Editing IPCC:AR6/WGII/Chapter-14 (section)

=== 14.5.4 Food, Fibre and Other Ecosystem Products ===

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<span id="observed-impacts-and-projected-risks-agriculture-livestock-and-forestry"></span>
==== 14.5.4.1 Observed Impacts and Projected Risks: Agriculture, livestock and forestry ====

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Climate change has affected crops across North America through changes in growing seasons and regions, extreme heat, precipitation, water stress and soil quality (Table 14.1; Figure 14.5; [[IPCC:Wg2:Chapter:Chapter-5#5.4.1|Section 5.4.1]] ; Figure 5.3) ( [[#Mann--2015|Mann and Gleick, 2015]] ; [[#Galloza--2017|Galloza et al., 2017]] ; [[#Otkin--2018|Otkin et al., 2018]] ). These changes directly influence crop productivity, quality and market price ( ''high confidence'' ) ( [[#Kistner--2018|Kistner et al., 2018]] ; [[#Reyes--2019|Reyes and Elias, 2019]] ). Effects of historical climate change on maize, soybean, barley and wheat crop yields vary from strong increases to strong decreases (e.g., &gt; −0.5 to &gt; +0.5 t ha −1 yr −1 for maize) within North America’s agroecological regions, even for the same crop ( [[#Ray--2019|Ray et al., 2019]] ). Across North America, climate change has generally reduced agricultural productivity by 12.5% since 1961, with progressively greater losses moving south from Canada to Mexico ( [[#Ortiz-Bobea--2021|Ortiz-Bobea et al., 2021]] ), yet responses are highly differential across regions and crops. Some crop loss events are partially attributed to climate change ( ''high confidence'' ) such as the 2012 Midwest and Great Plains drought, which cost agriculture 30 billion USD ( [[#Smith--2015|Smith and Matthews, 2015]] ; [[#Rupp--2017|Rupp et al., 2017]] ). Aridity is extending northward, altering crop suitability ranges (Figure 14.4); up to 50% of distributional shifts in growing regions for US crops between 1970 and 2010 may be related to climate change ( [[#Lant--2016|Lant et al., 2016]] ; [[#Cho--2017|Cho and McCarl, 2017]] ). Irrigation is expanding to areas formerly largely dependent on rainfall ( [[#Wang--2018b|Wang et al., 2018b]] ).

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[[File:b191f5b676b7541daffca3b488d66718 IPCC_AR6_WGII_Figure_14_004.png]]

'''Figure 14.4 |''' '''Freshwater resource risks as a function of global mean surface temperature increase relative to pre-industrial (1850–1900) levels.''' Estimated sensitivities are based on references cited in Table 14.3 (SM14.4).

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[[File:2df127e0f9e205d9d2a8b7a8b58bbc2f IPCC_AR6_WGII_Figure_14_005.png]]

'''Figure 14.5 |''' '''Crop responses to climate change will depend on existing mean climate, type of climate change and characteristics of crop types.''' Hypothesised responses for Crop Types A, B, C and D include changing crop yields or changing crop area. Adaptation actions may alter hypothesised responses. (Maps from [[#Matthews--2019|Matthews et al., 2019]] .)

Without adaptation, climate change is projected to reduce overall yields of important North American crops (e.g., wheat, maize, soybeans) ( ''high confidence'' ) (Tables SM14.3, SM14.4; [[#Chen--2017|Chen et al., 2017]] ; [[#Levis--2018|Levis et al., 2018]] ). For example, projected heat stress (RCP8.5) reduced mid-century (2040–2069) maize and cotton yields by 12–15% of historical yields (1950–2005), with the US-SW suffering the largest impacts (Table SM14.5; [[#Elias--2018|Elias et al., 2018]] ). Warming and heat extremes will delay or prevent chill accumulation, affecting perennial crop development (e.g., fruit set failure), yield (e.g., walnuts, pistachios, stone fruit) and quality (e.g., grapes) ( ''medium confidence'' ) ( [[#Parker--2020|Parker et al., 2020]] ). Warming will alter the length of growing seasons of cold-season crops (e.g., broccoli, lettuce) and will shift suitability ranges of warm-season California crops (e.g., tomatoes) ( ''medium confidence'' ) ( [[#Marklein--2020|Marklein et al., 2020]] ). Increasing atmospheric CO 2 will enhance yields yet reduce nutrient content of many crops ( ''high confidence'' ); a CO 2 concentration of 541 ppm (seen by 2050 in RCP8.5) would reduce per-capita nutrient availability in North American diets by 2.5–4.0% ( [[#Beach--2019|Beach et al., 2019]] ). Crop pest and pathogen outbreaks are expected to worsen under climate change ( ''high confidence'' ) ( [[#Deutsch--2018|Deutsch et al., 2018]] ; [[#Wolfe--2018|Wolfe et al., 2018]] ; [[#Zhang--2019a|Zhang et al., 2019a]] ).

