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

== CCB10 Economic dimensions of climate change and land ==

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Koko Warner (The United States of America), Aziz Elbehri (Morocco), Marta Guadalupe Rivera Ferre (Spain), Alisher Mirzabaev (Germany/Uzbekistan), Lindsay Stringer (United Kingdom), Anita Wreford (New Zealand)

Sustainable land management (SLM) makes strong social and economic sense. Early action in implementing SLM for climate change adaptation and mitigation provides distinct societal advantages. Understanding the full scope of what is at stake from climate change presents challenges because of inadequate accounting of the degree and scale at which climate change and land interactions impact society, and the importance society places on those impacts (Santos et al. 2016) (Sections 7.2.2, 5.3.1, 5.3.2 and 4.1). The consequences of inaction and delay bring significant risks, including irreversible change and loss in land ecosystem services (ES) – including food security – with potentially substantial economic damage to many countries in many regions of the world ( ''high confidence'' ).

This cross-chapter box brings together the salient economic concepts underpinning the assessments of SLM and mitigation options presented in this report. Four critical concepts are required to help assess the social and economic implications of land-based climate action:

# Value to society
# Damages from climate and land-induced interventions on land ecosystems
# Costs of action and inaction
# Decision-making under uncertainty

'''i. Value to society'''

Healthy functioning land and ecosystems are essential for human health, food and livelihood security. Land derives its value to humans from being a finite resource and vital for life, providing important ES from water recycling, food, feed, fuel, biodiversity and carbon storage and sequestration.

Many of these ES may be difficult to estimate in monetary terms, including when they hold high symbolic value, linked to ancestral history, or traditional and indigenous knowledge systems (Boillat and Berkes 2013 <sup>[[#fn:r1623|1623]]</sup> ). Such incommensurable values of land are core to social cohesion – social norms and institutions, trust that enables all interactions, and sense of community.

'''ii. Damages from climate and land-induced interventions on land ecosystems'''

Values of many land-based ES and their potential loss under land–climate change interaction can be considerable: in 2011, the global value of ES was 125 trillion USD per year and the annual loss due to land-use change was between 4.3 and 20.2 trillion USD per year from 2007 (Costanza et al. 2014 <sup>[[#fn:r1624|1624]]</sup> ; Rockström et al. 2009 <sup>[[#fn:r1625|1625]]</sup> ). The annual costs of land degradation are estimated to be about 231 billion USD per year or about 0.41% of the global GDP of 56.49 trillion USD in 2007 (Nkonya et al. 2016 <sup>[[#fn:r1626|1626]]</sup> ) (Sections 4.4.1 and 4.4.2).

Studies show increasingly negative effects on GDP from damage and loss to land-based values and service as global mean temperatures increase, although the impact varies across regions (Kompas et al. 2018 <sup>[[#fn:r1627|1627]]</sup> ).

'''iii. Costs of action and inaction'''

Evidence suggests that the cost of inaction in mitigation and adaptation, and land use, exceeds the cost of interventions in both individual countries, regions, and worldwide (Nkonya et al. 2016 <sup>[[#fn:r1628|1628]]</sup> ). Continued inaction reduces the future policy option space, dampens economic growth and increases the challenges of mitigation as well as adaptation (Moore and Diaz 2015 <sup>[[#fn:r1629|1629]]</sup> ; Luderer et al. 2013 <sup>[[#fn:r1630|1630]]</sup> ). The cost of reducing emissions is estimated to be considerably less than the costs of the damages at all levels (Kainuma et al. 2013 <sup>[[#fn:r1631|1631]]</sup> ; Moran 2011 <sup>[[#fn:r1632|1632]]</sup> ; Sánchez and Maseda 2016 <sup>[[#fn:r1633|1633]]</sup> ).

