Editing IPCC:AR6/WGII/Chapter-9 (section)

=== 9.5.10 African Marine Heatwaves ===

<div id="h2-21-siblings" class="h2-siblings"></div>

Marine heatwaves are periods of extreme warm sea surface temperature that persist for days to months and can extend up to thousands of kilometres ( [[#Hobday--2016|Hobday et al., 2016]] ; [[#Scannell--2016|Scannell et al., 2016]] ), negatively impacting marine ecosystems ( [[#9.6.1.4|Section 9.6.1.4]] ).

The number of marine heatwaves doubled in mediterranean north Africa and along the Somalian and southern African coastlines from 1982–2016 ( [[#Frölicher--2018|Frölicher et al., 2018]] ; [[#Oliver--2018|Oliver et al., 2018]] ; [[#Laufkötter--2020|Laufkötter et al., 2020]] ), ''very likely'' as a result of human-caused climate change ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). Marine heatwave intensity has increased along the southern African coastline ( [[#Oliver--2018|Oliver et al., 2018]] ). In the ecologically sensitive region west of southern Madagascar, the longest and most intense marine heatwave in the past 35 years was recorded during the austral summer of 2017 in the region, it lasted 48 days and reached a maximum intensity of 3.44°C above the 35-year average ( [[#Mawren--2021|Mawren et al., 2021]] ). Satellite-derived measurements of coastal marine heatwaves may under-report their intensity as measured against coastal ''in situ'' measurements ( [[#Schlegel--2017|Schlegel et al., 2017]] ).

Sea surface temperatures around Africa are projected to increase by 0.5°C–1.3°C for 1.5°C global warming and increase by 1.3°C–2.0°C for 3°C global warming (Figure 9.16 f). Globally, 87% of observed marine heatwaves have been attributed to human-caused global warming, and at 2°C of global warming, nearly all marine heatwaves would be attributable to heating of the climate caused by human activities ( [[#Frölicher--2018|Frölicher et al., 2018]] ; [[#Laufkötter--2020|Laufkötter et al., 2020]] ). Increases in frequency, intensity, spatial extent and duration of marine heatwaves are projected for all coastal zones of Africa. At 1°C and 3.5°C of global warming, the probability of marine heatwave days is between 4–15 times and 30–60 times higher compared to the pre-industrial (1861–1880) 99th percentile probability, with highest increases over equatorial and sub-tropical coastal regions (Figure 9.16; [[#Frölicher--2018|Frölicher et al., 2018]] ). These events are expected to overwhelm the ability of marine organisms and ecosystems to adapt to these changes ( [[#9.6.1|Section 9.6.1]] ; [[#Frölicher--2018|Frölicher et al., 2018]] ). Reducing emissions and limiting warming to lower levels reduces risk to these systems ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ).

<div id="box-9.2" class="h2-container box-container"></div>

'''Box 9.2 | Indigenous knowledge and local knowledge'''
<div id="h2-51-siblings" class="h2-siblings"></div>

This box aims to map the diversity of Indigenous Knowledge and local knowledge systems in Africa and highlights the potential of this knowledge to enable sustainability and effective climate adaptation. This box builds on the framing of the IPCC system for which ‘indigenous knowledge (IK) refers to the understandings, skills and philosophies developed by societies with long histories of interaction with their natural surroundings’ ( [[#IPCC--2019b|IPCC, 2019b]] ), while ‘local knowledge (LK) refers to the understandings and skills developed by individuals and populations, specific to the place where they live’ (Cross-Chapter Box INDIG in Chapter 18; [[#IPCC--2019b|IPCC, 2019b]] ).

Early warning systems and indicators of climate variability

In most African Indigenous agrarian systems, local communities integrate IK to anticipate or respond to climate variability ( [[#Mafongoya--2017|Mafongoya et al., 2017]] ). This holds potential for a more holistic response to climate change, as Indigenous Knowledge and local knowledge (IKLK) approaches seek solutions that increase resilience to a wide range of shocks and community stresses ( [[#IPCC--2019b|IPCC, 2019b]] ). In Africa, IKLK are exceptionally rich in ecosystem-specific knowledge, with the potential to enhance the management of natural hazards and climate variability ( ''high confidence'' ), but there is uncertainty about IKLK for adaptation under future climate conditions.