Climate change is anticipated to cause declines in livestock production across North America ( ''high confidence'' ) (Table 14.4; SM14.6; [[#Havstad--2018|Havstad et al., 2018]] ; [[#Murray-Tortarolo--2018|Murray-Tortarolo et al., 2018]] ). Increases in extreme temperature raise the risk of livestock heat stress, disease and pest impacts ( [[#Rojas-Downing--2017|Rojas-Downing et al., 2017]] ). Projected aridification reduces forage production in the southwest USA and northern Mexico ( ''high confidence'' ) ( [[#Polley--2013|Polley et al., 2013]] ; [[#Reeves--2014|Reeves et al., 2014]] ; [[#Cooley--2016|Cooley, 2016]] ; [[#Bradford--2020|Bradford et al., 2020]] ) and transforms grasslands into woody shrublands ( [[#Briske--2015|Briske et al., 2015]] ; [[#Murray-Tortarolo--2018|Murray-Tortarolo et al., 2018]] ), while warmer and wetter conditions in the northern regions (CA-PR, US-NW, US-NP) may enhance rangeland production by extending growing seasons ( ''high confidence'' ) ( [[#Hufkens--2016|Hufkens et al., 2016]] ; [[#Derner--2018|Derner et al., 2018]] ; [[#Zhang--2019a|Zhang et al., 2019a]] ). Increased CO 2 will enhance production ( ''medium confidence'' ) but reduce forage quality ( ''high confidence'' ) in US-NP and US-NW (Table SM14.6; [[#Derner--2018|Derner et al., 2018]] ).

'''Table 14.4 |''' Observed and projected impacts to food and fibre resources

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

! Observed change a

! References

! Projected change

! References

|-
| colspan="5"| '''Agriculture and livestock (Tables SM14.2–SM14.5)'''

|-
| Extreme events

| Estimates of yield reduction from heat stress for both maize and cotton indicate that historically, US-SW heat stress reduced cotton yield by 26% and maize yield by 18% compared with potential yield. Extreme heat was associated with increased crop failure in MX-CE, US-SW. Hailstorm increased frequency observed in MX coinciding with the most vulnerable stage or flowering period of maize. Extreme precipitation damages to soil, increased erosion, and reduced crop yields observed in Mexico and US-MW.

| [[#Altieri--2009|Altieri and Nicholls (2009)]] ; [[#Mastachi-Loza--2016|Mastachi-Loza et al. (2016)]] ; [[#Elias--2018|Elias et al. (2018)]] ; [[#Kistner--2018|Kistner et al. (2018)]] ; [[#Reyes--2019|Reyes and Elias (2019)]]

| Heat stress (RCP8.5) reduces mid-century (2040–2069) maize and cotton yields by 12–15% of historical yields (1950–2005) with largest impacts in US-SW, and additional drought-related stress in US-MW could reduce maize and soybean yields by ~5 and ~10%, respectively, by late century under RCP4.5. Warming and extreme heat (&gt;35%) will delay (or prevent) chill accumulation, impacting perennial crop development, yields and quality (US-SW). Increases in extreme temperature raise the risk of livestock heat stress, disease and pest impacts.

| [[#Jin--2017|Jin et al. (2017)]] ; [[#Rojas-Downing--2017|Rojas-Downing et al. (2017)]] ; [[#Elias--2018|Elias et al. (2018)]] ; [[#Parker--2020|Parker et al. (2020)]]

|-
| Mean growing season precipitation decline, mean temperature increase, drought

| Across the US Great Plains (US-SP, US-NP) between 1968 and 2013 climate change induced 3.55, −0.55 and 0.94% change in yield for (irrigated and non-irrigated) maize, sorghum and soybeans, respectively. Droughts and increasing temperatures reduced soil fertility in Mexico and contributed to soil erosion and degradation, and suitability loss of 18–22%. Experimental and simulated reductions in water supply of 25–50% result in similar-magnitude declines in yield for multiple food and forage crops (e.g., wheat, maize).

| [[#Frisvold--2012|Frisvold and Konyar (2012)]] ; [[#Leskovar--2012|Leskovar et al. (2012)]] ; [[#Aladenola--2014|Aladenola and Madramootoo (2014)]] ; Galloza et al. (2017); [[#Havstad--2018|Havstad et al. (2018)]] ; [[#Kukal--2018|Kukal and Irmak (2018)]]

| Warming alters the length of growing seasons of cold-season crops and shifts suitability ranges of warm-season California crops. Aridification reduces forage production in US-SW and MX-N. Warming is associated with reduced livestock growth and fertility, increased pathogens in US-SE, US-SP, US-MW and US-NE, and reduced milk production in US-MW.

