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

=== 2.4.2 Observed Responses to Climate Change by Species and Communities (Freshwater and Terrestrial) ===

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<span id="observed-range-shifts-driven-by-climate-change"></span>
==== 2.4.2.1 Observed Range Shifts Driven by Climate Change ====

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Poleward and upward range shifts were already attributable to climate warming with ''high confidence'' in AR5. Publication of observed range shifts in accord with climate change have accelerated since AR5 and strengthened attribution. Ongoing latitudinal and elevational range shifts driven by regional climate trends are now well-established globally across many groups of organisms, and attributable to climate change with ''very high confidence'' due to very high consistency across a now very large body of species and studies and an in-depth understanding of mechanisms underlying physiological and ecological responses to climate drivers (Table 2.2; Table 2.3, Table SM2.1) ( [[#Pöyry--2009|Pöyry et al., 2009]] ; [[#Chen--2011|Chen et al., 2011]] ; [[#Grewe--2013|Grewe et al., 2013]] ; [[#Gibson-Reinemer--2015|Gibson-Reinemer and Rahel, 2015]] ; [[#MacLean--2017|MacLean and Beissinger, 2017]] ; [[#Pacifici--2017|Pacifici et al., 2017]] ; [[#Anderegg--2019|Anderegg et al., 2019]] ). Range shifts stem from local population extinctions along warm-range boundaries ( [[#Anderegg--2019|Anderegg et al., 2019]] ) as well as from the colonisation of new regions at cold-range boundaries ( [[#Ralston--2017|Ralston et al., 2017]] ).

Many studies since AR4 have tended not to be designed as attribution studies, particularly recent large-scale, multi-species meta-analyses. That is to say, all the data available was included in such studies (from both undisturbed and highly degraded lands and including very short-term data sets of &lt;20 years), with little attempt to design the studies to differentiate the effects of climate change from those of other potential confounding variables. These studies tended to find greater lag and a lower proportion of species changing in the directions expected from climate change, with the authors concluding that LULCC, particularly habitat loss and fragmentation, was impeding wild species from effectively tracking climate change ( [[#Lenoir--2015|Lenoir and Svenning, 2015]] ; [[#Rumpf--2019|Rumpf et al., 2019]] ; [[#Lenoir--2020|Lenoir et al., 2020]] ).

Attribution is strong for species and species-interactions for which there is a robust mechanistic understanding of the role of climate on biological processes ''(high confidence)'' . Unprecedented outbreaks of spruce beetles occurring from Alaska to Utah in the 1990s were attributed to warm weather that, in Alaska, facilitated a halving of the insect’s life cycle from two years to one ( [[#Logan--2003|Logan et al., 2003]] ). Milder winters and warmer growing seasons were likewise implicated in poleward expansions and increasing outbreaks of several forest pests ( [[#Weed--2013|Weed et al., 2013]] ), leading to the current prediction that 41% of major insect pest species will further increase their damage as climate warms, and only 4% will reduce their impacts, while the rest will show mixed responses ( [[#Lehmann--2020|Lehmann et al., 2020]] ).

During their range shifts, forest pests remain climate-sensitive. For example, the distribution of the western spruce budworm is limited at its warm range edges by the adverse effects of mild winters on overwinter survival, and at its cool range by the ability to arrive at a cold-resistant stage before winter arrives ( [[#Régnière--2019|Régnière and Nealis, 2019]] ). We might therefore expect tree mortality from insect outbreaks to be most severe at sites climatically less suitable for the plants, where plants would be under more stress. However, ( [[#Jaime--2019|Jaime et al., 2019]] ), using separate species distribution models (SDMs) (MaxEnt) for the insects and plants, found that observed mortality of Scots pine from bark beetles was highest at sites that were most climatically suitable for the trees as well as for the insects. In a study of tree mortality in California, bark beetles selectively killed highly stressed fir trees, but killed pines according to their size irrespective of stress status ( [[#Stephenson--2019|Stephenson et al., 2019]] ).

Range shifts in a poleward and upward direction, following expected trajectories according to local and regional climate trends, are strongly occurring in freshwater fish populations in North America ( [[#Lynch--2016b|Lynch et al., 2016b]] ), Europe ( [[#Comte--2013|Comte and Grenouillet, 2013]] ; [[#Gozlan--2019|Gozlan et al., 2019]] ) and Central Asia ( [[#Gozlan--2019|Gozlan et al., 2019]] ) ''(medium evidence, high agreement)'' . Cold-water fish, such as coregonids and smelt have been negatively affected at the equatorial borders of their distributions ( [[#Jeppesen--2012|Jeppesen et al., 2012]] ). Upward elevational range shifts in rivers and streams have been observed. Systematic shifts towards higher elevation and upstream were found for 32 stream-fish species in France following regional variation in climate change ( [[#Comte--2013|Comte and Grenouillet, 2013]] ). Bull trout ( ''Salvelinus confluentus'' ) in Idaho (USA), were estimated to have lost 11–20% (8–16% per decade) of the headwater stream lengths necessary for cold-water spawning and early juvenile rearing, with the largest losses occurring in the coldest habitats ( [[#Isaak--2010|Isaak et al., 2010]] ). Range contractions of the same species have been found in the Rocky Mountains watershed ( [[#Eby--2014|Eby et al., 2014]] ). Likewise, the distribution of the stonefly ''Zapada glacier'' , endemic to the alpine streams of the Glacier National Park in Montana (USA), has been reduced over several decades by an upstream retreat to higher, cooler sites as water temperatures have increased and glacial masses have decreased ( [[#Giersch--2015|Giersch et al., 2015]] ).

The melting of glaciers has led to a change in water discharge associated with community turnover in glacier-fed streams ( [[#Cauvy-Fraunié--2019|Cauvy-Fraunié and Dangles, 2019]] ). For instance, glacier-obligate macro-invertebrates have started disappearing when glacial cover drops below approximately 50% ( ''robust evidence'' , ''high agreement'' ), reviewed in ( [[#Hotaling--2017|Hotaling et al., 2017]] ). For freshwater invertebrates, no meaningful trends have been detected in geographic extent or population size for most species ( [[#Gozlan--2019|Gozlan et al., 2019]] ).

An invasive freshwater cyanobacterium in lakes, ''Cylindrospermopsis raciborskii'' , originating from the tropics, has spread to temperate zones over the last few decades due to the climate change-induced earlier increase of water temperature in spring ( [[#Wiedner--2007|Wiedner et al., 2007]] ), aided by a competitive advantage in eutrophic systems ( [[#Ekvall--2013|Ekvall et al., 2013]] ; [[#Urrutia-Cordero--2016|Urrutia-Cordero et al., 2016]] ).

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<span id="observed-local-population-and-global-species-extinctions-driven-by-climate-change"></span>
==== 2.4.2.2 Observed Local Population and Global Species’ Extinctions Driven by Climate Change ====

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Disappearances of local populations within a species range are more frequent and better documented than whole species’ extinctions, and attribution to climate change is possible for sites with minimal confounding non-climatic stressors. Changes of temperature extremes are often more important to these local extinction rates than changes of mean annual temperature ''(high confidence)'' (see Sections 2.3.1, 2.3.2, 2.3.3.5, 2.4.2.6, Cross-Chapter Box EXTREMES in this chapter) ( [[#Parmesan--2013|Parmesan et al., 2013]] ). A global meta-analysis of 236 species of birds, mammals, amphibians, fish, invertebrates and plants across 132 independent studies found that changes in population abundances were strongly related to temperature variability globally, and significantly related to precipiation variability in lower latitudes ( [[#Pearce-Higgins--2015|Pearce-Higgins et al., 2015]] ). In a global study of 538 diverse plant and animal species, sites with local extinctions were associated with smaller changes of mean annual temperature but larger and faster changes of hottest yearly temperatures than sites where populations persisted ( [[#Román-Palacios--2020|Román-Palacios and Wiens, 2020]] ). Near warm range limits, 44% of species had suffered local extinctions. In both temperate and tropical regions, sites with local extinction had greater increases in maximum temperatures than those without: a T max increase of 0.456°C and 0.316°C versus a T mean increase of 0.153°C and 0.061°C for temperate ( ''n'' = 505 sites) and tropical ( ''n'' = 76 sites), respectively (P &lt; 0.001) ( [[#Román-Palacios--2020|Román-Palacios and Wiens, 2020]] ).

[[#Wiens--2016|Wiens (2016)]] assumed that population extinctions were primarily driven by climate change when they occurred at elevational or latitudinal ‘warm edge’ range limits, and were at relatively undisturbed sites stated by the authors to be under increasing climatic stress. By this criterion, climate-caused local extinctions were widespread among plants and animals globally, detected in 47% of 976 species examined. The percentage of species suffering these extinctions was higher in the Tropics (55%) than in temperate habitats (39%), higher in freshwater (74%) than in marine (51%) or terrestrial (46%) habitats, and higher in animals (50%) than in plants (39%). The difference between plants and animals varied with latitude; in the temperate zone, a much higher proportion of animals than plants suffered range-limit extinctions (38.6% of 207 animal species vs. 8.6% of 105 plants, P &lt; 0.0001) while at tropical sites, local extinction rates were (nonsignificantly) higher in plants (59% of 155 species) than in animals (52% of 349 species), the reverse of their temperate-zone relationship. Rates varied across animal groups from 35% in mammals, to 43% in birds, 56% in insects and 59% in fish ( [[#Wiens--2016|Wiens, 2016]] ).

Freshwater population extinctions are mainly due to habitat loss, the introduction of alien species, pollution, over-harvesting ( [[#Gozlan--2019|Gozlan et al., 2019]] ; [[#IPBES--2019|IPBES, 2019]] ) and climate change-induced epidemic diseases ( [[#Pounds--2006|Pounds et al., 2006]] )(see [[#2.4.2.7.1|Section 2.4.2.7.1]] ). Climate warming, particularly through the intensification and severity of droughts, contributes to the disappearance of small ponds which hold rare and endemic species ( [[#Bagella--2016|Bagella et al., 2016]] ). Systematic data on the extent and biology of small ponds is, however, lacking on the global scale. Extreme heat waves can lead to large local fish kills in lakes (see [[#2.3.3|Section 2.3.3.5]] ), when water temperature and oxygen concentrations surpass critical thresholds and threatening cold-water fish and amphibians ( [[#Thompson--2012|Thompson et al., 2012]] ). Evidence of a local extinction of some invertebrate species with a 1.4°C–1.7°C rise in mean annual stream winter temperature from 1981 to 2005 was reported in [[#Abrahams--2013|Abrahams et al. (2013)]] . Population declines of specialist species in glacier-fed streams, such as the non-biting midge ''Diamesa davisi'' (Chironomidae), can be attributed to climate-change-driven glacier retreat ( [[#Cauvy-Fraunié--2019|Cauvy-Fraunié and Dangles, 2019]] ), and the flatworm ''Crenobia alpina'' (Planariidae) has been reported as locally extinct in the Welsh Llyn Brianne river ( [[#Durance--2010|Durance and Ormerod, 2010]] ; [[#Larsen--2018|Larsen et al., 2018]] ).

Many high montane possums in Australia have low physiological tolerance to heat waves, with death occuring due to heat-driven dehydration at temperatures exceeding 29°C–30°C for &gt;4–5 h over several days ( [[#Meade--2018|Meade et al., 2018]] ; [[#Turner--2020|Turner, 2020]] ). Major declines have been recorded for several species, population extinctions have occured at lower elevations since the early 2000s, and the white sub-species of the lemuroid ringtail possum ( ''Hemibelideus lemuroides'' ) in Queensland, Australia, disappeared after heat waves in 2005 ( ''high confidence'' ): intensive censuses found only 2 individuals in 2009 ( [[#Chandler--2014|Chandler, 2014]] ; [[#Weber--2021|Weber et al., 2021]] ).

