Philippa Kaur

Surface-attached bacteria move towards antibiotics via twitching motilityWe used microfluidic devices and automated cell tracking to quantify the movement of P. aeruginosa cells as they are exposed to well-defined spatial gradients of antibiotics in developing biofilms (Fig. 1). We began with the antibiotic ciprofloxacin, which is widely used to treat P. aeruginosa infections27,28. To set a baseline, we first determined the minimum inhibitory concentration (hereafter MIC) of ciprofloxacin for P. aeruginosa (strain PAO1) in shaking cultures, which agrees with the published MIC of this strain (Fig. S129). We then exposed surface-attached cells to an antibiotic gradient in a microfluidic device where the antibiotic concentration ranged from zero to 10 times the MIC (Fig. 1A, B, Methods). After approximately 5 h of unbiased movement, we were surprised to see that twitching cells began to bias their movement towards increasing concentrations of ciprofloxacin (Fig. 1B, D, Movie 1). The movement bias, β, defined as the number of cells moving up the gradient divided by the number of cells moving down the gradient, peaks after approximately 10 h and then decays as the surface becomes crowded with cells (Movie 1) and tracking becomes difficult (Methods). The flow through the device also has a small influence on the direction of cell movement because it tends to pull cells in the downstream direction (Fig. 1B, C, E). However, this fluid flow is orthogonal to the direction of the antibiotic gradient, and so does not explain the movement towards antibiotics.Fig. 1: Twitching P. aeruginosa cells bias their motility towards increasing antibiotic concentrations.A A dual-inlet microfluidic device generates steady antibiotic gradients (e.g. ciprofloxacin, CMAX = 10X MIC) via molecular diffusion. Isocontours were calculated using mathematical modelling (Methods) and background shading shows approximate ciprofloxacin distribution visualised using fluorescein. B Red (blue) cell trajectories are moving towards (away from) increasing [ciprofloxacin]. Inset: A circular histogram of cell movement direction reveals movement bias towards increasing [ciprofloxacin]. A two-sided binomial test rejects the null hypothesis that trajectories are equally likely to be directed up or down the [ciprofloxacin] gradient (p  More

Franchini, M. & Mannucci, P. M. Air pollution and cardiovascular disease. Thromb. Res. 129, 230–234 (2012).Article 
CAS 

Google Scholar 
Langrish, J. P. et al. Reducing personal exposure to particulate air pollution improves cardiovascular health in patients with coronary heart disease. Environ. Health Perspect. 120, 367–372 (2012).Article 
CAS 

Google Scholar 
Tanwar, V., Katapadi, A., Adelstein, J. M., Grimmer, J. A. & Wold, L. E. Cardiac pathophysiology in response to environmental stress: A current review. Curr. Opin. Physiol. 1, 198–205 (2018).Article 

Google Scholar 
Franchini, M. & Mannucci, P. M. Particulate air pollution and cardiovascular risk: short-term and long-term effects. in Seminars in Thrombosis and Hemostasis. Vol. 35. 665–670 (© Thieme Medical Publishers, 2009).Shah, A. S. V. et al. Global association of air pollution and heart failure: A systematic review and meta-analysis. Lancet 382, 1039–1048 (2013).Article 
CAS 

Google Scholar 
Cesaroni, G. et al. Long term exposure to ambient air pollution and incidence of acute coronary events: Prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE Project. BMJ 348, f7412 (2014).Article 

Google Scholar 
Brook, R. D. et al. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation 121, 2331–2378 (2010).Article 
CAS 

Google Scholar 
Héroux, M.-E. et al. Quantifying the health impacts of ambient air pollutants: Recommendations of a WHO/Europe project. Int. J. Public Health 60, 619–627 (2015).Article 

Google Scholar 
An, Z., Jin, Y., Li, J., Li, W. & Wu, W. Impact of particulate air pollution on cardiovascular health. Curr. Allergy Asthma Rep. 18, 1–7 (2018).Article 
CAS 

Google Scholar 
Zanobetti, A., Baccarelli, A. & Schwartz, J. Gene-air pollution interaction and cardiovascular disease: A review. Prog. Cardiovasc. Dis. 53, 344–352 (2011).Article 
CAS 

Google Scholar 
Liang, R. et al. Effect of exposure to PM2.5 on blood pressure: A systematic review and meta-analysis. J. Hypertens. 32, 2130–2141 (2014).Article 
CAS 

Google Scholar 
Jerrett, M. et al. Traffic-related air pollution and obesity formation in children: A longitudinal, multilevel analysis. Environ. Heal. 13, 49 (2014).Article 

Google Scholar 
McConnell, R. et al. A longitudinal cohort study of body mass index and childhood exposure to secondhand tobacco smoke and air pollution: The Southern California Children’s Health Study. Environ. Health Perspect. 123, 360–366 (2015).Article 

Google Scholar 
Renzi, M. et al. Air pollution and occurrence of type 2 diabetes in a large cohort study. Environ. Int. 112, 68–76 (2018).Article 
CAS 

Google Scholar 
Jomova, K. et al. Arsenic: Toxicity, oxidative stress and human disease. J. Appl. Toxicol. 31, 95–107 (2011).CAS 

Google Scholar 
Al-Kindi, S. G., Brook, R. D., Biswal, S. & Rajagopalan, S. Environmental determinants of cardiovascular disease: Lessons learned from air pollution. Nat. Rev. Cardiol. 17, 656–672 (2020).Article 

Google Scholar 
Noroozian, M. The elderly population in iran: An ever growing concern in the health system. Iran. J. Psychiatry Behav. Sci. 6, 1 (2012).
Google Scholar 
Chokshi, D. A. & Farley, T. A. The cost-effectiveness of environmental approaches to disease prevention. N. Engl. J. Med. 367, 295–297 (2012).Article 
CAS 

Google Scholar 
Nieuwenhuijsen, M. J. Influence of urban and transport planning and the city environment on cardiovascular disease. Nat. Rev. Cardiol. 15, 432–438 (2018).Article 

Google Scholar 
Barnett, A. G. et al. The effects of air pollution on hospitalizations for cardiovascular disease in elderly people in Australian and New Zealand cities. Environ. Health Perspect. 114, 1018–1023 (2006).Article 
CAS 

Google Scholar 
Koken, P. J. M. et al. Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver. Environ. Health Perspect. 111, 1312–1317 (2003).Article 

Google Scholar 
Institute for Health Metrics and Evaluation. GBD 2019. (University of Washington, 2022).IHME. GBD 2019 Data and Tools Overview. (University of Washington, 2020).Dicker, D. et al. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 392, 1684–1735 (2018).Article 

Google Scholar 
Miller, D. C. & Salkind, N. J. Handbook of Research Design and Social Measurement (Sage, 2002).Book 

Google Scholar 
Rosenthal, F. S., Carney, J. P. & Olinger, M. L. Out-of-hospital cardiac arrest and airborne fine particulate matter: A case–crossover analysis of emergency medical services data in Indianapolis, Indiana. Environ. Health Perspect. 116, 631–636 (2008).Article 

Google Scholar 
Ensor, K. B., Raun, L. H. & Persse, D. A case-crossover analysis of out-of-hospital cardiac arrest and air pollution. Circulation 127, 1192–1199 (2013).Article 
CAS 

Google Scholar 
Forastiere, F. et al. A case-crossover analysis of out-of-hospital coronary deaths and air pollution in Rome, Italy. Am. J. Respir. Crit. Care Med. 172, 1549–1555 (2005).Article 

Google Scholar 
Levy, D. et al. A case-crossover analysis of particulate matter air pollution and out-of-hospital primary cardiac arrest. Epidemiology 12, 193–199 (2001).Article 
CAS 

Google Scholar 
Silverman, R. A. et al. Association of ambient fine particles with out-of-hospital cardiac arrests in New York City. Am. J. Epidemiol. 172, 917–923 (2010).Article 

Google Scholar 
Naghavi, M. et al. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 390, 1151–1210 (2017).Article 

Google Scholar 
Berend, N. Contribution of air pollution to COPD and small airway dysfunction. Respirology 21, 237–244 (2016).Article 

Google Scholar 
Vahedian, M., Khanjani, N., Mirzaee, M. & Koolivand, A. Associations of short-term exposure to air pollution with respiratory hospital admissions in Arak, Iran. J. Environ. Health Sci. Eng. 15, 17 (2017).Yaser, H. S., Narges, K., Yaser, S. & Rasoul, M. Air pollution and cardiovascular mortality in Kerman from 2006 to 2011. Am. J. Cardiovasc. Dis. Res. 2, 27–30 (2014).
Google Scholar 
Khaefi, M. et al. Association of particulate matter impact on prevalence of chronic obstructive pulmonary disease in Ahvaz, southwest Iran during 2009–2013. Aerosol Air Qual. Res. 17, 230–237 (2017).Article 
CAS 

Google Scholar 
Khaniabadi, Y. O. et al. Exposure to PM10, NO2, and O3 and impacts on human health. Environ. Sci. Pollut. Res. Int. 24, 2781–2789 (2017).Article 
CAS 

Google Scholar 
Momtazan, M. et al. An investigation of particulate matter and relevant cardiovascular risks in Abadan and Khorramshahr in 2014–2016. Toxin Rev. 38, 1–8 (2018).Martinelli, N., Olivieri, O. & Girelli, D. Air particulate matter and cardiovascular disease: A narrative review. Eur. J. Intern. Med. 24, 295–302 (2013).Article 
CAS 

Google Scholar 
Khaniabadi, Y. O. et al. Mortality and morbidity due to ambient air pollution in Iran. Clin. Epidemiol. Glob. Health 7, 222–227 (2019).Article 

Google Scholar 
Almeida-Silva, M. et al. Exposure and dose assessment to particle components among an elderly population. Atmos. Environ. 102, 156–166 (2015).Article 
ADS 
CAS 

Google Scholar 
Suh, H. H., Zanobetti, A., Schwartz, J. & Coull, B. A. Chemical properties of air pollutants and cause-specific hospital admissions among the elderly in Atlanta, Georgia. Environ. Health Perspect. 119, 1421–1428 (2011).Article 

Google Scholar 
Chien, L.-C., Yang, C.-H. & Yu, H.-L. Estimated effects of Asian dust storms on spatiotemporal distributions of clinic visits for respiratory diseases in Taipei children (Taiwan). Environ. Health Perspect. 120, 1215–1220 (2012).Article 

Google Scholar 
Khaniabadi, Y. O. et al. Chronic obstructive pulmonary diseases related to outdoor PM10, O3, SO2, and NO2 in a heavily polluted megacity of Iran. Environ. Sci. Pollut. Res. 25, 17726–17734 (2018).Article 
CAS 