| St-Pierre et al. (2003); [[#Polley--2013|Polley et al. (2013)]] ; [[#Key--2014|Key and Sneeringer (2014)]] ; [[#Reeves--2014|Reeves et al. (2014)]] ; [[#Cooley--2016|Cooley (2016)]] ; [[#Hufkens--2016|Hufkens et al. (2016)]] ; [[#Derner--2018|Derner et al. (2018)]] ; [[#Hristov--2018|Hristov et al. (2018)]] ; [[#Ortiz-Colón--2018|Ortiz-Colón et al. (2018)]] ; [[#Zhang--2019b|Zhang et al. (2019b)]] ; [[#Bowling--2020|Bowling et al. (2020)]] ; [[#Bradford--2020|Bradford et al. (2020)]] ; [[#Marklein--2020|Marklein et al. (2020)]]

|-
| Multiple drivers

| Climate change reduced total factor productivity of agriculture and livestock in North America by 12.5% (ranging from approximately −35 to 8%) between 2016 and 2015. Losses have been greatest in Mexico (−30 to −25%) (Figure 14.5), and lowest in Canada (&gt;0%). Reduced yield in Mexico and the USA; increased weed and pest pressure in US-NE, US-MW, US-NP and US-NW.

| [[#Garruña-Hernández--2012|Garruña-Hernández et al. (2012)]] ; Loreto et al. (2017); [[#Wolfe--2018|Wolfe et al. (2018)]] ; Torres Castillo et al. (2020; [[#Ortiz-Bobea--2021|Ortiz-Bobea et al. (2021)]]

| Declines in yield and changes in suitability ranges for maize (−18 to 5%), sorghum (−16 to 12%) and wheat (−38 to −15%) in Mexico (RCP4.5, 8.5; 2040–2099); northward shifts in the suitable area for six crops from the central USA (2100). Warming accompanied by increased CO 2 may benefit crop production of small grains in southern Canada up to 3°C global warming level (GWL), although benefits decline after 2.5°C GWL. Increased CO 2 enhances production but reduces forage quality in US-NP and US-NW. Without adaptation, 2°C GWL increases insect-caused production losses ~36 and ~44% for maize and wheat, respectively.

| Calderón-García et al. (2015); [[#Herrera-Pantoja--2015|Herrera-Pantoja and Hiscock (2015)]] ; [[#Lant--2016|Lant et al. (2016)]] ; [[#Chen--2017|Chen et al. (2017)]] ; [[#Montiel-González--2017|Montiel-González et al. (2017)]] ; [[#Reyer--2017|Reyer et al. (2017)]] ; [[#Derner--2018|Derner et al. (2018)]] ; [[#Deutsch--2018|Deutsch et al. (2018)]] ; [[#Levis--2018|Levis et al. (2018)]] ; [[#López-Blanco--2018|López-Blanco et al. (2018)]] ; Murray-Tortarolo et al. (2018); [[#Wolfe--2018|Wolfe et al. (2018)]] ; [[#Gomez%20Diaz--2019|Gomez Diaz et al. (2019)]] ; [[#Qian--2019|Qian et al. (2019)]] ; [[#Zhang--2019b|Zhang et al. (2019b)]] ; [[#Arce%20Romero--2020|Arce Romero et al. (2020)]]

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| colspan="5"| Aquaculture and fisheries (Tables SM14.6, SM14.8)

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| Extreme events

| MHW and HAB events of 2014–2016 resulted in multiple fishery closures along the west coast (US-NW, US-SW); disparate impacts observed between small and large vessels with greatest impacts on small vessel revenue and fishery participation; impacts highest for ports in the N-CC and least for fishing communities with diverse livelihoods and harvest portfolios. In the EBS, GOA and N-CC, declines in fish biomass and shifts in distribution were four times higher and greater during MHWs than that of general warming over the same period. Pelagic fish showed largest decrease in biomass (7%), as did Sockeye salmon and California anchovy; increased risk to hatcheries and low-lying pond systems from severe storms. Extreme heat is associated with reduced productivity of aquaculture species.

| Handisyde et al. (2017); [[#Food%20Agriculture%20Organization%20of%20the%20United%20Nations--2019|Food Agriculture Organization of the]] [[#United%20Nations--2019|United Nations (2019)]] ; [[#Froehlich--2019|Froehlich et al. (2019)]] ; [[#Reid--2019|Reid et al. (2019)]] ; [[#Bertrand--2020|Bertrand et al. (2020)]] ; [[#Cheung--2020|Cheung and Frölicher (2020)]] ; [[#Jardine--2020|Jardine et al. (2020)]] ; [[#Sippel--2020|Sippel et al. (2020)]] ; [[#Fisher--2021|Fisher et al. (2021)]]

| Doubling of MHW impact levels by 2050 among the most important fisheries species (over previous assessments that focus only on long-term climate change).

