Editing IPCC:AR6/WGII/Chapter-2 (section)

=== 2.5.3 Risk Assessment of Ecosystems and Related Services ===

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==== 2.5.3.1 Risks in Protected Areas ====

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National parks and other protected areas which, in June 2021, covered 15.7% of the global terrestrial area (UNEP-WCMC et al., 2021), conserve greater biodiversity than adjacent unprotected areas ( [[#Gray--2016|Gray et al., 2016]] ), and protect one-fifth of global vegetation carbon stocks and one-tenth of global soil carbon stocks ( [[#2.4.4.4|Section 2.4.4.4]] ). This section assesses climate change specifically in protected areas. Even though it is included in a part of the chapter on projected risks, it includes both observed exposure and projected risks to gather the information on protected areas into one place.

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===== 2.5.3.1.1 Observed exposure of protected areas =====

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In 2009, deforestation, agricultural expansion, overgrazing and urbanisation exposed one-third of the global protected area (6 million km 2 ) to intense human pressure, a 6% increase from 1993 ( [[#Venter--2016|Venter et al., 2016]] ; [[#Jones--2018|Jones et al., 2018]] ). The exposure to observed climate change has not yet been quantified for protected areas globally, but research has analysed the spatial patterns and magnitudes of observed changes for the 360,000 km 2 system of US national parks ( [[#Gonzalez--2018|Gonzalez et al., 2018]] ) including the first national park in the world. From 1895 to 2010, mean annual temperature of the US national park area increased at a rate of 1°C ± 0.2°C per century, double the rate of the whole USA, and precipitation decreased in 12% of the national park area, compared with 4% for the whole USA, due to a high fraction of US national park area being in the Arctic, at high elevations, and in the arid southwestern USA ( [[#Gonzalez--2018|Gonzalez et al., 2018]] ). In addition, analyses of weather-station measurements in and near six South African national parks found that the maximum temperature increased at a rate of 0.024°C ± 0.003°C yr -1 from 1960 to 2010 ( [[#Van%20Wilgen--2016|Van Wilgen et al., 2016]] ). While a substantial fraction of global protected area has been exposed to observed changes in human land cover, the global exposure to observed climate change is unquantified.

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===== 2.5.3.1.2 Projected risks in protected areas =====

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Under a climate change scenario of ~3.5°C temperature increase by 2070, current climate could disappear from individual protected areas that comprise half the global protected area, and novel climates (climate conditions that are currently not present in an individual protected area) could emerge in half the global protected area ( [[#Hoffmann--2019b|Hoffmann et al., 2019b]] ). A lower-emissions scenario of ~1.5°C could reduce the disappearance of current climate conditions to 40% and the exposure to novel climates to 41% ( [[#Hoffmann--2019b|Hoffmann et al., 2019b]] ). Models project the highest exposure to novel climates in subtropical projected areas ( [[#Hoffmann--2020|Hoffmann and Beierkuhnlein, 2020]] ). Projected disappearance of current climate conditions in protected areas is most extensive in Africa, Oceania, and North and South America ( [[#Elsen--2020|Elsen et al., 2020]] ).

Projections indicate greater exposure of tropical rainforests, shrublands and grasslands, temperate conifer forests and grasslands, and tundra to novel climates ( [[#Hoffmann--2019b|Hoffmann et al., 2019b]] ; [[#Elsen--2020|Elsen et al., 2020]] ). A climate change scenario of ~3.5°C temperature increase by 2100 could expose 32% of the protected area in humid tropical forests (1.6 million km 2 in 2000) to climate that would be novel to humid tropical-forest protected areas; by 2050, the climate currently present in humid tropical-forest protected areas could disappear from 0.6 million km 2 (12% of the current total area) ( [[#Tabor--2018|Tabor et al., 2018]] ). High rates of deforestation and climate change combined could expose 2% of the humid tropical-forest protected area ( [[#Tabor--2018|Tabor et al., 2018]] ). Regional analyses under RCP8.5 also project the substantial disappearance of the current climate in protected areas in Bolivia, Chile and Peru ( [[#Fuentes-Castillo--2020|Fuentes-Castillo et al., 2020]] ), Canada, Mexico and the USA ( [[#Batllori--2017|Batllori et al., 2017]] ; [[#Holsinger--2019|Holsinger et al., 2019]] ), China ( [[#Zomer--2015|Zomer et al., 2015]] ), Europe ( [[#Nila--2019|Nila et al., 2019]] ) and Indonesia ( [[#Scriven--2015|Scriven et al., 2015]] ). Projected climate change could expose an extensive part of the global protected area to disappearing and novel climate conditions ( ''high confidence'' ) (Cross-Chapter Paper 1).

Continued climate change increases the risks to individual species and vegetation types in protected areas. Under a climate change scenario of 4°C temperature increase by 2100, the suitable climate for two species of baobab trees ( ''Adansonia perrieri'' and ''A. suarezensis'' ) in Madagascar could shift entirely out of the protected areas network ( [[#Vieilledent--2013|Vieilledent et al., 2013]] ). Other species and vegetation types at risk from the partial disappearance of suitable climate in protected areas include Atlantic Forest amphibians in Brazil ( [[#Lemes--2014|Lemes et al., 2014]] ), birds in Finland ( [[#Virkkala--2013|Virkkala et al., 2013]] ), birds and trees in Canada and Mexico ( [[#Stralberg--2020|Stralberg et al., 2020]] ), bog woodlands in Germany ( [[#Steinacker--2019|Steinacker et al., 2019]] ), butterflies and mammals in Egypt ( [[#Leach--2013|Leach et al., 2013]] ) and tropical dry forests in Mexico ( [[#Prieto-Torres--2016|Prieto-Torres et al., 2016]] ). Projected disappearance of suitable climate conditions in protected areas increase risks to the survival of species and vegetation types of conservation concern in tropical, temperate and boreal ecosystems ( ''high confidence'' ) (Cross-Chapter Paper 1).

Protected rivers, lakes and other freshwater protected areas require inter-catchment connectivity to maintain species and population movements ( [[#Bush--2014a|Bush et al., 2014a]] ; [[#Hermoso--2016|Hermoso et al., 2016]] ; [[#Thieme--2016|Thieme et al., 2016]] ), but dams and other barriers interrupt connectivity ( [[#Grill--2019|Grill et al., 2019]] ). Climate change could also reduce freshwater connectivity ( [[#2.3.3.3|Section 2.3.3.3]] ). Globally, over two-thirds of river reaches (by length) lack protected areas in their upstream catchments and nine-tenths of river reaches (by length) do not achieve full, integrated protection ( [[#Abell--2017|Abell et al., 2017]] ).

Terrestrial and freshwater protected areas can also serve as climate change refugia, that is, locations where suitable conditions may persist for the species into the future (e.g., [[#2.6.5.6|Section 2.6.5.6]] ). In Canada, Mexico and the USA, only a fraction of the protected area is located in potential climate change refugia under a 4°C temperature increase, estimated at 4% ( [[#Michalak--2018|Michalak et al., 2018]] ) to 7% ( [[#Batllori--2017|Batllori et al., 2017]] ). Potential refugia from biome shifts due to climate change under temperature increases of 1.8°C–3.4°C cover &lt;1% of the area of US national parks ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ), a fraction that diminishes to near zero when climate change is combined with habitat fragmentation due to LUC ( [[#Eigenbrod--2015|Eigenbrod et al., 2015]] ). Protected areas in boreal ecosystems could serve as refugia for species shifting north in Canada ( [[#Berteaux--2018|Berteaux et al., 2018]] ) and Finland ( [[#Lehikoinen--2019|Lehikoinen et al., 2019]] ). Invasive species, habitat loss and other disturbances in protected areas could be lower than in unprotected areas across Europe ( [[#Gallardo--2017|Gallardo et al., 2017]] ), specifically in Spain ( [[#Regos--2016|Regos et al., 2016]] ), and also in Sri Lanka ( [[#Kariyawasam--2020|Kariyawasam et al., 2020]] ). Protected areas conserve refugia from climate change under a temperature increase of 4°C, which is important for biodiversity conservation but is limited to &lt;10% of the current protected area ( ''medium confidence'' ).

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==== 2.5.3.2 Risks to Ecosystems and Services from Wildfire ====

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===== 2.5.3.2.1 Future projections of wildfire globally =====

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Continued climate change under high-emission scenarios that increase global temperature ~4°C by 2100 could increase global burned area by 50% ( [[#Knorr--2016b|Knorr et al., 2016b]] ) to 70% ( [[#Kloster--2017|Kloster and Lasslop, 2017]] ) and global mean fire frequency by ~30% ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ), with increases on one-third ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ) to two-thirds ( [[#Moritz--2012|Moritz et al., 2012]] ) and decreases on one-fifth ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Moritz--2012|Moritz et al., 2012]] ) of land globally. Lower emissions that would limit the global temperature increase to &lt;2°C would reduce projected increases of global burned area to 30% ( [[#Lange--2020|Lange et al., 2020]] ) to 35% ( [[#Kloster--2017|Kloster and Lasslop, 2017]] ) and projected increases of fire frequency to ~20% ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Huang--2015|Huang et al., 2015]] ). Continued climate change could further lengthen fire weather seasons ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). Models combining projected climate change with potential agricultural expansion project decreases in total burned area ( [[#Huang--2015|Huang et al., 2015]] ; [[#Knorr--2016b|Knorr et al., 2016b]] ; [[#Park--2021|Park et al., 2021]] ). The area of projected increases in burned area and fire frequency due solely to continued climate change is higher for the world as a whole than the area of projected decreases ( ''medium evidence'' , ''medium agreement'' ).

