Editing IPCC:AR6/WGIII/Chapter-7 (section)

=== 7.6.2 Review of Observed Policies and Policy Instruments ===

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==== 7.6.2.1 Economic Incentives ====

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'''Emissions Trading/Carbon Taxes.''' While emissions trading programmes have been developed across the globe, forest and agriculture have not been included as part of the cap in any of the existing systems. However, offsets from forestry and agriculture have been included in several of the trading programs. New Zealand has a hybrid programme where carbon storage in forests can be voluntarily entered into the carbon trading program, but once entered, forests are counted both as a sink for carbon if net gains are positive, and a source when harvesting occurs. New Zealand is considering rules to include agricultural GHG emissions under a future cap ( [[#Henderson--2020|Henderson et al. 2020]] ; see: [https://www.agmatters.nz/topics/he-waka-eke-noa/ https://www.agmatters.nz/topics/he- waka-eke-noa/] ).

The state of California has developed a formal cap and trade programme that allows a limited number of forest and agricultural offset credits to be used under the cap. All offsets must meet protocols to account for additionality, permanence and leakage. Forest projects used as offsets in California currently are located in the USA, but the California Air Resources Board adopted a tropical forest carbon standard, allowing for avoided deforestation projects from outside the USA to enter the California market ( [[#CARB--2019|CARB 2019]] ).

Canadian provinces have developed a range of policy options that can include carbon offsets. Quebec has an emissions trading programme that plans to allow forest and agricultural offsets generated within the province to be utilised. Alberta also allows offsets to be utilised by regulated sectors while British Columbia allows offsets to be utilised by the government for its carbon neutrality goals ( [[#Government%20of%20Alberta--2021|Government of Alberta, 2021]] ). Over 20 countries and regions have adopted explicit carbon taxes on carbon emission sources and fossil fuels, however, the charges have not been applied to non-CO 2 agricultural emissions ( [[#OECD--2021a|OECD 2021a]] ). California may implement regulations on methane emissions from cattle, however, regulations if approved, will not go into effect until 2024. Institutional and trade-related barriers (e.g., leakage) likely will limit widespread implementation of taxes on emissions in the food sector globally. Many countries exempt purchases of fuels used in agricultural or fishery production from fuel or carbon taxes, thus lowering the effective tax rate imposed on those sectors ( [[#OECD--2021a|OECD 2021a]] ). Furthermore, bioenergy, produced from agricultural products, agricultural waste, and wood is often exempted from explicit carbon taxes. Colombia recently implemented a carbon tax on liquid fuels but allowed domestically produced forestry credits to offset the tax. Colombia also is in the process of developing an emissions trading scheme ( [[#OECD--2021a|OECD 2021a]] ).

'''REDD+/Payment for Ecosystem Services (PES).''' PES programmes for a variety of ecosystem services have long been utilised for conservation (e.g., [[#Wunder--2007|Wunder 2007]] ) and may now be as large as USD42 billion yr –1 ( [[#Salzman--2018|Salzman et al. 2018]] ). REDD+ emerged in the early 2000s and is a widely recognised example of PES programme focused on conservation of tropical forests (Table 7.4). However, our summation of actually paid funds in Table 7.4 is much smaller than what is portrayed by [[#Salzman--2018|Salzman et al. (2018)]] . REDD+ may operate at the country level, or for specific programmes or forests within a country. As with other PES programs, REDD+ has evolved towards a results-based programme that involves payments that are conditioned on meeting certain successes or milestones, such as rates of deforestation ( [[#Angelsen--2017|Angelsen 2017]] ).

