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    Ingestion of rubber tips of artificial turf fields by goldfish

    StatementsWe report our study in accordance with ARRIVE guidelines.Structure of artificial turf of ICUA schematic illustration of a ground plan of the artificial turf sports field of the ICU is shown in Fig. 1. This artificial turf was installed in 2013 by Japanese company B. The field is surrounded by ditches, and there are three drains that connect to sewer pipes. The artificial turf field of TGU was installed in 2011 by Japanese company C.Characterization of rubber tips of artificial turf field of ICU and TGURT were collected from the artificial fields of ICU and TGU. RT for the artificial turf field of ICU were made of residual part of rubber for making tires, window frames and windshields of automobiles. RT of ICU consists of a mixture of EPDM (ethylene-propylene-diene) and SBR (styrene-butadiene rubber) (personal communication from a Japanese company B). The RT of TGU was made of rubber of the residual part of rubber for making tires, window frames, etc. (personal communication from a Japanese company C). Information on raw material of the RT was not manifested.RT collected from the fields (ICU and TGU) was sieved to estimate the particle sizes. The RT of the ICU varied from 0.053 to 3.35 mm, and that of TGU varied from 0.212 to 3.35 mm. The specific gravity of the RT was obtained as follows: A certain amount of RT was weighed and poured into a 10 ml graduated cylinder containing some water. The total volume of the RT was obtained by measuring the rise in the meniscus of the water. The specific gravities of the tested RT were 1.28 (ICU) and 1.28 (TGU). Elemental analyses of RT (ICU and TGU) were conducted using micro-PIXE line analysis47, and calcium, sulfur, zinc, and iron were detected, but lead was under the detection limit from the RT of both ICU and TGU.Sampling of sediments in the ditches of the fieldTo examine the migration of RT from the field to the ditches, approximately 200 g of sediments in the ditches was sampled at four different sites, D1–D4 (Fig. 1), in the ICU. The ditch surrounding the field is made by connecting U-shaped concrete blocks and concrete lids. The inner width, length, and depth of the block are 24, 60, and 24 cm, respectively. The size of the lid is 33 × 60 × 4.5 cm with 1.5 × 9.0 cm snicks at short sides, which make an opening of the ditch of 3.0 × 9.0 cm size between two lids.Each sample was weighed (wet weight) and washed with water using a fine sieve to remove the soil. After the removal of the soil, the sediment was dried, and RT was collected manually. The collected RT was weighed, and the percentages of RT in the sediments were calculated (weight/weight).Goldfish and crucian carpA common variety of goldfish C. auratus of different sizes were obtained from a fish merchant in Saitama Prefecture and from a pet shop in Tokyo and then kept in the ICU. Approximately 200 fish of four different sizes (large, body weight (BW) ~ 100 g; medium, BW, ~ 30 g; small-medium, BW, ~ 15 g; small, BW ~ 4.0 g) were kept in three 800-L stock tanks maintained at 20 °C under a 16-h light/8-h dark (16 L/8 D) photoperiod (lights on at 06:00). Small body size fish were kept in a floating cage in one of the stock tanks. The fish were fed commercial floating goldfish feed (Itosui) once a day ad libitum. The fish stock tanks had circulation filtration systems equipped with sand filters. The filter was cleaned every week to maintain the water quality. The health condition of the fish was judged by their appetite. All the experimental fish (mixed sex) in the present study were kept in stock tanks for over two weeks before they were used for experiments. A total of 127 goldfish were used for the present study. The sample size of each experiment was determined by the results of preliminary experiments. Our preliminary survey confirmed that the fish feed we used did not contain RT-like substances. Therefore, the sample sizes of the control groups (goldfish) were smaller than those of the experimental groups to sacrifice fewer fish. All goldfish and crucian carp experiments were conducted in the ICU.Approximately 30 wild juvenile crucian carp C. auratus subsp. 2 weighing 1.4–4.6 g were obtained from a fish merchant in Saitama Prefecture and kept in an 800-L stock tank in the same conditions as that for goldfish. A total of 16 crucian carp were used for the present study.For the experiments, fish were transferred from the stock tanks to experimental 60-L glass aquaria, which were maintained at 20 °C under a 16-h light/8-h dark (16 L/8 D) photoperiod (lights on at 06:00). The experimental aquaria had a running water system, and dechlorinated tap water was added at 20 ml/min. Plastic box filters were also set to each experimental aquarium to maintain water quality. When stock fish were transferred to experimental aquaria, fish were randomly allocated to the aquaria. All the methods for using goldfish and crucian carp were performed in accordance with the guidelines of the Animal Experimentation Committee of International Christian University. The conduct of the present study was approved by the Animal Experimentation Committee of International Christian University.Co-ingestion of feed and RT by goldfish of three different body sizesWe examined whether RT are ingested by goldfish with feed and whether the body size of fish affects the ingestion of RT using three different body sizes of fish, large, medium, and small. First, we conducted an experiment using large body size fish (N = 24; BW, 91.9 ± 21.6 g, mean and SD). Three goldfish of large body size were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation of the environment and sinking fish feed. Fish were fed 3.0 g of large-size feed (Japan Pet Design Co. Ltd.) once a day. On the fourth day, fish were fed a mixture of RT collected from the field (ICU, 300 mg) and large feed (3.0 g). Control fish were fed only fish feed. At 90 min after feeding, the fish were transferred to a pail containing 0.05% 2-phenoxyethanol solution and deeply anesthetized. After body weight measurement, fish were dissected. We observed the intestine to determine whether RT was ingested. When RT was observed in the intestine, we collected the tips and counted the number of tips in each fish. The experimental tests were repeated eight times, and the data were combined.Second, we conducted an experiment using medium body size fish (N = 24; BW, 30.4 ± 12.4 g). Three goldfish of medium body size were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation. Fish were fed 1.0 g of medium-size feed (Kyorin) once a day. On the fourth day, fish were fed a mixture of RT (ICU, 300 mg) and medium feed (1.0 g). Control fish were fed only fish feed. At 90 min after feeding, fish were anesthetized and dissected, and then the intestine was observed as described above. The experimental tests were repeated eight times, and the data were combined.Third, we conducted an experiment using small body size fish (N = 40; BW, 4.4 ± 1.5 g). Four goldfish of small body size were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation. Fish were fed 0.5 g of small-size feed (Kyorin) once a day. On the fourth day, fish were fed a mixture of RT (ICU, 300 mg) and small feed (0.5 g). Because of the small size of fish, RT of small size particles (212–500 µm) were collected with sieves and used for the tests. Control fish were fed only fish feed. At 90 min after feeding, fish were anesthetized and dissected, and then the intestine was observed as described above. The experimental tests were repeated ten times, and the data were combined.In the first three experiments, all three control groups showed no ingestion of RT. From the results of the three experiments, it was clear that our experimental system was not contaminated with RT. Therefore, we omitted making control groups for further experiments to decrease the number of fish sacrificed from the standpoint of fish welfare.Fourth, we examined whether RT collected from TGU was ingested by goldfish. We conducted an experiment using large body size fish (N = 12; BW, 140.3 ± 27.0 g). Three goldfish of large body size were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation. Fish were fed 3.0 g of large-size feed once a day. On the fourth day, fish were fed a mixture of RT (TGU, 300 mg) and large feed (3.0 g). At 90 min after feeding, fish were anesthetized and dissected, and then the intestine was observed as described above. The experimental tests were repeated four times, and the data were combined.We conducted an additional experiment with a similar design to those of the four experiments to take photographs of the fish and RT using fish of small-medium body size (N = 9; BW, 12.8 ± 2.7 g). Three fish were transferred from the stock tank to the experimental 60-L glass aquarium and kept for two days for acclimation. Fish were given 0.5 g of medium-size feed once a day. On the third day, fish were given a mixture of RT of ICU (30 pieces; size 0.5–1.0 mm) and medium feed (0.5 g). At 60 min after feeding, fish were anesthetized and dissected, and photographs of RT in the intestine were taken. The experimental tests were repeated three times, and the data were combined.Active ingestion of RT by goldfishWe examined whether goldfish actively ingest RT when RT are given without fish feed using large body size fish (N = 9; BW, 122.4 ± 20.8 g). Three fish were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation. Fish were fed 3.0 g of large-size feed once a day. On the fourth day, fish were given 300 mg of RT (ICU) on the bottom of the aquarium. At 90 min after the placement of RT, fish were anesthetized and dissected, and then the intestine was observed as described above. The experimental tests were repeated three times, and the data were combined.Retention and elimination of ingested RT in the intestine of goldfishWe examined how long RT was retained in the intestine using large body size goldfish (N = 9; BW, 101.6 ± 11.4 g). Three goldfish were transferred from the stock tank to the experimental 60-L glass aquarium and kept for three days for acclimation. Fish were fed 3.0 g of large-size feed once a day. On Day 4, fish were given 1.0 g of RT (ICU). At 90 min after the placement of RT, each fish was individually transferred to three experimental 60-L glass aquaria. Then, each fish was fed 1.0 g of the feed. At 24 and 48 h (Day 5 and Day 6) after the transfer, we collected feces from fish and some water from the bottom of the aquaria. We observed whether RT was eliminated from the fish into the aquaria. When RT was observed in the feces and the bottom of the aquarium, we collected the RT and counted the number of RT. On Day 5, after the RT observation, each fish was fed 1.0 g of the feed. On Day 6, after RT observation in feces and water, the fish were anesthetized and dissected. We observed whether the intestine retained RT. The experimental tests were repeated three times, and the data were combined.Ingestion of RT by wild crucian carpWe examined whether wild Japanese crucian carp ingest RT. The experiment was conducted using juvenile crucian carp (N = 16, BW, 2.8 ± 0.9 g). Sixteen fish were transferred from the stock tank to three experimental 60-L glass aquaria (5 or 6 fish per aquarium) and kept for six days for acclimation. Fish were fed with 0.2 g of small-size feed once a day. On the seventh day, fish were fed a mixture of RT (ICU, 30 mg) and the small feed (0.2 g) or RT alone (30 mg). Because of the small size of fish, RT of small size particles (212–500 µm) were collected with sieves and used for the test. Control fish were fed only fish feed (0.2 g). At 6 h after feeding, fish were anesthetized and dissected, and then the intestine was observed as described above. More

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    Status does not predict stress among Hadza hunter-gatherer men

    Sapolsky, R. M. The influence of social hierarchy on primate health. Science 308, 648–652 (2005).Article 
    ADS 
    CAS 

    Google Scholar 
    Snyder-Mackler, N. et al. Social status alters immune regulation and response to infection in macaques. Science 354, 1041–1045 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Levy, E. J. et al. Higher dominance rank is associated with lower glucocorticoids in wild female baboons: A rank metric comparison. Horm. Behav. 125, 104826 (2020).Article 
    CAS 

    Google Scholar 
    Sapolsky, R. M. Social status and health in humans and other animals. Annu. Rev. Anthropol. 33, 393–418 (2004).Article 

    Google Scholar 
    Goymann, W. & Wingfield, J. C. Allostatic load, social status and stress hormones: the costs of social status matter. Anim. Behav. 67, 591–602 (2004).Article 

    Google Scholar 
    Cavigelli, S. A. & Chaudhry, H. S. Social status, glucocorticoids, immune function, and health: Can animal studies help us understand human socioeconomic-status-related health disparities?. Horm. Behav. 62, 295–313 (2012).Article 
    CAS 

    Google Scholar 
    Meyer, J. S. & Hamel, A. F. Models of stress in nonhuman primates and their relevance for human psychopathology and endocrine dysfunction. ILAR J. 55, 347–360 (2014).Article 
    CAS 

    Google Scholar 
    Saltzman, W., Schultz-Darken, N. J., Scheffler, G., Wegner, F. H. & Abbott, D. H. Social and reproductive influences on plasma cortisol in female marmoset monkeys. Physiol. Behav. 56, 801–810 (1994).Article 
    CAS 

    Google Scholar 
    Abbott, D. H. et al. Are subordinates always stressed? A comparative analysis of rank differences in cortisol levels among primates. Horm. Behav. 43, 67–82 (2003).Article 
    CAS 

    Google Scholar 
    Sadoughi, B., Lacroix, L., Berbesque, C., Meunier, H. & Lehmann, J. Effects of social tolerance on stress: Hair cortisol concentrations in the tolerant Tonkean macaques (Macaca tonkeana) and the despotic long-tailed macaques (Macaca fascicularis). Stress 1, 1–9 (2021).
    Google Scholar 
    Kawachi, I. & Berkman, L. Social cohesion, social capital, and health. Social Epidemiol. 174, 290–314 (2000).
    Google Scholar 
    Dong, M. et al. Insights into causal pathways for ischemic heart disease: adverse childhood experiences study. Circulation 110, 1761–1766 (2004).Article 

