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

== 9.6 Ecosystems ==

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<span id="observed-impacts-of-climate-change-on-african-biodiversity-and-ecosystem-services"></span>
=== 9.6.1 Observed Impacts of Climate Change on African Biodiversity and Ecosystem Services ===

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<span id="terrestrial-ecosystems"></span>
==== 9.6.1.1 Terrestrial Ecosystems ====

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The overall continental trend is woody plant expansion, particularly in grasslands and savannas, with woody plant cover increasing at a rate of 2.4% per decade (see Figure 9.17; [[#Stevens--2017|Stevens et al., 2017]] ; [[#Axelsson--2018|Axelsson and Hanan, 2018]] ). There is also increased grass cover in arid regions in southwestern Africa ( [[#Masubelele--2014|Masubelele et al., 2014]] ). There is ''high agreement'' that this is attributable to increased CO 2 , warmer and wetter climates, declines in burned area and release from herbivore browsing pressure, but the relative importance of these interacting drivers remains uncertain ( [[#O’Connor--2014|O’Connor et al., 2014]] ; [[#Stevens--2016|Stevens et al., 2016]] ; [[#García%20Criado--2020|García Criado et al., 2020]] ). Woody encroachment is the dominant trend in the western and central Sahel, occurring over 24% of the region, driven primarily by shifts in rainfall timing and recovery from drought ( [[#Anchang--2019|Anchang et al., 2019]] ; [[#Brandt--2019|Brandt et al., 2019]] ). Remote sensing studies demonstrate greening in southern Africa and forest expansion into water-limited savannas in central and west Africa ( [[#Baccini--2017|Baccini et al., 2017]] ; [[#Aleman--2018|Aleman et al., 2018]] ; [[#Piao--2020|Piao et al., 2020]] ), with increases in precipitation and atmospheric CO 2 the probable determinants of change ( [[#Venter--2018|Venter et al., 2018]] ; [[#Brandt--2019|Brandt et al., 2019]] ; [[#Zhang--2019|Zhang et al., 2019]] ). These trends of greening and woody plant expansion stand in contrast to the desertification and contraction of vegetated areas highlighted in AR5 ( [[#Niang--2014|Niang et al., 2014]] ), but are based on multiple studies and longer time series of observations. Reported cases of desertification and vegetation loss, for example, in the Sahel, appear transitory and localised rather than widespread and permanent ( [[#Dardel--2014|Dardel et al., 2014]] ; [[#Pandit--2018|Pandit et al., 2018]] ; [[#Sterk--2020|Sterk and Stoorvogel, 2020]] ).

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[[File:29c1d31d22d4753decc5ef662d422044 IPCC_AR6_WGII_Figure_9_017.png]]

'''Figure 9.17 |''' '''Widespread changes to African vegetation have been reported, especially increasing woody plant cover in many savannas and grasslands, with 37% of these changes proposed to be driven by human-caused climate change and increased CO''' '''2''' '''(a)'''. The warming of lakes and rivers has been detected across Africa and is attributed to climate change. Data on vegetation change was gathered from 156 studies published between 1989 and 2021 '''(b)''' . Climatic changes, mostly associated with changes in rainfall, are enhancing grass production in arid grasslands and savannas, and causing grass expansion into semi-desert regions with notable increases in the Sahel and southern Africa. Tropical forest expansion into mesic savannas is occurring on the fringes of the central African tropical forest. Interactions between land use, climate change and increasing atmospheric CO 2 concentrations are causing a widespread increase in woody plant cover encroachment in tropical savannas and grasslands. Some tree death and woody cover decline associated with climate and land use change have also been recorded across biomes. Of the reported changes to terrestrial vegetation, 24% were explicitly linked to climate change and a further 13% were proposed to be driven by climate change. In 48% of studies, no climate driver was mentioned and in 15% climate change was ruled out as the driver of change. Annual surface water temperatures in African lakes have warmed at a rate of 0.05°C–0.76°C per decade. Both satellite-based measures spanning 1985–2011 and ''in situ'' measurements spanning 1927–2014 agree on this warming trend. Other surface waters across Africa warmed from 1979–2018 at a rate of between 0.05°C and 0.5°C per decade ( [[#Woolway--2020|Woolway and Maberly, 2020]] ). Vegetation change data were taken from a larger, global literature survey of existing databases supplemented with newer studies documenting changes in tree, shrub and grass cover linked to climate and land use change in natural and semi-natural areas (for further details see [[IPCC:Wg2:Chapter:Chapter-2#2.4.3.5|Section 2.4.3.5]] ; Table SM2.1; Table SM9.2 for Africa vegetation change data and Table SM9.3 for studies reporting lake warming data).

Shifts in demography, geographic ranges, and abundance of plants and animals consistent with expected impacts of climate change are evident across Africa. These include uphill contractions of elevational range limits of birds ( [[#Neate-Clegg--2021|Neate-Clegg et al., 2021]] ), changes in species distributions previously reported in AR5 ( [[#Niang--2014|Niang et al., 2014]] ) and the death of many of the oldest and largest African baobabs ( [[#Patrut--2018|Patrut et al., 2018]] ). An increase in frequency and intensity of hot, dry weather after wildfires has led to a long-term decline in plant biodiversity in Fynbos since the 1960s ( [[#Slingsby--2017|Slingsby et al., 2017]] ). Increasing temperatures may have contributed to the declining abundance and range size of South African birds ( [[#Milne--2015|Milne et al., 2015]] ), including Cape Rockjumper ( ''Chaetops frenatus'' ) and protea canary ( ''Serinus leucopterus'' ), from increased risk of reproductive failure ( [[#Lee--2016|Lee and Barnard, 2016]] ; [[#Oswald--2020|Oswald et al., 2020]] ). For hot and dry regions (e.g., Kalahari), there is strong evidence that increased temperatures are having chronic sublethal impacts, including reduced foraging efficiency and loss of body mass ( [[#du%20Plessis--2012|du Plessis et al., 2012]] ; [[#Conradie--2019|Conradie et al., 2019]] ), and are approaching species physiological limits, with heat extremes driving mass mortality events in birds and bats ( [[#McKechnie--2021|McKechnie et al., 2021]] ). Vegetation change linked to climate change and increasing atmospheric CO 2 has had an indirect impact on animals. Increased woody cover has decreased the occurrence of bird, reptile and mammal species that require grassy habitats ( [[#Péron--2015|Péron and Altwegg, 2015]] ; [[#McCleery--2018|McCleery et al., 2018]] ). Decreased fruit production linked to rising temperatures has decreased the body condition of fruit-dependent forest elephants by 11% from 2008–2018 ( [[#Bush--2020|Bush et al., 2020]] ).

There is ''high agreement'' that land use activities counteract or exacerbate climate-driven vegetation change ( [[#Aleman--2017|Aleman et al., 2017]] ; [[#Timm%20Hoffman--2019|Timm Hoffman et al., 2019]] ). Decreased woody plant biomass in 11% of sub-Saharan Africa was attributed to land clearing for agriculture ( [[#Brandt--2017|Brandt et al., 2017]] ; [[#Ordway--2017|Ordway et al., 2017]] ). Localised loss of tree cover in Miombo woodlands and 16.6±0.5 Mha of forest loss in the Congo Basin between 2000–2014 was driven largely by forest clearing and drought mortality ( [[#McNicol--2018|McNicol et al., 2018]] ; [[#Tyukavina--2018|Tyukavina et al., 2018]] ).

