans and other periodic subject-specific reports

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Field study and desk-based analysis of pest and fire Methodology of data collection management techniques currently underway in the jurisdiction. Measuring/Recording Frequency Annual Calculation of the benefits lost through the loss of forest Calculation/analysis method (where carbon biomass in terms of emissions, based on extent of applicable) forest and tree cover lost due to fire or disease. Additional Comments Nil 5. Name of the indicator Preservation of Physical Cultural Resources (PCRs) Synergy with Cancun Safeguards 1/CP.16 Safeguard 3 To avoid or mitigate, adverse impacts on cultural resources Parameters from development projects. Evaluation of PCRs using field surveys by experts, to document the presence and significance of these PCRs, Description of parameter including sacred groves. This will ensure that the project draws upon the knowledge of local communities on local forest conditions and appropriate actions. Unit of measurement Quantitative Source of Data Field-based surveys Data collection will involve field based surveys, including village-level discussions and consultations with Methodology of data collection  Panchayat leaders and JFMC members.  Social Welfare Department of the jurisdiction.  Prominent civil society activists. Measuring/Recording Frequency Every 3-5 years Calculation/analysis method (where Percentage of resources depleted/impacted per annum. applicable) Additional Comments Nil

Social Safeguards Social criteria To ensure fully and effective participation of all relevant stakeholders especially indigenous communities and peoples. Five indicators are designed to address procedural criteria of Jurisdictional REDD+ in Forest- PLUS landscapes. 1. Name of the Indicator Support of tenure and resource rights Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 3 and 4 Parameters  Total land allotted to indigenous communities and total number of beneficiary households.  What are the kinds of rights they have under the Forest Rights Act (FRA) in the jurisdiction? Description of parameter  Data on prevailing customary land and resource rights,  Steps taken to strengthening tenure security,  Implementation of FRA and number of beneficiaries Unit of measurement Quantitative Source of data Annual report, FRA online portal, land record book, etc. Methodology of collection of data Data will be collected through primary and secondary sources including published reports, record book and online portal.

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Measuring/recording frequency Every five years Calculation/analysis method Percentage of beneficiaries to the total populations where applicable Additional comments Addressing land tenure and rights is highly complementary to the overall goals of REDD+ because forest communities with stronger land tenure have also been shown to be better stewards of sustainable resource use and conservation of forests48 2. Name of the Indicator Consideration of vulnerable groups Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 3 and 4 Parameters Involvement of vulnerable groups in REDD+ activities Description of parameter  Involvement of indigenous peoples, women, religious or ethnic minorities in various REDD+ activities as per project guidelines.  Activity wise involvement of vulnerable communities in decision making. Unit of measurement Quantitative Source of data Annual report, Activity register, FRA online portal, etc. Methodology of collection of data Data will be collected from record books and published literatures Measuring/recording frequency Every five years Calculation/analysis method Percentage of involvement to the total populations where applicable Additional comments Nil 3. Name of the Indicator Enhancement of livelihoods Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 4 and 5 Parameters Existing program implemented in the project area to support livelihood and capacity development of forest dependent communities Description of parameter Address alternative income sources as well as capacity building and knowledge transfer mechanism adopted to enhance livelihoods of the community. Unit of measurement Quantitative Source of data Annual report and activity register Methodology of collection of data Data will be collected from annual report and activity register Measuring/recording frequency Every year Calculation/analysis method Percentage of beneficiaries to the total populations. where applicable Additional comments Nil 4. Name of the Indicator Inclusion of guidance on benefit sharing Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 5 Parameters Availability of standard benefit sharing mechanism Description of parameter To ensure that benefits are distributed equitably among all stakeholders including local communities, government, and concession holders, as well as project developers and facilitators, if applicable.

48 Gregersen, H., Lakany, H. E., Bailey, L., & White, A. (2011). The Greener Side of REDD+: Lessons for REDD+ from Countries where Forest Area Is Increasing. Washington DC: Rights and Resources Initiative.