    Google Scholar 
    Galobardes, B., Lynch, J. W. & Davey Smith, G. Childhood socioeconomic circumstances and cause-specific mortality in adulthood: Systematic review and interpretation. Epidemiol. Rev. 26, 7–21 (2004).Article 

    Google Scholar 
    Lockwood, K. G., John-Henderson, N. A. & Marsland, A. L. Early life socioeconomic status associates with interleukin-6 responses to acute laboratory stress in adulthood. Physiol. Behav. 188, 212–220 (2018).Article 
    CAS 

    Google Scholar 
    Taylor, S. E. Mechanisms linking early life stress to adult health outcomes. Proc. Natl. Acad. Sci. 107, 8507–8512 (2010).Article 
    ADS 
    CAS 

    Google Scholar 
    Uchino, B. N. Social Support and Physical Health: Understanding the Health Consequences of Relationships (Yale University Press, 2004).Book 

    Google Scholar 
    Holt-Lunstad, J. & Uchino, B. N. Social support and health. Health Behav. Theory Res. Pract. 1, 183–204 (2015).
    Google Scholar 
    Gurven, M., Allen-Arave, W., Hill, K. & Hurtado, A. M. Reservation food sharing among the Ache of Paraguay. Hum. Nat. 12, 273–297 (2001).Article 
    CAS 

    Google Scholar 
    Hill, K. & Hurtado, A. M. Ache Life History: The Ecology and Demography of a Foraging People (Routledge, 2017).Book 

    Google Scholar 
    Kraft, T. S., Venkataraman, V. V., Tacey, I., Dominy, N. J. & Endicott, K. M. Foraging performance, prosociality, and kin presence do not predict lifetime reproductive success in Batek hunter-gatherers. Hum. Nat. 30, 71–97 (2019).Article 

    Google Scholar 
    Venkataraman, V. V., Kraft, T. S., Dominy, N. J. & Endicott, K. M. Hunter-gatherer residential mobility and the marginal value of rainforest patches. Proc. Natl. Acad. Sci. 114, 3097–3102 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Woodburn, J. Egalitarian societies. Man 1, 431–451 (1982).Article 

    Google Scholar 
    Marlowe, F. The Hadza: Hunter-Gatherers of Tanzania Vol. 3 (University of California Press, 2010).
    Google Scholar 
    Fedurek, P. et al. Status does not predict stress: Women in an egalitarian hunter–gatherer society. Evol. Hum. Sci. 2, 1–10 (2020).
    Google Scholar 
    Kornienko, O. & Santos, C. E. The effects of friendship network popularity on depressive symptoms during early adolescence: Moderation by fear of negative evaluation and gender. J. Youth Adolesc. 43, 541–553 (2014).Article 

    Google Scholar 
    Smelser, N. J. & Baltes, P. B. International Encyclopedia of the Social & Behavioral Sciences Vol. 11 (Elsevier, 2001).
    Google Scholar 
    Kim, D. A., Benjamin, E. J., Fowler, J. H. & Christakis, N. A. Social connectedness is associated with fibrinogen level in a human social network. Proc. R. Soc. B Biol. Sci. 283, 20160958 (2016).Article 

    Google Scholar 
    Kindermann, T. A. & Gest, S. D. Assessment of the peer group: Identifying naturally occurring social networks and capturing their effects. In Handbook of peer interactions, relationships, and groups, 100–117 (2009).Kornienko, O., Clemans, K. H., Out, D. & Granger, D. A. Friendship network position and salivary cortisol levels. Soc. Neurosci. 8, 385–396 (2013).Article 

    Google Scholar 
    La Greca, A. M. & Lopez, N. Social anxiety among adolescents: Linkages with peer relations and friendships. J. Abnorm. Child Psychol. 26, 83–94 (1998).Article 

    Google Scholar 
    Okamoto, J. et al. Social network status and depression among adolescents: An examination of social network influences and depressive symptoms in a Chinese sample. Res. Hum. Dev. 8, 67–88 (2011).Article 

    Google Scholar 
    Ulset, V. S. et al. Are unpopular children more likely to get sick? Longitudinal links between popularity and infectious diseases in early childhood. PLoS ONE 14, e0222222 (2019).Article 
    CAS 

    Google Scholar 
    Hawkes, K. Showing off: Tests of an hypothesis about men’s foraging goals. Ethol. Sociobiol. 12, 29–54 (1991).Article 

    Google Scholar 
    Smith, E. A. Why do good hunters have higher reproductive success?. Hum. Nat. 15, 343–364 (2004).Article 

    Google Scholar 
    Apicella, C. L., Feinberg, D. R. & Marlowe, F. W. Voice pitch predicts reproductive success in male hunter-gatherers. Biol. Lett. 3, 682–684 (2007).Article 
    CAS 

    Google Scholar 
    Apicella, C. L. Upper-body strength predicts hunting reputation and reproductive success in Hadza hunter–gatherers. Evol. Hum. Behav. 35, 508–518 (2014).Article 

    Google Scholar 
    Smith, K. M., Olkhov, Y. M., Puts, D. A. & Apicella, C. L. Hadza men with lower voice pitch have a better hunting reputation. Evol. Psychol. 15, 1474704917740466 (2017).Article 

    Google Scholar 
    MacDougall-Shackleton, S. A., Bonier, F., Romero, L. M. & Moore, I. T. Glucocorticoids and “stress” are not synonymous. Integr. Organ. Biol. 1, 017 (2019).
    Google Scholar 
    Ouellette, S. J. et al. Hair cortisol concentrations in higher-and lower-stress mother–daughter dyads: A pilot study of associations and moderators. Dev. Psychobiol. 57, 519–534 (2015).Article 
    CAS 

    Google Scholar 
    Stalder, T. et al. Stress-related and basic determinants of hair cortisol in humans: A meta-analysis. Psychoneuroendocrinology 77, 261–274 (2017).Article 
    CAS 

    Google Scholar 
    Heimbürge, S., Kanitz, E. & Otten, W. The use of hair cortisol for the assessment of stress in animals. Gen. Comp. Endocrinol. 270, 10–17 (2019).Article 

    Google Scholar 
    Fedurek, P. et al. Relationship between proximity and physiological stress levels in hunter-gatherers: The Hadza. Horm. Behav. 147, 105294 (2023).Article 

    Google Scholar 
    Bowers, K. et al. Maternal distress and hair cortisol in pregnancy among women with elevated adverse childhood experiences. Psychoneuroendocrinology 95, 145–148 (2018).Article 
    CAS 

    Google Scholar 
    Wells, S. et al. Associations of hair cortisol concentration with self-reported measures of stress and mental health-related factors in a pooled database of diverse community samples. Stress 17, 334–342 (2014).Article 
    CAS 

    Google Scholar 
    Faresjö, T. et al. Elevated levels of cortisol in hair precede acute myocardial infarction. Sci. Rep. 10, 1–8 (2020).Article 

    Google Scholar 
    Fuchs, A. et al. Link between children’s hair cortisol and psychopathology or quality of life moderated by childhood adversity risk. Psychoneuroendocrinology 90, 52–60 (2018).Article 
    CAS 

    Google Scholar 
    Staufenbiel, S. M., Penninx, B. W., Spijker, A. T., Elzinga, B. M. & van Rossum, E. F. Hair cortisol, stress exposure, and mental health in humans: A systematic review. Psychoneuroendocrinology 38, 1220–1235 (2013).Article 
    CAS 

    Google Scholar 
    Davison, B., Singh, G. R. & McFarlane, J. Hair cortisol and cortisone as markers of stress in Indigenous and non-Indigenous young adults. Stress 22, 210–220 (2019).Article 
    CAS 

    Google Scholar 
    Kim, E., Bolkan, C., Crespi, E. & Madigan, J. The relationship between hair cortisol, chronic stress, and well-being among older adults with dementia. Innov. Aging 3, S468 (2019).Article 

    Google Scholar 
    Woodburn, J. Egalitarian societies revisited. Proper. Equal. 1, 18–31 (2005).
    Google Scholar 
    Berbesque, J. C., Wood, B. M., Crittenden, A. N., Mabulla, A. & Marlowe, F. W. Eat first, share later: Hadza hunter–gatherer men consume more while foraging than in central places. Evol. Hum. Behav. 37, 281–286 (2016).Article 

    Google Scholar 
    Marlowe, F. W. & Berbesque, J. C. Tubers as fallback foods and their impact on Hadza hunter-gatherers. Am. J. Phys. Anthropol. 140, 751–758 (2009).Article 

    Google Scholar 
    Berbesque, J. C. & Marlowe, F. W. Sex differences in food preferences of Hadza hunter-gatherers. Evol. Psychol. 7, 147470490900700400 (2009).Article 

    Google Scholar 
    Hawkes, K., O’Connell, J. F. & Blurton Jones, N. G. Hunting income patterns among the Hadza: Big game, common goods, foraging goals and the evolution of the human diet. Philos. Trans. R. Soc. Lond. B 334, 243–251 (1991).Article 
    ADS 
    CAS 

    Google Scholar 
    Hawkes, K. Hunting and the evolution of egalitarian societies: Lessons from the Hadza. Hierarch. Action Cui Bono 27, 1–10 (2000).
    Google Scholar 
    Stibbard-Hawkes, D. N., Attenborough, R. D. & Marlowe, F. W. A noisy signal: To what extent are Hadza hunting reputations predictive of actual hunting skills?. Evol. Hum. Behav. 39, 639–651 (2018).Article 

    Google Scholar 
    Smith, K. M. & Apicella, C. Partner choice in human evolution: The role of character, hunting ability, and reciprocity in Hadza campmate selection. (2019).Smith, K. M. & Apicella, C. L. Hadza hunter-gatherers disagree on perceptions of moral character. Soc. Psychol. Pers. Sci. 11, 616–625 (2020).Article 

    Google Scholar 
    Gurven, M., Allen-Arave, W., Hill, K. & Hurtado, M. “It’s a wonderful life”: Signaling generosity among the Ache of Paraguay. Evol. Hum. Behav. 21, 263–282 (2000).Article 
    CAS 

    Google Scholar 
    Aktipis, A. et al. Cooperation in an uncertain world: For the Maasai of East Africa, need-based transfers outperform account-keeping in volatile environments. Hum. Ecol. 44, 353–364 (2016).Article 

    Google Scholar 
    Cronk, L. et al. Managing risk through cooperation: Need-based transfers and risk pooling among the societies of the Human Generosity Project. in Global Perspectives on Long Term Community Resource Management, 41–75 (Springer, 2019).Cronk, L. & Aktipis, A. Design principles for risk-pooling systems. Nat. Hum. Behav. 1, 1–9 (2021).
    Google Scholar 
    Jones, N. B. Demography and Evolutionary Ecology of Hadza Hunter-Gatherers Vol. 71 (Cambridge University Press, 2016).
    Google Scholar 
    Crittenden, A. N. et al. Oral health in transition: The Hadza foragers of Tanzania. PLoS ONE 12, e0172197 (2017).Article 

    Google Scholar 
    Bennett, F. J., Barnicot, N. A., Woodburn, J. C., Pereira, M. S. & Henderson, B. E. Studies on viral, bacterial, rickettsial and treponemal diseases in the Hadza of Tanzania and a note on injuries. Hum. Biol. 1, 243–272 (1973).
    Google Scholar 
    Ibar, C. et al. Evaluation of stress, burnout and hair cortisol levels in health workers at a University Hospital during COVID-19 pandemic. Psychoneuroendocrinology 128, 105213 (2021).Article 
    CAS 

    Google Scholar 
    Rajcani, J., Vytykacova, S., Solarikova, P. & Brezina, I. Stress and hair cortisol concentrations in nurses during the first wave of the COVID-19 pandemic. Psychoneuroendocrinology 129, 105245 (2021).Article 
    CAS 

    Google Scholar 
    Hill, K. R., Wood, B. M., Baggio, J., Hurtado, A. M. & Boyd, R. T. Hunter-gatherer inter-band interaction rates: Implications for cumulative culture. PLoS ONE 9, e102806 (2014).Article 
    ADS 

    Google Scholar 
    Bird, D. W., Bird, R. B., Codding, B. F. & Zeanah, D. W. Variability in the organization and size of hunter-gatherer groups: Foragers do not live in small-scale societies. J. Hum. Evol. 131, 96–108 (2019).Article 

    Google Scholar 
    Fedurek, P. et al. Social status does not predict in-camp integration among egalitarian hunter-gatherer men. Behav. Ecol. 33, 65–76 (2022).Article 

