Editing IPCC:AR6/WGII/Chapter-5 (section)

=== Constraining Adaptation: Previous Agricultural Development Pathways in India ===

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Government policies in colonial and postcolonial India invested in infrastructure, export production and synthetic input use ( [[#Gupta--1998|Gupta, 1998]] ; [[#Davis--2001|Davis, 2001]] ), setting the stage for current development trajectories and closing out other adaptive options. Although such policies increased national food production, they failed to address high levels of malnutrition, worsening regional inequities, degraded natural resources and an agrarian debt crisis ( [[#Singh--2000|Singh, 2000]] ; [[#Gupta--2016|Gupta et al., 2016]] ; [[#Gajjar--2019|Gajjar et al., 2019]] ). Agricultural livelihoods are increasingly considered unviable, with lower adaptive capacity of farmers, high debt levels ( [[#Gupta--2016|Gupta et al., 2016]] ), and Indigenous and local knowledge loss and denigration ( [[#Kumar--2016|Kumar, 2016]] ) alongside lower crop diversification ( [[#Srivastava--2016|Srivastava et al., 2016]] ). Government institutions aimed at infrastructure often lack adaptive capacity needed to address rural livelihoods ( [[#Singh--2017|Singh et al., 2017]] ; [[#Gajjar--2019|Gajjar et al., 2019]] ).

Adaptation options that consider adverse effects for different groups reduce the risk increasing vulnerability, negatively affecting socioeconomic factors to deal with climate impacts, or impeding efforts to implement SDGs ( ''high confidence'' ) ( [[#Juhola--2016|Juhola et al., 2016]] ; [[#Antwi-Agyei--2018|Antwi-Agyei et al., 2018]] ; [[#Paprocki--2018|Paprocki and Huq, 2018]] ; [[#Holsman--2019|Holsman et al., 2019]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Stringer--2020|Stringer et al., 2020]] ). Adaptation methods considering historical roots of current vulnerabilities can identify viable solutions, which are difficult to undertake because of path dependencies ( ''high confidence'' ) ( [[#Ribot--2014|Ribot, 2014]] ; [[#Albizua--2019|Albizua et al., 2019]] ; [[#Gajjar--2019|Gajjar et al., 2019]] ; [[#Paprocki--2019|Paprocki, 2019]] ; [[#Thomas--2020|Thomas, 2020]] ). Planning techniques that model outcomes for different groups from different adaptation options could be put in place to diminish maladaptation risks ( [[#Rodríguez--2019|Rodríguez et al., 2019]] ).

Inclusive planning initiatives such as community-based anticipatory adaptation combined with ‘two-way learning’ that considers future scenarios and different adaptation pathways can prevent maladaptation ( ''high confidence'' ) ( [[#Dovie--2017|Dovie, 2017]] ; [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Neset--2019a|Neset et al., 2019a]] ; [[#Rahman--2019|Rahman and Hickey, 2019]] ; [[#Work--2019|Work et al., 2019]] ; [[#Butler--2020|Butler et al., 2020]] ; [[#Nunn--2020|Nunn et al., 2020]] ; [[#Piggott-McKellar--2020|Piggott-McKellar et al., 2020]] ; [[#Westoby--2020|Westoby et al., 2020]] ; Table 5.20). Promising policy management tools combine temporal scales and mitigation–adaptation interactions and consider political dynamics, socioeconomic impacts and trade-offs for vulnerable groups, long-term support for policy leaders, efforts to establish livelihood ‘niches’ and ongoing participatory evaluation ( [[#Dovie--2017|Dovie, 2017]] ; [[#Holsman--2019|Holsman et al., 2019]] ; [[#Rahman--2019|Rahman and Hickey, 2019]] ; [[#Work--2019|Work et al., 2019]] ; [[#Butler--2020|Butler et al., 2020]] ). A focus on the most disadvantaged groups can help small-scale producers at higher risk to prevent maladaptation ( [[#FAO--2018c|FAO, 2018c]] ). Governance mechanisms have emerged that consider food security, socio-cultural factors, and land and water rights, using participatory, inclusive ‘two-way learning’ methods that involve vulnerable people alongside government ( [[#IPCC--2018|IPCC, 2018]] ; [[#Holsman--2019|Holsman et al., 2019]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Rahman--2019|Rahman and Hickey, 2019]] ; [[#Butler--2020|Butler et al., 2020]] ).

