Ecology

1.Zárate, M. A. & Tripaldi, A. The aeolian system of central Argentina. Aeolian Res. 3, 401–417 (2012).ADS 
Article 

Google Scholar 
2.Chapin III, F. S. Functional role of growth forms in ecosystem and global processes. In Scaling Physiology Process (ed. Ehleringer J. R. & Field C. B.) 287–312. (Elsevier Inc., 1993). https://doi.org/10.1016/C2009-0-03319-4.
Google Scholar 
3.Jump, A. S., Mátyás, C. & Peñuelas, J. The altitude-for-latitude disparity in the rangeretractions of woody species. Trends Ecol. Evol. (Amst.) 24, 694–701. https://doi.org/10.1016/j.tree.2009.06.007 (2009).Article 

Google Scholar 
4.Donohue, K., Rubio de Casas, R., Burghardt, L., Kovach, K. & Willis, C. G. Germination, postgermination adaptation, and species ecological ranges. Annu. Rev. Ecol. Evol. Syst. 41, 293–319 (2010).Article 

Google Scholar 
5.O’Connor, T. Local extinction in perennial grasslands: A life-history approach. Am. Nat. 137, 753–773 (1991).Article 

Google Scholar 
6.Rotundo, J. L., Aguiar, M. R. & Benech-Arnold, R. Understanding erratic seedling emergence in perennial grasses using physiological models and field experimentation. Plant Ecol. 216, 143–156 (2015).Article 

Google Scholar 
7.Duncan, C., Schultz, N. L., Good, M. K., Lewandrowski, W. & Cook, S. The risk-takers and-avoiders: Germination sensitivity to water stress in an arid zone with unpredictable rainfall. AoB Plants. 11(6), plz066 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
8.Pendleton, B. & Meyer, S. Habitat-correlated variation in blackbrush (Coleogyne ramosissima: Rosaceae) seed germination response. J. Arid Environ. 59, 229–243 (2004).ADS 
Article 

Google Scholar 
9.Chamorro, D. et al. Germination sensitivity to water stress in four shrubby species across the Mediterranean Basin. Plant Biol. 19(1), 23–31 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
10.Bewley, J. D. & Black, M. Seeds. In Seeds. (ed. Bewley, J. D. & Black, M.) 1–33. https://doi.org/10.1007/978-1-4899-1002-8. eBook ISBN978-1-4899-1002-8 (Springer, Boston, MA, 1994).
Google Scholar 
11.Bradford, K. J. Water relations in seed germination. In Seed Development and Germination (eds Kigel, J. & Galili, G.) 351–396 (Marcel Dekker Inc, 1995).
Google Scholar 
12.Batlla, D. & Benech-Arnold, R. L. The role of fluctuations in soil water content on the regulation of dormancy changes in buried seeds of Polygonum aviculare L. Seed Sci. Res. 16(1), 47–59 (2006).Article 
CAS 

Google Scholar 
13.Luna, B. & Chamorro, D. Germination sensitivity to water stress of eight Cistaceae species from the Western Mediterranean. Seed Sci. Res. 26(2), 101 (2016).Article 

Google Scholar 
14.Bradford, K. J. Threshold models applied to seed germination ecology. New Phytol. 165, 338–341 (2005).PubMed 
Article 
PubMed Central 

Google Scholar 
15.Garcia-Huidobro, J., Monteith, J. & Squire, G. Time, temperature and germination of pearl millet (Pennisetum typhoides S. & H.) I. Constant temperature. J. Exp. Bot. 33, 288–296 (1982).Article 

Google Scholar 
16.Bradford, K. J. A water relations analysis of seed germination rates. Plant Physiol. 94, 840–849 (1990).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
17.Bradford, K. J. & Still, D. W. Applications of hydrotime analysis in seed testing. Seed Technol. 26(1), 75–85 (2004).
Google Scholar 
18.Gummerson, R. J. The effect of constant temperature and osmotic potentials on the germination of sugar beet. J. Exp. Bot. 37, 729–741 (1986).Article 

Google Scholar 
19.Bradford, K. J. Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci. 50, 248–260 (2002).Article 
CAS 

Google Scholar 
20.Batlla, D. & Agostinelli, A. M. Thermal regulation of secondary dormancy induction in Polygonum aviculare seeds: A quantitative analysis using the hydrotime model. Seed Sci. Res. 27(3), 231–242 (2017).Article 
CAS 

Google Scholar 
21.Farahinia, P., Sadat-Noori, S. A., Mortazavian, M. M., Soltani, E. & Foghi, B. Hydrotime model analysis of Trachyspermum ammi (L.) Sprague seed germination. J. Appl. Res. Med. Aroma. 5, 88–91 (2017).
Google Scholar 
22.Wang, R., Bai, Y. & Tanino, K. Germination of winterfat (Eurotia lanata (Pursh) Moq.) seeds at reduced water potentials: Testing assumptions of hydrothermal time model. Environ. Exp. Bot. 53(1), 49–683 (2005).Article 

Google Scholar 
23.Alvarado, V. & Bradford, K. J. A hydrothermal time model explains the cardinal temperatures for seed germination. Plant Cell Environ. 25(8), 1061–1069 (2002).Article 

Google Scholar 
24.Bakhshandeh, E. & Gholamhossieni, M. Modelling the effects of water stress and temperature on seed germination of radish and cantaloupe. J. Plant Growth Regul. 38(4), 1402–1411 (2019).Article 
CAS 

Google Scholar 
25.Bakhshandeh, E. & Jamali, M. Population-based threshold models: A reliable tool for describing aged seeds response of rapeseed under salinity and water stress. Environ. Exp. Bot. 176, 104077 (2020).Article 
CAS 

Google Scholar 
26.Leva, P. E. Variación regional de las características agroecológicas y genéticas de Bromus pictus y Poa ligularis en estepas patagónicas (Universidad Nacional de Buenos Aires, 2010).
Google Scholar 
27.Palazzesi, L., Barreda, V. & Prieto, A. Análisis evolutivo de la vegetación cenozoica en las provincias de Chubut y Santa Cruz (Argentina) con especial atención en las comunidades herbáceo-arbustivas. Revista del Museo Argentino de Ciencias Naturales nueva serie 5(2), 151–161 (2014).
Google Scholar 
28.León, R. J., Bran, D., Collantes, M., Paruelo, J. M. & Soriano, A. Grandes unidades de vegetación de la Patagonia extra andina. Ecol. Austral. 8, 125–144 (1998).
Google Scholar 
29.Villalba, R. et al. Large-scale temperature changes across the southern Andes: 20th-century variations in the context of the past 400 years. Clim. Change. 59(1), 177–232 (2003).Article 

Google Scholar 
30.Godagnone, R., Bran, D. Inventario integrado de los recursos de la Provincia de Río Negro. (INTA, Argentina, Río Negro, 2009).
Google Scholar 
31.Soriano, A. La vegetación del Chubut. Revista Argentina de Agronomía. 17, 30–66 (1950).
Google Scholar 
32.Bertiller, M. B. & Coronato, F. Seed bank patterns of Festuca pallescens in semiarid Patagonia (Argentina): A possible limit to bunch reestablishment. Biodivers. Conserv. 3(1), 57–67 (1994).Article 

Google Scholar 
33.Defossé, G., Bertiller, M. & Robberecht, R. Germination characteristics of Festuca pallescens, a Patagonian bunchgrass with reclamation potential. Seed Sci. Technol. (Switzerland). 23(3), 715–723 (1995).
Google Scholar 
34.Bertiller, M. B., Elissalde, N. O., Rostagno, C. M. & Defossé, G. E. Environmental patterns and plant distribution along a precipitation gradient in western Patagonia. J. Arid Environ. 29, 85–97 (1993).Article 

Google Scholar 
35.Bran, D., Ayesa, J., López, C. Regiones ecológicas de Río Negro. Comunicación Técnica No 59. (INTA, EEA Bariloche, 2000).
Google Scholar 
36.Oliva, G. et al. Monitoring drylands: The MARAS system. J. Arid Environ. 161, 55–63 (2019).ADS 
Article 

Google Scholar 
37.López, A. S., Marchelli, P., Batlla, D., López, D. R. & Arana, M. V. Seed responses to temperature indicate different germination strategies among Festuca pallescens populations from semi-arid environments in North Patagonia. Agric. For. Meteorol. 272, 81–90 (2019).ADS 
Article 

Google Scholar 
38.Gaitán, J. J. et al. Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes. Ecol. Indic. 34, 181–191 (2013).Article 

Google Scholar 
39.Moore, R. P. Tetrazolium tests for diagnosing causes for seed weaknesses and for predicting and understanding performance. In Proceedings of the Association of Official Seed Analysts. Association of Official Seed Analysts, vol. 56, 70–73. https://www.jstor.org/stable/23432057 (1966).40.Michel, B. E. Evaluation of the water potentials of solutions of polyethylene glycol 8000 both in the absence and presence of other solutes. Plant Physiol. 72(1), 66–70 (1983).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
41.Di Rienzo, J. A., et al. InfoStat versión 2020 & Centro de Transferencia InfoStat. FCA, Universidad Nacional de Córdoba, Argentina. http://www.infostat.com.ar.42.Volis, S., Mendlinger, S. & Ward, D. Adaptive traits of wild barley plants of Mediterranean and desert origin. Oecologia 133(2), 131–138 (2002).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
43.Krichen, K., Mariem, H. B. & Chaieb, M. Ecophysiological requirements on seed germination of a Mediterranean perennial grass (Stipa tenacissima L.) under controlled temperatures and water stress. S. Afr. J. Bot. 94, 210–217 (2014).Article 