Increased wildfire due to continued climate change increases risks of tree mortality (Sections 2.5.2.6, 2.5.2.7, 2.5.3.2), biome shifts ( [[#2.5.2.2|Section 2.5.2.2]] ) and carbon emissions (Sections 2.5.2.10, 2.5.3.4). Wildfire and biome shifts under a projected climate change of 4°C above the pre-industrial period, combined with international trade and transport, cause high risks from invasive species across one-sixth of the global area including extensive high-biodiversity regions ( [[#Early--2016|Early et al., 2016]] ).

Wildfire risks to people include death and destruction of their homes, respiratory illnesses from smoke ( [[#Ford--2018|Ford et al., 2018]] ; [[#Machado-Silva--2020|Machado-Silva et al., 2020]] ), post-fire flooding from areas exposed by vegetation loss and degraded water quality due to increased sediment flow ( [[#Dahm--2015|Dahm et al., 2015]] ) and the chemical precursors of carcinogenic trihalomethanes when water is later chlorinated for drinking ( [[#2.5.3|Section 2.5.3.7]] ) ( [[#Uzun--2020|Uzun et al., 2020]] ). Under RCP8.5 and shared socioeconomic pathway SSP3 (high population growth, slow urbanisation), the number of people living in fire-prone areas could increase by three-quarters to 720 million in 2100, in a projected global population of 12.4 billion people ( [[#Knorr--2016b|Knorr et al., 2016b]] ). Lower emissions under RCP4.5 could reduce the number of people at risk by 70 million. In these projections, human population growth increases human exposure to wildfires more than increases in burned area ( [[#Knorr--2016b|Knorr et al., 2016b]] ). A global temperature increase &lt;2°C could increase global population exposure to wildfire by ~30% ( [[#Lange--2020|Lange et al., 2020]] ). Increased wildfire under continued climate change increases the probability of human exposure to fire and risks to public health ( ''medium evidence'' , ''high agreement'' ).

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===== 2.5.3.2.2 Future projections of wildfire in high-risk areas =====

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Regions identified by multiple global analyses as being at a high risk of increased burned area, fire frequency and fire weather include: the Amazon ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Huang--2015|Huang et al., 2015]] ; [[#Knorr--2016b|Knorr et al., 2016b]] ; [[#Burton--2018|Burton et al., 2018]] ; [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ), Mediterranean Europe ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Burton--2018|Burton et al., 2018]] ; [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ), the Arctic tundra ( [[#Moritz--2012|Moritz et al., 2012]] ; [[#Flannigan--2013|Flannigan et al., 2013]] ), Western Australia ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Burton--2018|Burton et al., 2018]] ; [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ) and the western USA ( [[#Gonzalez--2010|Gonzalez et al., 2010]] ; [[#Moritz--2012|Moritz et al., 2012]] ; [[#Knorr--2016b|Knorr et al., 2016b]] ). Higher-resolution spatial projections indicate high risks of increased wildfire in the Amazon, Australia, boreal ecosystems, Mediterranean Europe and the USA with climate change ( ''medium evidence'' , ''medium agreement'' ).

In the Amazon, climate change under RCP8.5, combined with high deforestation, could double the area of high fire probability ( [[#Fonseca--2019|Fonseca et al., 2019]] ), double the burned area by 2050 ( [[#Brando--2020|Brando et al., 2020]] ), increase the burned area by 400–2800% by 2100 ( [[#Le%20Page--2017|Le Page et al., 2017]] ) and increase fire intensity by 90% ( [[#De%20Faria--2017|De Faria et al., 2017]] ). Lower GHG emissions (RCP4.5) and reduced deforestation could reduce the risk of fires to a one-fifth increase in the area of high fire probability ( [[#Fonseca--2019|Fonseca et al., 2019]] ) and a 100–500% increase in burned area by 2100 ( [[#Le%20Page--2017|Le Page et al., 2017]] ). Moreover, increased fire, deforestation and drought, acting via vegetation–atmosphere feedbacks, increase the risk of extensive forest dieback and potential biome shifts of up to half of the Amazon rainforest to grassland, a tipping point that could release an amount of carbon that would substantially increase global emissions ( [[#Oyama--2003|Oyama and Nobre, 2003]] ; [[#Sampaio--2007|Sampaio et al., 2007]] ; [[#Lenton--2008|Lenton et al., 2008]] ; [[#Nepstad--2008|Nepstad et al., 2008]] ; [[#Malhi--2009|Malhi et al., 2009]] ; [[#Settele--2014|Settele et al., 2014]] ; [[#Lyra--2016|Lyra et al., 2016]] ; [[#Zemp--2017a|Zemp et al., 2017a]] ; [[#Zemp--2017b|Zemp et al., 2017b]] ; [[#Brando--2020|Brando et al., 2020]] ). Continued climate change, combined with deforestation, increases risks of wildfire and extensive forest dieback in the Amazon rainforest ( ''robust evidence'' , ''high agreement'' ).

In Australia, climate change under RCP8.5 increases the risk of pyro-convective fire by 20–40 days in rangelands of Western Australia, South Australia and the Northern Territory ( [[#Dowdy--2019|Dowdy et al., 2019]] ). Pyro-convective fire conditions could reach more frequently into the more populated areas of New South Wales, particularly at the start of the austral summer ( [[#Di%20Virgilio--2019|Di Virgilio et al., 2019]] ). GCMs do not agree, however, on the areas of projected fire increase in New South Wales ( [[#Clarke--2019|Clarke and Evans, 2019]] ). Increases in heat and potential increases in wildfire threaten the existence of temperature montane rainforest in Tasmania, Australia ( [[#Mariani--2019|Mariani et al., 2019]] ).

In Mediterranean Europe, climate change of 3°C of warming could double or triple the burned area whereas keeping the temperature increase to 1.5°C could limit the increase in burned area to 40–50% ( [[#Turco--2018|Turco et al., 2018]] ). Under RCP8.5, the frequency of heat-induced fire weather could increase by 30% ( [[#Ruffault--2020|Ruffault et al., 2020]] ). Severe fire followed by drought could cause biome shifts of forest to non-forest ( [[#Batllori--2019|Batllori et al., 2019]] ) and tree mortality &gt;50% ( [[#Dupire--2019|Dupire et al., 2019]] ).

In the Arctic tundra, boreal forests and northern peatlands, including permafrost areas, climate change under the scenario of a 4°C temperature increase could triple the burned area in Canada ( [[#Boulanger--2014|Boulanger et al., 2014]] ), double the number of fires in Finland ( [[#Lehtonen--2016|Lehtonen et al., 2016]] ), increase the lightning-driven burned area by 30–250% ( [[#Veraverbeke--2017|Veraverbeke et al., 2017]] ; [[#Chen--2021a|Chen et al., 2021a]] ), push half of the area of tundra and boreal forest in Alaska above the burning threshold temperature and double the burned area in Alaska ( [[#Young--2017a|Young et al., 2017a]] ). Thawing of Arctic permafrost due to a projected temperature of 4°C and the resultant wildfires could release 11–200 GtC which could substantially exacerbate climate change ( [[#2.5.2.9|Section 2.5.2.9]] ).

In the USA, climate change under RCP8.5 could increase the burned area by 60–80% by 2049 ( [[#Buotte--2019|Buotte et al., 2019]] ) and the number of fires with an area &gt;50 km 2 by 300–400% by 2070 ( [[#Barbero--2015|Barbero et al., 2015]] ). In montane forests, climate change under RCP8.5 increases the risk of fire-facilitated conversion of ~7% of forest to non-forest by 2050 ( [[#Parks--2019|Parks et al., 2019]] ). In California, climate change under a scenario of a 4°C temperature increase could double fire frequency in some areas ( [[#Mann--2016|Mann et al., 2016]] ), but emission reductions that limit the temperature increase to ~2°C could keep this from increasing ( [[#Westerling--2011|Westerling et al., 2011]] ). Carbon dioxide fertilisation and increased temperature under climate change could increase invasive grasses and wildfire in desert ecosystems of the southwestern USA where wildfire has historically been absent or infrequent, and increase the mortality of the sparse tree cover (Horn and St. Clair, 2017; [[#Klinger--2017|Klinger and Brooks, 2017]] ; [[#Syphard--2017|Syphard et al., 2017]] ; [[#Moloney--2019|Moloney et al., 2019]] ; [[#Sweet--2019|Sweet et al., 2019]] ).