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It will address vertical and horizontal transfer of benefits (both direct and indirect) arising from REDD+ projects. Unit of measurement Quantitative Source of data Annual report, activity register and audit report Methodology of collection of data Data will be collected from annual report, activity register and audit report Measuring/recording frequency Every five years Calculation/analysis method Percentage of beneficiaries to the total populations. where applicable Additional comments Benefits are usually considered in terms of cash, but may also come in the form of capacity building, infrastructure, and social and environmental services.49 5. Name of the Indicator Stakeholder involvement Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 4 and 7 Parameters Effective involvement of all stakeholders Description of parameter Involving all stakeholders (local communities, wood producers, wood processing industries, governments, NGOs, etc.) for joint long-term planning on resource availability and utilization. It will minimize the risk of displacement of emissions from REDD+ projects. Unit of measurement Quantitative Source of data Government reports and published literatures Methodology of collection of data Data on involvement of various stakeholder on different REDD+ activities will be accessed from government reports and literatures available. Measuring/recording frequency Every 2–3 years Calculation/analysis method Total number of stakeholder per village/village community area. where applicable Additional comments Stakeholders will have a significant impact on the regional trade in forest products which affects national emissions.

Economic/financial criteria Cost benefit analysis of the project is essential for long-term finance and secured REDD+ project. In order to ensure economic or financial security of the REDD+ project, a transparency fund utilization and disbursement mechanism should be ensured. Cooperation between the private and public sectors, working closely with indigenous peoples, local communities and civil society, will be necessary to scale up REDD+ finance and direct adequate funds towards implementing safeguards and establishing effective SIS. Such a cooperative approach will also be essential to the negotiations of a new international legal framework under the Durban Platform that includes forests in conjunction with stringent targets. Three indicators are designed to address economical/financial criteria of Jurisdictional REDD+ in Forest-PLUS landscapes. 1. Name of the Indicator Fund utilization and disbursement mechanism Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 2 Parameters To evaluate fund disbursement and utilization mechanism.

49 Roe, S., Streck, C., Pritchard, L., & Costenbader, J. (2013). Safeguards in REDD+ and Forest Carbon Standards: A Review of Social, Environmental and Procedural Concepts and Application. Climate Focus.

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Description of parameter This will ensure transparency in the system. It could help to ensure relevant stakeholder groups can access necessary information, and that decision-makers are held to account for meeting REDD+ targets and goals that have been set. Unit of measurement Quantitative Source of data Annual report, audit report, ledgers maintained at JFCM/VFC/EDC level Methodology of collection of data Data should be collected through study of existing annual report, audit reports and Ledger book. Measuring/recording frequency Yearly Calculation/analysis method Total fund utilized/disbursed (INR) where applicable Additional comments Nil

2. Name of the Indicator Costs for the implementation of policies and measures of REDD+ Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 6 Parameters To analyse implementation cost of REDD+. Description of parameter This indicator will help in feasibility study through cost-benefit analysis. It will ensure REDD+ results in long-lasting change for the good of the climate. Unit of measurement Quantitative Source of data Annual report, audit report, Ledgers maintained at JFCM/VFC/EDC level Methodology of collection of data Data should be collected through study of existing annual report, audit reports, and ledgers. Measuring/recording frequency Yearly Calculation/analysis method Expenditure (INR) per annum where applicable Additional comments Nil 3. Name of the Indicator Costs for changing land-use and forest management practices on the ground. Synergy with Cancun Safeguards 1/CP.16 Cancun safeguard 6 Parameters To analyze expenditure for changing land-use and forest management practices. Description of parameter This indicator will help in cost-benefit analysis. This will help in analyzing suitability of the system Unit of measurement Quantitative Source of data Annual report and audit report Methodology of collection of data Data should be collected through study of existing annual report, audit reports. It will ensure REDD+ results in long- lasting change for the good of the climate. Measuring/recording frequency Once every five years Calculation/analysis method Expenditure per annum where applicable QA/QC Random checks/site audits/interviews of key personnel, etc. to validate how effective the involvement is. Additional comments Nil