The costs of adapting to climate impacts are also projected to be substantial, although evidence is limited (summarised in Chambwera et al. 2014a <sup>[[#fn:r1634|1634]]</sup> ). Estimates range from 9 to 166 billion USD per year at various scales and types of adaptation, from capacity building to specific projects (Fankhauser 2017 <sup>[[#fn:r1635|1635]]</sup> ). There is insufficient literature about the costs of adaptation in the agriculture or land-based sectors (Wreford and Renwick 2012 <sup>[[#fn:r1636|1636]]</sup> ) due to lack of baselines, uncertainty around biological relationships and inherent uncertainty about anticipated avoided damage estimates, but economic appraisal of actions to maintain the functions of the natural environment and land sector generate positive net present values (Adaptation Sub-committee 2013 <sup>[[#fn:r1637|1637]]</sup> ).

Preventing land degradation from occurring is considered more cost-effective in the long term compared to the magnitude of resources required to restore already degraded land (Cowie et al. 2018a <sup>[[#fn:r1638|1638]]</sup> ) (Section 3.6.1). Evidence from drylands shows that each US dollar invested in land restoration provides between 3 and 6 USD in social returns over a 30-year period, using a discount rate between 2.5 and 10% (Nkonya et al. 2016 <sup>[[#fn:r1639|1639]]</sup> ). SLM practices reverse or minimise economic losses of land degradation, estimated at between 6.3 and 10.6 trillion USD annually, (ELD Initiative 2015 <sup>[[#fn:r1640|1640]]</sup> ) more than five times the entire value of agriculture in the market economy (Costanza et al. 2014 <sup>[[#fn:r1641|1641]]</sup> ; Fischer et al. 2017 <sup>[[#fn:r1642|1642]]</sup> ; Sandifer et al. 2015 <sup>[[#fn:r1643|1643]]</sup> ; Dasgupta et al. 2013 <sup>[[#fn:r1644|1644]]</sup> ) (Section 3.7.5).

Across other areas such as food security, disaster mitigation and risk reduction, humanitarian response, and healthy diet (to address malnutrition as well as disease), early action generates economic benefits greater than costs ( ''high evidence, high agreement'' ) (Fankhauser 2017 <sup>[[#fn:r1645|1645]]</sup> ; Wilkinson et al. 2018 <sup>[[#fn:r1646|1646]]</sup> ; Venton 2018 <sup>[[#fn:r1647|1647]]</sup> ; Venton et al. 2012 <sup>[[#fn:r1648|1648]]</sup> ; Clarvis et al. 2015 <sup>[[#fn:r1649|1649]]</sup> ; Nugent et al. 2018 <sup>[[#fn:r1650|1650]]</sup> ; Watts et al. 2018 <sup>[[#fn:r1651|1651]]</sup> ; Bertram et al. 2018 <sup>[[#fn:r1652|1652]]</sup> ) (Sections 6.3 and 6.4).

'''iv. Decision-making under uncertainty'''

Given that significant uncertainty exists regarding the future impacts of climate change, effective decisions must be made under unavoidable uncertainty (Jones et al., 2014 <sup>[[#fn:r1653|1653]]</sup> ).

Approaches that allow for decision-making under uncertainty are continually evolving (Section 7.5). An emerging trend is towards new frameworks that will enable multiple decision-makers with multiple objectives to explore the trade-offs between potentially conflicting preferences to identify strategies that are robust to deep uncertainties (Singh et al. 2015 <sup>[[#fn:r1654|1654]]</sup> ; Driscoll et al. 2016 <sup>[[#fn:r1655|1655]]</sup> ; Araujo Enciso et al. 2016 <sup>[[#fn:r1656|1656]]</sup> ; Herman et al. 2014 <sup>[[#fn:r1657|1657]]</sup> ; Pérez et al. 2016 <sup>[[#fn:r1658|1658]]</sup> ; Girard et al. 2015 <sup>[[#fn:r1659|1659]]</sup> ; Haasnoot et al. 2018 <sup>[[#fn:r1660|1660]]</sup> ; Roelich and Giesekam 2019 <sup>[[#fn:r1661|1661]]</sup> ).