In summary, under a high-emission scenario that increases global temperature 4°C by 2100, climate change could increase the global burned area by 50–70% and the global mean fire frequency by ~30%, with increases on one- to two-thirds and decreases on one-fifth of global land ( ''medium confidence'' ). Lower emissions that would limit the global temperature increase to &lt;2°C would reduce projected increases of burned area to ~35% and projected increases of fire frequency to ~20% ( ''medium confidence'' ). Increased wildfire, combined with erosion due to deforestation, could degrade water supplies ( ''high confidence'' ). For ecosystems with an historically low fire frequency, a projected 4°C rise in global temperature increases risks of fire, contributing to potential tree mortality and conversion of over half the Amazon rainforest to grassland and thawing of the Arctic permafrost that could release 11–200 GtC that could substantially exacerbate climate change ( ''medium confidence'' ).

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==== 2.5.3.3 Risks to Ecosystems and Services from Tree Mortality ====

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Under continued climate change, increased temperature, aridity, drought, wildfire ( [[#2.5.3.2|Section 2.5.3.2]] ) and insect infestations ( [[#2.4.4.3.3|Section 2.4.4.3.3]] ) will tend to increase tree mortality across many parts of the world ( [[#McDowell--2020|McDowell et al., 2020]] ). Loss of boreal and temperate forest to fire, wind and bark beetles could cause more negative than positive effects for most ecosystem services, including carbon storage to regulate climate change (Sections 2.4.4.3, 2.5.2.6, 2.5.2.7, 2.5.3.4), water supply for people ( [[#2.5.3.6.1|Section 2.5.3.6.1]] ), timber production and other forest products (Chapter 5) and protection from hazards ( [[#Thom--2016|Thom and Seidl, 2016]] ). In addition, deforestation in tropical and temperate forests can increase local temperatures by 0.3°C–2°C ( [[#Hesslerová--2018|Hesslerová et al., 2018]] ; [[#Lejeune--2018|Lejeune et al., 2018]] ; [[#Zeppetello--2020|Zeppetello et al., 2020]] ) and this effect can extend up to 50 km ( [[#Cohn--2019|Cohn et al., 2019]] ).

In Amazon rainforests, the relatively lower buffering capacity for plant moisture during drought increases the risk of tree mortality and, combined with increased heat from climate change and fire from deforestation, the possibility of a tipping point of extensive forest dieback and a biome shift to grassland ( [[#Oyama--2003|Oyama and Nobre, 2003]] ; [[#Sampaio--2007|Sampaio et al., 2007]] ; [[#Lenton--2008|Lenton et al., 2008]] ; [[#Nepstad--2008|Nepstad et al., 2008]] ; [[#Malhi--2009|Malhi et al., 2009]] ; [[#Salazar--2010|Salazar and Nobre, 2010]] ; [[#Settele--2014|Settele et al., 2014]] ; [[#Lyra--2016|Lyra et al., 2016]] ; [[#Zemp--2017b|Zemp et al., 2017b]] ; [[#Brando--2020|Brando et al., 2020]] ). This could occur at a 4°C–5°C temperature increase above that of the pre-industrial period ( [[#Salazar--2010|Salazar and Nobre, 2010]] ). Under RCP8.5, half the Amazon tropical evergreen forest could turn into grassland through drought-induced tree mortality and wildfire, but lower emissions (RCP4.5) could limit this loss to ~5% ( [[#Lyra--2016|Lyra et al., 2016]] ). The decline in precipitation due to reduced evapotranspiration inputs after forest loss could cause additional Amazon forest loss of one-quarter to one-third ( [[#Zemp--2017a|Zemp et al., 2017a]] ). Similarly, in Guinean tropical deciduous forest in Africa, climate change under RCP8.5 could increase mortality 700% by 2100 or 400% under lower emissions (RCP4.5; ( [[#Claeys--2019|Claeys et al., 2019]] ). These projections indicate risks of climate change-induced tree mortality reducing tropical forest areas in Africa and South America by up to half under a 4°C increase above the pre-industrial period, but a lower projection of a 2°C increase could limit the projected increases in tree mortality ( ''robust evidence'' , ''high agreement'' ).

Temperate and boreal forests possess greater diversity of physiological traits related to plant hydraulics, so they are more buffered against drought than tropical forests ( [[#Anderegg--2018|Anderegg et al., 2018]] ). Nevertheless, in temperate forests, drought-induced tree mortality under RCP8.5 could cause the loss of half the Northern Hemisphere conifer forest area by 2100 ( [[#McDowell--2016|McDowell et al., 2016]] ). In the western USA, under RCP8.5, one-tenth of forest area is highly vulnerable to drought-induced mortality by 2050 ( [[#Buotte--2019|Buotte et al., 2019]] ). In California, increased evapotranspiration in Sierra Nevada conifer forests increases the potential fraction of the area at risk of tree mortality by 15–20% per degree Celsius ( [[#Goulden--2019|Goulden and Bales, 2019]] ). In Alaska, fire-induced tree mortality from climate change under RCP8.5 could reduce the extent of spruce forest ( ''Picea'' sp.) by 8–44% by 2100 ( [[#Pastick--2017|Pastick et al., 2017]] ). Under RCP8.5, tree mortality from drought, wildfire and bark beetles could reduce the timber productivity of boreal forests in Canada by 2100 below the current levels ( [[#Boucher--2018|Boucher et al., 2018]] ; [[#Chaste--2019|Chaste et al., 2019]] ; [[#Brecka--2020|Brecka et al., 2020]] ). In Tasmania, projected increases in wildfire ( [[#Fox-Hughes--2014|Fox-Hughes et al., 2014]] ) increase the risk of mortality of mesic vegetation ( [[#Harris--2018b|Harris et al., 2018b]] ) and threaten the disappearance of the long-lived endemic pencil pine ( ''Athrotaxis cupressoides'' ) ( [[#Holz--2015|Holz et al., 2015]] ; [[#Worth--2016|Worth et al., 2016]] ) and temperate montane rainforest ( [[#Mariani--2019|Mariani et al., 2019]] ). These projections indicate risks of climate change-induced tree mortality reducing some temperate forest areas by half under emissions scenarios of 2.5°C–4°C above the pre-industrial period ( ''medium evidence'' , ''high agreement'' ).

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==== 2.5.3.4 Risk to Terrestrial-Ecosystem Carbon Stocks ====

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Globally, increasing atmospheric CO 2 enhances the terrestrial sink but temperature increases constrain it, reflecting the biological process understanding highlighted in previous IPCC reports ( ''high confidence'' ). Analyses of atmospheric inversion model output and spatial climate data indicate a sensitivity of net ecosystem productivity to CO 2 fertilisation of 3.1 ± 0.1 Gt to 8.1 ± 0.3 Gt per 100 ppm CO 2 (~1°C increase) and a sensitivity to temperature of -0.5 ± 0.2 Gt to -1.1 ± 0.1 Gt per degree Celsius ( [[#Fernandez-Martinez--2019|Fernandez-Martinez et al., 2019]] ). The future of the global land carbon sink ( [[#2.4.4.4|Section 2.4.4.4]] ) nevertheless remains highly uncertain because (i) of regionally complex interactions of climate change and changes in atmospheric CO 2 with vegetation, soil and aquatic processes, (ii) episodic events such as heat waves or droughts (and related impacts through mortality, wildfire or insects, pests and diseases) ( [[#2.5.3.2|Section 2.5.3.2]] , 2.5.3.3) are so far only incompletely captured in carbon cycle models, (iii) the legacy effects from historic LUC and environmental changes are incompletely captured but likely to decline in future and (iv) lateral carbon transport processes such as the export of inland waters and erosion are incompletely understood and modelled ( [[#Pugh--2019a|Pugh et al., 2019a]] ; [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ; [[#Krause--2020|Krause et al., 2020]] ; [[#Canadell--2021|Canadell et al., 2021]] ).

Enhanced carbon losses from terrestrial systems further limit the available carbon budget for global warming staying below 1.5°C ( [[#Rogelj--2018|Rogelj et al., 2018]] ). Analyses of satellite remote sensing and ground-based observations have indicated that, between 1982 and 2015, the CO 2 fertilisation effect has already declined, implying a negative climate system feedback ( [[#Wang--2020c|Wang et al., 2020c]] ). Peatlands, permafrost regions and tropical ecosystems are particularly vulnerable due to their large carbon stocks, in combination with over-proportional warming, increases in heat waves and droughts and/or a complex interplay of climate change and increasing atmospheric CO 2 (Sections 2.5.2.8, 2.5.2.9, 2.5.3.2).

