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

=== 5.4.4 Adaptation Options ===

<div id="h2-11-siblings" class="h2-siblings"></div>

Adaptation strategies in crop production range from field and farm-level technical options such as crop management and cultivar/crop options to livelihood diversification and income protection such as index-based insurance. This section assesses crop management options for different crop types. Feasibility of adaptation options in various systems is addressed in [[#5.1|Section 5.1.4]] .

<div id="5.4.4.1" class="h3-container"></div>

<span id="adaptation-options-for-major-crops"></span>
==== 5.4.4.1 Adaptation options for major crops ====

<div id="h3-12-siblings" class="h3-siblings"></div>

Crop management practices are the most commonly studied adaptation measures ( [[#Shaffril--2018|Shaffril et al., 2018]] ; [[#Hansen--2019a|Hansen et al., 2019a]] ; [[#Muchuru--2019|Muchuru and Nhamo, 2019]] ), but quantitative assessments are mostly limited to existing agronomic options such as changes in planting schedules, cultivars and irrigation ( [[#Beveridge--2018a|Beveridge et al., 2018a]] ; [[#Aggarwal--2019|Aggarwal et al., 2019]] ). This section draws on the global data set used in [[#5.4.3.2|Section 5.4.3.2]] ( [[#Hasegawa--2021b|Hasegawa et al., 2021b]] ) to estimate adaptation potential, defined as the difference in simulated yields with and without adaptations. A caveat to the analysis is that the data set includes management options if the literature treats them as adaptation. They include intensification measures such as fertilizer and water management, not allowing for physical and economic feasibility.

The overall adaptation potential of existing farm management practices to reduce yield losses averaged 8% in mid-century and 11% in end-century (Figure 5.9), which is insufficient to offset the negative impacts from climate change, particularly in currently warmer regions ( [[#5.4.3.2|Section 5.4.3.2]] ). Emission scenarios, crop species, regions and adaptation options do not show discernible differences. Combinations of two or more options do not necessarily have greater adaptation potential than a single option, though a fair comparison is difficult in the data set from independent studies. One regional study in West Africa found that currently promising management would no longer be effective under future climate, suggesting the need to evaluate effectiveness under projected climate change.

<div id="_idContainer029" class="Figure"></div>

[[File:30aa91bdc5e38afd5b5a4d74aa701431 IPCC_AR6_WGII_Figure_5_009.png]]

'''Figure 5.9 |''' '''Adaptation potential, defined as the difference between yield impacts with and without adaptation in projected impacts (Hasegawa et al''' '''.''' ''', 2021b).''' '''(a)''' Projections under three RCP scenarios by regions and '''(b)''' by options at mid-century (MC, 2040–2069) and end-century (EC, 2070–2100). ''n'' is the number of simulations. See Figure 5.6 for legends.

A global-scale meta-analysis estimated a 3–7% yield loss per degree Celsius increase in temperature ( [[#Zhao--2017|Zhao et al., 2017]] ). Two global-scale studies using multiple global gridded crop models found that growing-season adaptation through cultivar changes offsets global production losses up to 2°C of temperature increase ( [[#Minoli--2019|Minoli et al., 2019]] ; [[#Zabel--2021|Zabel et al., 2021]] ). While these studies do not account for CO 2 fertilisation effects, another global-scale study with the CO 2 fertilisation effects ( [[#Iizumi--2020|Iizumi et al., 2020]] ) showed that residual damage (climate change impacts after adaptation) would start to increase almost exponentially from 2040 towards the end of the century under RCP8.5. The cost required for adaptation and due to residual damage is projected to rise from USD 63 billion at 1.5°C to USD 80 billion at 2°C and to USD 128 billion at 3°C ( [[#Iizumi--2020|Iizumi et al., 2020]] ). All these global studies project that risks and damages are greater in tropical and arid regions, where crops are exposed to heat and drought stresses more often than in temperate regions ( [[#Sun--2019|Sun et al., 2019]] ; [[#Kummu--2021|Kummu et al., 2021]] ; SM5.4). There are still large uncertainties in the crop model projections ( [[#Müller--2021a|Müller et al., 2021a]] ), but these multiple lines of evidence suggest that warming beyond +2°C (projected to be reached by mid-century under high-emission scenarios) will substantially increase the cost of adaptation and the residual damage to major crops ( ''high confidence'' ). The residual damage will prevail much sooner in currently warmer regions, where the effect of even a modest temperature increase is greater ( [[#5.4.3.2|Section 5.4.3.2]] ).