'''Table 5.20 |''' Summary of the emerging literature on potential risks of maladaptation.

{| class="wikitable"
|-
! '''Description of''' '''adaptation''' '''strategy'''

! '''Potential negative impacts'''

! '''Maladaptation typology (1 = rebounding vulnerability, 2 = shifting, 3 = eroding SDGs) and confidence level'''

! '''Regions and''' '''countries''' '''affected'''

! '''Groups affected'''

! '''References'''

|-
| Agricultural intensification to increase productivity, in places with heavy rainfall events or rising pest/disease incidence

| Increases GHG emissions, water pollution, possible insect resistance and costs to farmers; possibly increases inequities.

May constrain adaptation policy options for development pathways due to lock-ins and trade-offs which entrench inequities.

| 1, 2, 3

''Robust evidence, medium agreement''

| USA, Africa, Asia (India, China), Europe

| Farmers, pastoralists/nearby communities who rely on water; small-scale farmers who cannot afford inputs; policymakers.

| Gajjar et al. (2019), [[#Guodaar--2019|Guodaar et al. (2019)]] , [[#Houser--2019|Houser and Stuart (2019)]] , [[#Neset--2019b|Neset et al. (2019b)]] , [[#Quan--2019|Quan et al. (2019)]] , Young and Ismail (2019)

|-
| Livelihood diversification into charcoal production

| Increases GHG emissions and deforestation rates

| 1, 3

''medium''

| Africa (Northern Ghana), South America (Peru)

| Small-scale food producers; Indigenous communities

| [[#Antwi-Agyei--2018|Antwi-Agyei et al. (2018)]] , [[#Zavaleta--2018|Zavaleta et al. (2018)]] , Young and Ismail (2019)

|-
| Irrigation projects or programmes that are either large-scale and/or rely on groundwater

| Reduces long-term potential for hydropower and groundwater availability, can increase salinisation and cost of water.

Can increase cost of farming and debt levels of farmers, squeezing out small-scale producers.

Can reduce water availability for aquaculture.

| 1, 2, 3

''high''

| Central China, India, Mediterranean areas, Europe, USA

| Food producers who rely on irrigation; consumers who rely on hydropower or groundwater; small-scale diversified producers who cannot afford irrigation; aquaculture.

| [[#Doody--2015|Doody et al. (2015)]] , [[#Herbert--2015|Herbert et al. (2015)]] , [[#Barik--2016|Barik et al. (2016)]] , [[#Daliakopoulos--2016|Daliakopoulos et al. (2016)]] [[#Fragaszy--2016|Fragaszy and Closas (2016)]] [[#Dalin--2017|Dalin et al. (2017)]] , [[#Foster--2018|Foster et al. (2018)]] [[#Hanaček--2018|Hanaček and Rodríguez-Labajos (2018)]] , Albizua et al. (2019), [[#Flörke--2019|Flörke et al. (2019)]] Gajjar et al. (2019), Zhang et al.(2019a)

|-
| Investment in improved cultivars or shift to different crops

| May displace local varieties; reduces diversity if too much policy/extension emphasis falls on a few varieties; may increase risk of crop loss from pests, disease or drought if reliant on a few varieties; may increase fertilizer use; may lead to loss of Indigenous or local knowledge.

| 1, 3

''medium''

| South America (Bolivia, Pacific Islands, Asia

| Small-scale food producers; Indigenous communities

| [[#Mcleod--2018|Mcleod et al. (2018)]] , [[#Meldrum--2018|Meldrum et al. (2018)]] , [[#Neset--2019b|Neset et al. (2019b)]] [[#Rahman--2019|Rahman and Hickey (2019)]]

|-
| Migration

| Can increase the workload of people left behind (often women), worsen rural livelihoods and food insecurity; can lead to worsened living conditions, food security and poverty in precarious urban conditions; may increase vulnerability to flooding in urban locations.