A large literature has investigated whether PES programmes have successfully protected habitats. Studies in the USA found limited additionality for programmes that encouraged conservation tillage practices, but stronger additionality for programmes that encouraged set-asides for grasslands or forests ( [[#Woodward--2016|Woodward et al. 2016]] ; [[#Claassen--2018|Claassen et al. 2018]] ), although the set-asides led to estimated leakage of 20 up to 100% ( [[#Pfaff--2017|Pfaff and Robalino 2017]] ; Kallio et al. 2018; [[#Wu--2000|Wu 2000]] ). Evidence from the EU similarly suggests that payments for some agroenvironmental practices may be additional, while others are not ( [[#Chabé-Ferret--2013|Chabé-Ferret and Subervie 2013]] ). Other studies, in particular in Latin America where many PES programmes have been implemented, have found a wide range of estimates of effectiveness (e.g., Honey-Rosés et al. 2011; [[#Robalino--2013|Robalino and Pfaff 2013]] ; [[#Alix-Garcia--2015|Alix-Garcia et al. 2015]] ; [[#Robalino--2015|Robalino et al. 2015]] ; [[#Mohebalian--2016|Mohebalian and Aguilar 2016]] ; [[#Jayachandran--2017|Jayachandran et al. 2017]] ; [[#Börner--2017|Börner et al. 2017]] ; [[#Burivalova--2019|Burivalova et al. 2019]] ). Despite concerns, the many lessons learned from PES programme implementation provide critical information that will help policymakers refine future PES programmes to increase their effectiveness ( ''medi'' ''um confidence'' ).

While expectations that carbon-centred REDD+ would be a simple and efficient mechanism for climate mitigation have not been met ( [[#Turnhout--2017|Turnhout et al. 2017]] ; [[#Arts--2019|Arts et al. 2019]] ), progress has nonetheless occurred. Measuring, monitoring and verification systems have been developed and deployed, REDD readiness programmes have improved capacity to implement REDD+ on the ground in over 50 countries, and a number of countries now have received results-based payments.

Empirical evidence that REDD+ funding has slowed deforestation is starting to emerge. [[#Simonet--2019|Simonet et al. (2019)]] showed that a REDD+ project in Brazil reduced deforestation certainly until 2018, while [[#Roopsind--2019|Roopsind et al. (2019)]] showed that country-level REDD+ payments to Guyana encouraged reduced deforestation and increased carbon storage. Although more impact evaluation (IE) analysis needs to be conducted on REDD+ payments, these studies support the country-level estimates of carbon benefits from REDD+ shown in Table 7.4. Nearly all of the analysis of PES and REDD+ to date has focused on the presence or absence of forest cover, with little to no analysis having been conducted on forest degradation, conservation, or enhancement of forest stocks.

'''Agroenvironmental Subsidy Programs/PES.''' Climate policy for agriculture has developed more slowly than in other sectors due to concerns with food security and livelihoods, political interests, and difficulties in coordinating diffuse and diverse activities and stakeholders (e.g., nutritional health, rural development, and biodiversity conservation) ( [[#Leahy--2020|Leahy et al. 2020]] ). However, a review of the National Adaptation Programme of Action (NAPAs), National Adaptation Plans (NAPs), NAMAs, and NDCs in the Paris Agreement suggest an increasing focus of policy makers on agriculture and food security. The vast majority of parties to the Paris Agreement recognise the significant role of agriculture in supporting a secure sustainable development pathway ( [[#Richards--2015|Richards and VanWey 2015]] ) with the inclusion of agriculture mitigation in 103 NDCs from a total of 160 NDC submissions. Livestock is the most frequently cited specific agricultural sub-sector, with mitigation activities generally focusing on increasing efficiency and productivity.

Agriculture is one of the most subsidised industries globally, especially in the European Union and the USA. While subsidy payments over the last 20 years have shifted modestly to programmes designed to reduce the environmental impact of the agricultural sector, only 15–20% of the more than USD700 billion spent globally on subsidies are green payments ( [[#OECD--2021b|OECD 2021b]] ). Under the Common Agricultural Policy in the EU, up to 30% of the direct payments to farmers (Pillar 1) have been green payments ( [[#Henderson--2020|Henderson et al. 2020]] ), including some actions that could increase carbon storage or reduce emissions. Similarly, at least 30% of the rural development payments (Pillar 2) are used for measures that reduce environmental impact, including reduction of GHG emissions and carbon storage. There is limited evidence that these policies contributed to the 20% reduction in GHG emissions from the agricultural sector in the EU between 1990 and 2018 ( [[#Baudrier--2015|Baudrier et al. 2015]] ; [[#Eurostat--2020|Eurostat 2020]] ).