Model projections suggest a reduction of permafrost extent and potentially large carbon losses for all warming scenarios ( [[#Canadell--2021|Canadell et al., 2021]] ). Already a mean temperature increase of 2°C could reduce the total permafrost area extent by about 5–20% by 2100 ( [[#Comyn-Platt--2018|Comyn-Platt et al., 2018]] ; [[#Yokohata--2020|Yokohata et al., 2020]] ). Associated CO 2 losses in the order of 15 Gt up to nearly 70 Gt by 2100 have been projected across a number of modelling studies ( [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ; [[#Comyn-Platt--2018|Comyn-Platt et al., 2018]] ; [[#Yokohata--2020|Yokohata et al., 2020]] ). Limiting the global temperature increase to 1.5°C versus 2°C could reduce projected permafrost CO 2 losses by 2100 by 24.2 Gt (median, calculated for a 3-m depth) ( [[#Comyn-Platt--2018|Comyn-Platt et al., 2018]] ). Losses are possibly underestimated in the studies that consider only the upper permafrost layers. Likewise, the actual committed carbon loss may well be larger (e.g., eventually a loss of approx. 40% of today’s permafrost area extent if climate is stabilised at 2°C above pre-industrial levels) due to the long time scale of warming in deep permafrost layers ( [[#Chadburn--2017|Chadburn et al., 2017]] ). It is not known at which level of global warming an abrupt permafrost collapse (estimated to enhance CO 2 emissions by 40% in 2300 in a high-emissions scenario) compared to gradual thaw ( [[#Turetsky--2020|Turetsky et al., 2020]] ) would have to be considered an important additional risk. Large uncertainties arise also from interactions with changes in surface hydrology and/or northward migrating woody vegetation as climate warms, which could dampen or even reverse projected net carbon losses in some regions ( [[#McGuire--2018a|McGuire et al., 2018a]] ; [[#Mekonnen--2018|Mekonnen et al., 2018]] ; [[#Pugh--2018|Pugh et al., 2018]] ). Overall, there is ''low confidence'' on how carbon–permafrost interactions will affect future carbon cycle and climate, although net carbon losses and thus positive (amplifying) feedbacks are ''likely'' (Sections 2.5.2.10, 2.5.3.5) ( [[#Shukla--2019|Shukla et al., 2019]] ). See also WGI AR6 ( [[#Canadell--2021|Canadell et al., 2021]] ) for a discussion on impacts of higher-emission and warming scenarios.

Peatland carbon is estimated as about 550–1000 Gt in northern latitudes (many of these peatlands would be found in permafrost regions) ( [[#Turetsky--2015|Turetsky et al., 2015]] ; [[#Nichols--2019|Nichols and Peteet, 2019]] ) and &gt;100 Gt in tropical regions ( [[#Turetsky--2015|Turetsky et al., 2015]] ; [[#Dargie--2017|Dargie et al., 2017]] ). For both northern mid- and high-latitude and tropical peatlands, a shift from contemporary CO 2 sinks to sources were simulated in high-warming scenarios ( [[#Wang--2018a|Wang et al., 2018a]] ; [[#Qiu--2020|Qiu et al., 2020]] ). Due to the lack of large-scale modelling studies, there is ''low confidence'' for climate change impacts on peat carbon uptake and emissions. The largest risk to tropical peatlands is expected to arise from drainage and conversion to forestry or agriculture, which would outpace the impacts of climate change ( [[#Page--2016|Page and Baird, 2016]] ; [[#Leifeld--2019|Leifeld et al., 2019]] ; [[#Cooper--2020|Cooper et al., 2020]] ). The magnitude of possible carbon losses is uncertain, however, and depends strongly on socioeconomic scenarios (Sections 2.4.3.8, 2.4.4.2; 2.4.4.4.2, 2.5.2.8).

For tropical and subtropical regions, the interplay of atmospheric CO 2 with precipitation and temperature becomes of particular importance for future carbon uptake, since in warm and dry environments, elevated CO 2 fosters plants with C3 photosynthesis and enhances their water-use efficiency relative to C4 species ( [[#Moncrieff--2014a|Moncrieff et al., 2014a]] ; [[#Midgley--2015|Midgley and Bond, 2015]] ; [[#Knorr--2016a|Knorr et al., 2016a]] ). As a consequence, enhanced woody cover is expected to occur in the future, especially in mesic savannas, while in xeric savannas an increase in woody cover would occur in regions with enhanced precipitation ( [[#Criado--2020|Criado et al., 2020]] ). Even though semiarid regions have dominated the global trend in land CO 2 uptake in recent decades ( [[#Ahlström--2015|Ahlström et al., 2015]] ), so far, most studies that investigated future climate change impacts on savanna ecosystems have concentrated on changes in the extent of land area affected (2.5.2.5) rather than on carbon cycling, with ''medium confidence'' for increasing woody cover:grass ratios ( [[#Moncrieff--2014a|Moncrieff et al., 2014a]] ; [[#Midgley--2015|Midgley and Bond, 2015]] ; [[#Moncrieff--2016|Moncrieff et al., 2016]] ; [[#Criado--2020|Criado et al., 2020]] ). Increases in woody vegetation in what is now grass-dominated would possibly come with a carbon benefit, for instance, it was found that a broad range of future climate and CO 2 changes would enhance vegetation carbon storage on Australian savannas ( [[#Scheiter--2015|Scheiter et al., 2015]] ). Results from a number of field experiments indicate, however, that impacts on total ecosystem carbon storage may be smaller due to a loss in below-ground carbon ( [[#Coetsee--2013|Coetsee et al., 2013]] ; [[#Wigley--2020|Wigley et al., 2020]] ). [[#Nunez--2021|Nunez et al. (2021)]] critique existing incentives to promote the invasion of non-native trees into treeless areas as a means of carbon sequestration, raising doubts about the effects on fire, albedo, biodiversity and water yield (see Box 2.2).

Substantial climate change-driven impacts on tropical tree cover and vegetation type are projected in all studies, irrespective of whether or not the degree amounts to a forest “dieback” (Sections 2.4.3.6, 2.4.4.3, 2.5.2.6, 2.5.3.3) ( [[#Davies-Barnard--2015|Davies-Barnard et al., 2015]] ; [[#Wu--2016a|Wu et al., 2016a]] ; [[#Zemp--2017a|Zemp et al., 2017a]] ; [[#Canadell--2021|Canadell et al., 2021]] ) . Accordingly, models also suggest a continuation of tropical forests acting as carbon sinks ( [[#Huntingford--2013|Huntingford et al., 2013]] ; [[#Mercado--2018|Mercado et al., 2018]] ). A recent study combining field plot data with statistical models ( [[#Hubau--2020|Hubau et al., 2020]] ) indicates that, in the Amazonian and possibly also in the African forest, the carbon sink in above-ground biomass already declined in the three decades up to 2015. This trend is distinct in the Amazon whereas data from Africa suggests a possible decline after 2010. The authors estimate the vegetation carbon sink in 2030–2040 to decline to zero±0.205 PgC yr -1 in the Amazon and to 0.26±0.215 PgC yr -1 in Africa (a loss of 14% compared to the present). Their results suggest that, over time, CO 2 fertilisation is outweighed by the impacts of higher temperatures and drought that enhance tree mortality and diminish growth. The degree of thermal resilience of tropical forests is still uncertain, however ( [[#Sullivan--2020|Sullivan et al., 2020]] ).

The lack of simulation studies that seek to quantify all important interacting factors (CO 2 , drought and fire) for future carbon cycling in savannas and tropical forests and the apparent disagreement between trends projected in models compared to data-driven estimates result in ''low confidence'' regarding the direction or magnitude of carbon flux and pool-size changes. Similar to tropical peatlands, given projected human population growth and socioeconomic changes, the continued conversion of forests and savannas into agricultural or pasture systems ''very likely'' poses a significant risk of rapid carbon loss which will amplify the climate change-induced risks substantially ( ''high confidence'' ) (2.5.2.10, 2.5.3.5) ( [[#Aragao--2014|Aragao et al., 2014]] ; [[#Searchinger--2015|Searchinger et al., 2015]] ; [[#Aleman--2016|Aleman et al., 2016]] ; [[#Nobre--2016|Nobre et al., 2016]] ).

The impacts of climate-induced altered animal composition and trophic cascades on land-ecosystem carbon cycling globally are as yet unquantified ( [[#Schmitz--2018|Schmitz et al., 2018]] ), even though climate change is expected to lead to shifts in consumer–resource interactions that also contribute to losses of top predators or top herbivores (Sections 2.4.2.2, 2.5.1.3, 2.5.4; ( [[#Lurgi--2012|Lurgi et al., 2012]] ; [[#Damien--2019|Damien and Tougeron, 2019]] ). Cascading trophic effects triggered by top predators or the largest herbivores propagate through food webs and reverberate through to the functioning of whole ecosystems, notably altering productivity, carbon and nutrient turnover and net carbon storage ( ''medium confidence'' ) ( [[#Wilmers--2016|Wilmers and Schmitz, 2016]] ; [[#Sobral--2017|Sobral et al., 2017]] ; [[#Stoner--2018|Stoner et al., 2018]] ). Across different field experiments, the ecosystem consequences of the presence or absence of herbivores and carnivores have been found to be quantitatively as large as the effects of other environmental change drivers such as warming, enhanced CO 2 , fire and variable nitrogen deposition ( ''medium confidence'' ) ( [[#Hooper--2012|Hooper et al., 2012]] ; [[#Smith--2015|Smith et al., 2015]] ). Some local and regional modelling experiments have begun to explore animal impacts on vegetation dynamics and carbon and nutrient cycling ( [[#Pachzelt--2015|Pachzelt et al., 2015]] ; [[#Dangal--2017|Dangal et al., 2017]] ; [[#Berzaghi--2019|Berzaghi et al., 2019]] ). Turnover rate is the chief factor that determines future land-ecosystem carbon dynamics and hence carbon–climate feedbacks ( [[#Friend--2014|Friend et al., 2014]] ). To improve projections, it is imperative to better quantify the broader role of carnivores, grazers and browsers and the way these interact in global studies of how ecosystems respond to climate change.