May affect mental health by disrupting existing social ties.

| 1, 3

''high''

| Asia, Africa, Central and South America

| Small-scale low-income food producers or rural workers; women

| Bettini et al. (2017), [[#Paprocki--2018|Paprocki (2018)]] , Chen et al. (2019), [[#Jacobson--2019|Jacobson et al. (2019)]] , Michael et al. (2019), Young and Ismail (2019), [[#Singh--2020|Singh and Basu (2020)]] , [[#Torres--2017|Torres and Casey (2017)]]

|-
| Coastal sea walls, embankments, canals, riverbed draining and dikes to reduce flood risk

| Can degrade coastal mangroves, deplete open freshwater fisheries, cause sedimentation of rivers, reduce fish diversity and increase flooding risk for particular vulnerable groups; may divert funds from other more sustainable measures.

| 1, 2, 3

''high''

| Asia, South Pacific Islands, West Africa

| Coastal communities dependent on mangroves and fisheries; low-income rural households with seasonal dependence on inland fisheries

| [[#Dovie--2017|Dovie (2017)]] , [[#Owusu-Daaku--2018|Owusu-Daaku (2018)]] , Freduah et al. (2019), [[#IPCC--2019c|IPCC (2019c)]] , [[#Rahman--2019|Rahman and Hickey (2019)]] , [[#Nunn--2020|Nunn et al. (2020)]] [[#Seddon--2020|Seddon et al. (2020)]] , [[#Thomas--2020|Thomas (2020)]]

|-
| River regulation for hydropower

| May have negative impacts on inland fisheries.

| 2, 3

| Global

| Small-scale inland fisheries and low-income rural households with seasonal dependence on inland fisheries

| [[#FAO--2018c|FAO (2018c)]]

|-
| Government policies to manage coastal fisheries which promote overcapitalisation of fisheries, including index insurance

| Government confiscation of fishing nets to prevent rapid decline of fish population can worsen livelihoods for small-scale fishers; subsidies of pre-mixed fuel to allow fishers to stay out longer due to shifting fish populations may increase total number of fishers and total fish catch; insurance payments may benefit larger-scale fishing fleets and push out small-scale fishers.

| 1, 3

''medium''

| West Africa

| Coastal small-scale fishery communities

| [[#FAO--2018b|FAO (2018b)]] , Freduah et al. (2019), [[#Holsman--2019|Holsman et al. (2019)]] , [[#Sainsbury--2019|Sainsbury et al. (2019)]]

|-
| Consultative stakeholder systems in fisheries or flood management

| May encourage inertia in the system due to a few powerful stakeholders participating in the consultative process.

| 2

''low''

| North America, Asia

| Coastal fisheries

| [[#Holsman--2019|Holsman et al. (2019)]] , [[#Rahman--2019|Rahman and Hickey (2019)]]

|-
| Climate services

| May reinforce existing inequities if climate services are attuned to powerful stakeholders in industry, services are privatised, there are limited ways to get input from vulnerable groups and planning budgets that use climate services are constrained.

| 1, 2, 3

''medium''

| North America

| Coastal fisheries, farming

| [[#Furman--2014|Furman et al. (2014)]] , [[#Webber--2017|Webber (2017)]] , [[#Nost--2019|Nost (2019)]]

|-
| Nature-based solutions mitigation and adaptation strategies such as reforestation or afforestation

| Can displace local communities’ access to land for food production and other ecosystem services, have negative impacts on Indigenous rights, reduce biodiversity and may not reduce GHG as much as conserving natural forests and wetlands or agroecological systems such as agroforestry or other means to increase soil C.

| 2, 3

''medium''

| Africa, Asia, and South America, e.g., Indonesia, Amazon, west-central Africa

| Indigenous communities; small-scale producers and forest-dependent communities

| Lunstrum et al. (2016), [[#Work--2019|Work et al. (2019)]] , [[#Seddon--2020|Seddon et al. (2020)]] , Cross-Working Group Box BIOECONOMY this chapter)

|-
| Social safety nets provide funds which increase consumption of processed, purchased food and erode Indigenous knowledge

| Decline in Indigenous knowledge of and collective approaches to seasonal adaptation strategies in hunting, fishing and food production; shift in dietary patterns to more processed and non-local foods; reduction in farming. Reduced capacity to respond to hazards through dispersed settlement, e.g., hunting, fishing, wild food collection. Increased population density increases deforestation and vulnerability.