    Google Scholar 
    Ponzi, D., Muehlenbein, M. P., Geary, D. C. & Flinn, M. V. Cortisol, salivary alpha-amylase and children’s perceptions of their social networks. Soc. Neurosci. 11, 164–174 (2016).Article 

    Google Scholar 
    Marlowe, F. W. Mate preferences among Hadza hunter-gatherers. Hum. Nat. 15, 365–376 (2004).Article 

    Google Scholar 
    Von Rueden, C. R. & Jaeggi, A. V. Men’s status and reproductive success in 33 nonindustrial societies: Effects of subsistence, marriage system, and reproductive strategy. Proc. Natl. Acad. Sci. 113, 10824–10829 (2016).Article 

    Google Scholar 
    Townsend, C. Egalitarianism, Evolution Of (Wiley, 2018).Book 

    Google Scholar 
    Winterhalder, B. Diet choice, risk, and food sharing in a stochastic environment. J. Anthropol. Archaeol. 5, 369–392 (1986).Article 

    Google Scholar 
    Cornell, T. & Allen, T. B. War and Games Vol. 3 (Boydell Press, 2002).
    Google Scholar 
    Smáradóttir, S. Health and Wellbeing in the Arctic: The Critical Issues of Food Insecurity and Suicide Among Indigenous People.Finkler, H. W. Violence and the administration of justice: A focus on inuit communities in Northern Canada. BC Third World LJ 4, 137 (1983).
    Google Scholar 
    Bowles, S. Did warfare among ancestral hunter-gatherers affect the evolution of human social behaviors?. Science 324, 1293–1298 (2009).Article 
    ADS 
    CAS 

    Google Scholar 
    Fry, D. P. & Söderberg, P. Lethal aggression in mobile forager bands and implications for the origins of war. Science 341, 270–273 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Gat, A. Proving communal warfare among hunter-gatherers: The quasi-rousseauan error. Evol. Anthropol. 24, 111–126 (2015).Article 

    Google Scholar 
    Kreyszig, E. Bernstein polynomials and numerical integration. Int. J. Numer. Meth. Eng. 14, 292–295 (1979).Article 
    MATH 

    Google Scholar 
    Meyer, D. et al. Misc functions of the department of statistics, probability theory group (formerly: E1071). Package e1071. TU Wien (2015).R Development Core. A Language ans Environment for Statistical Computing. (R Found Stat Comput Vienna, 2018).Wennig, R. Potential problems with the interpretation of hair analysis results. Forensic Sci. Int. 107, 5–12 (2000).Article 
    CAS 

    Google Scholar 
    Kumari, M., Shipley, M., Stafford, M. & Kivimaki, M. Association of diurnal patterns in salivary cortisol with all-cause and cardiovascular mortality: Findings from the Whitehall II study. J. Clin. Endocrinol. Metab. 96, 1478–1485 (2011).Article 
    CAS 

    Google Scholar 
    Marmot, M. G. & Sapolsky, R. Of baboons and men: Social circumstances, biology, and the social gradient in health. in Sociality, hierarchy, health: Comparative biodemography: Papers from a workshop (2014).Hoffman, M. C., Karban, L. V., Benitez, P., Goodteacher, A. & Laudenslager, M. L. Chemical processing and shampooing impact cortisol measured in human hair. Clin. Investig. Med. 37, E252 (2014).Article 
    CAS 

    Google Scholar 
    Sauvé, B., Koren, G., Walsh, G., Tokmakejian, S. & Van Uum, S. H. Measurement of cortisol in human hair as a biomarker of systemic exposure. Clin. Investig. Med. 30, E183–E191 (2007).Article 

    Google Scholar 
    Slominski, R., Rovnaghi, C. R. & Anand, K. J. Methodological considerations for hair cortisol measurements in children. Ther. Drug Monit. 37, 812 (2015).Article 
    CAS 

    Google Scholar 
    Xiang, L., Sunesara, I., Rehm, K. E. & Marshall, G. D. Jr. A modified and cost-effective method for hair cortisol analysis. Biomarkers 21, 200–203 (2016).Article 
    CAS 

    Google Scholar 
    Tukey, J. Exploratory Data Analysis (Addison-Wesley, 1977).MATH 

    Google Scholar 
    Mangiafico, S. & Mangiafico, M. S. Package ‘rcompanion’. Cran Repos 1–71 (2017).Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. lmerTest package: Tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Article 

    Google Scholar 
    Bates, D. M. lme4: Mixed-Effects Modeling with R. (2010).Lüdecke, D. ggeffects: Tidy data frames of marginal effects from regression models. J. Stat. Softw. 3(26), 772. https://doi.org/10.21105/joss.00772 (2018).Article 

    Google Scholar 
    Nowok, B., Raab, G. M. & Dibben, C. synthpop: Bespoke creation of synthetic data in R. J. Stat. Softw. 74, 1–26 (2016).Article 

    Google Scholar  More

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    Combined metagenomic and metabolomic analyses reveal that Bt rice planting alters soil C-N metabolism

    Bt rice led to the redistribution of soil nitrogenTo characterize the influence of Bt rice on soil environmental biochemistry, samples were first separated into two portions including soils and surface waters. Bt proteins were not detected in surface waters from all cultivars (Supplemental Table S2). However, Bt protein contents for rhizospheres from all three cultivars and bulk soils ranged between 64.14 and 126.68 pg/g soil (Supplemental Table S3). Bt protein contents in samples from Bt rice grown in IRRI rice nutrient solution reached 850 pg/ml (Supplementary Table S1). We speculated that the vast majority of Bt protein released from Bt plants was bound tightly to soil particles and was thus difficult to isolate, purify, and detect. Total N, NH4+-N, NO3−-N, and NO2−-N contents in T1C-1 rhizospheres were significantly higher than in the Minghui 63 rhizospheres, although the soil pH of T1C-1 rhizospheres was also significantly lower than for Minghui 63 soils (Supplemental Table S3). Interestingly, the total N, NH4+-N, and NO3−-N contents in the Zhonghua11 rhizospheres were significantly higher than in the Minghui 63 rhizospheres, pointing to an apparent impact of genotypic differences from different conventional cultivars on soil nitrogen. No differences in organic matter and total P contents were identified among all soil samples (Supplemental Table S3). In addition, the surface waters of T1C-1 exhibited higher NO3-N contents than Minghui 63 soils, but lower pH values than Minghui 63 (Supplemental Table 2), consistent with soil results.
    Bt rice altered soil microbial communities, but not surface water communitiesSoil and surface water samples were collected and analyzed to characterize metagenomic profiles associated with different cultivars. A total of 11,529,157 and 2,880,919 genes were obtained for soil and surface water samples, respectively (Supplementary Table S4). The α diversity indices, Shannon–Wiener index (H’), Simpson index (D), and Evenness (E) were significantly higher in soils than in surface waters, but significant differences were not observed for Richness (R) (Fig. 2A). Except for R, the α diversity indices E, H′, and D were significantly higher in the T1C-1 rhizosphere than in the other samples, suggesting that Bt rice increased soil microbial diversity rather than altering taxonomic compositions. Differences in α diversity indices were not observed among all of the surface water samples (Supplementary Table S5). Principal coordinates analysis (PCoA) (Fig. 2B) based on microbial taxonomic level (genera) and functional classifications (clusters of orthologous groups of proteins, COG) indicated that soil samples from different rice cultivars and bulk soils formed distinct clusters in ordination space. These distinct groupings were not observed for surface water samples, suggesting that Bt rice cultivation altered soil microbial community composition and functions, but these changes did not occur in surface waters. The rhizospheres of T1C-1, Minghui 63, and Zhonghua 11 shared substantial overlap in total genera (Supplementary Fig. S2A). In addition, 40 genera specifically inhabited T1C-1 rhizospheres (Supplementary Fig. S2B). To further identify taxa that were differential between T1C-1 and Minghui 63 soils, the 50 most abundant genera that were differentially abundant for T1C-1 or Minghui 63 were specifically analyzed using a T-test. Among these, 33 were elevated in T1C-1 soils compared with Minghui 63 soils (Supplementary Fig. S3). Thus, the strongest enrichment was observed for taxa in T1C-1 soils, which is consistent with the general increased α diversity indices for T1C-1 communities (Supplementary Table S5).Fig. 2: Comparison of soil and surface water shotgun metagenomic sequencing data.A Differences in α-diversity metrics, Shannon–Wiener index (H′), Simpson index (D), Richness (R), and Evenness (E) between soil and surface water communities. Black asterisks indicate that the α-diversity index was significantly higher in soils (***, p  More

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    Climate change threatens unique evolutionary diversity in Australian kelp refugia

    Krumhansl, K. A. et al. Global patterns of kelp forest change over the past half-century. Proc. Natl. Acad. Sci. 113(48), 13785–13790. https://doi.org/10.1073/pnas.1606102113 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Wernberg, T. et al. Biology and ecology of the globally significant kelp Ecklonia radiata. Oceanogr. Mar. Biol. https://doi.org/10.1201/9780429026379-6 (2019).Article 

    Google Scholar 
    Bennett, S. et al. The ‘Great Southern Reef’: Social, ecological and economic value of Australia’s neglected kelp forests. Mar. Freshw. Res. 67(1), 47–56. https://doi.org/10.1071/MF15232 (2015).Article 

    Google Scholar 
    Eger, A. et al. The economic value of fisheries, blue carbon, and nutrient cycling in global marine forests. EcoEvoRxiv. https://doi.org/10.32942/osf.io/n7kjs (2021).Article 

    Google Scholar 
    Smith, K. E. et al. Socioeconomic impacts of marine heatwaves: Global issues and opportunities. Science 374, 6566. https://doi.org/10.1126/science.abj3593 (2021).Article 
    CAS 

    Google Scholar 
    Coleman, M. et al. Loss of a globally unique kelp forest and genetic diversity from the northern hemisphere. Sci. Rep. 12, 5020. https://doi.org/10.1038/s41598-022-08264-3 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Vergés, A. et al. Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory, and loss of kelp. Proc. Natl. Acad. Sci. 113(48), 13791–13796. https://doi.org/10.1073/pnas.1610725113 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353(6295), 169–172. https://doi.org/10.1126/science.aad8745 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Wood, G. et al. Genomic vulnerability of a dominant seaweed points to future-proofing pathways for Australia’s underwater forests. Glob. Change Biol. 27(10), 2200–2212. https://doi.org/10.1111/gcb.15534 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Vranken, S. et al. Genotype-environment mismatch of kelp forests under climate change. Mol. Ecol. 30(15), 3730. https://doi.org/10.1111/mec.15993 (2021).Article 

    Google Scholar 
    Assis, J. et al. Deep reefs are climatic refugia for genetic diversity of marine forests. J. Biogeogr. 43(4), 833–844. https://doi.org/10.1111/jbi.12677 (2016).Article 

    Google Scholar 
    Lourenço, C. R. et al. Upwelling areas as climate change refugia for the distribution and genetic diversity of a marine macroalga. J. Biogeogr. 43(8), 1595–1607. https://doi.org/10.1111/jbi.12744 (2016).Article 

    Google Scholar 
    Graham, M. H., Kinlan, B. P., Druehl, L. D., Garske, L. E. & Banks, S. Deep-water kelp refugia as potential hotspots of tropical marine diversity and productivity. Proc. Natl. Acad. Sci. 104(42), 16576–16580. https://doi.org/10.1073/pnas.0704778104 (2007).Article 
    ADS 

    Google Scholar 
    Marzinelli, E. M. et al. Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests. PLoS ONE 10, e0118390. https://doi.org/10.1371/journal.pone.0118390 (2015).Article 
    CAS 

    Google Scholar 
    Coleman, M. A. et al. Variation in the strength of continental boundary currents determines continent-wide connectivity in kelp. J. Ecol. 99(4), 1026–1032. https://doi.org/10.1111/j.1365-2745.2011.01822.x (2011).Article 

    Google Scholar 
    Hampe, A. & Petit, R. J. Conserving biodiversity under climate change: The rear edge matters. Ecol. Lett. 8(5), 461–467. https://doi.org/10.1111/j.1461-0248.2005.00739.x (2005).Article 

    Google Scholar 
    Maggs, C. A. et al. Evaluating signatures of glacial refugia for North Atlantic benthic marine taxa. Ecology 89(sp11), S108–S122. https://doi.org/10.1890/08-0257.1 (2008).Article 

    Google Scholar 
    Grant, W. S., Lydon, A. & Bringloe, T. T. Phylogeography of split kelp Hedophyllum nigripes: Northern ice-age refugia and trans-Arctic dispersal. Polar Biol. 43, 1829–1841. https://doi.org/10.1007/s00300-020-02748-6 (2020).Article 