Google Scholar 
44.Petrů, M. & Tielbörger, K. Germination behaviour of annual plants under changing climatic conditions: Separating local and regional environmental effects. Oecologia 155(4), 717–728 (2008).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
45.Cavallaro, V. et al. Evaluation of variability to drought and saline stress through the germination of different ecotypes of carob (Ceratonia siliqua L.) using a hydrotime model. Ecol. Eng. 95, 557–566 (2016).Article 

Google Scholar 
46.Tognetti, P. M., Mazia, N. & Ibáñez, G. Seed local adaptation and seedling plasticity account for Gleditsia triacanthos tree invasion across biomes. Ann. Bot. 124(2), 307–318 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
47.Allen, P. S., Meyer, S. E. & Khan, M. A. Hydrothermal time as a tool in comparative germination studies. In Seed biology: advances and applications. Proceedings of the Sixth International Workshop on Seeds, Merida, Mexico, 1999. (ed. Black, M., Bradford, J. K. & Vazquez-Ramos, J.) 401–410. https://doi.org/10.1079/9780851994048.0401 (2000).48.Hu, X. W., Fan, Y., Baskin, C. C., Baskin, J. M. & Wang, Y. R. Comparison of the effects of temperature and water potential on seed germination of Fabaceae species from desert and subalpine grassland. Am. J. Bot. 102(5), 649–660 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
49.Ramírez-Tobías, H., Peña-Valdivia, C., Trejo, C., Aguirre, J. & Vaquera, H. Seed germination of Agave species as influenced by substrate water potential. Biol. Res. 47, 1–9 (2014).Article 
CAS 

Google Scholar 
50.Couso, L. Mecanismos de tolerancia a sequía y sus efectos sobre la habilidad competitiva de pastos de la estepa patagónica (Universidad Nacional de Buenos Aires, 2011).
Google Scholar 
51.López, D. R. Una aproximación Estructural-Funcional 1 del Modelo de Estados y Transiciones para el estudio de la dinámica de la vegetación en estepas de Patagonia norte (Universidad Nacional del Comahue, San Carlos de Bariloche, 2011).
Google Scholar 
52.Leva, P. E., Aguiar, M. R. & Premoli, A. C. Latitudinal variation of genecological traits in native grasses of Patagonian rangelands. Aust. J. Bot. 61(6), 475–485 (2013).Article 

Google Scholar 
53.López, D. R. & Cavallero, L. The role of nurse functional types in seedling recruitment dynamics of alternative states in rangelands. Acta Oecol. 79, 70–80 (2017).ADS 
Article 

Google Scholar 
54.Coronato, F. R. & Bertiller, M. B. Precipitation and landscape related effects on soil moisture in semi-arid rangelands of Patagonia. J. Arid Environ. 34(1), 1–9 (1996).ADS 
Article 

Google Scholar 
55.Coronato, F. R. & Bertiller, B. Climatic controls of soil moisture dynamics in an arid steppe of northern Patagonia, Argentina. Arid Land Res. Manag. 11, 277–288 (1997).
Google Scholar 
56.Heber, U., Santarius, K. A. Water stress during freezing. In Water and Plant Life. Ecological Studies (Analysis and Synthesis), vol. 19 (eds. Lange, O. L. et al.) 253–257. https://doi.org/10.1007/978-3-642-66429-8_16 (Springer, Berlin, Heidelberg, 1976).57.López, A. S., López, D. R., Caballe, G., Siffredi, G. L. & Marchelli, P. Local adaptation along a sharp rainfall gradient occurs in a native Patagonian grass, Festuca pallescens, regardless of extensive gene flow. Environ. Exp. Bot. 171, 103933 (2020).Article 
CAS 

Google Scholar 
58.López, A. S., Azpilicueta, M. M., López, D. R., Siffredi, G. L. & Marchelli, P. Phylogenetic relationships and intraspecific diversity of a North Patagonian Fescue: Evidence of differentiation and interspecific introgression at peripheral populations. Folia Geobot. 53, 115–131. https://doi.org/10.1007/s12224-017-9304-1 (2018).Article 

Google Scholar 
59.Smith, S., Riley, E., Tiss, J. & Fendenhein, D. Geographical variation in predictive seedling emergence in a perennial desert grass. J. Ecol. 88, 139–149 (2000).Article 

Google Scholar 
60.Bohara, H. et al. Influence of poultry litter and biochar on soil water dynamics and nutrient leaching from a very fine sandy loam soil. Soil Tillage Res. 189, 44–51 (2019).Article 

Google Scholar  More

1.Lane, R.S. Ekosystemy leśne Kalifornii jako obszary podwyższonego ryzyka zakażenia krętkami boreliozy z Lyme in Vademecum wybranych chorób odzwierzęcych w środowisku leśnym (ed. Skorupski, M., Wierzbicka, A.) 9–22 (Katedra Łowiectwa i Ochrony Lasu. Poznań, Poland, 2012).2.Siuda, K. Kleszcze Polski (Acari: Ixodida). cz. II Systematyka i rozmieszczenie. (Wydawnictwo Naukowe PWN, Warszawa. Poznań, Poland, 1993).3.Piesman, J. & Gern, L. Lyme borreliosis in Europe and North America. Parasitology 129, 191–220. https://doi.org/10.1017/S0031182003004694 (2004).Article 

Google Scholar 
4.ECDC. European Centre for Disease Prevention and Control: Second Expert Consultation on Tick-borne Diseases with Emphasis on Lyme Borreliosis and Tick-borne Encephalitis. http://www.ecdc.europa.eu/en/publications/publications/tick-borne-diseases-meeting-report.pdf (2012).5.Welc-Falęciak, R. et al. Co-infection and genetic diversity of tick-borne pathogens in roe deer from Poland. Vector-Borne Zoonotic Dis 13(5), 277–288. https://doi.org/10.1371/journal.pone.000433610.1089/vbz.2012.1136 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
6.Welc-Falęciak, R. et al. Rickettsiaceae and Anaplasmataceae infections in Ixodes ricinus ticks from urban and natural forested areas of Poland. Parasites Vectors 7, 121. https://doi.org/10.1371/journal.pone.000433610.1186/1756-3305-7-121 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
7.ECDC. European Centre for Disease Prevention and Control: Lyme Borreliosisin Europe. http://www.ecdc.europa.eu/en/healthtopics/vectors/world-health-day-2014/Documents/factsheet-lyme-borreliosis.pdf (2014).8.Rizzoli, A. et al. Lyme borreliosis in Europe. Euro Surveill. 16(27), 19906. http://www.eurosurveillance.org/ViewArticle.aspx? (2011).9.Burbaite, L. & Csányi, S. Roe deer population and harvest changes in Europe. Est. J. Ecol. 58(3), 169–180. https://doi.org/10.3176/eco.2009.3.02 (2009).Article 

Google Scholar 
10.Rizzoli, A., Hauffe, H. C., Tagliapietra, V., Netelerm, M. & Rosà, R. Forest structure and roe deer abundance predict tick-borne encephalitis risk in Italy. PLoS ONE 4(2), e4336. https://doi.org/10.1371/journal.pone.0004336 (2009).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
11.Jaenson, T. G. T., Jaenson, D. G. E., Eisen, L., Petersson, E. & Lindgren, E. Changes in the geographical distribution and abundance of the tick Ixodes ricinus during the past 30 years in Sweden. Parasites Vectors 5, 8 (2012).Article 

Google Scholar 
12.Andersen, N. S. et al. Reduction in human Lyme neuroborreliosis associated with a major epidemic among roe deer. Ticks Tick-borne Dis. 9, 379–381. https://doi.org/10.1016/j.ttbdis.2017.12.002 (2018).Article 
PubMed 

Google Scholar 
13.Carpi, G., Cagnacci, F., Neteler, M. & Rizzoli, A. Tick infestation on roe deer in relation to geographic and remotely sensed climatic variables in a tick-borne encephalitis endemic area. Epidemiol. Infect. 136, 1416–1424. https://doi.org/10.1017/S0950268807000039 (2008).CAS 
Article 
PubMed 

Google Scholar 
14.Zejda, J. & Bauerova, Z. Home range of field roe deer. Acta Sc. Nat. 19, 1–43 (1985).
Google Scholar 
15.Cibien, C., Bideau, E., Boisaubert, B. & Maublanc, M. L. Influence of habitat characteristic on winter social organization in field roe deer. Acta Theriol. 34, 219–226 (1989).Article 

Google Scholar 
16.Pielowski, Z. Sarna. (Wydawnictwo Świat, Warszawa, Poland, 1999).17.Siuda, K. Kleszcze (Acari: Ixodida) Polski. Część I. Zagadnienia ogólne. (Wydawnictwo Naukowe PWN, Warszawa, Poland, 1991).18.Kamieniarz, R. Struktura krajobrazu rolniczego a funkcjonowanie populacji sarny polnej. Rozprawy naukowe Uniwersytetu Przyrodniczego w Poznaniu, 463. (Poznań, Poland, 2013).19.Kadulski, S. Występowanie stawonogów pasożytniczych na łownych Lagomorpha i Artiodactyla Polski—próba syntezy. Zeszyty Naukowe Uniwersytet Gdański. Rozprawy i monografie. (Wydawnictwo Uniwersytet Gdański. Gdańsk, Poland, 1989).20.Sugar, L. Health status and parasitic infections in three Hungarian populations of roe deer Capreolus capreolus. In Global trends in Wildlife Management. 18th IUGB Congress (ed. Bobek, B., Perzanowski, K. and Regelin, W.L.) 269–271. (Jagiellonian University Kraków, Poland, Wydawnictwo Świat Press, Kraków-Warszawa, Poland, 1991).21.Jędrysiak, D. Stawonogi pasożytnicze sarny europejskiej Capreolus capreolus (L.) z terenów Pojezierzy Południowobałtyckich. PhD thesis, (Uniwersytet Gdański, Gdańsk, Poland, 2006).22.Kiffner, C., Lӧdige, C., Alings, M., Vor, T. & Rühe, F. Abundance estimation of Ixodes ricinus ticks (Acari: Ixodidae) on roe deer (Capreolus capreolus). Exp. Appl. Acarol. 52, 73–84. https://doi.org/10.1007/s10493-010-9341-4 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
23.Kiffner, C., Lӧdige, C., Alings, M., Vor, T. & Rühe, F. Attachment site selection of ticks on roe deer. Exp. Appl. Acarol. 53, 79–84. https://doi.org/10.1007/s10493-010-9378-4 (2011).CAS 
Article 
PubMed 

