Ecology

Effects of storage and technical variationWe first validated our methods by assessing the effect of storage and technical variation on microbiome composition. To quantify the effect of the two storage methods on bacterial composition in fresh samples, we performed a separate pilot study with nine faecal samples sourced from nine captive meerkats at Zurich University. Samples were immediately frozen after collection, and then either freeze-dried or kept frozen at −80 °C for seven days. Microbiome composition clustered strongly by sample identity in their beta diversity (Supplementary Fig. 1b), and storage did not significantly affect composition (Weighted Unifrac: F = 0.7, p = 0.52; Unweighted Unifrac: F = 1.0, p = 0.37). Across samples analysed in this study, storage had significant yet small effects on estimated bacterial load, with frozen samples overall having slightly lower estimated abundance (t = 7.2, p  More

1.Chaney, R. L., Kim, W. I., Kunhikrishnan, A., Yang, J. E. & Ok, Y. S. Integrated management strategies for arsenic and cadmium in rice paddy environments. Geoderma 270, 1–116. https://doi.org/10.1016/j.geoderma.2016.03.001 (2016).ADS 
Article 

Google Scholar 
2.Nakashima, K., Yamaguchi-Shinozaki, K. & Shinozaki, K. The transcriptional regulatory network in the drought response and its crosstalk in abiotic stress responses including drought, cold, and heat. Front. Plant Sci. 5, 170. https://doi.org/10.3389/fpls.2014.00170 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
3.Senthil-Nathan, S. Physiological and biochemical effect of neem and other Meliaceae plants secondary metabolites against Lepidopteran insects. Front. Physiol. 4, 359. https://doi.org/10.3389/fphys.2013.00359 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
4.Kalaivani, K., Maruthi-Kalaiselvi, M. & Senthil-Nathan, S. Seed treatment and foliar application of methyl salicylate (MeSA) as a defense mechanism in rice plants against the pathogenic bacterium, Xanthomonas oryzae pv. oryzae. Pest Biochem. Physiol. 171, 104718. https://doi.org/10.1016/j.pestbp.2020.104718 (2021).CAS 
Article 

Google Scholar 
5.Das, G. & Rao, G. J. N. Molecular marker assisted gene stacking for biotic and abiotic stress resistance genes in an elite rice cultivar. Front. Plant Sci. 6, 698. https://doi.org/10.3389/fpls.2015.00698 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
6.Senthil-Nathan, S. A review of biopesticides and their mode of action against insect pests. Environ. Sustain. https://doi.org/10.1007/978-81-322-2056-5_3 (2015).Article 

Google Scholar 
7.Shi, W. et al. Grain yield and quality responses of tropical hybrid rice to high night-time temperature. Food Crop Res. 190, 18–25. https://doi.org/10.1016/j.fcr.2015.10.006 (2016).Article 

Google Scholar 
8.Farooq, M. et al. Rice direct seeding: Experiences, challenges and opportunities. Soil Till. Res. 111, 87–98. https://doi.org/10.1016/j.still.2010.10.008 (2011).Article 

Google Scholar 
9.Brown, J. K. M. Yield penalties of disease resistance in crops. Curr. Opin. Plant Biol. 5, 339–344. https://doi.org/10.1016/S1369-5266(02)00270-4 (2002).CAS 
Article 
PubMed 

Google Scholar 
10.Liu, H. et al. Antifungal effect and mechanism of chitosan against the rice sheath blight pathogen, Rhizoctonia solani. Biotechnol. Lett. 34, 2291–2298. https://doi.org/10.1007/s10529-012-1035-z (2012).CAS 
Article 
PubMed 

Google Scholar 
11.Orzali, L., Corsi, B., Forni, C. & Riccinoi, L. Chitosan in agriculture: A new challenge for managing plant disease, biological activities and application of marine polysaccharides. Biol. Act. Appl. Mar. Polysaccharides. 17–36. https://doi.org/10.5772/66840 (2017).
12.Anosheh, H. P., Sadeghi, H. & Emam, Y. Chemical priming with urea and KNO3 enhances maize hybrids (Zea mays L.) seed viability under abiotic stress. J. Crop Sci. Biotechnol. 14, 289–295. https://doi.org/10.1007/s12892-011-0039-x (2011).Article 

Google Scholar 
13.Hänsch, R. & Mendel, R. R. Physiological functions of mineral micronutrients (Cu, Zn, Mn, Fe, Ni, Mo, B, Cl). Curr. Opin. Plant Biol. 12, 259–266. https://doi.org/10.1016/j.pbi.2009.05.006 (2009).CAS 
Article 
PubMed 

Google Scholar 
14.Savvides, A., Ali, S., Tester, M. & Fotopoulos, V. Chemical priming of plants against multiple abiotic stresses: Mission possible?. Trends Plant Sci. 21, 329–340. https://doi.org/10.1016/j.tplants.2015.11.003 (2016).CAS 
Article 
PubMed 

Google Scholar 
15.Kurita, K. Chitin and chitosan: Functional biopolymers from marine crustaceans. Mar. Biotechnol. 8, 203–226. https://doi.org/10.1007/s10126-005-0097-5 (2006).CAS 
Article 

Google Scholar 
16.Hamed, I., Özogul, F. & Regenstein, J. M. Industrial applications of crustacean by-products (chitin, chitosan, and chitooligosaccharides): A review. Trends Food Sci. Technol. 48, 40–50. https://doi.org/10.1016/j.tifs.2015.11.007 (2016).CAS 
Article 

Google Scholar 
17.Badawy, M. E. I. & Rabea, E. I. A. Biopolymer chitosan and its derivatives as promising antimicrobial agents against plant pathogens and their applications in crop protection. Int. J. Carbohydr. Chem. https://doi.org/10.1155/2011/460381 (2011).Article 

Google Scholar 
18.Davydova, V. N. et al. Chitosan antiviral activity: Dependence on structure and depolymerization method. Appl. Biochem. Microbiol. 47, 103–108. https://doi.org/10.1134/S0003683811010042 (2011).CAS 
Article 

Google Scholar 
19.Park, B. K. & Kim, M. M. Applications of chitin and its derivatives in biological medicine. Int. J. Mol. Sci. 11, 5152–5164. https://doi.org/10.3390/ijms11125152 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
20.Malerba, M. & Cerana, R. Chitosan effects on plant systems. Int. J. Mol. Sci. 17, 996. https://doi.org/10.3390/ijms17070996 (2016).CAS 
Article 
PubMed Central 

Google Scholar 
21.Liu, H. et al. Progress and constraints of dry direct-seeded rice in China. J. Food Agric. Environ. 2121, 465–472 (2014).
Google Scholar 
22.Li, B., Wang, X., Chen, R., Huangfu, W. & Xie, G. Antibacterial activity of chitosan solution against Xanthomonas pathogenic bacteria isolated from Euphorbia pulcherrima. Carbohydr. Polym. 72, 287–292. https://doi.org/10.1016/j.carbpol.2007.08.012 (2008).CAS 
Article 

Google Scholar 
23.Falcón-Rodríguez, A. B., Cabrera, J. C., Wégria, G., Onderwater, R. C. A., González, G., Nápoles, M. C., Costales, D., Rogers, H. J., Diosdado, E., González, S., Cabrera, G., González, L. & Wattiez, R. Practical use of oligosaccharins in agriculture. In Ist World Congress on the use of biostimulants in agriculture. Acta Hortic. 1009, 195–212 (2012).24.Yin, H. et al. Genome shuffling of Saccharomyces cerevisiae for enhanced glutathione yield and relative gene expression analysis using fluorescent quantitation reverse transcription polymerase chain reaction. J. Microbiol. Methods 127, 188–192. https://doi.org/10.1016/j.mimet.2016.06.012 (2016).CAS 
Article 
PubMed 

Google Scholar 
25.Borah, N. et al. Low energy rice stubble management through in situ decomposition. Procedia Environ. Sci. 35, 771–780. https://doi.org/10.1016/j.proenv.2016.07.092 (2016).CAS 
Article 