Vegetation changes interacting with climate and land use change have impacted fire regimes across Africa. The frequency of weather conducive for fire has increased in southern and west Africa and is expected to continue increasing in the 21st century under both RCP2.6 and RCP8.5 ( [[#Betts--2015|Betts et al., 2015]] ; [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ). Increased grass cover in arid regions introduced fire into regions where fuel was previously insufficient to allow fire spread, such as the arid Karoo in South Africa ( [[#du%20Toit--2015|du Toit et al., 2015]] ; [[#Strydom--2016|Strydom and Savage, 2016]] ). In contrast, shrub encroachment, increased precipitation ( [[#Zubkova--2019|Zubkova et al., 2019]] ), vegetation fragmentation and cropland expansion have reduced fire activity in many African grasslands and savannas ( [[#Andela--2014|Andela and van der Werf, 2014]] ; [[#Probert--2019|Probert et al., 2019]] ). These drivers are expected to negate the effect of increasing fire weather and ultimately lead to a reduction in the total burned area under RCP4.5 and RCP8.5 ( [[#Knorr--2016|Knorr et al., 2016]] ; [[#Moncrieff--2016|Moncrieff et al., 2016]] ; [[#Wu--2016|Wu et al., 2016]] ).

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<span id="vegetation-resilience"></span>
==== 9.6.1.2 Vegetation Resilience ====

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African ecosystems have a long evolutionary association with fire, large mammal herbivory and drought ( [[#Maurin--2014|Maurin et al., 2014]] ; [[#Charles-Dominique--2016|Charles-Dominique et al., 2016]] ). The maintenance of biodiversity depends on natural disturbance regimes. Natural regrowth of savanna plant biomass in southern Africa compensated for biomass removal through human activities ( [[#McNicol--2018|McNicol et al., 2018]] ), and rapid recovery occurred after the 2014–2016 extreme drought ( [[#Abbas--2019|Abbas et al., 2019]] ). During the same drought event, browsing and mixed feeder herbivores were resilient, but grazers declined by approximately 60% and were highly dependent on drought refugia ( [[#Abraham--2019|Abraham et al., 2019]] ). African tropical forests remained a carbon sink through the record drought and temperature experienced in the 2015–2016 El Niño, indicating resilience in the face of extreme environmental conditions ( [[#Bennett--2021|Bennett et al., 2021]] ). This is likely due to the presence of drought-tolerant species and floristic and functional shifts in tree species assemblages ( [[#Fauset--2012|Fauset et al., 2012]] ; [[#Aguirre-Gutiérrez--2019|Aguirre-Gutiérrez et al., 2019]] ). This resilience indicates that there is the capacity to recover from disturbances and short-term change. However, resilience has limits and beyond certain points, change can lead to irreversible shifts to different states (Figure 9.18).

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[[File:2231fbaa13ecb25d4097f6b0d5a9d818 IPCC_AR6_WGII_Figure_9_018.png]]

'''Figure 9.18 |''' '''Increases in atmospheric CO''' '''2''' '''and changes in aridity are projected to shift the geographic distribution of major biomes across Africa (''' '''high confidence''' ''').''' Arrows in the diagram indicate possible pathways of biome change from current conditions resulting from changes in CO 2 and aridity. Changes need not be gradual or linear and may occur rapidly if tipping points are crossed. Currently, widespread greening observed in Africa has been at least partially attributed to increasing atmospheric CO 2 concentrations. Future projected increases in aridity are expected to cause desertification in many regions, but it is highly uncertain how this will interact with the greening effect of CO 2 . Inset maps show the projected geographical extent of changes in CO 2 concentrations and aridity. CO 2 is projected to increase globally under all future emission scenarios. Aridity index maps show projected change in aridity (calculated as annual precipitation/annual potential evapotranspiration) at around 4°C global warming relative to 1850–1900 (RCP8.5 in 2070–2099) from 34 CMIP5 models ( [[#Scheff--2017|Scheff et al., 2017]] ). Shaded areas indicate regions where &gt;75% of models agree on the direction of change.

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<span id="freshwater-ecosystems"></span>
==== 9.6.1.3 Freshwater Ecosystems ====

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Small climatic variations have large impacts on ecosystem function in Africa’s freshwaters ( [[#Ndebele-Murisa--2014|Ndebele-Murisa, 2014]] ; [[#Ogutu-Ohwayo--2016|Ogutu-Ohwayo et al., 2016]] ). Warming of water temperatures from 0.2°C to 3.2°C occurred in several lakes over 1927–2014 and has been attributed to human-caused climate change (Figure 9.17; [[#Ogutu-Ohwayo--2016|Ogutu-Ohwayo et al., 2016]] ). Increased temperature, changes in rainfall and reduced wind speed altered the physical and chemical properties of inland water bodies, affecting water quality and productivity of algae, invertebrates and fish ( ''high confidence'' ). In deeper lakes, warmer surface waters and decreasing wind speeds reduced shallow waters mixing with nutrient-rich deeper waters, reducing biological productivity in the upper sunlit zone ( [[#Ndebele-Murisa--2014|Ndebele-Murisa, 2014]] ; [[#Saulnier-Talbot--2014|Saulnier-Talbot et al., 2014]] ). In several lakes, climate change was identified as causing changes in insect emergence time ( [[#Dallas--2014|Dallas and Rivers-Moore, 2014]] ) and in loss of fish habitats ( [[#Natugonza--2015|Natugonza et al., 2015]] ; [[#Gownaris--2016|Gownaris et al., 2016]] ). This set of changes can harm human livelihoods, for example, from reduced fisheries productivity (see [[#9.8.5|Section 9.8.5]] ; [[#Ndebele-Murisa--2014|Ndebele-Murisa, 2014]] ; [[#Ogutu-Ohwayo--2016|Ogutu-Ohwayo et al., 2016]] ) and reduced water supply and quality ( [[#9.7.1|Section 9.7.1]] ).

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<span id="marine-ecosystems"></span>
==== 9.6.1.4 Marine Ecosystems ====

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Anthropogenic climate change is already negatively impacting Africa’s marine biodiversity, ecosystem functioning and services by changing physical and chemical properties of seawater (increased temperature, salinity and acidification, and changes in oxygen concentration, ocean currents and vertical stratification) ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; 2018). Coastal ecosystems in west Africa are among the most vulnerable because of extensive low-lying deltas exposed to sea level rise, erosion, saltwater intrusion and flooding ( [[#Belhabib--2016|Belhabib et al., 2016]] ; [[#UNEP--2016b|UNEP, 2016b]] ; [[#Kifani--2018|Kifani et al., 2018]] ). In southern Africa, shifting distributions of anchovy, sardine, hake, rock lobster and seabirds have been partly attributed to climate change ( [[#Crawford--2015|Crawford et al., 2015]] ; [[#van%20der%20Lingen--2018|van der Lingen and Hampton, 2018]] ; [[#Vizy--2018|Vizy et al., 2018]] ), including southern shifts of 30 estuarine and marine fish species attributed to increased temperature and changes in water circulation from decreased river inflow ( [[#Augustyn--2018|Augustyn et al., 2018]] ). Warming sea surface temperatures inhibiting nutrient mixing have reduced phytoplankton biomass in the western Indian Ocean by 20% since the 1960s, potentially reducing tuna catches ( [[#Roxy--2016|Roxy et al., 2016]] ).