<div id="2.5.3.5" class="h3-container"></div>

<span id="feedbacks-between-ecosystems-and-climate"></span>
==== 2.5.3.5 Feedbacks between Ecosystems and Climate ====

<div id="h3-47-siblings" class="h3-siblings"></div>

The possibility of feedbacks and interactions between climate drivers and biological systems or ecological processes was identified as a significant emerging issue in AR5, and has since also been highlighted in the SRCCL and the SR1.5. It is virtually certain that land cover changes affect regional and global climate through changes to albedo, evapotranspiration and roughness ( ''very high confidence'' ) ( [[#Perugini--2017|Perugini et al., 2017]] ). There is growing evidence that biosphere-related climate processes are being affected by climate change in combination with disturbance and LULCC ( ''high confidence'' ) ( [[#Jia--2019|Jia et al., 2019]] ). It is virtually certain that land surface change caused by disturbances such as forest fires, hurricanes, phenological changes, insect outbreaks and deforestation affect carbon, water and energy exchanges, thereby influencing weather and climate ( ''very high confidence'' ) (Table 2.4; Figure 2.10) ( [[#Bright--2013|Bright et al., 2013]] ; [[#Brovkin--2013|Brovkin et al., 2013]] ; [[#Naudts--2016|Naudts et al., 2016]] ; [[#Prăvălie--2018|Prăvălie, 2018]] ).

<div id="_idContainer050" class="Figure"></div>

[[File:d856dff730369fa63df2c84157b62ea0 IPCC_AR6_WGII_Figure_2_010.png]]

'''Figure 2.10 | Terrestrial ecosystem feedbacks, which affect the Earth’s climate system dynamics.''' Perturbations and implications for climate system dynamics (warming/cooling) are shown for the three global forest biomes (adapted from Figure 5 in ( [[#Prăvălie--2018|Prăvălie, 2018]] ). The strength of the mechanism is estimated in general terms, based on the magnitude of carbon storage and evaporative cooling processes that characterise each forest biome ( [[#Bonan--2008|Bonan, 2008]] ). Carbon storage includes forest biomass, without accounting for carbon dynamics in soil, peat and underlying permafrost deposits. Implications of bio-geochemical shifts were only estimated in relation to the intensification of the carbon cycle and increase in biomass at high latitudes, assuming nitrogen availability for the stoichiometric demands of forest vegetation.

Feedbacks can be positive or negative (i.e., amplify or dampen the original forcing), vary spatially and seasonally, and act over large geographic areas and long time periods (more than decades), making them difficult to observe and quantify directly ( [[#Schimel--2015|Schimel et al., 2015]] ; [[#Canadell--2021|Canadell et al., 2021]] ). Due to the positive impacts of CO 2 on vegetation growth and ecosystem carbon storage ( ''high confidenc'' e) (Sections 2.4.4.4, 2.5.5.4) ( [[#Canadell--2021|Canadell et al., 2021]] ), the associated climate feedback is negative (i.e., increased removal of atmospheric CO 2 and dampened warming, compared to an absence of the feedback). By contrast, projected global losses of carbon in warmer climates ( [[#Canadell--2021|Canadell et al., 2021]] ) imply a positive climate feedback. WGI ( [[#Canadell--2021|Canadell et al., 2021]] ) assesses an overall increase in land carbon uptake through the 21st century. However, the overall strength of the carbon cycle–climate feedback remains very uncertain. One of the underlying reasons may be complex interactions with ecosystem water balance and nitrogen and phosphorous availability, which are poorly constrained by observational evidence and incompletely captured in ESMs ( [[#2.5.2.10|Section 2.5.2.10]] ) ( [[#Huntzinger--2017|Huntzinger et al., 2017]] ; [[#Canadell--2021|Canadell et al., 2021]] ).

Land ecosystems contribute substantially to global emissions of nitrous oxide and methane . As with CO 2 , these emissions respond both directly and indirectly to atmospheric CO 2 concentration and climate change, and this gives rise to potential additional bio-geochemical feedbacks in the climate system. A large part of these emissions stem from land and water management, such as fertilizer application, rice production, aquaculture or animal husbandry ( [[#Jia--2019|Jia et al., 2019]] ). However, nearly 60% of total nitrous oxide emissions (in 2007–2016) has been estimated to stem from natural ecosystems, especially in the Tropics ( [[#Tian--2019|Tian et al., 2019]] ; [[#Canadell--2021|Canadell et al., 2021]] ), while freshwater wetlands and peatlands are estimated to contribute between 83% (top-down estimates) and 40% (bottom-up estimates) of total natural CH 4 (and 31 and 20% of total methane emissions, respectively) for the period 2008–2017 ( [[#Canadell--2021|Canadell et al., 2021]] ). Median CH 4 emissions from northern-latitude wetlands in 2100 were estimated to be 12.1 and 13.5 PgC in emission scenarios leading to 1.5°C and 2°C warming, respectively ( [[#Comyn-Platt--2018|Comyn-Platt et al., 2018]] ). Likewise, global warming has been attributed to soil N 2 O emission increases since the pre-industrial period of 0.8 (0.3–1.3) TgN yr -1 ( [[#Tian--2020|Tian et al., 2020]] ). Overall, climate feedbacks from future altered land ecosystem emissions of CH 4 or N 2 O are uncertain, but are expected to be small ( [[#Canadell--2021|Canadell et al., 2021]] ).

Changes in regional biodiversity are integral parts of ecosystem–climate feedback loops, including and beyond carbon cycle processes (Figure 2.10; Table 2.4). For instance, the impacts of climate-induced altered animal composition and trophic cascades on ecosystem carbon turnover (see Sections 2.4.4.4, 2.5.3.4) could be a substantive contribution to carbon–climate feedbacks ( ''low confidence'' ). Additional surface–atmosphere feedbacks that arise from changes in vegetation cover and subsequently altered albedo, evapotranspiration or roughness (often summarised as biophysical feedbacks) can be regionally relevant and could amplify or dampen vegetation cover changes ( [[#Jia--2019|Jia et al., 2019]] ).

Climate-induced shifts towards forests in what is currently tundra would be expected to reduce regional albedo especially in spring, but also during parts of winter when trees are snow-free (whereas tundra vegetation would be covered in snow), which amplifies warming regionally ( ''high confidence'' ) ( [[#Perugini--2017|Perugini et al., 2017]] ; [[#Jia--2019|Jia et al., 2019]] ). Trees would also enhance momentum absorption compared to low tundra vegetation, thus impacting surface–atmosphere mixing of latent and sensible heat fluxes ( [[#Jia--2019|Jia et al., 2019]] ). Boreal forests insulate and stabilize permafrost and reduce fluctuations of ground temperature: the amplitude of variation of ground surface temperatures was 28°C at a forested site, compared to 60°C in nearby grassland ( [[#2.5.2.7|Section 2.5.2.7]] ) ( [[#Bonan--1989|Bonan, 1989]] ; [[#Stuenzi--2021a|Stuenzi et al., 2021a]] ; [[#Stuenzi--2021b|Stuenzi et al., 2021b]] ). Likewise, a shift in moist tropical forests towards vegetation with drought-tolerant traits could possibly reduce evapotranspiration, increase albedo, alter heat transfer at the surface and lead to a negative feedback to precipitation ( [[#2.5.2.6|Section 2.5.2.6]] ) ( [[#Jia--2019|Jia et al., 2019]] ). In savannas, restoration of woody vegetation has been shown to enhance cloud formation and precipitation in response to enhanced transpiration and turbulent mixing, leading to a positive feedback on woody cover ( [[#Syktus--2016|Syktus and McAlpine, 2016]] ). While this has not yet been systematically explored, similar feedbacks might also emerge from a CO 2 -induced woody cover increase in savannas ( ''low confidence'' ) ( [[#2.5.2.5|Section 2.5.2.5]] ).

Since biophysical feedbacks can contribute to both surface temperature warming or cooling, analyses so far suggest that, on a global scale, the net impact on climate change is small ( [[#Perugini--2017|Perugini et al., 2017]] ; [[#Jia--2019|Jia et al., 2019]] ), unless these feedbacks also accelerate vegetation mortality and lead to substantive carbon losses ( [[#Zemp--2017a|Zemp et al., 2017a]] ; [[#Lemordant--2019|Lemordant and Gentine, 2019]] ). More than one-third of the Earth’s land surface has at least 50% of its evapotranspiration regulated by vegetation, and in some regions between 40 and &gt;80% of the land’s evaporated water is returned to land as precipitation. Locally, both directly human-mediated and climate change-mediated changes in vegetation cover can therefore notably affect annual average freshwater availability to human societies, especially if negative feedbacks amplify the reduction of vegetation cover, evapotranspiration and precipitation ( ''medium confidence'' ) ( [[#Keys--2016|Keys et al., 2016]] ; [[#Keys--2018|Keys and Wang-Erlandsson, 2018]] ).