Common indicators for the quality of the rain season for local communities in Africa include flower and fruit production of local trees ( [[#Nkomwa--2014|Nkomwa et al., 2014]] ; [[#Jiri--2015|Jiri et al., 2015]] ; [[#Kagunyu--2016|Kagunyu et al., 2016]] ), insect, bird and animal behaviour and occurrence ( [[#Jiri--2016|Jiri et al., 2016]] ; [[#Mwaniki--2017|Mwaniki and Stevenson, 2017]] ; [[#Ebhuoma--2020|Ebhuoma, 2020]] ) and dry season temperatures ( [[#Kolawole--2016|Kolawole et al., 2016]] ; [[#Okonya--2017|Okonya et al., 2017]] ). Fulani herders in west Africa believe that when ‘nests hang high on trees, then rains will be heavy; when nests hang low, rains will be scarce’ ( [[#Roncoli--2002|Roncoli et al., 2002]] ). In South Africa, LK on weather forecasting is based on the hatching of insects, locust swarm movements and the arrival of migratory birds, which has enabled farmers to make adjustments to cropping practices ( [[#Muyambo--2017|Muyambo et al., 2017]] ; [[#Tume--2019|Tume et al., 2019]] ). Most of these IK indicators apply to specific communities, and are used for short-term forecasting (e.g., event-specific predictions, such as a violent storm, and onset rain predictions) ( [[#Zuma-Netshiukhwi--2013|Zuma-Netshiukhwi et al., 2013]] ; [[#Mutula--2014|Mutula et al., 2014]] ). There is evidence of communities that rely heavily on IKLK indicators to forecast seasonal variability across the continent ( [[#Kagunyu--2016|Kagunyu et al., 2016]] ; [[#Mwaniki--2017|Mwaniki and Stevenson, 2017]] ; [[#Tume--2019|Tume et al., 2019]] ). However, their accuracy is debatable, due to age-old knowledge losing accuracy because of recent changes in weather conditions ( [[#Shaffer--2014|Shaffer, 2014]] ; [[#Adjei--2018|Adjei and Kyerematen, 2018]] ). There are also some limitations in the transferability of IK across geographical scales, as its understanding is framed by traditional beliefs and cultural practices, and historical and social conditions of each community, which vary significantly across communities. This has direct implications for the adoption of IKLK in national policy and planned adaptation by governments. However, in some parts of Africa, evidence of the integration of IKLK and scientific-based weather forecasting is increasing ( [[#Jiri--2016|Jiri et al., 2016]] ; [[#Mapfumo--2017|Mapfumo et al., 2017]] ; [[#Williams--2020|Williams et al., 2020]] ).

Indigenous Knowledge and Local Knowledge and climate adaptation

Communities across Africa have long histories of using IKLK to cope with climate variability, reduce vulnerability and improve the capacity to cope with climate variability ( [[#Iloka%20Nnamdi--2016|Iloka Nnamdi, 2016]] ; [[#Mapfumo--2017|Mapfumo et al., 2017]] ). The adaptation is mostly incremental, such as customary rainwater harvesting practices and planting ahead of rains ( [[#Ajibade--2017|Ajibade and Eche, 2017]] ; [[#Makate--2019|Makate, 2019]] ), which are used to address the late-onset rains and rainfall variability. Although IKLK adaptation practices implemented by African communities are incremental, such practices record higher evidence of climate risk reduction compared to practices influenced by other knowledge types ( [[#Williams--2020|Williams et al., 2020]] ). African communities have used IKLK to cope, adapt to and manage climate hazards, mainly floods, wildfires, rainfall variability and droughts (see Box Table 9.2.1; [[#IPCC--2018b|IPCC, 2018b]] ; [[#IPCC--2019b|IPCC, 2019b]] ).

'''Table Box 9.2.1 |''' Selected studies where Indigenous knowledge and local knowledge have been used to cope with climate variability and climate change impacts in Africa.

{| class="wikitable"
|-
! Climate hazard

! Adaptation/coping strategy

! Indigenous group, community, country

! Evidence

|-
| ''Floods''

| Use IK to predict floods (village

elders acted as meteorologists) and use LK to prepare coping mechanisms (social capital); place valuable goods on higher ground, raise the floor level, leave the fields uncultivated when facing flood/drought, Indigenous earthen walls used to protect homesteads from flooding, planting of culturally flood-immunising Indigenous plants

| Coastal communities in Nigeria; Oshiwambo communities in the northern region of Namibia; Matabeleland and Mashonaland provinces in Zimbabwe; communities in Nyamwamba watershed, Uganda; subsistent farmers in Mount Oku and Mbaw, Cameroon; Akobo in South Sudan

| [[#Fabiyi--2013|Fabiyi and Oloukoi (2013)]] ; [[#Hooli--2016|Hooli (2016)]] ; [[#Lunga--2016|Lunga and Musarurwa (2016)]] ; Bwambale et al. (2018); Tume et al. (2019)

|-
| ''Wildfires''

| Early burning to prevent the intensity of the late-season fires

| Smallholders in Mutoko, Zimbabwe; Khwe and

Mbukushu communities in Namibia

| [[#Mugambiwa--2018|Mugambiwa (2018)]] ; Humphrey et al. (2021)

|-
| ''Rainfall variability''

| Change crop type (from maize to traditional millet and sorghum); no weeding; forecasting, rainwater harvesting; women perform rainmaking rituals, seed dressing and crop maintenance as adaptation measures; mulching

| Communities in Accra, Ghana; small-scale farmers in Ngamiland in Botswana; Malawi; Zimbabwe; women in Dikgale, South Africa, agro-pastoral smallholders in Ntungamo, Kamuli and Sembabule in Uganda

| Codjoe et al. (2014); [[#Nkomwa--2014|Nkomwa et al. (2014)]] ; [[#Lunga--2016|Lunga and Musarurwa (2016)]] ; [[#Rankoana--2016b|Rankoana (2016b)]] ; [[#Mugambiwa--2018|Mugambiwa (2018)]] ; [[#Mfitumukiza--2020|Mfitumukiza et al. (2020)]] ; Mogomotsi et al. (2020)

