# Evolutionary ecophysiology in extreme environments under a global change scenario

Pablo Burraco, Lucy Hawkes, Natalie Pilakouta, Frédéric Angelier, Kristien I Brans, Germán Orizaola

<figure><img src="image_1.png" /></figure>

## To cite this version:

Pablo Burraco, Lucy Hawkes, Natalie Pilakouta, Frédéric Angelier, Kristien I Brans, et al. Evolutionary ecophysiology in extreme environments under a global change scenario. Conservation Physiology, 2025, 13 (1), pp.coaf059. 10.1093/conphys/coaf059. hal-05340188

HAL Id: hal-05340188

https://hal.science/hal-05340188v1

Submitted on 31 Oct 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Evolutionary ecophysiology in extreme environments under a global change scenario

Pablo Burraco<fnref n="1" />,*, Lucy Hawkes<fnref n="2" />, Natalie Pilakouta<fnref n="3" />, Frédéric Angelier<fnref n="4" />, Kristien I. Brans<fnref n="5" /> and Germán Orizaola<fnref n="6" />,<fnref n="7" />,*

As wildlife increasingly has to face levels of environmental conditions that go far beyond normal ranges, understanding the ecological and evolutionary dynamics behind such extreme scenarios becomes essential for animal conservation. Here, we discuss the eco-physiological singularities of wildlife coping with extreme conditions. We first discuss the conditions under which scenarios can be considered 'extreme'. This includes distinguishing the nature of natural and anthropogenic disturbances, considering aspects such as their intensities, as well as the understanding of species biology and evolutionary history. To exemplify the diversity of wildlife responses to extreme conditions, we highlight five different representative study cases (two with natural causes, three of anthropogenic origin): birds at high altitude, fish in geothermal habitats, birds in pesticide-laden farmlands, invertebrates in urban ponds, and amphibians in radioactive zones. These examples illustrate the diverse physiological and ecological responses to extreme factors, emphasizing the complexity of wildlife adaptation under different scenarios. However, they also reveal significant knowledge gaps regarding long-term effects of responses to extreme environments, and the mechanistic basis behind these processes. Future research should ideally include long-term approaches making use of validated physiological markers of individual, population or species health or fitness. This information could be then incorporated into mechanistic models like Species Distribution Models (SDMs) to predict species geographic occurrence and the impact of future extreme scenarios. Such holistic and integrative physiological approaches will enhance our understanding of species and population resilience, and will facilitate the identification of vulnerable populations, ultimately improving management strategies. By prioritizing these research efforts, we will better anticipate the impacts of environmental changes on wildlife health, and thus improve biodiversity conservation strategies.

## Lay Summary

Understanding the effects of extreme environmental conditions on the ecology and physiology of wildlife is key to improve conservation strategies. Here, we discuss different representative study systems that examine the ecophysiology of animals coping with extreme environments. We identify research questions that should be incorporated by future studies in this field.

<footnote n="1">¹Doñana Biological Station (CSIC), c/ Americo Vespucio 26, 41092 Seville, Spain</footnote>

<footnote n="2">²Department of Biosciences, University of Exeter, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK</footnote>

<footnote n="3">³Centre for Biological Diversity, Biomedical Sciences Research Complex, University of St Andrews, Saint Andrews KY16 9TZ, UK</footnote>

<footnote n="4">⁴Centre d'Études Biologiques de Chizé, CNRS—La Rochelle Université, UMR7372, 405 Route de Prissé la Charrière, 79360 Villiers-en-Bois, France</footnote>

<footnote n="5">⁵Department of Biology, Vrije Universiteit Brussel, Etterbeek Brussels, Pleinlaan 2, 1050 Ixelles, Belgium</footnote>

<footnote n="6">⁶IMIB-Biodiversity Research Institute (Univ. Oviedo-CSIC-Princip. Asturias), Campus de Mieres, Edificio de Investigación – 5ª planta, c/ Gonzalo Gutiérrez Quirós s/n, 33600 Mieres, Asturias, Spain</footnote>

<footnote n="7">⁷Zoology Unit, Department of Biology of Organisms and Systems, University of Oviedo, Oviedo, c/ Catedrático Rodrigo Uría s/n, 33071, Asturias, Spain</footnote>

<footnote>*Corresponding authors: Pablo Burraco, Doñana Biological Station (CSIC), c/ Americo Vespucio26, 41092 Seville, Spain. E-mail: burraco@ebd.csic.es; Germán Orizaola, Zoology Unit, Department of Biology of Organisms and Systems, University of Oviedo, c/ Catedrático Rodrigo Uría s/n, 33071 Oviedo, Asturias, Spain. E-mail: orizaolagerman@uniovi.es</footnote>
**Key words:** Anthropogenic disturbances, biomarkers, climate change, conservation physiology, environmental stress

**Editor:** Andrea Fuller

Received 25 November 2024; Revised 13 June 2025; Editorial Decision 17 July 2025; Accepted 17 July 2025

**Cite as:** Burraco P, Hawkes L, Pilakouta N, Angelier F, Brans KI, Orizaola G (2025) Evolutionary ecophysiology in extreme environments under a global change scenario. *Conserv Physiol* 13(1): coaf059; doi:10.1093/conphys/coaf059.

Introduction

The study of wildlife responses to extreme environments is key to understand eco-evolutionary dynamics under the current context of global changes (Alberti, 2015, 2024; Fouqueau and Polechová, 2024). A classic definition of ‘extreme environment’ refers to a condition detrimental or fatal to highly organized life forms (Thiel, 2011). This view is often linked to extremophile organisms, such as microbes, which thrive in conditions beyond the tolerance limits of most other taxa (e.g. hydrothermal vents, highly acidic waters, or soda lakes; Rothschild and Mancinelli, 2001). Organisms capable of surviving these conditions often develop life-history or physiological strategies to cope with the stress associated with such environments, while balancing costs such as reductions in stored resources or loss of fitness (Wingfield et al., 2011; Boothby, 2019; Ando et al., 2021).

A broader interpretation of extreme environments should consider that most environmental factors naturally occur on a continuum (Rothschild and Mancinelli, 2001; Hardie and Hutchings, 2010; Wingfield et al., 2011). Thus, marginal and infrequent values outside the bounds of normal variability (e.g. the interquartile or >90% range of values for each condition within a given ecosystem) could be defined as ‘extreme’ (Rothschild and Mancinelli, 2001). These ‘severe conditions’ (sensu Wingfield et al., 2011) may be far from life-limiting but can compromise the normal functioning of organisms. From an evolutionary standpoint, extreme or severe environments can include high selective pressures, which may lead to reductions in fitness. In this context, species biology and distribution should be the two main aspects used to define environmental extremeness. For instance, the impact of a given condition can even vary within the same species due to factors, such as life-stage-dependent responses or local adaptations (e.g. Austin and Moehring, 2019; Kelly, 2019; Vicuña et al., 2019; Madeira et al., 2020; Ubach et al., 2022). Likewise, the occurrence and persistence of certain conditions can influence the responses of organisms. In some cases, exposure to ‘extreme’ conditions can be permanent (e.g. low oxygen levels at extreme altitude), whereas in others, it can be only transient (e.g. high temperatures during a heat-wave event). Among the former, many natural environmental conditions have been historically classified as extreme in the literature, including low temperatures in the polar regions or aridity in deserts. However, in most of these natural extreme environments, many taxa have developed physiological and life-history adaptations (Whiteman, 2021;

Storz et al., 2023; e.g. polar bears, freezing amphibians, mice in high mountains; Schmidt et al., 2024). Hence, the occurrence, intensity, and persistence of a given condition, along with the adaptive potential (evolutionary history) of organisms, will determine whether a condition or combination of conditions, can be considered as ‘extreme’ for an individual, population or species.

Human actions have modified not only the range, frequency and intensity of natural conditions (e.g. temperature, precipitation, light) but have also introduced novel sources of disturbance such as the release of chemical pollutants (e.g. pesticides, herbicides, heavy metals; Fischer et al., 2013; Saaristo et al., 2018). These anthropogenic conditions can impose physiological challenges, either on their own or synergistically with conditions that were previously not considered as extreme, ultimately leading to detrimental consequences. Yet, evidence suggests that new extreme environments can also drive phenotypic plasticity evolution, trait novelty and rapid adaptation (Chevin and Hoffmann, 2017; Wang and Guo, 2019; Parrilli et al., 2021). The understanding of the machinery underlying such evolutionary responses to extreme environments is therefore a major challenge for evolutionary biologists, ecologists and conservationists (Storey and Storey, 2005; Madliger et al., 2018; Gunga, 2020). This knowledge is crucial to predict biotic responses to future global change scenarios and to develop effective conservation actions.

Research on wildlife responses to natural and anthropogenic extreme environments has made great advances in the last years. This progress includes a deeper understanding of the biology and physiology of different study species or populations, a knowledge that is increasingly achieved through more complex, multifactorial, and realistic field and/or laboratory-based approaches (e.g. Maček et al., 2016; Dawson et al., 2020; Burraco et al., 2021c; Gerhard et al., 2023; see below details of some study systems). Long-term and longitudinal studies have shed light on how extreme factors impact individual condition and fitness, then contributing to understand the eco-evolutionary consequences of certain extreme environments (Hoset et al., 2014; Jenouvrier et al., 2015; e.g. Barneche et al., 2021; Gicquel et al., 2022). However, the study of ‘broad sense’ extreme environments is a relatively new field within a conservation framework, and therefore, there is a wide range of challenges and future directions to explore (Bailey and van de Pol, 2016; Van de Pol et al., 2017). In this paper, we discuss physiological and eco-evolutionary singularities of different extreme scenarios,
addressing both methodological and empirical aspects. We provide five distinct examples of research conducted on wildlife coping with different extreme conditions of natural or anthropogenic origin. For each case, we summarize the main characteristics of each extreme condition and its effects on the ecology, evolution and conservation of the study organisms, while examining the methodological challenges and unique features of each system. Finally, we offer some recommendations that could be relevant for future research in the field, with emphasis on the integration of physiological information to improve conservation and restoration actions.