Mangroves, seagrasses and coral reefs support nursery habitats for fish, sequester carbon, trap sediment and provide shoreline protection ( [[#Ghermandi--2019|Ghermandi et al., 2019]] ). Climate change is compromising these ecosystem services ( ''medium confidence'' ). Marine heatwaves associated with ENSO events have triggered mass coral bleaching and mortality over the past 20 years ( [[#Oliver--2018|Oliver et al., 2018]] ). Mass coral bleaching in the western Indian Ocean occurred in 1998, 2005, 2010 and 2015/2016 with coral cover just 30–40% of 1998 levels by 2016 ( [[#Obura--2017|Obura et al., 2017]] ; [[#Moustahfid--2018|Moustahfid et al., 2018]] ). The northern Mozambique Channel has served as a refuge from climate change and biological reservoir for the entire coastal east African region ( [[#McClanahan--2014|McClanahan et al., 2014]] ; [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ). A southern shift of mangrove species has been observed in south Africa ( [[#Peer--2018|Peer et al., 2018]] ) with loss in total suitable coastal habitats for mangroves and shifts in the distribution of some species of mangroves and a gain for others ( [[#Record--2013|Record et al., 2013]] ). Mangrove cover was reduced 48% in Mozambique in 2000 from Tropical Cyclone Eline, with 100% mortality of seaward mangroves dominated by ''Rhizophora mucronata'' ( [[#Macamo--2016|Macamo et al., 2016]] ). Recovery of mangrove species was observed 14 years later in sheltered sites. There is ''low confidence'' these cyclone-induced impacts are attributable to climate change owing, in part, to a lack of reliable long-term data sets ( [[#Macamo--2016|Macamo et al., 2016]] ). In west Africa, oil and gas extraction, deforestation, canalisation and de-silting of waterways have been the largest factors in mangrove destruction ( [[#Numbere--2019|Numbere, 2019]] ).

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<span id="projected-risks-of-climate-change-for-african-biodiversity-and-ecosystem-services"></span>
=== 9.6.2 Projected Risks of Climate Change for African Biodiversity and Ecosystem Services ===

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<span id="projected-biome-distribution"></span>
==== 9.6.2.1 Projected Biome Distribution ====

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The geography of African biomes is projected to shift due to changes in atmospheric CO 2 concentrations and aridity (Figure 9.18). Grassland expansion into the desert, woody expansion into grasslands and forest expansion into savannas are projected for areas of reduced aridity, caused by reduced moisture stress from CO 2 fertilisation under medium (RCP4.5) and high (SRES A2) emissions scenarios ( [[#Heubes--2011|Heubes et al., 2011]] ; [[#Moncrieff--2016|Moncrieff et al., 2016]] ). This greening trend may slow or reverse with continued temperature increase and/or in areas of increased aridity ( [[#Berdugo--2020|Berdugo et al., 2020]] ). The net impact of these effects on vegetation is highly uncertain ( [[#Trugman--2018|Trugman et al., 2018]] ; [[#Cook--2020a|Cook et al., 2020a]] ; [[#Martens--2021|Martens et al., 2021]] ). The maintenance or re-establishment of natural fire and large mammal herbivory processes can mitigate projected CO 2 and climate-driven changes ( [[#Scheiter--2016|Scheiter and Savadogo, 2016]] ; [[#Stevens--2016|Stevens et al., 2016]] ). Expansion of croplands and pastures will reduce ecosystem carbon storage in Africa, potentially reversing climate- and CO 2 -driven greening in savannas ( [[#Aleman--2018|Aleman et al., 2018]] ; [[#Quesada--2018|Quesada et al., 2018]] ).

Vegetation growth simulated by dynamic vegetation models is often highly sensitive to CO 2 fertilisation. These models project the African tropical forest carbon sink to be stable or strengthened under scenarios of future climate change ( [[#Huntingford--2013|Huntingford et al., 2013]] ; [[#Martens--2021|Martens et al., 2021]] ). In contrast, statistical modelling suggests it has begun to decline and will weaken further, decreasing from current estimates of 0.66 tonnes of carbon removed from the atmosphere per hectare per year to 0.55 tonnes of carbon ( [[#Hubau--2020|Hubau et al., 2020]] ). Increasing rainfall seasonality and aridity over central Africa ( [[#Haensler--2013|Haensler et al., 2013]] ) threatens the massive carbon store in the Congo Basin’s Cuvette Centrale peatlands, estimated at 30.6 billion tonnes ( [[#Dargie--2019|Dargie et al., 2019]] ).

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<span id="terrestrial-biodiversity"></span>
==== 9.6.2.2 Terrestrial Biodiversity ====

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Local extinction is when a species is extirpated from a local site. The magnitude and extent of local extinctions predicted across Africa increase substantially under all future GWLs ( ''high confidence'' ) (Table 9.5; Figure 9.19). Above 2°C, the risk of sudden disruption or loss of local biodiversity increases and becomes more widespread, especially in central, west and east Africa ( [[#Trisos--2020|Trisos et al., 2020]] ).

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[[File:d2c9e11f54cfd15d667d0193002e6a07 IPCC_AR6_WGII_Figure_9_019.png]]

'''Figure 9.19 |''' '''The loss of African biodiversity under future climate change is projected to be widespread and increasing substantially with every 0.5° above the current (2001–2020) level of global warming (''' high confidence ''').'''

'''(a)''' Projected biodiversity loss, quantified as percentage change in species abundance, range size or area of suitable habitat increases with increasing global warming levels (relative to 1850–1900). Above 1.5°C global warming, half of all assessed species are projected to lose &gt;30% of their population, range size or area of suitable habitat, with losses increasing to &gt;40% for &gt;2°C. The 2001–2020 level of global warming is around 1°C higher than 1850–1900 ( [[#IPCC--2021|IPCC, 2021]] ). Boxplots show the median (horizontal line), 50% quantiles (box), and points are studies of individual species or of multiple species (symbol size indicates the number of species in a study).

'''(b–c)''' The mean projected local extinction of vertebrates, plants and insects within 100 km grid cells increases in severity and extent under increased global warming (relative to 1850–1900). Local extinction &gt;10% is widespread by 1.5°C. Pixel colour shows the projected percentage of species undergoing local extinction and the agreement between multiple biodiversity models.

'''(d–e)''' The mean projected increase in species of freshwater fish vulnerable to local extinction within 10 km grid cells for future global warming. Around a third of fish species are projected to be vulnerable to extinction by 2°C global warming. Pixel colour shows the projected percentage of species vulnerable to extinction and agreement between multiple vulnerability models. In (a), data were obtained from 22 peer-reviewed papers published since 2012 investigating the impacts of projected climate change on African biodiversity. When a paper provided impact projections for several time periods, climate change scenarios or for more than one species, each impact was recorded as an individual biodiversity impact projection, resulting in a database of 1165 biodiversity impact projections. Data were initially collected by [[#Manes--2021|Manes et al. (2021)]] as part of a larger literature review for [https://www.ipcc.ch/chapter/cross-chapter-paper-1 Cross-Chapter Paper 1] on Biodiversity Hotspots and then expanded to include areas outside of African priority conservation areas (see Table SM 9.4). The literature review was limited to peer-reviewed publications that reported quantifiable risks to biodiversity, eliminating non-empirical studies. In (b–c), projections are based on intersecting current and future modelled species distributions at ~10 km spatial resolution from two recent global assessments of climate change impacts on terrestrial vertebrates ( [[#Newbold--2018|Newbold, 2018]] ; [[#Warren--2018|Warren et al., 2018]] ). In (d-e) projections are based on intersecting future species vulnerabilities from two recent assessments of climate change vulnerability of freshwater fish species ( [[#Nyboer--2019|Nyboer et al., 2019]] ; [[#Barbarossa--2021|Barbarossa et al., 2021]] ).