The USA spends USD4 billion yr –1 on conservation programs, or 12% of net farm income ( [[#Department%20of%20Agriculture--2020|Department of Agriculture 2020]] ). In real terms, this expenditure has remained constant for 15 years, supporting 12 Mha of permanent grass or woodland cover in the Conservation Reserve Program (CRP), which has increased soil carbon sequestration by 3 tCO 2 ha –1 yr –1 ( [[#Conant--2017|Conant et al. 2017]] ; [[#Paustian--2019|Paustian et al. 2019]] ), as well as other practices that could lower net emissions. Gross GHG emissions from the agricultural sector in the US, however, have increased since 1990 ( [[#USEPA--2020|USEPA 2020]] ) due to reductions in the area of land in the US CRP programme and changes in crop rotations, both of which caused soil carbon stocks to decline ( [[#USEPA--2020|USEPA 2020]] ). When combined with increased non-CO 2 gas emissions, the emission intensity of US agriculture increased from 1.5 to 1.7 tCO 2 ha –1 between 2005 and 2018 ( ''hi'' ''gh confidence'' ).

China has implemented large conservation programmes that have influenced carbon stocks. For example, the Sloping Land Conversion Program, combined with other programs, has increased forest cover and carbon stocks, reduced erosion and increased other ecosystem services in China in recent years ( [[#Ouyang--2016|Ouyang et al. 2016]] ). As part of Brazil’s national strategy, numerous practices to reduce GHG emissions from agriculture, and in particular from the animal agriculture industry, have been subsidised. Estimates by Manzatto et al. (2020) suggest that the programme may have reduced agricultural emissions by 169 MtCO 2 between 2010 and 2020. Given the large technical and economic potential for agroforestry to be deployed in Africa, subsidy approaches could be deployed along with other polices to enhance carbon through innovative practices such as regreening (Box 7.10).

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==== 7.6.2.2 Regulatory Approaches ====

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'''Regulations''' on land use include direct controls on how land is used, zoning, or legally set limits on converting land from one use to another. Since the early 2000s, Brazil has deployed various regulatory measures to slow deforestation, including enforcement of regulations on land-use change in the legal Amazon area. Enforcement of these regulations, among other approaches is credited with encouraging the large-scale reduction in deforestation and associated carbon emissions after 2004 ( [[#Nepstad--2014|Nepstad et al. 2014]] ). Empirical evidence has found that regulations reduced deforestation in Brazil ( [[#Arima--2014|Arima et al. 2014]] ) but over time, reversals occurred when enforcement was not consistent ( [[#Azevedo--2017|Azevedo et al. 2017]] ) (Box 7.9).

Many OECD countries have strong legal frameworks that influence agricultural and forest management on both public and private land. These include for example, legal requirements to protect endangered species, implement conservation tillage, protect riparian areas, replant forests after harvest, maintain historical species composition, forest certification, and other approaches. Increasingly, laws support more widespread implementation of nature-based solutions for a range of environmental issues (e.g., see [[#European%20Commission-EU--2021|European Commission-EU 2021]] ). The extent to which the combined influence of these regulations has enhanced carbon storage in ecosystems is not quantified although they are likely to explain some of the persistent carbon sink that has emerged in temperate forests of OECD countries ( ''high confidence'' ). In the least developed and developing countries, regulatory approaches face challenges in part because environmental issues are a lower priority than many other socio-economic issues (e.g., poverty, opportunity, essential services), and weak governance ( [[#Mayer%20Pelicice--2019|Mayer Pelicice 2019]] ; [[#Walker--2020|Walker et al. 2020]] ) (Box 7.2).