Most crop modelling studies on adaptation are still limited to a handful of options for each crop type ( [[#Beveridge--2018a|Beveridge et al., 2018a]] ). A range of other options are possible not just to reduce yield losses but to diversify risks to livelihoods, which are partially assessed in Sections 5.4.4.4 and 5.14.1. Current modelling approaches are not suited for the assessment of multiple dimensions of adaptation options. New studies are emerging that evaluate multiple options for productivity, sustainability and GHG emission ( [[#Xin--2019|Xin and Tao, 2019]] ; [[#Smith--2020b|Smith et al., 2020b]] ), but local- and household-scale assessment, taking account of future climatic variability, needs to be enhanced ( [[#Beveridge--2018a|Beveridge et al., 2018a]] ).

<div id="5.4.4.2" class="h3-container"></div>

<span id="adaptation-options-for-other-crops"></span>
==== 5.4.4.2 Adaptation options for other crops ====

<div id="h3-13-siblings" class="h3-siblings"></div>

Across this diverse group of cropping systems, distinct adaptation options and adaptation limits have emerged (Figure 5.10; [[#Acevedo--2020|Acevedo et al., 2020]] ; [[#Berrang-Ford--2021b|Berrang-Ford et al., 2021b]] ). Some crop types have already seen widescale implementation of climate adaptation (e.g., grapevines), while others show little evidence of preparation for climate change (e.g., leafy salad crops). Many adaptation responses are shared with the major crops, but prominent options such as plant breeding are underutilised and there is a lack of evidence for assessing adaptation for many crops ( [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Gunathilaka--2018|Gunathilaka et al., 2018]] ; [[#Manners--2018|Manners and van Etten, 2018]] ). Figure 5.10 assesses several adaptation options based on the perceived importance of each in the literature. Fruit and vegetable crops tend to be more reliant on ecosystem services in the form of pollination, biocontrol and other resources (water, nutrients, microbes, etc.), and ecosystem-based adaptation options are prominent. The range of crops means that there is great potential for crop switching, but cultural and economic barriers will make such options difficult to implement, with barriers to entry for production and marketing ( [[#Waha--2013|Waha et al., 2013]] ; [[#Magrini--2016|Magrini et al., 2016]] ; [[#Kongsager--2017|Kongsager, 2017]] ; [[#Rhiney--2018|Rhiney et al., 2018]] ). Perennial crops are exposed to a wide range of climate factors throughout the year and have significant barriers to implementing some of the common adaptation options, such as relocation or replacing tree species/cultivar; agronomic interventions on-farm are well used in high-value tree crops and provide some climate resilience, but longer-term options will be needed ( [[#Glenn--2013|Glenn et al., 2013]] ; [[#Mosedale--2016|Mosedale et al., 2016]] ; [[#Gunathilaka--2018|Gunathilaka et al., 2018]] ; [[#Sugiura--2019|Sugiura, 2019]] ).

<div id="_idContainer031" class="Figure"></div>

[[File:567738060f3c2f67f853d06bbdac5c91 IPCC_AR6_WGII_Figure_5_010.png]]

'''Figure 5.10 |''' '''Synthesis of literature on the implementation of on-farm adaptation options across different cropping systems.''' Adaptation options that have been implemented by growers are considered ‘tested’, while those that have not are considered ‘untested’. Untested options are those that appear in studies as suggestions by stakeholder or experts but were not implemented within the study. The assessment draws on &gt;200 articles published since AR5. The confidence is based on the evidence given in individual articles and on the number of articles. See SM5.2 for details.

Many fruit and vegetable crops are water demanding, and adaptation responses relating to water management and access to irrigation water are crucial. Rainwater storage and deficit irrigation techniques are frequently mentioned as adaptation options and can minimise the burden on off-farm water supplies ( [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Acevedo--2020|Acevedo et al., 2020]] ).