'''Valuation of benefits and damages and costing interventions: Measurement issues'''

Cost appraisal tools for climate adaptation are many and their suitability depends on the context (Section 7.5.2.2). Cost-benefit analysis (CBA) and cost-effectiveness analysis (CEA) are commonly applied, especially for current climate variability situations. However, these tools are not without criticism and their limitations have been observed in the literature (see Rogelj et al. 2018 <sup>[[#fn:r1662|1662]]</sup> ). In general, measuring costs and providing valuations are influenced by four conditions: measurement and valuation; the time dimension; externalities; and aggregate versus marginal costs.

'''Measurement and value issues'''

ES not traded in the market fall outside the formal or market-based valuation and so their value is either not accounted for or underestimated in both private and public decisions (Atkinson et al. 2018 <sup>[[#fn:r1663|1663]]</sup> ). Environmental valuation literature uses a range of techniques to assign monetary values to environmental outcomes where no market exists (Atkinson et al. 2018 <sup>[[#fn:r1664|1664]]</sup> ; Dallimer et al. 2018 <sup>[[#fn:r1665|1665]]</sup> ), but some values remain inestimable. For some indigenous cultures and peoples, land is not considered something that can be sold and bought, so economic valuations are not meaningful even as proxy approaches (Boillat and Berkes 2013 <sup>[[#fn:r1666|1666]]</sup> ; Kumpula et al. 2011 <sup>[[#fn:r1667|1667]]</sup> ; Pert et al. 2015 <sup>[[#fn:r1668|1668]]</sup> ; Xu et al. 2005 <sup>[[#fn:r1669|1669]]</sup> ).

While a rigorous CBA is broader than a purely financial tool and can capture non-market values where they exist, it can prioritise certain values over others (such as profit maximisation for owners, efficiency from the perspective of supply chain processes, and judgements about which parties bear the costs). Careful consideration must be given to whose perspectives are considered when undertaking a CBA and also to the limitations of these methods for policy interventions.

'''Time dimension (short versus long term) and the issue of discount rates'''

Economics uses a mechanism to convert future values to present day values known as discounting, or the pure rate of time preference. Discount rates are increasingly being chosen to reflect concerns about intergenerational equity, and some countries (e.g., the UK and France) apply a declining discount rate for long-term public projects. The choice of discount rate has important implications for policy evaluation (Anthoff, Tol, and Yohe, 2010 <sup>[[#fn:r1670|1670]]</sup> ; Arrow et al., 2014 <sup>[[#fn:r1671|1671]]</sup> ; Baral, Keenan, Sharma, Stork, and Kasel, 2014 <sup>[[#fn:r1672|1672]]</sup> ; Dasgupta et al., 2013 <sup>[[#fn:r1673|1673]]</sup> ; Lontzek, Cai, Judd, and Lenton, 2015 <sup>[[#fn:r1674|1674]]</sup> ; Sorokin et al., 2015 <sup>[[#fn:r1675|1675]]</sup> ; van den Bergh and Botzen, 2014 <sup>[[#fn:r1676|1676]]</sup> ) ( ''high evidence, high agreement'' ). Stern (2007), for example, used a much lower discount rate (giving almost equal weight to future generations) than the mainstream authors (e.g., Nordhaus (1941) <sup>[[#fn:r1677|1677]]</sup> and obtained much higher estimates of the damage of climate change).

'''Positive and negative externalities (consequences and impacts not accounted for in market economy),'''

All land use generates externalities (unaccounted for side effects of an activity). Examples include loss of ES (e.g., reduced pollinators; soil erosion, increased water pollution, nitrification, etc.). Positive externalities include sequestration of carbon dioxide (CO <sub>2</sub> ) and improved soil water filtration from afforestation. Externalities can also be social (e.g., displacement and migration) and economic (e.g., loss of productive land). In the context of climate change and land, the major externality is the agriculture, forestry and other land-use (AFOLU) sourced greenhouse gas (GHG) emissions. Examples of mechanisms to internalise externalities are discussed in 7.5.