## Case Studies of Ecophysiological Approaches to Extreme Environments

While the number of studies addressing the eco-physiological consequences of extreme environments is rapidly increasing, much of the research is scattered across systems and taxa, making it challenging to form general conclusions. Nonetheless, a substantial body of work documents physiological adjustments and evolutionary responses to a wide array of stressors in both natural and human-altered settings. For example, desert marsupials such as the wallabies have evolved exceptionally efficient renal physiology to cope with chronic water scarcity (Bradshaw *et al.*, 2001), whereas intertidal mussels use heat-shock proteins and dynamic shell gaping to withstand episodes of extremely high temperatures during low tide (Buckley *et al.*, 2001). Antarctic and Artic fish convergently produce antifreeze glycoproteins that prevent ice-crystal growth at sub-zero sea temperatures (Chen *et al.*, 1997), and reef-building corals in naturally acidic CO₂ vents show trans-generational shifts in calcification strategies that confer partial tolerance to ocean acidification (Kurihara *et al.*, 2020). Pans also provide compelling evidence: metal-hyperaccumulator species like *Arabidopsis halleri* thrive on heavy-metal substrates by up-regulating metal-chelation pathways (Noor *et al.*, 2024). Collectively, these and many other studies illustrate convergent themes—enhanced cellular repair, metabolic re-engineering and novel protective compounds—that underpin wildlife resilience when environmental conditions move beyond historical baselines.

A comprehensive evaluation of how animals shape their physiology to cope with extreme environments, either of natural and anthropogenic origin, is crucial to mechanistically understanding the eco-evolutionary consequences underlying some ecosystems. To show and discuss some possible approaches in this direction, we present five examples of research programs investigating the physiological effects and adaptations of wildlife exposed to extreme environments (Fig. 1A). Two of these examples focus on natural extremes (i.e. low oxygen at high altitudes, and elevated temperatures in geothermally warmed lakes), while the other three address anthropogenic extremes (i.e. urbanization, pesticides in agricultural fields, and ionizing radiation following a nuclear accident).

## Birds at extreme altitude

The highest parts of the planet such as the Tibetan Plateau in Asia, the Ethiopian highlands in Africa and the Andean Altiplano in South America, experience seasonally from extreme hypoxia, cold and xeric conditions and pose complex challenges to biodiversity (da Costa *et al.*, 2023). Despite this, birds are unparalleled in the animal kingdom for making spectacular migrations across vast scales, including travelling over the highest regions on earth. Flight is a particularly demanding form of exercise, and the pulmonary system of birds has evolved into an unidirectionally ventilated system with cross-current oxygen extraction, which permits huge rates of oxygen consumption (approximately twice as large as mammals; Butler *et al.*, 1988; Maina, 2008; Cieri and Farmer, 2016). Both of these aspects of the evolutionary ecology and physiology of birds has meant that birds are particularly well adapted to obtaining oxygen in hypoxic environments, not only at rest, but also during exercise there at high rates of volume of oxygen (VO₂; Maina, 2008; Cieri and Farmer, 2016). Although a range of work has demonstrated adaptations to high altitude in species such as mice (Chen *et al.*, 2023; Storz and Scott, 2023), a classic study system has been the bar-headed goose *Anser indicus* (Fig. 1A; Butler, 2010; Scott *et al.*, 2015; Hawkes *et al.*, 2017). In 1953, the expedition led by Tenzing Norgay and Edmund Hillary claimed to see bar-headed geese flying over Mount Everet (Swan, 1970). Since then, adaptations throughout the oxygen transport cascade have been extensively studied (Butler, 2010; Scott *et al.*, 2015; Hawkes *et al.*, 2017).

Geese are relatively tractable subjects to study, being large bodied and robust. To date, bar-headed geese have been studied in tissue preparations (Scott *et al.*, 2009), at rest in captivity (Black and Tenney, 1980; Scott and Milsom, 2007), running on a treadmill (Black and Tenney, 1980; Hawkes *et al.*, 2014), flying in a wind tunnel (Ward *et al.*, 2002; Meir and Milsom, 2013) and in the wild (Hawkes *et al.*, 2013; Scott *et al.*, 2015). These studies have been able to make use of approaches from classic physiological techniques (e.g. haemoglobin-oxygen dissociation curves) to state-of-the-art biotelemetry devices (Scott *et al.*, 2015).

Owing to the cardiovascular adaptations of birds to fund extremely high rates of oxygen consumption, most bird species can likely cope better than other taxa at high altitudes. Downy feathers can also help birds to cope with extreme cold (Terrill and Shultz, 2023), and extremely dry conditions may pose surprisingly little challenge to birds, because they can catabolize flight muscle during flight, producing metabolic water (Klaassen, 1996). It appears currently that few species of birds are as tolerant of hypoxia as the bar-headed goose, which has adaptations at every step of the oxygen transport cascade (Butler, 2010; Scott *et al.*, 2015; Hawkes *et al.*, 2017), but because flight costs scale following a power law with body mass (Bishop, 1997), it is likely that smaller species (e.g. alpine chough *Pyrrhocorax graculus digitatus*, or other smaller passerine species) may have proportionally lower
<figure><img src="image_3.png" /><figcaption>**Figure 1:** (A) The left section illustrates different examples of extreme environmental conditions—both of natural and anthropogenic origin—that wildlife may face. The right section summarizes previous research on various study systems, including birds living at high altitudes, fish inhabiting environments with extreme temperatures (e.g. geothermal habitats), invertebrates in urbanized areas, and vertebrates exposed to high levels of chemical pollution (e.g. birds in pesticide-contaminated farmlands, and amphibians in radioactive areas). For each system, key traits and the main observed effects are highlighted. (B) A conceptual overview of how eco-physiological research can be applied to understand and predict the consequences of environmental extremes for wildlife. (Left) This type of approach first requires characterizing normal patterns in life-history traits (e.g. lifespan, fitness) and physiological health markers (e.g. oxidative stress, DNA damage, cell apoptosis). (Middle) By studying shifts in these parameters, we can validate biomarkers and mechanistically unravel the eco-evolutionary consequences of environmental extremes. (Right) Finally, this information can then be integrated into mechanistic Species Distribution Models (SDMs) to improve predictions of environmental change impacts on biodiversity and to inform more effective conservation and restoration planning. Created with BioRender.com.</figcaption></figure>

costs, and therefore superior performance at altitude to even the bar-headed goose.

The ability of birds to perform well, even in hypoxic, cold and xeric conditions has important ramifications that warrant future study. First, birds can be major vectors for viruses, such as bird flu (Caliendo et al., 2022; Cui et al., 2022; Ramey et al., 2022; Klaassen and Wille, 2023; Lane et al., 2024), dispersing agents over long distances. Extreme environments normally inhibit pathogen survival, and/or restrict the distribution of their vectors, but species that can cope well with extreme environments can disperse pathogens through such environments, in some cases, even if asymptomatically infected (Eikenaar and Hegemann, 2016; Eikenaar et al., 2020; Tobolka et al., 2024). Second, as more species move into

high altitude environments seeking climate refugia (Keppel et al., 2024), birds will come into contact with a wider range of species, with differing abilities to compete for limited resources (Stenseth et al., 2015). Finally, the ability for vertebrate species to cope with extreme oxygen conditions continues to be of interest to medicine, sport and space travel (Keil et al., 2015; Magalhães, 2015).

## Fish in geothermal environments

Geothermal environments are key not only for the study of early life evolution on Earth but also for examining adaptation to extreme temperatures in wildlife (Jutfelt, 2020). For example, previous studies have taken advantage of a high-elevation geothermal stream system in the Andes to study
the effects of temperature on fish body size, macroinvertebrate community composition and transcriptional plasticity in anurans (e.g. Pastenes et al., 2017; Quenta-Herrera et al., 2021). There are also a number of studies on the reproductive phenology, thermal physiology and temperature preferences of 'hot spring frogs' (Buergeria japonica) found in geothermal hot springs in Taiwan and Japan (e.g. Chen et al., 2001; Komaki et al., 2020).

Geothermally warmed water bodies (also known as 'hot springs') adjacent to ambient-temperature lakes, which are much colder (Pilakouta et al., 2020, 2023a), are abundant in Iceland. There is one fish species that can be found in both of these thermal habitats: the threespine stickleback *Gasterostethus aculeatus* (Fig. 1A). These stickleback populations have been exposed to contrasting thermal regimes for hundreds to thousands of generations, and there are no differences in water chemistry between these thermal habitats other than temperature (Pilakouta et al., 2020). Given these repeated and independent pairs of warm and cold populations in close proximity, we can use the power of evolutionary replication to test the predictability of adaptation to high temperature by testing for parallel evolution across these population pairs.

A major advantage of this study system is the small geographic scale of these population pairs, which allows us to avoid confounding factors associated with latitudinal or altitudinal comparisons of different thermal environments (Jutfelt, 2020). Threespine sticklebacks are an established model in ecology and evolutionary biology with a well-annotated genome and transcriptome, and well-developed protocols for rearing and breeding this species in the lab (Reid et al., 2021). Thus, in addition to identifying phenotypic differences in wild-caught fish from warm and cold populations, we can conduct common-garden or reciprocal-transplant experiments to disentangle plastic and evolutionary changes in response to temperature in these populations (e.g. Pilakouta et al., 2023c). We can then link these phenotypic changes to the underlying molecular mechanisms and their effects on ecosystem-level processes.

Work on this study system has shown that hot-spring fish have diverged morphologically, physiologically and behaviourally compared to fish in ambient-temperature lakes. Firstly, fish living in hot springs are deeper-bodied, have shorter jaws and steeper craniofacial profiles, reflecting a more benthic diet (Pilakouta et al., 2023a). Secondly, they have a lower metabolic rate (Pilakouta et al., 2020), which could be adaptive, especially during the winter, when hot-spring fish are still experiencing relatively high temperatures but food, such as insect larvae, is scarce. Hot-spring fish are also less social (Pilakouta et al., 2023c). Lower sociability can be adaptive when there is high competition for food (Webster and Hart, 2006), as may be the case in these warm habitats. Lastly, fish from warm habitats prefer cooler temperatures when given a choice in the lab, even though they can persist at much higher temperatures in the wild (Pilakouta et al., 2023b).