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8.4 Benefit-Sharing Mechanism Benefit sharing is a key element of national REDD+ architectures, and its implementation will require compliance to safeguards to ascertain that contextual, procedural and distributive equity are considered. The jurisdictional REDD+ program of Hoshangabad District seeks to generate credits based on the reduction of GHG emissions at the jurisdictional level. The revenue generated from these carbon credits will be transferred to the intended beneficiaries as incentives to support the effectiveness of forest management and increase the efficiency of REDD+ programs. These benefits can come in a variety of ways through actions towards continued emissions reductions and carbon stock conservation in forests. In order to maintain the transparency and involvement of stakeholders in the benefit-sharing allocation, the decisions regarding investments of assets will require the approval of the Hoshangabad REDD+ Steering Committee and REDD+ Cell. For REDD+ to yield positive and desired outcomes, the state forest department of Madhya Pradesh (which is the implementing agency) need to put required policies, institutions, and financing and benefit-sharing mechanisms in place, which are regarded as crucial for the REDD+ mechanism to work on the ground throughout all phases of REDD+. The ways in which the financial benefits of REDD+ to be shared with domestic stakeholders particularly local resource users, will be critically important to the success of REDD+ in the countries. Developing international standards and safeguards suggest that REDD+ benefit sharing measures should be;  Equitable so that benefits are shared among stakeholders  Cost-efficient in delivering benefits  Effective in providing incentives and rewards that change the behavior of resource users over the long term in order to reduce emissions. Each phase of REDD+ can and should be designed and implemented to maximize benefits to indigenous people, local communities, small holders, and other partners while maintaining the effectiveness and efficiency of the program. Benefit sharing mechanisms may be based on existing governance structures, or can include new benefit sharing mechanisms and institutions. India has well developed institutional mechanisms and several policies, laws and regulations to support the system. Therefore it would be better to adopt and improve the existing benefit sharing mechanism rather than developing totally new system. The benefit of adopting existing institution and legal frameworks is that it can reduce the costs of founding and operating new institutions and could receive more political support at the national as well as at local level. The State Government of Madhya Pradesh in compliance with the central policy and guidelines have standardized benefit sharing mechanisms for various forestry and environment based projects/programs which will be applicable to all districts of the state. Benefit sharing of ecosystem services gained due to conservation and management approach are being shared with the local communities either in terms of monitory value or as right to use, sharing of harvest, incentive mechanism, etc. A transparent benefit sharing guidelines with illustrations based on purpose (agricultural, forestry, environmental), type of resource and traditional knowledge, degree of uncertainty in commercialization, and channel of transfer will reduce information asymmetry between implementation agency and users of biological resources and traditional knowledge.

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Well-structured benefits-sharing mechanisms include stakeholder engagement, incentives that encourage participation, monitoring and reporting on benefit streams, and dispute settlement mechanism. In addition, land ownership and user rights need to be clearly defined. Transparent, accountable and effective governance systems are needed to develop effective benefits sharing mechanisms and foster trust among stakeholders.50 REDD+ benefits may include both direct and indirect benefits. Direct benefits sharing may include cash flow and reward/incentives. Likewise, indirect benefits may include payment for ecosystem services, protection of livelihoods of forest-dwelling communities, enhanced local governance (e.g., transparency, accountability, law enforcement, conflict resolution, and participation including of communities and marginalize groups), greater institutional capacity, human resources capacity and knowledge, improved participation in decision-making, and enhanced resilience to climate change. 8.4.1 Features of Benefit-Sharing Mechanisms An important component to build legality in the REDD+ benefit distribution process is by safeguarding local participation in the design of benefit-sharing mechanisms, and supporting their active involvement in decisions making and resources management.51 This process will strengthen the effectiveness of forest manager efforts to reduce deforestation and forest degradation. Maintaining active and continued participation of stakeholders as well as ensuring reward for their efforts, rights to receive carbon benefits, secure land rights, implementing good governance and decision-making process are crucial and need particular attention when developing benefit sharing mechanisms. Major features of well-functioning benefit sharing mechanisms are given in Table 42. Table 42: Features of Benefit-Sharing Mechanisms and Their Importance Feature of benefit sharing Key area Importance mechanisms Identifies stakeholders, consults with Basis for determining incentives, Stakeholder them, and builds local capacity for them builds ownership, trust and engagement to engage. legitimacy. Estimates costs of people’s sacrifices, Clear and direct incentives for Incentive design determines level, form and timing of stakeholders to engage in REDD- benefit distribution. plus activities. Ensures proper procedures for General trust and legitimacy, and Delivery mechanism reporting, auditing, and monitoring of effective safeguards against benefit streams. corruption. Transparency Harnesses internal and external forces Cost-effective, meaningful levels provisions for increased transparency. of accountability. Prepares for changes in agreements, Avoids costly conflict, disciplines Dispute settlement adopts dispute settlement mechanisms. actors and reduces uncertainty. Source: IUCN (2009)52