Google Scholar 
26.Singh, R., Srivastava, M. & Shukla, A. Environmental sustainability of bioethanol production from rice straw in India: A review. Renew. Sustain. Energy Rev. 54, 202–216. https://doi.org/10.1016/j.rser.2015.10.005 (2016).CAS 
Article 

Google Scholar 
27.Mrudula, S. & Murugammal, R. Production of cellulase by Aspergillus niger under submerged and solid state fermentation using coir waste as a substrate. Braz. J. Microbiol. 42, 1119–1127. https://doi.org/10.1590/S1517-83822011000300033 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
28.El-Sayed, S. M. & Mahdy, M. E. Effect of chitosan on root-knot nematode, Meloidogyne javanica on tomato plants. Int. J. ChemTech Res. 7, 1985–1992 (2015).
Google Scholar 
29.Iriti, M. & Varoni, E. M. Chitosan-induced antiviral activity and innate immunity in plants. Environ. Sci. Pollut. Res. 22, 2935–2944. https://doi.org/10.1007/s11356-014-3571-7 (2015).CAS 
Article 

Google Scholar 
30.Orzali, L. et al. Chitosan in agriculture: A new challenge for chitosan in agriculture: A new challenge for managing plant disease managing plant disease. InTech Open Publisher https://doi.org/10.5772/66840 (2017).ADS 
Article 

Google Scholar 
31.Nanda, S., Mohammad, J., Reddy, S. N., Kozinski, J. A. & Dalai, A. K. Pathways of lignocellulosic biomass conversion to renewable fuels. Biomass Convers. Biorefinery 4, 157–191. https://doi.org/10.1007/s13399-013-0097-z (2014).CAS 
Article 

Google Scholar 
32.Aggarwal, N. K., Goyal, V., Saini, A., Yadav, A. & Gupta, R. Enzymatic saccharification of pretreated rice straw by cellulases from Aspergillus niger BK01. 3 Biotech 7, 158. https://doi.org/10.1007/s13205-017-0755-0 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
33.Fatma, H., Abd-EI-Zaher & Fadel, M. Production of bioethanol via enzymatic saccharification of rice straw by cellulase produced by Trichoderma Reesei under solid state fermentation. N. Y. Sci. J., 72–78. http://www.sciencepub.net/newyork (2010).34.Chang, A. K. T., Frias, R. R., Alvarez, L. V., Bigol, U. G. & Guzman, J. P. M. D. Comparative antibacterial activity of commercial chitosan and chitosan extracted from Auricularia sp. Biocatal. Agric. Biotechnol. 17, 189–195. https://doi.org/10.1016/j.bcab.2018.11.016 (2019).Article 

Google Scholar 
35.Lizárraga-Paulín, E. G., Miranda-Castro, S. P., Moreno-Martínez, E., Lara-Sagahón, A. V. & Torres-Pacheco, I. Maize seed coatings and seedling sprayings with chitosan and hydrogen peroxide: Their influence on some phenological and biochemical behaviors. J. Zhejiang Univ. Sci. B. 14, 87–96. https://doi.org/10.1631/jzus.B1200270 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
36.Hadwiger, L. A., Fristensky, B. & Riggleman, R. C. Chitosan, a natural regulator in plant-fungal pathogen interactions, increases crop yields. Chitin Chitosan Relat. Enzymes. https://doi.org/10.1016/b978-0-12-780950-2.50024-1 (1984).Article 

Google Scholar 
37.Mrda, J., Crnobarac, J., Dušanić, N., Jocić, S. & Miklič, V. Germination energy as a parameter of seed quality in different sunflower genotypes. Genetika 43, 427–436. https://doi.org/10.2298/GENSR1103427M (2011).Article 

Google Scholar 
38.Singh, H. et al. Seed priming techniques in field crops—A review. Agric. Rev. 36, 1–14. https://doi.org/10.18805/ag.v36i4.6662 (2015).Article 

Google Scholar 
39.Hameed, A., Sheikh, M. A., Farooq, T., Basra, S. M. A. & Jamil, A. Chitosan priming enhances the seed germination, antioxidants, hydrolytic enzymes, soluble proteins and sugars in wheat seeds. Agrochimica LVII, 31–46 (2013).
Google Scholar 
40.Zhou, Y. G. et al. Effects of chitosan on some physiological activity in germinating seed of peanut. J. Peanut Sci. 31, 22–25 (2002).
Google Scholar 
41.Samarah, N. H., Wang, H. & Welbaum, G. E. Pepper (Capsicum annuum) seed germination and vigour following nanochitin, chitosan or hydropriming treatments. Seed Sci. Technol. 44, 1–15. https://doi.org/10.15258/sst.2016.44.3.18 (2016).Article 

Google Scholar 
42.Chen, J. L. & Zhao, Y. Effect of molecular weight, acid, and plasticizer on the physicochemical and antibacterial properties of β-chitosan based films. J. Food Sci. 77, E127–E136. https://doi.org/10.1111/j.1750-3841.2012.02686.x (2012).CAS 
Article 
PubMed 

Google Scholar 
43.Kulikov, S. N., Chirkov, S. N., Il’ina, A. V., Lopatin, S. A. & Varlamov, V. P. Effect of the molecular weight of chitosan on its antiviral activity in plants. Appl. Biochem. Microbiol. 42, 200–203. https://doi.org/10.1134/S0003683806020165 (2006).CAS 
Article 

Google Scholar 
44.El Hadrami, A., Adam, L. R., El Hadrami, I. & Daayf, F. Chitosan in plant protection. Mar. Drugs 8, 968–987. https://doi.org/10.3390/md8040968 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
45.Orzali, L., Forni, C. & Riccioni, L. Effect of chitosan seed treatment as elicitor of resistance to Fusarium graminearum in wheat. Seed Sci. Technol. 42, 132–149. https://doi.org/10.15258/sst.2014.42.2.03 (2014).Article 

Google Scholar 
46.Rabea, E. I., Badawy, M. E. T., Stevens, C. V., Smagghe, G. & Steurbaut, W. Chitosan as antimicrobial agent: Applications and mode of action. Biomacromol 4, 1457–1465. https://doi.org/10.1021/bm034130m (2003).CAS 
Article 

Google Scholar 
47.Wang, X., El Hadrami, A., Adam, L. R. & Daayf, F. Differential activation and suppression of potato defence responses by Phytophthora infestans isolates representing US-1 and US-8 genotypes. Plant Pathol. 57, 1026–1037. https://doi.org/10.1111/j.1365-3059.2008.01866.x (2008).CAS 
Article 

Google Scholar 
48.Smits, J. P., Rinzema, A., Tramper, J., Schlösser, E. E. & Knol, W. Accurate determination of process variables in a solid-state fermentation system. Process Biochem. 31, 669–678. https://doi.org/10.1016/S0032-9592(96)00019-2 (1996).CAS 
Article 

Google Scholar 
49.Kalaivani, K., Kalaiselvi, M. M. & Senthil-Nathan, S. Effect of methyl salicylate (MeSA), an elicitor on growth, physiology and pathology of resistant and susceptible rice varieties. Sci. Rep. 6, 1–11 (2016).Article 

Google Scholar 
50.Rane, K. D. & Hoover, D. G. An evaluation of alkali and acid treatments for chitosan extraction from fungi. Process Biochem. 28, 115–118 (1993).CAS 
Article 

Google Scholar 
51.Crestini, C., Kovac, B. & Giovannozzi-Sermanni, G. Production of chitosan by fungi. 50, 207–210. https://doi.org/10.1002/bit.260500202 (1996).52.Khalaf, S. A. Production and characterization of fungal chitosan under solid-state fermentation conditions. Int. J. Agric. Biol. 6, 1033–1036 (2004).CAS 

Google Scholar 
53.Zhang, Z. T., Chen, D. H. & Chen, L. Preparation of two different serials of chitosan. J. Dong Hua Univ. Engl. Ed. 19, 36–39 (2002).
Google Scholar 
54.Chanthini, K. M. et al. Sustainable agronomic strategies for enhancing the yield and nutritional quality of wild tomato Solanum Lycopersicum (l) Var Cerasiforme Mill. Agronomy 9, 311 (2019).CAS 
Article 