    Google Scholar 
    Hoarau, G., Coyer, J. A., Veldsink, J. H., Stam, W. T. & Olsen, J. L. Glacial refugia and recolonization pathways in the brown seaweed Fucus serratus. Mol. Ecol. 16(17), 3606–3616. https://doi.org/10.1111/j.1365-294X.2007.03408.x (2007).Article 
    CAS 

    Google Scholar 
    Fraser, C. I., Nikula, R., Spencer, H. G. & Waters, J. M. Kelp genes reveal effects of subantarctic sea ice during the Last Glacial Maximum. Proc. Natl. Acad. Sci. 106(9), 3249–3253. https://doi.org/10.1073/pnas.0810635106 (2009).Article 
    ADS 

    Google Scholar 
    Assis, J. et al. Past climate changes and strong oceanographic barriers structured low-latitude genetic relics for the golden kelp Laminaria ochroleuca. J. Biogeogr. 45(10), 2326–2336. https://doi.org/10.1111/jbi.13425 (2018).Article 

    Google Scholar 
    Gersonde, R., Crosta, X., Abelmann, A. & Armand, L. Sea-surface temperature and sea ice distribution of the Southern Ocean at the EPILOG last glacial maximum—A circum-Antarctic view based on siliceous microfossil records. Quat. Sci. Rev. 24(7–9), 869–896. https://doi.org/10.1016/j.quascirev.2004.07.015 (2005).Article 
    ADS 

    Google Scholar 
    Bostock, H. C., Opdyke, B. N., Gagan, M. K., Kiss, A. E. & Fifield, L. K. Glacial/interglacial changes in the East Australian current. Clim. Dyn. 26, 645–659. https://doi.org/10.1007/s00382-005-0103-7 (2006).Article 

    Google Scholar 
    Brooke, B. P., Nichol, S. L., Huang, Z. & Beaman, R. J. Palaeoshorelines on the Australian continental shelf: Morphology, sea-level relationship and applications to environmental management and archaeology. Cont. Shelf Res. 134, 26–38. https://doi.org/10.1016/j.csr.2016.12.012 (2017).Article 
    ADS 

    Google Scholar 
    Williams, A. N., Ulm, S., Sapienza, T., Lewis, S. & Turney, C. S. M. Sea-level change and demography during the last glacial termination and early Holocene across the Australian continent. Quat. Sci. Rev. 182, 144–154. https://doi.org/10.1016/j.quascirev.2017.11.030 (2018).Article 
    ADS 

    Google Scholar 
    Durrant, H. M. S., Barrett, N. S., Edgar, G. J., Coleman, M. A. & Burridge, C. P. Shallow phylogeographic histories of key species in a biodiversity hotspot. Phycologia 54(6), 556–565. https://doi.org/10.2216/15-24.1 (2015).Article 

    Google Scholar 
    O’Hara, T. D. & Poore, G. C. B. Patterns of distribution for southern Australian marine echinoderms and decapods. J. Biogeogr. 27(6), 1321–1335. https://doi.org/10.1046/j.1365-2699.2000.00499.x (2000).Article 

    Google Scholar 
    Waters, J. M. Marine biogeographical disjunction in temperate Australia: Historical landbridge, contemporary currents, or both? Divers. Distrib. 14(4), 692–700. https://doi.org/10.1111/j.1472-4642.2008.00481.x (2008).Article 

    Google Scholar 
    Davis, T. R., Champion, C. & Coleman, M. A. Climate refugia for kelp within an ocean warming hotspot revealed by stacked species distribution modelling. Mar. Environ. Res. 166, 105267. https://doi.org/10.1016/j.marenvres.2021.105267 (2021).Article 
    CAS 

    Google Scholar 
    Barrows, T. T. & Juggins, S. Sea-surface temperatures around the Australian margin and Indian Ocean during the last glacial maximum. Quat. Sci. Rev. 24(7–9), 1017–1047. https://doi.org/10.1016/j.quascirev.2004.07.020 (2005).Article 
    ADS 

    Google Scholar 
    Richmond, S. & Stevens, T. Classifying benthic biotopes on sub-tropical continental shelf reefs: How useful are abiotic surrogates? Estuar. Coast. Shelf Sci. 138, 79–89. https://doi.org/10.1016/j.ecss.2013.12.012 (2014).Article 
    ADS 

    Google Scholar 
    Jordan, A. et al. Seabed Habitat Mapping of the Continental Shelf of NSW (New South Wales Department of Environment, Climate Change and Water, 2010).
    Google Scholar 
    Lewis, S. E., Sloss, C. R., Murray-Wallace, C. V., Woodroffe, C. D. & Smithers, S. G. Post-glacial sea-level changes around the Australian margin: A review. Quat. Sci. Rev. 74, 115–138. https://doi.org/10.1016/j.quascirev.2012.09.006 (2013).Article 
    ADS 

    Google Scholar 
    Millar, A. J. K. Marine benthic algae of Norfolk island, South Pacific. Aust. Syst. Bot. 12(4), 479–547. https://doi.org/10.1071/SB98004 (1999).Article 

    Google Scholar 
    Ridgway, K. R. & Dunn, J. R. Mesoscale structure of the mean East Australian current system and its relationship with topography. Prog. Oceanogr. 56, 189–222. https://doi.org/10.1016/S0079-6611(03)00004-1 (2003).Article 
    ADS 

    Google Scholar 
    Lough, J. M. & Hobday, A. J. Observed climate change in Australian marine and freshwater environments. Mar. Freshw. Res. 62(9), 984–999. https://doi.org/10.1071/MF10272 (2011).Article 

    Google Scholar 
    Sunday, J. M. et al. Species traits and climate velocity explain geographic range shifts in an ocean-warming hotspot. Ecol. Lett. 18(9), 944–953. https://doi.org/10.1111/ele.12474 (2015).Article 

    Google Scholar 
    Coleman, M. A. et al. Variation in the strength of continental boundary currents determines patterns of large-scale connectivity in kelp. J. Ecol. 99, 1026–1032 (2011).Article 

    Google Scholar 
    Maeda, T., Kawai, T., Nakaoka, M. & Yotsukura, N. Effective DNA extraction method for fragment analysis using capillary sequencer of the kelp, Saccharina. J. Appl. Phycol. 25, 337–347. https://doi.org/10.1007/s10811-012-9868-3 (2013).Article 
    CAS 

    Google Scholar 
    Lane, C. E., Lindstrom, S. C. & Saunders, G. W. A molecular assessment of northeast Pacific Alaria species (Laminariales, Phaeophyceae) with reference to the utility of DNA barcoding. Mol. Phylogenet. Evol. 44(2), 634–648. https://doi.org/10.1016/j.ympev.2007.03.016 (2007).Article 
    CAS 

    Google Scholar 
    Saunders, G. W. & McDevit, D. C. Acquiring DNA sequence data from dried archival red algae (Florideophyceae) for the purpose of applying available names to contemporary genetic species: A critical assessment. Botany 90, 191–203 (2012).Article 
    CAS 

    Google Scholar 
    Kearse, M. et al. Geneious basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28(12), 1647–1649. https://doi.org/10.1093/bioinformatics/bts199 (2012).Article 

    Google Scholar 
    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5), 1792–1797. https://doi.org/10.1093/nar/gkh340 (2004).Article 
    CAS 

    Google Scholar 
    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215(3), 403–410. https://doi.org/10.1016/S0022-2836(05)80360-2 (1990).Article 
    CAS 

    Google Scholar 
    Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34(12), 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).Article 
    CAS 

    Google Scholar 
    Clement, M., Posada, D. & Crandall, K. A. TCS: A computer program to estimate gene genealogies. Mol. Ecol. 9(10), 1657–1659. https://doi.org/10.1046/j.1365-294x.2000.01020.x (2000).Article 
    CAS 

    Google Scholar 
    Leigh, J. & Bryant, D. PopART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6(9), 1110–1116. https://doi.org/10.1111/2041-210X.12410 (2015).Article 

    Google Scholar 
    Inkscape Project. Inkscape Project. https://inkscape.org/ (2020).Coleman, M. A. et al. Connectivity within and among a network of temperate marine reserves. PLoS ONE 6(5), e20168. https://doi.org/10.1371/journal.pone.0020168 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Davis, T. R., Cadiou, G., Champion, C. & Coleman, M. A. Environmental drivers and indicators of change in habitat and fish assemblages within a climate change hotspot. Reg. Mar. Stud. https://doi.org/10.1016/j.rsma.2020.101295 (2020).Article 

    Google Scholar 
    Mix, A. C., Bard, E. & Schneider, R. Environmental processes of the ice age: Land, oceans, glaciers (EPILOG). Quat. Sci. Rev. 20(4), 627–657. https://doi.org/10.1016/S0277-3791(00)00145-1 (2001).Article 
    ADS 

    Google Scholar 
    Waters, J. M. Competitive exclusion: Phylogeography’s ‘elephant in the room’? Mol. Ecol. 20(21), 4388–4394. https://doi.org/10.1111/j.1365-294X.2011.05286.x (2011).Article 

    Google Scholar 
    Cresswell, G. R., Peterson, J. L. & Pender, L. F. The East Australian current, upwellings and downwellings off eastern-most Australia in summer. Mar. Freshw. Res. 68(7), 1208–1223. https://doi.org/10.1071/MF16051 (2016).Article 

    Google Scholar 
    Hewitt, G. Some genetic consequences of ice ages, and their role in divergence and speciation. Biol. J. Linn. Soc. 58(3), 247–276. https://doi.org/10.1006/bijl.1996.0035 (1995).Article 

    Google Scholar 
    Waters, J. M., Fraser, C. I. & Hewitt, G. M. Founder takes all: Density-dependent processes structure biodiversity. Trends Ecol. Evol. 28(2), 78–85. https://doi.org/10.1016/j.tree.2012.08.024 (2013).Article 

    Google Scholar 
    Wernberg, T. et al. Genetic diversity and kelp forest vulnerability to climatic stress. Sci. Rep. 8(1851), 1–8. https://doi.org/10.1038/s41598-018-20009-9 (2018).Article 
    CAS 

    Google Scholar 
    Coleman, M. A. & Kelaher, B. P. Connectivity among fragmented populations of a habitat-forming alga, Phyllospora comosa (Phaeophyceae, Fucales) on an urbanised coast. Mar. Ecol. Prog. Ser. 381, 63–70 (2009).Article 
    ADS 

    Google Scholar 
    Drábková, L. Z. DNA extraction from herbarium specimens. In Molecular Plant Taxonomy. Methods in Molecular Biology Vol. 1115 (ed. Besse, P.) (Humana Press, 2014).
    Google Scholar 
    Goff, L. J. & Moon, D. A. PCR amplification of nuclear and plastid genes from algal herbarium specimens and algal spores 1. J. Phycol. 29, 381 (1993).Article 
    CAS 

    Google Scholar 
    Nahor, O., Luzzatto-Knaan, T. & Israel, A. A new genetic lineage of Asparagopsis taxiformis (Rhodophyta) in the Mediterranean Sea: As the DNA barcoding indicates a recent Lessepsian introduction. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.873817 (2022).Article 

    Google Scholar 
    Coleman, M. A. & Brawley, S. H. Variability in temperature and historical patterns in reproduction in the Fucus distichus complex (Heterokontophyta; Phaeophyceae): Implications for speciation and collection of herbarium specimens. J. Phycol. 41, 1110–1119 (2005).Article 

    Google Scholar 
    Martins, N. et al. Hybrid vigour for thermal tolerance in hybrids between the allopatric kelps Laminaria digitata and L. pallida (Laminariales, Phaeophyceae) with contrasting thermal affinities. Eur. J. Phys. 54(4), 548–561 (2019).CAS 

    Google Scholar  More

  • in

    Metamorphic aerial robot capable of mid-air shape morphing for rapid perching

    Akçakaya, H. R. et al. Quantifying species recovery and conservation success to develop an IUCN Green List of Species. Conserv. Biol. 32, 1128–1138. https://doi.org/10.1111/cobi.13112 (2018).Article 

    Google Scholar 
    IUCN. The IUCN Red List of Threatened Species. Version 2021-3 (2022).Zellweger, F., De Frenne, P., Lenoir, J., Rocchini, D. & Coomes, D. Advances in microclimate ecology arising from remote sensing. Trends Ecol. Evol. 34, 327–341. https://doi.org/10.1016/j.tree.2018.12.012 (2019).Article 

    Google Scholar 
    Mohan, M. et al. Individual tree detection from unmanned aerial vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest. Forestshttps://doi.org/10.3390/f8090340 (2017).Article 

    Google Scholar 
    Dronova, I., Kislik, C., Dinh, Z. & Kelly, M. A review of unoccupied aerial vehicle use in wetland applications: Emerging opportunities in approach, technology, and data. Droneshttps://doi.org/10.3390/drones5020045 (2021).Article 