This kind of natural experiments can revolutionize our understanding of how organisms adapt to high temperatures, with still many important questions to address in this study system. For example, it would be worthwhile to further investigate physiological adaptation in response to food limitation in hot springs. A study on cavefish, which experience long periods of food deprivation, found evidence for insulin resistance as an adaptation to cope with their nutrient-limited environment (Riddle et al., 2018). Similarly, preliminary data show that hot-spring fish exhibit a number of characteristics associated with diabetes, with respect to their insulin resistance, fat storage, appetite and starvation resistance (N. Pilakouta, unpublished data). Using a wild organism where the symptoms of diabetes may have an adaptive purpose can overcome many of the limitations of current laboratory models (Albertson et al., 2009). Thus, linking this widely used evolutionary model system to a human disease has potential clinical applications, for example by allowing us to identify novel biomarkers or genetic pathways associated with glucose metabolism that could be applied to humans (Albertson et al., 2009; Riddle et al., 2018; Krishnan et al., 2022; Xiong et al., 2022).

## Invertebrates in urban environments

Urban abiotic and biotic environments are drastically altered via reduced vegetation cover and habitat fragmentation, elevated pollution levels of various sorts (e.g. thermal, chemical, light, noise pollution), the introduction of non-native species, telecoupling and the fingerprint of human societal vectors at play (i.e. economics, technological development, culture, politics). Throughout the years, cities and urbanized areas have therefore been identified as uniquely complex ecosystems, which shape ecology (Grimm et al., 2008) and evolution (Szulkin et al., 2020), and now set the stage for potential profound specific socio-eco-evolutionary feedback (Des Roches et al., 2021; Alberti, 2024). While ponds and pools are vital for biodiversity (Hill et al., 2021) and the residing biota is hypothesized to be more severely impacted by joint urban perturbations given their closed nature (Oertli and Parris, 2019), they remained largely unexplored in cities for long.

Experimental work using field and common garden studies in the strongly urbanized region of Flanders (Belgium) tested for urban adaptive evolutionary trait change in the cladoceran *Daphnia magna* (Fig. 1A), and examined potential eco-evolutionary feedback, focusing on the context of urban warming and chemical pollution (Brans et al., 2017, 2018b, 2021). *Daphnia magna* plays a dual key role in freshwater food webs, being a food source for higher trophic levels, as well as exerting top-down control on phytoplankton thereby stabilizing clear water phases and preventing toxic bloom formation (Ebert, 2022). *Daphnia magna* is cyclical parthenogenetic, which enables to culture asexually replicated isoclonal lineages for multiple generations prior to trait assessment in common garden experiments, thus
reducing the impact of (grand)maternal effects (Ebert, 2022). First, by studying replicated urban and rural populations, it was shown that *D. magna* exhibits genetic differentiation for key traits related to thermal adaptation to the observed warming in city ponds in the study region (i.e. the Urban Hot Tub Effect; Brans *et al.*, 2018a); urban populations evolved a higher heat tolerance, smaller size at maturity, higher haemoglobin tissue content (Brans *et al.*, 2017) and a faster pace-of life, including faster development and maturation, as well as higher fecundity, compared to rural populations (Brans *et al.*, 2018b). Physiological analyses on body tissue, revealed urban populations having higher storage levels of proteins, fat and carbohydrates and a more optimized antioxidant defence system. These physiological characteristics were intertwined with life history via the evolution of a pace-of-life syndrome in urban, but not rural animals (Brans *et al.*, 2018b). Finally, evolved higher organophosphate pesticide tolerance was detected in urban compared to rural populations by studying survival responses to chlorpyrifos, a commonly used pesticide in urban environments in the region till 2020 (Brans *et al.*, 2021). Remarkably, an extended study including water fleas and damselfly nymphs (Coenagrionidae), common water flea predators for which similar urban evolutionary responses have been documented (Tüzün *et al.*, 2017), found a cryptic thermal eco-evolutionary feedback. More specifically, urban evolution in water fleas offsets the evolved higher predation rates observed in urban compared to rural damselfly nymphs during a simulated heatwave (Vanvelk *et al.*, 2021; Brans *et al.*, 2022).

While *D. magna* reproduction cycles are key in assessing
contributions of genetic differentiation, plasticity and evolu-
tion of plasticity (Govaert *et al.*, 2016; Ebert, 2022), such
laboratory quantitative genetic analyses and settings only
limitedly mimic *in situ* environmental conditions. In order
to asses effective evo-to-socio feedback in the light of, for
example, effective top-down control of noxious algal and
cyanobacterial blooms in cities, future experiments would
benefit from a common gardening reciprocal transplant set-
up (De Meester *et al.*, 2019; Brans *et al.*, 2020). This enables
to test whether the urban evolutionary background of *D.
magna* shapes ecological food web interactions and ultimately
bloom formation. In addition, there is growing evidence that
the *Daphnia* gut microbiomes plays an important role in
acclimation and adaptation to toxic cyanobacteria (Houwen-
huyse *et al.*, 2021). To what extent urban *D. magna* are
characterized by a distinct gut microbiome, and whether this
drives adaptive and acclimation responses to urbanization-
related stressors, as well as toxic cyanobacteria, is unclear.
Thus, a reciprocal transplant across urban and rural settings
enables to shed light on how evolutionary trait change in
a key freshwater species or organism, can mitigate negative
impacts of warming and eutrophication, two key drivers of a
shift to a turbid, cyanobacteria-dominated state of freshwater
ecosystems, and, importantly, predicted to be the most pro-
nounced threats to freshwater ecosystems worldwide under
future climate change.

Birds in polluted agricultural fields

Many wild vertebrate species have co-evolved with human
activities for decades or even centuries. As a result, some of
them are particularly well adapted to human activities, and
this allowed them to thrive in anthropogenic environments
by occupying specific ecological niches that were created by
humans (Hendry et al., 2017). Farmland birds represent very
good examples of this phenomenon as they mainly rely on
historical agricultural activities. However, agricultural prac-
tices have changed at an unprecedented rate since the middle
of the 20th century. Mechanization, increase in the size of
land plots and the alteration of many ecological infrastruc-
tures (e.g. woods, hedgerows, ponds, etc.) have resulted in
drastic environmental changes that have imposed new, and
often, extreme constraints to farmland birds (Stanton et al.,
2018; Rigal et al., 2023). Among them, the massive use of
pesticides has represented a real threat to wild birds with huge
impact on some species that were at the edge of extinction
(Carson, 1962). Although several ‘old’ historical pesticides
have been banned in several countries (e.g. DDT), it is not
true in all countries. When banned, they have progressively
and continuously been replaced by new organic molecules
that aimed to either better control pests or improve health
safety (Matthews, 2015). These pesticides are widely used
in multiple agroecosystems worldwide, but vineyards often
represent one of the agroecosystems that rely the most on
pesticides and especially organic fungicides, such as triazoles
(Komárek et al., 2010; García et al., 2022), except in a few
specific cases (e.g. organic vineyards). Indeed, grapes are very
sensitive to pest fungi and the use of fungicides aims to
improve grape yields, especially under cold and wet climate
(Geppert et al., 2024).

Over the last decade, field and laboratory studies have
been conducted to assess the physiological and ecological
consequences of living in extremely highly contaminated
vineyards. By comparing the contamination levels of birds
living in vineyards, other agroecosystems, and theoretically
uncontaminated areas, studies aimed to test whether
vineyards represent an extreme environment regarding the
use of triazoles (Angelier et al., 2023; Prouteau et al., 2025).
By using experimental setups, these studies also aimed to
mimic the contamination that can be found in vineyards and
to test its impact on organismal systems and performance in
farmland birds.

Overall, birds living in vineyards show high levels of
some contaminants, notably triazoles, the main organic fungi-
cides used in crops (Angelier et al., 2023; Fig. 1A). This
contamination seems ubiquitous in agroecosystems because
birds were contaminated in locations close to cereal crops
(although to a much lower level). Studies using experimental
approaches showed that such extreme contamination by tria-
zoles in vineyards can induce some alterations in numerous
and key organismal systems (reviewed in Jiménez-Peñuela
et al., 2024), such as metabolism (Bellot et al., 2022), immu-
nity (Fernández-Vizcaíno et al., 2024) and the functioning of
the hypothalamus-pituitary-thyroid axis (Bellot *et al.*, 2025a). These physiological perturbations can alter the development and the survival of offspring (Bellot *et al.*, 2025b), echoing the reported dramatic drop of farmland birds in the last decades (i.e. from 1980 to 2016, Rigal *et al.*, 2023). Importantly, these results are not limited to a few study species (house sparrow, *Passer domesticus*, European blackbird, *Turdus merula*), as other articles have convincingly demonstrated detrimental impacts of these triazole fungicides on the reproduction and the physiology of other farmland species, such as red-legged partridges, *Alectoris rufa* (Lopez-Antia *et al.*, 2021; e.g. Fernández-Vizcaíno *et al.*, 2024). Altogether, these results demonstrate that vineyards certainly represent an extreme environment for farmland birds. The continuous release of new triazole substances, combined with the massive use of these fungicides in vineyards, may limit the ability of farmland birds to adapt quickly enough to this anthropogenic selection pressure and might therefore jeopardize bird biodiversity in vineyards (Zielonka *et al.*, 2024).

Multiple recent articles have demonstrated that vineyards are associated with the massive use of multiple fungicides including triazoles (Komárek *et al.*, 2010; e.g. García *et al.*, 2022), and that they can probably affect the fitness of farm-land birds (reviewed in Jiménez-Peñuela *et al.*, 2024). However, we definitely lack data to better understand how these birds may have evolved some mechanisms to counteract the detrimental effects of these pesticides on their performance (survival and reproduction). Future studies focusing on inter-population sensitivity to these pesticides are now warranted to understand if birds could adapt to such extreme contamination.

## Amphibians in radioactive areas

Life has evolved under various sources of ionizing radiation, originated mostly from naturally occurring radioactive materials in Earth's crust or from cosmic rays (i.e. background ionizing radiation; Sohrabi, 2013). The development of nuclear technology, especially since the second half of 20th century, lead to the industrial use of radioactive isotopes for the production of energy, the design of nuclear weapons, and the development of nuclear medicine, among many other uses (IAEA, 2024). As a consequence of both deliberate actions (e.g. use and test of nuclear weapons) or unintentional releases of radioactive material (e.g. nuclear accidents), the increase of radioactive levels in some areas may pose risks to the environment (e.g. Beresford and Copplesone, 2011), and it represents an example of new extreme conditions experienced by wildlife.

