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

=== 7.6.4 Barriers and Opportunities for AFOLU Mitigation ===

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The AR5 and other assessments have acknowledged many barriers and opportunities to effective implementation of AFOLU measures. Many of these barriers and opportunities focus on the context in developing countries, where a significant portion of the world’s cost-effective mitigation exists, but where domestic financing for implementation is likely to be limited. The SSPs capture some of this context, and as a result, IAMs ( [[#7.5|Section 7.5]] ) exhibit a wide range of land-use outcomes, as well as mitigation potential. Potential mitigation, however, will be influenced by barriers and opportunities that are not considered by IAMs or by bottom-up studies reviewed here. For example, more efficient food production systems, or sustainable intensification within agriculture, and globalised trade could enhance the extent of natural ecosystems leading to lower GHG emissions from the land system and lower food prices ( [[#Popp--2017|Popp et al. 2017]] ), but this (or any) pathway will create new barriers to implementation and encourage new opportunities, negating potential benefits (Box 7.11). It is critically important to consider the current context in any country.

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==== 7.6.4.1 Socio-economic Barriers and Opportunities ====

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'''Design and coverage of financing mechanisms.''' The lack of resources thus far committed to implementing AFOLU mitigation, income and access to alternative sources of income in rural households that rely on agriculture or forests for their livelihoods remains a considerable barrier to adoption of AFOLU ( ''high confidence'' ). [[#7.6.1|Section 7.6.1]] illustrates that to date only USD0.7 billion yr –1 has been spent on AFOLU mitigation, well short of the more than USD400 billion yr –1 that would be needed to achieve the economic potential described in [[#7.4|Section 7.4]] . Despite long-term recognition that AFOLU can play an important role in mitigation, the ''economic incentives'' necessary to achieve AFOLU aspirations as part of the Paris Agreement or to maintain temperatures below 2.0°C have not emerged. Without quickly ramping up spending, the lack of funding to implement projects remains a substantial barrier ( ''high confidence'' ). Investments are critically important in the livestock sector, which has the highest emissions reduction potential among options because actions in the sector influence agriculture specific activities, such as enteric fermentation, as well as deforestation ( [[#Mayberry--2019|Mayberry et al. 2019]] ). In many countries with export-oriented livestock industries, livestock farmers control large swaths of forests or re-forestable areas. Incentive mechanisms and funding can encourage adoption of mitigation strategies, but funding is currently too low to make consistent progress.

'''Scale and accessibility of financing.''' The largest share of funding to date has been for REDD+, and many of the commitments to date suggest that there will be significant funding in this area for the foreseeable future. Funding for conservation programmes in OECD countries and China affects carbon, but has been driven by other objectives such as water quality and species protection. Considerably less funding has been available for agricultural projects aimed at reducing carbon emissions, and outside of voluntary markets, there do not appear to be large sources of funding emerging either through international organisations, or national programs. In the agricultural sector, funding for carbon must be obtained by redirecting existing resources from non-GHG conservation to GHG measures, or by developing new funding streams ( [[#Henderson--2020|Henderson et al. 2020]] ).

'''Risk and uncertainty.''' Most approaches to reduce emissions, especially in agriculture, require new or different technologies that involve significant time or financial investments by the implementing landholders. Adoption rates are often slow due to risk aversion among agricultural operators. Many AFOLU measures require carbon to be compensated to generate positive returns, reducing the likelihood of implementation without clear financial incentives. Research to show costs and benefits is lacking in most parts of the world.

'''Poverty.''' Mitigation and adaptation can have important implications for vulnerable people and communities, for example, mitigation activities consistent with scenarios examined in the SR1.5 could raise food and fiber prices globally (Section. 7.5). In the NDCs, 82 Parties included references to social issues (e.g., poverty, inequality, human well-being, marginalisation), with poverty the most cited factor (70 Parties). The number of hungry and food insecure people in the world is growing, reaching 821 million in 2017, or one in every nine people ( [[#FAO--2018b|FAO 2018b]] ), and two-thirds live in rural areas (Laborde Debucquet et al. 2020). Consideration of rural poverty and food insecurity is central in AFOLU mitigation because there are a large number of farms in the world (about 570 million), and most are smaller than 2 hectares. It is important to better understand how different mitigation policies affect the poor.