Google Scholar 
55.Ellis, R. H. & Roberts, E. H. Improved equations for the prediction of seed longevity. Ann. Bot. 45, 13–30. https://doi.org/10.1093/oxfordjournals.aob.a085797 (1980).Article 

Google Scholar 
56.Chanthini, K. M. et al. Biocatalysis and agricultural biotechnology Chaetomorpha antennina (Bory) Kützing derived seaweed liquid fertilizers as prospective bio-stimulant for Lycopersicon esculentum (Mill). Biocatal. Agric. Biotechnol. 20, 101190 (2019).Article 

Google Scholar 
57.Murray, P. R., Baron, E. J., Pfaller, M. A., Tenover, F. C. & Yolke, R. H. Manual of clinical Microbiology 6th edn. (American Society of Microbiology Press, 1995).
Google Scholar 
58.French, E. R. Efficacy of five methods of inoculating potato plants with Pseudomonas solanacearum. Phytopathology 76, 1078 (1986).
Google Scholar 
59.Yasmin, S. et al. Biocontrol of Bacterial Leaf Blight of rice and profiling of secondary metabolites produced by rhizospheric Pseudomonas aeruginosa BRp3. Front. Microbiol. 8, 1895. https://doi.org/10.3389/fmicb.2017.01895 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
60.Hammerschmidt, R. & Kuć, J. Lignification as a mechanism for induced systemic resistance in cucumber. Physiol. Plant Pathol. 20, 61–71. https://doi.org/10.1016/0048-4059(82)90024-8 (1982).CAS 
Article 

Google Scholar 
61.Worthington, C. C. Worthington Enzyme Manual: Enzymes and Related Biochemicals (Worthington Biochemical Corporation, 1988).
Google Scholar  More

1.Rubel, F. et al. Geographical distribution of Dermacentor marginatus and Dermacentor reticulatus in Europe. Ticks Tick Borne Dis. 7, 224–233 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
2.Medlock, J. M. et al. Driving forces for changes in geographical distribution of Ixodes ricinus ticks in Europe. Parasites Vectors 6, 1–11 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
3.Jongejan, F. & Uilenberg, G. The global importance of ticks. Parasitology 129, 3–14 (2004).Article 

Google Scholar 
4.Földvári, G., Široký, P., Szekeres, S., Majoros, G. & Sprong, H. Dermacentor reticulatus: a vector on the rise. Parasites Vectors 9, 1–29 (2016).Article 

Google Scholar 
5.Ličková, M. et al. Dermacentor reticulatus is a vector of tick-borne encephalitis virus. Ticks Tick Borne Dis. 11, 101414 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
6.Pawełczyk, A. et al. Long-term study of Borrelia and Babesia prevalence and co-infection in Ixodes ricinus and Dermacentor recticulatus ticks removed from humans in Poland, 2016–2019. Parasites Vectors 14, 1–13 (2021).Article 
CAS 

Google Scholar 
7.Karbowiak, G. et al. The competition between immatures of Ixodes ricinus and Dermacentor reticulatus (Ixodida: Ixodidae) ticks for rodent hosts. J. Med. Entomol. 56, 448–452 (2018).Article 

Google Scholar 
8.Karbowiak, G. The occurrence of the Dermacentor reticulatus tick-its expansion to new areas and possible causes. Ann. Parasitol. 60, 37–47 (2014).PubMed 
PubMed Central 

Google Scholar 
9.Drehmann, M. et al. The Spatial Distribution of Dermacentor Ticks (Ixodidae) in Germany: Evidence of a continuing spread of Dermacentor reticulatus. Front. Vet. Sci. 7, 578220 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
10.Sands, B. O., Bryer, K. E. & Wall, R. Climate and the seasonal abundance of the tick Dermacentor reticulatus. Med. Vet. Entomol. https://doi.org/10.1111/mve.12518 (2021).Article 
PubMed 

Google Scholar 
11.Hasle, G. et al. Transport of ticks by migratory passerine birds to Norway. J. Parasitol. 95, 1342–1351 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
12.Kjær, L. J. et al. A large-scale screening for the taiga tick, Ixodes persulcatus, and the meadow tick, Dermacentor reticulatus, in southern Scandinavia, 2016. Parasites Vectors 12, 1–4 (2019).Article 

Google Scholar 
13.García-Sanmartín, J., Barandika, J. F., Juste, R. A., García-Pérez, A. L. & Hurtado, A. Distribution and molecular detection of Theileria and Babesia in questing ticks from northern Spain. Med. Vet. Entomol. 22, 318–325 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Olivieri, E. et al. The southernmost foci of Dermacentor reticulatus in Italy and associated Babesia canis infection in dogs. Parasites Vectors 9, 1–9 (2016).Article 
CAS 

Google Scholar 
15.Široký, P. et al. The distribution and spreading pattern of Dermacentor reticulatus over its threshold area in the Czech Republic: How much is range of this vector expanding?. Vet. Parasitol. 183, 130–135 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
16.Hornok, S. & Farkas, R. Influence of biotope on the distribution and peak activity of questing ixodid ticks in Hungary. Med. Vet. Entomol. 23, 41–46 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
17.Chitimia-Dobler, L. Spatial distribution of Dermacentor reticulatus in Romania. Vet. Parasitol. 214, 219–223 (2015).PubMed 
Article 

Google Scholar 
18.Akimov, I. & Nebogatkin, I. Distribution of Ticks from of the Genus Dermacentor (Acari, Ixodidae) in Ukraine. Vestnik Zoologii 45, 6 (2011).
Google Scholar 
19.Kiewra, D., Szymanowski, M., Czułowska, A. & Kolanek, A. The local-scale expansion of Dermacentor reticulatus ticks in Lower Silesia, SW, Poland. Ticks Tick Borne Dis. 12, 101599 (2021).PubMed 
Article 

Google Scholar 
20.Dwużnik-Szarek, D. et al. Monitoring the expansion of Dermacentor reticulatus and occurrence of canine babesiosis in Poland in 2016–2018. Parasites Vectors 14, 1–18 (2021).Article 

Google Scholar 
21.Zając, Z., Woźniak, A. & Kulisz, J. Density of Dermacentor reticulatus ticks in eastern Poland. Int. J. Environ. Res. Public Health 17, 2814 (2020).PubMed Central 
Article 

Google Scholar 
22.Ogden, N. H., Ben Beard, C., Ginsberg, H. S. & Tsao, J. I. Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations. J. Med. Entomol. 58, 1536–1545 (2020).Article 

Google Scholar 
23.Zając, Z., Sędzikowska, A., Maślanko, W., Woźniak, A. & Kulisz, J. Occurrence and Abundance of Dermacentor reticulatus in the habitats of the ecological corridor of the Wieprz river, eastern Poland. Insects 12, 96 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
24.Zając, Z., Bartosik, K. & Woźniak, A. Monitoring Dermacentor reticulatus host-seeking activity in natural conditions. Insects 11, 264 (2020).PubMed Central 
Article 

Google Scholar 
25.Global and European temperature—European Environment Agency. https://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature/global-and-european-temperature-assessment-1. Accessed 22 July 2021.26.Średnie i sumy miesięczne. Dane meteorologiczne https://meteomodel.pl/dane/srednie-miesieczne/?imgwid=351220495&par=sndp&max_empty=2. Accessed 22 July 2021.27.Vladimirov, L. N. et al. Quantifying the Northward Spread of Ticks (Ixodida) as climate warms in Northern Russia. Atmosphere 12, 233 (2021).ADS 
Article 

Google Scholar 
28.Mierzejewska, E. J., Alsarraf, M., Behnke, J. M. & Bajer, A. The effect of changes in agricultural practices on the density of Dermacentor reticulatus ticks. Vet. Parasitol. 211, 259–265 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
29.Zając, Z., Woźniak, A. & Kulisz, J. Infestation of dairy cows by ticks Dermacentor reticulatus (Fabricius, 1794) and Ixodes ricinus (Linnaeus, 1758) in eastern Poland. Ann. Parasitol. 66, 87–96 (2020).PubMed 
PubMed Central 