50 Maginnis S and Espinosa C (2009). REDD+ and benefit sharing. IUCN, Washington, USA. 51 Umunay P, Chhetri RB, Acharya H and Sapkota TP (2015). Institutional and cost-benefit-sharing arrangement for implementation of emission reductions programme in 12 TAL districts of Nepal. REDD Implementation Centre, Ministry of Forests and Soil Conservation, Nepal. 52 Maginnis S and Espinosa C (2009). REDD+ and benefit sharing. IUCN, Washington, USA.

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The development of benefit-sharing mechanisms depend upon government policies that provide carbon rights,53 that would support carbon trading as a form of property in voluntary and regulatory markets. 8.4.2 Institutional Benefit-Sharing The process of sharing financial incentives of REDD+ with domestic stakeholders, particularly village communities, determine the success of REDD+.54 Therefore, it is imperative to formulate a vibrant institutional arrangement system at the national and local levels for sharing of cost and benefits. Institutional mapping is essential to map the existing benefit-sharing mechanism within different state/jurisdiction/forest regimes, in order to build an understanding of the system and identify institutional gaps. Institutional mapping helped identify activities, types of benefits, key actors, beneficiaries and social values. Institutional arrangements supporting benefit sharing should be dynamic and inclusive to accommodate all valid concerns. The institutional based benefit-sharing mechanisms under REDD+ can be categorized along two main axes: (i) a vertical axis of benefit-sharing across scales from national to local, and (ii) a horizontal axis of sharing within and across communities, households and other local stakeholders.55 The above benefit sharing mechanism needs to be planned to maximize equity among the stakeholders responsible for minimizing negative forest change, improve the effectiveness of forest management and increase the efficiency of national and subnational programs.56 Critical analysis of the existing benefit-sharing system in the country/jurisdiction was carried out in assessing the application of best practices for reducing inequality against vulnerable groups (women and indigenous people), financial management procedures, mechanism of benefits distribution, independent monitoring of performance and the structural capacity to resolve disputes in existing forest regimes. In India, particularly in the state of Madhya Pradesh several national/international and state funded schemes are operational on forestry and livelihoods (Box 1). Each scheme/program follow some standard benefit sharing or usufruct sharing mechanism at community level. REDD+ project may adopt benefit sharing mechanism from the existing schemes or may develop its own benefit sharing mechanism on the basis of its learning from the existing system. BOX 1: Incentive Measures in India India has a gamut of economic incentives for forest dependent communities which has had a bearing on utilization/management of natural resources. A range of flexible incentives, in the framework of well-defined social/environmental goals or performance standards, is the most promising approach. Voluntary flexible incentives may have three complementary advantages: they reduce resistance to regulation, they provide value to landowners for supplying important non-market benefits associated with environmental conservation, and they encourage increases in conservation effort. The right incentive mechanisms can encourage positive changes in land-use patterns at lower cost. Incentives may also induce

53 Streck, C. (2009). Rights and REDD+: legal and regulatory considerations. Pages 151-162 in A. Angelsen, editor. Realising REDD+: national strategy and policy options. Center for International Forestry Research, Bogor, Indonesia. 54 USAID (2012) Institutional Assessment tool for benefit sharing under REDD+. Property Rights and Resource Governance Project (PRRGP) 55 Lindhjem, 2010. Who should benefit from REDD+? Rationales and realities. UN-REDD 2010. 56 Brockhaus, M. and A. Angelsen, 2012, Seeing REDD + through 4Is: A Political Economy Framework. Analysing REDD. Center for International Forestry Research (CIFOR), Bogor, Indonesia.