    Google Scholar 
    Farinha, A. & Lima, P. U. A novel underactuated hand suitable for human-oriented domestic environments. In: Proceedings – 2016 International Conference on Autonomous Robot Systems and Competitions, ICARSC 2016 106–111, https://doi.org/10.1109/ICARSC.2016.21 (2016).Hamaza, S., Georgilas, I., Heredia, G., Ollero, A. & Richardson, T. Design, modeling, and control of an aerial manipulator for placement and retrieval of sensors in the environment. J. Field Robotics 37, 1224–1245. https://doi.org/10.1002/rob.21963 (2020).Article 

    Google Scholar 
    Nakamura, A. et al. Forests and their canopies: Achievements and horizons in canopy science. Trends Ecol. Evol. 32, 438–451. https://doi.org/10.1016/j.tree.2017.02.020 (2017).Article 

    Google Scholar 
    Hang, K. et al. Perching and resting – A paradigm for UAV maneuvering with modularized landing gears. Sci. Roboticshttps://doi.org/10.1126/scirobotics.aau6637 (2019).Article 

    Google Scholar 
    Danko, T. W., Kellas, A. & Oh, P. Y. Robotic rotorcraft and perch-and-stare: Sensing landing zones and handling obscurants. In ICAR ’05. Proceedings., 12th International Conference on Advanced Robotics, 2005 296–302, https://doi.org/10.1109/ICAR.2005.1507427 (2005).Pauli, J. N., Zachariah Peery, M., Fountain, E. D. & Karasov, W. H. Arboreal folivores limit their energetic output, all the way to slothfulness. Am. Nat. 188, 196–204, https://doi.org/10.1086/687032 (2016).Olson, R. A., Glenn, Z. D., Cliffe, R. N. & Butcher, M. T. Architectural properties of sloth forelimb muscles (Pilosa: Bradypodidae). J. Mamm. Evol. 25, 573–588. https://doi.org/10.1007/s10914-017-9411-z (2018).Article 

    Google Scholar 
    Kovač, M., Germann, J., Hürzeler, C., Siegwart, R. Y. & Floreano, D. A perching mechanism for micro aerial vehicles. J. Micro-Nano Mechatron. 5, 77–91. https://doi.org/10.1007/s12213-010-0026-1 (2009).Article 

    Google Scholar 
    Toon, J. ’SlothBot in the Garden’ Demonstrates Hyper-Efficient Conservation Robot.Thomas, J. et al. Aggressive flight with quadrotors for perching on inclined surfaces. J. Mech. Robot. 8, 51007. https://doi.org/10.1115/1.4032250 (2016).Article 

    Google Scholar 
    Daler, L., Klaptocz, A., Briod, A., Sitti, M. & Floreano, D. A perching mechanism for flying robots using a fibre-based adhesive. In 2013 IEEE International Conference on Robotics and Automation, 4433–4438 (IEEE, 2013).Kovač, M., Germann, J., Hürzeler, C., Siegwart, R. Y. & Floreano, D. A perching mechanism for micro aerial vehicles. J. Micro-Nano Mechatron. 5, 77–91 (2009).Article 

    Google Scholar 
    Pope, M. T. et al. A multimodal robot for perching and climbing on vertical outdoor surfaces. IEEE Trans. Rob. 33, 38–48. https://doi.org/10.1109/TRO.2016.2623346 (2017).Article 

    Google Scholar 
    Lussier Desbiens, A., Asbeck, A. T. & Cutkosky, M. R. Landing, perching and taking off from vertical surfaces. Int. J. Robotics Res. 30, 355–370 (2011).Article 

    Google Scholar 
    Nguyen, H.-N., Siddall, R., Stephens, B., Navarro-Rubio, A. & Kovač, M. A Passively adaptive microspine grapple for robust, controllable perching. In 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft), 80–87 (IEEE, 2019).Braithwaite, A., Al Hinai, T., Haas-Heger, M., McFarlane, E. & Kovač, M. Tensile web construction and perching with nano aerial vehicles. In Robotics Research (eds Bicchi, A. & Burgard, W.) (Springer, Cham, 2018).
    Google Scholar 
    Zhang, K., Chermprayong, P., Alhinai, T. M., Siddall, R. & Kovac, M. SpiderMAV: Perching and stabilizing micro aerial vehicles with bio-inspired tensile anchoring systems. In International Conference on Intelligent Robots and Systems (2017).Roderick, W. R. T., Jiang, H., Wang, S., Lentink, D. & Cutkosky, M. R. Bioinspired grippers for natural curved surface perching. In Conference on Biomimetic and Biohybrid Systems, 604–610 (Springer, 2017).Thomas, J., Loianno, G., Daniilidis, K. & Kumar, V. Visual servoing of quadrotors for perching by hanging from cylindrical objects. IEEE Robotics Automation Lett.https://doi.org/10.1109/LRA.2015.2506001 (2016).Article 

    Google Scholar 
    McLaren, A., Fitzgerald, Z., Gao, G. & Liarokapis, M. A passive closing, tendon driven, adaptive robot hand for ultra-fast, aerial grasping and perching. In IEEE International Conference on Intelligent Robots and Systems 5602–5607, https://doi.org/10.1109/IROS40897.2019.8968076 (2019).Zhang, Z., Xie, P. & Ma, O. Bio-inspired trajectory generation for UAV perching. In 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 997–1002 (IEEE, 2013).Doyle, C. E. et al. An avian-inspired passive mechanism for quadrotor perching. IEEE/ASME Trans. Mechatron. 18, 506–517. https://doi.org/10.1109/TMECH.2012.2211081 (2013).Article 

    Google Scholar 
    Erbil, M. A., Prior, S. D. & Keane, A. J. Design optimisation of a reconfigurable perching element for vertical take-off and landing unmanned aerial vehicles. Int. J. Micro Air Veh. 5, 207–228 (2013).Article 

    Google Scholar 
    Chi, W., Low, K. H., Hoon, K. H. & Tang, J. An optimized perching mechanism for autonomous perching with a quadrotor. In IEEE International Conference on Robotics and Automation, 3109–3115, (2014). https://doi.org/10.1109/ICRA.2014.6907306Roderick, W. R. T., Cutkosky, M. R. & Lentink, D. Bird-inspired dynamic grasping and perching in arboreal environments. Sci. Roboticshttps://doi.org/10.1126/scirobotics.abj7562 (2021).Article 

    Google Scholar 
    Garcia-Rubiales, F. J., Ramon-Soria, P., Arrue, B. C., Ollero, A. Magnetic & detaching system for Modular UAVs with perching capabilities in industrial environments.,. International Workshop on Research. Education and Development on Unmanned Aerial Systems, RED-UAS2019(172–176), 2019. https://doi.org/10.1109/REDUAS47371.2019.8999704 (2019).Bai, L. et al. Design and experiment of a deformable bird-inspired UAV perching mechanism. J. Bionic Eng. 18, 1304–1316. https://doi.org/10.1007/s42235-021-00098-5 (2021).Article 

    Google Scholar 
    Joachimczak, M., Suzuki, R. & Arita, T. Artificial metamorphosis: Evolutionary design of transforming, soft-bodied robots. Artif. Life 22(271–298), 2016. https://doi.org/10.1162/artl_a_00207 (2016).Article 

    Google Scholar 
    Sims, K. Evolving Virtual Creatures. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’94, 15-22, https://doi.org/10.1145/192161.192167 (Association for Computing Machinery, 1994).Bongard, J. Morphological change in machines accelerates the evolution of robust behavior. Proc. Natl. Acad. Sci. 108, 1234–1239. https://doi.org/10.1073/pnas.1015390108 (2011).Article 
    ADS 

    Google Scholar 
    Truman, J. W. & Riddiford, L. M. The origins of insect metamorphosis. Nature 401, 447–452. https://doi.org/10.1038/46737 (1999).Article 
    ADS 
    CAS 

    Google Scholar 
    Campbell, N. A. et al. Biology: A Global Approach (Pearson New Your, NY, 2018).
    Google Scholar 
    Dai, J. S. & Rees Jones, J. Mobility in metamorphic mechanisms of foldable/erectable kinds. J. Mech. Des. 121, 375. https://doi.org/10.1115/1.2829470 (1999).Article 

    Google Scholar 
    Mintchev, S. & Floreano, D. Adaptive morphology: A design principle for multimodal and multifunctional robots. IEEE Robot. Autom. Mag. 23, 42–54 (2016).Article 

    Google Scholar 
    Shah, D. et al. Shape changing robots: Bioinspiration, simulation, and physical realization. Adv. Mater. 33, 2002882 (2021).Article 
    CAS 

    Google Scholar 
    Sareh, S., Siddall, R., Alhinai, T. & Kovac, M. Bio-inspired soft aerial robots: Adaptive morphology for high-performance flight. In Soft Robotics: Trends, Applications and Challenges, 65–74 (Springer, 2017).Derrouaoui, S. H., Bouzid, Y., Guiatni, M. & Dib, I. A comprehensive review on reconfigurable drones: classification characteristics design and control technologies. Unmanned Syst. 10(01), 3–29. https://doi.org/10.1142/S2301385022300013 (2022).Floreano, D. & Wood, R. J. Science, technology and the future of small autonomous drones. Nature 521, 460–466 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Hwang, D., Barron, E. J., Haque, A. B. & Bartlett, M. D. Shape morphing mechanical metamaterials through reversible plasticity. Sci. Robotics 7, eabg2171. https://doi.org/10.1126/scirobotics.abg2171 (2022).Article 

    Google Scholar 
    Siddall, R., Ortega Ancel, A. & Kovač, M. Wind and water tunnel testing of a morphing aquatic micro air vehicle. Interface focus 7, 20160085. https://doi.org/10.1098/rsfs.2016.0085 (2017).Article 

    Google Scholar 
    Chen, Y. et al. A biologically inspired, flapping-wing, hybrid aerial-aquatic microrobot. Sci. Roboticshttps://doi.org/10.1126/scirobotics.aao5619 (2017).Article 

    Google Scholar 
    Daler, L., Mintchev, S., Stefanini, C. & Floreano, D. A bioinspired multi-modal flying and walking robot. Bioinspiration Biomim.https://doi.org/10.1088/1748-3190/10/1/016005 (2015).Article 

    Google Scholar 
    Kovač, M., Wassim-Hraiz, Fauria, O., Zufferey, J. C. & Floreano, D. The EPFL jumpglider: A hybrid jumping and gliding robot with rigid or folding wings. In 2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011 1503–1508, https://doi.org/10.1109/ROBIO.2011.6181502 (2011).Riviere, V., Manecy, A. & Viollet, S. Agile robotic fliers: A morphing-based approach. Soft Roboticshttps://doi.org/10.1089/soro.2017.0120 (2018).Article 

    Google Scholar 
    Bucki, N. & Mueller, M. W. Design and control of a passively morphing quadcopter. In IEEE International Conference on Robotics and Automation, vol. 2019-May, 9116–9122, https://doi.org/10.1109/ICRA.2019.8794373 (2019).Mintchev, S., Daler, L., Eplattenier, G. L., Floreano, D. & Member, S. Foldable and self – deployable pocket sized quadrotor. In Proc. of the IEEE Conference on Robotics and Automation 2190–2195 (2015).Mintchev, S., Shintake, J. & Floreano, D. Bioinspired dual-stiffness origami. Sci. Robotics 0275, 1–8. https://doi.org/10.1126/scirobotics.aau0275 (2018).Article 

    Google Scholar 
    Zhao, M., Kawasaki, K., Anzai, T., Chen, X. & Noda, S. Transformable multirotor with two-dimensional multilinks : Modeling, control, and whole-body aerial manipulation. Int. J. Robot. Res.https://doi.org/10.1177/0278364918801639 (2018).Article 

    Google Scholar 
    Bucki, N., Tang, J. & Mueller, M. W. Design and control of a midair-reconfigurable quadcopter using unactuated hinges. IEEE Trans. Rob.https://doi.org/10.1109/TRO.2022.3193792 (2022).Article 

    Google Scholar 
    Shimoyama, I., Miura, H., Suzuki, K. & Ezura, Y. Insect-like microrobots with external skeletons. IEEE Control Syst. Mag. 13, 37–41. https://doi.org/10.1109/37.184791 (1993).Article 

    Google Scholar 
    Noh, M., Kim, S.-W., An, S., Koh, J.-S. & Cho, K.-J. Flea-inspired catapult mechanism for miniature jumping robots. IEEE Trans. Rob. 28, 1007–1018. https://doi.org/10.1109/tro.2012.2198510 (2012).Article 
    ADS 