Since AR5, freshwater ecosystems (lakes, reservoirs, rivers and ponds) have been increasingly recognised as important sources of GHG emissions (CO 2 , CH 4 and N 2 O) into the atmosphere. Key mechanisms which contribute to rising GHG emissions from freshwater ecosystems are the temperature imbalance between photosynthesis and respiration (respiration increases more than photosynthesis with rising temperature), CO 2 and CH 4 emissions from exposed sediments during droughts, increased transport of matter from land to water, changes in water retention time in rivers and lakes and the effects of temperature on lake stratification and anoxia that favour CH 4 emissions.

DelSontro et al. (2018) assembled the largest global data set to date on emission rates from lakes of CO 2 , CH 4 and N 2 O and found that they co-vary with lake size and trophic state. They estimated that moderate global increases in eutrophication of lakes could translate to 5–40% increases in the GHG effect in the atmosphere. Moreover, they estimated that GHG emissions from lakes and impoundments in past decades accounted for 1.25–2.30 PgCO 2 yr -1 ( [[#DelSontro--2018|DelSontro et al., 2018]] ), thus around 20% of global CO 2 emissions from the burning of fossil fuels (9.4 PgCO 2 yr -1 ) ( [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ).

Global warming will strongly enhance freshwater CH 4 emissions through a disproportionate increase in ebullition (gas flux) by 6–20% per 1°C increase in water temperature ( [[#Aben--2017|Aben et al., 2017]] ). It can be expected that ongoing eutrophication enhanced by climate change-related increases in the release of sediment nutrients and the loading of organic carbon and nutrients from catchments will enhance CH 4 ebullition on a global scale ( [[#Aben--2017|Aben et al., 2017]] ; [[#DelSontro--2018|DelSontro et al., 2018]] ; [[#Bartosiewicz--2019|Bartosiewicz et al., 2019]] ; [[#Beaulieu--2019|Beaulieu et al., 2019]] ; [[#Sanches--2019|Sanches et al., 2019]] ). The strongest increase in ebullition is expected in shallow waters where sediment temperatures are strongly related to atmospheric temperature ( [[#Aben--2017|Aben et al., 2017]] ). Given that small ponds and shallow lakes are the most abundant freshwater ecosystems globally, these may become hot spots of CH 4 ebullition in the future ( [[#Aben--2017|Aben et al., 2017]] ). On average, CH 4 , CO 2 and N 2 O account for 75, 23 and 2% of the total CO 2 -equivalent emissions, respectively, in lakes ( [[#DelSontro--2018|DelSontro et al., 2018]] ).

Furthermore, the exposure of lake and river sediments during droughts activates the decomposition of buried organic carbon. In dry river beds, mineralisation of buried organic matter is likely to increase with climate change as anoxic sediments are oxygenated downwards during drying, along with pulses of microbial activity following re-wetting of desiccated sediment. Conservative estimates indicate that adding emissions from exposed sediments of dry inland waters across diverse ecosystem types and climate zones to current global estimates of CO 2 emissions could result in a 6% (~0.12 PgC yr −1 ) increase of total inland water CO 2 emission rates covering streams and rivers (334 mmol m -2 day -1 ), lakes and reservoirs (320 mmol m -2 day -1 ) and small ponds (148 mmol m -2 day -1 ) ( [[#Marcé--2019|Marcé et al., 2019]] ; [[#Keller--2020|Keller et al., 2020]] ).

Overall, uncertainty as to the quantity of carbon fluxes within freshwater ecosystems and between terrestrial and freshwater systems, and subsequent emissions to the atmosphere remains very ''high'' ( [[#Raymond--2013|Raymond et al., 2013]] ; [[#Catalán--2016|Catalán et al., 2016]] ; [[#Stanley--2016|Stanley et al., 2016]] ; [[#Evans--2017|Evans et al., 2017]] ; [[#Drake--2018|Drake et al., 2018]] ; [[#Seekell--2018|Seekell et al., 2018]] ; [[#Sanches--2019|Sanches et al., 2019]] ; [[#Bodmer--2020|Bodmer et al., 2020]] ; [[#Keller--2020|Keller et al., 2020]] ; [[#Canadell--2021|Canadell et al., 2021]] ) (see Table SM2.1.). Projections of carbon fluxes are, for example, challenged by the complex interaction between rising water temperatures, loss of ice, changes in hydrology, ecosystem productivity, increased extreme events and variation in terrestrial-matter transport. While we are still short of empirical data, particularly in the Tropics ( [[#DelSontro--2018|DelSontro et al., 2018]] ), improvements in sensor technology ( [[#Eugster--2011|Eugster et al., 2011]] ; [[#Gonzalez-Valencia--2014|Gonzalez-Valencia et al., 2014]] ; [[#Maeck--2014|Maeck et al., 2014]] ; [[#Delwiche--2015|Delwiche et al., 2015]] ) and the use of statistically robust survey designs ( [[#Beaulieu--2016|Beaulieu et al., 2016]] ; [[#Wik--2016|Wik et al., 2016]] ) have improved the accuracy of measurements of GHG emissions in freshwater ecosystems. Global networks such as the Global Lakes Ecological Observatory Network (GLEON) increasingly allow a global view of carbon fluxes, thereby improving estimates of the contribution of freshwater ecosystems to global GHG emissions to the atmosphere.

In summary for freshwater systems, Drake et al. (2018) aggregated contemporary estimates of CO 2 and CH 4 emissions from freshwater ecosystems with global estimates made by [[#Raymond--2013|Raymond et al. (2013)]] , and arrived at an estimate of 3.9 PgC yr -1 . Rivers and streams accounted for 85% and lakes and reservoirs for 15% of the emissions ( [[#Raymond--2013|Raymond et al., 2013]] ). This trend will continue under scenarios of nutrient loading to inland waters over the next century where increased CH 4 emission of inland water has an atmospheric impact of 1.7–2.6 PgC/CO 2 -eq y −1 , which is equivalent to 18–33% of annual CO 2 emissions from burning fossil fuels ( ''medium evidence'' , ''medium agreement'' ) ( [[#Beaulieu--2019|Beaulieu et al., 2019]] ). For comparison, annual uptake of CO 2 in land ecosystems is estimated as 3.4 (± 0.9) PgC yr −1 ( [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ). The freshwater numbers combine CO 2 and CH 4 and are thus not directly comparable. However, they are indicative of the importance of better accounting for freshwater systems in global carbon budgets.

'''Table 2.4 |''' Terrestrial and freshwater ecosystem feedbacks which affect the Earth’s climate system dynamics, according to ( [[#Prăvălie--2018|Prăvălie, 2018]] ).

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

! '''Implications for warming/feedback mechanism'''

'''The Earth’s climate system dynamics'''

|-
| ''Phenological changes''

(sections 2.4.2.4, 2.4.2.5)

| Increased primary productivity and plant growth with CO 2 fertilisation ( [[#Mao--2016|Mao et al., 2016]] ; [[#Wang--2018a|Wang et al., 2018a]] ); increasing growing season length ( [[#Peñuelas--2009|Peñuelas et al., 2009]] ; [[#Barichivich--2013|Barichivich et al., 2013]] ); reduced diurnal temperature range through evapotranspiration (mid latitudes) and albedo (high latitudes) caused by vegetation greening ( [[#Jeong--2011|Jeong et al., 2011]] ); increased CO 2 storage in biomass (cooling) ( [[#Keenan--2014|Keenan et al., 2014]] ); reduced albedo in snow-covered regions as canopies become taller and darker (warming); increased evapotranspiration, a key component of the global water cycle and energy balance which influences global rainfall, temperature and atmospheric motion ( [[#Zeng--2017|Zeng et al., 2017]] )

|-
| ''Insect outbreaks''

(sections 2.4.4.2

| Reduced carbon uptake and storage (warming); increased surface albedo (cooling) ( [[#Landry--2016|Landry et al., 2016]] ); increased CO 2 emissions (warming); decreased LAI and gross primary productivity ( [[#Ghimire--2015|Ghimire et al., 2015]] ), leading to reduced evapotranspiration and increased land surface temperature ( [[#Bright--2013|Bright et al., 2013]] )

|-
| ''Range shifts''

(sections 2.4.2.1, 2.4.2.2, 2.4.2.3, 2.4.2.5, 2.4.3)

| Reduced albedo in snow-covered regions as trees expand polewards (warming) ( [[#Chae--2015|Chae et al., 2015]] ); enhanced permafrost thawing; expansion of insect outbreak range, increasing forest impact ( [[#Pureswaran--2018|Pureswaran et al., 2018]] ); biome-dependent changes in albedo and evapotranspiration regimes ( [[#Naudts--2016|Naudts et al., 2016]] ); reduction in snow and ice albedo in freshwater due to loss of ice (warming) ( [[#Lang--2018|Lang et al., 2018]] )

|-
| ''Die-off and large-scale mortality events''

(sections 2.4.2.2, 2.4.4.3)

| Decreased GPP; decline in carbon storage (warming); increased CO 2 emissions; increased solar radiation, reduced soil moisture and higher surface runoff; albedo effects ( [[#Lewis--2011|Lewis et al., 2011]] ; [[#Prăvălie--2018|Prăvălie, 2018]] )

|-
| ''Deforestation''