Google Scholar 
24.Tälleklint, L. & Jaenson, T. G. T. Infestation of mammals by Ixodes ricinus ticks (Acari: Ixodidae) in south-central Sweden. Exp. Appl. Acarol. 21, 755–771. https://doi.org/10.1371/journal.pone.000433610.1023/A%3A1018473122070 (1997).Article 
PubMed 

Google Scholar 
25.Vázquez, L. et al. Tick infestation (Acari: Ixodidae) in roe deer (Capreolus capreolus) from northwestern Spain: population dynamics and risk stratification. Exp. Appl. Acarol. 53, 399–409. https://doi.org/10.1371/journal.pone.000433610.1007/s10493-010-9403-7 (2011).Article 
PubMed 

Google Scholar 
26.Adamska, M. Infestation of game animals from north−western Poland by common tick (Ixodes ricinus) (Acari. Ixododa. Ixodidae). Ann. Parasitol. 54(1), 31–36 (2008).
Google Scholar 
27.Michalik, J. et al. Roe deer (Capreolus capreolus): important hosts for Ixodes ricinus reproduction in forest ecosystems of the Wielkopolska province, west-central Poland. In Stawonogi. Oddziaływanie na żywiciela (ed. Buczek, A. & Błaszak, C.) 87–91 (Wydawnictwo Akapit Lublin, Poland, 2008).28.Vor, T., Kiffner, C., Hagedorn, P., Nidrig, M. & Rühe, F. Tick burden on European roe deer (Capreolus capreolus). Exp. Appl. Acarol. 51, 405–417. https://doi.org/10.1371/journal.pone.000433610.1007/s10493-010-9337-0 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
29.Ivanović, I. et al. Hard tick (Acari: Ixodidae) co-infestation of roe deer (Capreolus capreolus Linnaeus, 1758) in vojvodina hunting resort (Serbia). Sci. Pap. Ser. D. Anim Sci LIX, 326–329 (2016).
Google Scholar 
30.Dominguez, G. North Spain (Burgos) wild mammals ectoparasites. Parasite 11, 267–272. https://doi.org/10.1051/parasite/2004113267 (2004).CAS 
Article 
PubMed 

Google Scholar 
31.Liebisch, A.& Walter, G. Untersuchungen von Zecken bei Haus- und Wildtieren in Deutschland. Zum Vorkommen und zur Biologie der Igelzecke (Ixodes hexagonus) und der Fuchszecke (Ixodes canisuga). Deut. Tierärztl. Woch. 93, 447–450 (1986).32.Król, N. et al. Tick burden on European roe deer (Capreolus capreolus) from Saxony, Germany, and detection of tick-borne encephalitis virus in attached ticks. Parasitol. Res. 119, 1387–1392. https://doi.org/10.1016/j.ttbdis.2014.06.007 (2020).Article 
PubMed 

Google Scholar 
33.Plan urządzania lasu dla nadleśnictwa Podanin, obręby: Margonin. Podanin. Na lata 2012–2021. (BULiGL oddz. w Szczecinku, Poland, 2012).34.Dudziński, M. & Dudziński, J. Studium uwarunkowań i kierunków zagospodarowania przestrzennego gminy Czempiń. Załącznik nr 1 do Uchwały Rady Miejskiej. (Czempiń, 2018).35.Rozporządzenia Ministra Środowiska z dnia marca 2005 r. w sprawie określenia okresów polowań na zwierzęta łowne. Dz. U. Nr 48, poz. 459 (2005).36.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Ausria (2021). https://www.R-project.org.37.Brooks, M.E. at al.glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. The R Journal 9(2), 378–400 https://doi.org/10.32614/RJ-2017-066 (2017)38.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).39.Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. (2017) lmerTest: Tests in Linear Mixed Effects Models. J. Stat. Softw. 82,13. https://doi.org/10.18637/jss.v082.i13 (2017).40.Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.3.5.1. https://CRAN.R-project.org/package=emmeans (2019). More

1.Watling, L., France, S. C., Pante, E. & Simpson, A. Biology of Deep-Water Octocorals. Advances in Marine Biology Vol. 60 (Elsevier, Amsterdam, 2011).
Google Scholar 
2.Sánchez, J. A. Diversity and Evolution of Octocoral Animal Forests at Both Sides of Tropical America. in Marine Animal Forests (ed. Rossi, S., Bramanti, L., Gori, A., & Orejas, C) 1–33 (Springer, 2016).3.Rossi, S., Bramanti, L., Gori, A. and Orejas, C. Marine animal forests: the ecology of benthic biodiversity hotspots. 1-1366. (Springer International Publishing, 2017)4.Cairns, S. D. Studies on western Atlantic Octocorallia (Gorgonacea: Primnoidae). Part 8: New records of Primnoidae from the New England and Corner Rise Seamounts. Proceedings of the Biological Society of Washington120(2), 243–263 (2007).5.Freiwald, A. and Roberts, J.M. Cold-water corals and ecosystems. (Springer, 2005)6.Buhl-Mortensen, L. & Buhl-Mortensen, P. Cold Temperate Coral Habitats. in Corals in a Changing World (2018).7.Braga-Henriques, A. et al. Diversity, distribution and spatial structure of the cold-water coral fauna of the Azores (NE Atlantic). Biogeosciences 10, 4009–4036 (2013).ADS 
Article 

Google Scholar 
8.Íris, S., Andre, F., Filipe, M. P., Gui, M. & Marina, C.-S. Census of Octocorallia (Cnidaria: Anthozoa) of the Azores (NE Atlantic) with a nomenclature update. Zootaxa 4550, 451 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
9.Tempera, F. et al. Mapping condor seamount seafloor environment and associated biological assemblages (Azores, NE Atlantic). Seafloor Geomorphol. Benthic Habitat https://doi.org/10.1016/B978-0-12-385140-6.00059-1 (2012).Article 

Google Scholar 
10.Andrews, A., Stone, R., Lundstrom, C. & DeVogelaere, A. Growth rate and age determination of bamboo corals from the northeastern Pacific Ocean using refined 210Pb dating. Mar. Ecol. Prog. Ser. 397, 173–185 (2009).ADS 
CAS 
Article 

Google Scholar 
11.Neves, B. D. M., Edinger, E., Layne, G. D. & Wareham, V. E. Decadal longevity and slow growth rates in the deep-water sea pen Halipteris finmarchica (Sars, 1851) (Octocorallia: Pennatulacea): implications for vulnerability and recovery from anthropogenic disturbance. Hydrobiologia 759, 147–170 (2015).CAS 
Article 

Google Scholar 
12.FAO. International guidelines for the management of deep-sea fisheries in the High Seas. (2009).13.OSPAR. Background document for coral gardens, Biodiversity Series, Publication Number: 15486/2010. (2010).14.Kim, K. & Lasker, H. R. Allometry of resource capture in colonial cnidarians and constraints on modular growth. Funct. Ecol. 12, 646–654 (1998).Article 

Google Scholar 
15.Gori, A. et al. Effects of food availability on the sexual reproduction and biochemical composition of the Mediterranean gorgonian Paramuricea clavata. J. Exp. Mar. Bio. Ecol. 444, 38–45 (2013).Article 

Google Scholar 
16.Coma, R. & Ribes, M. Seasonal energetic constraints in Mediterranean benthic suspension feeders: effects at different levels of ecological organization. Oikos 101, 205–215 (2003).Article 

Google Scholar 
17.Nisbet, R. M., Muller, E. B., Lika, K. & Kooijman, S. A. L. M. From molecules to ecosystems through dynamic energy budget models. J. Anim. Ecol. 69, 913–926 (2008).Article 

Google Scholar 
18.Sebens, K., Sarà, G. & Nishizaki, M. Energetics, Particle Capture, and Growth Dynamics of Benthic Suspension Feeders. in Marine Animal Forests 813–854 (Springer, 2017).19.Ribes, M., Coma, R. & Gili, J. M. Heterogeneous feeding in benthic suspension feeders: The natural diet and grazing rate of the temperate gorgonian Paramuricea clavata (Cnidaria: Octocorallia) over a year cycle. Mar. Ecol. Prog. Ser. 183, 125–137 (1999).ADS 
Article 

Google Scholar 
20.Orejas, C., Gili, J. M. & Arntz, W. Role of small-plankton communities in the diet of two Antarctic octocorals (Primnoisis antarctica and Primnoella sp.). Mar. Ecol. Prog. Ser. 250, 105–116 (2003).ADS 
Article 

Google Scholar 
21.Ribes, M., Coma, R. & Rossi, S. Natural feeding of the temperate asymbiotic octocoral-gorgonian Leptogorgia sarmentosa (Cnidaria: Octocorallia). Mar. Ecol. Prog. Ser. 254, 141–150 (2003).ADS 
CAS 
Article 