Two terrestrial and freshwater species have become extinct in the wild, with climate change implicated as a key driver. The cloud forest-restricted golden toad ( ''Incilius periglenes'' ) was extinct by 1990 in a nature preserve in Costa Rica, driven by successive extreme droughts. This occurred in the absence of chytridiomycosis infection, caused by the fungal pathogen Bd, verified during field censuses of golden toad populations in the process of extinction as well as genetic analyses of museum specimens, although Bd was present in other frog species in the region ( ''medium evidence'' , ''high agreement'' ) ( [[#Pounds--1999|Pounds et al., 1999]] ; [[#Pounds--2006|Pounds et al., 2006]] ; [[#Puschendorf--2006|Puschendorf et al., 2006]] ; [[#Richards-Hrdlicka--2013|Richards-Hrdlicka, 2013]] ). The interaction between expansion of chytrid fungus globally and local climate change is implicated in the extinction of a wide range of tropical amphibians ''(high confidence)'' (see [[#2.4.2.7.1|Section 2.4.2.7.1]] Case Study 2 Chytrid fungus and climate change).

The BC melomys ( ''Melomys rubicola'' ), the only mammal endemic to the Great Barrier Reef, inhabited a small (5-hectare) low-lying (&lt;3-m-high) cay in the Torres Strait Islands, Australia. Recorded as having a population size of several hundred in 1978, this mammal has not been seen since 2009 and was declared extinct in 2016 ( [[#Gynther--2016|Gynther et al., 2016]] ). SLR and documented increases in storm surge and in tropical cyclones, driven by climate change, led to multiple inundations of the island in the 2000s. Between 1998 and 2014, herbacious vegetation, the food resource for the BC melomys, declined by 97% in area (from 2.2 down to 0.065 hectares), and from 11 plant species down to two ( [[#Gynther--2016|Gynther et al., 2016]] ; [[#Watson--2016|Watson, 2016]] ; [[#Woinarski--2016|Woinarski, 2016]] ; [[#Woinarski--2017|Woinarski et al., 2017]] ). The island was unihabited with few non-climatic threats, providing ''high confidence'' in the attribution of extinction of the BC melomys to climate change-driven increases in the frequency and duration of island inundation ( [[#Turner--2007|Turner and Batianoff, 2007]] ; [[#Woinarski--2014|Woinarski et al., 2014]] ; [[#Gynther--2016|Gynther et al., 2016]] ; [[#Watson--2016|Watson, 2016]] ; [[#Woinarski--2017|Woinarski et al., 2017]] ).

In the IUCN Red List ( [[#IUCN--2019|IUCN, 2019]] ), 16.2% of terrestrial and freshwater species ( ''n'' = 3,777 species) that are listed as endangered, critically endangered or extinct in the wild ( ''n'' = 23,251 species) list climate change or severe weather as one of their threats.

In summary, local population extinctions caused by climate-change-driven increases in extreme weather and climate events have been widespread among plants and animals ''(very high confidence),'' and the first clear documentations of entire species driven extinct by recent climate change is emerging ''(medium confidence).''

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<span id="observed-changes-in-community-composition-driven-by-climate-change"></span>
==== 2.4.2.3 Observed Changes in Community Composition Driven by Climate Change ====

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===== 2.4.2.3.1 Overall patterns of community change =====

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The most common type of community change takes the form of ''in situ'' decreases in cold-adapted species and increases in warm-adapted species ( [[#Bowler--2017|Bowler et al., 2017]] ; [[#Hughes--2018|Hughes et al., 2018]] ; [[#Kuhn--2019|Kuhn and Gégout, 2019]] ; [[#Feeley--2020|Feeley et al., 2020]] ). This process has lead to increases of species richness on mountaintops and decreased richness at adjacent lower elevations ( ''medium evidence'' , ''high agreement'' ) ( [[#Forister--2010|Forister et al., 2010]] ; [[#Steinbauer--2018|Steinbauer et al., 2018]] ). While it is also expected from observed range shifts of individual species that species richness should increase along tropical/temperate ecotones and along temperate/boreal ecotones, to date this has not been well documented. Lewthwaite et al ( [[#Lewthwaite--2022|Lewthwaite and Mooers, 2022]] ) documented a small increase in local richness across Canada for 265 species of butterflies, but the stronger effect was an homogenization across the region, with generalist species generally expanding into new sites and leading to lower Beta-diversity (lower diversity among sites). In a study of 66 bumble bee species across North America and Europe, Soroye et al ( [[#Soroye--2020|Soroye et al., 2020]] ) did not find the expected pattern, with most sites, regardless of latitude, declining in species richness, even when individual species benefited from warming or increased precipitation at some sites. Observed shifts in community composition have consequences for species’ interactions. Such indirect effects of climate change have been shown to often have greater impacts on species than the direct effects of climate itself, particularly for higher-level consumers ( [[#Cahill--2013|Cahill et al., 2013]] ; [[#Ockendon--2014|Ockendon et al., 2014]] ).

Analyses indicated that responses in range shifts and timing were lagging behind the changes expected from regional warming. This type of lag, where biological response is less than expected from known underlying physiology or general climatic limits, is called ‘climate debt’. Examples of climate debt, measured from community composition changes, come from birds and butterflies in Europe ( [[#Devictor--2012|Devictor et al., 2012]] ) and lowland forest herbaceous plants in France ( [[#Bertrand--2011|Bertrand et al., 2011]] ). The French study found that larger debts occurred in communities with warmer baseline conditions and that some of the apparent debt stemmed from the ability of species to tolerate warming ''in situ'' , so no range shift was observed.

Prominent changes in freshwater community composition, such as increases in cyanobacteria and warm-tolerant zooplankton species, the loss of cold-water fish, gains in thermo-tolerant fish, macro-invertebrates, and floating macrophytes, are occurring ( ''medium evidence'' , ''high agreement'' , ''medium confidence'' ) ( [[#Adrian--2016|Adrian et al., 2016]] ; [[#Hossain--2016|Hossain et al., 2016]] ; [[#Short--2016|Short et al., 2016]] ; [[#Huisman--2018|Huisman et al., 2018]] ; [[#Gozlan--2019|Gozlan et al., 2019]] ). Geothermal streams have provided evidence about community structure and ecosystem function at high temperatures. A study of 14 such habitats reported simplified food web structures and shortened pathways of energy flux between consumers and resources ( ''high confidence'' ) ( [[#O’Gorman--2019|O’Gorman et al., 2019]] ). Changes in the relative abundance of species, species composition and biodiversity due to warming trends, and non-climate-driven changes are to be expected in lakes and rivers globally. However, thus far, empirical evidence and mechanistic understanding to inform modelling is too limited to draw general conclusions about the nature of current and future climate change-driven changes within entire food webs on a global scale ( [[#Urban--2016|Urban et al., 2016]] ).

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===== 2.4.2.3.2 Freshwater systems: mechanistic drivers and responses =====

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Physical changes in lakes (see [[#2.3.3|Section 2.3.3]] ) have affected primary production (see [[#2.4.4.5|Section 2.4.4.5.2]] ), algal-bloom formation and composition, zooplankton and fish size distribution, and species composition ( [[#Urrutia-Cordero--2017|Urrutia-Cordero et al., 2017]] ; [[#Gozlan--2019|Gozlan et al., 2019]] ; [[#Seltmann--2019|Seltmann et al., 2019]] ). Declines in the abundance of cold-stenothermal species, particularly the Arctic charr ( ''Salvelinus alpinus'' ), coregonids and smelt, and increases in eurythermal fish (e.g., the thermo-tolerant carp ''Cyprinus carpio'' , common bream, pike perch, roach and shad) have been observed in northern temperate lakes associated with warming trends ( ''medium evidence, high agreement'' ) ( [[#Jeppesen--2012|Jeppesen et al., 2012]] ; [[#Jeppesen--2014|Jeppesen et al., 2014]] ). These changes increase predation pressure on zooplankton and reduce grazing pressure on phytoplankton, which may result in higher phytoplankton biomass ( [[#De%20Senerpont%20Domis--2013|De Senerpont Domis et al., 2013]] ; [[#Jeppesen--2014|Jeppesen et al., 2014]] ; [[#Adrian--2016|Adrian et al., 2016]] ). Reduction in lake mixing lowers the concentration of nutrients in the epilimnion and may lead to higher silicon-to-phosphorous ratios that negatively affect diatom growth ( [[#Yankova--2017|Yankova et al., 2017]] ) or overall primary productivity (see [[#2.4.4.5|Section 2.4.4.5.2]] ).

In a study of 1567 lakes across Europe and North America, [[#Kakouei--2021|Kakouei (2021)]] identified climate change as the major driver of increases in phytoplankton biomass in remote areas with minimal LULCC. Greater temperature variability can be more important than long-term temperature trends as a driver of zooplankton biodiversity ( [[#Shurin--2010|Shurin et al., 2010]] ). Reductions of winter severity attributed to anthropogenic climate change are increasing winter algal biomass, and motile and phototropic species, at the expense of mixotrophic species ( [[#Özkundakci--2016|Özkundakci et al., 2016]] ; [[#Hampton--2017|Hampton et al., 2017]] ).

Tropical lakes are prone to loss of deep-water oxygen due to lake warming, with negative consequences for their fisheries and their biodiversity ( [[#Lewis%20Jr--2000|Lewis Jr, 2000]] ; [[#Van%20Bocxlaer--2012|Van Bocxlaer et al., 2012]] ). Many ancient tropical lakes (Malawi, Tanganyika, Victoria, Titicaca, Towuti and Matano) hold thousands of endemic animal species ( [[#Vadeboncoeur--2011|Vadeboncoeur et al., 2011]] ).

Observed effects of climate change on freshwater invertebrates are variable ( [[#Knouft--2017|Knouft and Ficklin, 2017]] ). In glacier-fed streams globally, climate change has caused community turnover and changes in abundances in terms of increased generalist and decreased specialist species ( [[#Lencioni--2018|Lencioni, 2018]] ; [[#Cauvy-Fraunié--2019|Cauvy-Fraunié and Dangles, 2019]] ). In turn, dragonflies in flowing waters, monitored during the warming period from 1988 through 2006 in Europe, did not show consistent changes in their distribution ( [[#Grewe--2013|Grewe et al., 2013]] ), reviewed in Knouft and Ficklin (2017). Long-term trends in the species composition and community structure of stream macro-invertebrates, specifically a general trend for decreases in species characteristic of cold, fast-flowing waters and increases of thermophilic species typical of stagnant or slow-moving waters, have been attributed to climate change ( ''robust evidence, high agreement'' ) ( [[#Daufresne--2007|Daufresne et al., 2007]] ; [[#Chessman--2015|Chessman, 2015]] ). A study of 14 geothermal streams reported simplified food web structures and shortened pathways of energy flux between consumers and resources ( [[#O’Gorman--2019|O’Gorman et al., 2019]] ). Macrophytes benefit from rising water temperatures, but increased shading from increased phytoplankton biomass could offset this ( [[#Hossain--2016|Hossain et al., 2016]] ; [[#Short--2016|Short et al., 2016]] ; [[#Zhang--2017a|Zhang et al., 2017a]] ).

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<span id="emergence-of-novel-communities-and-invasive-species"></span>
===== 2.4.2.3.3 Emergence of novel communities and invasive species =====

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As climate change is increasing the movements of species into new areas, there is concern about how exotic species are being impacted, either by becoming invasive or by already invasive species gaining even more advantage over native species. Modelling predicts that the effects of climate warming on food web structure and stability favour the success of invading species ( [[#Sentis--2021|Sentis et al., 2021]] ). Both simulated warming experiments ( [[#Zettlemoyer--2019|Zettlemoyer et al., 2019]] ) and long-term observations ( [[#Willis--2010|Willis et al., 2010]] ) have found phenologies of exotic species to respond more adaptively to warming than those of natives; in the long-term observations, the success of exotics was attributed to their greater phenological responsiveness. In an expert assessment of the future relative importance of different drivers of the impacts of biological invasions, climate change was named as the most important driver in polar regions, second-most important in temperate regions (after trade/transport), and third-most important in the tropics (after trade/transport and human demography/migration) ( [[#Essl--2020|Essl et al., 2020]] ).