'''Set asides and protected areas''' have been a widely utilised approach for conservation, and according to ( [[#FAO--2020d|FAO 2020d]] ), 726 Mha (18%) of forests are in protected areas globally. A review of land sparing and land sharing policies in developing countries indicated that most of them follow land sparing models, sometimes in combination with land sharing approaches. However, there is still no clear evidence of which policy provides the best results for ecosystem services provision, conservation, and livelihoods ( [[#Mertz--2017|Mertz and Mertens 2017]] ). The literature contains a wide range of results on the effectiveness of protected areas to reduce deforestation ( [[#Burivalova--2019|Burivalova et al. 2019]] ), with studies suggesting that protected areas provide significant protection of forests (e.g., [[#Blackman--2015|Blackman 2015]] ), modest protection ( [[#Andam--2008|Andam et al. 2008]] ), as well as increases in deforestation ( [[#Blackman--2015|Blackman 2015]] ) and possible leakage of harvesting to elsewhere (Kallio et al. 2018). An estimate of the contributions of protected areas to mitigation between 2000 and 2012, showed that in the tropics, PAs reduced carbon emissions from deforestation by 4.88 PgC, or around 29%, when compared to the expected rates of deforestation ( [[#Bebber--2017|Bebber and Butt 2017]] ). In that study, the tropical Americas (368.8 TgC yr −1 ) had the largest contribution, followed by Asia (25.0 TgC yr −1 ) and Africa (12.7 TgC yr −1 ). The authors concluded that local factors had an important influence on the effectiveness of protected areas. For example, in the Brazilian Amazon, protected area effectiveness is affected by the government agency controlling the land (federal indigenous lands, federal PAs, and state PAs) ( [[#Herrera--2019|Herrera et al. 2019]] ). Because protected areas limit not just land-use change, but also logging or harvesting non-timber forest products, they may be relatively costly approaches for forest conservation ( ''medi'' ''um confidence'' ).

'''Community forest management (CFM)''' allows less intensive use of forest resources, while at the same time providing carbon benefits by protecting forest cover. Community forest management provides property rights to communities to manage resources in exchange for their efforts to protect those resources. In many cases, the local communities are indigenous people who otherwise would have insecure tenure due to an advancing agricultural frontier or mining activity. Other examples are forest owner associations like those discussed in Box 7.8. According to the [[#Rights%20and%20Resources%20Initiative--2018|Rights and Resources Initiative (2018)]] , the area of forests under community management increased globally by 152 Mha from 2002 to 2017, with over 500 Mha under community management in 2017. Studies have now shown that improved property rights with community forest management can reduce deforestation and increase carbon storage ( [[#Deininger--2002|Deininger and Minten 2002]] ; [[#Alix-Garcia--2005|Alix-Garcia et al. 2005]] ; [[#Alix-Garcia--2007|Alix-Garcia 2007]] ; [[#Bowler--2012|Bowler et al. 2012]] ; [[#Blackman--2015|Blackman 2015]] ; [[#Fortmann--2017|Fortmann et al. 2017]] ; [[#Burivalova--2019|Burivalova et al. 2019]] ). Efforts to expand property rights, especially community forest management, have reduced carbon emissions from deforestation in tropical forests in the last two decades ( ''high confidence'' ), although the extent of carbon savings has not been quantified globally.

'''Bioenergy targets.''' Multiple policies have been enacted at national and supra-national levels to promote the use of bioenergy in the transport sector, and for bioelectricity production. Existing policies mandate or subsidise the production and use of bioenergy. In the past few years, policies have been proposed, put in place or updated in Australia (Renewable Energy Target), Brazil (RenovaBio, Nationally Determined Contribution), Canada (Clean Fuel Standard), China (Biodiesel Industrial Development Policy, Biodiesel Fuel Blend Standard), the European Union (Renewable Energy Directive II), the USA (Renewable Fuel Standards), Japan (FY2030), Russia (Energy Strategy Bill 2035), India (Revised National Policy on Biofuels), and South Africa (Biofuels Regulatory Framework).