Ionizing radiation released during the decay of radioactive isotopes can directly impact wildlife by damaging DNA strands through physical breaks in nucleotide sequences, or indirectly by interacting with other molecules (mostly water) which generates free radicals that can compromise individual performance and survival (Santivasi and Xia, 2014). Some of these effects have been studied in detail in areas

that experienced severe accidents in nuclear power plants such as Chornobyl (Ukraine, 1986) or Fukushima (Japan, 2011). Investigating the impact of radio-contaminated areas on wildlife arises as a unique opportunity to understand the adaptive capacity of organisms exposed to extreme levels of an abiotic factor that has only been historically present in the Earth at much lower doses (Karam and Leslie, 2005). However, despite these research efforts, there is still no scientific consensus about the long-term effects of ionizing radiation on the ecology and evolution of wildlife in radio-contaminated areas (Beresford *et al.*, 2020).

Amphibians are a great study system to evaluate the ecological and evolutionary effects of radiation. Many species inhabit both terrestrial and aquatic environments, exposing them to a full range of radioactive conditions. Amphibians often have an intermediate life-history pace with one generation every 2 to 3 years in most cases, and their low dispersal capacities facilitate the estimation of absorbed ionizing radiation (Burraco *et al.*, 2021b). Also, amphibian ecophysiology in response to environmental stress is relatively well known (Burraco and Gabor, 2023). Research has extensively examined the life history, physiology and genetics of Eastern tree frogs *Hyla orientalis* (Fig. 1A) living across a wide gradient of radioactive contamination within and around the Chornobyl Exclusion Zone, including their complete exposure to both internal and external radiation (Burraco *et al.*, 2021a, 2023; Burraco and Orizaola, 2022; Car *et al.*, 2022, 2023). Overall, studies on Chornobyl tree frogs have revealed that three decades after the accident, the levels of radioactive isotopes accumulated (i.e. total absorbed dose rate) by frogs currently living in the area are below those considered as potentially dangerous by international standards (ICRP, 2008; Burraco *et al.*, 2021b). This likely explains the lack of impact of radiation on different physiological traits in Chornobyl frogs, including liver morphology associated with organ function and individual health (Burraco *et al.*, 2023), blood biochemistry (Burraco *et al.*, 2021a), lifespan, the stress hormone corticosterone or the ageing marker telomere length (Burraco *et al.*, 2024). Another study found that Chornobyl tree frogs are much darker within the Exclusion Zone compared to those in the surrounding control area (44% darker, on average; Burraco and Orizaola, 2022). Differences in skin coloration of frogs were linked to high radiation levels at the time of the accident; frogs collected from areas with the highest levels of radiation in 1986 were darker than frogs from areas than those that experienced lower levels of radiation (Burraco and Orizaola, 2022). This darker pigmentation (i.e. higher concentration of melanin) detected in Chornobyl frogs still nowadays could be a consequence of rapid evolution linked to the protective role of melanin against ionizing radiation as found in organisms with lower level of organization (Cordero and Casadevall, 2020).

Beyond the eco-evolutionary significance of the study of ionizing radiation, understanding its long-term effects is crucial for accurately assessing the impact of nuclear accidents on
wildlife (Beresford *et al.*, 2020). A comprehensive evaluation of the consequences of extreme environments, such as those contaminated with ionizing radiation, requires integrating physiological and genetic information with a solid understanding of species biology. This knowledge is also relevant for assessing the level of risk to human repopulation of these areas. Field research in radiocontaminated areas should be complemented with additional approaches to investigate whether the effects of radiation are isotope-dependent or time (or dose-)dependent, how these effects may change throughout the life cycle of different organisms and whether they include transgenerational consequences.

## Relevance of Eco-Physiology for Wildlife Conservation

Research on the impact of extreme environments—both natural and anthropogenic—on wildlife can contribute to a better understanding of the responses and adaptations to environmental variation. This may be particularly helpful in the current scenario of rapid environmental change. The study of eco-evolutionary responses in extreme environments requires, at least, previously acquiring the following knowledge: (i) the range for the studied environmental condition and population or species, including historic exposure to the studied conditions; (ii) the basics of the species biology such as generation time, phenotypic plasticity and physiological levels under common ranges of variation of the studied conditions; (iii) possible interactions between the main studied condition and other relevant factors. Although not easy to acquire, this information will allow investigating whether wild populations have evolved specific physiological adaptations to cope with extreme environmental conditions.

During the last decades, ecophysiologists have increasingly highlighted the link between various physiological mechanisms and how environmental conditions impact animal health, finally shaping eco-evolutionary dynamics (Madliger et al., 2018; Isaksson, 2020). Some mechanisms have been presented as good indicators of wildlife responses and adaptations to stressful conditions. This is the case, among others, of organismal and tissue-specific metabolism, glucocorticoids (e.g. cortisol, corticosterone), heat shock proteins (HSPs), oxidative stress indicators, immune-related genes (immunoglobulins, cytokines) or telomere length (Sørensen et al., 2003; McCormick and Romero, 2017; Koch et al., 2021; Ohmer et al., 2021; Costantini, 2024). Such integrated stress response often involves energy costly process to restore homeostasis (McEwen and Wingfield, 2003), which can finally result in fitness decreases. For instance, glucocorticoids can modulate mitochondrial activity and the antioxidant machinery, whereas the overproduction of free radicals can influence cytokine signalling pathways and damage essential cell structures such as lipids, proteins or DNA (Vitale et al., 2013; Cain and Cidlowski, 2017).

Markers, such as HSPs, greatly respond to specific challenging conditions like thermal stress, enabling researchers to evaluate species' adaptability to climate change (Sørensen et al., 2003). Other markers, such as telomere length, are considered as crucial biomarkers for the cumulative impact of environmental stress on cellular and organismal ageing and health (Angelier et al., 2018; Burraco et al., 2020; Chatelain et al., 2020; Salmón and Burraco, 2022). Indeed, telomere dynamics are thought to be associated with high release of glucocorticoids, oxidative stress, heat shock proteins or the immune function, which likely explains the link between telomere shortening and accelerated organismal ageing or reduced health span (López-Otín et al., 2023). The use of epigenetic markers, and particularly the epigenetic clocks, also seems to be a prominent tool to comprehensively understand how environmental stressors influence both immediate and long-term health outcomes (Rey et al., 2020; Le Clercq et al., 2023).

Establishing baseline data on ecophysiological markers helps evolutionary ecologists and conservationists to identify deviations from normal health states when conditions become extreme. This includes the understanding of daily and seasonal variation and thresholds beyond physiological levels that become detrimental for the organism. An accurate evaluation of animal health under extreme environments should include both field and laboratory longitudinal approaches measuring different physiological markers, complemented with information on life-history traits (e.g. growth, reproduction), ideally throughout the lifetime of a number of individuals of populations exposed to a range of natural and anthropogenic environmental conditions (Fig. 1B, left). By comparing these responses under standard versus extreme conditions, we can identify shifts that may be adaptive or maladaptive, and begin to elucidate the underlying mechanisms driving population resilience or decline (Fig. 1B, middle). Physiological markers, in this context, offer valuable insight into the sub-lethal impacts of environmental stressors and can serve as early-warning indicators of population health.

Importantly, once such biomarkers are validated, they can be integrated into mechanistic frameworks such as Species Distribution Models (SDMs; Fig. 1B, right) to forecast species distribution under future scenarios (Kearney and Porter, 2009; Johnston et al., 2019; e.g. Becker et al., 2020; Burraco et al., 2021d). These models are a promising tool to inform conservation actions by identifying vulnerable populations which, therefore, should include the development of targeted management and restoration strategies. In addition, advances in technologies, such as high-throughput screenings (e.g. metabolomics, proteomics) or remote sensing monitoring, in combination with currently available physiological and modelling tools, could greatly help to anticipate the effects of global changes and particularly of extreme events, on the demography and health of wild populations.
## Acknowledgements

The Company of Biologists and the organization of the 2023 Society of Experimental Biology Centenary Conference in Edinburgh allowed us to organize a symposium on the evolutionary ecology of extreme environments where we set the theoretical grounds for this paper.

## Author contributions

P.B. and G.O. conceived the manuscript and drafted the first version. L.H., N.P., F.A., and K.I.B. contributed to the manuscript writing. All authors reviewed and approved the final manuscript.

## Conflicts of Interest

The authors have no conflicts of interest.

## Funding

This work was supported by the Spanish Ministry of Science and Innovation (Ramón y Cajal Program RyC2023-044964-I to P.B. and Ramón y Cajal Program RYC-2016-20656 to G.O.), the Biotechnology and Biosciences Research Council UK (to L.H.), the Agence Nationale de la Recherche (ANR project VITIBIRD ANR-20-CE34-0008 to F.A.), the Region Nouvelle-Aquitaine (MULTISTRESS project to F.A.), the Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail (ANSES project BiodiTox #2019/1/031 to F.A.), the Contrat Plan-État Region (CPER ECONAT to F.A.), the Centre National de la Recherche Scientifique (to F.A.), and the Research Foundation Flanders (FWO, post-doctoral fellow 1222123N to K.I.B.).

## References

* Alberti M (2015) Eco-evolutionary dynamics in an urbanizing planet. *Trends Ecol Evol* 30: 114–126. https://doi.org/10.1016/j.tree.2014.11.007.

* Alberti M (2024) Cities of the Anthropocene: urban sustainability in an eco-evolutionary perspective. *Philos Trans R Soc B Biol Sci* 379: 20220264. https://doi.org/10.1098/rstb.2022.0264.

* Albertson RC, Cresko W, Detrich HW, Postlethwait JH (2009) Evolutionary mutant models for human disease. *Trends Genet* 25: 74–81. https://doi.org/10.1016/j.tig.2008.11.006.

* Ando N, Barquera B, Bartlett DH, Boyd E, Burnim AA, Byer AS, Colman D, Gillilan RE, Gruebele M, Makhatadze G et al. (2021) The molecular basis for life in extreme environments. *Annu Rev Biophys* 50: 343–372. https://doi.org/10.1146/annurev-biophys-100120-072804.