120 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) innovations in conservation approach and in the techniques employed in land management for commercial uses that allow some habitat objectives to be met. Regulation, acquisition and incentives are necessary components for balancing ecological effectiveness with economic efficiency to conserve nature. Some of the major central or state schemes/programs with well-established sharing mechanism with local communities are: 1. Benefit sharing in NAP Scheme: Benefit sharing of harvest, Monitory benefit, Ecosystem services. 2. Benefit sharing under National Biodiversity Policy: local communities were recognized and rewarded for providing the genetic resource and associated traditional knowledge that resulted in commercialization of a drug with anti-fatigue properties called “Jeevani” (in tribal areas). 3. Benefit sharing under Tribal Act, FRA, 2006: Forestland, MFP, monetary benefits in terms of schemes. 4. Sharing under MGNREGA: In accordance with the provision of the MGNREGA Act 2005, where plantation has been done in the community lands, the tree and the entire usufruct from them are to be assigned to the vulnerable sections identified by the Gram Sabha. For plantation in the forestlands, sharing of usufruct to the households maintaining plantations should be not less than what is given under the Joint Forest Management system. 5. JFMCs: JFMCs have full rights over all the NTFPs except the nationalized Minor Forest Produce (tendu leaves, sal seeds, cashews, etc.). Benefit-sharing mechanisms vary according to State forest guidelines. In West Bengal, only 25% of the total sale from timber, inter-mediatory works, and cashew cultivation in the forests is shared with the communities. In MP, this amount is 30% of net income from the sale of timber and 100% of income from intermediate yield like thinning, cleaning, etc. In Rajasthan, 50% of total income from the sale of wood goes back to the community. In Tamil Nadu, 75% from the sale of wood is distributed among the communities and 25% is remitted to the village forest development fund, to be shared with the communities. In addition to these, communities are entitled to collect fuel wood and fodder grass which is available from forests free of cost in all states. 6. Benefit sharing under Japanese International Cooperation Agency (JICA) projects: Under JICA, the Committee members need to protect the forests and plantations for at least five years to be eligible for receiving benefits under the program. Upon satisfactory performance, the members receive 25% of the net income derived from forest crops for every harvest at the concerned forests and plantations. In addition, the members may also be given 25% of the income generated from intermediate felling. Furthermore, members are entitled to collect the following items free of royalty if they do not damage the forests and plantations:  Fallen twigs, grass, fruits, flowers, seeds and leaves, and medicinal plants;  One fourth of the products obtained as intermediate yields from thinning, etc.;  25% of the sale proceeds of minor forest products; and 7. GIM: Monitory benefit for JFMC/EDCs and environmental services for all. 8. Conservation Incentives: To encourage people, institutions, communities, men, and women to contribute to rehabilitation and conservation of elements of biological diversity, and reward excellence and achievement in these, several incentives and awards have been

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instituted by the government. Some of these are Indira Priyadarshini Vrikshamitra (Friend of Trees) Awards, B.P. Pal National Environment Fellowship Award for Biodiversity, Apna Van, and Indira Gandhi Paryavaran Puraskar. Several NGOs and private sectors honor scientist/researchers for their contribution on environmental conservation by providing incentives and awards.