Google Scholar 
30.Estrada-Peña, A. Climate, niche, ticks, and models: What they are and how we should interpret them. Parasitol. Res. 103, 87–95 (2008).Article 

Google Scholar 
31.Süss, J., Klaus, C., Gerstengarbe, F. W. & Werner, P. C. What makes ticks tick? Climate change, ticks, and tick-borne diseases. J. Travel Med. 15, 39–45 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
32.Paulauskas, A. et al. New localities of Dermacentor reticulatus ticks in the Baltic countries. Ticks Tick Borne Dis. 6, 630–635 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
33.Kubiak, K. et al. Dermacentor reticulatus ticks (Acari: Ixodidae) distribution in north-eastern Poland: An endemic area of tick-borne diseases. Exp. Appl. Acarol. 75, 289–298 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Silaghi, C., Weis, L. & Pfister, K. Dermacentor reticulatus and Babesia canis in Bavaria (Germany): A georeferenced field study with digital habitat characterization. Pathogens 9, 541 (2020).CAS 
PubMed Central 
Article 

Google Scholar 
35.Kohn, M. et al. Dermacentor reticulatus in Berlin/Brandenburg (Germany): Activity patterns and associated pathogens. Ticks Tick Borne Dis. 10, 191–206 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Kiewra, D., Czułowska, A., Dyczko, D., Zieliński, R. & Plewa-Tutaj, K. First record of Haemaphysalis concinna (Acari: Ixodidae) in Lower Silesia, SW, Poland. Exp. Appl. Acarol. 77, 449–454 (2019).PubMed 
Article 

Google Scholar 
37.Zieba, P. et al. A new locality of the Haemaphysalis concinna tick (Koch, 1844) in Poland and its role as a potential vector of infectious diseases. Ann. Parasitol. 65, 281–286 (2019).PubMed 

Google Scholar 
38.Gray, J. S., Dautel, H., Estrada-Peña, A., Kahl, O. & Lindgren, E. Effects of climate change on ticks and tick-borne diseases in Europe. Interdiscip. Perspect. Infect. Dis. 2009, 593232 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
39.Medlock, J. M. & Leach, S. A. Effect of climate change on vector-borne disease risk in the UK. Lancet Infect. Dis. 15, 721–730 (2015).PubMed 
Article 

Google Scholar 
40.Pfäffle, M., Littwin, N. & Petney, T. Host preferences of immature Dermacentor reticulatus (Acari: Ixodidae) in a forest habitat in Germany. Ticks Tick Borne Dis. 6, 508–515 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
41.Zając, Z., Bartosik, K., Kulisz, J. & Woźniak, A. Ability of adult Dermacentor reticulatus ticks to overwinter in the temperate climate zone. Biology 9, 145 (2020).PubMed Central 
Article 

Google Scholar 
42.Kiewra, D., Czułowska, A. & Lonc, E. Winter activity of Dermacentor reticulatus (Fabricius, 1794) in the newly emerging population of Lower Silesia, south-west Poland. Ticks Tick Borne Dis. 7, 1124–1127 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Buczek, A., Bartosik, K. & Zając, Z. Changes in the activity of adult stages of Dermacentor reticulatus (Ixodida: Amblyommidae) induced by weather factors in eastern Poland. Parasites Vectors 7, 245 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
44.Hubálek, Z., Halouzka, J. & Juricova, Z. Host-seeking activity of ixodid ticks in relation to weather variables. J. Vector Ecol. 28, 159–165 (2003).PubMed 
PubMed Central 

Google Scholar 
45.Bartosik, K., Wiśniowski, Ł & Buczek, A. Questing behavior of Dermacentor reticulatus adults (Acari: Amblyommidae) during diurnal activity periods in eastern Poland. J. Med. Entomol. 49, 859–864 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
46.Buczek, A., Bartosik, K., Wisniowski, L. & Tomasiewicz, K. Changes in population abundance of adult Dermacentor reticulatus (Acari: Amblyommidae) in long-term investigations in eastern Poland. Ann. Agric. Environ. Med. 20, 269–272 (2013).PubMed 
PubMed Central 

Google Scholar 
47.Mierzejewska, E. J., Estrada-Peña, A., Alsarraf, M., Kowalec, M. & Bajer, A. Mapping of Dermacentor reticulatus expansion in Poland in 2012–2014. Ticks Tick Borne Dis. 7, 94–106 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
48.Zając, Z. et al. Environmental determinants of the occurrence and activity of Ixodes ricinus ticks and the prevalance of tick-borne diseases in eastern Poland. Sci. Rep. 11, 15472 (2021).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
49.Kulisz, J., Bartosik, K., Zając, Z., Woźniak, A. & Kolasa, S. Quantitative parameters of the body composition influencing host seeking behavior of Ixodes ricinus adults. Pathogens 10, 706 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
50.Alasmari, S. & Wall, R. Metabolic rate and resource depletion in the tick Ixodes ricinus in response to temperature. Exp. Appl. Acarol. 83, 81–93 (2020).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
51.Zajac, Z., Bartosik, K. & Buczek, A. Factors influencing the distribution and activity of Dermacentor reticulatus (F.) ticks in an anthropopressure-unaffected area in central-eastern Poland. Ann. Agric. Environ Med. 23, 270–275 (2016).PubMed 
Article 

Google Scholar 
52.Bogdaszewska, Z. Range and ecology of Dermacentor reticulatus (Fabricius, 1794) in Mazuria focus. II. Seasonal activity patterns of the adults. Wiad. Parazytol. 50, 731–738 (2004).PubMed 

Google Scholar 
53.Razumova, I. V. The activity of Dermacentor reticulatus Fabr. (Ixodidae) ticks in nature. Med. Parasitol. Parasites Dis. 4, 8–14 (1999).
Google Scholar 
54.Szymański, S. Seasonal activity of Dermacentor reticulatus (Fabricius, 1794) (Acarina, Ixodidae) in Poland I. Adults. Acta Parasitol. Pol. 31, 247–255 (1987).
Google Scholar 
55.Hornok, S. Allochronic seasonal peak activities of Dermacentor and Haemaphysalis spp. under continental climate in Hungary. Vet. Parasitol. 163, 366–369 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
56.Randolph, S. E. & Storey, K. Impact of microclimate on immature tick-rodent host interactions (Acari: Ixodidae): Implications for parasite transmission. J. Med. Entomol. 36, 741–748 (1999).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
57.Nowak-Chmura, M. Ticks (Ixodida) of Central Europe (Pedagogical University of Cracow Press, 2013).
Google Scholar  More