* Angelier F, Costantini D, Blévin P, Chastel O (2018) Do glucocorticoids mediate the link between environmental conditions and telomere

dynamics in wild vertebrates? A review. *Gen Comp Endocrinol* 256: 99–111. https://doi.org/10.1016/j.ygcen.2017.07.007.

* Angelier F, Prouteau L, Brischoux F, Chastel O, Devier MH, Le Menach K, Martin S, Mohring B, Pardon P, Budzinski H (2023) High contamination of a sentinel vertebrate species by azoles in vineyards: a study of common blackbirds (*Turdus merula*) in multiple habitats in western France. *Environ Pollut* 316: 120655. https://doi.org/10.1016/j.envpol.2022.120655.

* Austin CJ, Moehring AJ (2019) Local thermal adaptation detected during multiple life stages across populations of *Drosophila melanogaster*. *J Evol Biol* 32: 1342–1351. https://doi.org/10.1111/jeb.13530.

* Bailey LD, van de Pol M (2016) Tackling extremes: challenges for ecological and evolutionary research on extreme climatic events. *J Anim Ecol* 85: 85–96. https://doi.org/10.1111/1365-2656.12451.

* Barneche DR, Hulatt CJ, Dossena M, Padfield D, Woodward G, Trimmer M, Yvon-Durocher G (2021) Warming impairs trophic transfer efficiency in a long-term field experiment. *Nature* 592: 76–79. https://doi.org/10.1038/s41586-021-03352-2.

* Becker DJ, Albery GF, Kessler MK, Lunn TJ, Falvo CA, Czirják G, Martin LB, Plowright RK (2020) Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defence. *J Anim Ecol* 89: 972–995. https://doi.org/10.1111/1365-2656.13166.

* Bellot P, Brischoux F, Budzinski H, Dupont SM, Fritsch C, Hope SF, Michaud B, Pallud M, Parenteau C, Prouteau L et al. (2025a) Chronic exposure to tebuconazole alters thyroid hormones and plumage quality in house sparrows (*Passer domesticus*). *Environ Sci Pollut Res* 32: 3328–3342. https://doi.org/10.1007/s11356-023-28259-5.

* Bellot P, Brischoux F, Fritsch C, Lièvre L, Ribout C, Angelier F (2025b) Chronic exposure to tebuconazole impairs offspring growth and survival in farmland birds: an experiment in captive house sparrows. *Environ Res* 275: 121321. https://doi.org/10.1016/j.envres.2025.121321.

* Bellot P, Dupont SM, Brischoux F, Budzinski H, Chastel O, Fritsch C, Lourdais O, Prouteau L, Rocchi S, Angelier F (2022) Experimental exposure to tebuconazole affects metabolism and body condition in a passerine bird, the house sparrow (*Passer domesticus*). *Environ Toxicol Chem* 41: 2500–2511. https://doi.org/10.1002/etc.5446.

* Beresford N, Copplestone D (2011) Effects of ionizing radiation on wildlife: what knowledge have we gained between the Chernobyl and Fukushima accidents? *Integr Environ Assess Manag* 7: 371–373. https://doi.org/10.1002/ieam.238.

* Beresford N, Horemans N, Copplestone D, Raines K, Orizaola G, Wood M, Laanen P, Whitehead H, Burrows J, Tinsley M et al. (2020) Towards solving a scientific controversy—the effects of ionising radiation on the environment. *J Environ Radioact* 211: 106033. https://doi.org/10.1016/j.jenvrad.2019.106033.

* Bishop CM (1997) Heart mass and the maximum cardiac output of birds and mammals: implications for estimating the maximum aerobic power input of flying animals. *Philos Trans R Soc B Biol Sci* 352: 447–456. https://doi.org/10.1098/rstb.1997.0032.
Black CP, Tenney SM (1980) Oxygen transport during progressive hypoxia in high-altitude and sea-level waterfowl. *Respir Physiol* **39**: 217–239. https://doi.org/10.1016/0034-5687(80)90046-8.

Boothby TC (2019) Mechanisms and evolution of resistance to environmental extremes in animals. *Evodevo* **10**: 30. https://doi.org/10.1186/s13227-019-0143-4.

Bradshaw SD, Morris KD, Bradshaw FJ (2001) Water and electrolyte homeostasis and kidney function of desert-dwelling marsupial walabies in western Australia. *J Comp Physiol B Biochem Syst Environ Physiol* **171**: 23–32. https://doi.org/10.1007/s003600000144.

Brans K, Almeida RA, Fajgenblat M (2021) Genetic differentiation in pesticide resistance between urban and rural populations of a non-target freshwater keystone interactor, *Daphnia magna*. *Evol Appl* **14**: 2541–2552. https://doi.org/10.1111/eva.13293.

Brans K, Engelen JMT, Souffreau C, De Meester L (2018a) Urban hot-tubs: local urbanization has profound effects on average and extreme temperatures in ponds. *Landsc Urban Plan* **176**: 22–29. https://doi.org/10.1016/j.landurbplan.2018.03.013.

Brans K, Govaert L, De Meester L (2020) Evolutionary dynamics of urban evolutionary biology. In: M Szulkin, J Munshi-South, A Charmantier, eds. *Urban Evolutionary Biology*. Oxford University Press, New York, NY, pp. 175-196, https://doi.org/10.1093/oso/9780198836841.003.0011.

Brans K, Jansen M, Vanoverbeke J, Tüzün N, Stoks R, De Meester L (2017) The heat is on: genetic adaptation to urbanization mediated by thermal tolerance and body size. *Glob Chang Biol* **23**: 5218–5227. https://doi.org/10.1111/gcb.13784.

Brans K, Stoks R. De Meester L (2018b) Urbanization drives genetic differentiation in physiology and structures the evolution of pace-of-life syndromes in the water flea Daphnia magna. *Proc R Soc B Biol Sci* **285**: 20180169. https://doi.org/10.1098/rspb.2018.0169.

Brans KI, Tüzün N, Sentis A, De Meester L, Stoks R (2022) Cryptic evolutionary feedback in the city: urban evolution of prey dampens the effect of urban evolution of the predator. *J Anim Ecol* **91**: 514–526. https://doi.org/10.1111/1365-2656.13601.

Buckley BA, Owen M, Hofmann GE (2001) Adjusting the thermostat: the threshold induction temperature for the heat-shock response in intertidal mussels (genus Mytilus) changes as a function of thermal history. *J Exp Biol* **204**: 3571–3579. https://doi.org/10.1242/jeb.204.20.3571.

Burraco P, Bonzom J-M, Car C, Beaugelin-Seiller K, Gashchak S, Orizaola G (2021a) Lack of impact of radiation on blood physiology biomarkers of Chernobyl tree frogs. *Front Zool* **18**: 33. https://doi.org/10.1186/s12983-021-00416-x.

Burraco P, Car C, Bonzom JM, Orizaola G (2021b) Assessment of exposure to ionizing radiation in Chernobyl tree frogs (*Hyla orientalis*). *Sci Rep* **11**: 20509. https://doi.org/10.1038/s41598-021-00125-9.

Burraco P, Gabor C (2023) Amphibian ecophysiology. In: Moreno-Rueda G, Comas M, eds. *Evolutionary Ecology of Amphibians*. CRC Press, Abingdon, Oxon, pp. 24–37. https://doi.org/10.1201/9781003093312-3.

Burraco P, Gabor C, Bryant A, Gardette V, Lengagne T, Bonzom JM, Orizaola G (2024) Ionizing radiation has negligible effects on the age, telomere length and corticosterone levels of Chornobyl tree frogs. *Biol Lett* **20**: 20240287. https://doi.org/10.1098/rsbl.2024.0287.

Burraco P, Laurila A, Orizaola G (2021c) Limits to compensatory responses to altered phenology in amphibian larvae. *Oikos* **130**: 231–239. https://doi.org/10.1111/oik.07919.

Burraco P, Lucas PM, Salmón P (2021d) Telomeres in a spatial context: a tool for understanding ageing pattern variation in wild populations. *Ecography* **2022**: e05565. https://doi.org/10.1111/ecog.05565.

Burraco P, Orizaola G (2022) Ionizing radiation and melanism in Chornobyl tree frogs. *Evol Appl* **15**: 1469–1479. https://doi.org/10.1111/eva.13476.

Burraco P, Orizaola G, Monaghan P, Metcalfe NB (2020) Climate change and ageing in ectotherms. *Glob Chang Biol* **26**: 5371–5381. https://doi.org/10.1111/gcb.15305.

Burraco P, Salla RF, Orizaola G (2023) Exposure to ionizing radiation and liver histopathology in the tree frogs of Chernobyl (Ukraine). *Chemosphere* **315**: 137753. https://doi.org/10.1016/j.chemosphere.2023.137753.

Butler JP, Banzett RB, Fredberg JJ (1988) Inspiratory valving in avian bronchi: aerodynamic considerations. *Respir Physiol* **72**: 241–255. https://doi.org/10.1016/0034-5687(88)90010-2.

Butler PJ (2010) High fliers: the physiology of bar-headed geese. *Comp Biochem Physiol A Mol Integr Physiol* **156**: 325–329. https://doi.org/10.1016/j.cbpa.2010.01.016.

Cain DW, Cidlowski JA (2017) Immune regulation by glucocorticoids. *Nat Rev Immunol* **17**: 233–247. https://doi.org/10.1038/nri.2017.1.

Caliendo V, Lewis NS, Pohlmann A, Baillie SR, Banyard AC, Beer M, Brown IH, Fouchier RAM, Hansen RDE, Lameris TK et al. (2022) Transatlantic spread of highly pathogenic avian influenza H5N1 by wild birds from Europe to North America in 2021. *Sci Rep* **12**: 11729. https://doi.org/10.1038/s41598-022-13447-z.

Car C, Gilles A, Armant O, Burraco P, Beaugelin-Seiller K, Gashchak S, Camilleri V, Cavalié I, Laloi P, Adam-Guillermin C et al. (2022) Unusual evolution of tree frog populations in the Chernobyl exclusion zone. *Evol Appl* **15**: 203–219. https://doi.org/10.1111/eva.13282.

Car C, Gilles A, Goujon E, Muller MLD, Camoin L, Frelon S, Burraco P, Granjeaud S, Baudelet E, Audebert S et al. (2023) Population transcriptogenomics highlights impaired metabolism and small population sizes in tree frogs living in the Chernobyl exclusion zone. *BMC Biol* **21**: 164. https://doi.org/10.1186/s12915-023-01659-2.