'''Cultural values and social acceptance.''' Barriers to adoption of AFOLU mitigation will be strongest where historical practices represent long-standing traditions ( ''high confidence'' ). Adoption of new mitigation practices, however, may proceed quickly if the technologies can be shown to improve crop yields, reduce costs, or otherwise improve livelihoods ( [[#Ranjan--2019|Ranjan 2019]] ). AR6 presents new estimates of the mitigation potential for shifts in diets and reductions in food waste, but given long-standing dietary traditions within most cultures, some of the strongest barriers exist for efforts to change diets ( ''medium confidence'' ). Furthermore, the large number of undernourished who may benefit from increased calories and meat will complicate efforts to change diets. Regulatory or tax approaches will face strong resistance, while efforts to use educational approaches and voluntary measures have limited potential to slow changes in consumption patterns due to free-riders, rebound effects, and other limitations. Food loss and waste occurs across the supply chain, creating significant challenges to reduce it ( [[#FAO--2019c|FAO 2019c]] ). Where food loss occurs in the production stage, in other words, in fields at harvest, there may be opportunities to align reductions in food waste with improved production efficiency, however, adoption of new production methods often requires new investments or changes in labour practices, both of which are barriers.

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==== 7.6.4.2 Institutional Barriers and Opportunities ====

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'''Transparent and accountable governance.''' Good governance and accountability are crucial for implementation of forest and agriculture mitigation. Effective nature-based mitigation will require large-scale estimation, modelling, monitoring, reporting and verification of GHG inventories, mitigation actions, as well as their implications for sustainable development goals and their interactions with climate change impacts and adaptation. Efforts must be made to integrate the accounting from projects to the country level. While global datasets have emerged to measure forest loss, at least temporarily (e.g., [[#Hansen--2013|Hansen et al. 2013]] ), similar datasets do not yet exist for forest degradation and agricultural carbon stocks or fluxes. Most developing countries have insufficient capacity to address research needs, modelling, monitoring, reporting and data requirements ( [[#Ravindranath--2017|Ravindranath et al. 2017]] ), compromising transparency, accuracy, completeness, consistency and comparability.

Opportunity for political participation of local stakeholders is barrier in most places where forest ownership rights are not sufficiently documented ( [[#Essl--2018|Essl et al. 2018]] ). Since incentives for self-enforcement can have an important influence on deforestation rates ( [[#Fortmann--2017|Fortmann et al. 2017]] ), weak governance and insecure property rights are significant barriers to introduction of forest carbon offset projects in developing countries, where many of the low-cost options for such projects exist (Gren and Zeleke 2016). Governance challenges exist at all levels of government, with poor coordination, insufficient information sharing, and concerns over accountability playing a prominent role within REDD+ projects and programmes ( [[#Ravikumar--2015|Ravikumar et al. 2015]] ). In some cases, governments are increasingly centralising REDD+ governance and limiting the distribution of governance functions between state and non-state actors ( [[#Zelli--2017|Zelli et al. 2017]] ; [[#Phelps--2010|Phelps et al. 2010]] ). Overlap and duplication in Forest Law Enforcement, Governance and Trade (FLEGT) and REDD+ also limits governance effectiveness ( [[#Gupta--2016|Gupta et al. 2016]] ).

'''Clear land tenure and land-use rights.''' Unclear property rights and tenure insecurity undermine the incentives to improve forest and agricultural productivity, lead to food insecurity, undermine REDD+ objectives, discourage adoption of farm conservation practices, discourage tree planting and forest management, and exacerbate conflict between different land users ( [[#Antwi-Agyei--2015|Antwi-Agyei et al. 2015]] ; [[#Felker--2017|Felker et al. 2017]] ; [[#Sunderlin--2018|Sunderlin et al. 2018]] ; [[#Borras--2018|Borras and Franco 2018]] ; [[#Riggs--2018|Riggs et al. 2018]] ; [[#Kansanga--2019|Kansanga and Luginaah 2019]] ). Some positive signs exist as over 500 million hectares of forests have been converted to community management with clear property rights in the past two decades ( [[#Rights%20and%20Resources%20Initiative--2018|Rights and Resources Initiative 2018]] ), but adoption of forest and agricultural mitigation practices will be limited in large remaining areas with unclear property rights ( [[#Gupta--2016|Gupta et al. 2016]] ).