Google Scholar 
Omidi Khaniabadi, Y. et al. Air quality modeling for health risk assessment of ambient PM10, PM2.5 and SO2 in Iran. Hum. Ecol. Risk Assess. Int. J. 25, 1298–1310 (2019).Newell, K., Kartsonaki, C., Lam, K. B. H. & Kurmi, O. P. Cardiorespiratory health effects of particulate ambient air pollution exposure in low-income and middle-income countries: A systematic review and meta-analysis. Lancet Planet. Health 1, e368–e380 (2017).Article 

Google Scholar 
Dominici, F. et al. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA 295, 1127–1134 (2006).Article 
CAS 

Google Scholar 
Qiu, H. et al. Inflammatory and oxidative stress responses of healthy elders to solar-assisted large-scale cleaning system (SALSCS) and changes in ambient air pollution: A quasi-interventional study in Xi’an, China. Sci. Total Environ. 806, 151217 (2022).Article 
ADS 
CAS 

Google Scholar 
Fiordelisi, A. et al. The mechanisms of air pollution and particulate matter in cardiovascular diseases. Heart Fail. Rev. 22, 337–347 (2017).Article 
CAS 

Google Scholar 
Yang, D., Yang, X., Deng, F. & Guo, X. Ambient air pollution and biomarkers of health effect. Ambient Air Pollut. Health Impact China 1017, 59–102 (2017).Lim, S. S. et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 2224–2260 (2012).Article 

Google Scholar 
Newby, D. E. et al. Expert position paper on air pollution and cardiovascular disease. Eur. Heart J. 36, 83–93 (2015).Article 
CAS 

Google Scholar 
Brook, R. D., Newby, D. E. & Rajagopalan, S. Air pollution and cardiometabolic disease: An update and call for clinical trials. Am. J. Hypertens. 31, 1–10 (2018).Article 
CAS 

Google Scholar 
Kang, S.-H. et al. Ambient air pollution and out-of-hospital cardiac arrest. Int. J. Cardiol. 203, 1086–1092 (2016).Article 

Google Scholar 
Thurston, G. D. et al. Ambient particulate matter air pollution exposure and mortality in the NIH-AARP diet and health cohort. Environ. Health Perspect. 124, 484–490 (2016).Article 

Google Scholar 
Gallagher, L. G. et al. Applying a moving total mortality count to the cities in the NMMAPS database to estimate the mortality effects of particulate matter air pollution. Circulation 172, 872–879 (2010).
Google Scholar 
Rodopoulou, S., Samoli, E., Chalbot, M.-C.G. & Kavouras, I. G. Air pollution and cardiovascular and respiratory emergency visits in Central Arkansas: A time-series analysis. Sci. Total Environ. 536, 872–879 (2015).Article 
ADS 
CAS 

Google Scholar 
Teng, T.-H.K. et al. A systematic review of air pollution and incidence of out-of-hospital cardiac arrest. J. Epidemiol. Commun. Health 68, 37–43 (2014).Article 

Google Scholar 
Brook, R. D. et al. Air pollution and cardiovascular disease: A statement for healthcare professionals from the expert panel on population and prevention science of the American Heart Association. Circulation 109, 2655–2671 (2004).Article 

Google Scholar 
Raza, A. et al. Short-term effects of air pollution on out-of-hospital cardiac arrest in Stockholm. Eur. Heart J. 35, 861–868 (2014).Article 
CAS 

Google Scholar 
Baccarelli, A. et al. Effects of exposure to air pollution on blood coagulation. J. Thromb. Haemost. 5, 252–260 (2007).Article 
CAS 

Google Scholar 
Franchini, M. & Mannucci, P. M. Thrombogenicity and cardiovascular effects of ambient air pollution. Blood 118, 2405–2412 (2011).Article 
CAS 

Google Scholar 
Yin, F. et al. Diesel exhaust induces systemic lipid peroxidation and development of dysfunctional pro-oxidant and pro-inflammatory high-density lipoprotein. Arterioscler. Thromb. Vasc. Biol. 33, 1153–1161 (2013).Article 
CAS 

Google Scholar 
Chirinos, J. A. et al. Elevation of endothelial microparticles, platelets, and leukocyte activation in patients with venous thromboembolism. J. Am. Coll. Cardiol. 45, 1467–1471 (2005).Article 
CAS 

Google Scholar 
Adar, S. D. et al. Fine particulate air pollution and the progression of carotid intima-medial thickness: A prospective cohort study from the multi-ethnic study of atherosclerosis and air pollution. PLoS Med. 10, e1001430 (2013).Article 

Google Scholar 
Kampfrath, T. et al. Chronic fine particulate matter exposure induces systemic vascular dysfunction via NADPH oxidase and TLR4 pathways. Circ. Res. 108, 716–726 (2011).Article 
CAS 

Google Scholar 
Sun, Q. et al. Long-term air pollution exposure and acceleration of atherosclerosis and vascular inflammation in an animal model. JAMA 294, 3003–3010 (2005).Article 
CAS 

Google Scholar 
Dennekamp, M. et al. Outdoor air pollution as a trigger for out-of-hospital cardiac arrests. Epidemiology 21, 494–500 (2010).Straney, L. et al. Evaluating the impact of air pollution on the incidence of out-of-hospital cardiac arrest in the Perth Metropolitan Region: 2000–2010. J. Epidemiol. Commun. Health 68, 6–12 (2014).Article 

Google Scholar 
Sullivan, J. et al. Exposure to ambient fine particulate matter and primary cardiac arrest among persons with and without clinically recognized heart disease. Am. J. Epidemiol. 157, 501–509 (2003).Article 
CAS 

Google Scholar 
Barton, T. J. et al. Traditional cardiovascular risk factors strongly underestimate the 5-year occurrence of cardiovascular morbidity and mortality in spinal cord injured individuals. Arch. Phys. Med. Rehabil. 102, 27–34 (2021).Article 

Google Scholar 
Burg, M. M. et al. Risk for incident hypertension associated with PTSD in military veterans, and the effect of PTSD treatment. Psychosom. Med. 79, 181 (2017).Article 

Google Scholar 
Hinojosa, R. Veterans’ likelihood of reporting cardiovascular disease. J. Am. Board Fam. Med. 32, 50–57 (2019).Article 

Google Scholar 
Rush, T., LeardMann, C. A. & Crum-Cianflone, N. F. Obesity and associated adverse health outcomes among US military members and veterans: Findings from the millennium cohort study. Obesity 24, 1582–1589 (2016).Article 

Google Scholar 
Stefanovics, E. A., Potenza, M. N. & Pietrzak, R. H. Smoking, obesity, and their co-occurrence in the US military veterans: Results from the national health and resilience in veterans study. J. Affect. Disord. 274, 354–362 (2020).Article 

Google Scholar 
Brook, R. D. et al. Insights into the mechanisms and mediators of the effects of air pollution exposure on blood pressure and vascular function in healthy humans. Hypertension 54, 659–667 (2009).Article 
CAS 

Google Scholar 
Rajagopalan, S. & Brook, R. D. Air pollution and type 2 diabetes: Mechanistic insights. Diabetes 61, 3037–3045 (2012).Article 
CAS 

Google Scholar 
Franklin, S. S. & Wong, N. D. Hypertension and cardiovascular disease: Contributions of the Framingham Heart Study. Glob. Heart 8, 49–57 (2013).Article 

Google Scholar 
Gu, D. et al. Blood pressure and risk of cardiovascular disease in Chinese men and women. Am. J. Hypertens. 21, 265–272 (2008).Article 

Google Scholar 
Wang, H. et al. Blood pressure, body mass index and risk of cardiovascular disease in Chinese men and women. BMC Public Health 10, 189 (2010).Article 

Google Scholar 
O’Brien, E. The Lancet Commission on hypertension: Addressing the global burden of raised blood pressure on current and future generations. J. Clin. Hypertens. 19, 564–568 (2017).Article 

Google Scholar 
Cai, Y. et al. Associations of short-term and long-term exposure to ambient air pollutants with hypertension: A systematic review and meta-analysis. Hypertension 68, 62–70 (2016).Article 
CAS 

Google Scholar 
Zhang, Z., Laden, F., Forman, J. P. & Hart, J. E. Long-term exposure to particulate matter and self-reported hypertension: A prospective analysis in the Nurses’ Health Study. Environ. Health Perspect. 124, 1414–1420 (2016).Article 

Google Scholar 
Cosselman, K. E., Navas-Acien, A. & Kaufman, J. D. Environmental factors in cardiovascular disease. Nat. Rev. Cardiol. 12, 627 (2015).Article 
CAS 

Google Scholar 
Baccarelli, A. et al. Effects of particulate air pollution on blood pressure in a highly exposed population in Beijing, China: A repeated-measure study. Environ. Heal. 10, 108 (2011).Article 

Google Scholar 
Mordukhovich, I. et al. Black carbon exposure, oxidative stress genes, and blood pressure in a repeated-measures study. Environ. Health Perspect. 117, 1767–1772 (2009).Article 
CAS 

Google Scholar 
Chen, H. et al. Spatial association between ambient fine particulate matter and incident hypertension. Circulation 129, 562–569 (2014).Article 
CAS 

Google Scholar 
Honjo, K. et al. The effects of smoking and smoking cessation on mortality from cardiovascular disease among Japanese: Pooled analysis of three large-scale cohort studies in Japan. Tob. Control 19, 50–57 (2010).Article 

Google Scholar 
Lawlor, D. A., Song, Y.-M., Sung, J., Ebrahim, S. & Smith, G. D. The association of smoking and cardiovascular disease in a population with low cholesterol levels: A study of 648 346 men from the Korean national health system prospective cohort study. Stroke 39, 760–767 (2008).Article 
CAS 

Google Scholar 
Wold, L. E. et al. Cardiovascular remodeling in response to long-term exposure to fine particulate matter air pollution. Circ. Hear. Fail. 5, 452–461 (2012).Article 
CAS 

Google Scholar 
Zoeller, R. T. et al. Endocrine-disrupting chemicals and public health protection: A statement of principles from The Endocrine Society. Endocrinology 153, 4097–4110 (2012).Article 
CAS 

Google Scholar 
Ruiz, D., Becerra, M., Jagai, J. S., Ard, K. & Sargis, R. M. Disparities in environmental exposures to endocrine-disrupting chemicals and diabetes risk in vulnerable populations. Diabetes Care 41, 193–205 (2018).Article 
CAS 

Google Scholar 
Taylor, D. Toxic Communities: Environmental Racism, Industrial Pollution, and Residential Mobility (NYU Press, 2014).
Google Scholar 
Newbold, R. R., Padilla-Banks, E. & Jefferson, W. N. Environmental estrogens and obesity. Mol. Cell. Endocrinol. 304, 84–89 (2009).Article 
CAS 