Carson R (1962) *Silent Spring*. Houghton Mifflin, Boston.

Chatelain M, Drobniak SM, Szulkin M (2020) The association between stressors and telomeres in non-human vertebrates: a meta-analysis. *Ecol Lett* **23**: 381–398. https://doi.org/10.1111/ele.13426.

Chen L, Devries AL, Cheng CHC (1997) Convergent evolution of antifreeze glycoproteins in Antarctic notothenioid fish and Arctic cod. *Proc Natl Acad Sci U S A* **94**: 3817–3822. https://doi.org/10.1073/pnas.94.8.3817.
Chen TC, Kam YC, Lin YS (2001) Thermal physiology and reproduc-
tive phenology of *Buergeria japonica* (Rhacophoridae) breeding in
a stream and a geothermal hotspring in Taiwan. *Zoolog Sci* 18:
591–596. https://doi.org/10.2108/zsj.18.591.

Chen X, Zaiwei W, Junhu SU, Huan LI, Xiong J, Keyi FU, Zilong
W, Yuan X, Ziyue S, Miao X et al. (2023) Altitude-dependent
metabolite biomarkers reveal the mechanism of plateau pika adap-
tation to high altitudes. *Integr Zool* 18: 1041–1055. https://doi.
org/10.1111/1749-4877.12710.

Chevin LM, Hoffmann AA (2017) Evolution of phenotypic plasticity in extreme environments. *Philos Trans R Soc B Biol Sci* 372: 20160138. https://doi.org/10.1098/rstb.2016.0138.

Cieri RL, Farmer CG (2016) Unidirectional pulmonary airflow in verte-
brates: a review of structure, function, and evolution. *J Comp Physiol
B Biochem Syst Environ Physiol* 186: 541–552. https://doi.org/10.1007/
s00360-016-0983-3.

Cordero RJB, Casadevall A (2020) Melanin. *Curr Biol* 30: R142–R143.
https://doi.org/10.1016/j.cub.2019.12.042.

Costantini D (2024) *The Role of Organismal Oxidative Stress in the Ecology and Life-history Evolution of Animals*. Springer Nature Switzerland, Aargau. https://doi.org/10.1007/978-3-031-65183-0.

Cui P, Shi J, Wang C, Zhang Y, Xing X, Kong H, Yan C, Zeng X, Liu L, Tian G et al. (2022) Global dissemination of H5N1 influenza viruses bearing the clade 2.3.4.4b HA gene and biologic analysis of the ones detected in China. *Emerg Microbes Infect* 11: 1693–1704. https://doi.org/10.1080/22221751.2022.2088407.

Dawson NJ, Alza L, Nandal G, Scott GR, McCracken KG (2020) Conver-
gent changes in muscle metabolism depend on duration of high-
altitude ancestry across andean waterfowl. *Elife* 9: e56259. https://
doi.org/10.7554/eLife.56259.

De Meester L, Brans K, Govaert L, Souffreau C, Mukherjee S, Vanvelk H, Korzeniowski K, Kilsdonk L, Decaestecker E, Stoks R et al. (2019) Analysing eco-evolutionary dynamics—the challenging complexity of the real world. *Funct Ecol* 33: 43–59. https://doi.org/10.1111/1365-2435.13261.

Des Roches S, Brans KI, Lambert MR, Rivkin LR, Savage AM, Schell CJ, Correa C, De Meester L, Diamond SE, Grimm NB et al. (2021) Socio-eco-evolutionary dynamics in cities. *Evol Appl* 14: 248–267. https://doi.org/10.1111/eva.13065.

Ebert D (2022) *Daphnia* as a versatile model system in ecology and evolution. *Evodevo* 13: 16. https://doi.org/10.1186/s13227-022-00199-0.

Eikenaar C, Hegemann A (2016) Migratory common blackbirds have lower innate immune function during autumn migration than resident conspecifics. *Biol Lett* 12: 20160078–20160081. https://doi.org/10.1098/rsbl.2016.0078.

Eikenaar C, Hessler S, Hegemann A (2020) Migrating birds rapidly increase constitutive immune function during stopover. *R Soc Open Sci* 7: 192031. https://doi.org/10.1098/rsos.192031.

Fernández-Vizcaíno E, Mateo R, Fernández de Mera IG, Mougeot F, Camarero PR, Ortiz-Santaliestra ME (2024) Transgenerational effects of triazole fungicides on gene expression and egg compounds in non-exposed offspring: a case study using red-legged partridges (*Alectoris rufa*). *Sci Total Environ* 926: 171546. https://doi.org/10.1016/j.scitotenv.2024.171546.

Fischer BB, Pomati F, Eggen RIL (2013) The toxicity of chemical pollutants in dynamic natural systems: the challenge of integrating environmental factors and biological complexity. *Sci Total Environ* 449: 253–259. https://doi.org/10.1016/j.scitotenv.2013.01.066.

Fouqueau L, Polechová J (2024) Eco-evolutionary dynamics in changing environments: integrating theory with data. *J Evol Biol* 37: 579–587. https://doi.org/10.1093/jeb/voae067.

García MG, Sánchez JIL, Bravo KAS, Cabal MDC, Pérez-Santín E (2022) Review: presence, distribution and current pesticides used in Spanish agricultural practices. *Sci Total Environ* 845: 157291. https://doi.org/10.1016/j.scitotenv.2022.157291.

Geppert C, da Cruz M, Alma A, Andretta L, Anfora G, Battaglia D, Burgio G, Caccavo V, Chiesa SG, Cinquatti F et al. (2024) Climate and landscape composition explain agronomic practices, pesticide use and grape yield in vineyards across Italy. *Agr Syst* 215: 103853. https://doi.org/10.1016/j.agsy.2024.103853.

Gerhard M, Koussoroplis AM, Raatz M, Pansch C, Fey SB, Vajedsamiei J, Calderó-Pascual M, Cunillera-Montcusí D, Juvigny-Khenafou NPD, Polazzo F et al. (2023) Environmental variability in aquatic ecosystems: avenues for future multifactorial experiments. *Limnol Oceanogr Lett* 8: 247–266. https://doi.org/10.1002/lol2.10286.

Gicquel M, East ML, Hofer H, Benhaiem S (2022) Early-life adversity predicts performance and fitness in a wild social carnivore. *J Anim Ecol* 91: 2074–2086. https://doi.org/10.1111/1365-2656.13785.

Govaert L, Pantel JH, De Meester L (2016) Eco-evolutionary partitioning metrics: assessing the importance of ecological and evolutionary contributions to population and community change. *Ecol Lett* 19: 839–853. https://doi.org/10.1111/ele.12632.

Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, Briggs JM (2008) Global change and the ecology of cities. *Science* 319: 756–760. https://doi.org/10.1126/science.1150195.

Gunga HC (2020) *Human Physiology in Extreme Environments*. Academic Press, London.

Hardie DC, Hutchings JA (2010) Evolutionary ecology at the extremes of species' ranges. *Environ Rev* 18: 1–20. https://doi.org/10.1139/A09-014.

Hawkes LA, N. Batbayar N, Bishop CM, Butler PJ, Frappell PB, Meir JU, Milsom WK, Natsagdorj T, Scott GS (2017) Goose migration over the Himalayas: physiological adaptations. In: HH Prins, T Namgail, eds. *Bird Migration Across the Himalayas: Wetland Functioning Amidst Mountains and Glaciers*. Cambridge University Press, Cambridge, pp. 241–253. https://doi.org/10.1017/9781316335420.019.
Hawkes LA, Balachandran S, Batbayar N, Butler PJ, Chua B, Douglas DC, Frappell PB, Hou Y, Milsom WK, Newman SH et al. (2013) The para-dox of extreme high-altitude migration in bar-headed geese *Anser indicus*. *Proc R Soc B Biol Sci* 280: 20122114. https://doi.org/10.1098/rspb.2012.2114.

Hawkes LA, Butler PJ, Frappell PB, Meir JU, Milsom WK, Scott GR, Bishop CM (2014) Maximum running speed of captive bar-headed geese is unaffected by severe hypoxia. *PloS One* 9: e94015. https://doi.org/10.1371/journal.pone.0094015.

Hendry AP, Gotanda KM, Svensson EI (2017) Human influences on evolution, and the ecological and societal consequences. *Philos Trans R Soc B Biol Sci* 372: 20160028. https://doi.org/10.1098/rstb.2016.0028.

Hill MJ, Greaves HM, Sayer CD, Hassall C, Milin M, Milner VS, Marazzi L, Hall R, Harper LR, Thornhill I et al. (2021) Pond ecology and conservation: research priorities and knowledge gaps. *Ecosphere* 12: e03853. https://doi.org/10.1002/ecs2.3853.

Hoset KS, Espmark Y, Fossøy F, Stokke BG, Jensen H, Wedege MI, Moksnes A (2014) Extra-pair paternity in relation to regional and local climate in an Arctic-breeding passerine. *Polar Biol* 37: 89-97. https://doi.org/10.1007/s00300-013-1412-7.

Houwenhuyse S, Stoks R, Mukherjee S, Decaestecker E (2021) Locally adapted gut microbiomes mediate host stress tolerance. *ISME J* 15: 2401-2414. https://doi.org/10.1038/s41396-021-00940-y.

IAEA (2024) Nuclear hydrogen projects to support clean energy transition: updates on international initiatives and IAEA activities. *Int J Hydrogen Energy* 54: 768-779.

ICRP (2008) Environmental protection: the concept and use of reference animals and plants. *Ann ICRP* 38: 1-242.

Isaksson C (2020) Urban ecophysiology: beyond costs, stress and biomarkers. *J Exp Biol* 223: jeb203794. https://doi.org/10.1242/jeb.203794.

Jenouvrier SP, Péron C, Weimerskirch H (2015) Extreme climate events and individual heterogeneity shape life-history traits and population dynamics. *Ecol Monogr* 85: 605-624. https://doi.org/10.1890/14-1834.1.

Jiménez-Peñuela J, Santamaría-Cervantes C, Fernández-Vizcaíno E, Mateo R, Ortiz-Santaliestra ME (2024) Integrating adverse effects of triazole fungicides on reproduction and physiology of farmland birds. *J Avian Biol* 2025: e03313. https://doi.org/10.1111/jav.03313.