Global extinction is when a species is extirpated from all areas. At 2°C global warming, 11.6% of African species (mean 11.6%, 95% CI 6.8–18.2%) assessed are at risk of global extinction, placing Africa second only to South America in the magnitude of projected biodiversity losses ( [[#Urban--2015|Urban, 2015]] ). At &gt;2°C, 20% of north African mammals may lose all suitable climates ( [[#Soultan--2019|Soultan et al., 2019]] ), and over half of the dwarf succulents in South African Karoo may lose &gt;90% of their suitable habitat ( [[#Young--2016|Young et al., 2016]] ). Among the thousands of species at risk, many are species of ecological, cultural and economic importance such as African wild dogs ( [[#Woodroffe--2017|Woodroffe et al., 2017]] ) and Arabica coffee ( [[#Moat--2019|Moat et al., 2019]] ).

With increasing warming, there is a lower likelihood species can migrate rapidly enough to track shifting climates, increasing global extinction risk and biodiversity loss across more of Africa ( ''high confidence'' ). Immigration of species from elsewhere may partly compensate for local extinctions and lead to local biodiversity gains in some regions ( [[#Newbold--2018|Newbold, 2018]] ; [[#Warren--2018|Warren et al., 2018]] ). However, more regions face net losses than net gains. At 1.5°C global warming, &gt;46% of localities face net declines in vertebrate species richness of &gt;10%, with net increases projected for less than 15% of localities ( [[#Barbet-Massin--2015|Barbet-Massin and Jetz, 2015]] ; [[#Newbold--2018|Newbold, 2018]] ). At &gt;2°C, 9% of species face complete range loss by 2100, regardless of their dispersal ability ( [[#Urban--2015|Urban, 2015]] ). With &gt;4°C global warming, a net loss of &gt;10% of vertebrate species richness is projected across 85% of Africa ( [[#Barbet-Massin--2015|Barbet-Massin and Jetz, 2015]] ; [[#Mokhatla--2015|Mokhatla et al., 2015]] ; [[#Newbold--2018|Newbold, 2018]] ; [[#Warren--2018|Warren et al., 2018]] ). Mountain top endemics and species in north and southern Africa are at risk due to disappearing cold climates ( [[#Milne--2015|Milne et al., 2015]] ; [[#Garcia--2016|Garcia et al., 2016]] ; [[#Bentley--2018|Bentley et al., 2018]] ; [[#Soultan--2019|Soultan et al., 2019]] ). For hot regions such as the Sahara, Congo Basin and Kalahari, no warmer-adapted species are available elsewhere to compensate for local extinctions, so the resilience of local biodiversity will depend entirely on the persistence of species ( [[#Burrows--2014|Burrows et al., 2014]] ; [[#Garcia--2014|Garcia et al., 2014]] ). The capacity for species to avoid extinction through behavioural thermoregulation, plasticity or evolution is uncertain but will become increasingly ''unlikely'' under higher warming scenarios ( [[#Conradie--2019|Conradie et al., 2019]] ).

'''Table 9.5 |''' Risk of local extinction increases across Africa with increasing global warming.

{| class="wikitable"
|-
! '''Global warming level (relative to 1850–1900)'''

! '''Taxa'''

! '''Percentage of species at a site at risk of local extinction'''

! '''Extent across Africa (percentage of the land area of Africa)'''

! '''Areas at risk'''

! '''References'''

|-
| 1.5°C

| Plants, insects, vertebrates

| &gt;10%

| &gt;90%

| Widespread. Hot and/or arid regions especially at risk, including Sahara, Sahel and Kalahari

| Figure 9.29b; [[#Newbold--2018|Newbold (2018)]] ; [[#Warren--2018|Warren et al. (2018)]]

|-
| &gt;2°C

| Plants, insects, vertebrates

| &gt;50%

| 18%

| Widespread

| [[#Newbold--2018|Newbold (2018)]] ; [[#Warren--2018|Warren et al. (2018)]]

|-
| &gt;4°C

| Plants, insects, vertebrates

| &gt;50%

| 45–73%

| Widespread. Higher uncertainty for central African tropical forests due to lower agreement between biodiversity models

| Fig. 9.29c; [[#Newbold--2018|Newbold (2018)]] ; [[#Warren--2018|Warren et al. (2018)]]

|}

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<span id="marine-ecosystems-1"></span>
==== 9.6.2.3 Marine Ecosystems ====

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African coastal and marine ecosystems are highly vulnerable to climate change ( ''high confidence'' ). At 1.5°C of global warming, mangroves will be exposed to sedimentation and sea level rise, while seagrass ecosystems will be most affected by heat extremes ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) and turbidity ( [[#Wong--2014|Wong et al., 2014]] ). These risks will be amplified at 2°C and 3°C ( ''virtually certain'' ) ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ). Over 90% of east African coral reefs are projected to be destroyed by bleaching at 2°C of global warming ( ''very high confidence'' ) ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ). At around 2.5°C global warming, an important reef-building coral ( ''Diploastrea heliopora'' ) in the central Red Sea is projected to stop growing altogether ( [[#Cantin--2010|Cantin et al., 2010]] ). By 2.5°C, suitable habitat of &gt;50% of species are projected to decline for coastal lobster in east and north Africa, with large declines for the commercially important lobster species ''Jasus lalandii'' in southern Africa ( [[#Boavida-Portugal--2018|Boavida-Portugal et al., 2018]] ). More generally, tropical regions, especially exclusive economic zones in west Africa, are projected to lose large numbers of marine species and may experience sudden declines with extratropical regions having potential net increases as species track shifting temperatures poleward (García Molinos et al., 2016; [[#Trisos--2020|Trisos et al., 2020]] ).

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<span id="freshwater-ecosystems-1"></span>
==== 9.6.2.4 Freshwater Ecosystems ====

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Above 2°C global warming, the proportion of freshwater fish species vulnerable to climate change increases substantially ( ''high confidence'' ) (Figure 9.19). At 2°C, 36.4% of fish species are projected to be vulnerable to local or global extinction by 2100, increasing to 56.4% under 4°C warming (average of values from ( [[#Nyboer--2019|Nyboer et al., 2019]] ; [[#Barbarossa--2021|Barbarossa et al., 2021]] ) (Figure 9.19). Global warming reduces available habitat for freshwater species due to reduced precipitation and increased drought leading to increasing water temperatures above optimal physiological limits in floodplains, estuaries, wetlands, ephemeral pools, rivers and lakes ( [[#Dalu--2017|Dalu et al., 2017]] ; [[#Kalacska--2017|Kalacska et al., 2017]] ; [[#Nyboer--2018|Nyboer and Chapman, 2018]] ). Along the Zambezi River, projected flow reductions could cause a 22% reduction in annual spawning habitat and depletion of food resources for fry and juvenile fish that could impede fish migration and reduce stocks ( [[#Kangalawe--2017|Kangalawe, 2017]] ; [[#Martínez-Capel--2017|Martínez-Capel et al., 2017]] ; [[#Tamatamah--2020|Tamatamah and Mwedzi, 2020]] ). More aquatic species will have the capacity to cope with 2°C compared to 4°C global warming, with more negative effects on physiological performance at 4°C ( [[#Dallas--2016|Dallas, 2016]] ; [[#Pinceel--2016|Pinceel et al., 2016]] ; [[#Zougmoré--2016|Zougmoré et al., 2016]] ; [[#Nyboer--2017|Nyboer and Chapman, 2017]] ; [[#Ross-Gillespie--2018|Ross-Gillespie et al., 2018]] ). Endemic, specialised fish species will have a lower capacity to adjust to elevated water temperatures compared to hardier generalist fishes ( [[#McDonnell--2015|McDonnell and Chapman, 2015]] ; [[#Nyboer--2017|Nyboer and Chapman, 2017]] ; [[#Lapointe--2018|Lapointe et al., 2018]] ; [[#Reizenberg--2019|Reizenberg et al., 2019]] ). More work is needed to understand the risk for invertebrates ( [[#Dallas--2014|Dallas and Rivers-Moore, 2014]] ; [[#Cohen--2016|Cohen et al., 2016]] ), and to understand the potential effects of reduced mixing of water and other climate risks on freshwater biodiversity.