<div id="5.4.4.3" class="h3-container"></div>

<span id="cultivar-improvements"></span>
==== 5.4.4.3 Cultivar improvements ====

<div id="h3-14-siblings" class="h3-siblings"></div>

As stated in AR5, cultivar improvements are one effective countermeasure against climate change ( [[#Porter--2014|Porter et al., 2014]] ; [[#Challinor--2016|Challinor et al., 2016]] ; [[#Atlin--2017|Atlin et al., 2017]] ). Plant breeding biotechnology for climate change adaptation draws upon modern biotechnology and conventional breeding, with the latter often assisted by genomics and molecular markers. Plant breeding biotechnology will contribute to adaptation for large-scale producers ( ''high confidence'' ). However, in addition to inconsistencies in meeting farmer expectations, a variety of socioeconomic and political variables strongly influence, and limit, uptake of climate-resilient crops ( [[#Acevedo--2020|Acevedo et al., 2020]] ; [[#Rhoné--2020|Rhoné et al., 2020]] ).

Genome sequencing significantly increases the rate and accuracy for identifying genes of agronomic traits that are relevant to climate change, including adaptation to stress from pests and disease, temperature and water extremes ( ''high confidence'' ) ( [[#Brozynska--2016|Brozynska et al., 2016]] ; [[#Scheben--2016|Scheben et al., 2016]] ; [[#Voss-Fels--2016|Voss-Fels and Snowdon, 2016]] ). Access to this information where it is needed and in practical timeframes, as well as the expertise to use it, will limit the sharing of benefits by the most vulnerable groups and countries ( ''high agreement'' , ''limited evidence'' ) ( [[#Heinemann--2018|Heinemann et al., 2018]] ).

Genetic improvements for climate change adaptation using modern biotechnology have not reliably translated into the field ( [[#Hu--2014|Hu and Xiong, 2014]] ; [[#Nuccio--2018|Nuccio et al., 2018]] ; [[#Napier--2019|Napier et al., 2019]] ), but good progress has been made by conventional breeding. Desirable traits that adapt plants to environmental stress are inherited as a complex of genes, each of which makes a small contribution to the trait ( [[#Negin--2017|Negin and Moshelion, 2017]] ). Adaptation by conventional breeding requires making rapid incremental changes in the best germplasm to keep pace with the environment ( [[#Millet--2016|Millet et al., 2016]] ; [[#Atlin--2017|Atlin et al., 2017]] ; [[#Cobb--2019|Cobb et al., 2019]] ). Further improvements would be difficult without ''in situ'' and ''ex situ'' conservation of plant genetic resources to maintain critical germplasm for breeding ( [[#Dempewolf--2014|Dempewolf et al., 2014]] ; [[#Castañeda-Álvarez--2016|Castañeda-Álvarez et al., 2016]] ).

Despite the advances in sequencing, phenotyping remains a significant bottleneck ( [[#Ghanem--2015|Ghanem et al., 2015]] ; [[#Negin--2017|Negin and Moshelion, 2017]] ; [[#Araus--2018|Araus and Kefauver, 2018]] ); the emergence of high-throughput phenotyping platforms may reduce this bottleneck in future. Emerging modern biotechnology such as gene/genome editing may in the future increase the ability to better translate genetic improvements into the field ''(medium agreement'' , ''limited evidence)'' ( [[#Puchta--2017|Puchta, 2017]] ; [[#Yamamoto--2018|Yamamoto et al., 2018]] ; [[#Friedrichs--2019|Friedrichs et al., 2019]] ; [[#Kawall--2019|Kawall, 2019]] ; [[#Zhang--2019b|Zhang et al., 2019b]] ).

Other breeding approaches assisted by genomics have been making steady gains in introducing traits that adapt crops to climate change ( ''high confidence'' ). DNA sequence information is used to identify markers of desirable traits that can be enriched in breeding programmes, as well as to quantify the genetic variability in species ( [[#Gepts--2014|Gepts, 2014]] ; [[#Brozynska--2016|Brozynska et al., 2016]] ; [[#Voss-Fels--2016|Voss-Fels and Snowdon, 2016]] ). However, breeding for smallholder farmers and the stresses caused by climate change are unlikely to be addressed by the private sector and will require more public investment and adjusting to the local social-ecological system ( [[#Glover--2014|Glover, 2014]] ; [[#Heinemann--2014|Heinemann et al., 2014]] ; [[#Acevedo--2020|Acevedo et al., 2020]] ). Modern biotechnology has not demonstrated the scale neutrality needed to serve smallholder-dominated agroecosystems, due to a combination of the kinds of traits and restrictions that come from the predominant intellectual property rights instruments used in their commercialisation, as well as the focus on a small number of major crop species ( ''medium confidence)'' ( [[#Fischer--2016|Fischer, 2016]] ; [[#Montenegro%20de%20Wit--2020|Montenegro de Wit et al., 2020]] ).