However, not all exotic species become invasive. As novel climate conditions develop, novel communities made up of new combinations of species are emerging as populations and species adapt and shift their ranges differentially, not always with negative consequences ( ''high confidence'' ) ( [[#Dornelas--2014|Dornelas et al., 2014]] ; [[#Evers--2018|Evers et al., 2018]] ; [[#Teixeira--2020|Teixeira and Fernandes, 2020]] ). Novel communities differ in composition, structure, function and evolutionary trajectories, as the proportions of specialists and generalists, native, introduced and range-shifting species change and species interactions are altered, ultimately affecting ecosystem dynamics and functioning ( [[#Lurgi--2012|Lurgi et al., 2012]] ; [[#Hobbs--2014|Hobbs et al., 2014]] ; [[#Heger--2019|Heger and van Andel, 2019]] ). The exact nature of novel communities is difficult to predict because species-level uncertainties propagate at the community level due to ecological interactions ( [[#Williams--2007|Williams and Jackson, 2007]] ). However, observations, experimental mesocosms ( [[#Bastazini--2021|Bastazini et al., 2021]] ), and theoretical models ( [[#Lurgi--2012|Lurgi et al., 2012]] ; [[#Sentis--2021|Sentis et al., 2021]] ) provide support that novel communities will continue to emerge with climate change ''(medium confidence)'' .

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<span id="observed-phenological-responses-to-climate-change"></span>
==== 2.4.2.4 Observed Phenological Responses to Climate Change ====

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Since AR5, the number of studies of changes in phenology (timing of biological events) has increased substantially, aided by advances in remote sensing ( [[#Piao--2019|Piao et al., 2019]] ). Phenological studies have documented particularly consistent conclusions on responses of plants and animals to warming, including the advancement of spring events and the lengthening of growing seasons in temperate regions (via a combination of advancement of spring events and, to a lesser extent, the retardation of autumn events) ( ''robust evidence'' , ''high agreement'' ) (Table 2.2, Table 2.3, Table SM2.1) ( [[#Menzel--2020|Menzel et al., 2020]] ). In the Tropics, by contrast, changes in precipitation have more strongly influenced animal phenology than have temperature changes ( [[#Cohen--2018|Cohen et al., 2018]] ). A meta-analysis compared observed phenological advances in birds with expectations due to warming local climates, and concluded that the observed advances fell short of what was expected and that a substantial phenological climate debt had been generated ( [[#Radchuk--2019|Radchuk et al., 2019]] ).

Taxonomic groups have differed in their responses ( [[#Parmesan--2007|Parmesan, 2007]] ; [[#Thackeray--2010|Thackeray et al., 2010]] ), and a few have completely diverged from general trends. For example, seabirds continue to breed with their pre-climate-change phenologies ( [[#Keogan--2018|Keogan et al., 2018]] ). Newer reviews and analyses reveal differences in responses across continents and time intervals ( [[#Piao--2019|Piao et al., 2019]] ). Mean advance in days per decade for plants was 5.5 in China and 3.0–4.2 in Europe, but only 0.9 in North America ( [[#Piao--2019|Piao et al., 2019]] ). Mean values for the retardation of autumn leaf fall, which can be more influenced by photoperiod and less by temperature than spring leaf-out, were 0.36 days per decade in Europe ( [[#Menzel--2020|Menzel et al., 2020]] ), 2.6 days per decade in China and around 3 days per decade in the USA ( ''medium evidence'' , ''high agreement'' ) ( [[#Piao--2019|Piao et al., 2019]] ).

The rapid rate of the advancement of spring events in the 1990s slowed down in the 2000s, and stalled or even reversed in some regions ( [[#Menzel--2020|Menzel et al., 2020]] ). [[#Wang--2019|Wang et al. (2019)]] noted, from remote sensing, that during the ‘global warming hiatus’ from 1998 to 2012, there were no global trends in either spring green-up or autumn colouring. Annual crops, the timing of which is determined by farmers, were an exception. When natural systems were advancing fast prior to 1998, farmers advanced more slowly, but during the natural ‘hiatus’, farmed crops advanced faster than wild plants and cultivated trees ( [[#Menzel--2020|Menzel et al., 2020]] ). In a long (67 years) European time series ( [[#Menzel--2020|Menzel et al., 2020]] ), autumn leaf colouring showed delays attributed to winter and spring warming in 57% of observations (mean delay of 0.36 days per decade); spring and summer phenologies advanced in 89% of wild plants, despite decreased winter chilling, with around 60% of trends significant and ‘strongly attributable’ to winter and spring warming; and the growing season lengthened in 84% of cases (mean lengthening 0.26 days yr -1 ) (Table 2.2).

'''Table 2.2 |''' Global fingerprints of climate change impacts across wild species. (Updated from ( [[#Parmesan--2015|Parmesan and Hanley, 2015]] ). For each study for which data were made available, a response for an individual species or functional group was classified as (1) no response (i.e., no significant change in the measured trait over time), (2) if a significant change was found, the response was classified as either consistent or not consistent with expectations according to local or regional climate trends. Percentages are approximate and estimated for the studies as a whole. Individual analyses within the studies may differ. The specific metrics of climate change analysed for associations with biological change vary somewhat across studies, but most use changes in local or regional temperatures (e.g., mean monthly T or mean annual T), with some using precipitation metrics (e.g., total annual rainfall). For example, a consistent response would be poleward range shifts in areas that are warming. Probability (P) of getting the observed ratio of consistent-to-not consistent responses by chance was &lt;10–13 for ( [[#Parmesan--2003|Parmesan and Yohe, 2003]] ; [[#Root--2003|Root et al., 2003]] ; [[#Root--2005|Root et al., 2005]] ; [[#Poloczanska--2013|Poloczanska et al., 2013]] ) and &lt;0.001 for [[#Rosenzweig--2008|Rosenzweig et al. (2008)]] . The last collumn distinguishes studies that were designed for attribution to climate change (e.g. by analysing only long-term data from relatively undisturbed habitats (see section 2.1.3 and 2.4.1)( [[#Parmesan--2013|Parmesan et al., 2013]] ; [[#Cramer--2014|Cramer et al., 2014]] ) from those that analysed all available data, including data from areas highly-impacted by non-climate drivers (e.g. LULCC).

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

! '''N: total numbers of species, functional groups or studies'''

! '''Species in given system: Terrestrial (T) Marine (M) Freshwater (F)'''

! '''Types of change'''

! '''Changes documented'''

! '''Geographical region'''

! '''Study allows for attribution to climate change'''

|-
| colspan="7"| '''2.2a Observed phenological changes'''

|-
| ( [[#Parmesan--2003|Parmesan and Yohe, 2003]] )

| 677 species

| T: 461 plants, 168 birds, 35 insects; T/F: 9 amphibians; F: 2 fish

| Spring phenology

| Overall: 9% delay; 27% no trend; 62% advance

Mean change 2.3 days per decade advance

| Global

| Yes

|-
| ( [[#Menzel--2006|Menzel et al., 2006]] )

| Agricultural crops, fruit trees, wild plants

| 100% T

| Spring and autumn phenology

| From 1971 to 2000, 48% responding as expected; spring advance 2.5 days per decade, mean autumn delay 0.2 days per decade, fruit ripening 2.4 days per decade advance; farming activities 0.4 days per decade advance

| Europe

| Yes

|-
| ( [[#Parmesan--2007|Parmesan, 2007]] )

| 203 species

| T, F

| Spring phenology

| Overall advance 2.8 days per decade

20 changes (delays), 153 advances, 8 no change; significantly more advance at higher latitudes

| Global

| Yes

|-
| ( [[#Rosenzweig--2008|Rosenzweig et al., 2008]] )

| 55 studies (~100–200 species)

| T: 65%

M: 13%

F: 22%

| Various

| 90% of changes consistent with local/regional climate change

| Global

| Yes

|-
| ( [[#Thackeray--2010|Thackeray et al., 2010]] )

| 726 taxa

| T: birds, moths, aphids, terrestrial plants; M and F: phytoplankton

| Spring phenology

| 83.5% of ‘trends’ were advances; mean overall advance 3.9 days per decade; T plants 93% advancing, mean 5.8 days per decade; F plants 62% advancing, mean 2.3 days per decade; secondary consumers advanced less than primary consumers and producers

| UK

| No

|-
| ( [[#While--2014|While and Uller, 2014]] )

| 59 populations, 17 studies

| T/F, 100% Amphibians

| Phenology

| 35% statistically significant change; mean advance 6.1 ± 1.65 days per decade; range 17.5 days delay to 41.9 days advance; 65% ( ''n'' = 47 populations) found significant relationship between breeding phenology and temperature; higher latitudes advanced more

| Global

| No

|-
| ( [[#Gill--2015|Gill et al., 2015]] )

| 64 studies

| T: 100%

trees

| Delay of autumn senescence

| Delay averaged 0.33 days yr -1 and 1.20 days per degree Celsius warming; more delay at low latitudes across Northern Hemisphere; high-latitude species driven more by photoperiod than low-latitude species

| Global

| No

|-
| ( [[#Ficetola--2016|Ficetola and Maiorano, 2016]] )

| 66 studies of temperature effects;

15 of precipitation

| T/F 100% amphibians

| Phenology and abundances

| Population dynamics driven by precipitation while breeding phenology driven by temperature

| Global

| No

|-
| ( [[#Halupka--2017|Halupka and Halupka, 2017]] )

| 28 species multi-brooded, 27 species single-brooded, some species several populations

| T 100% (birds)

| Phenology: length of breeding season

| Shows differences in sign of response between single and multi-broods and migrants vs. residents; Season extended by 4 days per decade for multi-brooded, shortened by 2 days per decade for single-brooded;

Multi: 26 species; 15 of 34 populations significantly extended, none significantly reduced

| Northern Hemisphere

| Yes

|-
| ( [[#Kharouba--2018|Kharouba et al., 2018]] )

| 88 species in 54 pair-wise interactions

|
| T: changes in relative phenologies of consumers and their resources

| Asynchrony between consumers and resources has increased in some cases and decreased in others, with no significant trend; the prediction that asynchronies should be increasing in general is not supported.

| Global

| No

|-
| ( [[#Cohen--2018|Cohen et al., 2018]] )

| 127 studies

| T: 100% animals

| Phenological trends

| 81% of 127 studies of animals show phenological change in direction of earlier spring; some studies were multi-species.