Google Scholar 
22.Cocito, S. et al. Nutrient acquisition in four Mediterranean gorgonian species. Mar. Ecol. Prog. Ser. 473, 179–188 (2013).ADS 
CAS 
Article 

Google Scholar 
23.Leal, M. C. et al. Temporal changes in the trophic ecology of the asymbiotic gorgonian Leptogorgia virgulata. Mar. Biol. 161, 2191–2197 (2014).Article 

Google Scholar 
24.Fabricius, K. E., Benayahu, Y. & Genin, A. Herbivory in Asymbiotic Soft Corals. Science (80-) 268, 90–92 (1995).ADS 
CAS 
Article 

Google Scholar 
25.Rossi, S., Ribes, M., Coma, R. & Gili, J. M. Temporal variability in Zooplankton prey capture rate of the passive suspension feeder Leptogorgia sarmentosa (Cnidaria: Octocorallia), a case study. Mar. Biol. 144, 89–99 (2004).Article 

Google Scholar 
26.Coma, R., Llorente-Llurba, E., Serrano, E., Gili, J. M. & Ribes, M. Natural heterotrophic feeding by a temperate octocoral with symbiotic zooxanthellae: a contribution to understanding the mechanisms of die-off events. Coral Reefs 34, 549–560 (2015).ADS 
Article 

Google Scholar 
27.Orejas, C., Gili, J., López-González, P. & Arntz, W. Feeding strategies and diet composition of four Antarctic cnidarian species. Polar Biol. 24, 620–627 (2001).Article 

Google Scholar 
28.Sherwood, O. A., Jamieson, R. E., Edinger, E. N. & Wareham, V. E. Stable C and N isotopic composition of cold-water corals from the Newfoundland and Labrador continental slope: Examination of trophic, depth and spatial effects . Deep. Res. Part I Oceanogr. Res. Pap. 55, 1392–1402 (2008).ADS 
CAS 
Article 

Google Scholar 
29.Kiriakoulakis, K. et al. Lipids and nitrogen isotopes of two deep-water corals from the North-East Atlantic: initial results and implications for their nutrition. in Cold-Water Corals and Ecosystems 715–729 (Springer, 2005).30.Naumann, M. S., Tolosa, I., Taviani, M., Grover, R. & Ferrier-Pagès, C. Trophic ecology of two cold-water coral species from the Mediterranean Sea revealed by lipid biomarkers and compound-specific isotope analyses. Coral Reefs 34, 1165–1175 (2015).ADS 
Article 

Google Scholar 
31.Naumann, M. S., Orejas, C., Wild, C. & Ferrier-Pagès, C. First evidence for zooplankton feeding sustaining key physiological processes in a scleractinian cold-water coral. J. Exp. Biol. 214, 3570–3576 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
32.Sherwood, O. et al. Stable isotopic composition of deep-sea gorgonian corals Primnoa spp.: a new archive of surface processes. Mar. Ecol. Prog. Ser. 301, 135–148 (2005).ADS 
CAS 
Article 

Google Scholar 
33.Imbs, A. B., Demidkova, D. A. & Dautova, T. N. Lipids and fatty acids of cold-water soft corals and hydrocorals: a comparison with tropical species and implications for coral nutrition. Mar. Biol. 163, 202 (2016).Article 
CAS 

Google Scholar 
34.Salvo, F., Hamoutene, D., Hayes, V. E. W., Edinger, E. N. & Parrish, C. C. Investigation of trophic ecology in Newfoundland cold-water deep-sea corals using lipid class and fatty acid analyses. Coral Reefs 37, 157–171 (2018).ADS 
Article 

Google Scholar 
35.Davies, A. J. et al. Downwelling and deep-water bottom currents as food supply mechanisms to the cold-water coral Lophelia pertusa (Scleractinia) at the Mingulay Reef Complex. Limnol. Oceanogr. 54, 620–629 (2009).ADS 
Article 

Google Scholar 
36.Agusti, S. et al. Ubiquitous healthy diatoms in the deep sea confirm deep carbon injection by the biological pump. Nat. Commun. 6, 1–8 (2015).Article 
CAS 

Google Scholar 
37.Fabricius, K. E., Genin, A. & Benayahu, Y. Flow-dependent herbivory and growth in zoxanthellae-free soft corals. Limnol. Oceanogr. 40, 1290–1301 (1995).ADS 
Article 

Google Scholar 
38.Widdig, A. & Schlichter, D. Phytoplankton: a significant trophic source for soft corals?. Helgol. Mar. Res. 55, 198–211 (2001).ADS 
Article 

Google Scholar 
39.Colaço, A., Giacomello, E., Porteiro, F. & Menezes, G. M. Trophodynamic studies on the Condor seamount (Azores, Portugal, North Atlantic) . Deep. Res. Part II Top. Stud. Oceanogr. 98, 178–189 (2013).ADS 
Article 

Google Scholar 
40.Addamo, A. M. et al. Merging scleractinian genera: the overwhelming genetic similarity between solitary Desmophyllum and colonial Lophelia. BMC Evol. Biol. https://doi.org/10.1186/s12862-016-0654-8 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
41.Mueller, C. E., Larsson, A. I., Veuger, B., Middelburg, J. J. & van Oevelen, D. Opportunistic feeding on various organic food sources by the cold-water coral Lophelia pertusa. Biogeosciences 11, 123–133 (2014).ADS 
Article 

Google Scholar 
42.Roushdy, H. & Hansen, V. Filtration of phytoplankton by the octocoral Alcyonium digitatum. Nature 190, 649–650 (1961).ADS 
Article 

Google Scholar 
43.Sorokin, Y. Biomass, metabolic rates and feeding of some common reef zoantharians and octocorals. Aust. J. Mar. Freshw. Resour. 42, 729–741 (1991).Article 

Google Scholar 
44.Seemann, J. The use of 13C and 15N isotope labeling techniques to assess heterotrophy of corals. J. Exp. Mar. Biol. Ecol. 442, 88–95 (2013).CAS 
Article 

Google Scholar 
45.Orejas, C. et al. The effect of flow speed and food size on the capture efficiency and feeding behaviour of the cold-water coral Lophelia pertusa. J. Exp. Mar. Biol. Ecol. 481, 34–40 (2016).Article 

Google Scholar 
46.Carmo, V. et al. Variability of zooplankton communities at Condor seamount and surrounding areas, Azores (NE Atlantic) . Deep. Sea Res. Part II Top. Stud. Oceanogr. 98, 63–74 (2013).ADS 
Article 

Google Scholar 
47.Gori, A., Grover, R., Orejas, C., Sikorski, S. & Ferrier-Pagès, C. Uptake of dissolved free amino acids by four cold-water coral species from the Mediterranean Sea . Deep. Sea Res. Part II Top. Stud. Oceanogr. 99, 42–50 (2014).ADS 
CAS 
Article 

Google Scholar 
48.Sweetman, A. K. et al. Major impacts of climate change on deep-sea benthic ecosystems. Elementa Science of the Anthropocene vol. 5 (2017).49.Migné, A. & Davoult, D. Experimental nutrition in the soft coral Alcyonium digitatum (Cnidaria: Octocorallia): Removal rate of phytoplankton and zooplankton. Cah. Biol. Mar. 43, 9–16 (2002).
Google Scholar 
50.Sebens, K. P. & Koehl, M. A. R. Predation on zooplankton by the benthic anthozoans Alcyonium siderium (Alcyonacea) and Metridium senile (Actiniaria) in the New England subtidal. Mar. Biol. 81, 255–271 (1984).Article 

Google Scholar 
51.Gili, J.-M., Coma, R., Orejas, C., López-González, P. & Zabala, M. Are Antarctic suspension-feeding communities different from those elsewhere in the world?. Polar Biol. 24, 473–485 (2001).Article 

Google Scholar 
52.Rossi, S. et al. Temporal variation in protein, carbohydrate, and lipid concentrations in Paramuricea clavata (Anthozoa, Octocorallia): evidence for summer-autumn feeding constraints. Mar. Biol. 149, 643–651 (2006).CAS 
Article 

Google Scholar 
53.Coma, R., Ribes, M., Gili, J.-M. & Zabala, M. Seasonality in coastal benthic ecosystems. Trends Ecol. Evol. 15, 448–453 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
54.Bythell, J. C. & Wild, C. Biology and ecology of coral mucus release. J. Exp. Mar. Biol. Ecol. 408, 88–93 (2011).Article 

Google Scholar 
55.Brooke, S., Holmes, M. & Young, C. Sediment tolerance of two different morphotypes of the deep-sea coral Lophelia pertusa from the Gulf of Mexico. Mar. Ecol. Prog. Ser. 390, 137–144 (2009).ADS 
Article 

Google Scholar 
56.Larsson, A. I., van Oevelen, D., Purser, A. & Thomsen, L. Tolerance to long-term exposure of suspended benthic sediments and drill cuttings in the cold-water coral Lophelia pertusa. Mar. Pollut. Bull. 70, 176–188 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
57.Ragnarsson, S. Á. et al. The impact of anthropogenic activity on cold-water corals. in Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots 989–1023 (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-21012-4_27.58.Rix, L. et al. Coral mucus fuels the sponge loop in warm- and cold-water coral reef ecosystems. Sci. Rep. 6, 18715 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
59.Lampert, W. Release of dissolved organic carbon by grazing zooplankton. Limnol. Oceanogr. 23, 831–834 (1978).ADS 
CAS 
Article 

Google Scholar 
60.Moller, E. F. Sloppy feeding in marine copepods: prey-size-dependent production of dissolved organic carbon. J. Plankton Res. 27, 27–35 (2004).Article 
CAS 