Google Scholar 
Szyszkowicz, M., Rowe, B. H. & Brook, R. D. Even low levels of ambient air pollutants are associated with increased emergency department visits for hypertension. Can. J. Cardiol. 28, 360–366 (2012).Article 
CAS 

Google Scholar 
van den Hooven, E. H. et al. Air pollution, blood pressure, and the risk of hypertensive complications during pregnancy: The generation R study. Hypertension 57, 406–412 (2011).Article 

Google Scholar 
Vali, M. et al. Effect of meteorological factors and Air Quality Index on the COVID-19 epidemiological characteristics: An ecological study among 210 countries. Environ. Sci. Pollut. Res. 38, 1–11 (2021).Kiani, B. et al. Association between heavy metals and colon cancer: An ecological study based on geographical information systems in North-Eastern Iran. BMC Cancer 21, 1–12 (2021).Article 

Google Scholar 
Cyranoski, D. China tests giant air cleaner to combat smog. Nature 555, 152–154 (2018).Article 
ADS 
CAS 

Google Scholar  More

Schneider-Crease, I. et al. Identifying wildlife reservoirs of neglected taeniid tapeworms: Non-invasive diagnosis of endemic Taenia serialis infection in a wild primate population. PLoS Negl Trop Dis 11, e0005709 (2017).Article 

Google Scholar 
Schneider-Crease, I. et al. Ecology eclipses phylogeny as a major driver of nematode parasite community structure in a graminivorous primate. Funct. Ecol. 34, 1898–1906 (2020).Article 

Google Scholar 
Gillespie, T. R. Noninvasive assessment of gastrointestinal parasite infections in free-ranging primates. Int. J. Primatol. 27, 1129 (2006).Article 

Google Scholar 
Budischak, S. A., Hoberg, E. P., Abrams, A., Jolles, A. E. & Ezenwa, V. O. A combined parasitological molecular approach for noninvasive characterization of parasitic nematode communities in wild hosts. Mol. Ecol. Resour. 15, 1112–1119 (2015).Article 

Google Scholar 
Ghalehnoei, H., Bagheri, A., Fakhar, M. & Mishan, M. A. Circulatory microRNAs: promising non-invasive prognostic and diagnostic biomarkers for parasitic infections. Eur. J. Clin. Microbiol. Infect. Dis. 39, 395–402 (2020).Article 
CAS 

Google Scholar 
Hing, S., Narayan, E. J., Andrew Thompson, R. C. & Godfrey, S. S. The relationship between physiological stress and wildlife disease: consequences for health and conservation. Wildl Res. 43, 51–60 (2016).Article 

Google Scholar 
Kersey, D. C. & Dehnhard, M. The use of noninvasive and minimally invasive methods in endocrinology for threatened mammalian species conservation. Gen. Comp. Endocrinol. 203, 296–306 (2014).Article 
CAS 

Google Scholar 
Behringer, V. & Deschner, T. Non-invasive monitoring of physiological markers in primates. Horm. Behav. 91, 3–18 (2017).Article 
CAS 

Google Scholar 
Higham, J. P., Stahl-Hennig, C. & Heistermann, M. Urinary suPAR: A non-invasive biomarker of infection and tissue inflammation for use in studies of large free-ranging mammals. R Soc Open Sci. 7, 191825 (2020).Article 
ADS 
CAS 

Google Scholar 
Heistermann, M. & Higham, J. P. Urinary neopterin, a non-invasive marker of mammalian cellular immune activation, is highly stable under field conditions. Sci Rep. 5, 16308 (2015).Article 
ADS 
CAS 

Google Scholar 
Higham, J. P. et al. Evaluating noninvasive markers of nonhuman primate immune activation and inflammation. Am. J. Phys. Anthropol. 158, 673–684 (2015).Article 

Google Scholar 
Behringer, V. et al. Elevated neopterin levels in wild, healthy chimpanzees indicate constant investment in unspecific immune system. BMC Zool. 4, 1–7 (2019).Article 

Google Scholar 
Dibakou, S. E., Basset, D., Souza, A., Charpentier, M. & Huchard, E. Determinants of variations in fecal neopterin in free-ranging mandrills. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2019.00368 (2019).Article 

Google Scholar 
Löhrich, T., Behringer, V., Wittig, R. M., Deschner, T. & Leendertz, F. H. The use of neopterin as a noninvasive marker in monitoring diseases in wild chimpanzees. EcoHealth 15, 792–803 (2018).Article 

Google Scholar 
Behringer, V., Stevens, J. M. G., Leendertz, F. H., Hohmann, G. & Deschner, T. Validation of a method for the assessment of urinary neopterin levels to monitor health status in nonhuman primate species. Front Physiol. 8, 51 (2017).Article 

Google Scholar 
Negrey, J. D., Behringer, V., Langergraber, K. E. & Deschner, T. Urinary neopterin of wild chimpanzees indicates that cell-mediated immune activity varies by age, sex, and female reproductive status. Sci. Rep. 11, 9298 (2021).Article 
ADS 
CAS 

Google Scholar 
Behringer, V. et al. Cell-mediated immune ontogeny is affected by sex but not environmental context in a long-lived primate species. Front. Ecol. Evol. 9, 272 (2021).Article 

Google Scholar 
Müller, N., Heistermann, M., Strube, C., Schülke, O. & Ostner, J. Age, but not anthelmintic treatment, is associated with urinary neopterin levels in semi-free ranging Barbary macaques. Sci. Rep. 7, 41973 (2017).Article 
ADS 

Google Scholar 
Dibakou, S. E. et al. Ecological, parasitological and individual determinants of plasma neopterin levels in a natural mandrill population. Int. J. Parasitol. Parasites Wildl. 11, 198–206 (2020).Article 

Google Scholar 
Eisenhut, M. Neopterin in diagnosis and monitoring of infectious diseases. J. Biomark. 2013, 196432 (2013).Article 

Google Scholar 
Franceschi, C. & Campisi, J. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases. J Gerontol. A Biol. Sci. Med Sci. 69(Suppl 1), S4–9 (2014).Article 

Google Scholar 
Basha, S., Surendran, N. & Pichichero, M. Immune responses in neonates. Expert. Rev. Clin. Immunol. 10, 1171–1184 (2014).Article 
CAS 

Google Scholar 
Werner, E. R. et al. Determination of neopterin in serum and urine. Clin. Chem. 33, 62–66 (1987).Article 
CAS 

Google Scholar 
Lucore, J. M., Marshall, A. J., Brosnan, S. F. & Benítez, M. E. Validating urinary neopterin as a biomarker of immune response in captive and wild capuchin monkeys. Front. Vet. Sci. 9, 918036. https://doi.org/10.3389/fvets.2022.918036 (2022).Article 

Google Scholar 
Berdowska, A. & Zwirska-Korczala, K. Neopterin measurement in clinical diagnosis. J. Clin. Pharm. Ther. 26, 319–329 (2001).Article 
CAS 

Google Scholar 
Denz, H. et al. Value of urinary neopterin in the differential diagnosis of bacterial and viral infections. Klin. Wochenschr. 68, 218–222 (1990).Article 
CAS 

Google Scholar 
Reibnegger, G. et al. Urinary neopterin reflects clinical activity in patients with rheumatoid arthritis. Arthritis Rheum. 29, 1063–1070 (1986).Article 
CAS 

Google Scholar 
Huber, C. et al. Immune response-associated production of neopterin. Release from macrophages primarily under control of interferon-gamma. J. Exp. Med. 160, 310–316 (1984).Article 
CAS 

Google Scholar 
Horak, E., Gassner, I., Sölder, B., Wachter, H. & Fuchs, D. Neopterin levels and pulmonary tuberculosis in infants. Lung 176, 337–344 (1998).Article 
CAS 

Google Scholar 
Fendrich, C. et al. Urinary neopterin concentrations in rhesus monkeys after infection with simian immunodeficiency virus (SIVmac 251). AIDS 3, 305–307 (1989).Article 
CAS 

Google Scholar 
Chan, C. P. Y. et al. Detection of serum neopterin for early assessment of dengue virus infection. J. Infect. 53, 152–158 (2006).Article 

Google Scholar 
Wu, D. F., Behringer, V., Wittig, R. M., Leendertz, F. H. & Deschner, T. Urinary neopterin levels increase and predict survival during a respiratory outbreak in wild chimpanzees (Taï National Park, Côte d’Ivoire). Sci. Rep. 8, 13346 (2018).Article 
ADS 

Google Scholar 
Maizels, R. M. & McSorley, H. J. Regulation of the host immune system by helminth parasites. J. Allergy Clin. Immunol. 138, 666–675 (2016).Article 
CAS 

Google Scholar 
Maizels, R. M. & Yazdanbakhsh, M. Immune regulation by helminth parasites: Cellular and molecular mechanisms. Nat. Rev. Immunol. 3, 733–744 (2003).Article 
CAS 

Google Scholar 
Yazdanbakhsh, M., Kremsner, P. G. & van Ree, R. Allergy, parasites, and the hygiene hypothesis. Science 296, 490–494 (2002).Article 
ADS 
CAS 

Google Scholar 
Faz-López, B., Morales-Montor, J. & Terrazas, L. I. Role of macrophages in the repair process during the tissue migrating and resident helminth infections. Biomed. Res. Int. 2016, 8634603 (2016).Article 

Google Scholar 
Garcia, H. H., Rodriguez, S., Friedland, J. S. Cysticercosis Working Group in Peru. Immunology of Taenia solium taeniasis and human cysticercosis. Parasite Immunol. 36, 388–396. https://doi.org/10.1111/pim.12126 (2014)Article 
CAS 

Google Scholar 
Thaiss, C. A., Zmora, N., Levy, M. & Elinav, E. The microbiome and innate immunity. Nature 535, 65–74 (2016).Article 
ADS 
CAS 

Google Scholar 
Schneider-Crease, I. A., Griffin, R. H., Gomery, M. A., Bergman, T. J. & Beehner, J. C. High mortality associated with tapeworm parasitism in geladas (Theropithecus gelada) in the Simien Mountains National Park, Ethiopia. Am. J. Primatol. https://doi.org/10.1002/ajp.22684 (2017).Article 

Google Scholar 
Nguyen, N. et al. Fitness impacts of tapeworm parasitism on wild gelada monkeys at Guassa, Ethiopia. Am. J. Primatol. 77, 579–594 (2015).Article 

Google Scholar 
Schneider-Crease, I. A. et al. Helminth infection is associated with dampened cytokine responses to viral and bacterial stimulations in Tsimane forager-horticulturalists. Evol. Med. Public Health 9, 349–359 (2021).Article 

Google Scholar 
Roberts, E. K., Lu, A., Bergman, T. J. & Beehner, J. C. Female reproductive parameters in wild geladas (Theropithecus gelada). Int. J. Primatol. 38, 1–20 (2017).Article 

