Ecology

1.Sogin, M. L. et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. P Natl Acad. Sci. USA 103, 12115–12120 (2006).CAS 
ADS 

Google Scholar 
2.Pedros-Alio, C. The rare bacterial biosphere. Ann. Rev. Mar. Sci. 4, 449–466 (2012).PubMed 

Google Scholar 
3.Lynch, M. D. J. & Neufeld, J. D. Ecology and exploration of the rare biosphere. Nat. Rev. Microbiol. 13, 217–229 (2015).CAS 
PubMed 

Google Scholar 
4.Campbell, B. J., Yu, L. Y., Heidelberg, J. F. & Kirchman, D. L. Activity of abundant and rare bacteria in a coastal ocean. P Natl Acad. Sci. USA 108, 12776–12781 (2011).CAS 
ADS 

Google Scholar 
5.Gobet, A. et al. Diversity and dynamics of rare and of resident bacterial populations in coastal sands. Isme J. 6, 542–553 (2012).PubMed 

Google Scholar 
6.Wilhelm, L. et al. Rare but active taxa contribute to community dynamics of benthic biofilms in glacier-fed streams. Environ. Microbiol. 16, 2514–2524 (2014).CAS 
PubMed 

Google Scholar 
7.Lawson, C. E. et al. Rare taxa have potential to make metabolic contributions in enhanced biological phosphorus removal ecosystems. Environ. Microbiol. 17, 4979–4993 (2015).CAS 
PubMed 

Google Scholar 
8.Newton, R. J. & Shade, A. Lifestyles of rarity: understanding heterotrophic strategies to inform the ecology of the microbial rare biosphere. Aquat. Micro. Ecol. 78, 51–63 (2016).
Google Scholar 
9.Lauro, F. M. et al. The genomic basis of trophic strategy in marine bacteria. P Natl Acad. Sci. USA 106, 15527–15533 (2009).CAS 
ADS 

Google Scholar 
10.Klappenbach, J. A., Dunbar, J. M. & Schmidt, T. M. RRNA operon copy number reflects ecological strategies of bacteria. Appl Environ. Micro. 66, 1328–1333 (2000).CAS 
ADS 

Google Scholar 
11.Roller, B. R. K., Stoddard, S. F. & Schmidt, T. M. Exploiting rRNA operon copy number to investigate bacterial reproductive strategies. Nat. Microbiol. 1, 16160 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
12.Polz, M. F. & Cordero, O. X. Bacterial evolution: genomics of metabolic trade-offs. Nat. Microbiol. 1, 16181 (2016).CAS 
PubMed 

Google Scholar 
13.Giovannoni, S. J. SAR11 bacteria: the most abundant plankton in the oceans. Ann. Rev. Mar. Sci. 9, 231–255 (2017).PubMed 

Google Scholar 
14.Elser, J. J. et al. Biological stoichiometry from genes to ecosystems. Ecol. Lett. 3, 540–550 (2000).
Google Scholar 
15.Hessen, D. O., Elser, J. J., Sterner, R. W. & Urabe, J. Ecological stoichiometry: an elementary approach using basic principles. Limnol. Oceanogr. 58, 2219–2236 (2013).CAS 
ADS 

Google Scholar 
16.Acharya, K., Kyle, M. & Elser, J. J. Biological stoichiometry of Daphnia growth: an ecophysiological test of the growth rate hypothesis. Limnol. Oceanogr. 49, 656–665 (2004).CAS 
ADS 

Google Scholar 
17.Hendrixson, H. A., Sterner, R. W. & Kay, A. D. Elemental stoichiometry of freshwater fishes in relation to phylogeny, allometry and ecology. J. Fish. Biol. 70, 121–140 (2007).
Google Scholar 
18.Matzek, V. & Vitousek, P. M. N: P stoichiometry and protein: RNA ratios in vascular plants: an evaluation of the growth-rate hypothesis. Ecol. Lett. 12, 765–771 (2009).PubMed 

Google Scholar 
19.Ghoul, M. & Mitri, S. The ecology and evolution of microbial competition. Trends Microbiol 24, 833–845 (2016).CAS 
PubMed 

Google Scholar 
20.Laland, K., Matthews, B. & Feldman, M. W. An introduction to niche construction theory. Evol. Ecol. 30, 191–202 (2016).PubMed 
PubMed Central 

Google Scholar 
21.Ratzke, C., Barrere, J. & Gore, J. Strength of species interactions determines biodiversity and stability in microbial communities. Nat. Ecol. Evol. 4, 376–383 (2020).PubMed 

Google Scholar 
22.Větrovský, T. & Baldrian, P. The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses. Plos ONE 8, e57923 (2013).PubMed 
PubMed Central 
ADS 