Globally, there is a notable lack of programmes aimed specifically at breeding for climate resilience in fruits and vegetables, although there have been calls to begin this process ( [[#Kole--2015|Kole et al., 2015]] ). Breeding for climate resilience in vegetables has great potential given the range of crop species available. Tolerance to abiotic stress is reasonably advanced in pulses ( [[#Araújo--2015|Araújo et al., 2015]] ; [[#Varshney--2018|Varshney et al., 2018]] ), but examples of translation to commercial cultivars are still limited ( [[#Varshney--2018|Varshney et al., 2018]] ; [[#Varshney--2019|Varshney et al., 2019]] ). The infrastructure for germplasm collection, maintenance, testing and breeding lags behind that of major crops (partly because of the large number of species involved) ( [[#Keatinge--2016|Keatinge et al., 2016]] ; [[#Atlin--2017|Atlin et al., 2017]] ).

Participatory plant breeding (PPB) facilitates interaction between Indigenous and local knowledge systems and scientific research and can be an effective adaptation strategy in generating varieties well adapted to the socio-ecological context and climate hazards ( ''high confidence'' ) (Table 5.5, Westengen and Brysting, 2014; [[#Humphries--2015|Humphries et al., 2015]] ; [[#Anderson--2016|Anderson et al., 2016]] ; [[#Migliorini--2016|Migliorini et al., 2016]] ; [[#Leitão--2019|Leitão et al., 2019]] ; [[#Ceccarelli--2020|Ceccarelli and Grando, 2020]] ; [[#Singh--2020|Singh et al., 2020]] ).

'''Table 5.5 |''' PPB as cultivar improvement adaptation method.

{| class="wikitable"
|-
! '''Region'''

! '''Crop(s) used for breeding'''

! '''Results'''

|-
| West Africa

| Sorghum and pearl millet

| * Released sorghum and millet varieties which were selected for climate variability (e.g., drought), low soil fertility, pest and disease resistance, gendered preferences for processing, and nutrition ( [[#Camacho-Henriquez--2015|Camacho-Henriquez et al., 2015]] ; [[#Weltzien--2019|Weltzien et al., 2019]] ).
* Farmers who adopted these varieties increased yield, income and food security, alongside increased technical knowledge of plant breeding, and increased breeders’ understanding of local farmers’ varietal requirements ( [[#Trouche--2016|Trouche et al., 2016]] ).
* Joint learning with scientists led to increased genetic gain both in terms of operational scale and focused breeding for diverse farmer priorities ( [[#Weltzien--2019|Weltzien et al., 2019]] ).

|-
| South America (Andes)

| Potato

| * PPB with Indigenous Quechua and Aymara farmers resulted in potato varieties with traits from wild relatives, with yield stability, higher yields under low input use and disease resistance under climate change impacts such as increased hail or frost events and upward expansion of pests and diseases ( [[#Camacho-Henriquez--2015|Camacho-Henriquez et al., 2015]] ; [[#Scurrah--2019|Scurrah et al., 2019]] ).

|-
| Asia (southwest China)

| Maize

| * PPB done primarily with women farmers, led to 1500 landraces safeguarded, 12 farmer-preferred varieties released and 30 landraces released, bred for improved yield (15–20% increases), drought resistance, taste, market potential and other priority traits ( [[#Song--2019|Song et al., 2019]] ).
* Studies suggest PPB improved farmer knowledge, income and access to resilient seeds, and strengthened institutions such as women-led farmer cooperatives and Farmers’ Seed Network of China ( [[#Song--2019|Song et al., 2019]] ).