Altogether, we found that, while traffic volume declined by  > 7% during the pandemic year (with a maximum monthly decline of nearly 40%), the absolute number of annual WVCs was largely unchanged. This resulted in significant increases of  > 8% in collision rates between vehicles and wildlife during the pandemic year, peaking at a  > 27% nationwide increase in April 2020. Other studies from the first several months of the pandemic documented similar transient declines in the number of WVCs when the pandemic began which then reversed in many jurisdictions as the pandemic progressed and traffic rebounded26,27. We observed a similar pattern over the first five months of the pandemic at the national scale (Fig. 2): WVCs initially declined during the pandemic in step with declines in traffic volume, but then started to increase to baseline levels at a faster rate than traffic, possibly due to behavioral lags by wildlife following traffic-mediated increases in wildlife road use. Though based on coarse-scale data, our research aligns with assertions from studies during27 and prior to the pandemic3,15,16,28,29 that the relationship between traffic volume and WVCs is non-linear.We postulate that the observed non-linear relationship between traffic volume and WVCs is the result of greater use of roads and roadsides by certain wildlife species, namely large mammals (Table S1), in response to decreasing traffic volume, as prior research has suggested3,14,15,16. This explanation is consistent with accounts of various wildlife species making increased use of human spaces during the pandemic17,20,21: with less cars on the roads, wildlife might be less deterred from roads by the noise and light pollution that accompany high traffic volumes9,10,11,20 and perceive roads as less risky, thereby increasing their willingness to attempt road crossings3,8,15,16. Beyond incidentally crossing roads while moving about the landscape8,9, wildlife might be attracted to roads for travel, mates, or other resources8,10,11. Many animals are shown to utilize roads to move efficiently across the landscape11,12, and roads and the surrounding areas are comparatively open, such that wildlife might select roads and roadsides for enhanced visibility to find mates, detect predators, or locate prey10,13. Roadsides also can provide foraging opportunities and essential nutrients for wildlife via abundant, high-quality early successional vegetation and high salt concentrations10,11. As such, decreased road traffic during the pandemic might have caused certain wildlife species to tolerate the risks associated with roads in order to access the benefits of roads and roadsides.An alternative explanation for the observed increases in collision rates is that human driving behavior, rather than animal behavior, changed during the pandemic. With fewer cars on the road, people might drive faster35, rendering it more difficult for both humans and wildlife to avoid collisions3. Preliminary studies from throughout the United States have indeed suggested changes to human driving behavior during the pandemic, with several jurisdictions reporting increased vehicle speeds35,36. Despite reported increases in vehicle speeds, however, the total number of vehicle collisions (the sum of both wildlife and non-wildlife collisions) mirrored trends in traffic volume and declined considerably during the pandemic37,38. Thus, because changes to human behavior appear to have had a minimal effect on vehicle collisions overall, it is unlikely that the observed changes in collision rates are due to increased vehicle speeds alone. Still, we cannot discount the possibility that changes to human driving behavior contributed to the patterns documented here, and future work should more explicitly test the relative effects of changes in traffic volume on both human driving behavior and wildlife space-use, as well as the resultant impacts on WVCs.A greater understanding of human driving behavior would also help explain our findings regarding changes in traffic patterns during the pandemic. Nationwide, the severity of COVID-19 restrictions accounted for a large amount of the variation in changes in monthly traffic volume (R2 = 0.968), but the severity of restrictions was less influential on changes in yearly traffic across states (Tables S3 and S4). Restrictions implemented throughout the pandemic were largely enacted for the purpose of minimizing travel, and other research has demonstrated that these restrictions were effective at reducing human mobility18,21. Our state-level findings, however, imply that it was not only the restrictions themselves that reduced travel, but possibly also the associated anxiety regarding the risk of contracting the SARS-CoV-2 virus, as has been suggested in other studies21,22,23,24; although we observed the greatest declines in traffic volume early in the pandemic (Fig. 2A) when restrictions were most stringent (Fig. S2)21, there was widespread anxiety about the risks posed by SARS-CoV-2 during this time22,23, which likely motivated people to stay home independent of restrictions24. Indeed, anxiety and risk perception might explain the relationship between traffic volume and the other covariates in our top models (Table S4). Declines in traffic were greatest in the most densely populated states (Fig. 4A) and in states that had the highest and the lowest disease burdens (Fig. 4B). The risk of SARS-CoV-2 transmission is greater in more densely populated states due to the close proximity of and frequent interactions amongst people21. As such, people may have altered their road use more in densely populated states as compared to sparsely populated ones due to differing perceptions of disease transmission risk23—though differences in infrastructure in relation to population density likely contributed to this pattern as well39. Similarly, declines in traffic volume in states with larger outbreaks of SARS-CoV-2 might have been driven by increases in the perceived risk of contracting the virus21,23. Alternatively, traffic reductions in states with low disease burdens might reflect increased compliance with stay-at-home orders, and therefore less opportunity for disease spread40,41; essentially, reductions in traffic volume might be the cause of locally low disease burdens therein, rather than a consequence. Altogether, we posit that the observed heterogeneity in traffic volume between states is, at least in part, attributed to differences in the perceived risk posed by the SARS-CoV-2 virus.Regardless of the mechanisms underlying changes in traffic volume and WVCs, our observation that the annual number of WVCs was largely unchanged despite substantive declines in traffic volume has implications for mitigating WVCs going forward. Most directly, the lack of a directional change in WVCs suggests that road traffic levels in the United States are currently such that even large decreases in traffic volume would have minimal long-term effects on the absolute number of WVCs. As such, decreasing collisions by reducing traffic volume would require even larger and longer-lasting changes in traffic than those observed during the pandemic. Since such massive and sustained reductions in traffic are unlikely4,5,6, WVCs in the United States essentially represent a fixed cost as of now, both for human society and wildlife populations. As such, these transient decreases in traffic likely provided minimal reprieve to large mammals from collision-induced mortality, in contrast to speculation that changes in human mobility during the COVID-19 pandemic had substantial positive effects for wildlife populations by freeing wildlife from the pervasive direct and indirect effects of humans17,18,19,20,26,27,42.Indeed, it is possible that short-term decreases in traffic volume might ultimately be harmful to those wildlife species that increased their road use. Although the increases in collision rates we observed at the beginning of the pandemic were rapid and corresponded to nationwide declines in traffic volume (see also26,27), collision rates remained elevated even as traffic approached baseline levels in July (Fig. 2B). If wildlife responses to changes in traffic are asymmetric (i.e., increases in wildlife road use following declines in traffic occur more rapidly than decreases in wildlife road use in response to increased traffic), then short-term declines in traffic volume might lead to net increases in the number WVCs over longer timeframes, ultimately proving detrimental to certain wildlife populations1,3. Future work should evaluate the long-term effects of the pandemic on wildlife populations, specifically with regards to collision-induced mortality17,20,26,27,42.Although the COVID-19 pandemic provided an opportunity to examine the short-term effects of transient decreases in traffic volume on WVCs, the longer-term effects of expanding human populations, greater road densities, and altogether higher traffic volumes on WVCs are less clear. Similar to the increases in wildlife road use in response to decreases in traffic volume theorized here, steady increases in traffic might reduce wildlife road use long-term3,14,15,16; since road traffic is indeed increasing through time4,5,6, we might therefore see declines in WVCs as roads become more effective at repelling wildlife1,3,14. Although these reductions in vehicle-induced wildlife mortality are welcome, this would see roads increasingly serve as barriers to animal movement and gene flow43, further fragmenting already disconnected wildlife populations8. Thus, policy makers and urban planners should invest in infrastructure such as overpasses, underpasses, and fencing that enables wildlife to cross high-traffic roads safely or directs wildlife towards low-risk areas8,9. Even substantive short-term declines in road traffic are not sufficient to mitigate wildlife-vehicle conflict on their own. More

Gene Expression and Therapy Group, King’s College London, Faculty of Life Sciences & Medicine, Department of Medical and Molecular Genetics, Guy’s Hospital, London, UKRobin Mesnage & Michael N. AntoniouCentre for Ecology, Evolution & Behaviour, Department of Biological Sciences, School of Life Sciences and the Environment, Royal Holloway University of London, Egham, UKEdward A. Straw, Mark J. F. Brown & Ellouise LeadbeaterHeartland Health Research Alliance, Port Orchard, WA, USACharles BenbrookANSES, Sophia Antipolis Laboratory, Unit of Honey Bee Pathology, Sophia Antipolis, FranceMarie-Pierre ChauzatAgricultural Economics and Policy Group, ETH Zürich, Zürich, SwitzerlandRobert FingerSchool of Life Sciences, University of Sussex, Brighton, UKDave GoulsonBC3 — Basque Centre for Climate Change, Scientific Campus of the University of Basque Country, Leioa, SpainAna López-BallesterosCentre D’Études Biologiques de Chizé, UMR 7372, CNRS & La Rochelle Université, Villiers-en-bois, FranceNiklas MöhringInstitute of Bee Health, Vetsuisse Faculty, University of Bern, Bern, SwitzerlandPeter NeumannSchool of Agriculture and Food Science, University College Dublin, Dublin, IrelandEdward A. Straw, Dara Stanley & Linzi J. ThompsonDepartment of Botany, School of Natural Sciences, Trinity College Dublin, Dublin, IrelandJane C. Stout & Elena ZiogaDepartment of Ecoscience, Aarhus University, Aarhus, DenmarkChristopher J. ToppingSchool of Chemical Sciences, Glasnevin Campus, Dublin City University, Dublin, IrelandBlánaid WhiteInstitute of Zoology, University of Natural Resources and Life Sciences, Vienna, Vienna, AustriaJohann G. ZallerCorrespondence to
Robin Mesnage or Edward A. Straw. More