| [[#Cheung--2020|Cheung and Frölicher (2020)]]

|-
| Multiple drivers

| Climate shocks reduce catch, revenue and county-level wages and employment among commercial harvesters in US-NE. Climate variability during 1996–2017 is responsible for a 16% (95% CI: 10–22%) decline in county-level fishing employment in New England; impacts mediated by local biology and institutions. Seafood is an important source of nutrients and protein for Indigenous Peoples in CA-BC. Polices that incorporate nutrition in fisheries management are limited in North America.

| [[#Marushka--2019|Marushka et al. (2019)]] ; [[#Oremus--2019|Oremus (2019)]] ; also see [[#14.5.6|Section 14.5.6]]

| Declines in North American catch potential of flatfish under RCP8.5 for the EBS, GOA, GOMX, US-SE and US-NE; declines in productivity for multiple species in Mexico, with the largest declines in productivity (&gt;35%) for abalone and Pacific sardine. Impacts are greatest for artisanal species; declines in fish community biomass for all North American coasts except US-SW and the Canadian Arctic; declines are greater under RCP8.5 than RCP2.6. Modest increases (up to 10%) in landings of CA-QC and CA-AT surf clams and shrimp are projected under RCP2.6 by 2100 and declines in snow crab up to 16% are expected (RCP2.6, 8.5). Mussel landings increase 21%, while declines in shellfish and lobster landings (2090) are twice as high under RCP8.5 (42–54%) as RCP2.6. Shellfish and snow crab landings decline in CA-QC and CA-QT; declines under RCP8.5 are double those of RCP2.6. Climate change reduces EBS blue king crab recovery in simulations. Relative to the USA and Canada, Mexico has the strongest benefits in net catch under RCP2.6 relative to RCP8.5 ( &gt;30% increase in catch); increases of 70% in catch potential projected for the Canadian Arctic (CA-NE, CA-NW) under RCP8.5 (versus minimal changes under RCP2.6). High-resolution and size-spectrum models project declines in groundfish catch and biomass in S-EBS. Shifting transboundary stocks may increase challenges.

| [[#Weatherdon--2016|Weatherdon et al. (2016)]] ; [[#Cheung--2018|Cheung (2018)]] ; Carozza et al. (2019); [[#Cisneros-Mata--2019|Cisneros-Mata et al. (2019)]] ; [[#Reum--2019|Reum et al. (2019)]] ; [[#Tai--2019|Tai et al. (2019)]] ; [[#Mendenhall--2020|Mendenhall et al. (2020)]] ; [[#Wilson--2020|Wilson et al. (2020)]]

|-
| Ocean and lake acidification

| Ocean acidification (OA) reduced maximum sustainable yield, catch and profits of EBS Tanner crab in simulations. Survival of larval and juvenile red king crab in the lab decreased 97–100% with decreasing pH; no appreciable effects of pH on larval growth of walleye pollock in the lab (Hurst, 2013); mixed evidence of impacts of changes in pH on freshwater or saltwater finfish aquaculture; OA reduced growth, calcification, attachment and increased mortality in calcifying molluscs and seaweeds in the USA and Canada; OA may benefit non-calcifying seaweeds.

| Long et al. (2013a); [[#Seung--2015|Seung et al. (2015)]] ; [[#Punt--2016|Punt et al. (2016)]] ; [[#Clements--2017|Clements and Chopin (2017)]] ; Handisyde et al. (2017); Swiney et al. (2017); [[#Food%20Agriculture%20Organization%20of%20the%20United%20Nations--2019|Food Agriculture Organization of the]] [[#United%20Nations--2019|United Nations (2019)]] ; [[#Froehlich--2019|Froehlich et al. (2019)]] ; [[#Reid--2019|Reid et al. (2019)]] ; [[#Stewart-Sinclair--2020|Stewart-Sinclair et al. (2020)]]

| Declines for some shellfisheries and flatfish due to OA and temperature. OA conditions under RCP8.5 reach critical risk thresholds for mollusc harvests earlier in northern regions than southern areas. OA risk to shellfisheries is highest in N-CC. OA causes 1% additional decline in Arctic cod populations by 2100 under RCP8.5. OA influences management reference points of Northern Rock sole. OA and temperature reduce probability of recovery in simulations of EBS blue king crab.

| [[#Ekstrom--2015|Ekstrom et al. (2015)]] ; [[#Reum--2019|Reum et al. (2019)]] ; [[#Steiner--2019|Steiner et al. (2019)]] ; [[#Wilson--2020|Wilson et al. (2020)]] ; [[#Punt--2021|Punt et al. (2021)]]

|-
| Mean temperature increase

| Species distributions have shifted poleward and phenology has shifted earlier with the strongest effects on bony fish. Warming over the past century (2001–2010 to 1930–1939) is associated with declines in maximum sustainable yield along the entire west coast of North America that range from −14% in the EBS to −29% in the CC-S. Along the east coast, declines of −3 to −9% were observed in the GOMX and US-SE, while increases of 8–15% were observed in the US-NE and CA-CQ; mixed positive and negative growth and mortality responses for aquaculture species in North America. Juvenile red king crab survival decreases as temperatures increase in lab experiments. American Lobster abundances declined (78%) in South New England and have increased (515%) in the Gulf of Maine due to water temperature changes and differing conservation measures (between 1985 and 2014 for the GOM, and 1997 and 2014 for southern New England).