Google Scholar 
23.Molenaar, D., van Berlo, R., de Ridder, D. & Teusink, B. Shifts in growth strategies reflect tradeoffs in cellular economics. Mol. Syst. Biol. 5, 323–323 (2009).PubMed 
PubMed Central 

Google Scholar 
24.Nemergut, D. R. et al. Decreases in average bacterial community rRNA operon copy number during succession. Isme J. 10, 1147–1156 (2016).CAS 
PubMed 

Google Scholar 
25.Wu, L. W. et al. Microbial functional trait of rRNA operon copy numbers increases with organic levels in anaerobic digesters. Isme J. 11, 2874–2878 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
26.Wu, L. W. et al. Global diversity and biogeography of bacterial communities in wastewater treatment plants. Nat. Microbiol. 4, 2579–2579 (2019).PubMed 

Google Scholar 
27.Stoddard, S. F., Smith, B. J., Hein, R., Roller, B. R. K. & Schmidt, T. M. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res. 43, D593–D598 (2015).CAS 
PubMed 

Google Scholar 
28.Dai, T. et al. Dynamics of coastal bacterial community average ribosomal RNA operon copy number reflect its response and sensitivity to ammonium and phosphate. Environ. Pollut. 260, 113971 (2020).CAS 
PubMed 

Google Scholar 
29.Zhou, J., Deng, Y., Luo, F., He, Z. & Yang, Y. Phylogenetic molecular ecological network of soil microbial communities in response to elevated CO2. Mbio 2, e00122–00111 (2011).PubMed 
PubMed Central 

Google Scholar 
30.Vellend, M. Conceptual Synthesis in Community Ecology. Q Rev. Biol. 85, 183–206 (2010).PubMed 

Google Scholar 
31.Frey, E. Evolutionary game theory: Theoretical concepts and applications to microbial communities. Phys. A 389, 4265–4298 (2010).MathSciNet 
CAS 
MATH 

Google Scholar 
32.Boeuf, D. et al. Biological composition and microbial dynamics of sinking particulate organic matter at abyssal depths in the oligotrophic open ocean. P Natl Acad. Sci. USA 116, 11824 (2019).CAS 

Google Scholar 
33.Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
34.Gralka, M., Szabo, R., Stocker, R. & Cordero, O. X. Trophic Interactions and the Drivers of Microbial Community Assembly. Curr. Biol. 30, R1176–R1188 (2020).CAS 
PubMed 

Google Scholar 
35.Gorter, F. A., Manhart, M. & Ackermann, M. Understanding the evolution of interspecies interactions in microbial communities. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190256 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
36.Gandhi, S. R., Korolev, K. S. & Gore, J. Cooperation mitigates diversity loss in a spatially expanding microbial population. P Natl Acad. Sci. USA 116, 23582–23587 (2019).CAS 

Google Scholar 
37.Calatayud, J. et al. Positive associations among rare species and their persistence in ecological assemblages. Nat. Ecol. Evol. 4, 40–45 (2020).PubMed 

Google Scholar 
38.Furman, O. et al. Stochasticity constrained by deterministic effects of diet and age drive rumen microbiome assembly dynamics. Nat. Commun. 11, 1904 (2020).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
39.Tardy, V. et al. Stability of soil microbial structure and activity depends on microbial diversity. Env. Microbiol. Rep. 6, 173–183 (2014).CAS 

Google Scholar 
40.Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: networks, competition, and stability. Science 350, 663–666 (2015).CAS 
PubMed 
ADS 

Google Scholar 
41.Blanchet, F. G., Cazelles, K. & Gravel, D. Co-occurrence is not evidence of ecological interactions. Ecol. Lett. 23, 1050–1063 (2020).PubMed 

Google Scholar 
42.Blasche, S. et al. Metabolic cooperation and spatiotemporal niche partitioning in a kefir microbial community. Nat. Microbiol. 6, 196–208 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
43.Chatzinikolaou, E. et al. Spatio-temporal benthic biodiversity patterns and pollution pressure in three Mediterranean touristic ports. Sci. Total Environ. 624, 648–660 (2018).CAS 
PubMed 
ADS 

Google Scholar 
44.Filippini, G. et al. Sediment bacterial communities associated with environmental factors in Intermittently Closed and Open Lakes and Lagoons (ICOLLs). Sci. Total Environ. 693, 133462 (2019).CAS 
PubMed 
ADS 

Google Scholar 
45.Pesant, S. et al. Open science resources for the discovery and analysis of Tara Oceans data. Sci. Data 2, 150023 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
46.Huse, S. M. et al. Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. Plos Genet. 4, e1000255 (2008).PubMed 
PubMed Central 

Google Scholar 
47.Salas-González, I. et al. Coordination between microbiota and root endodermis supports plant mineral nutrient homeostasis. Science 371, eabd0695 (2021).PubMed 