AffiliationsEarth, Atmospheric, and Planetary Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USAGabriela Serrato MarksSchool of Science, Technology, Accessibility, Mathematics and Public Health, Gallaudet University, Washington DC, USACaroline SolomonScience, Technology & Society Department, Rochester Institute of Technology, Rochester, NY, USAKaitlin Stack WhitneyAuthorsGabriela Serrato MarksCaroline SolomonKaitlin Stack WhitneyCorresponding authorsCorrespondence to
Gabriela Serrato Marks, Caroline Solomon or Kaitlin Stack Whitney. More

1.Smith, F. A. et al. Body size evolution across the Geozoic. Annu. Rev. Earth. Planet. Sci. 44, 523–553 (2016).ADS 
CAS 
Article 

Google Scholar 
2.Sallan, L. & Galimberti, A. K. Body-size reduction in vertebrates following the end-Devonian mass extinction. Science 350, 812–815 (2015).ADS 
CAS 
Article 

Google Scholar 
3.Heim, N. A., Knope, M. L., Schaal, E. K., Wang, S. C. & Payne, J. L. Cope’srule in the evolution of marine animals. Science 347, 867–870 (2015).ADS 
CAS 
Article 

Google Scholar 
4.Kammer, T. W. & Ausich, W. I. The, “Age of Crinoids”: A Mississippian biodiversity spike coincident with wide spread carbonate ramps. Palaios 21, 238–248 (2006).ADS 
Article 

Google Scholar 
5.Wright, D. F. Phenotypic innovation and adaptive constraints in the evolutionary radiation of Palaeozoic crinoids. Sci. Rep. 7, 13745 (2017).ADS 
Article 

Google Scholar 
6.Segessenman, D. C. & Kammer, T. W. Testing reduced evolutionary rates during the Late Palaeozoic Ice Age using the crinoid fossil record. Lethaia 51, 330–343 (2018).Article 

Google Scholar 
7.Cole, S. R. & Hopkins, M. J. Selectivity and the effect of mass extinctions on disparity and functional ecology. Sci. Adv. 7, eabf4072 (2021).ADS 
Article 

Google Scholar 
8.Baumiller, T. K. Echinoderms Through Time (Echinoderms Dijon) (eds. David, B., Guille, A., Féral, J. P. & Roux, M.) 193–198 (Balkema, 1994).9.Foote, M. Ecological controls on the evolutionary recovery of post-Paleozoic crinoids. Science 274, 1492–1495 (1996).ADS 
CAS 
Article 

Google Scholar 
10.Sallan, L. C., Kammer, T. W., Ausich, W. I. & Cook, L. A. Persistent predator-prey dynamics revealed by mass extinction. Proc. Natl. Acad. Sci. U.S.A. 108, 8335–8338 (2011).ADS 
CAS 
Article 

Google Scholar 
11.Ausich, W. I. & Kammer, T. W. Mississippian crinoid biodiversity, biogeography and macroevolution. Palaeontology 56, 727–740 (2013).Article 

Google Scholar 
12.Brom, K. R., Salamon, M. A. & Gorzelak, P. Body-size increase in crinoids following the end-Devonian mass extinction. Sci. Rep. 8, 9606 (2018).ADS 
Article 

Google Scholar 
13.Borths, M. R. & Ausich, W. I. Ordovician-Silurian Lilliput crinoids during the end-Ordovician biotic crisis. Swiss J. Palaeontol. 130, 7–18 (2011).Article 

Google Scholar 
14.Payne, J. L., Jost, A. B., Wang, S. C. & Skotheim, J. M. A shift in the long-term mode of foraminiferan size evolution caused by the end-Permian mass extinction. Evolution 67, 816–827 (2013).CAS 
Article 

Google Scholar 
15.Finnegan, S., Heim, N. A., Peters, S. E. & Fischer, W. W. Climate change and the selective signature of the Late Ordovician mass extinction. Proc. Natl. Acad. Sci. U.S.A. 109, 6829–6834 (2012).ADS 
CAS 
Article 

Google Scholar 
16.Peters, S. E. & Ausich, W. I. A sampling-adjusted macroevolutionary history for Ordovician-Early Silurian crinoids. Paleobiology 43, 104–116 (2008).Article 

Google Scholar 
17.Ausich, W. I. & Deline, B. Macroevolutionary transition in crinoids following the Late Ordovician extinction event (Ordovician–Early Silurian). Palaeogeogr. Palaeoclimatol. Palaeoecol. 361, 38–48 (2012).Article 

Google Scholar 
18.Huttenlocker, A. K. Body size reductions in non mammalian eutheriodont therapsids (synapsida) during the end-permian mass extinction. PLoS ONE 9, e87553 (2014).ADS 
Article 

Google Scholar 
19.Urbanek, A. Biotic crises in the history of upper Silurian graptoloids: A palaeobiological model. Hist. Biol. 7, 29–50 (1993).Article 

Google Scholar 
20.Alroy, J. et al. Phanerozoic trends in the global diversity of marine invertebrates. Science 321, 97–100 (2008).ADS 
CAS 
Article 

Google Scholar 
21.Stigall, A. L. Speciation collapse and invasive species dynamics during the Late Devonian “Mass Extinction”. GSA Today 22, 4–9 (2012).Article 

Google Scholar 
22.Hone, D. W. E., Keesey, T. M., Pisani, D. & Purvis, A. Macroevolutionary trends in the Dinosauria: Cope’srule. J. Evol. Biol. 18, 587–595 (2005).CAS 
Article 

Google Scholar 
23.Hunt, G. & Roy, K. Fittings and comparing models of phyletic evolution: Random walks and beyond. Paleobiology 32, 578–601 (2006).Article 

Google Scholar 
24.Hunt, G., Hopkins, M. J. & Lidgard, S. Simple versus complex models of trait evolution and stasis as are sponse to environmental change. Proc. Natl. Acad. Sci. U.S.A. 112, 4885–4890 (2015).ADS 
CAS 
Article 

Google Scholar 
25.Syverson, V. J. & Baumiller, T. K. Temporal trends of predation resistance in Paleozoic crinoid arm branching morphologies. Paleobiology 40, 417–427 (2014).Article 

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

Google Scholar 
27.Ebert, T. A. Negative growth and longevity in the purple sea urchin Strongylocentrotus purpuratus (Stimpson). Science 157, 557–558 (1967).ADS 
CAS 
Article 

Google Scholar 
28.Sato, K. N. et al. Response of sea urchin fitness traits to environmental gradients across the southern California oxygen minimum zone. Front. Mar. Sci. 5, 258 (2018).Article 

Google Scholar 
29.Brom, K. R. Body-size trends of cyrtocrinids (Crinoidea, Cyrtocrinida). Ann. Paleontol. 105, 109–118 (2019).ADS 
Article 

Google Scholar 
30.Webster, G. D. & Webster, D. W. Bibliography and Index of Paleozoic Crinoids, Coronates, and Hemistreptocrinoids. 1758–2012. http://crinoids.azurewebsites.net (2014)31.Hunt, G., & Paleo, T.S. Analyze Paleontological Time Series. R Package Version 0.5.2. http://cran.r-project.org/web/packages/paleoTS/ (2019).32.RStudio Team. RStudio: Integrated Development for R. (RStudio, PBC, 2020). http://www.rstudio.com/.33.Bergman, N. M., Lenton, T. M. & Watson, A. J. COPSE: A new model of biogeochemical cycling over Phanerozoic time. Am. J. Sci. 304, 397–437 (2004).ADS 
CAS 
Article 

Google Scholar 
34.Royer, D. L., Berner, R. A., Montañez, I. P., Tabor, N. J. & Beerling, D. J. CO2 as a primary driver of Phanerozoic climate. GSA Today 14, 4–10 (2004).Article 