| 1, 3

''low''

| South America (Amazonian region of Peru), Africa (South Africa)

| Indigenous communities

| [[#Lemos--2016|Lemos et al. (2016)]] , [[#Zavaleta--2018|Zavaleta et al. (2018)]]

|-
| Community-based adaptation strategies

| Local gender and other social inequities can lead to ‘elite capture’ that reinforces inequity; power dynamics between the funding agency and local participants can make local community involvement tokenistic. There may be inadequate attention to socio-cultural preferences and structural factors which foster maladaptation such as inappropriate crops or animals used.

| 1, 3

''high''

| Pacific Islands, Africa, Asia

| Small-scale food producers; Indigenous communities, other vulnerable groups such as women and low-caste groups

| [[#McNamara--2017|McNamara and Buggy (2017)]] [[#Jamero--2018|Jamero et al. (2018)]] , [[#Singh--2018|Singh (2018)]] [[#Bezner%20Kerr--2019|Bezner Kerr et al. (2019)]] Piggott-McKellar et al. (2020), [[#Westoby--2020|Westoby et al. (2020)]]

|-
| Digital agriculture for increased precision and efficient use of fertilizers, pesticides, water

| Could lead to net job losses, particularly for those with lower levels of education; increased surveillance and employer scrutiny of lower-skilled workers in fields, greenhouses and processing plants and warehouses; separate workers from employees and companies who collect data. Overall increased racial, income inequities and unequal working conditions.

| 2, 3

''low''

| North America, South America, Europe, Asia, parts of Africa

| Farmworkers; small-scale food producers who cannot afford digital technologies; rural communities

| ( [[#Furman--2014|Furman et al. (2014)]] , [[#Rotz--2019|Rotz et al. (2019)]]

|-
| Increased credit access for livelihood diversification

| High interest rates, tight return policies could increase debt loads for low-income households, which could rebound vulnerability. Household may invest in livelihood strategies which are vulnerable to climate change impacts, or which increase GHG.

| 1, 3

''low''

| Asia (Bangladesh)

| Low-income landless people or small-scale producers

| Rahman et al. (2018)

|-
| Aquaculture

| Large-scale coastal aquaculture can increase soil salinisation and reduce land available for other food production and increase migration.

| 2, 3

''low''

| Asia (Bangladesh)

| Small-scale mixed systems including rice production and other rural livelihoods

| [[#Paprocki--2018|Paprocki (2018)]] , [[#Paprocki--2018|Paprocki and Huq (2018)]]

|}

'''Table 5.21 |''' Strategies to avoid maladaptation (adapted from [[#Magnan--2014|Magnan, 2014]] ; [[#Lim-Camacho--2015|Lim-Camacho et al., 2015]] ; [[#Sovacool--2015|Sovacool et al., 2015]] ; [[#FAO--2018b|FAO, 2018b]] ; [[#Paprocki--2018|Paprocki and Huq, 2018]] ; [[#Sainsbury--2019|Sainsbury et al., 2019]] ).

{| class="wikitable"
|-
! '''Type of maladaptation'''

! '''Strategies'''

|-
| Environmental

| # Prevent negative effects on ecosystem services ''in situ'' (e.g., habitat degradation, pollution) that increase exposure to climate hazards.

# Avoid increasing pressure on other socio-ecological systems.

# Ensure ecosystems’ protective role as natural buffer zones is sustained against current and future climate-related hazards, such as storms, floods and sea level rise.

# Provide some duplication and ensure flexibility of adaptation strategies to reduce risk because of uncertainties about climate change impacts and ecosystem response (e.g., agrobiodiversity to reduce pest outbreaks).

|-
| Socio-cultural

| # Consider local social characteristics and cultural values that could affect risks and environmental dynamics.

# Support local skills and knowledge related to climate-related hazards.

# Support capacity-building for new skills needed by local communities.

|-
| Political-economic

| # Consider the political dynamics and power imbalances and create inclusive processes to involve the most vulnerable and disadvantaged groups in decisions.

# Work to reduce socioeconomic inequities, poverty and food insecurity.

# Support livelihood diversification.

# Focus on the impacts of adaptation on the poorest, structurally disadvantaged and vulnerable groups, and take power imbalances into account.

# Work across the full supply chain to consider linkages and possible ripple effects.

|}

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