Google Scholar 
61.Burton, T., Killen, S. S., Armstrong, J. D. & Metcalfe, N. B. What causes intraspecific variation in resting metabolic rate and what are its ecological consequences?. Proc. R. Soc. B Biol. Sci. 278, 3465–3473 (2011).CAS 
Article 

Google Scholar 
62.Burgess, S. C. et al. Metabolic scaling in modular animals. Invertebr. Biol. 136, 456–472 (2017).Article 

Google Scholar 
63.Maier, S. R. et al. Survival under conditions of variable food availability: Resource utilization and storage in the cold-water coral Lophelia pertusa. Limnol. Oceanogr. 64, 1651–1671 (2019).ADS 
CAS 
Article 

Google Scholar 
64.Okie, J. G. et al. Niche and metabolic principles explain patterns of diversity and distribution: theory and a case study with soil bacterial communities. Proc. R. Soc. B Biol. Sci. 282, 20142630 (2015).Article 

Google Scholar 
65.van Oevelen, D. et al. The cold-water coral community as hotspot of carbon cycling on continental margins: a food-web analysis from Rockall Bank (northeast Atlantic). Limnol. Oceanogr. 54, 1829–1844 (2009).ADS 
Article 

Google Scholar 
66.Cathalot, C. et al. Cold-water coral reefs and adjacent sponge grounds: hotspots of benthic respiration and organic carbon cycling in the deep sea. Front. Mar. Sci. 2, 37 (2015).Article 

Google Scholar 
67.Coppari, M., Zanella, C. & Rossi, S. The importance of coastal gorgonians in the blue carbon budget. Sci. Rep. 9, 1–12 (2019).CAS 
Article 

Google Scholar 
68.Moller, E. F. & Nielsen, T. G. Production of bacterial substrate by marine copepods: effect of phytoplankton biomass and cell size. J. Plankton Res. 23, 527–536 (2001).Article 

Google Scholar 
69.Titelman, J., Riemann, L., Holmfeldt, K. & Nilsen, T. Copepod feeding stimulates bacterioplankton activities in a low phosphorus system. Aquat. Biol. 2, 131–141 (2008).Article 

Google Scholar 
70.Violle, C. & Jiang, L. Towards a trait-based quantification of species niche. J. Plant Ecol. 2, 87–93 (2009).Article 

Google Scholar 
71.Yesson, C. et al. Global habitat suitability of cold-water octocorals. J. Biogeogr. 39, 1278–1292 (2012).Article 

Google Scholar 
72.Kearney, M., Simpson, S. J., Raubenheimer, D. & Helmuth, B. Modelling the ecological niche from functional traits. Philos. Trans. R. Soc. B Biol. Sci. 365, 3469–3483 (2010).Article 

Google Scholar 
73.Violle, C. et al. Let the concept of trait be functional!. Oikos 116, 882–892 (2007).Article 

Google Scholar 
74.Evans, T. G., Diamond, S. E. & Kelly, M. W. Mechanistic species distribution modelling as a link between physiology and conservation. Conservation Physiology 3, cov056 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
75.Johnson, J. Y. Description of a new species of flexible coral belonging to the genus Juncella, obtained at Madeira. Proc. Zool. Soc. London 505–506 (1863).76.Weinberg, S. & Grasshoff, M. Gorgonias. El Mar Mediterraneo. Fauna, Flora, Ecologia. II/1. Guia Sistematica y de Identificacion. (Ediciones Omega, 2003).77.Carpine, C. & Grasshoff, M. Les gorgonaires de la Méditerranée. Bull. l’Institut Océanographique 1–140 (1975).78.Brito, A. & Ocaña, O. Corales de las Islas Canarias. (2004).79.Cau, A. et al. Deepwater corals biodiversity along roche du large ecosystems with different habitat complexity along the south Sardinia continental margin (CW Mediterranean Sea). Mar. Biol. 162, 1865–1878 (2015).Article 

Google Scholar 
80.Tempera, F. et al. Mapping the Condor seamount seafloor environment and associated biological assemblages (Azores, NE Atlantic). In Seafloor geomorphology as benthic habitat: geohab atlas of seafloor geomorphic features and benthic habitats (eds Harris, P. T. & Baker, E. K.) 807–818 (Elsevier, Amsterdam, 2012).
Google Scholar 
81.Santos, M. et al. Phytoplankton variability and oceanographic conditions at Condor seamount, Azores (NE Atlantic) . Deep. Sea Res. Part II Top. Stud. Oceanogr. 98, 52–62 (2013).ADS 
Article 

Google Scholar 
82.Sorokin, Y. I. On the feeding of some scleractinian corals with bacteria and dissolved organic matter. Limnol. Oceanogr. 18, 380–386 (1973).ADS 
CAS 
Article 

Google Scholar 
83.Maier, S. R. et al. Survival under conditions of variable food availability: Resource utilization and storage in the cold-water coral Lophelia pertusa. Limnol. Oceanogr. https://doi.org/10.1002/lno.11142 (2019).Article 

Google Scholar 
84.Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

Google Scholar 
85.Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, New York , 2009).MATH 
Book 

Google Scholar 
86.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
87.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: linear and Nonlinear mixed effects models. R package version 3.1–140. (2019). More

1.Nat. Clim. Change 9, 491 (2019).2.Arneth, A. et al. Proc. Natl Acad. Sci. USA 117, 30882–30891 (2020).CAS 
Article 

Google Scholar 
3.Dinerstein, E. et al. Sci. Adv. 6, eabb2824 (2020).Article 

Google Scholar 
4.Mammola, S. et al. BioScience 69, 641–650 (2019).Article 

Google Scholar 
5.Ficetola, G. F., Canedoli, C. & Stoch, F. Conserv. Biol. 33, 214–216 (2019).Article 

Google Scholar 
6.Chen, Z. et al. World Karst Aquifer Map (WHYMAP WOKAM) (BGR, IAH, KIT & UNESCO, 2017); https://doi.org/10.25928/b2.21_sfkq-r4067.World Database on Protected Areas (IUCN & UNEP-WCMC, 2016).8.Mammola, S. et al. Anthr. Rev. 6, 98–116 (2019).
Google Scholar 
9.Pallarés, S. et al. Anim. Conserv. https://doi.org/10.1111/acv.12654 (2021).10.Castaño-Sánchez, A., Hose, G. C. & Reboleira, A. S. P. Sci. Rep. 10, 12328 (2020).Article 

Google Scholar 
11.Taylor, R. G. et al. Nat. Clim. Change 3, 322–329 (2012).Article 

Google Scholar 
12.Griebler, C. & Avramov, M. Freshw. Sci. 34, 355–367 (2015).Article 

Google Scholar 
13.Gleeson, T., Wada, Y., Bierkens, M. F. P. & van Beek, L. P. H. Nature 488, 197–200 (2012).CAS 
Article 

Google Scholar 
14.Wu, W. Y. et al. Nat. Commun. 11, 3710 (2020).CAS 
Article 

Google Scholar 
15.Famiglietti, J. S. Nat. Clim. Change 4, 945–948 (2014).Article 

Google Scholar 
16.Frick, W. F. et al. Ann. N. Y. Acad. Sci. 1469, 5–25 (2020).Article 

Google Scholar 
17.Browning, E. et al. Mamm. Rev. https://doi.org/10.1111/mam.12239 (2021).18.Deharveng, L. & Bedos, A. In Cave Ecology 107–172 (Springer, 2019).19.Stein, H. et al. Sci. Rep. 2, 673 (2012).Article 

Google Scholar 
20.Culver, D. C. & Holsinger, J. R. Nat. Speleol. Soc. Bull. 54, 79–80 (1992).
Google Scholar 
21.Magnabosco, C. et al. Nat. Geosci. 11, 707–717 (2018).CAS 
Article 

Google Scholar  More

Genetic diversity and population structure across European urban and rural populationsA total of 192 great tits from the nine paired urban–rural populations were genotyped at 517,603 filtered SNPs, with 10–16 individuals per sampling site (Supplementary Table 1). We quantified the relative degree of urbanisation for each site (urbanisation score: PCurb, from principal component analysis, PCA; see “Methods”, Fig. 1b, Supplementary Fig. 1 and Supplementary Table 1) to inform our genetic downstream analyses. Population structuring based on 314,351 LD (linkage-disequilibrium)-pruned SNPs (excluding small linkage groups and the Z-chromosome) was overall low across the 18 studied sites (Supplementary Fig. 2), with each of the first two principal components explaining More

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript. More

1.Landis, D. A. Designing agricultural landscapes for biodiversity-based ecosystem services. Basic Appl. Ecol. 18, 1–12 (2017).
Google Scholar 
2.Aguilar, J. et al. Crop species diversity changes in the United States: 1978–2012. PLoS ONE 10, e0136580 (2015).PubMed 
PubMed Central 

Google Scholar 
3.Census of Agriculture (USDA National Agricultural Statistics Service, 2017); www.nass.usda.gov/AgCensus4.Fahrig, L. et al. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecol. Lett. 14, 101–112 (2011).PubMed 

Google Scholar 
5.Meehan, T. D., Werling, B. P., Landis, D. A. & Gratton, C. Agricultural landscape simplification and insecticide use in the Midwestern United States. Proc. Natl Acad. Sci. USA 108, 11500–11505 (2011).ADS 
CAS 
PubMed 

Google Scholar 
6.Tiemann, L. K., Grandy, A. S., Atkinson, E. E., Marin-Spiotta, E. & McDaniel, M. D. Crop rotational diversity enhances belowground communities and functions in an agroecosystem. Ecol. Lett. 18, 761–771 (2015).CAS 
PubMed 