'''Lack of institutional capacity.''' Institutional complexity, or lack thereof, represents a major challenge when implementing large and complex mitigation programmes (e.g., REDD+) in agriculture, forest and other land uses ( [[#Bäckstrand--2017|Bäckstrand et al. 2017]] ). Without sufficient capacity, many synergies between agricultural and forest programs, or mitigation and adaptation opportunities, may be missed ( [[#Duguma--2014|Duguma et al. 2014]] ). Another aspect of institutional complexity is the different biophysical and socio-economic circumstances as well as the public and private financial means involved in the architecture and implementation of REDD+ and other initiatives ( [[#Zelli--2017|Zelli et al. 2017]] ).

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==== 7.6.4.3 Ecological Barriers and Opportunities ====

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'''Availability of land and water.''' Climate mitigation scenarios in the two recent special reports (SR1.5 and SRCCL) that aim to limit global temperature increase to 2°C or less involve carbon dioxide (CO 2 ) removal from the atmosphere. To support large-scale CDR, these scenarios involve significant land-use change, due to afforestation/reforestation, avoided deforestation, and deployment of biomass energy with carbon capture and storage (BECCS). While a considerable amount of land is certainly available for new forests or new bioenergy crops, that land has current uses that will affect not only the costs, but also the willingness of current users or owners, to shift uses. Regions with private property rights and a history of market-based transactions may be the most feasible for land-use change or land management change to occur. Areas with less secure tenure or a land market with fewer transactions in general will likely face important hurdles that limit the feasibility of implementing novel nature-based solutions.

Implementation of nature-based solution may have local or regionally important consequences for other ecosystem services, some of which may be negative ( ''high confidence'' ). Land-use change has important implications for the hydrological cycle, and the large land-use shifts suggested for BECCS when not carried out in a carefully planned manner, are expected to increase water demands substantially across the globe ( [[#Stenzel--2019|Stenzel et al. 2019]] ; [[#Rosa--2020|Rosa et al. 2020]] ). Afforestation can have minor to severe consequences for surface water acidification, depending on site-specific factors and exposure to air pollution and sea-salts ( [[#Futter--2019|Futter et al. 2019]] ). The potential effects of coastal afforestation on sea-salt related acidification could lead to re-acidification and damage on aquatic biota.

'''Specific soil conditions, water availability, GHG emission-reduction potential as well as natural variability and resilience.''' Recent analysis by ( [[#Cook-Patton--2020|Cook-Patton et al. 2020]] ) illustrates large variability in potential rates of carbon accumulation for afforestation and reforestation options, both within biomes/ecozones and across them. Their results suggest that while there is large potential for afforestation and reforestation, the carbon uptake potential in land-based climate change mitigation efforts is highly dependent on the assumptions related to climate drivers, land use and land management, and soil carbon responses to land-use change. Less analysis has been conducted on bioenergy crop yields, however, bioenergy crop yields are also likely to be highly variable, suggesting that bioenergy supply could exceed or fall short of expectations in a given region, depending on site conditions.

The effects of climate change on ecosystems, including changes in crop yields, shifts in terrestrial ecosystem productivity, vegetation migration, wildfires, and other disturbances also will affect the potential for AFOLU mitigation. Climate is expected to reduce crop yields, increase crop and livestock prices, and increase pressure on undisturbed forest land for food production creating new barriers and increasing costs for implementation of many nature-based mitigation techniques ( ''medium confidence'' ) (IPCC AR6 WGII Chapter 5).

The observed increase in the terrestrial sink over the past half century can be linked to changes in the global environment, such as increased atmospheric CO 2 concentrations, N deposition, or changes in climate ( [[#Ballantyne--2012|Ballantyne et al. 2012]] ), though not always proven from ground-based information (Vandersleen et al. 2015). While the terrestrial sink relies on regrowth in secondary forests ( [[#Houghton--2017|Houghton and Nassikas 2017]] ), there is emerging evidence that the sink will slow in the Northern Hemisphere as forests age ( [[#Nabuurs--2013|Nabuurs et al. 2013]] ), although saturation may take decades ( [[#Zhu--2018|Zhu et al. 2018]] ). Forest management through replanting, variety selection, fertilisation, and other management techniques, has increased the terrestrial carbon sink over the last century ( [[#Mendelsohn--2019|Mendelsohn and Sohngen 2019]] ). Saturation of the sink in situ may not occur when, for example, substitution effects of timber usage are also considered.