<div id="9.6.2.5" class="h3-container"></div>

<span id="climate-change-and-ecosystem-services"></span>
==== 9.6.2.5 Climate Change and Ecosystem Services ====

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Direct human dependence on provisioning ecosystem services in Africa is high ( [[#Egoh--2012|Egoh et al., 2012]] ; [[#IPBES--2018|IPBES, 2018]] ). For example, natural forests provided 21% of rural household income across 11 African countries ( [[#Angelsen--2014|Angelsen et al., 2014]] ) and wild-harvested foods (including fisheries) provide important nutrition to millions of Africans, including through important micronutrients and increased dietary diversity (Sections 9.8.2.3; 9.8.5; [[#Powell--2013|Powell et al., 2013]] ; [[#Baudron--2019a|Baudron et al., 2019a]] ).

Climate change has affected ecosystem services in Africa by reducing fish stocks, crop and livestock productivity, and water provisioning due to heat and drought (see Sections 9.8.2.1; 9.8.2.2; 9.8.2.4; 9.8.5.1). Woody encroachment is decreasing cattle production and water supply ( [[#Smit--2015|Smit and Prins, 2015]] ; [[#Stafford--2017|Stafford et al., 2017]] ), but can also provide forage for goat production, as well as resins, fuelwood and charcoal ( [[#Reed--2015|Reed et al., 2015]] ; [[#Stafford--2017|Stafford et al., 2017]] ; [[#Charis--2019|Charis et al., 2019]] ). Local communities perceive climate change to have decreased crop and livestock productivity, reduced wild food availability and reduced forest resources across Africa (see Sections 9.8.2.1; 9.8.2.2; 9.8.2.4; 9.8.2.3; [[#Onyekuru--2014|Onyekuru and Marchant, 2014]] ).

With global warming &gt;3°C, and with high population growth and agricultural expansion (SSP3, 2081–2100), 1.2 billion Africans are projected to be negatively affected by pollution of drinking water from reduced water quality regulation by ecosystems and 27 million people affected by reduced coastal protection by ecosystems ( [[#Chaplin-Kramer--2019|Chaplin-Kramer et al., 2019]] ). The number of people affected reduces to 0.4 billion and 22 million, respectively, under a sustainable development scenario with global warming below 2°C (SSP1, 2081–2100). The African tropical forest carbon sink has been more resilient than Amazonia to recent warming but may already have peaked, and this service is predicted to decline with further warming, reducing 14% by the 2030s ( [[#Hubau--2020|Hubau et al., 2020]] ; [[#Sullivan--2020|Sullivan et al., 2020]] ). This declining carbon storage may be offset by CO 2 fertilization ( ''low confidence'' ) ( [[#Martens--2021|Martens et al., 2021]] ). Climate change is projected to shift the geographic distribution of important human and livestock disease vectors (see Sections 9.8.2.4; 9.10.2). Changes in rainfall seasonality compounded with land privatisation and population growth may adversely impact nomadic and semi-nomadic pastoralists who follow shifting patterns of greening vegetation ( [[#Van%20Der%20Ree--2015|Van Der Ree et al., 2015]] ).

<div id="9.6.2.6" class="h3-container"></div>

<span id="invasive-species"></span>
==== 9.6.2.6 Invasive Species ====

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Invasive species threaten African ecosystems and livelihoods ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). For instance, economic impacts were estimated at USD 1 billion per year for smallholder maize farmers in east Africa ( [[#Pratt--2017|Pratt et al., 2017]] ). Climate change is projected to change patterns of invasive species spread ( ''high confidence'' ). The area of suitable climate for ''Lantana camara'' is projected to contract ( [[#Taylor--2012|Taylor et al., 2012]] ) and to expand for ''Prosopis juliflora'' ( [[#Sintayehu--2020|Sintayehu et al., 2020]] ). Bioclimatic suitability for fall armyworm, a major threat to maize, is projected to decrease in central Africa but expand in southern and west Africa ( [[#Zacarias--2020|Zacarias, 2020]] ), and to expand for coffee berry borer ( ''Hypothenemus hampei'' ) in Uganda and around Mount Kenya ( [[#Jaramillo--2011|Jaramillo et al., 2011]] ). Climate suitability for tephritid fruit flies is projected to decrease in central Africa ( [[#Hill--2016|Hill et al., 2016]] ). Increased water temperature is projected to favour invasive over local freshwater fish populations and shift the range of invasive aquatic plants in South Africa ( [[#Hoveka--2016|Hoveka et al., 2016]] ; [[#Shelton--2018|Shelton et al., 2018]] ). Alterations to lake and river connectivity are predicted to modify invasion pathways in Lake Tanganyika and water hyacinth coverage may increase with warmer waters in Lake Victoria ( [[#Masters--2010|Masters and Norgrove, 2010]] ; [[#Plisnier--2018|Plisnier et al., 2018]] ).

<div id="9.6.3" class="h2-container"></div>

<span id="nature-based-tourism-in-africa"></span>
=== 9.6.3 Nature-based Tourism in Africa ===

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Nature-based tourism is important for African economies and jobs. Tourism contributed 8.5% of Africa’s 2018 gross domestic product (GDP) (World Travel and Tourism Council, 2019a) with wildlife tourism contributing a third of tourism revenue (USD 70.6 billion), supporting 8.8 million jobs ( [[#World%20Travel%20and%20Tourism%20Council--2019b|World Travel and Tourism Council, 2019b]] ).

Climate change is already negatively affecting tourism in Africa ( ''high confidence'' ). The 2015–2018 Cape Town drought caused severe water restrictions, reducing tourist arrivals and spending with associated job losses ( [[#Dube--2020|Dube et al., 2020]] ). Human-caused climate change increased the likelihood of the reduced rainfall that caused the drought by a factor of three ( [[#Otto--2018|Otto et al., 2018]] )( [[#Pascale--2020|Pascale et al., 2020]] ). Extreme heat days have increased across South African national parks since the 1990s ( [[#van%20Wilgen--2016|van Wilgen et al., 2016]] ). This reduces animal mobility, decreasing animal viewing opportunities ( [[#Dube--2020|Dube and Nhamo, 2020]] ). Tourists and employees also fear heat stress ( [[#Dube--2020|Dube and Nhamo, 2020]] ). Visitors to South Africa’s national parks preferred to visit in cool-to-mild temperatures ( [[#Coldrey--2020|Coldrey and Turpie, 2020]] ). Extreme weather conditions disrupted tourist activities and damaged infrastructure at Victoria Falls, Hwange National Park, Kruger National Park and the Okavango Delta ( [[#Dube--2018|Dube et al., 2018]] ; [[#Dube--2018|Dube and Nhamo, 2018]] ; [[#Mushawemhuka--2018|Mushawemhuka et al., 2018]] ; [[#Dube--2020|Dube and Nhamo, 2020]] ). Rainfall variability and drought alter wildlife migrations, affecting tourist visits to the Serengeti ( [[#Kilungu--2017|Kilungu et al., 2017]] ). Reduced tourism decreases revenue for national park management ( [[#van%20Wilgen--2016|van Wilgen et al., 2016]] ).