(sections 2.4.3.6, 2.4.3.7)

| Reduced carbon storage (warming) ( [[#Pugh--2019a|Pugh et al., 2019a]] ); increase in (regional) surface air temperature due to reduced evaporation (less cooling); increased albedo in high-latitude systems (regional radiative cooling) ( [[#Loranty--2014|Loranty et al., 2014]] ); increased air temperature and diurnal temperature variation ( [[#Alkama--2016|Alkama and Cescatti, 2016]] ), locally and globally ( [[#Winckler--2019|Winckler et al., 2019]] ); reduced precipitation ( [[#Perugini--2017|Perugini et al., 2017]] ); decreased biogenic volatile organic compounds (BVOC) and aerosol emissions (warming through direct and indirect aerosol effects; cooling associated with reduction in atmospheric methane ( [[#Jia--2019|Jia et al., 2019]] )

|-
| ''Forest degradation''

(sections 2.4.3.6, 2.4.3.7)

| Reduced carbon storage (warming) ( [[#de%20Paula--2015|de Paula et al., 2015]] ; [[#Bustamante--2016|Bustamante et al., 2016]] ; [[#de%20Andrade--2017|de Andrade et al., 2017]] ; [[#Mitchard--2018|Mitchard, 2018]] )

|-
| ''Fragmentation''

| Carbon losses because biomass is less developed at forest edges ( [[#Pütz--2014|Pütz et al., 2014]] ; [[#Chaplin-Kramer--2015|Chaplin-Kramer et al., 2015]] ; [[#Haddad--2015|Haddad et al., 2015]] )

|-
| ''Air pollution''

| Decreased plant productivity, transpiration and carbon sequestration in forests with lower biomass due to ozone toxicity ( [[#Sitch--2007|Sitch et al., 2007]] ; [[#Ainsworth--2012|Ainsworth et al., 2012]] ); increased (regional) productivity due to increase in diffuse solar radiation caused by terrestrial aerosols ( [[#Xie--2021|Xie et al., 2021]] )

|-
| ''Declining populations of megafauna''

| Changes to physical and chemical properties of organic matter, soils and sediments influence carbon uptake and storage ( [[#Schmitz--2018|Schmitz et al., 2018]] ); increased or decreased carbon storage biomass and carbon storage, with differences across biomes determined by floristic structure and animal size ( [[#Bello--2015|Bello et al., 2015]] ; [[#Osuri--2016|Osuri et al., 2016]] ; [[#Peres--2016|Peres et al., 2016]] ; [[#He--2017|He et al., 2017]] ; [[#Berzaghi--2018|Berzaghi et al., 2018]] ; [[#Schmitz--2018|Schmitz et al., 2018]] ; [[#He--2019|He et al., 2019]] )

|-
| ''Fire''

(sections 2.4.4.2, 2.5.3.2)

| Increased carbon and aerosol emissions ( [[#van%20der%20Werf--2017|van der Werf et al., 2017]] ); surface warming ( [[#Liu--2019b|Liu et al., 2019b]] ); albedo effect dependent on ecosystem and species-level traits ( [[#Rogers--2015|Rogers et al., 2015]] ; [[#Chen--2018a|Chen et al., 2018a]] ) (initial albedo decreases post-fire; increased albedo where snow exposure is increased by canopy removal and species composition changes during recovery); black carbon deposition on snow and sea ice (short-term) ( [[#Randerson--2006|Randerson et al., 2006]] ); indirect increases in carbon emissions due to soil erosion ( [[#Caon--2014|Caon et al., 2014]] )

|-
| ''Changes in forest composition'' (sections 2.4.3.6, 2.4.3.7, 2.5.2.6, 2.5.2.7)

| Reduced carbon storage due to the decline of biomass (warming) ( [[#McIntyre--2015|McIntyre et al., 2015]] )

|-
| ''Woody encroachment in non-forested ecosystems''

(sections 2.4.3.3, 2.4.3.4, 2.4.3.5, 2.5.2.3, 2.5.2.4, 2.5.2.5, Box 2.1)

| Reduced production, increased water use, reduced albedo and altered land–atmosphere feedbacks; increased carbon storage in woody savannas ( [[#Zhou--2017|Zhou et al., 2017]] ; [[#Mureva--2018|Mureva et al., 2018]] ); uncertain feedbacks to the carbon cycle (some suggest an increase, others a decrease)

|-
| ''NPP shifts''

(section 2.4.4.5)

| Reduced albedo following high-latitude expansion of trees caused by photosynthetic enhancement of growth (cooling); increased photosynthesis and net ecosystem production (NEP) ( [[#Fernandez-Martinez--2019|Fernandez-Martinez et al., 2019]] ); increased NPP in nutrient-limited ecosystems due to increased nitrogen deposition from agriculture and combustion ( [[#Du--2018|Du and de Vries, 2018]] ; [[#Schulte-Uebbing--2018|Schulte-Uebbing and de Vries, 2018]] ); nutrient-limited lakes are likely to become less productive, while nutrient-rich lakes are likely to become more productive due to warming-induced prolongation of stable stratification ( [[#Adrian--2016|Adrian et al., 2016]] ; [[#Kraemer--2017|Kraemer et al., 2017]] )

|-
| ''Bio-geochemical shifts''

| Decline in carbon storage due to nitrogen limitation in nutrient-limited systems (warming) ( [[#Reich--2014|Reich et al., 2014]] ; [[#Wieder--2015|Wieder et al., 2015]] ); increased carbon storage on land ( [[#Peñuelas--2013|Peñuelas et al., 2013]] ) and in lakes ( [[#Heathcote--2015|Heathcote et al., 2015]] ; [[#Mendonça--2017|Mendonça et al., 2017]] ); increase in CO 2 and CH 4 emissions from freshwater ecosystems due to increased eutrophication ( [[#DelSontro--2018|DelSontro et al., 2018]] ), the imbalance between losses and gains of CO 2 by photosynthesis and respiration (the metabolic theory of ecology), enhanced emissions from exposed river and lake sediments during droughts and re-wetting ( [[#Marcé--2019|Marcé et al., 2019]] ; [[#Keller--2020|Keller et al., 2020]] ), enhanced CH 4 ebullition of seasonally hypoxic lakes ( [[#Aben--2017|Aben et al., 2017]] ; [[#DelSontro--2018|DelSontro et al., 2018]] ; [[#Bartosiewicz--2019|Bartosiewicz et al., 2019]] ; [[#Beaulieu--2019|Beaulieu et al., 2019]] ; [[#Sanches--2019|Sanches et al., 2019]] ) and increased transfer of organic carbon from land to water (particularly in permafrost areas) ( [[#Wauthy--2018|Wauthy et al., 2018]] )

|}

<div id="2.5.3.6 " class="h3-container"></div>

<span id="risks-to-freshwater-ecosystem-services-drinking-water-fisheries-and-hydropower"></span>
==== 2.5.3.6 Risks to Freshwater Ecosystem Services: Drinking Water, Fisheries and Hydropower ====

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AR5 named water supply and biodiversity as freshwater ecosystem services vulnerable to climate change. We discuss the risks to these and to additional services identified by model projections based both on climate-change scenarios ( [[#Schröter--2005|Schröter et al., 2005]] ; [[#Boithias--2014|Boithias et al., 2014]] ; [[#Huang--2019|Huang et al., 2019]] ; [[#Jorda-Capdevila--2019|Jorda-Capdevila et al., 2019]] ) and on the Common International Classification of Ecosystem Services ( ''high confidence'' ) (CICES, 2018). The effects of floods, droughts, permafrost and glacier-melting on global changes in water quality, particularly with respect to contamination with pollutants, are described in [[IPCC:Wg2:Chapter:Chapter-4#4.2.6|Section 4.2.6]] .

<div id="2.5.3.6.1" class="h4-container"></div>

<span id="risks-to-the-quantity-and-quality-of-drinking-water"></span>
===== 2.5.3.6.1 Risks to the quantity and quality of drinking water =====

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Forests and other vegetated ecosystems assist the production of drinkable water by facilitating the infiltration of rainfall and snowfall into the ground, where water either moves through the saturated soil zone to supply streams and other surface waters or infiltrates further to recharge groundwater aquifers ( [[#Ellison--2012|Ellison et al., 2012]] ; [[#Bonnesoeur--2019|Bonnesoeur et al., 2019]] ). Globally, 4 billion people depend on forested watersheds for drinking water ( [[#Mekonnen--2016|Mekonnen and Hoekstra, 2016]] ). [[IPCC:Wg2:Chapter:Chapter-4|Chapter 4]] assesses the physical science of water supply, including precipitation, runoff and hydrology as well as the social aspects of human water use. This section assesses the ecological aspects of risks to freshwater supplies for people.