    Google Scholar 
    Miyashita, S., Guitron, S., Ludersdorfer, M., Sung, C. R. & Rus, D. An untethered miniature origami robot that self-folds, walks, swims, and degrades. In Proceedings – IEEE International Conference on Robotics and Automation 2015-June, 1490–1496, https://doi.org/10.1109/ICRA.2015.7139386 (2015).Morgan, J., Magleby, S. P. & Howell, L. L. An approach to designing origami-adapted aerospace mechanisms. J. Mech. Des.https://doi.org/10.1115/1.4032973 (2016).Article 

    Google Scholar 
    Liang, X. et al. The AmphiHex: A novel amphibious robot with transformable leg-flipper composite propulsion mechanism. In IEEE International Conference on Intelligent Robots and Systems 3667–3672, https://doi.org/10.1109/IROS.2012.6386238 (2012).Polygerinos, P. et al. Soft robotics: Review of fluid-driven intrinsically soft devices; manufacturing, sensing, control, and applications in human-robot interaction. Adv. Eng. Mater.https://doi.org/10.1002/adem.201700016 (2017).Article 

    Google Scholar 
    Coyle, S., Majidi, C., LeDuc, P. & Hsia, K. J. Bio-inspired soft robotics: Material selection, actuation, and design. Extreme Mech. Lett. 22, 51–59. https://doi.org/10.1016/j.eml.2018.05.003 (2018).Article 

    Google Scholar 
    Rus, D. & Tolley, M. T. Design, fabrication and control of soft robots. Nature 521, 467–475. https://doi.org/10.1038/nature14543 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Laschi, C., Mazzolai, B. & Cianchetti, M. Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Sci. Robotics 1, eaah3690. https://doi.org/10.1126/scirobotics.aah3690 (2016).Article 

    Google Scholar 
    Boyraz, P., Runge, G. & Raatz, A. An overview of novel actuators for soft robotics. High Throughput 7, 1–21. https://doi.org/10.3390/act7030048 (2018).Article 

    Google Scholar 
    Miriyev, A., Stack, K. & Lipson, H. Soft material for soft actuators. Nat. Commun. 8, 1–8. https://doi.org/10.1038/s41467-017-00685-3 (2017).Article 
    CAS 

    Google Scholar 
    Nguyen, P. H. & Kovač, M. Adopting physical artificial intelligence in soft aerial robots. IOP Conf. Ser.: Mater. Sci. Eng. 1261, 012006. https://doi.org/10.1088/1757-899X/1261/1/012006 (2022).Article 

    Google Scholar 
    Kim, S.-J., Lee, D.-Y., Jung, G.-P. & Cho, K.-J. An origami-inspired, self-locking robotic arm that can be folded flat. Sci. Robotics 3, eaar2915. https://doi.org/10.1126/scirobotics.aar2915 (2018).Article 

    Google Scholar 
    Ruiz, F., Arrue, B. C. & Ollero, A. SOPHIE: Soft and flexible aerial vehicle for physical interaction with the environment. IEEE Robotics Automation Lett. 7, 11086–11093. https://doi.org/10.1109/LRA.2022.3196768 (2022).Article 

    Google Scholar 
    Doshi, N. et al. Model driven design for flexure-based microrobots. In IEEE International Conference on Intelligent Robots and Systems 2015-Decem, 4119–4126, https://doi.org/10.1109/IROS.2015.7353959 (2015).Koh, J.-S., Doshi, N., Wood, R. J., Temel, F. Z. & McClintock, H. The milliDelta: A high-bandwidth, high-precision, millimeter-scale Delta robot. Sci. Robotics 3, eaar3018. https://doi.org/10.1126/scirobotics.aar3018 (2018).Article 

    Google Scholar 
    Backus, S. B., Sustaita, D., Odhner, L. U. & Dollar, A. M. Mechanical analysis of avian feet: Multiarticular muscles in grasping and perching. R. Soc. Open Sci.https://doi.org/10.1098/rsos.140350 (2015).Article 

    Google Scholar 
    Paine, C. E. T. et al. Functional explanations for variation in bark thickness in tropical rain forest trees. Funct. Ecol. 24, 1202–1210. https://doi.org/10.1111/j.1365-2435.2010.01736.x (2010).Article 

    Google Scholar 
    Miriyev, A. & Kovač, M. Skills for physical artificial intelligence. Nat. Mach. Intell. 2, 658–660. https://doi.org/10.1038/s42256-020-00258-y (2020).Article 

    Google Scholar 
    Felton, S., Tolley, M., Demaine, E., Rus, D. & Wood, R. A method for building self-folding machines. Science 345, 644–646. https://doi.org/10.1126/science.1252610 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Siddall, R., Byrnes, G., Full, R. J. & Jusufi, A. Tails stabilize landing of gliding geckos crashing head-first into tree trunks. Commun. Biol. 4, 1–12. https://doi.org/10.1038/s42003-021-02378-6 (2021).Article 
    CAS 

    Google Scholar 
    Feduccia, A. Evidence from claw geometry indicating arboreal habits of Archaeopteryx. Science 259, 790–793. https://doi.org/10.1126/science.259.5096.790 (1993).Article 
    ADS 
    CAS 

    Google Scholar  More

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    Impact of meltwater flow intensity on the spatiotemporal heterogeneity of microbial mats in the McMurdo Dry Valleys, Antarctica

    Doran PT, Lyons WB, McKnight DM. Life in Antarctic deserts and other cold dry environments: astrobiological analogs. Cambridge: Cambridge University Press; 2010.Barrett JE, Virginia RA, Lyons WB, McKnight DM, Priscu JC, Doran PT, et al. Biogeochemical stoichiometry of Antarctic dry valley ecosystems. J Geophys Res Biogeosci. 2007;112:1–12.Doran PT, McKay CP, Clow GD, Dana GL, Fountain AG, Nylen T, et al. Valley floor climate observations from the McMurdo Dry Valleys, Antarctica, 1986–2000. J Geophys Res Atmosph. 2002;107:ACL 13-1-ACL -2.Fountain AG, Nylen TH, Monaghan A, Basagic HJ, Bromwich D. Snow in the McMurdo dry valleys, Antarctica. Int J Climatol J R Meteorol Soc. 2010;30:633–42.Article 

    Google Scholar 
    Hawes I, Schwarz AM. Absorption and utilization of irradiance by cyanobacterial mats in two ice‐covered antarctic lakes with contrasting light climates. J Phycol. 2001;37:5–15.Article 
    CAS 

    Google Scholar 
    McKnight DM, Niyogi DK, Alger AS, Bomblies A, Conovitz PA, Tate CM. Dry valley streams in Antarctica: ecosystems waiting for water. Bioscience. 1999;49:985–95.Article 

    Google Scholar 
    Toner JD, Sletten RS, Prentice ML. Soluble salt accumulations in Taylor Valley, Antarctica: implications for paleolakes and Ross Sea Ice Sheet dynamics. J Geophys Res Earth Surface. 2013;118:198–215.Article 
    CAS 

    Google Scholar 
    Doran PT, Priscu JC, Lyons WB, Walsh JE, Fountain AG, McKnight DM, et al. Antarctic climate cooling and terrestrial ecosystem response. Nature. 2002;415:517–20.Article 
    CAS 

    Google Scholar 
    Gooseff MN, Barrett JE, Adams BJ, Doran PT, Fountain AG, Lyons WB, et al. Decadal ecosystem response to an anomalous melt season in a polar desert in Antarctica. Nat Ecol Evolut. 2017;1:1334–8.Article 

    Google Scholar 
    Obryk MK, Doran PT, Fountain AG, Myers M, McKay CP. Climate from the McMurdo dry valleys, Antarctica, 1986–2017: Surface air temperature trends and redefined summer season. J Geophys Res Atmosph. 2020;125:e2019JD032180.Article 

    Google Scholar 
    Nielsen UN, Wall DH, Adams BJ, Virginia RA, Ball BA, Gooseff MN, et al. The ecology of pulse events: insights from an extreme climatic event in a polar desert ecosystem. Ecosphere. 2012;3:1–15.Article 

    Google Scholar 
    Fountain AG, Saba G, Adams B, Doran P, Fraser W, Gooseff M, et al. The impact of a large-scale climate event on Antarctic ecosystem processes. Bioscience. 2016;66:848–63.Article 

    Google Scholar 
    Andriuzzi W, Adams B, Barrett J, Virginia R, Wall D. Observed trends of soil fauna in the Antarctic Dry Valleys: early signs of shifts predicted under climate change. Ecology. 2018;99:312–21.Article 
    CAS 

    Google Scholar 
    Adams BJ, Wall DH, Virginia RA, Broos E, Knox MA. Ecological biogeography of the terrestrial nematodes of Victoria Land, Antarctica. ZooKeys. 2014;419:29.Article 

    Google Scholar 
    Cary SC, McDonald IR, Barrett JE, Cowan DA. On the rocks: the microbiology of Antarctic Dry Valley soils. Nat Rev Microbiol. 2010;8:129–38.Article 
    CAS 

    Google Scholar 
    Jungblut AD, Hawes I, Mountfort D, Hitzfeld B, Dietrich DR, Burns BP, et al. Diversity within cyanobacterial mat communities in variable salinity meltwater ponds of McMurdo Ice Shelf, Antarctica. Environ Microbiol. 2005;7:519–29.Article 
    CAS 

    Google Scholar 
    Kohler TJ, Stanish LF, Crisp SW, Koch JC, Liptzin D, Baeseman JL, et al. Life in the main channel: long-term hydrologic control of microbial mat abundance in McMurdo Dry Valley streams, Antarctica. Ecosystems. 2015;18:310–27.Article 
    CAS 

    Google Scholar 
    Sommers P, Darcy JL, Porazinska DL, Gendron E, Fountain AG, Zamora F, et al. Comparison of microbial communities in the sediments and water columns of frozen cryoconite holes in the McMurdo Dry Valleys, Antarctica. Front Microbiol. 2019;10:65.Article 

    Google Scholar 
    Wharton RA Jr, Parker BC, Simmons GM Jr. Distribution, species composition and morphology of algal mats in Antarctic dry valley lakes. Phycologia. 1983;22:355–65.Article 

    Google Scholar 
    Esposito R, Spaulding S, McKnight DM, Van de Vijver B, Kopalová K, Lubinski D, et al. Inland diatoms from the McMurdo dry valleys and James Ross Island, Antarctica. Botany. 2008;86:1378–92.Article 

    Google Scholar 
    Van Horn DJ, Wolf CR, Colman DR, Jiang X, Kohler TJ, McKnight DM, et al. Patterns of bacterial biodiversity in the glacial meltwater streams of the McMurdo Dry Valleys, Antarctica. FEMS Microbiol Ecol. 2016;92:fiw148.Article 

    Google Scholar 
    Wlostowski AN, Gooseff MN, McKnight DM, Jaros C, Lyons WB. Patterns of hydrologic connectivity in the McMurdo Dry Valleys, Antarctica: a synthesis of 20 years of hydrologic data. Hydrol Proces. 2016;30:2958–75.Article 

    Google Scholar 
    McKnight DM, Tate C. Canada stream: a glacial meltwater stream in Taylor Valley, south Victoria Land, Antarctica. J N Am Benthol Soc. 1997;16:14–7.Article 

    Google Scholar 
    Davey MC, Clarke KJ. Fine structure of a terrestrial cyanobacterial mat from Antarctica 1. J Phycol. 1992;28:199–202.Article 

    Google Scholar 
    Vincent WF. Cyanobacterial dominance in the polar regions. The ecology of cyanobacteria: Springer, Dordrecht; 2000. p. 321–40.McKnight DM, Tate C, Andrews E, Niyogi D, Cozzetto K, Welch K, et al. Reactivation of a cryptobiotic stream ecosystem in the McMurdo Dry Valleys, Antarctica: a long-term geomorphological experiment. Geomorphology. 2007;89:186–204.Article 

    Google Scholar 
    Varin T, Lovejoy C, Jungblut AD, Vincent WF, Corbeil J. Metagenomic analysis of stress genes in microbial mat communities from Antarctica and the High Arctic. Appl Environ Microbiol. 2012;78:549–59.Article 

    Google Scholar 
    Alger A. Ecological processes in a cold desert ecosystem: the abundance and species distribution of algal mats in glacial meltwater streams in Taylor Valley, Antarctica. Occasional paper/University of Colorado; 1997.Marizcurrena JJ, Cerdá MF, Alem D, Castro-Sowinski S. Living with pigments: the colour palette of Antarctic life. The ecological role of micro-organisms in the antarctic environment. Springer, Cham; 2019. p. 65–82.Vincent W, Downes M, Castenholz R, Howard-Williams C. Community structure and pigment organisation of cyanobacteria-dominated microbial mats in Antarctica. Eur J Phycol. 1993;28:213–21.Article 