Google Scholar 
7.Abson, D. J., Fraser, E. D. & Benton, T. G. Landscape diversity and the resilience of agricultural returns: a portfolio analysis of land-use patterns and economic returns from lowland agriculture. Agric. Food Secur. 2, 2 (2013).
Google Scholar 
8.Dainese, M. et al. A global synthesis reveals biodiversity-mediated benefits for crop production. Sci. Adv. 5, eaax0121 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
9.Ojha, S. & Dimov, L. Variation in the diversity-productivity relationship in young forests of the eastern United States. PLoS ONE 12, e0187106 (2017).PubMed 
PubMed Central 

Google Scholar 
10.Smith, R. G., Gross, K. L. & Robertson, G. P. Effects of crop diversity on agroecosystem function: crop yield response. Ecosystems 11, 355–366 (2008).
Google Scholar 
11.Karp, D. S. et al. Crop pests and predators exhibit inconsistent responses to surrounding landscape composition. Proc. Natl Acad. Sci. USA 115, E7863–E7870 (2018).CAS 
PubMed 

Google Scholar 
12.Bastian, O., Grunewald, K., Syrbe, R. U., Walz, U. & Wende, W. Landscape services: the concept and its practical relevance. Landsc. Ecol. 29, 1463–1479 (2014).
Google Scholar 
13.Winfree, R. et al. Species turnover promotes the importance of bee diversity for crop pollination at regional scales. Science 359, 791–793 (2018).ADS 
CAS 
PubMed 

Google Scholar 
14.Duarte, G. T., Santos, P. M., Cornelissen, T. G., Ribeiro, M. C. & Paglia, A. P. The effects of landscape patterns on ecosystem services: meta-analyses of landscape services. Landsc. Ecol. 33, 1247–1257 (2018).
Google Scholar 
15.Li, C. et al. Crop diversity for yield increase. PLoS ONE 4, e8049 (2009).ADS 
PubMed 
PubMed Central 

Google Scholar 
16.Swinton, S. M., Lupi, F., Robertson, G. P. & Hamilton, S. K. Ecosystem services and agriculture: cultivating agricultural ecosystems for diverse benefits. Ecol. Econ. 64, 245–252 (2007).
Google Scholar 
17.Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
18.Burchfield, E. K., Nelson, K. S. & Spangler, K. The impact of agricultural landscape diversification on US crop production. Agric. Ecosyst. Environ. 285, 106615 (2019).
Google Scholar 
19.Galpern, P., Vickruck, J., Devries, J. H. & Gavin, M. P. Landscape complexity is associated with crop yields across a large temperate grassland region. Agric. Ecosyst. Environ. 290, 106724 (2020).
Google Scholar 
20.Morris, E. K. et al. Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories. Ecol. Evol. 4, 3514–3524 (2014).PubMed 
PubMed Central 

Google Scholar 
21.Burke, M. & Emerick, K. Adaptation to climate change: evidence from US agriculture. Am. Econ. J. Econ. Pol. 8, 106–140 (2016).
Google Scholar 
22.Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3, 497–501 (2013).ADS 

Google Scholar 
23.Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).ADS 
CAS 
PubMed 

Google Scholar 
24.Schauberger, B., Rolinski, S. & Müller, C. A network-based approach for semi-quantitative knowledge mining and its application to yield variability. Environ. Res. Lett. 11, 123001 (2016).ADS 

Google Scholar 
25.Burchfield, E., Matthews-Pennanen, N., Stoebner, J. & Lant, C. Changing yields in the central United States under climate and technological change. Clim. Change 159, 329–346 (2019).ADS 

Google Scholar 
26.Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).ADS 
CAS 
PubMed 

Google Scholar 
27.Troy, T. J., Kipgen, C. & Pal, I. The impact of climate extremes and irrigation on US crop yields. Environ. Res. Lett. 10, 054013 (2015).ADS 

Google Scholar 
28.Chaplin‐Kramer, R., O’Rourke, M. E., Blitzer, E. J. & Kremen, C. A meta‐analysis of crop pest and natural enemy response to landscape complexity. Ecol. Lett. 14, 922–932 (2011).PubMed 

Google Scholar 
29.Grab, H., Danforth, B., Poveda, K. & Loeb, G. Landscape simplification reduces classical biological control and crop yield. Ecol. Appl. 28, 348–355 (2018).PubMed 

Google Scholar 
30.Martin, E. A. et al. The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe. Ecol. Lett. 22, 1083–1094 (2019).PubMed 
PubMed Central 

Google Scholar 
31.Lark, T. J., Spawn, S. A., Bougie, M. & Gibbs, H. K. Cropland expansion in the United States produces marginal yields at high costs to wildlife. Nat. Commun. 11, 4295 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
32.Finney, D. M. & Kaye, J. P. Functional diversity in cover crop polycultures increases multifunctionality of an agricultural system. J. Appl. Ecol. 54, 509–517 (2017).
Google Scholar 
33.Bowles, T. M. et al. Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth 2, 284–293 (2020).
Google Scholar 
34.Tscharntke, T. et al. Landscape perspectives on agricultural intensification and biodiversity-ecosystem service management. Ecol. Lett. 8, 857–874 (2012).
Google Scholar 
35.Swift, M. J., Izac, A.-M. N. & van Noordwijk, M. Biodiversity and ecosystem services in agricultural landscapes—are we asking the right questions? Agric. Ecosyst. Environ. 104, 113–134 (2004).
Google Scholar 
36.CropScrape—Cropland Data Layer (USDA National Agricultural Statistics Service, 2018); https://nassgeodata.gmu.edu/CropScape/37.Schulte, L. A. et al. Prairie strips improve biodiversity and the delivery of multiple ecosystem services from corn–soybean croplands. Proc. Natl Acad. Sci. USA 114, 11247–11252 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
38.Albrecht, M. et al. The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis. Ecol. Lett. 23, 1488–1498 (2020).PubMed 
PubMed Central 

Google Scholar 
39.Liang, X. Z. et al. Determining climate effects on US total agricultural productivity. Proc. Natl Acad. Sci. USA 114, E2285–E2292 (2017).CAS 
PubMed 

Google Scholar 
40.Brandes, E. et al. Subfield profitability analysis reveals an economic case for cropland diversification. Environ. Res. Lett. 11, 014009 (2016).ADS 

Google Scholar 
41.Capmourteres, V. et al. Precision conservation meets precision agriculture: a case study from southern Ontario. Agric. Syst. 167, 176–185 (2018).
Google Scholar 
42.Census of Agriculture (USDA National Agricultural Statistics Service, 2019); www.nass.usda.gov/AgCensus43.Ray, D. K., Gerber, J. S., Macdonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nat. Commun. 6, 5989 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
44.Ramankutty, N., Evan, A. T., Monfreda, C. & Foley, J. A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochem. Cycles 22, GB1003 (2008).
Google Scholar 
45.PRISM Climate Data (PRISM Climate Group, 2004) http://www.prism.oregonstate.edu/46.Miller, P., Lanier, W. & Brandt, S. Using Growing Degree Days to Predict Plant Stages (Montana State University, 2001); http://store.msuextension.org/publications/AgandNaturalResources/MT200103AG.pdf47.agweather connection (Mesonet, 2007); https://www.mesonet.org/mesonet_connection/V2_No8.pdf48.Corn Growing Degree Days (NDAWN: North Dakota Agricultural Weather Network, 2017); https://ndawn.ndsu.nodak.edu/help-corn-growing-degree-days.html49.Gridded Soil Survey Geographic (gSSURGO) Database for the Conterminous United States (US Department of Agriculture, Natural Resources Conservation Service, 2014); https://gdg.sc.egov.usda.gov/50.Dobos, R. R., Sinclair, H. R., Jr & Robotham, M. P. User Guide for the National Commodity Crop Productivity Index (NCCPI, 2012).51.Plexida, S. G., Sfougaris, A. I., Ispikoudis, I. P. & Papanastasis, V. P. Selecting landscape metrics as indicators of spatial heterogeneity—a comparison among Greek landscapes. Int. J. Appl. Earth Obs. Geoinf. 26, 26–35 (2014).ADS 

Google Scholar 
52.Schindler, S., Poirazidis, K. & Wrbka, T. Towards a core set of landscape metrics for biodiversity assessments: a case study from Dadia National Park, Greece. Ecol. Indic. 8, 502–514 (2008).
Google Scholar 
53.Turner, M. G. Spatial and temporal analysis of landscape patterns. Landsc. Ecol. 4, 21–30 (1990).
Google Scholar 
54.Li, H. & Wu, J. Use and misuse of landscape indices. Landsc. Ecol. 19, 389–399 (2004).
Google Scholar 
55.Hesselbarth, M. H., Sciaini, M., With, K. A., Wiegand, K. & Nowosad, J. landscapemetrics: an open-source R tool to calculate landscape metrics. Ecography 42, 1–10 (2019).
Google Scholar 
56.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017); https://www.R-project.org/57.Rue, H., Martino, S. & Chopin, N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J. R. Stat. Soc. Series B Stat. Methodol. 71, 319–392 (2009).MathSciNet 
MATH 

Google Scholar 
58.Blanc, E. & Schlenker, W. The use of panel models in assessments of climate impacts on agriculture. Rev. Environ. Econ. Policy 11, 258–279 (2017).
Google Scholar 
59.Level III Ecoregions of the Continental United States (US Environmental Protection Agency, 2011); https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states60.Bakka, H. et al. Spatial modeling with R-INLA: a review. Wiley Interdiscip. Rev. Comput. Stat. 10, e1443 (2018).MathSciNet 

Google Scholar 
61.2018 Cartographic Boundary Files [data set] (US Census Bureau, 2018); https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html More