Mean advance since 1950: 2.88 days per decade.

| Europe

North America

Australia

Japan

| No

|-
| ( [[#Keogan--2018|Keogan et al., 2018]] )

| 145 populations, 209 time series

| T: Seabirds breeding sites

| Phenological trends

| No change in breeding dates between 1952 and 2015

| Global

| Yes

|-
| ( [[#Radchuk--2019|Radchuk et al., 2019]] )

| 4835 studies, 1413 species

| T: animals; T/F amphibians

| Phenological trends

| Greatest phenological advancements in amphibians, followed by insects and birds, in this order.

| Global but most in Northern Hemisphere

| No

|-
| ( [[#Piao--2019|Piao et al., 2019]] )

| Review

| T: Plants

| Spring and autumn phenologies

| Rate of advance slowing down across Northern Hemisphere and reversed in parts of western North America in response to regional cooling since 1980s

| Global

| No

|-
| ( [[#Menzel--2020|Menzel et al., 2020]] )

| 53 species in Germany, 37 in Austria, 21 in Switzerland (includes overlaps)

| T: Plants

| Spring and autumn phenologies

| Long time series: 1951–2018. Autumn leaf colouring: mean delay 0.36 days per decade; spring phenology (leaf-unfolding) mean advance 0.24 days per decade; summer phenology (fruit ripening) mean advance 0.26 days per decade. Growing season length mean increase 0.26 days yr -1 but farming season length decreased by 0.02 days yr -1 .

| Europe

| Yes

|-
| colspan="7"| '''2.2b. Observed Changes In Distributions, Abundances And Local Population Extinctions'''

|-
| ( [[#Parmesan--2003|Parmesan and Yohe, 2003]] )

| 920 species

| T: 85.2%

M: 13.5%

F: 1.3%

| Distributions and abundances

| 50% of species (460/920) showed changes in distribution or abundances consistent with local or regional climate change

| Global

| Yes

|-
| ( [[#Root--2003|Root et al., 2003]] )

| 926 species

| T: 94%

M: 5.4%

F: 0.6%

| Distributions and abundances

| 52% of species (483/926) showed changes in distribution or abundances consistent with local or regional climate change

| Global

| Yes

|-
| ( [[#Rosenzweig--2008|Rosenzweig et al., 2008]] )

| 18 studies

| T: 65%

M: 13%

F: 22%

| Distributions and abundances

| 90% of studies showed changes in distribution or abundances consistent with local or regional climate change

| Global

| Yes

|-
| ( [[#Pöyry--2009|Pöyry et al., 2009]] )

| 48 species

| T: butterflies

| Range shifts

| From 1992 to 2004, 37 ranges shifted poleward, 9 shifted equatorially, 2 no change. Non-threatened species expanded poleward by 84.5 km, threatened species showed no significant change (&lt;2.1 km)

| Finland

| Yes

|-
| ( [[#Tingley--2009|Tingley et al., 2009]] )

| 53 species

| T: birds

| Elevational range shifts

| Resurvey (2003–2008) of historical elevational transects (1911–1929). 90.6% of species tracked their climate niche (temperature and/or precipitation) with regional climate change; Lower-elevation species (mean range centroid = 916 m) tracked only precipitation; high-elevation species (mean range centroid = 1944 m) tracked only temperature; species that tracked both temperature and precipitation had mid-elevation range centroids (1374–1841 m)

| California, USA

| Yes

|-
| ( [[#Chen--2011|Chen et al., 2011]] )

| 24 taxonomic group × region combinations for latitude, 31 for elevation

| T &gt;264

M &gt;10

F &gt;34

| Range shifts: elevation and latitude

| Mean upward elevation shift 11.0 m per decade

Poleward shift 16.9 km per decade

| Pseudo-global

| No

|-
| ( [[#Grewe--2013|Grewe et al., 2013]] )

| 90 species

| T/F Dragonflies

| Shifts of northern range boundaries

| 48 poleward shifts; 26 equatorial; 16 no change from 1988 to 2006

Southern lentic (standing water) species expanded 116 km polewards; southern lotic (running water) and all northern species stayed stable.

| Europe

| No

|-
| ( [[#Mason--2015|Mason et al., 2015]] )

| 21 animal groups, 1573 species

| T: birds, Lepidoptera

T/F: Odonates

| Range shifts in 3 time periods

| Northward shifts 23 km per decade (1966–1975) and 18 km per decade (1986–1995), with significant differences among taxa in rates of change

| UK

| Yes

|-
| ( [[#Gibson-Reinemer--2015|Gibson-Reinemer and Rahel, 2015]] )

| 13 studies, 273 species:

Plants, birds, mammals, marine inverterbrates

| T and M

| Range shifts in 2 or 3 areas for each species;

shift measured as change of limit or centroid

| 50% shifts of cold limits inconsistent with each other within species despite similar warming; species showing inconsistent shifts (including stable vs. directional or different directions) = 47% plants, 54% birds, 46% marine invertebrates, 60% mammals. Large difference in magnitude of range shifts when in same direction (mean difference 8.8 times)

| Global

| No

|-
| ( [[#Ficetola--2016|Ficetola and Maiorano, 2016]] )

| 66 studies of temperature effects; 15 studies of precipitation effects

| T/F 100% (amphibians)

| Phenology and abundances

| Population dynamics driven by precipitation, breeding phenology driven by temperature

| Global

| No

|-
| ( [[#Scheffers--2016|Scheffers et al., 2016]] )

| 94 ecological processes

| T, F, M

| All possible types and levels of ecological change

| 82% of ecological processes affected by climate change

| Global

| No

|-
| ( [[#Wiens--2016|Wiens, 2016]] )

| 976 species

| T, F, M

| Population extinction rates near warm latitudinal and elevational range limits

| 47% of species suffered climate-related local extinctions: fish 59%, insects 56%, birds 44%, plants 39%, amphibians 37%, mammals 35%

| Global

| Yes

|-
| ( [[#Bowler--2017|Bowler et al., 2017]] )

| 1167 populations, 22 communities

| T: 48%

M: 61%

F: 35%

| Abundance;

population trends

| T species with warm-temperature preference performed better than cool preferers; F and M species: no effect of temperature preference on performance; 47% of species with significant abundance changes: 61% M, 48% T, 35% F

| Europe

| Yes

|-
| ( [[#Pacifici--2017|Pacifici et al., 2017]] )

| 873 mammals, 1272 birds

| T: 100% (birds and mammals)

| Multiple: range change, abundance, reproductive rate, survival, body mass

| Estimated negative impacts (range contraction, reduced reproductive rates or other measures of fitness estimates) for IUCN-threatened species based on actual observed change in more common, related species; 47% threatened mammals and 23% birds negatively impacted by climate change in part of their ranges

| Global for birds; mammals North America

| Unclear (complex methods)

|-
| ( [[#MacLean--2017|MacLean and Beissinger, 2017]] )

| 21 studies

26 assemblages of taxonomically related species

| T: Plants and animals

| Range shifts in latitude and altitude related to species’ traits: dispersal, body size, habitat, diet specialization and historic range limit

| High-latitude/altitude range boundaries shifted less than lower-latitude/altitude boundaries. Author explanation is that habitat limits were reached (e.g., mountain tops). Magnitudes of shifts positively related to dispersal traits and habitat breadth.

| Global

| No

|-
| ( [[#Ralston--2017|Ralston et al., 2017]] )

| 46 species

| T: Birds

| Shifts in climate niche breadth, filling of climate space and overall abundance

| Species increasing in abundance were also increasing breeding climate niche breadth and niche filling. Declining species were opposite: niche breadths narrowing and greater climate debt.

| North America

| No

|-
| ( [[#Rumpf--2019|Rumpf et al., 2019]] )

| 1026 species

| T: plants, invertebrates, vertebrates

| Comparison of rates of range limit shift at leading and trailing elevational edges

| No difference in mean rate of shift of leading and trailing edges; elevational range sizes not changing systematically. Greater lags in regions with faster warming.

| Global

| No

|-
| ( [[#Freeman--2018|Freeman et al., 2018]] )

| 975 species, 32 elevational gradients

| T: plants, endotherms, ectotherms

| Comparison of rates of range limit shift at leading and trailing elevational edges

| Mean change at warm limit 92 ± 455 m per degree Celsius; cool limit 131 ± 465 m per degree Celsius; (± SD, not significantly different from each other). Available area and range sizes decreased for mountaintop species.

| Global

| No

|-
| ( [[#Anderegg--2019|Anderegg et al., 2019]] )

| Meta-analysis

50 studies, &gt;100 species

| T: 100% woody plants

| Mortality at dry range edges

| 100 individual species + a community of 828 species

mortality at range edges due to drought was 33% greater than for core populations

| Apparently global

| Yes;

drought not warming

|-
| ( [[#Román-Palacios--2020|Román-Palacios and Wiens, 2020]] )

| 10 studies, 538 species, 581 sites

| T: plants and animals

| Analysis for drivers of population extinctions at warm range edges

| 44% of species had suffered local population extinctions near warm-range limits. In temperate regions, sites with local extinction had greater increases in maximum temperature than those without (0.456°C vs. 0.153°C, P &lt; 0.001, ''n'' = 505 sites) and smaller increases in mean temperatures (0.412°C vs. 1.231°C, P &lt; 0.001). In tropical regions, range edges with local extinction also had greater increases in maximum temperatures (0.316°C vs. 0.061°C, P &lt; 0.001, ''n'' = 76), but changes in mean temperatures were similar between edges with and without extinctions (0.415°C vs. 0.406°C, P = 0.9)

| Global

| Yes

|}

Changes in freshwater systems are consistent with changes in terrestrial systems: earlier development of phytoplankton and zooplankton and earlier spawning by fish in spring as well as extension of the growing season are occurring ( ''robust evidence'' , ''high agreement'' ) ( [[#Adrian--2009|Adrian et al., 2009]] ; [[#De%20Senerpont%20Domis--2013|De Senerpont Domis et al., 2013]] ; [[#Adrian--2016|Adrian et al., 2016]] ; [[#Thackeray--2016|Thackeray et al., 2016]] ). Phenological changes in lakes have been related to rising water temperatures, reduced ice cover and prolonged thermal stratification (increasing evidence and agreement since AR5; ''very high confidence'' ). Crozier and Hutchings (2014) reviewed the phenological changes in fish and documented that changes in the timing of migration and reproduction, age at maturity, age at juvenile migration, growth, survival and fecundity were associated primarily with changes in temperature. The median return time of Atlantic salmon to rivers in Newfoundland and Labrador advanced by 12–21 days over the past decades, associated with overall warmer conditions ( [[#Dempson--2017|Dempson et al., 2017]] ).

<div id="2.4.2.5" class="h3-container"></div>

<span id="observed-complex-phenological-and-range-shift-responses"></span>
==== 2.4.2.5 Observed Complex Phenological and Range Shift Responses ====

<div id="h3-11-siblings" class="h3-siblings"></div>

Early meta-analyses tested the straightforward hypotheses that warming should shift timing earlier and ranges polewards. Once these trends had been established ( [[#IPCC--2014b|IPCC, 2014b]] ; [[#Parmesan--2015|Parmesan and Hanley, 2015]] ), exceptions to them became a focus of study. For example, in northern regions of the Northern Hemisphere, the spring flowering of some plants was delayed instead of being advanced as to be expected with warming ( [[#Cook--2012a|Cook et al., 2012a]] ; [[#Cook--2012b|Cook et al., 2012b]] ; [[#Legave--2015|Legave et al., 2015]] ). These turned out to be species requiring vernalisation (winter chilling) to speed their development in spring ( [[#Ettinger--2020|Ettinger et al., 2020]] ). For these plants, phenological changes result from the combined effects of advancement caused by spring warming and retardation caused by winter warming. Incorporating this level of complexity into analyses revealed that a greater proportion of species was responding to climate change than estimated according to the simple expectation that warming would always cause advancement (92% responding versus 72% from earlier analyses) ( [[#Cook--2012b|Cook et al., 2012b]] ).

Animal species can show vernalisation equivalent to that in plants ( [[#Stålhandske--2017|Stålhandske et al., 2017]] ). However, a semi-global meta-analysis of terrestrial animals failed to detect the delaying effects of warming winters ( [[#Cohen--2018|Cohen et al., 2018]] ). The same animal-based meta-analysis contrasted phenological changes in temperate-zone animals, which are principally explained by changes in temperature, with those at lower latitudes, which tend to follow changes in precipitation ( [[#Cohen--2018|Cohen et al., 2018]] ).

Vitasse et al. (2018), working with alpine trees, found that phenological delay with increasing elevation had declined from 34 days/1000 m in 1960 to 22 days/1000 m in 2016, greatly reducing the differences in timing between trees growing at different elevations. This reduction was greatest after warmer winters, suggesting that winter warming is a principal cause of the overall trend.

[[#Lian--2020|Lian et al. (2020)]] observed that earlier spring leaf-out in the Northern Hemisphere is causing increases in evapotranspiration that are not fully compensated by increased precipitation. The consequence is a greater soil moisture deficit in summer, expected to exacerbate impacts of heat waves as well as drought stress. In Arctic freshwater ecosystems, [[#Heim--2015|Heim et al. (2015)]] demonstrated the importance of seasonal cues for fish migration, which can be impacted by climate change due to reduced stream connectivity and fragmentation, earlier peak flows and increased evapotranspiration.