Google Scholar 
35.Veizer, J. & Prokoph, A. Temperatures and oxygen isotopic composition of Phanerozoic oceans. Earth. Sci. Rev. 146, 92–104 (2015).ADS 
CAS 
Article 

Google Scholar 
36.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. Linear and Nonlinear MixedEffectsModels. R Package Version 3.1-143. http://cran.r-project.org/package=nlme (2019).37.Sookias, R. B., Benson, R. B. & Butler, R. J. Biology, not environment, drives major patterns in maximum tetrapod body size through time. Biol. Lett. 8, 674–677 (2012).Article 

Google Scholar 
38.Rego, B. L., Wang, S. C., Altiner, D. & Payne, J. L. Within- and among-genus components of size evolution during mass extinction, recovery, and background intervals: A case study of Late Permian through Late Triassic foraminifera. Paleobiology 38, 627–643 (2012).Article 

Google Scholar 
39.Zhang, Z., Augustin, M. & Payne, J. L. Phanerozoic trends in brachiopod body-size from synoptic data. Paleobiology 41, 491–501 (2015).Article 

Google Scholar  More

1.Zhang, X. et al. Plant defense resistance in natural enemies of a specialist insect herbivore. Proc. Natl. Acad. Sci. U. S. A. 116, 23174–23181. https://doi.org/10.1073/pnas.1912599116 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
2.Wittstock, J. & Gershenzon, U. Constitutive plant toxins and their role in defense against herbivores and pathogens. Curr. Opin. Plant Biol. 5, 300–307. https://doi.org/10.1016/s1369-5266(02)00264-9 (2002).CAS 
Article 
PubMed 

Google Scholar 
3.Stahl, E., Hilfiker, O. & Reymond, P. Plant-arthropod interactions: Who is the winner?. Plant J. 93, 703–728. https://doi.org/10.1111/tpj.13773 (2018).CAS 
Article 
PubMed 

Google Scholar 
4.de Bruijn, W. J. C., Gruppen, H. & Vincken, J. P. Structure and biosynthesis of benzoxazinoids: Plant defence metabolites with potential as antimicrobial scaffolds. Phytochemistry 155, 233–243. https://doi.org/10.1016/j.phytochem.2018.07.005 (2018).CAS 
Article 
PubMed 

Google Scholar 
5.Arbona, V. & Gomez-Cadenas, A. Metabolomics of disease resistance in crops. Curr. Issues Mol. Biol. 19, 13–30 (2016).PubMed 

Google Scholar 
6.Ben-Abu, Y., Beiles, A., Flom, D. & Nevo, E. Adaptive evolution of benzoxazinoids in wild emmer wheat, Triticum dicoccoides, at “Evolution Canyon”, Mount Carmel, Israel. PLoS ONE 13(2), e0190424. https://doi.org/10.1371/journal.pone.0190424 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
7.Frey, M., Schullehner, K., Dick, R., Fiesselmann, A. & Gierl, A. Benzoxazinoid biosynthesis, a model for evolution of secondary metabolic pathways in plants. Phytochemistry 70(15–16), 1645–1651. https://doi.org/10.1016/j.phytochem.2009.05.012 (2009).CAS 
Article 
PubMed 

Google Scholar 
8.Zdero, C., Bohlmann, F. & Niemeyer, H. M. Isocedrene and guaiane derivatives from Pleocarphus revolutus. J. Nat. Prod. 51, 509–512. https://doi.org/10.1021/np50057a009 (1988).CAS 
Article 
PubMed 

Google Scholar 
9.Carlsen, S. C. et al. Allelochemicals in rye (Secale cereale L.): Cultivar and tissue differences in the production of benzoxazinoids and phenolic acids. Nat. Prod. Commun. 4, 199–208 (2009).CAS 
PubMed 

Google Scholar 
10.Martos, A., Givovich, A. & Niemeyer, H. M. Effect of DIMBOA, an aphid resistance factor in wheat, on the aphid predator Eriopis connexa Germar (Coleoptera: Coccinellidae). J. Chem. Ecol. 18, 469–479. https://doi.org/10.1007/BF00994245 (1992).CAS 
Article 
PubMed 

Google Scholar 
11.Perez, F. J. Allelopathic effect of hydroxamic acids from cereals on Avena sativa and A. fatua Francisco. Phytochemistry 29, 773–776. https://doi.org/10.1016/0031-9422(90)80016-A (1990).CAS 
Article 

Google Scholar 
12.Dutartre, L., Hilliou, F. & Feyereisen, R. Phylogenomics of the benzoxazinoid biosynthetic pathway of Poaceae: Gene duplications and origin of the Bx cluste. BMC Evol. Biol. 12, 64. https://doi.org/10.1186/1471-2148-12-64 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
13.Meredith, A., Wilkes, D. R. M. & Copeland, L. Hydroxamic acids in cereal roots inhibit the growth of take-all. Soil Biol. Biochem. 31, 1831–1836. https://doi.org/10.1016/S0038-0717(99)00104-2 (1999).Article 

Google Scholar 
14.Macias, F. A., Valerin, M. D., Oliveros-Bastidas, A., Castellano, D. & Simonet, A. M. Structure-activity relationships (SAR) studies of benzoxazinones, their degradation products and analogues. phytotoxicity on standard target species (STS). J. Agric. Food Chem. 53, 538–548. https://doi.org/10.1021/jf0484071 (2005).CAS 
Article 
PubMed 

Google Scholar 
15.Nakagawa, E., Amano, T., Hirai, N. & Iwamura, H. Partial purification and characterisation of a 2,4,5-trichlorophenol detoxifying O-glucosyltransferase from wheat. Phytochemistry 38, 1349–1354. https://doi.org/10.1016/s0031-9422(03)00191-2 (2003).Article 

Google Scholar 
16.Levy, A. A. & Feldman, M. Intra-population and inter-population variations in grain protein percentage in wild tetraploid wheat, Triticum-turgidum var dicoccoides. Euphytica 42(3), 251–258. https://doi.org/10.1007/BF00034461 (1989).Article 

Google Scholar 
17.Święcicka, M. et al. Changes in benzoxazinoid contents and the expression of the associated genes in rye (Secale cereale L.) due to brown rust and the inoculation procedure. PLoS ONE https://doi.org/10.1371/journal.pone.0233807 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
18.Levy, A. A., Galili, G. & Feldman, M. Polymorphism and genetic-control of high molecular-weight glutenin subunits in wild tetraploid wheat Triticum-turgidum var dicoccoides. Heredity 61, 63–72. https://doi.org/10.1007/BF00034461 (1988).CAS 
Article 

Google Scholar 
19.Abu-Zaitoun, S. et al. Unlocking the genetic diversity within a Middle-East panel of durum wheat landraces for adaptation to semi-arid climate. Agronomy 8, 233–245 (2018).Article 

Google Scholar 
20.Avivi, L. High grain protein content in wild wheat. Can J. Genet. Cytol. 19, 569–570. https://doi.org/10.1139/g77-062 (1977).Article 

Google Scholar 
21.Ozkan, H., Levy, A. A. & Feldman, M. Allopolyploidy-induced rapid genome evolution in the wheat (Aegilops-Triticum) group. Plant Cell 8, 1735–1747. https://doi.org/10.1105/tpc.010082 (2001).Article 

Google Scholar 
22.Yang, M. et al. Plant-plant-microbe mechanisms involved in soil-borne disease suppression on a maize and pepper intercropping system. PLoS ONE https://doi.org/10.1371/journal.pone.0115052 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
23.Hanhineva, K. et al. Non-targeted analysis of spatial metabolite composition in strawberry (Fragariaxananassa) flowers. Phytochemistry 69(13), 2463–2481. https://doi.org/10.1016/j.phytochem.2008.07.009 (2008).CAS 
Article 
PubMed 

Google Scholar 
24.Haas, M., Schreiber, M. & Mascher, M. Domestication and crop evolution of wheat and barley: Genes, genomics, and future directions. J. Integr. Plant Biol. 61(3), 204–225. https://doi.org/10.1111/jipb.12737 (2019).Article 
PubMed 