|}

<div id="5.4.4.4" class="h3-container"></div>

<span id="integrated-approach-to-enhance-agroecosystem-resilience"></span>
==== 5.4.4.4 Integrated approach to enhance agroecosystem resilience ====

<div id="h3-15-siblings" class="h3-siblings"></div>

Diversifying agricultural systems is an adaptation strategy that can strengthen resilience to climate change, with socioeconomic and environmental co-benefits, but trade-offs and benefits vary by socio-ecological context ( ''high confidence'' ) (Table 5.6, [[#M’Kaibi--2015|M’Kaibi et al., 2015]] ; [[#Bellon--2016|Bellon et al., 2016]] ; [[#Jones--2017b|Jones, 2017b]] ; [[#Schulte--2017|Schulte et al., 2017]] ; [[#Jarecki--2018|Jarecki et al., 2018]] ; [[#Jones--2018|Jones et al., 2018]] ; [[#Luna-Gonzalez--2018|Luna-Gonzalez and Sorensen, 2018]] ; [[#Sibhatu--2018|Sibhatu and Qaim, 2018]] ; [[#Renard--2019|Renard and Tilman, 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Bozzola--2020|Bozzola and Smale, 2020]] ; [[#Mulwa--2020|Mulwa and Visser, 2020]] ). Crop diversification alongside livestock, fish and other species can be applied at various scales in a range of systems, from rainfed or irrigated to urban and home gardens in multiple spatial and temporal arrangements such as mixed planting, intercrops, crop rotation, diversified management of field margins, agroforestry ( [[#5.10.1.3|Section 5.10.1.3]] ) and integrated crop livestock systems ( [[#5.10.1.1|Section 5.10.1.1]] , [[#Isbell--2017|Isbell et al., 2017]] ; [[#Kremen--2018|Kremen and Merenlender, 2018]] ; [[#Dainese--2019|Dainese et al., 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Hussain--2020|Hussain et al., 2020]] ; [[#Renwick--2020|Renwick et al., 2020]] ; [[#Tamburini--2020|Tamburini et al., 2020]] ; [[#Snapp--2021|Snapp et al., 2021]] ; see [[#5.1|Section 5.1]] 4 and Cross-Chapter Box NATURAL in Chapter 2).

'''Table 5.6 |''' Agroecosystem diversification practices, climate change adaptation mechanisms, trade-offs, co-benefits and constraints to implementation.

{| class="wikitable"
|-
! '''Agroecosystem diversification practice and'''

'''mechanism for climate change adaptation'''

! '''Benefits, trade-offs and constraints to implementation with examples'''

|-
| '''''Crop diversification'''''

* Diversifying revenue streams and food supply (portfolio effect).
* Can impact multiple plant and soil biological and physicochemical properties associated with building SOM, improving soil structure and water conservation.

| * Crop diversification reduces cereal crop sensitivity to '''precipitation variability''' , yield losses and crop insurance payouts under '''drought''' ( ''high confidence'' ) ( [[#McDaniel--2014|McDaniel et al., 2014]] ; [[#Williams--2016|Williams et al., 2016]] ; [[#Iizumi--2019|Iizumi and Wagai, 2019]] ; [[#Renwick--2020|Renwick et al., 2020]] ; [[#Huang--2021|Huang et al., 2021]] ; [[#Kane--2021|Kane et al., 2021]] ).
* For example, a study in Canada comparing diversified rotations and monoculture corn found significant positive yield impacts, yield stability and increased SOC under both RCP4.5 and RCP8.5 by 2100 ( [[#Jarecki--2018|Jarecki et al., 2018]] ).
* Diverse agroecosystems with a range of native, neglected and introduced species, often maintained through Indigenous knowledge and farmer seed systems, offer adaptation opportunities in some regions ( ''medium evidence'' , ''high agreement'' ) ( [[#Bezner%20Kerr--2014|Bezner Kerr, 2014]] ; Westengen and Brysting, 2014; [[#Camacho-Henriquez--2015|Camacho-Henriquez et al., 2015]] ; [[#Ghosh-Jerath--2015|Ghosh-Jerath et al., 2015]] ; [[#Adhikari--2017|Adhikari et al., 2017]] ; Li and Siddique, 2018; [[#Scurrah--2019|Scurrah et al., 2019]] ).
* Diversified landscapes can also enhance CES, by supporting cultural heritage crops, recreational and aesthetic experiences ( ''medium confidence'' ) ( [[#Novikova--2017|Novikova et al., 2017]] ; [[#Martínez-Paz--2019|Martínez-Paz et al., 2019]] ; [[#Alcon--2020|Alcon et al., 2020]] ).
* Diversified cropping systems often require new knowledge, equipment access to inputs and viable markets for new products ( [[#van%20Zonneveld--2020|van Zonneveld et al., 2020]] ). Barriers to diversification, or those which support agroecosystem simplification, include environmental constraints such as elevation or soil type, along with institutional constraints such as low research investment, limited policy support, subsidies that encourage monocrops, poor market access, market instability and limited access to seeds ( [[#Kaushal--2015|Kaushal and Muchomba, 2015]] ; [[#DeLonge--2016|DeLonge et al., 2016]] ; [[#Burchfield--2018|Burchfield and de la Poterie, 2018]] ).