| [[#Poloczanska--2016|Poloczanska et al. (2016)]] ; [[#McCoy--2017|McCoy et al. (2017)]] ; Swiney et al. (2017); [[#Le%20Bris--2018|Le Bris et al. (2018)]] ; [[#Miller--2018|Miller et al. (2018)]] ; [[#Food%20Agriculture%20Organization%20of%20the%20United%20Nations--2019|Food Agriculture Organization of the]] [[#United%20Nations--2019|United Nations (2019)]] ; [[#Free--2019|Free et al. (2019)]] ; [[#Reid--2019|Reid et al. (2019)]] ; [[#Weiskerger--2019|Weiskerger et al. (2019)]] ; [[#Bertrand--2020|Bertrand et al. (2020)]] ; [[#Le--2020|Le et al. (2020)]]

| By end of century, North American fish biomass, catch potential and revenue are ~9% higher under RCP2.6 than RCP8.5 and differences are greatest for US fisheries (relative to Canada and Mexico; poleward redistributions (reported ranges of 10.3–39.1 km per decade) and to depth decrease access to shellfisheries in CA-QC and subsistence species in CA-BC (−28% by 2100), with impacts increasing north to south and under RCP8.5 as compared with RCP2.6. Climate change (RCP8.5) shifts the relative percentage of catch and profits for the USA–Canada transboundary stocks under RCP8.5 (but not RCP2.6); decreases in biomass of historically large fisheries in US-NA and CA-QC, and US-AK and important subsistence species in CA-WA and CA-BC, while some increases in the North Atlantic. Declines are greater under RCP8.5 relative to RCP2.6. In EBS (US-AK), community biomass, catches and mean body size decreases by 36, 61 and 38%, respectively, under RCP8.5 (2100). Climate change causes declines in global marine aquaculture production under RCP8.5 with impacts greater for bivalve than finfish and with significant disparities among regions in direction and magnitude of changes; greatest declines for finfish aquaculture expected in northern regions (GOA, CA-BC, CA-CQ), and large declines for bivalve production (declines of 20–100%) for Canada. Declines become more probable by 2050–2070.

| [[#Weatherdon--2016|Weatherdon et al. (2016)]] ; [[#Cheung--2018|Cheung (2018)]] ; Froehlich et al. (2018); [[#Morley--2018|Morley et al. (2018)]] ; [[#Greenan--2018|Greenan et al. (2018)]] ; [[#Steiner--2019|Steiner et al. (2019)]] ; [[#Sumaila--2019|Sumaila et al. (2019)]] ; [[#Bryndum-Buchholz--2020|Bryndum-Buchholz et al. (2020)]] ; [[#Holsman--2020|Holsman et al. (2020)]] ; Palacios-Abrantes et al. (2020); [[#Reum--2020|Reum et al. (2020)]] ; [[#Sumaila--2020|Sumaila and Zwaag (2020)]] ; [[#Whitehouse--2020|Whitehouse and Aydin (2020)]] ; [[#Wilson--2020|Wilson et al. (2020)]]

|}

Notes: See Figure 14.1 for region acronym definitions. (a)

Climate-change impacts on forests ( [[#14.5.1|Section 14.5.1]] ; see Box 14.2) may affect timber production by altering tree species distributions, productivity, and wildfire and insect disturbances ( ''medium confidence'' ). Southern or drier locations may shift from forests to other vegetation types, whereas higher-latitude areas may experience forest expansion ( [[#Brecka--2018|Brecka et al., 2018]] ). Tree species composition is projected to change with climate change ( [[#Wang--2015|Wang et al., 2015]] ; [[#Bose--2017|Bose et al., 2017]] ). Tree growth may increase or decrease from changes in temperature or moisture depending on location, with lower growth expected from warming in water-limited areas ( [[#Littell--2010|Littell et al., 2010]] ). Increased productivity associated with more favourable climate conditions is projected for boreal forests ( [[#Brecka--2018|Brecka et al., 2018]] ), although in some regions, growth will reverse and decline with additional warming ( [[#D’Orangeville--2018|D’Orangeville et al., 2018]] ; [[#Chaste--2019|Chaste et al., 2019]] ). As a result of these changes, timber yields in North America either may increase in the future ( [[#Beach--2015|Beach et al., 2015]] ; [[#EPA--2015a|EPA, 2015a]] ) or decrease ( [[#Boulanger--2014|Boulanger et al., 2014]] ; [[#McKenney--2016|McKenney et al., 2016]] ; [[#D’Orangeville--2018|D’Orangeville et al., 2018]] ; [[#Thorne--2018|Thorne et al., 2018]] ; [[#Chaste--2019|Chaste et al., 2019]] ) depending on location and the mechanisms included. Wildfires and insect outbreaks are projected to increase with future climate change, thereby limiting biomass ( [[#Gauthier--2015|Gauthier et al., 2015]] ; [[#Bentz--2019|Bentz et al., 2019]] ; [[#Chaste--2019|Chaste et al., 2019]] ).