1.Bourne DG, Morrow KM, Webster NS. Insights into the coral microbiome: underpinning the health and resilience of reef ecosystems. Annu Rev Microbiol. 2016;70:317–40.CAS 
PubMed 
Article 

Google Scholar 
2.Ainsworth TD, Thurber RV, Gates RD. The future of coral reefs: a microbial perspective. Trends Ecol Evol. 2010;25:233–40.PubMed 
Article 

Google Scholar 
3.Huettel M, Wild C, Gonelli S. Mucus trap in coral reefs: formation and temporal evolution of particle aggregates caused by coral mucus. Mar Ecol Prog Ser. 2006;307:69–84.Article 

Google Scholar 
4.Coffroth M. Mucous sheet formation on poritid corals: an evaluation of coral mucus as a nutrient source on reefs. Mar Biol. 1990;105:39–49.CAS 
Article 

Google Scholar 
5.Brown BE, Bythell JC. Perspectives on mucus secretion in reef corals. Mar Ecol Prog Ser. 2005;296:291–309.CAS 
Article 

Google Scholar 
6.Sweet M, Croquer A, Bythell J. Bacterial assemblages differ between compartments within the coral holobiont. Coral Reefs. 2011;30:39–52.Article 

Google Scholar 
7.Yancey PH. Organic osmolytes as compatible, metabolic and counteracting cytoprotectants in high osmolarity and other stresses. J Exp Biol. 2005;208:2819–30.CAS 
PubMed 
Article 

Google Scholar 
8.Burg MB, Ferraris JD. Intracellular organic osmolytes: function and regulation. J Biol Chem. 2008;283:7309–13.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
9.Singh LR, Dar TA, editors. Cellular osmolytes: from chaperoning protein folding to clinical perspectives. 1st ed. Singapore: Springer Nature Singapore Pte Ltd.; 2017.10.Yancey PH, Heppenstall M, Ly S, Andrell RM, Gates RD, Carter VL, et al. Betaines and dimethylsulfoniopropionate as major osmolytes in cnidaria with endosymbiotic dinoflagellates. Physiol Biochem Zool. 2010;83:167–73.CAS 
PubMed 
Article 

Google Scholar 
11.Mayfield AB, Gates RD. Osmoregulation in anthozoan—dinoflagellate symbiosis. Compar Biochem Physiol A. 2007;147:1–10.Article 
CAS 

Google Scholar 
12.Rublee PA, Lasker HR, Gottfried M, Roman MR. Production and bacterial colonization of mucus from the soft coral Briarium asbestinum. Bull Mar Sci. 1980;30:888–93.
Google Scholar 
13.Wild C, Woyt H, Huettel M. Influence of coral mucus on nutrient fluxes in carbonate sands. Mar Ecol Prog Ser. 2005;287:87–98.CAS 
Article 

Google Scholar 
14.Coles SL, Strathmann R. Observations on coral mucus “flocs” and their potential trophic significance. Limnol Oceanogr. 1973;18:673–8.Article 

Google Scholar 
15.Pernice M, Raina J-B, Rädecker N, Cárdenas A, Pogoreutz C, Voolstra CR. Down to the bone: the role of overlooked endolithic microbiomes in reef coral health. ISME J. 2020;14:325–34.PubMed 
Article 

Google Scholar 
16.Falini G, Fermani S, Goffredo S. Coral biomineralization: a focus on intra-skeletal organic matrix and calcification. Semin Cell Dev Biol. 2015;46:17–26.Article 

Google Scholar 
17.Constantz B, Weiner S. Acidic macromolecules associated with the mineral phase of scleractinian coral skeletons. J Exp Zool. 1988;248:253–8.CAS 
Article 

Google Scholar 
18.Muscatine L, Goiran C, Land L, Jaubert J, Cuif JP, Allemand D. Stable isotopes (delta C-13 and delta N-15) of organic matrix from coral skeleton. Proc Natl Acad Sci USA. 2005;102:1525–30.CAS 
PubMed 
Article 

Google Scholar 
19.Sorek M, Díaz-Almeyda EM, Medina M, Levy O. Circadian clocks in symbiotic corals: the duet between Symbiodinium algae and their coral host. Mar Genom. 2014;14:47–57.Article 

Google Scholar 
20.Agostini S, Suzuki Y, Higuchi T, Casareto B, Yoshinaga K, Nakano Y, et al. Biological and chemical characteristics of the coral gastric cavity. Coral Reefs. 2012;31:147–56.Article 

Google Scholar 
21.Rosenberg E, Koren O, Reshef L, Efrony R, Zilber-Rosenberg I. The role of microorganisms in coral health, disease and evolution. Nat Rev Microbiol. 2007;5:355–62.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
22.Ritchie KB. Bacterial symbionts of corals and Symbiodinium. In: Rosenberg E, Gophna U editors. Beneficial microorganisms in multicellular life forms. 1st ed. Berlin Heidelberg: Springer-Verlag Berlin Heidelberg; 2012. pp 139–50.23.Apprill A, Weber LG, Santoro AE. Distinguishing between microbial habitats unravels ecological complexity in coral microbiomes. mSystems. 2016;1:e00143–00116.PubMed 
PubMed Central 
Article 

Google Scholar 
24.Pollock FJ, McMinds R, Smith S, Bourne DG, Willis BL, Medina M, et al. Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny. Nat Commun. 2018;9:1–13.CAS 
Article 

Google Scholar 
25.Shapiro BJ, Friedman J, Cordero OX, Preheim SP, Timberlake SC, Szabó G, et al. Population genomics of early events in the ecological differentiation of bacteria. Science. 2012;336:48–51.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
26.Youngblut ND, Wirth JS, Henriksen JR, Smith M, Simon H, Metcalf WW, et al. Genomic and phenotypic differentiation among Methanosarcina mazei populations from Columbia River sediment. ISME J. 2015;9:2191–205.PubMed 
PubMed Central 
Article 

Google Scholar 
27.Wielgoss S, Didelot X, Chaudhuri RR, Liu X, Weedall GD, Velicer GJ, et al. A barrier to homologous recombination between sympatric strains of the cooperative soil bacterium Myxococcus xanthus. ISME J. 2016;10:2468–77.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
28.Chase AB, Arevalo P, Brodie EL, Polz MF, Karaoz U, Martiny JB. Maintenance of sympatric and allopatric populations in free-living terrestrial bacteria. Mbio. 2019;10:e02361–02319.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
29.Huggett MJ, Apprill A. Coral microbiome database: integration of sequences reveals high diversity and relatedness of coral-associated microbes. Environ Microbiol Rep. 2019;11:372–85.PubMed 
Article 

Google Scholar 
30.Apprill A, Marlow HQ, Martindale MQ, Rappe MS. The onset of microbial associations in the coral Pocillopora meandrina. ISME J. 2009;3:685–99.PubMed 
Article 

Google Scholar 
31.Epstein HE, Torda G, Munday PL, van Oppen MJH. Parental and early life stage environments drive establishment of bacterial and dinoflagellate communities in a common coral. ISME J. 2019;13:1635–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
32.Freire I, Gutner-Hoch E, Muras A, Benayahu Y, Otero A. The effect of bacteria on planula-larvae settlement and metamorphosis in the octocoral Rhytisma fulvum fulvum. PLoS ONE. 2019;14:e0223214.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
33.Miura N, Motone K, Takagi T, Aburaya S, Watanabe S, Aoki W, et al. Ruegeria sp. strains isolated from the reef-building coral Galaxea fascicularis inhibit growth of the temperature-dependent pathogen Vibrio coralliilyticus. Mar Biotechnol. 2019;21:1–8.CAS 
Article 

Google Scholar 
34.Apprill A, Hughen K, Mincer T. Major similarities in the bacterial communities associated with lesioned and healthy Fungiidae corals. Environ Microbiol. 2013;15:2063–72.CAS 
PubMed 
Article 

Google Scholar 
35.Sekar R, Kaczmarsky LT, Richardson LL. Microbial community composition of black band disease on the coral host Siderastrea siderea from three regions of the wider Caribbean. Mar Ecol Prog Ser. 2008;362:85–98.CAS 
Article 

Google Scholar 
36.Casey JM, Connolly SR, Ainsworth TD. Coral transplantation triggers shift in microbiome and promotion of coral disease associated potential pathogens. Sci Rep. 2015;5:11903–11903.PubMed 
PubMed Central 
Article 

Google Scholar 
37.Tsang RHL, Ang PO. Resistance to temperature stress and Drupella corallivory may promote the dominance of Platygyra acuta in the marginal coral communities in Hong Kong. Mar Environ Res. 2019;144:20–27.CAS 
PubMed 
Article 

Google Scholar 
38.Tam TW, Ang PO Jr. Repeated physical disturbances and the stability of sub‐tropical coral communities in Hong Kong, China. Aquat Conserv. 2008;18:1005–24.Article 

Google Scholar 
39.Ang Jr PO, Choi LS, Choi MM, Cornish A, Fung HL, Lee MW et al. Hong Kong. In: Centre JWR editors. Status of coral reefs of the East Asian Seas region: 2004. Tokyo: Ministry of the Environment; 2005. pp 121–52.40.Luo H, Moran MA. Evolutionary ecology of the marine Roseobacter clade. Microbiol Mol Biol Rev. 2014;78:573–87.PubMed 
PubMed Central 
Article 

Google Scholar 
41.Pujalte MJ, Lucena T, Ruvira MA, Arahal DR, Macián MC. The family Rhodobacteraceae. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F editors. The Prokaryotes: alphaproteobacteria and Betaproteobacteria. 4th ed. Berlin Heidelberg: Springer-Verlag Berlin Heidelberg; 2014. pp 439–512.42.Johannes RE, Wiebe WJ. Method for determination of coral tissue biomass and composition. Limnol Oceanogr. 1970;15:822–4.Article 