|-
| '''Legume diversification''' can be effective for both mitigation and adaptation, by reducing '''use of nitrogen derived from fossil fuels''' , and meat consumption, and providing ecosystem services through '''nutrient cycling, increasing soil biological activity and erosion control''' ( [[#Snapp--2019|Snapp et al., 2019]] ).

| * Can increase food security and nutrition by increasing cereal productivity and stability in intercropped systems, diversify diets and increase income in crop sales ( ''high agreement, medium evidence'' ) ( [[#Snapp--2019|Snapp et al., 2019]] ; [[#Steward--2019|Steward et al., 2019]] ; [[#Renwick--2020|Renwick et al., 2020]] ), but legume production may be constrained by pest, disease, limited access to genetic material, market access and food preferences ( [[#Anders--2020|Anders et al., 2020]] ).

|-
| '''Organic amendments, no/low tillage or crop residue retention''' may increase diversity in soil biological organisms, which might be important in building resilience to multiple stresses such as '''drought and pest pressure''' ( [[#Furze--2017|Furze et al., 2017]] ; [[#Blundell--2020|Blundell et al., 2020]] ; [[#de%20Vries--2020|de Vries et al., 2020]] ; [[#Stefan--2021|Stefan et al., 2021]] ; [[#Yang--2021|Yang et al., 2021]] ).

| * Higher organic matter does not consistently improve soil hydraulic properties ( [[#Minasny--2018|Minasny and McBratney, 2018]] ; [[#Basche--2019|Basche and DeLonge, 2019]] ).
* Can decrease '''yield variability under dry conditions''' and increase rainfed annual crop yield productivity ( ''high agreement'' ) ( [[#Pittelkow--2014|Pittelkow et al., 2014]] ; [[#Williams--2016|Williams et al., 2016]] ; [[#Williams--2018|Williams et al., 2018]] ; [[#Degani--2019|Degani et al., 2019]] ; [[#Steward--2019|Steward et al., 2019]] ; [[#Bowles--2020|Bowles et al., 2020]] ; [[#Marini--2020|Marini et al., 2020]] ; [[#Sanford--2021|Sanford et al., 2021]] ).

|-
| '''Livestock integration''' . Inclusion of legumes and other forage into crop rotation allows mixed crop and livestock operations to '''mitigate farm-level risk and ecosystem buffering''' .

| * Benefits to productivity and stability of annual crop yields in some contexts (see [[#5.10.3|Section 5.10.3]] , ''high agreement'' , ''medium evidence'' ) ( [[#Stark--2018|Stark et al., 2018]] ; [[#Peterson--2020|Peterson et al., 2020]] ; [[#de%20Albuquerque%20Nunes--2021|de Albuquerque Nunes et al., 2021]] ).

|-
| Traditional and locally adapted '''mixed cropping and agroforestry practices''' which include leguminous trees can improve soil fertility and microclimate ( [[#Sida--2018|Sida et al., 2018]] ; [[#Amadu--2020|Amadu et al., 2020]] ).

| Benefits: resilience to extreme events such as hurricanes can be promoted by supporting ecosystem functions to mitigate impacts and accelerate recovery ( ''high agreement'' , ''medium evidence'' ) ( [[#Altieri--2015|Altieri et al., 2015]] ; [[#Simelton--2015|Simelton et al., 2015]] ; [[#Sida--2018|Sida et al., 2018]] ; [[#Perfecto--2019|Perfecto et al., 2019]] ).