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<span id="observed-impacts-and-projected-risks-fisheries-and-aquaculture"></span>
==== 14.5.4.2 Observed Impacts and Projected Risks: Fisheries and Aquaculture ====

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Climate impacts outlined in [[#14.5.2|Section 14.5.2]] have induced yield losses for multiple subsistence, recreational and commercial fisheries ( ''very high confidence'' ), and contributed to commercial fishery closures across North America (Sections 14.5.1, 14.5.3; Figure 14.6; Table SM14.7; [[#Lynn--2014|Lynn et al., 2014]] ; [[#Barbeaux--2020|Barbeaux et al., 2020]] ; [[#Fisher--2021|Fisher et al., 2021]] ). Climate-driven declines in productivity are widespread ( ''high confidence'' ) (Figure 14.6), although a few increases are observed in northern regions ( ''medium confidence'' ) ( [[#Cunningham--2018|Cunningham et al., 2018]] ; [[#Crozier--2019|Crozier et al., 2019]] ; [[#Zhang--2019b|Zhang et al., 2019b]] ). Redistribution of species has increased travel distance to fishing grounds, shifted stocks across regulatory and international boundaries, and increased interactions with protected species ( ''very high confidence'' ) (Figure 14.6; Table SM14.7; Cross-Chapter Box MOVING PLATE in Chapter 5; [[#Morley--2018|Morley et al., 2018]] ; [[#Free--2019|Free et al., 2019]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Rogers--2019|Rogers et al., 2019]] ; [[#Stevenson--2019|Stevenson and Lauth, 2019]] ; [[#Young--2019|Young et al., 2019]] ). Climate shocks have reduced yield and increased instability in fishery revenue ( ''high confidence'' ) ( [[#Fisher--2021|Fisher et al., 2021]] ).

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[[File:34e7d9a9d584fc1c80a2c35191a335ca IPCC_AR6_WGII_Figure_14_006.png]]

'''Figure 14.6 |''' '''Case studies of climate-change impacts on North American fisheries (blue text) and aquaculture (gray text).'''

Declines in yield and poleward stock redistributions (an average of ~20.6 km per decade) are expected to continue under climate change and increase in magnitude with atmospheric carbon ( ''high confidence'' ) (Table 14.4; [[#Hare--2016|Hare et al., 2016]] ; [[#Pecl--2017|Pecl et al., 2017]] ; [[#Rheuban--2017|Rheuban et al., 2017]] ; [[#Morley--2018|Morley et al., 2018]] ; [[#Smale--2019|Smale et al., 2019]] ; [[#Szuwalski--2021|Szuwalski et al., 2021]] ). For example, without adaptation, end-of-century losses of Bering Sea pollock yield (relative to persistence scenarios) is ''likely'' to reach 50% under moderate (RCP4.5) and 80% under low (RCP8.5) mitigation scenarios, respectively ( [[#Holsman--2020|Holsman et al., 2020]] ). Expanding HABs, pathogens and altered ocean chemistry (OA and dissolved oxygen) will reduce yields and increase closures of fisheries along all North American coasts ( ''medium confidence'' ) ( [[#14.5.2|Section 14.5.2]] ; [[#Deutsch--2015a|Deutsch et al., 2015a]] ; [[#Ekstrom--2015|Ekstrom et al., 2015]] ; [[#Seung--2015|Seung et al., 2015]] ; [[#Punt--2016|Punt et al., 2016]] ; [[#Howard--2020|Howard et al., 2020]] ). For fisheries that represent 56% of current US fishing revenue, projected annual net losses under high-emission scenarios (RCP8.5, 2021–2100) may reach double that of low-emission scenarios (RCP2.6) ( [[#Moore--2021|Moore et al., 2021]] ).

Warming waters and OA have impacted aquaculture production in North America ( ''high confidence'' ) (Figure 14.6; [[#Clements--2017|Clements and Chopin, 2017]] ; [[#Reid--2019|Reid et al., 2019]] ; [[#Stewart-Sinclair--2020|Stewart-Sinclair et al., 2020]] ). Under climate change (RCP8.5), declines in marine finfish and bivalve aquaculture become ''likely'' by mid-century ( [[#Froehlich--2018|Froehlich et al., 2018]] ; [[#Stewart-Sinclair--2020|Stewart-Sinclair et al., 2020]] ). Adaptation is possible but uncertain ( [[#Bitter--2019|Bitter et al., 2019]] ; [[#Fitzer--2019|Fitzer et al., 2019]] ; [[#Reid--2019|Reid et al., 2019]] ), especially with increasing extreme events. Nature-based aquaculture solutions (e.g., conservation aquaculture, restorative aquaculture) could aid carbon mitigation and local-level adaptation, especially for seaweed and bivalve culture (see Box 14.7; [[#Froehlich--2017|Froehlich et al., 2017]] ; [[#Froehlich--2019|Froehlich et al., 2019]] ; [[#Reid--2019|Reid et al., 2019]] ; [[#Theuerkauf--2019|Theuerkauf et al., 2019]] ).