Google Scholar 
43.Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20:1–14.Article 

Google Scholar 
44.Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.CAS 
PubMed 
Article 

Google Scholar 
45.Achtman M, Wagner M. Microbial diversity and the genetic nature of microbial species. Nat Rev Microbiol. 2008;6:431–40.CAS 
PubMed 
Article 

Google Scholar 
46.Feil EJ, Spratt BG. Recombination and the population structures of bacterial pathogens. Annu Rev Microbiol. 2001;55:561–90.CAS 
PubMed 
Article 

Google Scholar 
47.Wang X, Zhang Y, Ren M, Xia T, Chu X, Liu C, et al. Cryptic speciation of a pelagic Roseobacter population varying at a few thousand nucleotide sites. ISME J. 2020;14:3106–19.48.Lawson DJ, Hellenthal G, Myers S, Falush D. Inference of population structure using dense haplotype data. PLoS Genet. 2012;8:e1002453.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Didelot X, Wilson DJ. ClonalFrameML: efficient inference of recombination in whole bacterial genomes. PLoS Comput Biol. 2015;11:e1004041.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
50.Excoffier L, Lischer HE. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010;10:564–7.PubMed 
Article 

Google Scholar 
51.Sun Y, Luo H. Homologous recombination in core genomes facilitates marine bacterial adaptation. Appl Environ Microbiol. 2018;84:e02545–02517.CAS 
PubMed 
PubMed Central 

Google Scholar 
52.Librado P, Vieira FG, Rozas J. BadiRate: estimating family turnover rates by likelihood-based methods. Bioinformatics. 2011;28:279–81.PubMed 
Article 
CAS 

Google Scholar 
53.Slatkin M, Maddison WP. A cladistic measure of gene flow inferred from the phylogenies of alleles. Genetics 1989;123:603–13.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
54.Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:1–8.Article 
CAS 

Google Scholar 
55.Lohr KE, Khattri RB, Guingab-Cagmat J, Camp EF, Merritt ME, Garrett TJ, et al. Metabolomic profiles differ among unique genotypes of a threatened Caribbean coral. Sci Rep. 2019;9:1–11.CAS 
Article 

Google Scholar 
56.Hill R, Li C, Jones A, Gunn J, Frade P. Abundant betaines in reef-building corals and ecological indicators of a photoprotective role. Coral Reefs. 2010;29:869–80.Article 

Google Scholar 
57.Gowrishankar J. Nucleotide sequence of the osmoregulatory proU operon of Escherichia coli. J Bacteriol. 1989;171:1923–31.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
58.Chandravanshi M, Gogoi P, Kanaujia SP. Computational characterization of TTHA0379: A potential glycerophosphocholine binding protein of Ugp ATP-binding cassette transporter. Gene. 2016;592:260–8.CAS 
PubMed 
Article 

Google Scholar 
59.Ziegler C, Bremer E, Krämer R. The BCCT family of carriers: from physiology to crystal structure. Mol Microbiol. 2010;78:13–34.CAS 
PubMed 

Google Scholar 
60.Geiger O, López-Lara IM, Sohlenkamp C. Phosphatidylcholine biosynthesis and function in bacteria. Biochim Biophys Acta Mol Cell Biol Lipids. 2013;1831:503–13.CAS 
Article 

Google Scholar 
61.Lidbury I, Kimberley G, Scanlan DJ, Murrell JC, Chen Y. Comparative genomics and mutagenesis analyses of choline metabolism in the marine Roseobacter clade. Environ Microbiol. 2015;17:5048–62.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
62.Thole S, Kalhoefer D, Voget S, Berger M, Engelhardt T, Liesegang H, et al. Phaeobacter gallaeciensis genomes from globally opposite locations reveal high similarity of adaptation to surface life. ISME J. 2012;6:2229–44.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
63.Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, DuGar B, et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature. 2011;472:57–63.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
64.Jones M, Talfournier F, Bobrov A, Grossmann JG, Vekshin N, Sutcliffe MJ, et al. Electron transfer and conformational change in complexes of trimethylamine dehydrogenase and electron transferring flavoprotein. J Biol Chem. 2002;277:8457–65.CAS 
PubMed 
Article 

Google Scholar 
65.Chen Y. Comparative genomics of methylated amine utilization by marine Roseobacter clade bacteria and development of functional gene markers (tmm, gmaS). Environ Microbiol. 2012;14:2308–22.CAS 
PubMed 
Article 

Google Scholar 
66.Schäfer H, McDonald IR, Nightingale PD, Murrell JC. Evidence for the presence of a CmuA methyltransferase pathway in novel marine methyl halide‐oxidizing bacteria. Environ Microbiol. 2005;7:839–52.PubMed 
Article 
CAS 

Google Scholar 
67.McNicholas PM, Chiang RC, Gunsalus RP. Anaerobic regulation of the Escherichia coli dmsABC operon requires the molybdate‐responsive regulator ModE. Mol Microbiol. 1998;27:197–208.CAS 
PubMed 
Article 

Google Scholar 
68.Loschi L, Brokx SJ, Hills TL, Zhang G, Bertero MG, Lovering AL, et al. Structural and biochemical identification of a novel bacterial oxidoreductase. J Biol Chem. 2004;279:50391–50400.CAS 
PubMed 
Article 

Google Scholar 
69.Hillyer KE, Dias DA, Lutz A, Wilkinson SP, Roessner U, Davy SK. Metabolite profiling of symbiont and host during thermal stress and bleaching in the coral Acropora aspera. Coral Reefs. 2017;36:105–18.Article 

Google Scholar 
70.Rösgen J. Molecular basis of osmolyte effects on protein and metabolites. Methods Enzymol. 2007;428:459–86.PubMed 
Article 
CAS 

Google Scholar 
71.Cunliffe M. Correlating carbon monoxide oxidation with cox genes in the abundant marine Roseobacter clade. ISME J. 2011;5:685–91.CAS 
PubMed 
Article 

Google Scholar 
72.Bartling P, Vollmers J, Petersen J. The first world swimming championships of Roseobacters—phylogenomic insights into an exceptional motility phenotype. Syst Appl Microbiol. 2018;41:544–54.PubMed 
Article 

Google Scholar 
73.Michael V, Frank O, Bartling P, Scheuner C, Goker M, Brinkmann H, et al. Biofilm plasmids with a rhamnose operon are widely distributed determinants of the ‘swim-or-stick’ lifestyle in roseobacters. ISME J. 2016;10:2498–513.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
74.Armitage JP. Behavioural responses of bacteria to light and oxygen. Arch Microbiol. 1997;168:249–61.CAS 
PubMed 
Article 

Google Scholar 
75.Jorgensen NOG. Uptake of urea by estuarine bacteria. Aquat Micro Ecol. 2006;42:227–42.Article 

Google Scholar 
76.Pernice M, Raina J-B, Rädecker N, Cárdenas A, Pogoreutz C, Voolstra CR. Down to the bone: the role of overlooked endolithic microbiomes in reef coral health. ISME J. 2019: 1–10.77.Krajewska B, Ureases I. Functional, catalytic and kinetic properties: a review. J Mol Catal B Enzym. 2009;59:9–21.CAS 
Article 

Google Scholar 
78.Cheng L, Cord-Ruwisch R. In situ soil cementation with ureolytic bacteria by surface percolation. Ecol Eng. 2012;42:64–72.Article 

Google Scholar 
79.Cho BC, Park MG, Shim JH, Azam F. Significance of bacteria in urea dynamics in coastal surface waters. Mar Ecol Prog Ser. 1996;142:19–26.Article 

Google Scholar 
80.Jin D, Zhao SG, Zheng N, Beckers Y, Wang JQ. Urea metabolism and regulation by rumen bacterial urease in ruminants—a review. Ann Anim Sci. 2018;18:303–18.Article 

Google Scholar 
81.Collier JL, Baker KM, Bell SL. Diversity of urea-degrading microorganisms in open-ocean and estuarine planktonic communities. Environ Microbiol. 2009;11:3118–31.CAS 
PubMed 
Article 

Google Scholar 
82.Biscéré T, Ferrier-Pagès C, Grover R, Gilbert A, Rottier C, Wright A, et al. Enhancement of coral calcification via the interplay of nickel and urease. Aquat Toxicol. 2018;200:247–56.PubMed 
Article 
CAS 

Google Scholar 
83.Crossland C, Barnes D. The role of metabolic nitrogen in coral calcification. Mar Biol. 1974;28:325–32.CAS 
Article 

Google Scholar 
84.Goodkin NF, Switzer AD, Mccorry D, Devantier L, True J, Hughen KA, et al. Coral communities of Hong Kong: long-lived corals in a marginal reef environment. Mar Ecol Prog Ser. 2011;426:185–96.Article 

Google Scholar 
85.Bernasconi R, Stat M, Koenders A, Paparini A, Bunce M, Huggett MJ. Establishment of coral-bacteria symbioses reveal changes in the core bacterial community with host ontogeny. Front Mirobiol. 2019;10:1529.Article 

Google Scholar 
86.Chu X, Li S, Wang S, Luo D, Luo H. Gene loss through pseudogenization contributes to the ecological diversification of a generalist Roseobacter lineage. ISME J. 2020;15:489–502.PubMed 
Article 
CAS 

Google Scholar 
87.Gardner SN, Slezak T, Hall BG. kSNP3. 0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics. 2015;31:2877–8.CAS 
PubMed 
Article 

Google Scholar 
88.Krzywinski M, Schein JE, Birol I, Connors JM, Gascoyne RD, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More