Google Scholar 
Beehner, J. C. et al. Corrigendum to “Testosterone related to age and life-history stages in male baboons and geladas” [Horm. Behav. 56/4 (2009) 472-480]. Horm Behav. 80, 149 (2016).Article 

Google Scholar 
Erb, R. E., Tillson, S. A., Hodgen, G. D. & Plotka, E. D. Urinary creatinine as an index compound for estimating rate of excretion of steroids in the domestic sow. J. Anim. Sci. 30, 79–85 (1970).Article 
CAS 

Google Scholar 
Tinsley Johnson, E., Snyder-Mackler, N., Lu, A., Bergman, T. J. & Beehner, J. C. Social and ecological drivers of reproductive seasonality in geladas. Behav. Ecol. 29, 574–588 (2018).Article 

Google Scholar 
Kaushik, S. & Kaur, J. Effect of chronic cold stress on intestinal epithelial cell proliferation and inflammation in rats. Stress 8, 191–197 (2005).Article 
CAS 

Google Scholar 
Jarvey, J. C., Low, B. S., Pappano, D. J. & Bergman, T. J. Graminivory and fallback foods: annual diet profile of geladas (Theropithecus gelada) living in the Simien Mountains National Park, Ethiopia. Int. J. Primatol. https://doi.org/10.1007/s10764-018-0018-x (2018).Article 

Google Scholar 
Gowda, C., Hadley, C. & Aiello, A. E. The association between food insecurity and inflammation in the US adult population. Am. J. Public Health. 102, 1579–1586 (2012).Article 

Google Scholar 
Becker, D. J. et al. Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence. J. Anim. Ecol. 89, 972–995 (2020).Article 

Google Scholar 
Bates, D., Maechler, M., Bolker, B. & Walker, S. lme4: Linear mixed-effects models using Eigen and S4. R package version 1, 1–7 (2014).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2021. https://www.R-project.org/.Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest Package: Tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Article 

Google Scholar 
Simon, A. K., Hollander, G. A. & McMichael, A. Evolution of the immune system in humans from infancy to old age. Proc. Biol. Sci. 282, 20143085 (2015).
Google Scholar 
Heinonen, S. et al. Infant immune response to respiratory viral infections. Immunol. Allergy Clin. North Am. 39, 361–376 (2019).Article 

Google Scholar 
Teran, R. et al. Immune system development during early childhood in tropical Latin America: Evidence for the age-dependent down regulation of the innate immune response. Clin. Immunol. 138, 299–310 (2011).Article 
CAS 

Google Scholar 
van de Pol, M. & Verhulst, S. Age-dependent traits: a new statistical model to separate within- and between-individual effects. Am. Nat. 167, 766–773 (2006).Article 

Google Scholar 
Furman, D. et al. Chronic inflammation in the etiology of disease across the life span. Nat. Med. 25, 1822–1832 (2019).Article 
CAS 

Google Scholar 
Petrovsky, N., McNair, P. & Harrison, L. C. Diurnal rhythms of pro-inflammatory cytokines: regulation by plasma cortisol and therapeutic implications. Cytokine 10, 307–312 (1998).Article 
CAS 

Google Scholar 
Lasselin, J., Rehman, J.-U., Åkerstedt, T., Lekander, M. & Axelsson, J. Effect of long-term sleep restriction and subsequent recovery sleep on the diurnal rhythms of white blood cell subpopulations. Brain Behav. Immun. 47, 93–99 (2015).Article 

Google Scholar 
Auzéby, A., Bogdan, A., Krosi, Z. & Touitou, Y. Time-dependence of urinary neopterin, a marker of cellular immune activity. Clin Chem. 34, 1866–1867 (1988).Article 

Google Scholar 
Ansari, A. & Williams, J. F. The eosinophilic response of the rat to infection with Taenia taeniaeformis. J. Parasitol. 62, 728–736 (1976).Article 
CAS 

Google Scholar 
Schneider-Crease, I. A., Snyder-Mackler, N., Jarvey, J. C. & Bergman, T. J. Molecular identification of Taenia serialis coenurosis in a wild Ethiopian gelada (Theropithecus gelada). Vet. Parasitol. 198, 240–243 (2013).Article 
CAS 

Google Scholar 
Terrazas, L. I., Bojalil, R., Govezensky, T. & Larralde, C. Shift from an early protective Th1-type immune response to a late permissive Th2-type response in murine cysticercosis (Taenia crassiceps). J. Parasitol. 84, 74–81 (1998).Article 
CAS 

Google Scholar 
Toenjes, S. A., Spolski, R. J., Mooney, K. A. & Kuhn, R. E. The systemic immune response of BALB/c mice infected with larval Taenia crassiceps is a mixed Th1/Th2-type response. Parasitology 118(Pt 6), 623–633 (1999).Article 
CAS 

Google Scholar 
Gaze, S. et al. Characterising the mucosal and systemic immune responses to experimental human hookworm infection. PLoS Pathog. 8, e1002520 (2012).Article 
CAS 

Google Scholar 
Johnston, M. J. G., MacDonald, J. A. & McKay, D. M. Parasitic helminths: a pharmacopeia of anti-inflammatory molecules. Parasitology 136, 125–147 (2009).Article 
CAS 

Google Scholar 
Cortés, A., Muñoz-Antoli, C., Esteban, J. G. & Toledo, R. Th2 and Th1 responses: Clear and hidden sides of immunity against intestinal helminths. Trends Parasitol. 33, 678–693 (2017).Article 

Google Scholar 
White, M. P. J., McManus, C. M. & Maizels, R. M. Regulatory T-cells in helminth infection: induction, function and therapeutic potential. Immunology 160, 248–260 (2020).Article 
CAS 

Google Scholar 
Maizels, R. M. & Holland, M. J. Parasite immunity: Pathways for expelling intestinal helminths. Curr Biol. 8, R711–R714 (1998).Article 
CAS 

Google Scholar 
Zhang, D. & Frenette, P. S. Cross talk between neutrophils and the microbiota. Blood 133, 2168–2177 (2019).Article 
CAS 

Google Scholar 
Wang, J., Chen, W.-D. & Wang, Y.-D. The relationship between gut microbiota and inflammatory diseases: The role of macrophages. Front. Microbiol. 11, 1065 (2020).Article 

Google Scholar 
Pallikkuth, S. et al. Age associated microbiome and microbial metabolites modulation and its association with systemic inflammation in a rhesus macaque model. Front. Immunol. 12, 748397 (2021).Article 
CAS 

Google Scholar 
Pierce, Z. et al. The infant gut microbiome is associated with stool markers of macrophage and neutrophil activity. FASEB J. 30, 668–9 (2016).
Google Scholar 
Levast, B. et al. Impact on the gut microbiota of intensive and prolonged antimicrobial therapy in patients with bone and joint infection. Front. Med. https://doi.org/10.3389/fmed.2021.586875 (2021).Article 

Google Scholar 
Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).Article 
ADS 
CAS 

Google Scholar 
Round, J. L. & Mazmanian, S. K. The gut microbiota shapes intestinal immune responses during health and disease. Nat. Rev. Immunol. 9, 313–323 (2009).Article 
CAS 

Google Scholar 
Libertucci, J. & Young, V. B. The role of the microbiota in infectious diseases. Nat. Microbiol. 4, 35–45 (2019).Article 
CAS 

Google Scholar 
Huttenhower, C. et al. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).Article 
ADS 
CAS 

Google Scholar 
Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).Article 
ADS 
CAS 

Google Scholar 
Blaser, M. J. & Falkow, S. What are the consequences of the disappearing human microbiota?. Nat. Rev. Microbiol. 7, 887–894 (2009).Article 
CAS 

Google Scholar 
Brown, E. M., Kenny, D. J. & Xavier, R. J. Gut microbiota regulation of T cells during inflammation and autoimmunity. Annu. Rev. Immunol. 37, 599–624 (2019).Article 
CAS 

Google Scholar 
Gollwitzer, E. S. & Marsland, B. J. Impact of early-life exposures on immune maturation and susceptibility to disease. Trends Immunol. 36, 684–696 (2015).Article 
CAS 

Google Scholar 
Ravi, A. et al. Loss of microbial diversity and pathogen domination of the gut microbiota in critically ill patients. Microbial. Genomics https://doi.org/10.1099/mgen.0.000293 (2019).McLaren, M. R. & Callahan, B. J. Pathogen resistance may be the principal evolutionary advantage provided by the microbiome. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190592 (2020).Article 

Google Scholar 
Ragonnaud, E. & Biragyn, A. Gut microbiota as the key controllers of “healthy” aging of elderly people. Immun Ageing 18, 2 (2021).Article 

Google Scholar 
Wilmanski, T. et al. Gut microbiome pattern reflects healthy ageing and predicts survival in humans. Nat. Metab. 3, 274–286 (2021).Article 

Google Scholar 
Cattadori, I. M. et al. Impact of helminth infections and nutritional constraints on the small intestine microbiota. PLoS ONE 11, e0159770 (2016).Article 

Google Scholar 
Houlden, A. et al. Chronic Trichuris muris infection in C57BL/6 mice causes significant changes in host microbiota and metabolome: Effects reversed by pathogen clearance. PLoS ONE 10, e0125945 (2015).Article 

Google Scholar 
Holm, J. B. et al. Chronic Trichuris muris infection decreases diversity of the intestinal microbiota and concomitantly increases the abundance of Lactobacilli. PLoS ONE 10, e0125495 (2015).Article 

Google Scholar 
Peachey, L. E., Jenkins, T. P. & Cantacessi, C. This gut ain’t big enough for both of us. Or is it? Helminth–microbiota interactions in veterinary species. Trends Parasitol. 33, 619–632 (2017).Article 

Google Scholar  More

World Health Organization. World Health Statistics 2018. (WHO, 2018).Wynne, N. E., Lorenzo, M. G. & Vinauger, C. Mechanism and plasticity of vectors’ host-seeking behavior. Curr. Opin. Insect Sci. 40, 1–5 (2020).Article 

Google Scholar 
Carlile, P. A., Peters, R. A. & Evans, C. S. Detection of a looming stimulus by the Jacky dragon: Selective sensitivity to characteristics of an aerial predator. Anim. Behav. 72, 553–562 (2006).Article 

Google Scholar 
Ingle, D. J. Visually elicited evasive behavior in frogs. Bioscience 40, 284–291 (1990).Article 

Google Scholar 
Yilmaz, M. & Meister, M. Rapid innate defensive responses of mice to looming visual stimuli. Curr. Biol. 23, 2011–2015 (2013).Article 
CAS 

Google Scholar 
Temizer, I., Donovan, J. C., Baier, H. & Semmelhack, J. L. A visual pathway for looming-evoked escape in larval zebrafish. Curr. Biol. 25, 1823–1834 (2015).Article 
CAS 