|-
| ''Droughts''

| Traditional drying of food for preservation (to consume during short-term droughts); harvesting wild fruits and vegetables; herd splitting by pastorals

| Communities in Accra, Ghana; Malawi; South Africa, Uganda; smallholder farmers in Mutoko, Zimbabwe; agro-pastoralists in Makueni, Kenya; pastoralists in South Omo, Ethiopia

| [[#Egeru--2012|Egeru (2012)]] ; [[#Gebresenbet--2012|Gebresenbet and Kefale (2012)]] ; Codjoe et al. (2014); [[#Kamwendo--2014|Kamwendo and Kamwendo (2014)]] ; [[#Okoye--2017|Okoye and Oni (2017)]] ; [[#Mugambiwa--2018|Mugambiwa (2018)]]

|-
| ''Drought-related water scarcity''

| Traditional rainwater harvesting to supplement both irrigation and domestic water; Indigenous water bottle technology for irrigation

| Smallholder farmers in Beaufort, South Africa

| [[#Ncube--2018|Ncube (2018)]]

|}

IKLK and adaptation/coping strategies in Table Box 9.2.1 are supportive measures that communities cannot solely rely upon, but which can be used to complement other adaptation options to increase community resilience.

<div id="_idContainer045" class="Box_Header-continued"></div>

Box 9.2

African Indigenous language and climate change adaptation

The diversity of African languages is crucial for climate adaptation. Africa has over 30% of the world’s Indigenous languages ( [[#Seti--2016|Seti et al., 2016]] ), which are exceptionally rich in ecosystem-specific knowledge on biodiversity, soil systems and water ( [[#Oyero--2007|Oyero, 2007]] ; [[#Mugambiwa--2018|Mugambiwa, 2018]] ). Taking into consideration the low level of literacy in Africa, especially among women and girls, Indigenous languages hold great potential for more effective climate change communication and services that enable climate adaptation ( [[#Brooks--2005|Brooks et al., 2005]] ; [[#Ologeh--2018|Ologeh et al., 2018]] ; [[#IPCC--2019b|IPCC, 2019b]] ). African traditional beliefs and cultural practices place great value on the natural environment, especially land as the dwelling place of the ancestors and source of livelihoods ( [[#Tarusarira--2017|Tarusarira, 2017]] ; see [[#9.12|Section 9.12]] ).

Limitations of African Indigenous Knowledge and Local Knowledge in climate adaptation

Studies on IKLK and climate change adaptation conducted in various African countries and across ecosystems indicate that Indigenous environmental knowledge is negatively affected by several factors. Local farmers who depend on this knowledge system for their livelihoods hold the view that African governments do not support and promote it in policy development. Most government agricultural extension workers still consider IK to be unscientific and unreliable ( [[#Seaman--2014|Seaman et al., 2014]] ; [[#Mafongoya--2017|Mafongoya et al., 2017]] ). At the national level, there is a lack of recognition and inclusion of IKLK in adaptation planning by African governments, partly because most of the IK and LK in African local communities remains undocumented, but also because IKLK are inadequately captured in the literature ( [[#Ford--2016|Ford et al., 2016]] ; [[#IPCC--2019b|IPCC, 2019b]] ). This knowledge is predominantly preserved in the memories of the elderly and is handed down orally or by demonstration from generation to generation. It gradually disappears due to memory gaps, and when those holding the knowledge die or refuse to pass it to another generation, the knowledge becomes extinct ( [[#Rankoana--2016a|Rankoana, 2016a]] ). The way in which IK is transmitted, accessed and shared in most African societies is not smooth ( [[#IIED--2015|IIED, 2015]] ). IK is also threatened by urbanisation, which attracts rural migrants to urban areas where IKLK use may be more limited ( [[#Fernández-Llamazares--2015|Fernández-Llamazares et al., 2015]] ). Further, most African societies that use IK were once colonised, whereby the African Indigenous ways of knowing were devalued and marginalised ( [[#Bolden--2018|Bolden et al., 2018]] ). There are concerns about the effectiveness of both IK indicators and related adaptation responses by communities in predicting and adapting to weather events under future climate conditions ( [[#Speranza--2009|Speranza et al., 2009]] ; [[#Shaffer--2014|Shaffer, 2014]] ; [[#Hooli--2016|Hooli, 2016]] ).

[[File:e4a0e6fda6a2e04cab531a882ad51537 IPCC_AR6_WGII_Figure_9_Box_9_2_1.png]]

'''Figure Box 9.2.1 |''' '''Indigenous earth walls (''' '''hayit''' ''') built by Indigenous people in Akobo, Jonglei Region, South Sudan, to protect their houses and infrastructure from the worst flood in 25 years that occurred in 2019.''' The wall is 1–2 m high. Photo credit: Laurent-Charles Tremblay-Levesque.

<div id="_idContainer046" class="Box_Header-continued"></div>

Box 9.2

<div id="9.6" class="h1-container"></div>

<span id="ecosystems"></span>