Precipitation has also been implicated in exceptions to the rule that ranges should be shifting to higher elevations. In dry climates, increases in precipitation accompanying climate warming can facilitate downslope range shifts ( [[#Tingley--2012|Tingley et al., 2012]] ).

Multiple responses can co-occur. [[#Hällfors--2021|Hällfors et al. (2021)]] , in a study of 289 Lepidoptera in Finland, found that, with warming, 45% had either shifted their range northward or advanced their flight season. The 15% of species that did both (shifting northward by 113.1 km and advancing their flight period by 2.7 days per decade, on average, over a 20-year period) had the largest population increases, and the 40% of species that showed no response had the largest population declines.

<div id="2.4.2.6" class="h3-container"></div>

<span id="observed-changes-to-physiology-and-morphology-driven-by-climate-change"></span>
==== 2.4.2.6 Observed Changes to Physiology and Morphology Driven by Climate Change ====

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

Impacts on species physiology in terrestrial and freshwater systems have been observed, and attributed to climate change ( ''medium confidence'' ). These include changes in tolerance to high temperatures ( [[#Healy--2012|Healy and Schulte, 2012]] ; [[#Gunderson--2015|Gunderson and Stillman, 2015]] ; [[#Deery--2021|Deery et al., 2021]] ), increased metabolic costs of living at elevated temperatures ( [[#Scheffers--2016|Scheffers et al., 2016]] ) and shifts in sex ratios in species with temperature-dependent sex determination. For example, warmer temperatures have driven the masculinisation of lizard populations ( [[#Schwanz--2008|Schwanz and Janzen, 2008]] ; [[#Schwanz--2016|Schwanz, 2016]] ; [[#Edmands--2021|Edmands, 2021]] ) and the feminisation of turtle populations ( [[#Telemeco--2009|Telemeco et al., 2009]] ). Skewed sex ratios can lead to mate shortages, reduced population growth, reduced adaptive potential and increased extinction risk, because genetic diversity decreases as fewer individuals mate and heterozygosity is lost ( [[#Mitchell--2010|Mitchell and Janzen, 2010]] ; [[#Edmands--2021|Edmands, 2021]] ).

Behavioural plasticity (flexibility) such as nest-site selection can provide a partial buffer from the effects of increasing temperature by placing the individual in a slightly cooler microclimate, but there are environmental and physical limits to this plasticity ( ''medium confidence'' ) ( [[#Refsnider--2016|Refsnider and Janzen, 2016]] ; [[#Telemeco--2017|Telemeco et al., 2017]] ). Plasticity in heat tolerance (e.g., due to reversible acclimation or acclimatisation) can also potentially compensate for rising temperatures ( [[#Angilletta%20Jr--2009|Angilletta Jr, 2009]] ), but ectotherms have relatively low acclimation in thermal tolerance and acclimation is expected to only slightly reduce the risk of overheating in even the most plastic taxa ( ''low confidence'' ) ( [[#Gunderson--2015|Gunderson and Stillman, 2015]] ).

Geographic variation in thermal tolerance plasticity is expected to influence the vulnerability and range shifts of species in response to climate change ( [[#Gunderson--2015|Gunderson and Stillman, 2015]] ; [[#Sun--2021|Sun et al., 2021]] ). In many ectotherms, plasticity in thermal tolerance increases polewards, as thermal seasonality increases ( [[#Chown--2004|Chown et al., 2004]] ), contributing to higher vulnerability to warming in tropical organisms ( ''low confidence'' ) ( [[#Huey--2009|Huey et al., 2009]] ; [[#Campos--2021|Campos et al., 2021]] ). Some species have evolved extreme upper thermal limits at the expense of plasticity, reflecting an evolutionary trade-off between these traits ( [[#Angilletta--2003|Angilletta et al., 2003]] ; [[#Stillman--2003|Stillman, 2003]] ). The most heat-tolerant species, such as those from extreme environments, may therefore be at a greater risk of warming because of an inability to physiologically adjust to thermal change ( ''low confidence'' ) ( [[#Bozinovic--2011|Bozinovic et al., 2011]] ; [[#Overgaard--2014|Overgaard et al., 2014]] ; [[#Magozzi--2015|Magozzi and Calosi, 2015]] ).

Physiological changes have observable impacts on morphology, such as changes in body size (and length of appendages), and colour changes in butterflies, dragonflies and birds ( ''medium confidence'' ) ( [[#Galeotti--2009|Galeotti et al., 2009]] ; [[#Karell--2011|Karell et al., 2011]] ). However, trends are not always linear or consistent across realms, taxonomic groups or geographic regions ( [[#Gotanda--2015|Gotanda et al., 2015]] ). Some morphological changes arise in response to environmental changes, rather than as the result of genetic adaptation or selection for an optimal body type. For example, dietary changes associated with climate change have led to changes in chipmunk skull morphology ( [[#Walsh--2016|Walsh et al., 2016]] ).

Decreased body size has been suggested as a general response of species to climate change in freshwater species, given the temperature-related constraints of metabolism with larger size. Reduced body size in response to global warming has been documented for freshwater bacteria, plankton and fish, as well as a shift towards smaller species ( [[#Daufresne--2009|Daufresne et al., 2009]] ; [[#Winder--2009|Winder et al., 2009]] ; [[#Jeppesen--2010|Jeppesen et al., 2010]] ; [[#Crozier--2014|Crozier and Hutchings, 2014]] ; [[#Jeppesen--2014|Jeppesen et al., 2014]] ; [[#Farmer--2015|Farmer et al., 2015]] ; [[#Rasconi--2015|Rasconi et al., 2015]] ; [[#Woodward--2016|Woodward et al., 2016]] ). However, the lack of systematic empirical evidence in fresh waters, and confounding effects such as interactions between temperature, nutrient availability and predation, limit generalisations in attributing observed body size changes to climate change ''(low confidence)'' ( [[#Pomati--2020|Pomati et al., 2020]] Nutrients).

Evidence is weak for a consistent reduction in body size across taxonomic groups in terrestrial animals ( ''low confidence'' ) ( [[#Siepielski--2019|Siepielski et al., 2019]] ). Decreased body size in warmer climates (as higher surface area-to-volume ratios maximise heat loss) is expected, based on biogeographic patterns such as Bergmann’s rule, but both increases and decreases have been documented in mammals, birds, lizards and invertebrates and were attributed to climate change ( [[#Teplitsky--2014|Teplitsky and Millien, 2014]] ; [[#Gotanda--2015|Gotanda et al., 2015]] ; [[#Gardner--2019|Gardner et al., 2019]] ; [[#Hill--2021|Hill et al., 2021]] ). Contrasting patterns (increased body size) may be due to short-term modifications in selection pressures (e.g., changes to predation and competition), variation in life histories or as a result of interactions with climate variables other than temperature (e.g., changes to food availability along with rainfall changes) and other disturbances ( [[#Yom-Tov--2004|Yom-Tov and Yom-Tov, 2004]] ; [[#Gardner--2019|Gardner et al., 2019]] ; [[#Wilson--2019|Wilson et al., 2019]] ) or use of different body size measurements (linear vs. volumetric dimensions) ( [[#Salewski--2014|Salewski et al., 2014]] ).

Several lines of evidence suggest the evolution of melanism in response to climate change ( ''low confidence'' ), with colour changes associated with thermoregulation being demonstrated in butterflies ( [[#Zeuss--2014|Zeuss et al., 2014]] ; [[#MacLean--2016|MacLean et al., 2016]] ; [[#MacLean--2019a|MacLean et al., 2019a]] ), beetles ( [[#de%20Jong--1998|de Jong and Brakefield, 1998]] ; [[#Brakefield--2011|Brakefield and de Jong, 2011]] ; [[#Zvereva--2019|Zvereva et al., 2019]] ), dragonflies ( [[#Zeuss--2014|Zeuss et al., 2014]] ) and phasmids ( [[#Nosil--2018|Nosil et al., 2018]] ). Such changes may represent decreased phenotypic diversity and, potentially, genetic diversity ( ''low confidence'' ), but the consequences of climate change for the genetic structure and diversity of populations have not been widely assessed ( [[#Pauls--2013|Pauls et al., 2013]] ). Simplistically, the thermal melanism hypothesis suggests that lighter (higher-reflectance) individuals should be fitter and therefore be selected for in a warmer climate ( [[#Clusella-Trullas--2007|Clusella-Trullas et al., 2007]] ). However, several biotic (e.g., thermoregulatory requirements, predator avoidance and signalling) and abiotic (e.g., UV, moisture and inter-annual variability) factors interact to influence changes in colour, making attribution to climate change across species and broad geographic regions difficult ( [[#Kingsolver--2015|Kingsolver and Buckley, 2015]] ; [[#Stuart-Fox--2017|Stuart-Fox et al., 2017]] ; [[#Clusella-Trullas--2020|Clusella-Trullas and Nielsen, 2020]] ).

Interactions between morphological changes and changes in phenology may facilitate or constrain adaptation to climate change ( ''medium confidence'' ) ( [[#Hedrick--2021|Hedrick et al., 2021]] ). For example, advancing phenology in migratory species may impose selection on morphological traits (e.g., wing length) to increase migration speed. If advancing spring phenology results in earlier breeding, this may offset the effect of rising temperatures in the breeding range and reduce the effect of increasing temperature on body size ( [[#Zimova--2021|Zimova et al., 2021]] ). A study of 52 species of North American migratory birds, based on &gt;70,000 specimens, showed that spring migration phenology has advanced over the past 40 years, concurrent with widespread shifts in morphology (reduced body size and increased wing length), perhaps to compensate for the increased metabolic cost of flight as body size decreases ( [[#Weeks--2020|Weeks et al., 2020]] ).

A lack of understanding of physiological constraints and mechanisms remains a barrier to predicting many of the ecological effects of climate change ( [[#Bozinovic--2011|Bozinovic et al., 2011]] ; [[#Vázquez--2017|Vázquez et al., 2017]] ; [[#González-Tokman--2020|González-Tokman et al., 2020]] ). Many behavioural, morphological and physiological responses are highly species- and context-specific, making generalisations difficult ( [[#Bodensteiner--2021|Bodensteiner et al., 2021]] ). Recent advances in mechanistic understanding (from experiments), in process-based modelling (including micro-climates and developmental processes) ( [[#Carter--2021|Carter and Janzen, 2021]] ) and in the sophistication of niche models ( [[#Kearney--2009|Kearney et al., 2009]] ) have improved projections, but comprehensive tests of geographic patterns and processes in thermal tolerance and plasticity are still lacking, with studies limited to a few phylogenetically restricted analyses showing mixed results ( [[#Gunderson--2015|Gunderson and Stillman, 2015]] ). Improved understanding of the mechanistic basis for observed geographic patterns in thermal tolerance and plasticity is needed to identify the physiological limits of species, the potential for adaptation and the presence of evolutionary trade-offs, which will strongly influence population declines, species range shifts, invasive interactions and the success of conservation interventions ( [[#Cooke--2021|Cooke et al., 2021]] ; [[#Ryan--2021|Ryan and Gunderson, 2021]] ).

<div id="2.4.2.7" class="h3-container"></div>

<span id="observed-impacts-of-climate-change-on-diseases-of-wildlife-and-associated-impacts-on-humans"></span>
==== 2.4.2.7 Observed Impacts of Climate Change on Diseases of Wildlife and Associated Impacts on Humans ====

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Assessment of changes in diseases of terrestrial and freshwater wild organisms was scarce in WGII AR4, AR5, IPCC SR1.5 and IPCC SRCCL. Further, most emerging infectious diseases (EIDs) are zoonoses, that is, they are transmissible between humans and animals, and are climate sensitive ( [[#Woolhouse--2001|Woolhouse et al., 2001]] ; [[#Woolhouse--2005|Woolhouse and Gowtage-Sequeria, 2005]] ; [[#McIntyre--2017|McIntyre et al., 2017]] ; [[#Salyer--2017|Salyer et al., 2017]] ). AR4 found weak-to-moderate evidence that disease vectors and their diseases had changed their distributions in concert with climate change, but attribution studies were lacking ( [[#Smith--2014|Smith et al., 2014]] ). In AR5, WGII AR5 Chapter 11 , geographic expansion of a few VBDs to higher latitudes and elevations were detected and associated with regional climate trends, but the non-climatic drivers were not well assessed, leading to a ''medium confidence'' in attribution ( [[#Smith--2014|Smith et al., 2014]] )). Here, we build on previous assessments by focussing on changes in the population dynamics and geographic distribution of diseases in wild animals as well as diseases in humans and domestic animals that are harboured, amplified and transmitted by wild animal reservoir hosts and vectors.