Future climate change is projected to further negatively affect nature-based tourism. Decreased snow and forest cover may reduce visits to Kilimanjaro National Park ( [[#Kilungu--2019|Kilungu et al., 2019]] ). Woody plant expansion in savanna and grasslands reduce tourist’s game viewing experience and negatively impact conservation revenues ( [[#Gray%20Emma--2013|Gray Emma and Bond William, 2013]] ; [[#Arbieu--2017|Arbieu et al., 2017]] ). Visitation rates to South African national parks, based on mean monthly temperatures, are projected to decline 4% with 2°C global warming ( [[#Coldrey--2020|Coldrey and Turpie, 2020]] ). Sea level rise and increased intensity of storms is projected to reduce beach tourism due to beach erosion ( [[#Grant--2015|Grant, 2015]] ; [[#Amusan--2017|Amusan and Olutola, 2017]] ). Tourism in the Victoria Falls, Okavango and Chobe hydrological systems may be negatively affected by heat and increased variability of rainfall and river flow ( [[#Saarinen--2012|Saarinen et al., 2012]] ; [[#Dube--2019|Dube and Nhamo, 2019]] ). Increased extreme heat will increase air turbulence and weight restrictions on aircraft, which could make air travel more uncomfortable and expensive to African destinations ( [[#Coffel--2015|Coffel and Horton, 2015]] ; [[#Dube--2019|Dube and Nhamo, 2019]] ).

<div id="9.6.3.1" class="h3-container"></div>

<span id="protected-areas-and-climate-change"></span>
==== 9.6.3.1 Protected Areas and Climate Change ====

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African protected areas store around 1.5% of global land ecosystem carbon stocks and support biodiversity ( [[#Gray--2016|Gray et al., 2016]] ; [[#Melillo--2016|Melillo et al., 2016]] ; [[#Sala--2018|Sala et al., 2018]] ). They also support livelihoods and economies, such as through nature-based tourism and improved fisheries ( [[#Brockington--2015|Brockington and Wilkie, 2015]] ; [[#Mavah--2018|Mavah et al., 2018]] ; [[#Ban--2019|Ban et al., 2019]] ).

Climate change and land use change will interact to influence the effectiveness of African protected areas ( ''high confidence'' ). Species representation in the existing African protected area network is projected to decrease due to species range shifts for mammals, bats, birds and amphibians ( [[#Hole--2009|Hole et al., 2009]] ; [[#Baker--2015|Baker et al., 2015]] ; [[#Payne--2016|Payne and Bro-Jørgensen, 2016]] ; [[#Smith--2016|Smith et al., 2016]] ; [[#Phipps--2017|Phipps et al., 2017]] ). Species ability to disperse between areas to track shifting climates is increasingly impaired by land transformation and fencing, which also impact seasonal wildlife migrations ( [[#Lovschal--2017|Lovschal et al., 2017]] ; [[#Sloan--2017|Sloan et al., 2017]] ). On land, only 0.5% of the African protected area network is connected through low-impact landscapes ( [[#Ward--2020|Ward et al., 2020]] ). Linear transport infrastructure (e.g., roads, railways, pipelines) and fencing from proposed ‘development corridors’ are projected to bisect over 400 protected areas and degrade around 1800 more ( [[#Laurance--2015|Laurance et al., 2015]] ). Climate change could increase human–wildlife conflict as resultant resource shortages cause communities to move into protected areas for harvesting or livestock grazing, or wildlife to move out of protected areas and into contact with people ( [[#Mukeka--2018|Mukeka et al., 2018]] ; [[#Kupika--2019|Kupika et al., 2019]] ; [[#Hambira--2020|Hambira et al., 2020]] ). See [[#9.6.4|Section 9.6.4]] for the role of land and ocean protected areas in climate change adaptation.

<div id="9.6.4" class="h2-container"></div>

<span id="ecosystem-based-adaptation-in-africa"></span>
=== 9.6.4 Ecosystem-based Adaptation in Africa ===

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Ecosystem-based adaptation (EbA) uses biodiversity and ecosystem services to assist people to adapt to climate change ( [[#Swanepoel--2019|Swanepoel and Sauka, 2019]] ). Africa’s Nationally Determined Contributions (NDCs) show 36% of adaptation actions identified by 52 countries are considered to be EbA (Figure 9.20).

<div id="_idContainer058" class="Figure"></div>

[[File:67ee19000e11abd3395e09f78acef13b IPCC_AR6_WGII_Figure_9_020.png]]

'''Figure 9.20 |''' '''Over a third (36%) of all adaptation actions identified in the NDCs of 52 African countries as of early 2020 were ecosystem-based adaptations (EbA).''' Of these actions ±83% fall within the agriculture, land use/forestry, environment and water sectors. The EbA actions identified from the NDCs span 12 primary sectors and 29 sub-sectors.

EbA can reduce climate impacts and there is high agreement EbA can be more cost-effective than traditional grey infrastructure when a range of economic, social and environmental benefits are also accounted for (Table 9.6; [[#Baig--2016|Baig et al., 2016]] ; [[#Emerton--2017|Emerton, 2017]] ; [[#Chausson--2020|Chausson et al., 2020]] ). This is particularly relevant in Africa where climate vulnerabilities are strongly linked to natural resource-based livelihood practices and existing grey infrastructure levels are low in many regions ( [[#Dube--2016|Dube et al., 2016]] ; [[#Reid--2019|Reid et al., 2019]] ). However, financial constraints limit EbA project implementation ( [[#Mumba--2016|Mumba et al., 2016]] ; [[#Swanepoel--2019|Swanepoel and Sauka, 2019]] ).

'''Table 9.6 |''' The beneficial outcomes of ecosystem-based adaptation (EbA) actions and assessed confidence in these outcomes. Assessment is provided for EbA options in the four most prevalent EbA sectors identified in the Nationally Determined Contributions of 52 African countries (Figure 9.20). See Chapter 2.6.3 and 3.6.2 of this report for further assessment of EbA approaches in terrestrial, freshwater and marine systems.