Google Scholar 
48.Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. P Natl Acad. Sci. USA 108, 4516 (2011).CAS 
ADS 

Google Scholar 
49.Wear, E. K., Wilbanks, E. G., Nelson, C. E. & Carlson, C. A. Primer selection impacts specific population abundances but not community dynamics in a monthly time-series 16S rRNA gene amplicon analysis of coastal marine bacterioplankton. Environ. Microbiol. 20, 2709–2726 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
50.Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).CAS 
PubMed 

Google Scholar 
51.Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu Rev. Ecol. Syst. 33, 475–505 (2002).
Google Scholar 
52.Wu, L. W. et al. Long-term successional dynamics of microbial association networks in anaerobic digestion processes. Water Res. 104, 1–10 (2016).PubMed 

Google Scholar 
53.Galand, P. E., Casamayor, E. O., Kirchman, D. L. & Lovejoy, C. Ecology of the rare microbial biosphere of the Arctic Ocean. P Natl Acad. Sci. USA 106, 22427–22432 (2009).CAS 
ADS 

Google Scholar 
54.Ju, F. & Zhang, T. Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant. Isme J. 9, 683–695 (2015).CAS 
PubMed 
ADS 

Google Scholar  More

1.Lyson, T. R. et al. Origin of the unique ventilatory apparatus of turtles. Nat. Commun. 5(5211), 1–11. https://doi.org/10.1038/ncomms6211 (2014).CAS 
Article 

Google Scholar 
2.Gans, C. & Hughes, G. The mechanism of lung ventilation in the tortoise Testudo graeca Linné. J. Exp. Biol. 47(1), 1–20 (1967).CAS 
Article 
PubMed 

Google Scholar 
3.Jackson, D. C., Singer, J. H. & Downey, P. T. Oxidative cost of breathing in the turtle Chrysemys picta bellii. Am. J. Physiol. 261, R1325–R1328 (1991).CAS 
PubMed 

Google Scholar 
4.Landberg, T., Mailhot, J. D. & Brainerd, E. L. Lung ventilation during treadmill locomotion in a semi-aquatic turtle, Trachemys scripta. J. Exp. Zool. 311A, 551–562. https://doi.org/10.1002/jez.478 (2009).Article 

Google Scholar 
5.Ruhr, I., Rose, K., Sellers, W., Crossley, D. II. & Codd, J. Turning turtle: Scaling relationships and self-righting ability in Chelydra serpentina. Proc. R. Soc. B. 288, 20210213. https://doi.org/10.1098/rspb.2021.0213 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
6.Pritchard, P. C. H. Encyclopaedia of Turtles (TFH, 1979).
Google Scholar 
7.Carr, A. Handbook of Turtles: The Turtles of the United States, Canada, and Baja California (Cornell University Press, 1952).
Google Scholar 
8.Rivera, G. Ecomorphological variation in shell shape of the freshwater turtle Pseudemys concinna inhabiting different aquatic flow regimes. Int. Comp. Biol. 48(6), 769–787. https://doi.org/10.1093/icb/icn088 (2008).Article 

Google Scholar 
9.McNeill Alexander, R. Gaits of mammals and turtles. J. R. Soc. Jpn. 11(3), 314–319 (1993).Article 

Google Scholar 
10.Zani, P. A. & Kram, R. Low metabolic cost of locomotion in ornate box turtles, Terrapene ornate. J. Exp. Biol. 211, 3671–3676. https://doi.org/10.1242/jeb.019869 (2008).Article 
PubMed 

Google Scholar 
11.Sellers, W. I., Rose, K. A. R., Crossley, D. A. II. & Codd, J. R. Inferring cost of transport from whole-body kinematics in three sympatric turtle species with different locomotor habits. Comp. Biochem. Physiol. A. 247, 110739. https://doi.org/10.1016/j.cbpa.2020.110739 (2020).CAS 
Article 

Google Scholar 
12.Chiari, Y., van der Meijden, A., Caccone, A., Claude, J. & Gilles, B. Self-righting potential and the evolution of shell shape in Galápagos tortoises. Sci. Rep. 7(1), 1–8. https://doi.org/10.1038/s41598-017-15787-7 (2017).CAS 
Article 

Google Scholar 
13.Woledge, R. C. The energetics of tortoise muscle. J. Physiol. 197(3), 685–707 (1968).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
14.Steyermark, A. C. & Spotila, J. R. Body temperature and maternal identity affect snapping turtle (Chelydra serpentina) righting response. Copeia 4, 1050–1057. https://doi.org/10.1643/0045-8511(2001)001[1050:BTAMIA]2.0.CO;2 (2001).Article 