Increased disease incidence is correlated with regional climatic changes, as expected from a basic understanding of underlying biology and relationships between temperature, precipitation, and disease ecology ( ''robust evidence'' , ''high agreement'' ) ( [[#Norwegian%20Polar%20Institute--2009|Norwegian Polar Institute, 2009]] ; [[#Tersago--2009|Tersago et al., 2009]] ; [[#Tabachnick--2010|Tabachnick, 2010]] ; [[#Paz--2015|Paz, 2015]] ; [[#Dewage--2019|Dewage et al., 2019]] ; [[#Deksne--2020|Deksne et al., 2020]] ; [[#Shocket--2020|Shocket et al., 2020]] ; [[#Couper--2021|Couper et al., 2021]] ). Whether increases in diseases in wild and domestic animals correspond to an increased risk of disease in nearby human populations is complicated by the potential buffering effects of the local medical system, access to health care and the socioeconomic status, education, behaviours and general health of the human population (see also [[IPCC:Wg2:Chapter:Chapter-7|Chapter 7]] and Cross-Chapter Box ILLNESS in this chapter).

<div id="2.4.2.7.1" class="h4-container"></div>

<span id="direct-effects-of-climate-and-climate-change-on-reproduction-seasonality-the-length-of-the-growing-season-and-the-transmission-of-pathogens-vectors-and-hosts"></span>
===== 2.4.2.7.1 Direct effects of climate and climate change on reproduction, seasonality, the length of the growing season and the transmission of pathogens, vectors and hosts =====

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VBDs require arthropod vector hosts (e.g., insects or ticks), while other infectious diseases (e.g., fungi, bacteria and helminths) have free-living life stages and/or complex life cycles that require intermediate hosts (e.g., snails), all of which have temperature-driven rates of development and replication/reproduction ( ''robust evidence'' , ''high agreement'' ) ( [[#Mordecai--2013|Mordecai et al., 2013]] ; [[#Liu-Helmersson--2014|Liu-Helmersson et al., 2014]] ; [[#Moran--2014|Moran and Alexander, 2014]] ; [[#Bernstein--2015|Bernstein, 2015]] ; [[#Marcogliese--2016|Marcogliese, 2016]] ; [[#Ogden--2016|Ogden and Lindsay, 2016]] ; [[#Mordecai--2017|Mordecai et al., 2017]] ; [[#Short--2017|Short et al., 2017]] ; [[#Caminade--2019|Caminade et al., 2019]] ; [[#Cavicchioli--2019|Cavicchioli et al., 2019]] ; [[#Mordecai--2019|Mordecai et al., 2019]] ; [[#Liu--2020|Liu et al., 2020]] ; [[#Rocklöv--2020|Rocklöv and Dubrow, 2020]] ). Additionally, microbes such as bacteria thermally adapt to temperature changes through multiple mechanisms, indicating that warming will not reduce antibiotic resistance ( [[#MacFadden--2018|MacFadden et al., 2018]] ; [[#Pärnänen--2019|Pärnänen et al., 2019]] ; [[#Shukla--2019|Shukla, 2019]] ; [[#McGough--2020|McGough et al., 2020]] ; [[#Rodriguez-Verdugo--2020|Rodriguez-Verdugo et al., 2020]] ).

There is increasing evidence of the role of extreme events in disease outbreaks ''(very high confidence)'' ( [[#Tjaden--2018|Tjaden et al., 2018]] ; [[#Bryson--2020|Bryson et al., 2020]] ). Heat waves have been associated with outbreaks of helminth pathogens, especially in sub-Arctic and Arctic areas. For example, a severe outbreak of microfilaremia, a VBD spread by mosquitoes and flies, plagued reindeer in northern Europe following extreme high temperatures ( [[#Laaksonen--2010|Laaksonen et al., 2010]] ). More frequent and severe extreme events such as floods, droughts, heat waves and storms can either increase or decrease outbreaks, depending upon the region and disease ( ''robust evidence'' , ''high agreement'' ) ( [[#Anyamba--2001|Anyamba et al., 2001]] ; [[#Marcheggiani--2010|Marcheggiani et al., 2010]] ; [[#Brown--2013|Brown and Murray, 2013]] ; [[#Paz--2015|Paz, 2015]] ; [[#Boyce--2016|Boyce et al., 2016]] ; [[#Wu--2016b|Wu et al., 2016b]] ; [[#Wilcox--2019|Wilcox et al., 2019]] ; [[#Nosrat--2021|Nosrat et al., 2021]] ). Heavy precipitation events have been shown to increase some infectious diseases with aquatic life-cycle components such as mosquito-borne, helminth, and rodent-borne diseases ( ''robust evidence'' , ''high agreement'' ) ( [[#Anyamba--2001|Anyamba et al., 2001]] ; [[#Zhou--2005|Zhou et al., 2005]] ; [[#Wu--2008|Wu et al., 2008]] ; [[#Brown--2013|Brown and Murray, 2013]] ; [[#Anyamba--2014|Anyamba et al., 2014]] ; [[#Boyce--2016|Boyce et al., 2016]] ). Conversely, flooding also increases flow rate and decreases parasite load and diversity in other aquatic wildlife ( [[#Hallett--2008|Hallett and Bartholomew, 2008]] ; [[#Bjork--2009|Bjork and Bartholomew, 2009]] ; [[#Marcogliese--2016|Marcogliese, 2016]] ; [[#Marcogliese--2016|Marcogliese et al., 2016]] ) and can reduce mosquito abundance by flushing them out of the system ( [[#Paaijmans--2007|Paaijmans et al., 2007]] ; [[#Paz--2015|Paz, 2015]] ).

Droughts reduce the aquatic habitat of some mosquito species while simultaneously increasing the availability of stagnant standing pools of water that are ideal breeding habitats for other species, such as dengue-vector ''Aedes'' mosquitoes ( ''medium evidence'' , ''medium agreement'' ) ( [[#Chareonviriyaphap--2003|Chareonviriyaphap et al., 2003]] ; [[#Chretien--2007|Chretien et al., 2007]] ; [[#Padmanabha--2010|Padmanabha et al., 2010]] ; [[#Trewin--2013|Trewin et al., 2013]] ; [[#Paz--2015|Paz, 2015]] ). Extreme drought has been associated with an increase in bluetongue virus haemorrhagic disease in wildlife in eastern North America, although the mechanisms involved were not identified ( [[#Christensen--2020|Christensen et al., 2020]] ). Heat waves in some regions, especially coastal regions, have increased parasitism and decreased host richness and abundance, leading to population crashes ( [[#Larsen--2014|Larsen and Mouritsen, 2014]] ; [[#Mouritsen--2018|Mouritsen et al., 2018]] ). Changes in temperature and precipitation, especially extreme events, can alter community structure ( [[#Larsen--2011|Larsen et al., 2011]] ) by increasing or decreasing parasites and their host organisms, and even altering host behaviour in ways that are advantageous to parasites ( [[#Macnab--2012|Macnab and Barber, 2012]] ).

Climate change not only affects the occurrence of pathogens and their hosts in terms of geographic space but also impacts the temporal patterns of disease transmission. Warmer winters allow greater over-winter survival of arthropod vectors, which, coupled with lengthened transmission seasons, drive increases in vector population sizes, pathogen prevalence, and thus the proportion of vectors infected ( ''robust evidence'' , ''high agreement'' ) ( [[#Laaksonen--2009|Laaksonen et al., 2009]] ; [[#Molnár--2013|Molnár et al., 2013]] ; [[#Waits--2018|Waits et al., 2018]] ). For example, a parasitic nematode lung worm ( ''Umingmakstrongylus pallikuukensis'' ) has shortened its larval development time by half (from two years to one year), which has increased infection rates in North American musk oxen ( [[#Norwegian%20Polar%20Institute--2009|Norwegian Polar Institute, 2009]] ).

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

<span id="case-study-1-climate-change-impacts-on-pathogenic-helminths-in-europe"></span>
===== Case Study 1: Climate change impacts on pathogenic helminths in Europe =====

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Parasitic helminths can reduce growth and yield, kill livestock and infect humans and wildlife, leading to health, agricultural and economic losses ( [[#Fairweather--2011|Fairweather, 2011]] ; [[#Charlier--2016|Charlier et al., 2016]] ; [[#Charlier--2020|Charlier, 2020]] ). Attribution of increased incidence and risk of helminth disease to climate change is stronger than for other human diseases, thanks to long-term records and careful analysis of other anthropogenic drivers (e.g., LUC, agricultural/livestock intensification, and anti-helminthic intervention and resistance) ( [[#van%20Dijk--2008|van Dijk et al., 2008]] ; [[#van%20Dijk--2010|van Dijk et al., 2010]] ; [[#Fox--2011b|Fox et al., 2011b]] ; [[#Martínez-Valladares--2013|Martínez-Valladares et al., 2013]] ; [[#Charlier--2016|Charlier et al., 2016]] ; [[#Innocent--2017|Innocent et al., 2017]] ; [[#Mehmood--2017|Mehmood et al., 2017]] ).

In Europe, evidence from laboratory studies, long-term surveillance, statistical analyses and modelling shows that multiple helminth pathogens and their host snails have extended their transmission windows and increased their survival, fecundity, growth and abundances ( ''robust evidence'' , ''high agreement'' ). Furthermore, they have expanded or shifted their ranges poleward due to increases in temperature, precipitation and humidity ( ''robust evidence'' , ''high agreement'' ) ( [[#Lee--1995|Lee et al., 1995]] ; [[#Pritchard--2005|Pritchard et al., 2005]] ; [[#Poulin--2006|Poulin, 2006]] ; [[#van%20Dijk--2008|van Dijk et al., 2008]] ; [[#van%20Dijk--2010|van Dijk et al., 2010]] ; [[#Fairweather--2011|Fairweather, 2011]] ; [[#Fox--2011b|Fox et al., 2011b]] ; [[#Martínez-Valladares--2013|Martínez-Valladares et al., 2013]] ; [[#Bosco--2015|Bosco et al., 2015]] ; [[#Caminade--2015|Caminade et al., 2015]] ; [[#Caminade--2019|Caminade et al., 2019]] ). These documented changes in climate, hosts and pathogens have been linked to a higher incidence and more frequent outbreaks of disease in livestock across Europe ( ''very high confidence'' ).

<span id="case-study-2-chytrid-fungus-and-climate-change"></span>
===== Case Study 2: Chytrid fungus and climate change =====

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Infection by the chytrid fungus, Bd ''(Batrachochytrium dendrobatidis),'' can cause chytridiomycosis in amphibians. Bd is widely distributed globally and has caused catastrophic disease in amphibians, associated with the decline of 501 species and extinction of a further 90 species, primarily in tropical regions of the Americas and Australia ( [[#Scheele--2019|Scheele et al., 2019]] ; [[#Fisher--2020|Fisher and Garner, 2020]] ). Bd successfully travelled with high-elevation Andean frog species as they expanded their elevational ranges upward, driven by regional warming, to &gt; 5200 m ( [[#Seimon--2017|Seimon et al., 2017]] ).