Increasing concentrations of CO 2 are expected to increase carbon stocks globally, with the strongest effects in the tropics ( [[#Schimel--2015|Schimel et al. 2015]] ; [[#Kim--2017a|Kim et al. 2017a]] ) (IPCC AR6 WGII Chapter 5) and economic models suggest that future sink potential may be robust to the impacts of climate change ( [[#Tian--2018|Tian et al. 2018]] ). However, it is uncertain if this large terrestrial carbon sink will continue in the future ( [[#Aragão--2018|Aragão et al. 2018]] ), as it is increasingly recognised that gains due to CO 2 fertilisation are constrained by climate and increasing disturbances ( [[#Schurgers--2018|Schurgers et al. 2018]] ; [[#Duffy--2021|Duffy et al. 2021]] ) (IPCC AR6 WGII Chapter 5). Further, negative synergies between local impacts like deforestation and forest fires may interact with global drivers like climate change and lead to tipping points ( [[#Lovejoy--2018|Lovejoy and Nobre 2018]] ). Factors that reduce permanence or slow forest growth will drive up costs of forest mitigation measures, suggesting that climate change presents a formidable challenge to implementation of nature-based solutions beyond 2030 ( ''hi'' ''gh confidence'' ).

In addition to climate change, [[#Dooley--2018|Dooley and Kartha (2018)]] also note that technological and social factors could ultimately limit the feasibility of agricultural and forestry mitigation options, especially when deployed at large scale. Concern is greatest with widespread use of bioenergy crops, which could lead to forest losses ( [[#Harper--2018|Harper et al. 2018]] ). Deployment of BECCS and forest-based mitigation can be complementary ( [[#Favero--2017|Favero et al. 2017]] ; [[#Baker--2019|Baker et al. 2019]] ), but inefficient policy approaches could lead to net carbon emissions if BECCS replaces high-carbon content ecosystems with crops.

'''Adaptation benefits and biodiversity conservation.''' Biodiversity may improve resilience to climate change impacts as more-diverse systems could be more resilient to climate change impacts, thereby maintaining ecosystem function and preserving biodiversity ( [[#Hisano--2018|Hisano et al. 2018]] ). However, losses in ecosystem functions due species shifts or reductions in diversity may impair the positive effects of biodiversity on ecosystems. Forest management strategies based on biodiversity and ecosystems functioning interactions can augment the effectiveness of forests in reducing climate change impacts on ecosystem functioning ( ''high confidence'' ). In spite of the many synergies between climate policy instruments and biodiversity conservation, however, current policies often fall short of realising this potential ( [[#Essl--2018|Essl et al. 2018]] ).

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==== 7.6.4.4 Technological Barriers and Opportunities ====

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'''Monitoring, reporting, and verification.''' Development of satellite technologies to assess potential deforestation has grown in recent years with the release of 30 m data by [[#Hansen--2013|Hansen et al. (2013)]] , however, this data only captures tree cover loss, and increasing accuracy over time may limit its use for trend analysis ( [[#Ceccherini--2020|Ceccherini et al. 2020]] ; [[#Palahí--2021|Palahí et al. 2021]] ). Datasets on forest losses are less well developed for reforestation and afforestation. As [[#Mitchell--2017|Mitchell et al. (2017)]] point out, there has been significant improvement in the ability to measure changes in tree and carbon density on sites using satellite data, but these techniques are still evolving and improving and they are not yet available for widespread use.

Ground-based forest inventory measurements have been developed in many countries, most prominently in the Northern Hemisphere, but more and more countries are starting to develop and collect national forest inventories. Training and capacity building is going on in many developing countries under UNREDD and FAO programmes. Additional efforts to harmonise data collection methods and to make forest inventory data available to the scientific community would improve confidence in forest statistics, and changes in forest statistics over time. To some extent the Global Forest Biodiversity Initiative fills in this data gap ( [https://gfbi.udl.cat/ https://g fbi.udl.cat/] ).

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