* Can increase food security, livelihoods and productivity, but local context and resource availability must be considered to optimise species arrangement and benefits and can have considerable implementation barriers and costs ( ''high confidence'' ) (see Sections 5.10.3, 5.14 and Cross-Chapter Box NATURAL in Chapter 2). ( [[#Altieri--2015|Altieri et al., 2015]] ; [[#Simelton--2015|Simelton et al., 2015]] ; [[#Sida--2018|Sida et al., 2018]] ; [[#Perfecto--2019|Perfecto et al., 2019]] ).

|}

Diversification improves regulating and supporting ecosystem services such as pest control, soil fertility and health, pollination, nutrient cycling, water regulation and buffering of temperature extremes ( ''high confidence'' ) ( [[#Barral--2015|Barral et al., 2015]] ; [[#Prieto--2015|Prieto et al., 2015]] ; [[#Tiemann--2015|Tiemann et al., 2015]] ; [[#Schulte--2017|Schulte et al., 2017]] ; [[#Beillouin--2019a|Beillouin et al., 2019a]] ; [[#Dainese--2019|Dainese et al., 2019]] ; [[#Kuyah--2019|Kuyah et al., 2019]] ; [[#Tamburini--2020|Tamburini et al., 2020]] ), which can in turn mediate yield stability and reduced risk of crop loss according to socio-ecological contexts and time since adoption ( ''high confidence'' ) ( [[#Prieto--2015|Prieto et al., 2015]] ; [[#Roesch-McNally--2018|Roesch-McNally et al., 2018]] ; [[#Sida--2018|Sida et al., 2018]] ; [[#Williams--2018|Williams et al., 2018]] ; [[#Birthal--2019|Birthal and Hazrana, 2019]] ; [[#Degani--2019|Degani et al., 2019]] ; [[#Amadu--2020|Amadu et al., 2020]] ; [[#Bowles--2020|Bowles et al., 2020]] ; [[#Li--2020|Li et al., 2020]] ; [[#Sanford--2021|Sanford et al., 2021]] ).

Agroecosystem diversification often has variable impacts depending on crop combination, agro-ecological zone and soil types, and rigorous assessments of adaptive gains with traditional and locally diversified systems and potential trade-offs still need to be conducted across socio-ecological contexts. The quantitative upstanding will assist in enhancing multiple benefits of diversification tailored for each condition (Table 5.6). Progress is also needed via breeding and/or agronomy to adapt underutilised as well as major food crops to diversified agroecosystems and optimise management of nutrients, pest and disease pressure and other socio-ecological constraints ( [[#Araújo--2015|Araújo et al., 2015]] ; [[#Foyer--2016|Foyer et al., 2016]] ; [[#Adams--2018|Adams et al., 2018]] ; [[#Pang--2018|Pang et al., 2018]] ).

Managing for diversity and flexibility at multiple scales is central to developing adaptive capacity. Policies to support diversification include shifting subsidies towards diversified systems, public procurement for diverse foods for schools and other public institutions, investment in shorter value chains, lower insurance premiums and payments for ecosystem services that include diversification ( [[#Sorensen--2015|Sorensen et al., 2015]] ; [[#Guerra--2017|Guerra et al., 2017]] ; [[#Nehring--2017|Nehring et al., 2017]] ; [[#Valencia--2019|Valencia et al., 2019]] ). Integrated landscape approaches involving multiple stakeholders ( [[#Reed--2016|Reed et al., 2016]] ) including urban governments can support diversification at a regional scale through public and private sector investment in extension services, regional supply chains, agritourism and other incentives for diversified landscapes ( [[#Milder--2014|Milder et al., 2014]] ; [[#Münke--2015|Münke et al., 2015]] ; [[#Sorensen--2015|Sorensen et al., 2015]] ; [[#Pérez-Marin--2017|Pérez-Marin et al., 2017]] ; [[#Caron--2018|Caron et al., 2018]] ; 5.14.1.5).

<div id="5.5" class="h1-container"></div>

<span id="livestock-based-systems"></span>