However, in order to finalize the suited benefit sharing system for REDD+ jurisdiction of Hoshangabad District, a common discussion through stakeholder consultations was carried out with state forest department. It allows insights to be obtained from stakeholders, including their concerns, experience and knowledge relevant to the REDD+ benefits sharing mechanism, and to integrate their needs, claims, roles and responsibilities into the formulation of such mechanisms to ensure effectiveness, equity, efficiency, and transparency. 8.4.3 Fund-Based and Market-Based Financing for REDD+: Possible Channels While benefits are distributed from the national or sub-national Jurisdictional REDD+ agency, there will be a number of actors/beneficiaries at various levels to take a share of the REDD+ benefits, for their contribution or may be as their right to resources. The two major financing sources expected for REDD+ are (1) fund-based and (2) market-based funding. The key difference between fund-based and market-based financing is that fund-based assets are intended to support readiness and the continuing efforts of countries to engage in REDD, while market-based fund represent direct payments (purchases) in exchange for the carbon stock, environmental service of forest carbon sequestration and storage, etc.57 It differs according to the source of funds, and the channels by which the funds reach their anticipated beneficiaries. Fund-based payments would typically be directed from international (bilateral and multilateral donor) institutions and organizations to the national level organization (including national government implementing body, country level international donor/NGOs, national NGOs) and then to sub-national entities and local communities (including regional office of international donor/NGO, government regional/state/district office, regional/district level NGOs) to support the development of national-level REDD programs. Different organization/institution would be designated for different purposes and geographical locations based on apparent need in supporting national REDD+ mechanism. Market-based fund flow could be directed through the International based financial bodies (organization/NGOs, etc.) to the national government, regional or local government administrator, or directly to a sub-national or community-based entity. Funds distributed to the national government could either go directly to local communities or through a sub-national intermediary organization or developer. In contrast to the needs-based provision of fund-based resources, market-based funding would be disseminated principally based on the performance of the recipients in increasing carbon stocks in their forests. The horizontal distribution of benefits at the lowest level is crucial for responsible management of the forests. It involved benefit distribution to private and community forest owners. This is the bottom beneficiary level where the drivers for deforestation and forest degradation find

57 Khatri, D. B., Karki, R., & Bushley, B. (2010). REDD+ Payments and Benefit-Sharing Mechanisms in Nepal. ForestAction.

122 Jurisdictional REDD+ Project | Hoshangabad District (Madhya Pradesh) application. Therefore distribution of benefits (especially cash) along the vertical axis should not starve the lowest levels of sufficient incentives to participate in the national REDD+ Strategy.58 8.4.4 Transfer of Funds Three possible approaches and six possible scenarios for transferring funds between the international/ national and local bodies has been identified based on the REDD+ experience of different countries. National Approach: There are four possible scenarios under the national approach: 1. International payment received by National REDD+ Cell and utilized. 2. International/national payment received by National REDD+ Cell and transferred to the State REDD+ Cell. 3. International/national payment received by National REDD+ Cell and distributed through the regional/local government system bodies (like REDD+ Cell) to the projects or actors (project level). 4. International/national payment received by National REDD+ Cell and distribute directly to projects Sub-National Approach: There are two possible scenario under subnational approach: 5. International/national payment received directly by State REDD+ Cell and utilized. 6. International/national payment received by State REDD+ Cell and distribute to REDD+ projects (beneficiaries). Project Approach: There is one possible scenario under project approach: 7. Individual project/actors (or their aggregate bodies) directly access international/ national market, investors, or donors and receive fund directly. As the state of Madhya Pradesh has well established institutional system and well described decentralized system of fund transfer from the central government to the state department and finally to beneficiaries. Considering the present fund flow mechanism in the state as well as at district level, fund transfer scenario 3 and 6 could be the most suitable as compared to other scenario. 8.4.5 Fund flow through MPFD and proposed Benefit Sharing REDD+ has the potential to generate a variety of benefits. Direct financial incentives (e.g., carbon credits payments) are the primary mechanism for achieving emissions reductions, and REDD+ proponents hope that these payments will flow to local forest communities and others directly contributing to REDD+. There are also a number of (monetary and non-monetary) “co-benefits” that can also arise from REDD+. Decision-making process for REDD+ benefit sharing should include effective engagement of state level government agencies (i.e., MPFD) and local/village level community institutions (i.e., JFMCs/Village Development Committees) to help maintain the legality of REDD+ and to lead to solutions suited to different local contexts. Benefits then distributed horizontally by states agency to local level constituencies could be either monetary or non-monetary, allocated based on efforts made to address the drivers of deforestation and forest degradation, reduce barriers to sustainable natural resource management, and support sustainable rural development.