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<span id="food-and-fibre-adaptation-cross-cutting-themes"></span>
==== 14.5.4.3 Food and Fibre Adaptation: Cross-Cutting Themes ====

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Across food and fibre systems, climate resilience is enhanced through diversifying income and harvest portfolios as well as increasing local biodiversity and functional redundancy ( ''high confidence'' ) ( [[#Messier--2019|Messier et al., 2019]] ; [[#Rogers--2019|Rogers et al., 2019]] ; [[#Young--2019|Young et al., 2019]] ; [[#Aquilué--2020|Aquilué et al., 2020]] ; [[#Fisher--2021|Fisher et al., 2021]] ). Ecosystem-based practices and sustainable intensification (increasing yields while minimising resource demand and ecosystem impacts) ( [[#Cassman--2020|Cassman and Grassini, 2020]] ; [[#Rockström--2021|Rockström et al., 2021]] ) will help the sector meet food production demands under climate change ( ''medium confidence'' ), but effectiveness generally declines and is less certain after 2050 in scenarios without carbon mitigation ( ''high confidence'' ) ( [[#Bermeo--2014|Bermeo et al., 2014]] ; [[#Gaines--2018|Gaines et al., 2018]] ; [[#Costello--2020|Costello et al., 2020]] ; [[#Free--2020|Free et al., 2020]] ; [[#Holsman--2020|Holsman et al., 2020]] ). Across the sector, successful adaptation is underpinned by approaches that meaningfully consider the coupled social–ecological networks around food and fibre production and value IK ( ''very high confidence'' ) (see Box 14.1; [[#FAO--2018|FAO, 2018]] ; [[#Steele--2018|Steele et al., 2018]] ; [[#Calliari--2019|Calliari et al., 2019]] ). Integrated modelling, participatory planning and inclusive decision making promote effective and equitable adaptation responses ( ''very high confidence'' ) (Figure 14.7, [[#14.7|Section 14.7]] ) [[#Toledo-Hernández--2017|Toledo-Hernández et al., 2017]] ; [[#Eakin--2018|Eakin et al., 2018]] ; [[#Monterroso--2018|Monterroso and Conde, 2018]] ; [[#Alexander--2019|Alexander et al., 2019]] ; [[#Hodgson--2019|Hodgson and Halpern, 2019]] ; [[#Holsman--2019|Holsman et al., 2019]] ; [[#Samhouri--2019|Samhouri et al., 2019]] ; [[#Barbeaux--2020|Barbeaux et al., 2020]] ; [[#Hollowed--2020|Hollowed et al., 2020]] ), while a paucity of high-resolution and locally tailored climate change information remains a barrier to adaptation ( [[#Ekstrom--2015|Ekstrom et al., 2015]] ; [[#Donatti--2017|Donatti et al., 2017]] ; [[#Young--2019|Young et al., 2019]] ).

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[[File:3b24303c1e90af7468a5dff3ded366af IPCC_AR6_WGII_Figure_14_007.png]]

'''Figure 14.7 |''' '''Adaptation in North American food sectors is shown, modified from Cottrell et al''' '''.''' '''(2019).'''

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==== 14.5.4.4 Food and Fibre Adaptation: Agriculture, Livestock and Forestry ====