Johnston ASA, Boyd RJ, Watson JW, Paul A, Evans LC, Gardner EL, Boult VL (2019) Predicting population responses to environmental change from individual-level mechanisms: towards a standardized mechanistic approach. *Proc R Soc B Biol Sci* 286: 20191916. https://doi.org/10.1098/rspb.2019.1916.

Jutfelt F (2020) Metabolic adaptation to warm water in fish. *Funct Ecol* 34: 1138-1141. https://doi.org/10.1111/1365-2435.13558.

Karam PA, Leslie SA (2005) Changes in terrestrial natural radiation levels over the history of life. *Radioact Environ* 7: 107-117. https://doi.org/10.1016/S1569-4860(04)07011-1.

Kearney M, Porter W (2009) Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges. *Ecol Lett* 12: 334-350. https://doi.org/10.1111/j.1461-0248.2008.01277.x.

Keil G, Cummings E, de Magalhães JP (2015) Being cool: how body temperature influences ageing and longevity. *Biogerontology* 16: 383-397. https://doi.org/10.1007/s10522-015-9571-2.

Kelly M (2019) Adaptation to climate change through genetic accommodation and assimilation of plastic phenotypes. *Philos Trans R Soc B Biol Sci* 374: 20180176. https://doi.org/10.1098/rstb.2018.0176.

Keppel G, Stralberg D, Morelli TL, Bátori Z (2024) Managing climate-change refugia to prevent extinctions. *Trends Ecol Evol* 39: 800-808. https://doi.org/10.1016/j.tree.2024.05.002.

Klaassen M (1996) Metabolic constraints on long-distance migration in birds. *J Exp Biol* 199: 57-64. https://doi.org/10.1242/jeb.199.1.57.

Klaassen M, Wille M (2023) The plight and role of wild birds in the current bird flu panzootic. *Nat Ecol Evol* 7: 1541-1542. https://doi.org/10.1038/s41559-023-02182-x.

Koch RE, Buchanan KL, Casagrande S, Crino O, Dowling DK, Hill GE, Hood WR, McKenzie M, Mariette MM, Noble DWA et al. (2021) Integrating mitochondrial aerobic metabolism into ecology and evolution. *Trends Ecol Evol* 36: 321-332. https://doi.org/10.1016/j.tree.2020.12.006.

Komaki S, Sutoh Y, Kobayashi K, Saito S, Saito CT, Igawa T, Lau Q (2020) Hot spring frogs (*Buergeria japonica*) prefer cooler water to hot water. *Ecol Evol* 10: 9466-9473. https://doi.org/10.1002/ece3.6637.

Komárek M, Čadková E, Chrastný V, Bordas F, Bollinger JC (2010) Contamination of vineyard soils with fungicides: a review of environmental and toxicological aspects. *Environ Int* 36: 138-151. https://doi.org/10.1016/j.envint.2009.10.005.

Krishnan J, Seidel CW, Zhang N, Singh NP, VanCampen J, Peuß R, Xiong S, Kenzior A, Li H, Conaway JW et al. (2022) Genome-wide analysis of cis-regulatory changes underlying metabolic adaptation of cavefish. *Nat Genet* 54: 684–693. https://doi.org/10.1038/s41588-022-01049-4.

Kurihara H, Suhara Y, Mimura I, Golbuu Y (2020) Potential acclimatization and adaptive responses of adult and trans-generation coral larvae from a naturally acidified habitat. *Front Mar Sci* 7: 581160. https://doi.org/10.3389/fmars.2020.581160.

Lane JV, Jeglinski JWE, Avery-Gomm S, Ballstaedt E, Banyard AC, Barychka T, Brown IH, Brugger B, Burt TV, Careen N et al. (2024) High pathogenicity avian influenza (H5N1) in northern gannets (*Morus bassanus*): global spread, clinical signs and demographic consequences. *Ibis* 166: 633-650. https://doi.org/10.1111/ibi.13275.

Le Clercq LS, Kotzé A, Grobler JP, Dalton DL (2023) Biological clocks as age estimation markers in animals: a systematic review and meta-analysis. *Biol Rev* 98: 1972-2011. https://doi.org/10.1111/brv.12992.

Lopez-Antia A, Ortiz-Santaliestra ME, Mougeot F, Camarero PR, Mateo R (2021) Birds feeding on tebuconazole treated seeds have reduced breeding output. *Environ Pollut* 271: 116292. https://doi.org/10.1016/j.envpol.2020.116292.
López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G (2023) Hallmarks of aging: an expanding universe. *Cell* 186: 243–278. https://doi.org/10.1016/j.cell.2022.11.001.

Maček I, Vodnik D, Pfanz H, Low-Décarie E, Dumbrell AJ (2016) Locally extreme environments as natural long-term experiments in ecology. *Adv Ecol Res* 55: 283–323. https://doi.org/10.1016/bs.aecr.2016.08.001.

Madeira D, Madeira C, Costa PM, Vinagre C, Pörtner HO, Diniz MS (2020) Different sensitivity to heatwaves across the life cycle of fish reflects phenotypic adaptation to environmental niche. *Mar Environ Res* 162: 105192. https://doi.org/10.1016/j.marenvres.2020.105192.

Madliger CL, Love OP, Hultine KR, Cooke SJ (2018) The conservation physiology toolbox: status and opportunities. *Conserv Physiol* 6: coy029. https://doi.org/10.1093/conphys/coy029.

Magalhães JP (2015) The big, the bad and the ugly. *EMBO Rep* 16: 771–776. https://doi.org/10.15252/embr.201540606.

Maina JN (2008) Functional morphology of the avian respiratory system, the lung-air sac system: efficiency built on complexity. *Ostrich* 79: 117–132. https://doi.org/10.2989/OSTRICH.2008.79.2.1.575.

Matthews G (2015) *Pesticides: Health, Safety and the Environment*. John Wiley & Sons, Oxford. https://doi.org/10.1002/9781118975923.

McCormick SD, Romero LM (2017) Conservation endocrinology. *Bio-science* 67: 429–442. https://doi.org/10.1093/biosci/bix026.

McEwen BS, Wingfield JC (2003) The concept of allostasis in biology and biomedicine. *Horm Behav* 43: 2–15. https://doi.org/10.1016/S0018-506X(02)00024-7.

Meir JU, Milsom WK (2013) High thermal sensitivity of blood enhances oxygen delivery in the high-flying bar-headed goose. *J Exp Biol* 216: 2172–2175. https://doi.org/10.1242/jeb.085282.

Noor I, Sohail H, Akhtar MT, Cui J, Lu Z, Mostafa S, Hasanuzzaman M, Hussain S, Guo N, Jin B (2024) From stress to resilience: unraveling the molecular mechanisms of cadmium toxicity, detoxification and tolerance in plants. *Sci Total Environ* 954: 176462. https://doi.org/10.1016/j.scitotenv.2024.176462.

Oertli B, Parris KM (2019) Review: toward management of urban ponds for freshwater biodiversity. *Ecosphere* 10: e02810. https://doi.org/10.1002/ecs2.2810.

Ohmer MEB, Costantini D, Czirják G, Downs CJ, Ferguson LV, Flies A, Franklin CE, Kayigwe AN, Knutie S, Richards-Zawacki CL *et al*. (2021) Applied ecoimmunology: using immunological tools to improve conservation efforts in a changing world. *Conserv Physiol* 9: coab074. https://doi.org/10.1093/conphys/coab074.

Parrilli E, Tedesco P, Fondi M, Tutino ML, Lo Giudice A, de Pascale D, Fani R (2021) The art of adapting to extreme environments: the model system Pseudoalteromonas. *Phys Life Rev* 36: 137–161. https://doi.org/10.1016/j.plrev.2019.04.003.

Pastenes L, Valdivieso C, Di Genova A, Travisany D, Hart A, Montecino M, Orellana A, Gonzalez M, Gutiérrez RA, Allende ML *et al*. (2017) Global gene expression analysis provides insight into local adaptation to

geothermal streams in tadpoles of the Andean toad *Rhinella spinulosa*. *Sci Rep* 7: 1966. https://doi.org/10.1038/s41598-017-01982-z.

Pilakouta N, Humble JL, Hill IDC, Arthur J, Costa APB, Smith BA, Kristjánsson BK, Skulason S, Killen SS, Lindstrom J *et al*. (2023a) Testing the predictability of morphological evolution in contrasting thermal environments. *Evolution* 77: 239–253. https://doi.org/10.1093/evolut/qpac018.

Pilakouta N, Killen SS, Kristjánsson BK, Skúlason S, Lindström J, Metcalfe NB, Parsons KJ (2020) Multigenerational exposure to elevated temperatures leads to a reduction in standard metabolic rate in the wild. *Funct Ecol* 34: 1205–1214. https://doi.org/10.1111/1365-2435.13538.

Pilakouta N, Killen SS, Kristjánsson BK, Skúlason S, Lindström J, Metcalfe NB, Parsons KJ (2023b) Geothermal stickleback populations prefer cool water despite multigenerational exposure to a warm environment. *Ecol Evol* 13: e9654. https://doi.org/10.1002/ece3.9654.

Pilakouta N, O'Donnell PJ, Crespel A, Levet M, Claireaux M, Humble JL, Kristjánsson BK, Skúlason S, Lindström J, Metcalfe NB *et al*. (2023c) A warmer environment can reduce sociability in an ectotherm. *Glob Chang Biol* 29: 206–214. https://doi.org/10.1111/gcb.16451.

Prouteau L, Dévier MH, Angelier F, Chastel O, Brischoux F, Pardon P, Le MK, Budzinski H (2025) Biomonitoring of azole fungicides in free-living blackbird plasma using on-line solid-phase extraction coupled to liquid chromatography-tandem mass spectrometry (SPE HPLC-MS/MS). *J Chromatogr A* 1748: 465725. https://doi.org/10.1016/j.chroma.2025.465725.

Quenta-Herrera E, Daza A, Lazzaro X, Jacobsen D, Dangles O, Cauvy-Fraunié S (2021) Aquatic biota responses to temperature in a high Andean geothermal stream. *Freshw Biol* 66: 1889–1900. https://doi.org/10.1111/fwb.13798.