New findings since AR5 from controlled laboratory experiments (manipulating temperature, humidity and water availability), intensive analyses of observed patterns of infection and disease in nature, and modelling studies have led to an emerging consensus that interactions between chytrids and amphibians are climate-sensitive, and that the interaction of climate change and Bd has driven many of the globally observed declines and extinctions of ~90 amphibian species ( ''robust evidence'' , ''high agreement'' ) ( [[#Rohr--2010|Rohr and Raffel, 2010]] ; [[#Puschendorf--2011|Puschendorf et al., 2011]] ; [[#Rowley--2013|Rowley and Alford, 2013]] ; [[#Raffel--2015|Raffel et al., 2015]] ; [[#Sauer--2018|Sauer et al., 2018]] ; [[#Cohen--2019a|Cohen et al., 2019a]] ; [[#Sauer--2020|Sauer et al., 2020]] ; [[#Turner--2021|Turner et al., 2021]] ).

The ‘thermal mismatch hypothesis’ posits that vulnerability to disease should be higher at warm temperatures in cool-adapted species and higher at cool temperatures in warmth-adapted species and is generally supported ( [[#Pounds--2006|Pounds et al., 2006]] ). However, the most recent studies reveal more complex mechanisms underlying amphibian disease–climate change dynamics, including variation in thermal preferences among individuals in a single amphibian population ( ''robust evidence'' , ''high agreement'' ) ( [[#Zumbado-Ulate--2014|Zumbado-Ulate et al., 2014]] ; [[#Sauer--2018|Sauer et al., 2018]] ; [[#Cohen--2019b|Cohen et al., 2019b]] ; [[#Neely--2020|Neely et al., 2020]] ; [[#Sauer--2020|Sauer et al., 2020]] ).

Bd is not universally harmful; it has been recorded as endemic in frog populations that do not suffer disease, where it may be commensal rather than parasitic ( [[#Puschendorf--2006|Puschendorf et al., 2006]] ; [[#Puschendorf--2011|Puschendorf et al., 2011]] ; [[#Rowley--2013|Rowley and Alford, 2013]] ). Projections of future impacts are difficult, as the virulence is variable across Bd populations and dependent upon the evolutionary and ecological history and evolutionary potential of both a local amphibian population and the endemic or invading Bd ( ''robust evidence'' , ''high agreement'' ) ( [[#Retallick--2004|Retallick et al., 2004]] ; [[#Daskin--2011|Daskin et al., 2011]] ; [[#Puschendorf--2011|Puschendorf et al., 2011]] ; [[#Phillips--2013|Phillips and Puschendorf, 2013]] ; [[#Rowley--2013|Rowley and Alford, 2013]] ; [[#Zumbado-Ulate--2014|Zumbado-Ulate et al., 2014]] ; [[#Sapsford--2015|Sapsford et al., 2015]] ; [[#Voyles--2018|Voyles et al., 2018]] ; [[#Bradley--2019|Bradley et al., 2019]] ; [[#Fisher--2020|Fisher and Garner, 2020]] ; [[#McMillan--2020|McMillan et al., 2020]] ). Further, specific local habitats might serve as regional climate refugia from chytrid infection (e.g., hot and dry) ( ''medium evidence'' , ''high agreement'' ) ( [[#Zumbado-Ulate--2014|Zumbado-Ulate et al., 2014]] ; [[#Cohen--2019b|Cohen et al., 2019b]] ; [[#Neely--2020|Neely et al., 2020]] ; [[#Turner--2021|Turner et al., 2021]] ).

<div id="2.4.2.7.2" class="h4-container"></div>

<span id="changes-in-geographic-distribution-and-connectivity-patterns-of-pathogens"></span>
===== 2.4.2.7.2 Changes in geographic distribution and connectivity patterns of pathogens =====

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As species’ geographic ranges and migration patterns are modified by climate change ( [[#2.4.2.1|Section 2.4.2.1]] , Table 2.2), pathogens accompany them. Diverse vectors and associated parasites, pests and pathogens of plants and animals are being recorded at higher latitudes and elevations in conjunction with regional temperature increases and precipitation changes ( ''robust evidence'' , ''high agreement'' ), although analysis of realised disease incidence often lacks the inclusion of non-climatic versus climate drivers, compromising attribution ( [[#Ollerenshaw--1959|Ollerenshaw and Rowlands, 1959]] ; [[#Purse--2005|Purse et al., 2005]] ; [[#Laaksonen--2010|Laaksonen et al., 2010]] ; [[#van%20Dijk--2010|van Dijk et al., 2010]] ; [[#Alonso--2011|Alonso et al., 2011]] ; [[#Genchi--2011|Genchi et al., 2011]] ; [[#Pinault--2011|Pinault and Hunter, 2011]] ; [[#Jaenson--2012|Jaenson et al., 2012]] ; [[#Loiseau--2012|Loiseau et al., 2012]] ; [[#Kweka--2013|Kweka et al., 2013]] ; [[#Medlock--2013|Medlock et al., 2013]] ; [[#Dhimal--2014a|Dhimal et al., 2014a]] ; [[#Dhimal--2014b|Dhimal et al., 2014b]] seasonal; [[#Siraj--2014|Siraj et al., 2014]] ; [[#Khatchikian--2015|Khatchikian et al., 2015]] ; [[#Hotez--2016a|Hotez, 2016a]] ; [[#Hotez--2016b|Hotez, 2016b]] ; [[#Bett--2017|Bett et al., 2017]] ; [[#Mallory--2017|Mallory and Boyce, 2017]] ; [[#Strutz--2017|Strutz, 2017]] ; [[#Booth--2018|Booth, 2018]] ; [[#Dumic--2018|Dumic and Severnini, 2018]] ; [[#Carignan--2019|Carignan et al., 2019]] ; [[#Gorris--2019|Gorris et al., 2019]] ; [[#Le--2019|Le et al., 2019]] ; [[#Stensgaard--2019b|Stensgaard et al., 2019b]] snails and; [[#Brugueras--2020|Brugueras et al., 2020]] ; [[#Gilbert--2021|Gilbert, 2021]] ).

At least six major VBDs affected by climate drivers have recently emerged in Nepal and are now considered endemic, with climate change implicated as a primary driver as LULCC has been assessed to have a minimal influence on these diseases ( ''high confidence'' ) (Table SM2.1). There is ''increasing evidence'' that climate warming has extended the elevational distribution of ''Anopheles'' , ''Culex'' and ''Aedes'' mosquito vectors above 2000 m in Nepal ( ''limited evidence'' , ''high agreement'' ) ( [[#Dahal--2008|Dahal, 2008]] ; [[#Dhimal--2014a|Dhimal et al., 2014a]] ; [[#Dhimal--2014b|Dhimal et al., 2014b]] ; [[#Dhimal--2015|Dhimal et al., 2015]] ), with similar trends being recorded in neighbouring Himalayan regions ( ''medium evidence'' , ''high agreement'' ) ( [[#Phuyal--2020|Phuyal et al., 2020]] ; [[#Dhimal--2021|Dhimal et al., 2021]] ). Host animals in novel areas may be immunologically naive, and therefore more vulnerable to severe illness ( [[#Bradley--2005|Bradley et al., 2005]] ; [[#Hall--2016|Hall et al., 2016]] ).

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

<span id="case-study-3-arctic-and-sub-arctic-disease-expansion-and-intensification"></span>
===== Case Study 3: Arctic and sub-Arctic disease expansion and intensification =====

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High Arctic regions have warmed by more than double the global average, &gt;2°C in most areas (Sections 2.3.1.1.2, Figure 2.11, and Atlas 11.2.1.2 in ( [[#IPCC--2021a|IPCC, 2021a]] )). Experimental field ecology studies and computational models of Arctic and sub-Arctic regions indicate that milder winters have reduced the mortality of vectors and reservoir hosts and increased their habitat as forested taiga expands into previously treeless tundra (Table SM2.1) ( [[#Parkinson--2014|Parkinson et al., 2014]] ). Warmer temperatures and longer seasonal windows have allowed faster reproduction/replication, accelerated development and increased the number of generations per year of pathogens, vectors and some host animals, which, in turn, increases the populations of disease organisms and disease transmission (Sections 2.4.2.4, 2.4.4.3.3). Higher numbers of ticks, mosquitoes, ''Culicoides'' biting midges, deer flies, horseflies and Simuliidae black flies, that transmit a variety of pathogens, are being documented in high-latitude regions and where they have been historically absent ( ''robust evidence'' , ''high agreement'' ) ( [[#Waits--2018|Waits et al., 2018]] ; [[#Caminade--2019|Caminade et al., 2019]] ; [[#Gilbert--2021|Gilbert, 2021]] ). In concert with these poleward shifts of hosts and vectors, pathogens, particularly tick-borne pathogens and helminth infections, have increased dramatically in incidence and severity from once-rare occurrences and have appeared in new regions ( ''very high confidence'' ) ( [[#Caminade--2019|Caminade et al., 2019]] ; [[#Gilbert--2021|Gilbert, 2021]] ).

Zoonoses and VBDs that have been historically rare or never documented in the Arctic and sub-Arctic regions of Europe, Asia, and North America, such as anthrax, cryptosporidiosis, elaphostrongylosis, filariasis ( [[#Huber--2020|Huber et al., 2020]] ), tick-borne encephalitis and tularemia ( [[#Evander--2009|Evander and Ahlm, 2009]] ; [[#Parkinson--2014|Parkinson et al., 2014]] ; [[#Pauchard--2016|Pauchard et al., 2016]] ), are spreading poleward and increasing in incidence, associated with warming temperatures ( ''robust evidence'' , ''high agreement'' , ''very high confidence'' ) (Table SM2.1) ( [[#Omazic--2019|Omazic et al., 2019]] ). Recent anthrax outbreaks and mass mortality events of humans and reindeer, respectively, have been linked to abnormally hot summer temperatures that caused the permafrost to melt and exposed diseased animal carcasses, releasing thawed, highly infectious ''Bacillus anthracis'' spores ( ''medium evidence'' , ''medium agreement'' ) (Ezhova et al., 2019; [[#Hueffer--2020|Hueffer et al., 2020]] ; [[#Ezhova--2021|Ezhova et al., 2021]] ). Multiple contributing factors conspired over different timescales to compound a 2016 anthrax outbreak occurring on the Yamal peninsula: (i) rapid permafrost thawing for 5 years preceding the outbreak, (ii) thick snow cover the year before the outbreak insulated the warmed permafrost and kept it from re-freezing, and (iii) anthrax vaccination rates had decreased or ceased in the region (Ezhova et al., 2019; [[#Ezhova--2021|Ezhova et al., 2021]] ). These precursors converged with an unusually dry and hot summer that: (i) melted permafrost, creating an anthrax exposure hazard; (ii) increased the vector insect population; and (iii) weakened the immune systems of reindeer, thereby increasing their susceptibility ( [[#Waits--2018|Waits et al., 2018]] ; [[#Hueffer--2020|Hueffer et al., 2020]] ).

Warmer temperatures have increased blood-feeding insect harassment of reindeer with compounding consequences: (1) increased insect-bite rates lead to higher parasite loads, (2) time spent by reindeer in trying to escape biting flies reduces foraging while simultaneously increasing their energy expenditure, (3) the combination of (1) and (2) leads to poor body condition which subsequently leads to (4) reduced winter survival and fecundity ( [[#Mallory--2017|Mallory and Boyce, 2017]] ). As temperatures warm and connectivity increases between the Arctic and the rest of the world, tourism, resource extraction and increased commercial transport will create additional risks of biological invasion by infectious agents and their hosts ( [[#Pauchard--2016|Pauchard et al., 2016]] ). These increases in introduction risk compounded with climate change have already begun to harm Indigenous Peoples dependent on hunting and herding livestock (horses and reindeer) that are suffering increased pathogen infection ''(high confidence)'' ( [[#Deksne--2020|Deksne et al., 2020]] ; [[#Stammler--2020|Stammler and Ivanova, 2020]] ).