Google Scholar 
Scarano, F., Tomsic, D. & Sztarker, J. Direction selective neurons responsive to horizontal motion in a crab reflect an adaptation to prevailing movements in flat environments. J. Neurosci. https://doi.org/10.1523/JNEUROSCI.0372-20.2020 (2020).Article 

Google Scholar 
Scarano, F. & Tomsic, D. Escape response of the crab Neohelice to computer generated looming and translational visual danger stimuli. J. Physiol. Paris 108, 141–147 (2014).Article 

Google Scholar 
Santer, R. D., Rind, F. C., Stafford, R. & Simmons, P. J. Role of an identified looming-sensitive neuron in triggering a flying locust’s escape. J. Neurophysiol. 95, 3391–3400 (2006).Article 

Google Scholar 
Simmons, P. J., Rind, F. C. & Santer, R. D. Escapes with and without preparation: The neuroethology of visual startle in locusts. J. Insect Physiol. 56, 876–883 (2010).Article 
CAS 

Google Scholar 
Dupuy, F., Casas, J., Body, M. & Lazzari, C. R. Danger detection and escape behaviour in wood crickets. J. Insect Physiol. 57, 865–871 (2011).Article 
CAS 

Google Scholar 
Muijres, F. T., Elzinga, M. J., Melis, J. M. & Dickinson, M. H. Flies evade looming targets by executing rapid visually directed banked turns. Science 344, 172–177 (2014).Article 
ADS 
CAS 

Google Scholar 
Ache, J. M. et al. Neural basis for looming size and velocity encoding in the Drosophila giant fiber escape pathway. Curr. Biol. 29, 1073-1081.e4 (2019).Article 
CAS 

Google Scholar 
Domenici, P., Booth, D., Blagburn, J. M. & Bacon, J. P. Cockroaches keep predators guessing by using preferred escape trajectories. Curr. Biol. 18, 1792–1796 (2008).Article 
CAS 

Google Scholar 
Smolka, J., Zeil, J. & Hemmi, J. M. Natural visual cues eliciting predator avoidance in fiddler crabs. Proc. Biol. Sci. 278, 3584–3592 (2011).
Google Scholar 
Card, G. & Dickinson, M. Performance trade-offs in the flight initiation of Drosophila. J. Exp. Biol. 211, 341–353 (2008).Article 

Google Scholar 
Sun, Y. A. & Wyman, R. J. Neurons of the Drosophila giant fiber system: I. Dorsal longitudinal motor neurons. J. Comp. Neurol. 387, 157–166 (1997).Article 
CAS 

Google Scholar 
von Reyn, C. R. et al. Feature integration drives probabilistic behavior in the Drosophila escape response. Neuron 94, 1190-1204.e6 (2017).Article 

Google Scholar 
Fotowat, H., Fayyazuddin, A., Bellen, H. J. & Gabbiani, F. A novel neuronal pathway for visually guided escape in Drosophila melanogaster. J. Neurophysiol. 102, 875–885 (2009).Article 

Google Scholar 
Card, G. & Dickinson, M. H. Visually mediated motor planning in the escape response of Drosophila. Curr. Biol. 18, 1300–1307 (2008).Article 
CAS 

Google Scholar 
Matherne, M. E., Cockerill, K., Zhou, Y., Bellamkonda, M. & Hu, D. L. Mammals repel mosquitoes with their tails. J. Exp. Biol. 221, 178905 (2018).Article 

Google Scholar 
Cribellier, A. et al. Diurnal and nocturnal mosquitoes escape looming threats using distinct flight strategies. Curr. Biol. 32, 1232-1246.e5 (2022).Article 
CAS 

Google Scholar 
Cribellier, A., Spitzen, J., Straw, A. D., van Leeuwen, J. L. & Muijres, F. T. Escape flight performances of night-active malaria mosquitoes: the role of visual and airflow cues of an approaching object. in Integrative and Comparative Biology. Vol. 61. E170–E171 (Oxford University Press Inc Journals Dept, 2021).Reid, J. A. Anopheline Mosquitoes of Malaya and Borneo. Studies from the Institute for Medical Research, Malaysia. (1968).Clements, A. N. The Biology of Mosquitoes. Volume 2: Sensory Reception and Behaviour (CABI Publishing, 1999).
Google Scholar 
Tuno, N., Tsuda, Y., Takagi, M. & Swonkerd, W. Pre- and postprandial mosquito resting behavior around cattle hosts. J. Am. Mosq. Control Assoc. 19, 211–219 (2003).
Google Scholar 
Day, J. F. & Edman, J. D. Mosquito engorgement on normally defensive hosts depends on host activity Patterns. J. Med. Entomol. 21, 732–740 (1984).Article 
CAS 

Google Scholar 
Edman, J. D., Webber, L. A. & Kale, H. W. Effect of mosquito density on the interrelationship of host behavior and mosquito feeding success. Am. J. Trop. Med. Hyg. 21, 487–491 (1972).Article 
CAS 

Google Scholar 
Christophers, S. R. Aedes aegypti: The Yellow Fever Mosquito. (1960).Ponlawat, A. & Harrington, L. C. Blood feeding patterns of Aedes aegypti and Aedes albopictus in Thailand. J. Med. Entomol. 42, 844–849 (2005).Article 

Google Scholar 
Walilko, T. J., Viano, D. C. & Bir, C. A. Biomechanics of the head for Olympic boxer punches to the face. Br. J. Sports Med. 39, 710–719 (2005).Article 
CAS 

Google Scholar 
Reiser, M. B. & Dickinson, M. H. A modular display system for insect behavioral neuroscience. J. Neurosci. Methods 167, 127–139 (2008).Article 

Google Scholar 
Cribellier, A. Biomechanics of Flying Mosquitoes During Capture and Escape. Doctoral Dissertation. (Wageningen University, 2021).Hu, X., Leming, M. T., Whaley, M. A. & O’Tousa, J. E. Rhodopsin coexpression in UV photoreceptors of Aedes aegypti and Anopheles gambiae mosquitoes. J. Exp. Biol. 217, 1003–1008 (2014).
Google Scholar 
Tammero, L. F., Frye, M. A. & Dickinson, M. H. Spatial organization of visuomotor reflexes in Drosophila. J. Exp. Biol. 207, 113–122 (2004).Article 

Google Scholar 
Tammero, L. F. & Dickinson, M. H. Collision-avoidance and landing responses are mediated by separate pathways in the fruit fly, Drosophila melanogaster. J. Exp. Biol. 205, 2785–2798 (2002).Article 

Google Scholar 
Muijres, F. T. et al. Escaping blood-fed malaria mosquitoes minimize tactile detection without compromising on take-off speed. J. Exp. Biol. 220, 3751–3762 (2017).Article 
CAS 

Google Scholar 
van Veen, W. G., van Leeuwen, J. L. & Muijres, F. T. Malaria mosquitoes use leg push-off forces to control body pitch during take-off. J. Exp. Zool. A Ecol. Integr. Physiol. 333, 38–49 (2020).Article 

Google Scholar 
Caro, T. et al. Benefits of zebra stripes: Behaviour of tabanid flies around zebras and horses. PLoS ONE 14, e0210831 (2019).Article 
CAS 

Google Scholar 
Edman, J. D., Webber, L. A. & Schmid, A. A. Effect of host defenses on the feeding pattern of Culex nigripalpus when offered a choice of blood sources. J. Parasitol. 60, 874–883 (1974).Article 
CAS 

Google Scholar 
Walker, E. D. & Edman, J. D. The influence of host defensive behavior on mosquito (Diptera: Culicidae) biting persistence1. J. Med. Entomol. 22, 370–372 (1985).Article 
CAS 

Google Scholar 
Warnes, M. L. & Finlayson, L. H. Effect of host behaviour on host preference in Stomoxys calcitrans. Med. Vet. Entomol. 1, 53–57 (1987).Article 
CAS 

Google Scholar 
Vinauger, C. et al. Modulation of host learning in Aedes aegypti mosquitoes. Curr. Biol. 28, 333-344.e8 (2018).Article 
CAS 

Google Scholar 
Wolff, G. H. & Riffell, J. A. Olfaction, experience and neural mechanisms underlying mosquito host preference. J. Exp. Biol. 221, 157131 (2018).Article 

Google Scholar 
Alonso San Alberto, D. et al. The olfactory gating of visual preferences to human skin and visible spectra in mosquitoes. Nat. Commun. 13, 1–14 (2022).Article 

Google Scholar 
van Breugel, F., Riffell, J., Fairhall, A. & Dickinson, M. H. Mosquitoes use vision to associate odor plumes with thermal targets. Curr. Biol. 25, 2123–2129 (2015).Article 

Google Scholar 
Vinauger, C. et al. Visual-olfactory integration in the human disease vector mosquito, Aedes aegypti. Curr. Biol. 29, 2509-2516.e5 (2019).Article 
CAS 

Google Scholar 
Grant, A. J. & O’Connell, R. J. Age-related changes in female mosquito carbon dioxide detection. J. Med. Entomol. 44, 617–623 (2007).Article 
CAS 

Google Scholar 
Tallon, A. K., Hill, S. R. & Ignell, R. Sex and age modulate antennal chemosensory-related genes linked to the onset of host seeking in the yellow-fever mosquito, Aedes aegypti. Sci. Rep. 9, 43 (2019).Article 
ADS 

Google Scholar 
Eilerts, D. F., VanderGiessen, M., Bose, E. A., Broxton, K. & Vinauger, C. Odor-specific daily rhythms in the olfactory sensitivity and behavior of Aedes aegypti mosquitoes. Insects 9, 147 (2018).Article 

Google Scholar 
Taylor, B. & Jones, M. D. The circadian rhythm of flight activity in the mosquito Aedes aegypti (L). The phase-setting effects of light-on and light-off. J. Exp. Biol. 51, 59–70 (1969).Article 
CAS 

Google Scholar 
Peirce, J. et al. PsychoPy2: Experiments in behavior made easy. Behav. Res. Methods 51, 195–203 (2019).Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. arXiv [stat.CO] (2014).Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363 (2008).Article 
MathSciNet 
MATH 

Google Scholar 
Lund, U., & Agostinelli, C. Package “Circular”. Repository CRAN (2017).Bunn, A. G. A dendrochronology program library in R (dplR). Dendrochronologia 26, 115–124 (2008).Article 

Google Scholar 
Walker, J. A. Estimating velocities and accelerations of animal locomotion: A simulation experiment comparing numerical differentiation algorithms. J. Exp. Biol. 201, 981–995 (1998).Article 

Google Scholar 
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2009).Book 
MATH 

Google Scholar  More

Tölgyesi, C., Buisson, E., Helm, A., Temperton, V. M. & Török, P. Urgent need for updating a slogan of global climate actions from ‘tree planting’ to ‘restore native vegetation’. Restor. Ecol. 30, e13594. https://doi.org/10.1111/rec.13594 (2021).Article 