    Google Scholar 
    Howard‐Williams C, Vincent CL, Broady PA, Vincent WF. Antarctic stream ecosystems: variability in environmental properties and algal community structure. Int Revue Gesamten Hydrobiol Hydrogr. 1986;71:511–44.Article 

    Google Scholar 
    Esposito R, Horn S, McKnight DM, Cox M, Grant M, Spaulding S, et al. Antarctic climate cooling and response of diatoms in glacial meltwater streams. Geophys Res Lett. 2006;33:L07406.1–L07406.4.Stanish LF, Nemergut DR, McKnight DM. Hydrologic processes influence diatom community composition in Dry Valley streams. J N Am Benthol Soc. 2011;30:1057–73.Article 

    Google Scholar 
    Cullis JD, Stanish LF, McKnight DM. Diel flow pulses drive particulate organic matter transport from microbial mats in a glacial meltwater stream in the McMurdo Dry Valleys. Water Resour Res. 2014;50:86–97.Article 
    CAS 

    Google Scholar 
    Amaral-Zettler LA, McCliment EA, Ducklow HW, Huse SM. A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA genes. PloS ONE. 2009;4:e6372.Article 

    Google Scholar 
    Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.Article 
    CAS 

    Google Scholar 
    Stoeck T, Bass D, Nebel M, Christen R, Jones MD, Breiner HW, et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol. 2010;19:21–31.Article 
    CAS 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.Article 
    CAS 

    Google Scholar 
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.Article 
    CAS 

    Google Scholar 
    Bertrand EM, McCrow JP, Moustafa A, Zheng H, McQuaid JB, Delmont TO, et al. Phytoplankton–bacterial interactions mediate micronutrient colimitation at the coastal Antarctic sea ice edge. Proc Natl Acad Sci. 2015;112:9938–43.Article 
    CAS 

    Google Scholar 
    Dupont CL, McCrow JP, Valas R, Moustafa A, Walworth N, Goodenough U, et al. Genomes and gene expression across light and productivity gradients in eastern subtropical Pacific microbial communities. ISME J. 2015;9:1076–92.Article 
    CAS 

    Google Scholar 
    Schmieder R, Lim YW, Edwards R. Identification and removal of ribosomal RNA sequences from metatranscriptomes. Bioinformatics. 2012;28:433–5.Article 
    CAS 

    Google Scholar 
    Rho M, Tang H, Ye Y. FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res. 2010;38:e191.Article 

    Google Scholar 
    Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012;40:D109–14.Article 
    CAS 

    Google Scholar 
    Finn R, Mistry J, Tate J, Coggill P, Heger A. Pfam: the protein families database. Nucleic Acids Res. 2014;42:222–30.Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011;39:W29–37.Article 
    CAS 

    Google Scholar 
    Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.Article 
    CAS 

    Google Scholar 
    Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 2008;9:1–13.Article 

    Google Scholar 
    Kolody B, McCrow J, Allen LZ, Aylward F, Fontanez K, Moustafa A, et al. Diel transcriptional response of a California Current plankton microbiome to light, low iron, and enduring viral infection. ISME J. 2019;13:2817–33.Article 
    CAS 

    Google Scholar 
    Bolhuis H, Stal LJ. Analysis of bacterial and archaeal diversity in coastal microbial mats using massive parallel 16S rRNA gene tag sequencing. ISME J. 2011;5:1701–12.Article 
    CAS 

    Google Scholar 
    Sorokovikova EG, Belykh OI, Gladkikh AS, Kotsar OV, Tikhonova IV, Timoshkin OA, et al. Diversity of cyanobacterial species and phylotypes in biofilms from the littoral zone of Lake Baikal. J Microbiol. 2013;51:757–65.Article 
    CAS 

    Google Scholar 
    Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J. 2013;7:2061–8.Article 
    CAS 

    Google Scholar 
    Kohler TJ, Stanish LF, Liptzin D, Barrett JE, McKnight DM. Catch and release: Hyporheic retention and mineralization of N‐fixing Nostoc sustains downstream microbial mat biomass in two polar desert streams. Limnol Oceanogr Lett. 2018;3:357–64.Article 
    CAS 

    Google Scholar 
    Coyne KJ, Parker AE, Lee CK, Sohm JA, Kalmbach A, Gunderson T, et al. The distribution and relative ecological roles of autotrophic and heterotrophic diazotrophs in the McMurdo Dry Valleys, Antarctica. FEMS Microbiol Ecol. 2020;96:fiaa010.Article 
    CAS 

    Google Scholar 
    McKnight DM, Runkel RL, Tate CM, Duff JH, Moorhead DL. Inorganic N and P dynamics of Antarctic glacial meltwater streams as controlled by hyporheic exchange and benthic autotrophic communities. J N Am Benthol Soc. 2004;23:171–88.Article 

    Google Scholar 
    Howard-Williams C, Priscu JC, Vincent WF. Nitrogen dynamics in two Antarctic streams. Hydrobiologia. 1989;172:51–61.Article 
    CAS 

    Google Scholar 
    Hopkins D, Sparrow A, Elberling B, Gregorich E, Novis P, Greenfield L, et al. Carbon, nitrogen and temperature controls on microbial activity in soils from an Antarctic dry valley. Soil Biol Biochem. 2006;38:3130–40.Article 
    CAS 

    Google Scholar 
    Singley JG, Gooseff MN, McKnight DM, Hinckley E. The Role of Hyporheic Connectivity in Determining Nitrogen Availability: Insights from an Intermittent Antarctic Stream. J Geophys Res Biogeosci. 2021;126:e2021JG006309.Article 
    CAS 

    Google Scholar 
    Raymond-Bouchard I, Whyte LG. From transcriptomes to metatranscriptomes: cold adaptation and active metabolisms of psychrophiles from cold environments. Psychrophiles: from biodiversity to biotechnology. Springer, Cham; 2017. p. 437–57.Králová S. Role of fatty acids in cold adaptation of Antarctic psychrophilic Flavobacterium spp. Syst Appl Microbiol. 2017;40:329–33.Article 

    Google Scholar 
    Chua MJ, Campen RL, Wahl L, Grzymski JJ, Mikucki JA. Genomic and physiological characterization and description of Marinobacter gelidimuriae sp. nov., a psychrophilic, moderate halophile from Blood Falls, an Antarctic subglacial brine. FEMS Microbiol Ecol. 2018;94:fiy021.Article 

    Google Scholar 
    Gururani MA, Venkatesh J, Tran LSP. Regulation of photosynthesis during abiotic stress-induced photoinhibition. Mol Plant. 2015;8:1304–20.Article 
    CAS 

    Google Scholar 
    Murata N, Takahashi S, Nishiyama Y, Allakhverdiev SI. Photoinhibition of photosystem II under environmental stress. Biochim Biophys Acta Bioenerg. 2007;1767:414–21.Article 
    CAS 

    Google Scholar 
    Seifert GJ. Fascinating fasciclins: a surprisingly widespread family of proteins that mediate interactions between the cell exterior and the cell surface. Int J Mol Sci. 2018;19:1628.Article 

    Google Scholar 
    Meng J, Hu B, Yi G, Li X, Chen H, Wang Y, et al. Genome-wide analyses of banana fasciclin-like AGP genes and their differential expression under low-temperature stress in chilling sensitive and tolerant cultivars. Plant Cell Rep. 2020;39:693–708.Article 
    CAS 

    Google Scholar 
    Rai R, Singh S, Chatterjee A, Rai KK, Rai S, Rai L. All4894 encoding a novel fasciclin (FAS-1 domain) protein of Anabaena sp. PCC7120 revealed the presence of a thermostable β-glucosidase. Algal Res. 2020;51:102036.Article 

    Google Scholar 
    Knight C, DeVries A. Ice growth in supercooled solutions of a biological “antifreeze”, AFGP 1–5: An explanation in terms of adsorption rate for the concentration dependence of the freezing point. Phys Chem Chem Phys. 2009;11:5749–61.Article 
    CAS 

    Google Scholar 
    Kubota N. Effects of cooling rate, annealing time and biological antifreeze concentration on thermal hysteresis reading. Cryobiology. 2011;63:198–209.Article 
    CAS 

    Google Scholar 
    Takamichi M, Nishimiya Y, Miura A, Tsuda S. Effect of annealing time of an ice crystal on the activity of type III antifreeze protein. FEBS J. 2007;274:6469–76.Article 
    CAS 

    Google Scholar 
    Vance TD, Bayer‐Giraldi M, Davies PL, Mangiagalli M. Ice‐binding proteins and the ‘domain of unknown function’3494 family. FEBS J. 2019;286:855–73.Article 
    CAS 

    Google Scholar 
    Bar Dolev M, Braslavsky I, Davies PL. Ice-binding proteins and their function. Ann Rev Biochem. 2016;85:515–42.Article 
    CAS 

    Google Scholar 
    Niederberger TD, Bottos EM, Sohm JA, Gunderson T, Parker A, Coyne KJ, et al. Rapid microbial dynamics in response to an induced wetting event in Antarctic Dry Valley soils. Front Microbiol. 2019;10:621.Article 

    Google Scholar 
    Lee KC, Caruso T, Archer SD, Gillman LN, Lau MC, Cary SC, et al. Stochastic and deterministic effects of a moisture gradient on soil microbial communities in the McMurdo Dry Valleys of Antarctica. Front Microbiol. 2018;9:2619.Article 

    Google Scholar 
    De Scally S, Makhalanyane TP, Frossard A, Hogg I, Cowan DA. Antarctic microbial communities are functionally redundant, adapted and resistant to short term temperature perturbations. Soil Biol Biochem. 2016;103:160–70.Article 

    Google Scholar 
    Zeglin LH, Dahm CN, Barrett JE, Gooseff MN, Fitpatrick SK, Takacs-Vesbach CD. Bacterial community structure along moisture gradients in the parafluvial sediments of two ephemeral desert streams. Microbial Ecol. 2011;61:543–56.Article 

    Google Scholar 
    Ramoneda J, Hawes I, Pascual-García AJ, Mackey TY, Sumner DD, Jungblut A. Importance of environmental factors over habitat connectivity in shaping bacterial communities in microbial mats and bacterioplankton in an Antarctic freshwater system. FEMS Microbiol Ecol. 2021;97:fiab044.Article 
    CAS 

    Google Scholar 
    Levy JS, Fountain AG, Obryk M, Telling J, Glennie C, Pettersson R, et al. Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere. Geomorphology. 2018;323:80–97.Article 

    Google Scholar 
    Fountain AG, Levy JS, Gooseff MN, Van Horn D. The McMurdo Dry Valleys: a landscape on the threshold of change. Geomorphology. 2014;225:25–35.Article 

    Google Scholar 
    Barrett J, Virginia R, Wall D, Doran P, Fountain A, Welch K, et al. Persistent effects of a discrete warming event on a polar desert ecosystem. Glob Change Biol. 2008;14:2249–61.Article 

    Google Scholar 
    Gooseff MN, McKnight DM, Doran P, Fountain AG, Lyons WB. Hydrological connectivity of the landscape of the McMurdo Dry Valleys, Antarctica. Geogr Compass. 2011;5:666–81.Article 

    Google Scholar 
    Vick-Majors TJ, Priscu JC, Amaral-Zettler LA. Modular community structure suggests metabolic plasticity during the transition to polar night in ice-covered Antarctic lakes. ISME J. 2014;8:778–89.Article 
    CAS 

    Google Scholar 
    Bielewicz S, Bell E, Kong W, Friedberg I, Priscu JC, Morgan-Kiss RM. Protist diversity in a permanently ice-covered Antarctic lake during the polar night transition. ISME J. 2011;5:1559–64.Article 

    Google Scholar 
    Vick TJ, Priscu JC. Bacterioplankton productivity in lakes of the Taylor Valley, Antarctica, during the polar night transition. Aquat Microbial Ecol. 2012;68:77–90.Article 

    Google Scholar 
    Morgan‐Kiss R, Lizotte M, Kong W, Priscu J. Photoadaptation to the polar night by phytoplankton in a permanently ice‐covered Antarctic lake. Limnolo Oceanogr. 2016;61:3–13.Article 

    Google Scholar 
    Chan Y, Van Nostrand JD, Zhou J, Pointing SB, Farrell RL. Functional ecology of an Antarctic dry valley. Proc Natl Acad Sci. 2013;110:8990–5.Article 
    CAS 

    Google Scholar  More

  • in

    Memory pays off

    Burt, W. H. J. Mamm. 24, 346–352 (1943).Article 

    Google Scholar 
    Heathcote, R. J. P. et al. Nature Ecol. Evol. https://doi.org/10.1038/s41559-022-01950-5 (2023).Article 