58 IUCN. (2012). Benefit Sharing in Uganda’s Forestry Sector: Issues and Options for REDD Implementation in Uganda. IUCN. Retrieved from https://cmsdata.iucn.org/downloads/redd__benefit_sharing_in_uganda___full_study.pdf

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A standard fund flow process and sharing of benefit among the stakeholders in Forest-PLUS landscapes is drawn based on the learning from REDD+ projects of Indonesia, Mexico, Tanzania, and other African countries. The vertical fund flow involve fund received by the MPFD from the international funding agencies/national level agencies and its movement down to the MP REDD+ Cell and to district level forest agencies (FDAs). The horizontal fund flow includes fund flows from FDA to Gram Panchayat, village community (JFMCs/EDCs) and finally to beneficiary. Local stakeholders should have the opportunity to develop their own investment plans that specify how they intend to reduce deforestation and forest degradation. Multi-stakeholder committees should be formed at the state level to select investment plans based on state-level REDD+ strategies, guided by the central/state government. Safeguards will guide the development and implementation of investment plans, government policies and benefit sharing. Sharing of funds should be finalized after consultation with all the stakeholders and following existing policy/norms. However, a generalized fund sharing mechanism is projected for various forest areas of India based on the benefit sharing mechanism proposed for various REDD+ project across the globe.59, 60, 61 The existing resource sharing mechanisms in community managed forest lands of India was also taken into consideration.62 Government Forest Areas: This includes lands under the control of state forest department and central government like reserve forests, protected forests, national parks, biosphere reserves, etc. As these lands are under the greater control of central or state government, we propose 50 percent share for forest department also. Funds for higher institutions: Maximum 50 percent of the fund may be utilized for implementation, institutional charges and maintenance activities of higher level institutions (like REDD+ cell, SFDA, FDA, etc.). This fund may also be used as corpus fund for payment to community in case of emergency or delay of fund release from national or international funders. Funds for village community/households: Minimum 50 percent of the fund may be utilized for distribution at the village level. Effective method of disbursement of fund should be adopted at community level (detail is described in next section). Community Forest Areas: The community forestlands are managed by the local community with technical inputs from state forest department. Therefore higher share of benefit are suggested for communities (figure 5). 1. Funds for higher institutions: Maximum 10 percent (0–10 percent) of the fund may be utilized for institutional charges and maintenance activities of higher level institutions (like REDD+ cell, SFDA, FDA, etc.) subject to approval. 2. Funds for village community/households: Ninety to hundred percent of the fund may be utilized for distribution at the village level. Effective method of disbursement of fund should be adopted at community level (detail is described in next section).

59 Institutional and Cost-Benefit-Sharing Arrangement for Implementation of Emission Reductions Programme in 12 TAL Districts of Nepal. REDD Implementation Centre, Ministry of Forests and Soil Conservation, Nepal. 60 Developed comparing REDD+ case study of Tanzania, Africa, Indonesia, and Nepal. 61 USAID. (2012). Institutional assessment tool for benefit sharing under REDD+. 62 Vemuri A (2008). Joint Forest Management in India: An Unavoidable and Conflicting Common Property Regime in Natural Resource Management. Journal of Development and Social Transformation.