Google Scholar 
Dengler, J., Janišová, M., Török, P. & Wellstein, C. Biodiversity of Palaearctic grasslands: A synthesis. Agric. Ecosyst. Environ. 182, 1–14 (2014).Article 

Google Scholar 
Dass, P., Houlton, B. Z., Wang, Y. & Warlind, D. Grasslands may be more reliable carbon sinks than forests in California. Environ. Res. Lett. 13, 074027. https://doi.org/10.1088/1748-9326/aacb39 (2018).Article 
ADS 

Google Scholar 
Terrer, C. et al. A trade-off between plant and soil carbon storage under elevated CO2. Nature 591, 599–603 (2021).Article 
ADS 
CAS 

Google Scholar 
Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).Article 
ADS 
CAS 

Google Scholar 
Stevens, C. J. Recent advances in understanding grasslands. F1000 Res. https://doi.org/10.12688/f1000research.15050.1 (2018).Article 

Google Scholar 
Klaus, V. H. et al. Do biodiversity-ecosystem functioning experiments inform stakeholders how to simultaneously conserve biodiversity and increase ecosystem service provisioning in grasslands?. Biol. Conserv. 245, 108552. https://doi.org/10.1016/j.biocon.2020.108552 (2020).Article 

Google Scholar 
Dudley, N. et al. Grasslands and savannahs in the UN decade on ecosystem restoration. Restor. Ecol. 28, 1313–1317 (2020).Article 

Google Scholar 
Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth Environ. 2, 720–735 (2021).Article 
ADS 

Google Scholar 
Lengyel, S. et al. Restoration for variability: Emergence of the habitat diversity paradigm in terrestrial ecosystem restoration. Restor. Ecol. 28, 1087–1099 (2020).Article 

Google Scholar 
Waldén, E. & Lindborg, R. Long term positive effect of grassland restoration on plant diversity: Success or not?. PLoS ONE 11, e0155836. https://doi.org/10.1371/journal.pone.0155836 (2016).Article 
CAS 

Google Scholar 
Lengyel, S. et al. Grassland restoration to conserve landscape-level biodiversity: A synthesis of early results from a large-scale project. Appl. Veg. Sci. 15, 264–276 (2012).Article 

Google Scholar 
Sojneková, M. & Chytrý, M. From arable land to species-rich semi-natural grasslands: Succession in abandoned fields in a dry region of central Europe. Ecol. Eng. 77, 373–381 (2015).Article 

Google Scholar 
Ellis, E. C. et al. Used planet: A global history. Proc. Natl. Acad. Sci. USA 110, 7978–7985 (2013).Article 
ADS 
CAS 

Google Scholar 
Levers, C., Schneider, M., Prishchepov, A. V., Estel, S. & Kuemmerle, T. Spatial variation in determinants of agricultural land abandonment in Europe. Sci. Total Environ. 644, 95–111 (2018).Article 
ADS 
CAS 

Google Scholar 
Winkler, K., Fuchs, R., Rounsevell, M. & Herold, M. Global land use changes are four times greater than previously estimated. Nat. Commun. 12, 2501. https://doi.org/10.1038/s41467-021-22702-2 (2021).Article 
ADS 
CAS 

Google Scholar 
Perpiña Castillo, C. et al. Agricultural Land Abandonment in the EU within 2015–2030 (No: JRC113718) (Joint Research Centre (Seville site), 2018).Müller, D., Leitão, P. J. & Sikor, T. Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees. Agric. Syst. 117, 66–77 (2013).Article 

Google Scholar 
Prishchepov, A. V., Müller, D., Dubinin, M., Baumann, M. & Radeloff, V. C. Determinants of agricultural land abandonment in post-Soviet European Russia. Land Use Policy 30, 873–884 (2013).Article 

Google Scholar 
Prishchepov, A. V., Schierhorn, F. & Löw, F. Unraveling the diversity of trajectories and drivers of global agricultural land abandonment. Land 10, 97 (2021).Article 

Google Scholar 
Bossuyt, B. & Honnay, O. Can the seed bank be used for ecological restoration? An overview of seed bank characteristics in European communities. J. Veg. Sci. 19, 875–884 (2008).Article 

Google Scholar 
Humphries, T., Florentine, S., Dowling, K., Turville, C. & Sinclair, S. Weed management for landscape scale restoration of global temperate grasslands. Land Degrad. Dev. 32, 1090–1102 (2021).Article 

Google Scholar 
Valkó, O. et al. Dynamics in vegetation and seed bank composition highlight the importance of post-restoration management in sown grasslands. Restor. Ecol. 29, e13192. https://doi.org/10.1111/rec.13192 (2021).Article 

Google Scholar 
Valkó, O. et al. High-diversity sowing in establishment gaps: A promising new tool for enhancing grassland biodiversity. Tuexenia 36, 359–378 (2016).
Google Scholar 
Kövendi-Jakó, A. et al. Three years of vegetation development worth 30 years of secondary succession in urban-industrial grassland restoration. Appl. Veg. Sci. 22, 138–149 (2019).Article 

Google Scholar 
Kiss, R. et al. Establishment gaps in species-poor grasslands: Artificial biodiversity hotspots to support the colonization of target species. Restor. Ecol. 29, e13135. https://doi.org/10.1111/rec.13135 (2021).Article 

Google Scholar 
Török, P., Vida, E., Deák, B., Lengyel, S. & Tóthmérész, B. Grassland restoration on former croplands in Europe: An assessment of applicability of techniques and costs. Biodivers. Conserv. 20, 2311–2332 (2011).Article 

Google Scholar 
Critchley, C. N. R., Fowbert, J. A., Sherwood, A. J. & Pywell, R. F. Vegetation development of sown grass margins in arable fields under a countrywide agri-environment scheme. Biol. Conserv. 132, 1–11 (2006).Article 

Google Scholar 
Wagner, M., Walker, K. J. & Pywell, R. F. Seed bank dynamics in restored grassland following the sowing of high-and low-diversity seed mixtures. Restor. Ecol. 26, S189–S199 (2018).Article 

Google Scholar 
Lepš, J. et al. Long-term effectiveness of sowing high and low diversity seed mixtures to enhance plant community development on ex-arable fields. Appl. Veg. Sci. 10, 97–110 (2007).
Google Scholar 
Török, P. et al. Restoring grassland biodiversity: Sowing low diversity seed mixtures can lead to rapid favourable changes. Biol. Conserv. 148, 806–812 (2010).Article 

Google Scholar 
Schaub, S. et al. The costs of diversity: Higher prices for more diverse grassland seed mixtures. Environ. Res. Lett. 16, 094011. https://doi.org/10.1088/1748-9326/ac1a9c (2021).Article 
ADS 
CAS 

Google Scholar 
Werner, C. M., Vaughn, K. J., Stuble, K. L., Wolf, K. & Young, T. P. Persistent asymmetrical priority effects in a California grassland restoration experiment. Ecol. Appl. 26, 1624–1632 (2016).Article 

Google Scholar 
Williams, D. W., Jackson, L. L. & Smith, D. D. Effects of frequent mowing on survival and persistence of forbs seeded into a species-poor grassland. Restor. Ecol. 15, 24–33 (2007).Article 

Google Scholar 
Klaus, V. H. et al. Enriching plant diversity in grasslands by large-scale experimental sward disturbance and seed addition along gradients of land-use intensity. J. Plant Ecol. 10, 581–591 (2017).
Google Scholar 
Kiss, R. et al. Zoochory on and off: A field experiment for trait-based analysis of establishment success of grassland species. J. Veg. Sci. 32, e13051. https://doi.org/10.1111/jvs.13051 (2021).Article 

Google Scholar 
Weidlich, E. W. A. et al. Priority effects and ecological restoration. Restor. Ecol. 29, e13317. https://doi.org/10.1111/rec.13317 (2021).Article 

Google Scholar 
Wilsey, B. Restoration in the face of changing climate: Importance of persistence, priority effects, and species diversity. Restor. Ecol. 29, e13132. https://doi.org/10.1111/rec.13132 (2021).Article 

Google Scholar 
von Gillhaussen, P. et al. Priority effects of time of arrival of plant functional groups override sowing interval or density effects: A grassland experiment. PLoS ONE 9, e86906. https://doi.org/10.1371/journal.pone.0086906 (2014).Article 
ADS 
CAS 

Google Scholar 
Eddy, K. C. & Van Auken, O. W. Priority effects allow Coreopsis tinctoria to avoid interspecific competition with a C4 grass. Am. Midl. Nat. 181, 104–114 (2019).Article 

Google Scholar 
Delory, B. M., Weidlich, E. W., von Gillhaussen, P. & Temperton, V. M. When history matters: The overlooked role of priority effects in grassland overyielding. Funct. Ecol. 33, 2369–2380 (2019).Article 

Google Scholar 
Fenner, M. The effects of the parent environment on seed germinability. Seed Sci. Res. 1, 75–84 (1991).Article 

Google Scholar 
Ruprecht, E., Donath, T. W., Otte, A. & Eckstein, R. L. Chemical effects of a dominant grass on seed germination of four familial pairs of dry grassland species. Seed Sci. Res. 18, 239–248 (2008).Article 

Google Scholar 
Partzsch, M., Faulhaber, M. & Meier, T. The effect of the dominant grass Festuca rupicola on the establishment of rare forbs in semi-dry grasslands. Folia Geobot. 53, 103–113 (2018).Article 

Google Scholar 
Fenesi, A., Kelemen, K., Sándor, D. & Ruprecht, E. Influential neighbours: Seeds of dominant species affect the germination of common grassland species. J. Veg. Sci. 31, 1028–1038 (2020).Article 

Google Scholar 
Garbowski, M. et al. Getting to the root of restoration: Considering root traits for improved restoration outcomes under drought and competition. Restor. Ecol. 28, 1384–1395 (2020).Article 

Google Scholar 
Rehling, F., Sandner, T. M. & Matthies, D. Biomass partitioning in response to intraspecific competition depends on nutrients and species characteristics: A study of 43 plant species. J. Ecol. 109, 2219–2233 (2021).Article 

Google Scholar 
Gross, K. L. & Mittelbach, G. G. Negative effects of fertilization on grassland species richness are stronger when tall clonal species are present. Folia Geobot. 52, 401–409 (2017).Article 

Google Scholar 
Bakker, J. P. & Berendse, F. Constraints in the restoration of ecological diversity in grassland and heathland communities. Trends Ecol. Evol. 14, 63–68 (1999).Article 
CAS 

Google Scholar 
Kiss, R., Valkó, O., Tóthmérész, B. & Török, P. Seed bank research in Central-European grasslands: An overview. In Seed Banks: Types Roles and Research (ed. Murphy, J.) 1–34 (Nova Science Publishers, 2016).
Google Scholar 
Prach, K., Jongepierová, I. & Řehounková, K. Large-scale restoration of dry grasslands on ex-arable land using a regional seed mixture: Establishment of target species. Restor. Ecol. 21, 33–39 (2013).Article 