    Google Scholar 
    Moorcroft, P. R., Lewis, M. A. & Crabtree, R. L. Proc. R. Soc. Lond. B 273, 1651–1659 (2006).
    Google Scholar 
    Moorcroft, P. R. & Barnett, A. Ecology 89, 1112–1119 (2008).Article 

    Google Scholar 
    Hattori, A. & Takuro, S. J. Mar. Biol. Assoc. U.K. 93, 2265–2272 (2013).Article 

    Google Scholar 
    Van Moorter, B. et al. Oikos 118, 641–652 (2009).Article 

    Google Scholar 
    Merkle, J. A., Potts, J. R. & Fortin, D. Oikos 126, https://doi.org/10.1111/oik.03356 (2017).Bracis, C., Gurarie, E., Van Moorter, B. & Goodwin, R. A. PLoS ONE 10, e0136057 (2015).Article 

    Google Scholar 
    Ranc, N., Cagnacci, F. & Moorcroft, P. R. Ecol. Lett. 25, 716–728 (2022).Article 

    Google Scholar 
    Schlägel, U. E. & Lewis, M. A. Methods Ecol. Evol. 5, 1236–1246 (2014).Article 

    Google Scholar 
    Ranc, N., Moorcroft, P. R., Ossi, F. & Cagnacci, F. Proc. Natl Acad. Sci. USA 118, e2014856118 (2021).Article 
    CAS 

    Google Scholar 
    Ranc, N. et al. Sci. Rep. 10, 11946 (2020).Merkle, J. A., Fortin, D. & Morales, J. M. Ecol. Lett. 17, 924–931 (2014).Article 
    CAS 

    Google Scholar 
    Gaynor, K. M., Brown, J. S., Middleton, A. D., Power, M. E. & Brashares, J. S. Trends Ecol. Evol. 34, 355–368 (2019).Article 

    Google Scholar 
    Rigoudy, N. L. A. et al. Behav. Ecol. 33, 789–797 (2022).Article 

    Google Scholar 
    Forrester, T. D., Casady, D. S. & Wittmer, H. U. Behav. Ecol. Sociobiol. 69, 603–612 (2015).Article 

    Google Scholar 
    Jesmer, B. R. et al. Science 361, 1023–1025 (2018).Article 
    CAS 

    Google Scholar  More

  • in

    Increases in intraspecific body size variation are common among North American mammals and birds between 1880 and 2020

    Bradshaw, W. E. & Holzapfel, C. M. Evolutionary response to rapid climate change. Science 312, 1477–1478 (2006).Article 
    CAS 

    Google Scholar 
    Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nat. Clim. Change 1, 401–406 (2011).Article 

    Google Scholar 
    Audzijonyte, A. et al. Fish body sizes change with temperature but not all species shrink with warming. Nat. Ecol. Evol. 4, 809–814 (2020).Article 

    Google Scholar 
    Gardner, J. L., Heinsohn, R. & Joseph, L. Shifting latitudinal clines in avian body size correlate with global warming in Australian passerines. Proc. R. Soc. B 276, 3845–3852 (2009).Article 

    Google Scholar 
    Bergmann C. Über die Verhältnisse der Wärmeökonomie der Thiere zu ihrer Grösse (Göttinger Studien, 1847).Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L. & Heinsohn, R. Declining body size: a third universal response to warming? Trends Ecol. Evol. 26, 285–291 (2011).Article 

    Google Scholar 
    Darimont, C. T. et al. Human predators outpace other agents of trait change in the wild. Proc. Natl Acad. Sci. USA 106, 952–954 (2009).Article 
    CAS 

    Google Scholar 
    van Gils, J. A. et al. Body shrinkage due to Arctic warming reduces red knot fitness in tropical wintering range. Science 352, 819–821 (2016).Article 

    Google Scholar 
    Ryding, S., Klaassen, M., Tattersall, G. J., Gardner, J. L. & Symonds, M. R. E. Shape-shifting: changing animal morphologies as a response to climatic warming. Trends Ecol. Evol. 36, 1036–1048 (2021).Article 

    Google Scholar 
    Des Roches, S. et al. The ecological importance of intraspecific variation. Nat. Ecol. Evol. 2, 57–64 (2018).Article 

    Google Scholar 
    Enquist, B. J. et al. Scaling from traits to ecosystems: developing a general trait driver theory via integrating trait-based and metabolic scaling theories. Adv. Ecol. Res 52, 249–318 (2015).Article 

    Google Scholar 
    González-Suárez, M. & Revilla, E. Variability in life-history and ecological traits is a buffer against extinction in mammals. Ecol. Lett. 16, 242–251 (2013).Article 

    Google Scholar 
    Ducatez, S., Sol, D., Sayol, F. & Lefebvre, L. Behavioural plasticity is associated with reduced extinction risk in birds. Nat. Ecol. Evol. 4, 788–793 (2020).Article 

    Google Scholar 
    Brady, S. P. et al. Causes of maladaptation. Evol. Appl. 12, 1229–1242 (2019).Article 

    Google Scholar 
    Scheele, B. C., Foster, C. N., Banks, S. C. & Lindenmayer, D. B. Niche contractions in declining species: mechanisms and consequences. Trends Ecol. Evol. 32, 346–355 (2017).Article 

    Google Scholar 
    Campbell-Staton, S. C. et al. Ivory poaching and the rapid evolution of tusklessness in African elephants. Science 374, 483–487 (2021).Article 
    CAS 

    Google Scholar 
    Thompson M. J., Capilla-Lasheras P., Dominoni D. M., Réale D. & Charmantier A. Phenotypic variation in urban environments: mechanisms and implications. Trends Ecol. Evol. 37, 171–182 (2022).Starrfelt, J. & Kokko, H. Bet-hedging—a triple trade-off between means, variances and correlations. Biol. Rev. 87, 742–755 (2012).Article 

    Google Scholar 
    Heino, M., Díaz Pauli, B. & Dieckmann, U. Fisheries-induced evolution. Annu. Rev. Ecol. Evol. Syst. 46, 461–480 (2015).Article 

    Google Scholar 
    Kindsvater, H. K. & Palkovacs, E. P. Predicting eco-evolutionary impacts of fishing on body size and trophic role of Atlantic cod. Copeia 105, 475–482 (2017).Article 

    Google Scholar 
    Hantak, M. M., McLean, B. S., Li, D. & Guralnick, R. P. Mammalian body size is determined by interactions between climate, urbanization, and ecological traits. Commun. Biol. 4, 972 (2021).Article 

    Google Scholar 
    Freckleton, R. P., Harvey, P. H. & Pagel, M. Bergmann’s rule and body size in mammals. Am. Nat. 161, 821–825 (2003).Article 

    Google Scholar 
    Riddell, E. A., Odom, J. P., Damm, J. D. & Sears, M. W. Plasticity reveals hidden resistance to extinction under climate change in the global hotspot of salamander diversity. Sci. Adv. 4, eaar5471 (2018).Article 

    Google Scholar 
    Cooke, R. S. C., Eigenbrod, F. & Bates, A. E. Projected losses of global mammal and bird ecological strategies. Nat. Commun. 10, 2279 (2019).Article 

    Google Scholar 
    Yang, J. et al. Large underestimation of intraspecific trait variation and its improvements. Front. Plant Sci. 11, 53 (2020).Article 

    Google Scholar 
    Olsen, E. M. et al. Maturation trends indicative of rapid evolution preceded the collapse of northern cod. Nature 428, 932–935 (2004).Article 
    CAS 

    Google Scholar 
    Antonson, N. D., Rubenstein, D. R., Hauber, M. E. & Botero, C. A. Ecological uncertainty favours the diversification of host use in avian brood parasites. Nat. Commun. 11, 4185 (2020).Article 

    Google Scholar 
    Rode, K. D., Amstrup, S. C. & Regehr, E. V. Reduced body size and cub recruitment in polar bears associated with sea ice decline. Ecol. Appl. 20, 768–782 (2010).Article 

    Google Scholar 
    Edeline, E. et al. Harvest-induced disruptive selection increases variance in fitness-related traits. Proc. R. Soc. B 276, 4163–4171 (2009).Article 

    Google Scholar 
    Hays, G. C. et al. Changes in mean body size in an expanding population of a threatened species. Proc. R Soc. B https://doi.org/10.1098/rspb.2022.0696 (2022).Halfwerk, W. et al. Adaptive changes in sexual signalling in response to urbanization. Nat. Ecol. Evol. 3, 374–380 (2019).Article 

    Google Scholar 
    Fernández-Chacón, A. et al. Protected areas buffer against harvest selection and rebuild phenotypic complexity. Ecol. Appl. 30, e02108 (2020).Article 

    Google Scholar 
    Sánchez-Tójar, A., Moran, N. P., O’Dea, R. E., Reinhold, K. & Nakagawa, S. Illustrating the importance of meta-analysing variances alongside means in ecology and evolution. J. Evol. Biol. 33, 1216–1223 (2020).Article 

    Google Scholar 
    Reed, T. E., Waples, R. S., Schindler, D. E., Hard, J. J. & Kinnison, M. T. Phenotypic plasticity and population viability: the importance of environmental predictability. Proc. R. Soc. B 277, 3391–3400 (2010).Article 

    Google Scholar 
    Klump, B. C. et al. Innovation and geographic spread of a complex foraging culture in an urban parrot. Science 373, 456–460 (2021).Article 
    CAS 

    Google Scholar 
    Bosse, M. et al. Recent natural selection causes adaptive evolution of an avian polygenic trait. Science 358, 365–368 (2017).Article 
    CAS 

    Google Scholar 
    Singer, M. C. & Parmesan, C. Lethal trap created by adaptive evolutionary response to an exotic resource. Nature 557, 238–241 (2018).Article 
    CAS 

    Google Scholar 
    Usui, R., Sheeran, L. K., Asbury, A. M. & Blackson, M. Impacts of the COVID-19 pandemic on mammals at tourism destinations: a systematic review. Mamm. Rev. 51, 492–507 (2021).Article 

    Google Scholar 
    Meineke, E. K. & Daru, B. H. Bias assessments to expand research harnessing biological collections. Trends Ecol. Evol. 36, 1071–1082 (2021).Article 

    Google Scholar 
    The IUCN Red List of Threatened Species. Version 2021-2 (IUCN, accessed November 2021); https://www.iucnredlist.orgBoyd, R. J. et al. ROBITT: a tool for assessing the risk-of-bias in studies of temporal trends in ecology. Methods Ecol. Evol. 13, 1497–1507 (2022).Article 

    Google Scholar 
    Thornton, P. K., Ericksen, P. J., Herrero, M. & Challinor, A. J. Climate variability and vulnerability to climate change: a review. Glob. Change Biol. 20, 3313–3328 (2014).Article 

    Google Scholar 
    Botero, C. A., Weissing, F. J., Wright, J. & Rubenstein, D. R. Evolutionary tipping points in the capacity to adapt to environmental change. Proc. Natl Acad. Sci. USA 112, 184–189 (2015).Article 
    CAS 

    Google Scholar 
    Niklas, K. J. The scaling of plant and animal body mass, length, and diameter. Evolution 48, 44–54 (1994).Article 
    CAS 

    Google Scholar 
    Van Valen, L. Morphological variation and width of ecological niche. Am. Nat. 99, 377–390 (1965).Article 

    Google Scholar 
    Gaillard, J. M. et al. Generation time: a reliable metric to measure life-history variation among mammalian populations. Am. Nat. 166, 119–123 (2005).Article 

    Google Scholar 
    Postma, E. in Quantitative Genetics in the Wild (eds Charmantier, A. et al.) 16–33 (Oxford Univ. Press, 2014).Jones, K. E. et al. PanTHERIA: a species‐level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648 (2009).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).Bates D., Mächler M., Bolker B. & Walker S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Ives, A. R., Dinnage, R., Nell, L. A., Helmus, M. & Li, D. phyr: Model based phylogenetic analysis. R package version 1.1.0 https://CRAN.R-project.org/package=phyr (2020).Upham, N. S., Esselstyn, J. A. & Jetz, W. Inferring the mammal tree: species-level sets of phylogenies for questions in ecology, evolution, and conservation. PLoS Biol. 17, e3000494 (2019).Article 
    CAS 

    Google Scholar 
    Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).Article 
    CAS 

    Google Scholar 
    Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 4, vey016 (2018).Article 

    Google Scholar 
    Hurlbert, S. H. & Lombardi, C. M. Final collapse of the Neyman–Pearson decision theoretic framework and rise of the neoFisherian. Ann. Zool. Fenn. 46, 311–349 (2009).Article 

    Google Scholar  More