'''Aggregate versus marginal costs'''

Costs of climate change are often referred to through the marginal measure of the social cost of carbon (SCC), which evaluate the total net damages of an extra metric tonne of CO <sub>2</sub> emissions due to the associated climate change (Nordhaus 2014 <sup>[[#fn:r1678|1678]]</sup> ). The SCC can be used to determine a carbon price, but SCC depends on discount rate assumptions and may neglect processes, including large losses of biodiversity, political instability, violent conflicts, large-scale migration flows, and the effects of climate change on the development of economies (Stern 2013 <sup>[[#fn:r1679|1679]]</sup> ; Pezzey 2019 <sup>[[#fn:r1680|1680]]</sup> ).

At the sectoral level, marginal abatement cost (MAC) curves are widely used for the assessment of costs related to CO <sub>2</sub> or GHG emissions reduction. MAC measures the cost of reducing one more GHG unit and MAC curves are either expert-based or model- derived and offer a range of approaches and assumptions on discount rates or available abatement technologies (Moran 2011 <sup>[[#fn:r1681|1681]]</sup> ).

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==== 7.3.4.1 Windows of opportunity ====

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Windows of opportunity are important learning moments wherein an event or disturbance in relation to land, climate, and food security triggers responsive social, political, policy change ( ''medium agreement'' ). Policies play an important role in windows of opportunity and are important in relation to managing risks of desertification, soil degradation, food insecurity, and supporting response options for SLM ( ''high agreement'' ) (Kivimaa and Kern 2016 <sup>[[#fn:r337|337]]</sup> ; Gupta et al. 2013b <sup>[[#fn:r338|338]]</sup> ; Cosens et al. 2017 <sup>[[#fn:r339|339]]</sup> ; Darnhofer 2014 <sup>[[#fn:r340|340]]</sup> ; Duru et al. 2015 <sup>[[#fn:r341|341]]</sup> ) (Chapter 6).

A wide range of events or disturbances may initiate windows of opportunity – ranging from climatic events and disasters, recognition of a state of land degradation, an ecological social or political crisis, and a triggered regulatory burden or opportunity. Recognition of a degraded system such as land degradation and desertification (Chapters 3 and 4) and associated ecosystem feedbacks, allows for strategies, response options and policies to address the degraded state (Nyström et al. 2012 <sup>[[#fn:r343|343]]</sup> ). Climate related disasters (flood, droughts, etc.) and crisis may trigger latent local adaptive capacities leading to systemic equitable improvement (McSweeney and Coomes 2011 <sup>[[#fn:r344|344]]</sup> ), or novel and innovative recombining of sources of experience and knowledge, allowing navigation to transformative social ecological transitions (Folke et al. 2010 <sup>[[#fn:r345|345]]</sup> ). The occurrence of a series of punctuated crises such as floods or droughts, qualify as windows of opportunity when they enhance society’s capacity to adapt over the long term (Pahl-Wostl et al. 2013 <sup>[[#fn:r346|346]]</sup> ). A disturbance from an ecological, social, or political crisis may be sufficient to trigger the emergence of new approaches to governance wherein there is a change in the rules of the social world such as informal agreements surrounding human activities or formal rules of public policies (Olsson et al. 2006 <sup>[[#fn:r347|347]]</sup> ; Biggs et al. 2017 <sup>[[#fn:r348|348]]</sup> ) (Section 7.6). A combination of socio-ecological changes may provide windows of opportunity for a socio-technical niche to be adopted on a greater scale, transforming practices towards SLM such as biodiversity-based agriculture (Darnhofer 2014 <sup>[[#fn:r349|349]]</sup> ; Duru et al. 2015 <sup>[[#fn:r350|350]]</sup> ).

Policy may also create windows of opportunity. A disturbance may cause inconvenience, including high costs of compliance with environmental regulations, thereby initiating a change of behaviour (Cosens et al. 2017 <sup>[[#fn:r351|351]]</sup> ). In a similar vein, multiple regulatory requirements existing at the time of a disturbance may result in emergent processes and novel solutions in order to correct for piecemeal regulatory compliance (Cosens et al. 2017 <sup>[[#fn:r352|352]]</sup> ). Lastly, windows of opportunity can be created by a policy mix or portfolio that provides for creative destruction of old social processes and there by encourages new innovative solutions (Kivimaa et al. 2017b <sup>[[#fn:r353|353]]</sup> ) (Section 7.4.8).

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