Ramey AM, Hill NJ, DeLiberto TJ, Gibbs SEJ, Camille Hopkins M, Lang AS, Poulson RL, Prosser DJ, Sleeman JM, Stallknecht DE *et al*. (2022) Highly pathogenic avian influenza is an emerging disease threat to wild birds in North America. *J Wildl Manage* 86: e22171. https://doi.org/10.1002/jwmg.22171.

Reid K, Bell MA, Veeramah KR (2021) Threespine stickleback: a model system for evolutionary genomics. *Annu Rev Genomics Hum Genet* 22: 357–383. https://doi.org/10.1146/annurev-genom-111720-081402.

Rey O, Eizaguirre C, Angers B, Baltazar-Soares M, Sagonas K, Prunier JG, Blanchet S (2020) Linking epigenetics and biological conservation: towards a conservation epigenetics perspective. *Funct Ecol* 34: 414–427. https://doi.org/10.1111/1365-2435.13429.

Riddle MR, Aspiras AC, Gaudenz K, Peuß R, Sung JY, Martineau B, Peavey M, Box AC, Tabin JA, McGaugh S *et al*. (2018) Insulin resistance in cavefish as an adaptation to a nutrient-limited environment. *Nature* 555: 647–651. https://doi.org/10.1038/nature26136.

Rigal S, Dakos V, Alonso H, Auniņš A, Benkő Z, Brotons L, Chodkiewicz T, Chylarecki P, De Carli E, Del Moral JC *et al*. (2023) Farmland practices are driving bird population decline across Europe. *Proc Natl Acad Sci U S A* 120: e2216573120. https://doi.org/10.1073/pnas.2216573120.
Rothschild LJ, Mincinelli RL (2001) Life in extreme environments. *Nature* 409: 1092–1101. https://doi.org/10.1038/35059215.

Saaristo M, Brodin T, Balshine S, Bertram MG, Brooks BW, Ehlman SM, McCallum ES, Sih A, Sundin J, Wong BBM *et al*. (2018) Direct and indirect effects of chemical contaminants on the behaviour, ecology and evolution of wildlife. *Proc R Soc B Biol Sci* 285: 20181297. https://doi.org/10.1098/rspb.2018.1297.

Salmón P, Burraco P (2022) Telomeres and anthropogenic disturbances in wildlife: a systematic review and meta-analysis. *Mol Ecol* 31: 6018–6039. https://doi.org/10.1111/mec.16370.

Santivasi WL, Xia F (2014) Ionizing radiation-induced DNA damage, response, and repair. *Antioxidants Redox Signal* 21: 251–259. https://doi.org/10.1089/ars.2013.5668.

Schmidt R, Zummach C, Sinai N, Sabino-Pinto J, Künzel S, Dausmann KH, Ruthsatz K (2024) Physiological responses to a changing winter climate in an early spring-breeding amphibian. *Ecol Evol* 14: e70042. https://doi.org/10.1002/ece3.70042.

Scott GR, Egginton S, Richards JG, Milsom WK (2009) Evolution of muscle phenotype for extreme high altitude flight in the bar-headed goose. *Proc R Soc B Biol Sci* 276: 3645–3653. https://doi.org/10.1098/rspb.2009.0947.

Scott GR, Hawkes LA, Frappell PB, Butler PJ, Bishop CM, Milsom WK (2015) How bar-headed geese fly over the Himalayas. *Physiology* 30: 107–115. https://doi.org/10.1152/physiol.00050.2014.

Scott GR, Milsom WK (2007) Control of breathing and adaptation to high altitude in the bar-headed goose. *Am J Physiol Regul Integr Comp Physiol* 293: R379–R391. https://doi.org/10.1152/ajpregu.00161.2007.

Sohrabi M (2013) World high background natural radiation areas: need to protect public from radiation exposure. *Radiat Meas* 50: 166–171. https://doi.org/10.1016/j.radmeas.2012.03.011.

Sørensen JG, Kristensen TN, Loeschcke V (2003) The evolutionary and ecological role of heat shock proteins. *Ecol Lett* 6: 1025–1037. https://doi.org/10.1046/j.1461-0248.2003.00528.x.

Stanton RL, Morrissey CA, Clark RG (2018) Analysis of trends and agricultural drivers of farmland bird declines in North America: a review. *Agric Ecosyst Environ* 254: 244–254. https://doi.org/10.1016/j.agee.2017.11.028.

Stenseth NC, Durant JM, Fowler MS, Matthysen E, Adriaensen F, Jonzén N, Chan KS, Liu H, De Laet J, Sheldon BC *et al*. (2015) Testing for effects of climate change on competitive relationships and coexistence between two bird species. *Proc R Soc B Biol Sci* 282: 20141958. https://doi.org/10.1098/rspb.2014.1958.

Storey KB, Storey JM (2005) Biochemical adaptation to extreme environments. In W Walz, ed, *Biochemical Adaptation to Extreme Environments*. Humana Press, Totowa, NJ, pp. 169–200.

Storz JF, Liphardt S, Quiroga-Carmona M, Bautista NM, Opazo JC, Wheeler TB, D'Elía G, Good JM (2023) Genomic insights into the mys-

tery of mouse mummies on the summits of Atacama volcanoes. *Curr Biol* 33: R1040–R1042. https://doi.org/10.1016/j.cub.2023.08.081.

Storz JF, Scott GR (2023) To what extent do physiological tolerances determine elevational range limits of mammals? *J Physiol* 602: 5475–5484. https://doi.org/10.1113/JP284586.

Swan L (1970) Goose of the Himalayas. *Nat Hist* 70: 68–75.

Szulkin M, Munshi-South J, Charmantier A (2020) *Urban Evolutionary Biology*. Oxford University Press, Oxford. https://doi.org/10.1093/oso/9780198836841.001.0001.

Terrill RS, Shultz AJ (2023) Feather function and the evolution of birds. *Biol Rev* 98: 540–566. https://doi.org/10.1111/brv.12918.

Thiel V (2011) Extreme environments. In: J Reitner, V Thiel, eds, *Encyclopedia of Geobiology. Encyclopedia of Earth Sciences Series*. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9212-1_87.

Tobolka M, Zielińska Z, Fusani L, Huber N, Maggini I, Pola G, Marasco V (2024) Controlled expression of avian pre-migratory fattening influences indices of innate immunity. *Biol Open* 13: bio060018. https://doi.org/10.1242/bio.060018.

Tüzün N, Op de Beeck L, Brans K, Janssens L, Stoks R (2017) Microgeographic differentiation in thermal performance curves between rural and urban populations of an aquatic insect. *Evol Appl* 10: 1067–1075. https://doi.org/10.1111/eva.12512.

Ubach A, Páramo F, Prohom M, Stefanescu C (2022) Weather and butterfly responses: a framework for understanding population dynamics in terms of species’ life-cycles and extreme climatic events. *Oecologia* 199: 427–439. https://doi.org/10.1007/s00442-022-05188-7.

Van de Pol M, Jenouvrier S, Cornelissen JHC, Visser ME (2017) Behavioural, ecological and evolutionary responses to extreme climatic events: challenges and directions. *Philos Trans R Soc B Biol Sci* 372: 20160134. https://doi.org/10.1098/rstb.2016.0134.

Vanvelk H, Govaert L, van den Berg EM, Brans KI, De Meester L (2021) Interspecific differences, plastic, and evolutionary responses to a heat wave in three co-occurring daphnia species. *Limnol Oceanogr* 66: 1201–1220. https://doi.org/10.1002/lno.11675.

da Costa FV, Viana-Júnior AB, Aguilar R, Silveira FAO, Cornelissen TG (2023) Biodiversity and elevation gradients: insights on sampling biases across worldwide mountains. *J Biogeogr* 50: 1879–1889. https://doi.org/10.1111/jbi.14696.

Vicuña L, Fernandez MI, Vial C, Valdebenito P, Chaparro E, Espinoza K, Ziegler A, Bustamante A, Eyheramendy S (2019) Adaptation to extreme environments in an admixed human population from the Atacama Desert. *Genome Biol Evol* 11: 2468–2479. https://doi.org/10.1093/gbe/evz172.

Vitale G, Salvioli S, Franceschi C (2013) Oxidative stress and the aging endocrine system. *Nat Rev Endocrinol* 9: 228–240. https://doi.org/10.1038/nrendo.2013.29.

Wang Y, Guo B (2019) Adaption to extreme environments: a perspective from fish genomics. *Rev Fish Biol Fish* 29: 735–747. https://doi.org/10.1007/s11160-019-09577-9.
Ward S, Bishop CM, Woakes AJ, Butler PJ (2002) Heart rate and the rate of oxygen consumption of flying and walking barnacle geese (*Branta leucopsis*) and bar-headed geese (*Anser indicus*). *J Exp Biol* 205: 3347-3356. https://doi.org/10.1242/jeb.205.21.3347.

Webster MM, Hart PJB (2006) Kleptoparasitic prey competition in shoaling fish: effects of familiarity and prey distribution. *Behav Ecol* 17: 959-964. https://doi.org/10.1093/beheco/arl037.

Whiteman JP (2021) Polar Bear Behavior: Morphologic and physiologic adaptations. In: RW Davis, AM Pagano, eds. *Ethology and Behavioral Ecology of Sea Otters and Polar Bears*. Springer International Publishing, Cham, pp. 219-246. https://doi.org/10.1007/978-3-030-66796-2_12.

Wingfield JC, Kelley JP, Angelier F (2011) What are extreme environmental conditions and how do organisms cope with them? *Curr Zool* 57: 363-374. https://doi.org/10.1093/czoolo/57.3.363.

Xiong S, Wang W, Kenzior A, Olsen L, Krishnan J, Persons J, Medley G, Peuß R, Wang Y, Chen S *et al*. (2022) Enhanced lipogenesis through Ppary helps cavefish adapt to food scarcity. *Curr Biol* 32: 2272-2280.e6. https://doi.org/10.1016/j.cub.2022.03.038.

Zielonka NB, Shutt JD, Butler SJ, Dicks LV (2024) Management practices, and not surrounding habitats, drive bird and arthropod biodiversity within vineyards. *Agric Ecosyst Environ* 367: 108982. https://doi.org/10.1016/j.agee.2024.108982.