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Land management and horticulture approaches that preserve and improve soil structure and organic matter can reduce erosion ( ''high confidence'' ) (Sections 14.5.1, 14.5.3; [[#Lal--2011|Lal et al., 2011]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ). Preserving biodiversity and water, changing planting dates and double cropping are also effective climate adaptation strategies ( [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Hernandez-Ochoa--2018|Hernandez-Ochoa et al., 2018]] ; [[#Monterroso-Rivas--2018|Monterroso-Rivas et al., 2018]] ; [[#Wolfe--2018|Wolfe et al., 2018]] ). Traditional agriculture inherently includes climate adaptive practices that enhance biodiversity, soil quality and agricultural production (e.g., multiple cultivars, heat-tolerant heritage cattle breeds) ( [[#Bermeo--2014|Bermeo et al., 2014]] ; [[#Gomez-Aiza--2017|Gomez-Aiza et al., 2017]] ; [[#Ortiz-Colón--2018|Ortiz-Colón et al., 2018]] ). Agroecology and agroforestry (see Box 14.7) in North America has expanded from (but not replaced) traditional and rural practices in Mexico ( [[#Metcalfe--2020a|Metcalfe et al., 2020a]] ) as a sustainable and climate-resilient alternative to industrial agriculture ( [[#Schoeneberger--2017|Schoeneberger et al., 2017]] ) that increases productivity (by 6–65% depending on the crop), enhances microclimates and provides co-benefits for GHG mitigation ( [[#Abbas--2017|Abbas et al., 2017]] ; [[#Cardinael--2017|Cardinael et al., 2017]] ; [[#Schoeneberger--2017|Schoeneberger et al., 2017]] ; [[#Snapp--2021|Snapp et al., 2021]] ). Irrigation is an effective adaptation strategy in key agricultural areas ( [[#Miller--2017|Miller, 2017]] ; [[#Lund--2018|Lund et al., 2018]] ) and could stabilise food security in rain-fed regions (e.g., southeast Mexico) ( [[#Spring--2014|Spring, 2014]] ); water allocation must balance multiple needs and rights ( ''medium confidence'' ) ( [[#14.5.3|Section 14.5.3]] ; [[#Brown--2015b|Brown et al., 2015b]] ; [[#Levis--2018|Levis et al., 2018]] ; [[#Gomez%20Diaz--2019|Gomez Diaz et al., 2019]] ). Heritage livestock breeds, changing species and precision-ranching technology may promote ranch and rangeland resilience ( [[#Zhao--2013|Zhao et al., 2013]] ). In loblolly pine plantations in the southern USA, effective adaptation includes reducing tree density and, less effectively, shifting to slash pine ( [[#Susaeta--2014|Susaeta et al., 2014]] ). Salvage logging following forest disturbances (e.g., insect outbreaks) can increase timber harvest ( [[#Bogdanski--2011|Bogdanski et al., 2011]] ; [[#USDA%20Forst%20Service--2011|USDA Forst Service, 2011]] ; [[#Han--2018|Han et al., 2018]] ; [[#Morris--2018a|Morris et al., 2018a]] ).

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==== 14.5.4.5 Food and Fibre Adaptation: Fisheries and Aquaculture ====

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Proactive and ecosystem-based management increases climate resilience in fisheries ( ''high confidence'' ), but effectiveness after 2050 may be limited without global carbon mitigation ( ''medium confidence'' ) ( [[#Gaichas--2017|Gaichas et al., 2017]] ; [[#Gaines--2018|Gaines et al., 2018]] ; [[#Kritzer--2019|Kritzer et al., 2019]] ; [[#Barbeaux--2020|Barbeaux et al., 2020]] ; [[#Free--2020|Free et al., 2020]] ; [[#Holsman--2020|Holsman et al., 2020]] ). Flexibility (e.g., mobility, diverse incomes or harvest portfolios) underpins climate resilience across regions, management policies and fisheries, although small-scale fisheries have less scope for adaptation ( [[#Aguilera--2015|Aguilera et al., 2015]] ; [[#Young--2019|Young et al., 2019]] ). Climate-informed and dynamic management ( [[#Hazen--2018|Hazen et al., 2018]] ) improves modelled fishery performance ( ''medium confidence'' ) ( [[#14.5.2|Section 14.5.2]] ; [[#Froehlich--2017|Froehlich et al., 2017]] ; [[#Tommasi--2017a|Tommasi et al., 2017a]] ; [[#Tommasi--2017b|Tommasi et al., 2017b]] ; [[#Karp--2019|Karp et al., 2019]] ; [[#Barbeaux--2020|Barbeaux et al., 2020]] ), yet planning and policies that directly incorporate climate-change information remain limited ( [[#Skern-Mauritzen--2015|Skern-Mauritzen et al., 2015]] ; [[#Marshall--2019b|Marshall et al., 2019b]] ). Expanding aquaculture across North America will ''likely'' address deficits in nutritional and protein yields ( [[#Gentry--2019|Gentry et al., 2019]] ; [[#Costello--2020|Costello et al., 2020]] ), yet aquaculture initiatives have largely progressed without explicitly considering climate impacts ( [[#FAO--2018|FAO, 2018]] ; [[#Froehlich--2019|Froehlich et al., 2019]] ), and critical elements for climate adaptation (e.g., climate-informed zoning, monitoring, insurance) are not widely implemented ( [[#Liñan-Cabello--2016|Liñan-Cabello et al., 2016]] ; [[#FAO--2018|FAO, 2018]] ; [[#Stewart-Sinclair--2020|Stewart-Sinclair et al., 2020]] ). Climate-informed and standardised aquaculture governance, and increased coordination with fishery and coastal management, is needed for climate resilience ( ''high confidence'' ) ( [[#Brugère--2019|Brugère et al., 2019]] ; [[#Froehlich--2019|Froehlich et al., 2019]] ; [[#Free--2020|Free et al., 2020]] ; [[#Galparsoro--2020|Galparsoro et al., 2020]] ).

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