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

! '''EbA Action(s)'''

! '''Outcome(s)'''

! '''Confidence'''

! '''Source(s)'''

|-
| rowspan="3"| Agriculture

| rowspan="2"| Conservation agriculture

| Improved soil and water conservation

| ''High''

| [[#Thierfelder--2017|Thierfelder et al. (2017)]]

|-
| Improved agricultural productivity and drought resilience

| ''Medium''

| [[#Pittelkow--2015|Pittelkow et al. (2015)]] ; [[#Thierfelder--2017|Thierfelder et al. (2017)]] ; Adenle et al. (2019)

|-
| Diversified crop varieties

| Improved agricultural productivity and drought resilience

| ''High''

| [[#Shiferaw--2014|Shiferaw et al. (2014)]] ; [[#Tesfaye--2016|Tesfaye et al. (2016)]] ; [[#Thierfelder--2017|Thierfelder et al. (2017)]]

|-
| rowspan="4"| Environment

| rowspan="4"| Ecosystem protection and restoration

| Carbon sequestration and storage

| ''High''

| [[#Melillo--2016|Melillo et al. (2016)]] ; [[#Griscom--2017|Griscom et al. (2017)]] ; [[#FAO--2018a|FAO (2018a)]]

|-
| Stepping stones for species migrating due to climate change

| ''Medium''

| [[#Beale--2013|Beale et al. (2013)]] ; Roberts et al. (2020)

|-
| Increased ecosystem resilience to disturbance

| ''High''

| [[#Anthony--2015|Anthony et al. (2015)]] ; Sierra-Correa and Cantera Kintz (2015); [[#Kroon--2016|Kroon et al. (2016)]] ; [[#Roberts--2017|Roberts et al. (2017)]]

|-
| Livelihood diversification opportunities from ecotourism, resource harvesting and rangelands (among others)

| ''Medium''

| [[#Lunga--2016|Lunga and Musarurwa (2016)]] ; Bedelian and Ogutu (2017); [[#Agyeman--2019|Agyeman (2019)]] ; [[#Kupika--2019|Kupika et al. (2019)]] ; [[#Naidoo--2019|Naidoo et al. (2019)]]

|-
| rowspan="2"| Forestry and other land use

| rowspan="2"| Restoration/ reforestation

Sustainable forestry and land management

| Restoration of degraded ecosystems and enhanced carbon sequestration

| ''High''

| [[#Mugwedi--2018|Mugwedi et al. (2018)]]

|-
| Reducing pressure on forests for food and energy needs

| ''Medium''

| [[#Peprah--2017|Peprah (2017)]] ; [[#Zegeye--2018|Zegeye (2018)]]

|-
| rowspan="2"| Water

| rowspan="2"| Integrated catchment management

| Improved flood attenuation capacity

| ''High''

| [[#Bradshaw--2007|Bradshaw et al. (2007)]] ; Mwenge Kahinda et al. (2016); Rawlins et al. (2018)

|-
| Improved resilience of freshwater ecosystems

| ''High''

| [[#Ndebele-Murisa--2014|Ndebele-Murisa (2014)]] ; [[#Natugonza--2015|Natugonza et al. (2015)]] ; (2019); [[#Tamatamah--2020|Tamatamah and Mwedzi (2020)]]

|}

Evidence for EbA in Africa is largely case study based and often anecdotal ( [[#Reid--2018|Reid et al., 2018]] ). There is ''high agreement'' that costs, challenges and negative outcomes of EbA interventions are still poorly understood ( [[#Reid--2016|Reid, 2016]] ; [[#Chaplin-Kramer--2019|Chaplin-Kramer et al., 2019]] ), despite limited evidence for the efficacy of context-specific applications at different scales ( [[#Doswald--2014|Doswald et al., 2014]] ).

<div id="9.6.4.1" class="h3-container"></div>

<span id="terrestrial-ecosystems-1"></span>
==== 9.6.4.1 Terrestrial Ecosystems ====

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Improved ecosystem care and restoration are cost-effective for carbon sequestration while providing multiple environmental, social and economic co-benefits ( [[#Griscom--2017|Griscom et al., 2017]] ; [[#Shukla--2019|Shukla et al., 2019]] ). Protecting and restoring natural forests and wetlands reduces flood risk across multiple African countries ( [[#Bradshaw--2007|Bradshaw et al., 2007]] ). In Kenya, enclosures for rangeland regeneration diversified income sources, which could increase the adaptive capacity of local people ( [[#Mureithi--2016|Mureithi et al., 2016]] ; [[#Wairore--2016|Wairore et al., 2016]] ). Sustainable agroforestry in semi-arid regions provides income sources from fuelwood, fruit and timber and reduces exposure to drought, floods and erosion ( [[#Quandt--2017|Quandt et al., 2017]] ). Forest protection in Zimbabwe maintains honey production during droughts, providing food supply options if crops fail ( [[#Lunga--2016|Lunga and Musarurwa, 2016]] ). Community-based natural resource management in pastoral communities improved institutional governance outcomes through involving community members in decision making, increasing the capacity of these communities to respond to climate change ( [[#Reid--2014|Reid, 2014]] ).

EbA can also increase ecological resilience. Re-introduction of fire and large mammals can restore ecosystem services, enhance adaptive capacity and benefit people by combatting woody encroachment, restoring grazing and increasing streamflow ( [[#Asner--2016|Asner et al., 2016]] ; [[#Stafford--2017|Stafford et al., 2017]] ; [[#Cromsigt--2018|Cromsigt et al., 2018]] ). Herbivores can also reduce fuel loads in areas facing increased fire risk ( [[#Hempson--2017|Hempson et al., 2017]] ).

Protected areas can be ‘stepping stones’ that facilitate climate-induced species range shifts ( [[#Roberts--2020|Roberts et al., 2020]] ), preserve medicinal plant diversity despite climate change ( [[#Kaky--2017|Kaky and Gilbert, 2017]] ) and provide livelihood diversification opportunities (Table 9.6). Protecting 30% of sub-Saharan Africa’s land area could reduce the proportion of species at risk of extinction by around 60% in both low and high warming scenarios ( [[#Hannah--2020|Hannah et al., 2020]] ). The role of protected areas in EbA can be strengthened by: (a) increasing coverage of diverse environments and high carbon storage ecosystems, (b) restoring habitat, (c) maintaining intact habitat, (d) participatory, equitable conservation and adaptation strategies; (e) cooperating across borders and (f) adequate monitoring ( [[#Gillson--2013|Gillson et al., 2013]] ; [[#Rannow--2014|Rannow et al., 2014]] ; [[#Midgley--2015|Midgley and Bond, 2015]] ; [[#Pecl--2017|Pecl et al., 2017]] ; [[#Dinerstein--2019|Dinerstein et al., 2019]] ; [[#Roberts--2020|Roberts et al., 2020]] ).

<div id="9.6.4.2" class="h3-container"></div>

<span id="freshwater-ecosystems-2"></span>
==== 9.6.4.2 Freshwater Ecosystems ====

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EbA can mitigate flooding and increase the resilience of freshwater ecosystems (Table 9.6). Adaptation in African freshwater ecosystems is heavily influenced by non-climate anthropogenic factors, including land use change, water abstraction and diversion, damming and overfishing ( [[#Dodds--2013|Dodds et al., 2013]] ; [[#Kimirei--2020|Kimirei et al., 2020]] ; [[#UNESCO%20and%20UN-Water--2020|UNESCO and UN-Water, 2020]] ). Wetlands and riparian areas support biodiversity, act as natural filtration systems and serve as buffers to changes in the hydrological cycle, thereby increasing the resilience of freshwater ecosystems and the people that rely on them ( [[#Ndebele-Murisa--2014|Ndebele-Murisa, 2014]] ; [[#Musinguzi--2015|Musinguzi et al., 2015]] ; [[#Lowe--2019|Lowe et al., 2019]] ). However, national adaptation programmes of action, NAPs and national communications rarely consider the ecological stability of ecosystems safeguarding the very water resources they seek to preserve ( [[#Kolding--2016|Kolding et al., 2016]] ). Some countries have mandated the protection of riparian zones, but implementation is low ( [[#Musinguzi--2015|Musinguzi et al., 2015]] ; [[#Muchuru--2018|Muchuru and Nhamo, 2018]] ). Protecting terrestrial areas surrounding Lake Tanganyika benefited fish diversity ( [[#Britton--2017|Britton et al., 2017]] ). Afforestation reduces water availability but forest restoration and removing invasive plant species can increase water flows in regions facing water insecurity from climate change ( [[#Chausson--2020|Chausson et al., 2020]] ; [[#Le%20Maitre--2020|Le Maitre et al., 2020]] ). Regular, long-term monitoring of African freshwaters would improve understanding of responses to climate change. General principles for this type of monitoring were developed for Lake Tanganyika ( [[#Plisnier--2018|Plisnier et al., 2018]] ) and could be applied to develop harmonised, regional monitoring of African lakes, rivers and wetlands ( [[#Tamatamah--2020|Tamatamah and Mwedzi, 2020]] )