Google Scholar 
Adler, P. B. et al. Competition and coexistence in plant communities: intraspecific competition is stronger than interspecific competition. Ecol. Lett. 21, 1319–1329 (2018).Article 

Google Scholar 
Baskin, C. C. & Baskin, J. M. Seeds: Ecology, Biogeography, And Evolution of Dormancy and Germination (Academic Press, 1998).
Google Scholar 
Kövendi-Jakó, A. et al. Effect of seed storing duration and sowing year on the seedling establishment of grassland species in xeric environments. Restor. Ecol. 29, e13209. https://doi.org/10.1111/rec.13209 (2020).Article 

Google Scholar 
Cevallos, D., Szitár, K., Halassy, M., Kövendi-Jakó, A. & Török, K. Larger seed mass predicts higher germination and emergence rates in sand grassland species with non-dormant seeds. Acta Bot. Hung. 64, 237–258 (2022).Article 

Google Scholar 
Leishman, M. R., Wright, I. J., Moles, A. T. & Westoby, M. The evolutionary ecology of seed size. In Seeds: The Ecology of Regeneration in Plant Communities (ed. Fenner, M.) 31–57 (CAB International, 2000).Chapter 

Google Scholar 
Westoby, M., Falster, D. S., Moles, A. T., Vesk, P. A. & Wright, I. J. Plant ecological strategies: Some leading dimensions of variation between species. Annu. Rev. Ecol. Evol. Syst. 33, 125–215 (2002).Article 

Google Scholar 
Moles, A. T. & Westoby, M. Seed size and plant strategy across the whole life cycle. Oikos 113, 91–105 (2006).Article 

Google Scholar 
Scotton, M. Seed production in grassland species: Morpho-biological determinants in a species-rich semi-natural grassland. Grass Forage Sci. 73, 764–776 (2018).Article 

Google Scholar 
Thompson, K., Bakker, J. P. & Bekker, R. M. The Soil Seed Banks of North West Europe: Methodology, Density and Longevity (Cambridge University Press, 1997).
Google Scholar 
Fick, S. E. & Hijmans, R. J. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
ENSCONET (European Native Seed Conservation Network). ENSCONET Seed Collecting Manual for Wild Species. ENSCONET, Royal Botanic Gardens, Kew and Universidad Politécnica de Madrid (2009). http://www.kew.org/sites/default/files/ENSCONET_Collecting_protocol_English.pdf. Accessed 15 April 2014).Borhidi, A. Social behaviour types, the naturalness and relative indicator values of the higher plants in the Hungarian flora. Acta Bot. Hung. 39, 97–181 (1995).
Google Scholar 
Király, G. (ed). Új magyar füvészkönyv. Magyarország hatásos növényei (New Hungarian Herbal. The Vascular Plants of Hungary. Identification Key) [in Hungarian]. (Aggtelek National Park Directorate, 2009).R Core Team. R: A Language and Environment for Statistical Computing (4.0.5). Computer Software. R Foundation for Statistical Computing. https://www.R-project.org (2021).Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R. J. 9, 378–400 (2017).Article 

Google Scholar 
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means (Version 1.3.4) [R]. https://CRAN.R-project.org/package=emmeans (2019). More

Indonesia’s bleeding toad (Leptophryne cruentata) is critically endangered.Credit: Pepew Fegley/Shutterstock

One-quarter of all plant and animal species are threatened with extinction owing to factors such as climate change and pollution. Starting this week, negotiators and ministers from more than 190 countries are meeting at a United Nations biodiversity summit called COP15 in Montreal, Canada, to address the emergency.
10 startling images of nature in crisis — and the struggle to save it
From 7 to 19 December, they will be trying to seal a new deal to save Earth’s biodiversity. The treaty, known as the post-2020 Global Biodiversity Framework, is intended to establish precise targets for countries to protect and restore nature, including conserving 30% of the planet by 2030 and cutting nutrient pollution, such as reducing nitrogen fertilizer loss from farmland.Time is running out. “We’re driving species to extinction at a rate about 1,000 times faster than they are created through evolution,” says Stuart Pimm, an ecologist at Duke University in Durham, North Carolina, and head of Saving Nature, a non-profit conservation organization.As COP15 kicks off, researchers and policy experts are concerned that countries still disagree on too many issues to secure a deal that will protect species and ecosystems effectively. Here, Nature looks at the extent of the crisis, and what scientists say countries must do to succeed.Which species are most at risk, and what’s threatening them?Among the most at-risk groups are amphibians and reef-forming corals. A global assessment shows that more than 40% of amphibians are threatened with extinction1, including the critically endangered bleeding toad (Leptophryne cruentata), which lives in Mount Gede Pangrango National Park in Java, Indonesia.These toads were thought to be extinct until the year 2000, when some were spotted by a team led by Mirza Kusrini, a herpetologist at Bogor Agricultural University in Indonesia. But the researchers found that the amphibians were infected with chytrid (Chytridiomycota sp.), a fungus that has devastated global amphibian populations. Kusrini says that climate change is probably making life hard for the tiny toad, which got its common name from the crimson, splatter-like spots covering its body. Warm weather can stimulate fungal outbreaks and shift the timing of behaviours, such as the toads’ breeding season, making the amphibians vulnerable.

Source: Red List Index/IUCN

Global warming, which has been raising sea temperatures, is also responsible for harming coral reefs around the globe (see ‘Threat assessment’). Over a period of 9 years, up to 2018, 14% of the world’s coral died out — a massive problem, because today, coral reefs support one-quarter of all marine species.Research shows that climate change is quickly becoming a large threat to biodiversity2. But still, the most-destructive forces are the conversion of land and seas for agricultural uses and people exploiting natural resources through fishing, logging, hunting and the wildlife trade. About 75% of land and 66% of ocean areas have been significantly altered, usually for producing food.What might happen if species disappear?It’s difficult to predict, because doing so requires knowledge of which species are present in a particular ecosystem, such as a rainforest, and what functions they have, says Shahid Naeem, an ecologist at Columbia University in New York City. Much of that information is often unknown. However, scientists have shown3 that ecosystems with less biodiversity are not as good at capturing and converting resources into biomass, such as happens when plants capture nutrients or sunlight used for growth.
Why deforestation and extinctions make pandemics more likely
Neither are less-diverse ecosystems as good at decomposing and recycling biological materials and nutrients. For example, studies show that dead organisms are broken down, and their nutrients recycled, more quickly when a high variety of plant litter covers the forest floor4. Ecosystems with low biodiversity also have low resilience — they are not as able to bounce back after a perturbation or shock, such as a fire, as more-diverse systems are, Naeem says.“If we lose parts of our system, it simply won’t function very efficiently, and it won’t be very robust,” he adds. “The science behind that is rock solid.”Ecosystems also provide clean water and can sometimes prevent diseases from spreading to humans. When species are lost, these services deteriorate, Kusrini says. For example, most amphibians eat insects, many of which are considered pests, such as cockroaches, termites and mosquitoes. Studies have shown a rise in cases of malaria — spread by mosquitoes — in areas in Central America where amphibian populations have collapsed5. “You know when they disappear”, Kusrini says, because insect numbers rise and people start using more pesticides to kill them.What solutions do researchers say are needed to protect biodiversity?Protecting and conserving habitats is central to saving species. This idea is captured in the framework being negotiated at COP15. The draft includes the goal of conserving at least 30% of the world’s land and sea by 2030. But for protections to be most effective, they must include regions that are rich in biodiversity, such as tropical forests, Pimm says. Despite an increase in protected areas worldwide over the past ten years, species numbers have still declined, because these safeguards were not in the right places, studies show6.

Delegates at COP15 in Montreal show their support for a new agreement among nations to protect Earth’s biodiversity.Credit: UN Convention on Biological Diversity (CC BY 2.0)

“What we’re going to be looking for at COP15 is more quality, not just more quantity,” Pimm says.Eradicating invasive species is another important conservation strategy, and the framework’s draft currently calls for cutting the introduction of such species in half. Some estimates suggest that invasive predators, such as cats and rats, are responsible for more than half of all extinctions of birds, mammals and reptiles7.It’s important that nations agree on a framework with at least some quantifiable targets, so that progress can be measured, and so that countries can be held accountable if they fail to meet their targets, researchers say. “I’m afraid what will happen is, they will produce a long list of ‘waffle’,” Pimm says. “We need quantification.”Will nations manage to agree on a new deal to protect nature?As COP15 begins, the outlook is not good. The text of the draft is still littered with unresolved issues. At a press conference on 6 December, Elizabeth Mrema, executive secretary of the Convention on Biological Diversity — the global treaty that underpins the new biodiversity deal — said that national negotiators had made insufficient progress in a final round of discussions before the start of the summit. She urged countries to compromise, otherwise they will fail to reach a deal. “The state of the planet is in crisis,” Mrema said. “This is our last chance to act.”
Troubled biodiversity plan gets billion-dollar funding boost
One key contentious issue is how to finance biodiversity conservation, particularly in low- and middle-income countries, which are home to much of the world’s biodiversity. These nations, including Brazil and Gabon, would like a new fund to be established with US$100 billion added per year in aid. So far, that proposal has not gained traction with wealthier countries. “They really need to have the financial commitments, because things don’t get done without the money,” Naeem says.Despite the pessimism, Naeem is certain that scientists and advocates will keep pushing for a deal. “There would be real change” if countries were able to achieve a universal decrease in biodiversity loss, he says. More

Coyne, J. A. & Orr, H. A. Speciation 83–178 (Sinauer, 2004).Dieckmann, U., Doebeli, M., Metz, J. A. & Tautz, D. Adaptive Speciation (Cambridge University Press, 2004).Butlin, R. K., Galindo, J. & Grahame, J. W. Sympatric, parapatric or allopatric: the most important way to classify speciation? Philos. T. Roy. Soc. B 363, 2997–3007 (2008).Article 

Google Scholar 
Smadja, C. M. & Butlin, R. K. A framework for comparing processes of speciation in the presence of gene flow. Mol. Ecol. 20, 5123–5140 (2011).Article 

Google Scholar 
Seehausen, O. et al. Genomics and the origin of species. Nat. Rev. Genet. 15, 176–192 (2014).Article 
CAS 

Google Scholar 
Kulmuni, J., Butlin, R. K., Lucek, K., Savolainen, V. & Westram, A. M. Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers. Philos. T. Roy. Soc. B 375, 20190528 (2020).Article 

Google Scholar 
Hofreiter, M. & Stewart, J. Ecological change, range fluctuations and population dynamics during the Pleistocene. Curr. Biol. 19, R584–R594 (2009).Article 
CAS 