Diminished vegetation cover following wildfires ( [[#2.5.3.2|Section 2.5.3.2]] ) and tree mortality ( [[#2.5.3.3|Section 2.5.3.3]] ) can reduce long-term water infiltration, increase soil erosion and flash floods and release sediment that degrades drinking water quality. Widlfires increase impacts of extreme precipitation events due to climate change, which contribute to increased surface runoff and hence increased risks of land erosion, landslides and flooding ( [[#Ebel--2012|Ebel et al., 2012]] ; [[#Robinne--2020|Robinne et al., 2020]] ). Under current conditions, nearly half the global land area is at a moderate-to-high risk of water scarcity due to wildfires ( [[#Robinne--2018|Robinne et al., 2018]] ; [[#Robinne--2020|Robinne et al., 2020]] ). From 1984 to 2014, wildfires in the western USA affected 6–11% of stream and river length ( [[#Ball--2021|Ball et al., 2021]] ). Under a high-emissions scenario of a 3.5°C temperature increase, post-fire erosion across the western USA could double sedimentation and degrade drinking water quality in one-third of watersheds by 2050 ( [[#Sankey--2017|Sankey et al., 2017]] ). In Brazil, post-fire vegetation loss tends to increase runoff, reduce infiltration and reduce groundwater recharge and flow of springs ( [[#Rodrigues--2019|Rodrigues et al., 2019]] ). Runoff from wildfires can contain DOC precursors for the formation of carcinogenic trihalomethanes during chlorination of water for drinking ( [[#Uzun--2020|Uzun et al., 2020]] ) as well as chromium, mercury, selenium and other toxic trace metals ( [[#Burton--2016|Burton et al., 2016]] ; [[#Burton--2019|Burton et al., 2019]] ).

Net effects of deforestation and afforestation on runoff and water supply depend on local factors, leading to conflicting evidence of effects of land cover change ( [[#Ellison--2012|Ellison et al., 2012]] ; [[#Chen--2021b|Chen et al., 2021b]] ), but combinations of climate change and deforestation are projected to reduce water flows ( [[#Olivares--2019|Olivares et al., 2019]] ). In southern Thailand, the combination of the conversion of forest to rubber plantations and a one-third increase in rainfall could increase erosion and sediment load by 15% ( [[#Trisurat--2016|Trisurat et al., 2016]] ). In the watershed that supplies São Paulo, Brazil, afforestation could increase water quantity and quality ( [[#Ferreira--2019|Ferreira et al., 2019]] ). In most regions with dry or Mediterranean subtropical climates, projected climate change can reduce surface water and groundwater resources ( [[#Doell--2015|Doell et al., 2015]] ). In northeast Spain, reduced precipitation and vegetation cover under the high-emissions scenario of a 3.5°C temperature increase could reduce drinking water supplies by half by 2100 ( [[#Bangash--2013|Bangash et al., 2013]] ).

Changes in algal biomass development and the spread of cyanobacteria blooms, related to global warming, resemble those triggered by eutrophication with the well-known negative effects on the services lakes provide, particularly for drinking water provision and recreation ( ''robust evidence'' , ''high agreement'' , ''high confidence'' ) ( [[#Carvalho--2013|Carvalho et al., 2013]] ; [[#Adrian--2016|Adrian et al., 2016]] ; [[#Gozlan--2019|Gozlan et al., 2019]] ).

Based on a 10% increase in precipitation, ( [[#de%20Wit--2016|de Wit et al., 2016]] ) estimated an increased mobilisation of organic carbon from soils to freshwaters of at least 30%, demonstrating the importance of climate wetting for the carbon cycle. Browning negatively affects the taste of drinking water and this may be difficult to address ( [[#Kothawala--2015|Kothawala et al., 2015]] ; [[#Kritzberg--2020|Kritzberg et al., 2020]] ). It also often reduces attractiveness for recreational purposes, especially swimming ( [[#Arthington--2003|Arthington and Hadwen, 2003]] ; [[#Keeler--2015|Keeler et al., 2015]] ). Based on a worst-case climate scenario until 2030, ( [[#Weyhenmeyer--2016|Weyhenmeyer et al., 2016]] ) projected an increase in the browning of lakes and rivers in boreal Sweden by a factor of 1.3. The chemical character of DOM, as modified by climate change ( [[#Kellerman--2014|Kellerman et al., 2014]] ), determines its amenability to removal by water treatment ( [[#Ritson--2014|Ritson et al., 2014]] ). Therefore, in order to provide safe and acceptable drinking water, more advanced, more expensive and more energy/resource-intensive technical solutions may be required ( [[#Matilainen--2010|Matilainen et al., 2010]] ).

In summary, climate change increases risks to the integrity of watersheds and the provision of safe, acceptable freshwater to people ( ''medium evidence'' , ''medium agreement'' ).

<div id="2.5.3.6.2" class="h4-container"></div>

<span id="risks-to-freshwater-fisheries-and-biodiversity"></span>
===== 2.5.3.6.2 Risks to freshwater fisheries and biodiversity =====

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Climate change will increase water temperatures and decrease dissolved oxygen levels ( [[#2.3.1|Section 2.3.1]] ), impacting freshwater fisheries which form an important ecosystem service ( [[#Vári--2022|Vári et al., 2022]] ). People living in the vicinity of cold lakes will be affected by projected losses of ice. In a worst-case scenario (an air temperatures increase of 8°C), 230,400 lakes and 656 million people in 50 countries will be impacted ( [[#Reid--2019|Reid et al., 2019]] ; [[#Sharma--2019|Sharma et al., 2019]] ). Winter ice-fishing ( [[#Orru--2014|Orru et al., 2014]] ), transportation via ice roads ( [[#Prowse--2011|Prowse et al., 2011]] ) and cultural activities ( [[#Magnuson--2014|Magnuson and Lathrop, 2014]] ) are ecosystem services at stake from the ongoing loss of lake ice.

Eutrophication of central European lakes has wiped out a significant proportion of the endemic fish fauna ( [[#Vonlanthen--2012|Vonlanthen et al., 2012]] ), so climate-induced further eutrophication is expected to represent an additional threat to fish fauna and commercial fisheries ( [[#Ficke--2007|Ficke et al., 2007]] ). Given that the ecological consequences of lake warming may be especially strong in the Tropics ( [[#2.3.1|Section 2.3.1.1]] ), ecosystem services may be most affected there. Tropical lakes support important fisheries ( [[#Lynch--2016a|Lynch et al., 2016a]] ; [[#McIntyre--2016|McIntyre et al., 2016]] ) that provide a critical source of nutrition to adjacent human populations. These lakes are especially prone to the loss of deep-water oxygen due to warming, with adverse consequences for the productivity of fisheries and for biodiversity ( ''medium evidence'' , ''medium agreement'' ) ( [[#Lewis%20Jr--2000|Lewis Jr, 2000]] ; [[#Van%20Bocxlaer--2012|Van Bocxlaer et al., 2012]] ).

Tropical lakes tend to be hotspots of freshwater biodiversity ( [[#Vadeboncoeur--2011|Vadeboncoeur et al., 2011]] ; [[#Brawand--2014|Brawand et al., 2014]] ; [[#Sterner--2020|Sterner et al., 2020]] ); ancient tropical lakes such as Malawi, Tanganyika, Victoria, Titicaca, Towuti and Matano hold thousands of animal species found nowhere else ( [[#Vadeboncoeur--2011|Vadeboncoeur et al., 2011]] ). While biodiversity and several ecosystem services can be considered synergistic (food webs, tourism and of aesthetic and spiritual value) ( [[#Langhans--2019|Langhans et al., 2019]] ), others can be considered antagonistic in case of a strong ecosystem service demand (such as water abstraction, water use and food security in terms of overexploitation). Here, the balance between biodiversity and ecosystem services is key ( [[#Langhans--2019|Langhans et al., 2019]] ), where biodiversity can be integrated into water policy by means of integrated water resource management (IWRM) towards NbS ( [[#Ligtvoet--2017|Ligtvoet et al., 2017]] )

<div id="2.5.3.6.3" class="h4-container"></div>

<span id="risks-to-hydropower-and-erosion-control"></span>
===== 2.5.3.6.3 Risks to hydropower and erosion control =====

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River banks, riparian vegetation and macrophyte beds play important roles in erosion control through reducing current velocities, increasing sedimentation and reducing turbidity ( [[#Madsen--2001|Madsen et al., 2001]] ). Rates of flow in rivers affect inland navigation ( [[#Vári--2022|Vári et al., 2022]] ). Changing seasonality in snow-dominated basins is expected to enhance hydropower production in winter but decrease it during summer ( [[#Doell--2015|Doell et al., 2015]] ). Glacier melt changes hydrological regimes, sediment transport and bio-geochemical and contaminant fluxes from rivers to oceans, profoundly influencing ecosystem services that glacier-fed rivers provide, particularly the provision of water for agriculture, hydropower and consumption ( [[#Milner--2017|Milner et al., 2017]] ). Loss of glacial mass and snowpack has already impacted flow rates, quantities and seasonality (Chapter 4, in this report) ( [[#Hock--2019|Hock et al., 2019]] ). Meltwater yields from glacier ice are likely to increase in many regions during the next decades but decrease thereafter, as glaciers become smaller and smaller and finally disappear ( [[#Hock--2019|Hock et al., 2019]] ).

<div id="2.5.4" class="h2-container"></div>

<span id="key-risks-to-terrestrial-and-freshwater-ecosystems-from-climate-change"></span>