While current policies focus on bioenergy to decarbonise the energy system, some also contain provisions to minimise the potential environmental and social trade-offs from bioenergy production. For instance, the EU Renewable Energy Directive (EU-RED II) and US Renewable Energy Standard (US-RFS) assign caps on the use of biofuels, which are associated with indirect land-use change and food-security concerns. The Netherlands has a stringent set of 36 sustainability criteria to which the certified biomass needs to comply. The EU-RED II also sets a timeline for the complete phase-out of high-risk biofuels ( [[#7.4.4|Section 7.4.4]] ).

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==== 7.6.2.3 Voluntary Actions and Agreements ====

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'''Forest certification programs''' , such as Forest Sustainability Council (FSC) or Programme for the Endorsement of Forest Certification (PEFC), are consumer driven, voluntary programmes that influence timber harvesting practices, and may reduce emissions from forest degradation with reduced impact logging and other approaches ( ''medium confidence'' ). Forest certification has expanded globally to over 440 Mha ( [[#Kraxner--2017|Kraxner et al. 2017]] ). As the area of land devoted to certification has increased, the amount of timber produced from certified land has increased. In 2018, FSC accounted for harvests of 427 million m 3 and jointly FSC and PEFC accounted for 689 million m 3 in 2016 or around 40% of total industrial wood production ( [[#FAO--2018c|FAO 2018c]] ). There is evidence that reduced impact logging can reduce carbon losses in tropical regions ( [[#Pearson--2014|Pearson et al. 2014]] ; [[#Ellis--2019|Ellis et al. 2019]] ). However, there is conflicting evidence about whether forest certification reduces deforestation (e.g., [[#Blackman--2018|Blackman et al. 2018]] ; [[#Tritsch--2020|Tritsch et al. 2020]] ).

'''Supply chain management''' in the food sector encourages more widespread use of conservation measures in agriculture ( ''high confidence'' ). The number of private commitments to reduce deforestation from supply chains has greatly increased in recent years, with at least 865 public commitments by 447 producers, processors, traders, manufacturers and retailers as of December, 2020 ( [[#New%20York%20Declaration%20on%20Forests--2021|New York Declaration on Forests 2021]] ). Industry partnerships with NGOs, such as the Roundtable on Sustainable Palm Oil (RSPO), have become more widespread and visible in agricultural production. For example, RSPO certifies members all along the supply chain for palm oil and claims around 19% of total production. Similar sustainability efforts exist for many of the world’s major agricultural products, including soybeans, rice, sugar cane, and cattle.

There is evidence that the Amazon Soy Moratorium (ASM), an industry-NGO effort whereby large industry consumers agreed voluntarily not to purchase soybeans grown on land deforested after 2006, reduced deforestation in the legal Amazon ( [[#Nepstad--2014|Nepstad et al. 2014]] ; [[#Gibbs--2015|Gibbs et al. 2015]] ). However, recent studies have shown that some deforestation from the Amazon was displaced to the Cerrado (Brazilian savannas) region ( [[#Moffette--2021|Moffette and Gibbs 2021]] ), which is a global hotspot for biodiversity, and has significant carbon stocks. These results illustrate the importance of broadening the scope of supply chain management to minimise or eliminate displacement ( [[#Lima--2019|Lima et al. 2019]] ). In addition, while voluntary efforts may improve environmental outcomes for a time, it is not clear that they are sufficient to deliver long-term reductions in deforestation, given the increases in deforestation that have occurred in the Amazon in recent years (Box 7.9). Voluntary efforts would be more effective at slowing deforestation if they present stronger linkages to regulatory or other approaches ( [[#Lambin--2018|Lambin et al. 2018]] ).

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