<div id="2.4.2.7.3" class="h4-container"></div>

<span id="biodiversitydisease-links"></span>
===== 2.4.2.7.3 Biodiversity–disease links =====

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Anthropogenic impacts, such as disturbances caused by climate change, can reduce biodiversity via multiple mechanisms and increase the risk of human diseases ( ''limited evidence'' , ''low agreement'' ), but more research is needed to understand the underlying mechanisms ( [[#Civitello--2015|Civitello et al., 2015]] ; [[#Young--2017b|Young et al., 2017b]] ; [[#Halliday--2020|Halliday et al., 2020]] ; [[#Rohr--2020|Rohr et al., 2020]] ; [[#Glidden--2021|Glidden et al., 2021]] ). Known wildlife hosts of human-shared pathogens and parasites overall comprise a greater proportion of local species richness (18–72% higher) and abundance (21–144% higher) at sites under substantial human use (agricultural and urban land) compared with nearby undisturbed habitats ( [[#Gibb--2020|Gibb et al., 2020]] ).

Exploitation of wildlife and degradation of natural habitats have increased opportunities for a ‘spill over’ of pathogens from wildlife to human populations and also the emergence of zoonotic disease epidemics and pandemics ( ''robust evidence'' , ''high agreement'' ); animal and human migrations driven by climate change have added to this increased risk ( ''medium evidence'' , ''medium agreement'' ) (see [[#2.4.2.1|Section 2.4.2.1]] , Chapter 8, Cross-Chapter Box MOVING PLATE in Chapter 5) ( [[#Patz--2004|Patz et al., 2004]] ; [[#Cleaveland--2007|Cleaveland et al., 2007]] ; [[#Karesh--2012|Karesh et al., 2012]] ; [[#Altizer--2013|Altizer et al., 2013]] ; [[#Allen--2017|Allen et al., 2017]] ; [[#Plowright--2017|Plowright et al., 2017]] ; [[#Faust--2018|Faust et al., 2018]] ; [[#Carlson--2020|Carlson et al., 2020]] ; [[#Gibb--2020|Gibb et al., 2020]] ; [[#Hockings--2020|Hockings et al., 2020]] ; [[#IPBES--2020|IPBES, 2020]] ; [[#Volpato--2020|Volpato et al., 2020]] ; [[#Glidden--2021|Glidden et al., 2021]] ). Agricultural losses and subsequent food scarcity, increasing due to climate change, can also lead to an increase in the use of bushmeat, and thus increase the risk of diseases jumping from wild animals to humans ( ''medium evidence'' , ''high agreement'' ) ( [[#Brashares--2004|Brashares et al., 2004]] ; [[#Leroy--2004|Leroy et al., 2004]] ; [[#Wolfe--2004|Wolfe et al., 2004]] ; [[#Rosen--2010|Rosen and Smith, 2010]] ; [[#Kurpiers--2016|Kurpiers et al., 2016]] ).

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===== 2.4.2.7.4 Implications of changes in diseases in wild animals for humans =====

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Changes in temperature, precipitation, humidity and extreme events have been associated with more frequent disease outbreaks, increases in disease incidence and severity, novel diseases and the emergence of vectors in new areas for wild animals, with a mechanistic understanding of the roles of these drivers from experimental studies providing ''high confidence'' for the role of climate change. However, attributing how this has impacted human infectious diseases remains difficult, and definitive attribution studies are lacking. The specific role of recent climate change is difficult to examine in isolation in most regions where human disease incidence has also been affected by LUC (particularly agricultural and urban expansion), changes in public health access and measures, socioeconomic changes, increased global movement of people and changes in vector and rodent control programs, supporting ''medium confidence'' in the role of climate change driving the observed changes in vector-borne and infectious human diseases globally. Exceptions are in areas noted above (the Arctic, sub-Arctic, and high-elevation regions), in which climate change fingerprints are strong and concurrent changes in non-climatic drivers are less pronounced than in other regions ( ''high confidence'' for climate change attribution) (see Table SM2.1, Sections 5.5.1.3, 7.2.2.1, Cross-Chapter Box ILLNESS this Chapter) ( [[#Harvell--2002|Harvell et al., 2002]] ; [[#Norwegian%20Polar%20Institute--2009|Norwegian Polar Institute, 2009]] ; [[#Tersago--2009|Tersago et al., 2009]] ; [[#Tabachnick--2010|Tabachnick, 2010]] ; [[#Altizer--2013|Altizer et al., 2013]] ; [[#Garrett--2013|Garrett et al., 2013]] ; [[#Paz--2015|Paz, 2015]] ; [[#Wu--2016b|Wu et al., 2016b]] ; [[#Caminade--2019|Caminade et al., 2019]] ; [[#Dewage--2019|Dewage et al., 2019]] ; [[#Coates--2020|Coates and Norton, 2020]] ; [[#Deksne--2020|Deksne et al., 2020]] ; [[#Shocket--2020|Shocket et al., 2020]] ; [[#Couper--2021|Couper et al., 2021]] ; [[#Gilbert--2021|Gilbert, 2021]] ).

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==== 2.4.2.8 Observed Evolutionary Responses to Climate Change ====

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Previous sections document the tendency of species to retain their climate envelopes by some combination of range shift and phenological change ''(very high confidence)'' . However, this tracking of climate change can be incomplete, causing species or populations to experience hotter conditions than those to which they are adapted, and thereby incur ‘climate debts’ (section 2.4.2.3.1) ( [[#Devictor--2012|Devictor et al., 2012]] ). The importance of population-level debt is illustrated by a study in which the estimated debt values were correlated with population dynamic trends in a North American migratory songbird, the yellow warbler, ''Setophaga petechia.'' Populations that were genetic outliers for their local climate space had larger population declines (greater debt) than those with genotypes closer to the average values for that particular climate space. Debt values were estimated from genomic analyses independent of the population trends, and were distributed across the species’ range in a mosaic, not simply concentrated at range margins, rendering the results robust to being confounded by broad-scale geographical trends ( [[#Bay--2018|Bay et al., 2018]] ). Soroye et al. (2020) found similar results for 66 species of bumble-bees across Europe and North America, with declines in abundances spread throughout species’ ranges, but being greatest where populations already near their climate limits were being pushed beyond their climatic tolerances with climate change {2.4.2.3.1} .

In the absence of evolutionary constraints, climate debts can be cancelled by genetically based increases in thermal tolerance and the ability to perform in high ambient temperatures. In species already showing local adaptation to climate, populations currently living at relatively cool sites should be able to evolve to adopt the traits of populations currently at warmer sites as their local experience of climate changes ( [[#Singer--2017|Singer, 2017]] ; [[#Socolar--2017|Socolar et al., 2017]] ).

An increasing number of studies document evolutionary responses to climate change in populations not at their warm range limits ( [[#Franks--2012|Franks and Hoffmann, 2012]] ). Organisms with short generation times should have a higher capacity to genetically track climate change than species with long generation times, such as mammals ( [[#Boutin--2014|Boutin and Lane, 2014]] ). Indeed, observed evolutionary impacts have been mainly documented in insects, especially at expanding range margins ( [[#Chuang--2016|Chuang and Peterson, 2016]] ) where evolutionary changes have increased dispersal ability ( [[#Thomas--2001|Thomas et al., 2001]] ) and decreased host specialisation ( [[#Bridle--2014|Bridle et al., 2014]] ; [[#Lancaster--2020|Lancaster, 2020]] ) ''(medium evidence, medium agreement)'' .

Away from range margins, individual populations experiencing regional warming have evolved diverse traits related to climate adaptation. For example, pitcher-plant mosquitoes ( ''Wyeomyia smithii)'' in Pacific Northwest America have evolved to wait for shorter days before initiating diapause. This adaptation to lengthening summers enables them to delay overwintering until later and add an extra generation each year ( [[#Bradshaw--2001|Bradshaw and Holzapfel, 2001]] ). Among 26 populations of ''Drosophila subobscura'' studied on three continents, 22 experienced climate warming across two or more decades, and 21 of these 22 showed increasing frequency of the chromosome inversion characteristic of populations adapted to hot climates ''(robust evidence, high agreement)'' ( [[#Balanya--2006|Balanya et al., 2006]] ).

However, for populations already at their warm range limits, their ability to track climate change ''in situ'' would require evolving to survive and reproduce outside their species’ historical climate envelope: abilities of wild species to do this is not supported by experimental or observational evidence ( ''medium evidence'' , ''high agreement'' ) ( [[#Singer--2017|Singer, 2017]] ). Whether or not they can depends on the level of ‘niche conservatism’ operating at the species level ( [[#Lavergne--2010|Lavergne et al., 2010]] ). If a species whose range limits are determined by climate finds itself completely outside of its traditional climate envelope, extinction is expected in the absence of ‘evolutionary rescue’ ( [[#Bell--2009|Bell and Gonzalez, 2009]] ; [[#Bell--2019|Bell et al., 2019]] ).

To investigate the evolutionary potential of a species to survive in a novel climate entirely outside its traditional climate envelope, experiments have been carried out on ectotherms testing thermal performance, thermal tolerance and their evolvabilities ( [[#Castaneda--2019|Castaneda et al., 2019]] ; [[#Xue--2019|Xue et al., 2019]] ). Tests of thermal performance have been complicated, as both long-term acclimation and trans-generational effects occur ( [[#Sgro--2016|Sgro et al., 2016]] ). However, the results to date have been consistent: despite widespread local adaptation to climate across species’ ranges, substantial constraints exist regarding the evolution of greater stress tolerance (e.g., high temperatures and drought) at warm range limits ( ''medium evidence'' , ''high agreement'' ) ( [[#Hoffmann--2011|Hoffmann and Sgro, 2011]] ; [[#MacLean--2019b|MacLean et al., 2019b]] ).

For example, as temperature was experimentally increased, the amount of genetic variance in the fitness of ''Drosophila melanogaster'' decreased; in hot environments, flies had low evolvability ( [[#Kristensen--2015|Kristensen et al., 2015]] ). The hypothesis that heat-stress tolerance is evolutionarily constrained is further supported by experiments in which 22 ''Drosophila'' spp. drawn from tropical and temperate climes were subjected to extremes of heat and cold. They differed, as expected, in cold tolerances, but not in heat tolerances nor in temperatures at which optimal performances were observed ( [[#MacLean--2019b|MacLean et al., 2019b]] ).

Plasticity (flexibility) in acclimating to thermal regimes helps organisms adapt to environmental change. The form and extent of plasticity can vary among populations experiencing different climates ( [[#Kelly--2019|Kelly, 2019]] ) and generate phenotypic values outside the prior range for the species, but plasticity itself has not yet been observed to evolve in response to climate change ( [[#Kelly--2019|Kelly, 2019]] ).

Relevant genetic changes in nature (e.g., affecting heat tolerance) have not yet been shown to alter the boundaries of existing genetic variation for any species. Further, a recent global analysis of 91 species found, on average, a 5.4–6.5% decline in genetic diversity within populations since the start of the Industrial Revolution, with much larger declines for island species (27.6–30.9% reductions) ( [[#Leigh--2019|Leigh et al., 2019]] ). In [[#Leigh--2019|Leigh et al. (2019)]] , genetic declines were documented in both common and already endangered species of fish, mammals, birds, insects, amphibians and reptiles. These declines in genetic diversity, though not caused by climate change, decrease the abilities of wild species to adapt to climate change via evolutionary responses. Evolutionary rescue of entire species has not yet been observed in nature, nor is it expected, based on experimental and theoretical studies ( ''medium evidence'' , ''high agreement'' ).

Hybridisation between closely related species has increased in recent decades as one species shifts its range boundaries and positions itself more closely to the other. Hybrids between polar bears and brown bears have been documented in northern Canada ( [[#Kelly--2010|Kelly et al., 2010]] ). In North American rivers, hybridisation between invasive rainbow trout and native cutthroat trout has increased in frequency as the rainbow trout has expanded into warming waters ( [[#Muhlfeld--2014|Muhlfeld et al., 2014]] ). Whether climate-changed induced hybridisations can generate novel climate adaptations remains to be seen.

In summary, with our present knowledge, evolution is not expected to be sufficient to prevent the extinction of whole species if a species’ climate space disappears within the region they inhabit ( ''high confidence'' ).

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