<div id="9.6.4.3" class="h3-container"></div>

<span id="marine-and-coastal-ecosystems"></span>
==== 9.6.4.3 Marine and Coastal Ecosystems ====

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Marine and coastal ecosystems such as mangroves, seagrass and coral reefs provide storm protection and food security for coastal communities ( ''high confidence'' ) ( [[#IPCC--2019d|IPCC, 2019d]] ). Restoring reef systems reduced wave height in Madagascar ( [[#Narayan--2016|Narayan et al., 2016]] ), but there is limited evidence for the efficacy of coral reef restoration at large scales with increased warming ( [[IPCC:Wg2:Chapter:Chapter-3|Chapter 3]] [[IPCC:Wg2:Chapter:Chapter-3#3.6.3|Section 3.6.3]] ). Populations at risk from storm surge and/or sea level rise coincide with areas of high coastal EbA potential from Mozambique to Somalia, and coastlines of the Gulf of Guinea, Gambia, Guinea-Bissau and Sierra Leone ( [[#Jones--2020|Jones et al., 2020]] ). Understanding hotspots of EbA potential is particularly important for west Africa with some of the highest levels of human dependence on marine ecosystems at high risk from climate change and large populations vulnerable to sea level rise (Sections 9.9.3.1; 9.8.5.2; [[#Selig--2018|Selig et al., 2018]] ; [[#Trisos--2020|Trisos et al., 2020]] ).

Marine protected areas (MPAs) can yield multiple adaptation benefits, such as buffering species from extinction and increasing fish stocks, as well as storing large amounts of carbon ( [[#Edgar--2014|Edgar et al., 2014]] ; [[#Roberts--2017|Roberts et al., 2017]] ; [[#Lovelock--2019|Lovelock and Duarte, 2019]] ). However, this potential of MPAs will reach limits with increased warming ( [[#Roberts--2017|Roberts et al., 2017]] ). For example, MPAs cannot prevent coral bleaching at scale and mass die-offs are well-described from MPAs following climate shocks ( [[#Bates--2019|Bates et al., 2019]] ; [[#Bruno--2019|Bruno et al., 2019]] ). However, prioritising MPA coverage of climate refugia, such as the Northern Mozambique Channel, may offer some increased resilience ( [[#McClanahan--2014|McClanahan et al., 2014]] ).

<div id="box-9.3" class="h2-container box-container"></div>

'''Box 9.3 | Tree planting in Africa'''
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Due to widespread deforestation and forest degradation ( [[#Malhi--2014|Malhi et al., 2014]] ), future scenarios to limit global warming include large-scale reforestation and afforestation ( [[#Griscom--2017|Griscom et al., 2017]] ; [[#Bastin--2019|Bastin et al., 2019]] ). Africa has been targeted through the AFR100 ( https://afr100.org ) to plant ~1 million km 2 of trees by 2030 (Bond et al 2019). Maintaining existing indigenous forest and indigenous forest restoration is a win–win, maximising benefits to biodiversity, adaptation and mitigation ( [[#Griscom--2017|Griscom et al., 2017]] ; [[#Watson--2018|Watson et al., 2018]] ; [[#Lewis--2019|Lewis et al., 2019]] ) ( ''high confidence)'' .

Yet many areas targeted by AFR100 erroneously mark Africa’s open ecosystems (grasslands, savannas, shrublands) as degraded and suitable for afforestation (Figure Box 9.3.1; ( [[#Veldman--2015|Veldman et al., 2015]] ; [[#Bond--2019|Bond et al., 2019]] ) ''(high confidence)'' . These ecosystems are not ''degraded'' , they are ancient ecosystems that evolved in the presence of disturbances (fire/herbivory) ( [[#Maurin--2014|Maurin et al., 2014]] ; [[#Bond--2016|Bond and Zaloumis, 2016]] ; [[#Charles-Dominique--2016|Charles-Dominique et al., 2016]] ). Afforestation prioritises carbon sequestration at the cost of biodiversity and other ecosystem services ( [[#Veldman--2015|Veldman et al., 2015]] ; [[#Bond--2019|Bond et al., 2019]] ). Furthermore, it remains uncertain how much carbon can be sequestered as, compared to grassy ecosystems, afforestation can reduce belowground carbon stores and increase aboveground carbon loss to fire and drought ( [[#Yang--2019|Yang et al., 2019]] ; [[#Wigley--2020b|Wigley et al., 2020b]] ; [[#Nuñez--2021|Nuñez et al., 2021]] ). Thus, afforested areas may store less carbon than ecosystems they replace ( [[#Dass--2018|Dass et al., 2018]] ; [[#Heilmayr--2020|Heilmayr et al., 2020]] ). Afforestation would reduce livestock forage, ecotourism potential and water availability ( [[#Gray%20Emma--2013|Gray Emma and Bond William, 2013]] ; [[#Anadón--2014|Anadón et al., 2014]] ; [[#Cao--2016|Cao et al., 2016]] ; [[#Stafford--2017|Stafford et al., 2017]] ; [[#Du--2021|Du et al., 2021]] ), and may reduce albedo thereby increasing warming ( [[#Bright--2015|Bright et al., 2015]] ; [[#Baldocchi--2019|Baldocchi and Penuelas, 2019]] ).

Exotic tree species are often selected for planting (e.g., ''Pinus'' spp. or ''Eucalyptus'' spp.), but in parts of Africa, they have become invasive ( [[#Zengeya--2017|Zengeya, 2017]] ; [[#Witt--2018|Witt et al., 2018]] ), increasing fire hazards and decreasing biodiversity and water resources ( [[#Nuñez--2021|Nuñez et al., 2021]] ) ''(high confidence)'' . Negative impacts of afforestation on ecosystems are not restricted to plantations of exotic species; they extend to inappropriate planting of native forest species ( [[#Slingsby--2020|Slingsby et al., 2020]] ).

[[File:ad5db9c8a058e1a7ed6f164858cddc79 IPCC_AR6_WGII_Figure_9_Box_9_3_1.png]]

'''Figure Box 9.3.1 |''' '''Many proposed tree planting plans in Africa present risks to biodiversity and livelihoods, because they are focused on'''

(a) naturally non-forested ecosystems like savannas, grasslands and shrublands which

(b) host uniquely adapted biodiversity and

(c) offer important ecosystem services like grazing which supports subsistence and commercial agriculture. Figure adapted from [[#Veldman--2015|Veldman et al. (2015)]] ; [[#Bond--2019|Bond et al. (2019)]] .

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