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8.4.6 Benefit Distribution at the Village Level India has well-developed JFM guidelines that are being followed by all the states and UTs for implementation of community based schemes and programs. For REDD+ project, JFM guidelines may be adopted for community based payment to make it cost effective and to minimize local dispute. Benefits can be distributed through the existing village governing bodies (panchayat or JFMC, etc.) or new community groups as the case may be. 8.4.7 Eligibility Criteria and Distribution Agreements There must be well accepted criteria to determine the share of payment to each participating village/households/individuals. The provision of benefits could be based on aggregate wattage to multiple criteria set on mutual agreement, such as:  Quality of forest conserved  Community participation  Total land holding  Area under forest cover. It is important to ensure that equitable design criteria are met. It is very important to ensure that more susceptible groups/people such as ethnic minorities, the small landholders and landless poor, women and children are given due importance. It may also be necessary to know the impact of benefit transferred on the prosperity of the communities and the local economy.63 Ensuring the poor or the most vulnerable sections of society benefit from REDD+ is key mainly to build both national and international legitimacy, and foster successful delivery of conservation and social objectives. Whereas REDD+ is performance-based, there may be good reasons for sharing some level and types of benefits among villages or other actors that are not directly involved in REDD+. For example, villages outside the project area may bear some expenses (e.g., controlled access to previously used resources) and/or influence project success (e.g., be a source of leakage).64 It is necessary to avoid conflicts between those who get benefit, and those who do not get. Such sharing may also be a practical obligation, e.g., where access to a forest on the land of one village is actually controlled by another village not involved in the REDD+ scheme. At the same time, as discussed above, revenues cannot be shared with all people. The scope of benefit sharing will need to balance inclusiveness and limitations, based on fair criteria. 8.4.8 Integrating Safeguards in Benefit-Sharing Mechanisms Safeguard policies often provide a platform for the participation of stakeholders in assessing impacts, as well as mitigating negative impacts. An appropriately designed safeguard system could identify potential positive impacts of REDD+ activities, and actions that could support positive move. An important element of any REDD+ safeguard system is broad participation and open access to information. REDD+ benefit sharing should be designed, implemented and monitored in accordance with the developing national safeguards system. Drawing on international safeguards, relevant considerations may include:

63 Mohammed EY (2011). Pro-poor benefit distribution in REDD+: who gets what and why does it matter? REDD Working Paper. IIED, London. 64 Campese, J. (2012). Equitable Benefit Sharing: Exploring Experiences and Lessons for REDD+ in Tanzania. Tanzania Natural Resource Forum.

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 Full and effective participation  Free, prior and informed consent  Effective representation  Transparency  Accountability  Gender equality  Respect for human rights  Secure land, forest and carbon tenure  Dispute resolution; and monitoring.

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9.0 Other Project Details 9.1 Start Date and Crediting Period The start date for project crediting is to be determined based on the actual emissions saving activities on ground. The expected date is August 15, 2017. The program-crediting period is 20 years and no months. It will be renewed every 10 years. 9.2 Details of Project Design The REDD+ design includes many components that addresses sustainable management and enhancement of forest resources. Under the USAID-funded Forest-PLUS Program, many activities have been initiated in the landscape to conserve forests. Major drivers of forest change in the jurisdiction were identified through intensive socio-economic surveys and consultations with personnel from MPFD. Socio-economic analysis included the use of household surveys and focused group discussions in villages to evaluate the forest dependency of local communities. 9.3 Activities and Consultations in the Program The landscape for the Project in Hoshangabad was finalized in June 2013, as part of the USAID- funded Forest-PLUS program. It was approved by the MoEFCC, after a joint decision taken by the MoEFCC, Forest Survey of India, Indian Council of Forestry Research and Education, Indira Ghandi National Forest Academy, and USAID based on the selection criteria. It was further decided that a jurisdictional REDD+ project will be promoted as the first jurisdictional REDD+ project in India (at a sub-national level), covering the whole Hoshangabad District as the jurisdiction. The evidence and capabilities in favor of this decision was:  India’s Draft National REDD+ Policy endorses the development of jurisdictional REDD+ at sub-national scales.  International REDD+ negotiations are increasingly focusing towards the development of jurisdictional REDD+ Programs.  It will be the first jurisdictional-level REDD+ Program in India, and one of the first in the world.  It would help develop national jurisdictional REDD+ methodologies.  It would be able to capture Hoshangabad’s accomplishments in forest regrowth and associated carbon credits.

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