Google Scholar 
Longman, J., Mills, B. J. W., Manners, H. R., Gernon, T. M. & Palmer, M. R. Late Ordovician climate change and extinctions driven by elevated volcanic nutrient supply. Nat. Geosci. 14, 924–929 (2021).Article 
ADS 
CAS 

Google Scholar 
Thomson, R. C., Spink, P. Q. & Shaffer, H. B. A global phylogeny of turtles reveals a burst of climate-associated diversification on continental margins. Proc. Natl Acad. Sci. USA 118, e2012215118 (2021).Article 
CAS 

Google Scholar 
Chaboureau, A. C., Sepulchre, P., Donnadieu, Y. & Franc, A. Tectonic-driven climate change and the diversification of angiosperms. Proc. Natl Acad. Sci. USA 111, 14066–14070 (2014).Article 
ADS 
CAS 

Google Scholar 
Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).Article 
ADS 
CAS 

Google Scholar 
Schmitt, T. Molecular biogeography of Europe: Pleistocene cycles and postglacial trends. Front. Zool. 4, 11 (2007).Article 

Google Scholar 
Haffer, J. Speciation in Amazonian forest birds. Science 165, 131–137 (1969).Article 
ADS 
CAS 

Google Scholar 
Ebdon, S. et al. The Pleistocene species pump past its prime: evidence from European butterfly sister species. Mol. Ecol. 30, 3575–3589 (2021).Article 

Google Scholar 
Excoffier, L., Foll, M. & Petit, R. J. Genetic consequences of range expansions. Annu. Rev. Ecol. Evol. Syst. 40, 481–501 (2009).Article 

Google Scholar 
Baker, H. G. Self-compatibility and establishment after ‘long-distance’ dispersal. Evolution 9, 347–349 (1955).
Google Scholar 
Fisher, R. The Genetical Theory of Natural Selection 125–129 (Oxford University Press, 1930).Endler, J. A. Geographic Variation, Speciation, and Clines. Monographs in Population Biology Vol. 10, 53–65, 142–150 (Princeton University Press, 1977).Doebeli, M. & Dieckmann, U. Speciation along environmental gradients. Nature 421, 259–264 (2003).Article 
ADS 
CAS 

Google Scholar 
Ispolatov, J. & Doebeli, M. Diversification along environmental gradients in spatially structured populations. Evol. Ecol. Res. 11, 295–304 (2009).
Google Scholar 
Rettelbach, A., Servedio, M. R. & Hermisson, J. Speciation in peripheral populations: effects of drift load and mating systems. J. Evol. Biol. 29, 1073–1090 (2016).Article 
CAS 

Google Scholar 
Wright, S. I., Kalisz, S. & Slotte, T. Evolutionary consequences of self-fertilization in plants. Proc. R. Soc. Lond. Ser. B 280, 20130133 (2013).
Google Scholar 
Hu, X.-S. Mating system as a barrier to gene flow. Evolution 69, 1158–1177 (2015).Article 
CAS 

Google Scholar 
Glémin, S. How are deleterious mutations purged? Drift versus nonrandom mating. Evolution 57, 2678–2687 (2003).
Google Scholar 
Warwick, S. I., Francis, A. & Al-Shehbaz, I. A. Brassicaceae: species checklist and database on CD-Rom. Plant Syst. Evol. 259, 249–258 (2006).Article 

Google Scholar 
Warwick, S. I., Al-Shehbaz, I. A. & Sauder, C. A. Phylogenetic position of Arabis arenicola and generic limits of Aphragmus and Eutrema (Brassicaceae) based on sequences of nuclear ribosomal DNA. Can. J. Bot. 84, 269–281 (2006).Article 
CAS 

Google Scholar 
Hohmann, N. et al. Taming the wild: resolving the gene pools of non-model Arabidopsis lineages. BMC Evol. Biol. 14, e224 (2014).Article 

Google Scholar 
Novikova, P. Y. et al. Sequencing of the genus Arabidopsis identifies a complex history of nonbifurcating speciation and abundant trans-specific polymorphism. Nat. Genet. 48, 1077–1082 (2016).Article 
CAS 

Google Scholar 
Perrier, A. & Willi, Y. Intraspecific variation in reproductive barriers between two recently-diverged, allopatric Arabidopsis species. J. Evol. Biol. https://doi.org/10.1111/jeb.14122 (2022). (in press).Griffin, P. C. & Willi, Y. Evolutionary shifts to self-fertilisation restricted to geographic range margins in North American Arabidopsis lyrata. Ecol. Lett. 17, 484–490 (2014).Article 
CAS 

Google Scholar 
Willi, Y., Fracassetti, M., Zoller, S. & Van Buskirk, J. Accumulation of mutational load at the edges of a species range. Mol. Biol. Evol. 35, 781–791 (2018).Article 
CAS 

Google Scholar 
Schmickl, R., Jørgensen, M. H., Brysting, A. K. & Koch, M. A. The evolutionary history of the Arabidopsis lyrata complex: a hybrid in the Amphi-Beringian area closes a large distribution gap and builds up a genetic barrier. BMC Evol. Biol. 10, e98 (2010).Article 

Google Scholar 
Pyhäjärvi, T., Aalto, E. & Savolainen, O. Time scales of divergence and speciation among natural populations and subspecies of Arabidopsis lyrata (Brassicaceae). Am. J. Bot. 99, 1314–1322 (2012).Article 

Google Scholar 
Dyke, A. S. in Quaternary Glaciations – Extent and Chronology, Part II: North America (Elsevier, Amsterdam, 2004).Kirkpatrick, M. & Ravigné, V. Speciation by natural and sexual selection: models and experiments. Am. Nat. 159, S22–S35 (2002).Article 

Google Scholar 
Igic, B., Lande, R. & Kohn, J. R. Loss of self‐incompatibility and its evolutionary consequences. Int. J. Plant Sci. 169, 93–104 (2008).Article 

Google Scholar 
Willi, Y. & Määttänen, K. Evolutionary dynamics of mating system shifts in Arabidopsis lyrata. J. Evol. Biol. 23, 2123–2131 (2010).Article 
CAS 

Google Scholar 
Lucek, K. & Willi, Y. Drivers of linkage disequilibrium across a species’ geographic range. PLoS Genet. 17, e1009477 (2021).Article 
CAS 

Google Scholar 
Pironon, S. et al. Geographic variation in genetic and demographic performance: new insights from an old biogeographical paradigm: the centre-periphery hypothesis. Biol. Rev. 92, 1877–1909 (2017).Article 

Google Scholar 
Encinas-Viso, F., Young, A. G. & Pannell, J. R. The loss of self-incompatibility in a range expansion. J. Evol. Biol. 33, 1235–1244 (2020).Article 

Google Scholar 
Jarne, P. & Auld, J. R. Animals mix it up too: the distribution of self-fertilization among hermaphroditic animals. Evolution 60, 1816–1824 (2006).
Google Scholar 
Foxe, J. P. et al. Reconstructing origins of loss of self-incompatibility and selfing in North American Arabidopsis lyrata: a population genetic context. Evolution 64, 3495–3510 (2010).Article 

Google Scholar 
Koski, M. H., Layman, N. C., Prior, C. J., Busch, J. W. & Galloway, L. F. Selfing ability and drift load evolve with range expansion. Evol. Lett. 3, 500–512 (2019).Article 

Google Scholar 
Prior, C. J. & Busch, J. W. Selfing rate variation within species is unrelated to life‐history traits or geographic range position. Am. J. Bot. 108, 2294–2308 (2021).Article 

Google Scholar 
Skeels, A. & Cardillo, M. Reconstructing the geography of speciation from contemporary biodiversity data. Am. Nat. 193, 240–254 (2019).Article 

Google Scholar 
Sánchez-Castro, D., Perrier, A. & Willi, Y. Reduced climate adaptation at range edges in North American Arabidopsis lyrata. Glob. Ecol. Biogeogr. 31, 1066–1077 (2022).Article 

Google Scholar 
Roessler, K. et al. The genome-wide dynamics of purging during selfing in maize. Nat. Plants 5, 980–990 (2019).Article 
CAS 

Google Scholar 
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).Hu, T. T. et al. The Arabidopsis lyrata genome sequence and the basis of rapid genome size change. Nat. Genet. 43, 476–481 (2011).Article 

Google Scholar 
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).Article 

Google Scholar 
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).Article 
CAS 

Google Scholar 
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).Article 
CAS 

Google Scholar 
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).Article 
CAS 

Google Scholar 
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).Article 
CAS 

Google Scholar 
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).Article 
CAS 

Google Scholar 
Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).Article 
CAS 

Google Scholar 
Excoffier, L., Dupanloup, I., Huerta-Sánchez, E., Sousa, V. C. & Foll, M. Robust demographic inference from genomic and SNP data. PLoS Genet. 9, e1003905 (2013).Article 

Google Scholar 
Marchi, N. et al. The genomic origins of the world’s first farmers. Cell 185, 1842–1859 (2022).Article 
CAS 

Google Scholar 
Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).Article 
CAS 

Google Scholar 
Genete, M., Castric, V. & Vekemans, X. Genotyping and de novo discovery of allelic variants at the Brassicaceae self-incompatibility locus from short-read sequencing data. Mol. Biol. Evol. 7, 1193–1201 (2020).Article 

Google Scholar 
Lynch, M. et al. Genome-wide linkage-disequilibrium profiles from single individuals. Genetics 198, 269–281 (2014).Article 

Google Scholar 
R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2021).Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).Article 
CAS 

Google Scholar 
Nychka, D., Furrer, R., Paige, J. & Sain, S. fields: tools for spatial data. R package version 14.1 https://github.com/dnychka/fieldsRPackage (2021).Asquith, W. lmomco—L-moments, censored L-moments, trimmed L-moments, L-comoments, and many distributions. R package version 2.4.7 (2022).Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).Article 

Google Scholar 
Lemon, J. Plotrix: a package in the red light district of R. R. N. 6, 8–12 (2006).
Google Scholar 
Pebesma, E. J. & Bivand, R. S. Classes and methods for spatial data in R. R. N. 5, 9–13 (2005).
Google Scholar 
Bivand, R. S., Pebesma, E. & Gomez-Rubio, V. Applied Spatial Data Analysis with R Second edition (Springer, 2013). More

Field parameters and major ionsThe results of the hydrochemistry and environmental isotopes for the 40 lakes are presented spatially in Figs. S1–S11 and are located in Tables S1 and S2.The lake waters are oxic (8.6–12.6 mg l−1) and range from slightly acidic (pH 6.0) to slightly alkaline (pH 9.2). Lake water temperatures are generally highest for lakes along the west coast (greater than 10 °C, Table S2). Phosphate concentrations are below detection level (0.1 mg l−1) for all lakes and nitrate was low ranging from below detection limit ( More