Google Scholar 
25.Beleggia, R. et al. Evolutionary metabolomics reveals domestication-associated changes in tetraploid wheat kernels. Mol. Biol. Evol. 33(7), 1740–1753. https://doi.org/10.1093/molbev/msw050 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
26.Ugine, T. A., Krasnoff, S. B., Grebenok, R. J., Behmer, S. T. & Losey, E. Prey nutrient content creates omnivores out of predators. Ecol. Lett. 22, 275–283. https://doi.org/10.1111/ele.13186 (2019).Article 
PubMed 

Google Scholar 
27.Coll, M. & Guershon, M. Omnivory in terrestrial arthropods: Mixing plant and prey diets. Annu. Rev. Entomol. 47, 267–297. https://doi.org/10.1146/annurev.ento.47.091201.145209 (2002).CAS 
Article 
PubMed 

Google Scholar 
28.Calvert, W. H., Hedrick, L. E. & Brower, L. P. Mortality of the monarch butterfly (Danaus plexippus L.): Avian predation at five overwintering sites in Mexico. Science 204, 847–851. https://doi.org/10.1126/science.204.4395.847 (1979).ADS 
CAS 
Article 
PubMed 

Google Scholar 
29.Skelhorn, J. & Rowe, C. Avian predators taste-reject aposematic prey on the basis of their chemical defence. Biol. Lett. 2, 348–350. https://doi.org/10.1098/rsbl.2006.0483 (2006).Article 
PubMed 
PubMed Central 

Google Scholar 
30.Kumar, P., Pandit, S. S., Steppuhn, A. & Baldwin, L. T. Natural history-driven, plant-mediated RNAi-based study reveals CYP6B46’s role in a nicotine-mediated antipredator herbivore defense. Proc. Natl. Acad. Sci. U.S.A. 111, 1245–1252. https://doi.org/10.1073/pnas.1314848111 (2014).ADS 
CAS 
Article 
PubMed 

Google Scholar 
31.Matthews, S. B. et al. Metabolite profiling of a diverse collection of wheat lines using ultraperformance liquid chromatography coupled with time-of-flight mass spectrometry. PLoS ONE 7(8), e44179. https://doi.org/10.1371/journal.pone.0044179 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
32.Parween, T., Jan, S., Mahmooduzzafar, S., Fatma, T. & Siddiqui, Z. H. Selective effect of pesticides on plant. Crit. Rev. Food Sci. Nutr. 56(1), 160–179. https://doi.org/10.1080/10408398.2013.787969 (2016).CAS 
Article 
PubMed 

Google Scholar 
33.Masisi, K., Beta, T. & Moghadasian, M. H. Antioxidant properties of diverse cereal grains: A review on in vitro and in vivo studies. Food Chem. 96, 90–97. https://doi.org/10.1016/j.foodchem.2015.09.021 (2016).CAS 
Article 

Google Scholar 
34.Hostetler, G. L., Ralston, R. A. & Schwartz, S. J. Flavones: Food sources, bioavailability, metabolism, and bioactivity. Adv. Nutr. 8(3), 423–435. https://doi.org/10.3945/an.116.012948 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
35.Perez-Vizcaino, F. & Fraga, C. G. Research trends in flavonoids and health. Arch. Biochem. Biophys. 646, 107–112. https://doi.org/10.1016/j.abb.2018.03.022 (2018).CAS 
Article 
PubMed 

Google Scholar 
36.Nevo, E. “Evolution Canyon,” a potential microscale monitor of global warming across life. Proc. Natl. Acad. Sci. U. S. A. 109(8), 2960–2965. https://doi.org/10.1073/pnas.1120633109 (2012).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
37.Nevo, E. et al. Evolution of wild cereals during 28 years of global warming in Israel. Proc. Natl. Acad. Sci. U. S. A. 109(9), 3412–3415. https://doi.org/10.1073/pnas.1121411109 (2012).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
38.Hebelstrup, K. H. Differences in nutritional quality between wild and domesticated forms of barley and emmer wheat. Plant Sci. 256, 1–4. https://doi.org/10.1016/j.plantsci.2016.12.006 (2017).CAS 
Article 
PubMed 

Google Scholar 
39.Avni, R. et al. Wild emmer genome architecture and diversity elucidate wheat evolution and domestication. Science 357(6346), 93–97. https://doi.org/10.1126/science.aan0032 (2017).ADS 
CAS 
Article 
PubMed 

Google Scholar 
40.Salamini, F., Ozkan, H., Brandolini, A., Schäfer-Pregl, R. & Martin, W. Genetics and geography of wild cereal domestication in the near east. Nat. Rev. Genet. 3(6), 429–441. https://doi.org/10.1038/nrg817 (2002).CAS 
Article 
PubMed 

Google Scholar 
41.Zörb, C., Langenkämper, G., Betsche, T., Niehaus, K. & Barsch, A. Metabolite profiling of wheat grains (Triticum aestivum L.) from organic and conventional agriculture. J. Agric. Food Chem. 54(21), 8301–8306. https://doi.org/10.1016/j.phytochem.2007.06.020 (2006).CAS 
Article 
PubMed 

Google Scholar 
42.Zörb, C., Niehaus, K., Barsch, A., Betsche, T. & Langenkämper, G. Levels of compounds and metabolites in wheat ears and grains in organic and conventional agriculture. J. Agric. Food Chem. 57(20), 9555–9562. https://doi.org/10.1021/jf9019739 (2009).CAS 
Article 
PubMed 

Google Scholar 
43.Zörb, C., Betsche, T. & Langenkämper, G. Search for diagnostic proteins to prove authenticity of organic wheat grains (Triticum aestivum L.). J. Agric. Food Chem. 57(7), 2932–2937. https://doi.org/10.1021/jf802923r (2009).CAS 
Article 
PubMed 

Google Scholar 
44.Hanhineva, K. et al. Qualitative characterization of benzoxazinoid derivatives in whole grain rye and wheat by LC-MS metabolite profiling. J. Agric. Food Chem. 59(3), 921–927. https://doi.org/10.1021/jf103612u (2011).CAS 
Article 
PubMed 

Google Scholar 
45.Brodsky, L., Moussaieff, A., Shahaf, N., Aharoni, A. & Rogachev, I. Evaluation of peak picking quality in LC–MS metabolomics data. Anal. Chem. 82(22), 9177–9187. https://doi.org/10.1021/ac101216e (2010).CAS 
Article 
PubMed 

Google Scholar 
46.Ben-Abu, Y. et al. Durum wheat evolution—A genomic analysis. Proc. Int. Symp. Genet. Breed. Durum Wheat 110, 29–44 (2014).
Google Scholar 
47.Iannucci, A., Fragasso, M., Beleggia, R., Nigro, F. & Papa, R. Evolution of the crop rhizosphere: Impact of domestication on root exudates in tetraploid wheat (Triticum turgidum L.). Front. Plant Sci. 8, 2124. https://doi.org/10.3389/fpls.2017.02124 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
48.Okada, K., Abe, H. & Arimura, G. Jasmonates induce both defense responses and communication in monocotyledonous and dicotyledonous plants. Plant Cell Physiol. 56(1), 16–27. https://doi.org/10.1093/pcp/pcu158 (2015).CAS 
Article 
PubMed 

Google Scholar 
49.Givovich, A., Morse, S., Cerda, H., Niemeyer, H. M. & Wratten, S. D. Hydroxamic acid glucosides in honeydew of aphids feeding on wheat. J. Chem. Ecol. 18, 841–846. https://doi.org/10.1007/BF00988324 (1992).CAS 
Article 
PubMed 

Google Scholar 
50.Shavit, R., Batyrshina, Z. S., Dotan, N. & Tzin, V. Cereal aphids differently affect benzoxazinoid levels in durum wheat. PLoS ONE https://doi.org/10.1371/journal.pone.0208103 (2018).Article 
PubMed 
PubMed Central 

Google Scholar  More