Google Scholar 
15.Rubin, A. M., Blob, R. W. & Mayerl, C. J. Biomechanical factors influencing successful self-righting in the Pleurodire turtle, Emydura subglobosa. J. Exp. Biol. 221, jeb182642. https://doi.org/10.1242/jeb.182642 (2018).Article 
PubMed 

Google Scholar 
16.Penn, D. & Brockmann, H. J. Age-biased stranding and righting in male horseshoe crabs, Limulus polyphemus. Anim. Behav. 49, 1531–1539. https://doi.org/10.1016/003-3472(95)90074-8 (1995).Article 

Google Scholar 
17.Bonnet, X. et al. Sexual dimorphism in steppe tortoises (Testudo horsfieldii): Influence of the environment and sexual selection on body shape and mobility. Biol. J. Linn. Soc. 72, 357–372. https://doi.org/10.1006/bjls.2000.0504 (2001).Article 

Google Scholar 
18.Zuffi, M. A. L. & Corti, C. Aspects of population ecology of Testudo hermanni hermanni from Asinara Island, NW Sardinia (Italy, Western Mediterranean Sea): Preliminary data. Amphib-Reptil. 24, 441–447 (2003).Article 

Google Scholar 
19.Domokos, G. & Várkonyi, P. L. Geometry and self-righting of turtles. Proc. R. Soc. B. 275(1630), 11–17. https://doi.org/10.1098/rspb.2007.1188 (2008).Article 
PubMed 

Google Scholar 
20.Mann, G. K. H., O’Riain, M. J. & Hofmeyr, M. D. Shaping up to fight: Sexual selection influences body shape and size in the fighting tortoise (Chersina angulata). J. Zool. 269, 373–379. https://doi.org/10.1111/j.1469-7998.2006.00079x (2006).Article 

Google Scholar 
21.Golubović, A., Bonnet, X., Djordjević, S., Djurakic, M. & Tomović, L. Variations in righting behavior across Hermann’s tortoise populations. J. Zool. 291, 69–75. https://doi.org/10.1111/jzo.12047 (2013).Article 

Google Scholar 
22.Golubović, A., Andelkovic, M., Arsovski, D., Bonnet, X. & Tomović, L. Locomotor performances reflect habitat constraints in an armoured species. Behav. Ecol. Sociobiol. 71, 93. https://doi.org/10.1007/s00265-017-2318-0 (2017).Article 

Google Scholar 
23.Ashe, V. M. The righting reflex in turtles: A description and comparison. Psychol. Sci. 20, 150–152. https://doi.org/10.3758/BF03335647 (1970).Article 

Google Scholar 
24.Golubović, A., Tomović, L. & Ivanović, A. Geometry of self-righting: The case of Hermann’s tortoises. Zool. Anz. 254, 99–105. https://doi.org/10.1016/j.jcz.2014.12.003 (2015).Article 

Google Scholar 
25.Finkler, M. S. Influence of water availability during hatching on hatchling size, body composition, desiccation tolerance, and terrestrial locomotor performance in the snapping turtle, Chelydra serpentina. Physiol. Biochem. Zool. 72, 714–722. https://doi.org/10.1086/316711 (1999).CAS 
Article 
PubMed 

Google Scholar 
26.Stojadinović, D., Milošević, D. & Crnobrnja-Isailović, J. Righting time versus shell size and shape dimorphism in adult Hermann’s tortoises: Field observations meet theoretical predictions. Anim. Biol. 63(4), 381–396. https://doi.org/10.1163/15707563-00002420 (2013).Article 

Google Scholar 
27.Delmas, V., Baudry, E., Girondot, M. & Prevot-Julliard, A.-C. The righting reflex as a fitness indicator in freshwater turtles. Biol. J. Linn. Soc. 91, 99–109. https://doi.org/10.1111/j.1095-8312/2007.00780.x (2007).Article 

Google Scholar 
28.Burger, J. Behavior of hatchling diamondback terrapins (Malaclemys terrapin) in the field. Copeia 1976, 742. https://doi.org/10.2307/1443457 (1976).Article 

Google Scholar 
29.Landberg, T., Mailhot, J. D. & Brainerd, E. L. Lung ventilation during treadmill locomotion in a terrestrial turtle, Terrapene carolina. J. Exp. Biol. 206, 3391–3404. https://doi.org/10.1242/jeb.00553 (2003).Article 
PubMed 

Google Scholar 
30.Gaunt, A. S. & Gans, C. Mechanics of respiration in the snapping turtle, Chelydra serpentina (Linné). J. Morph. 128, 195–227. https://doi.org/10.1002/jmor.1051280205 (1969).Article 

Google Scholar 
31.Lambertz, M., Böhme, W. & Perry, S. F. The anatomy of the respiratory system in Platysternon megacephalum Gray, 1831 (Testudines: Crytodira) and related species, and its phylogenetic implications. Comp. Biochem. Physiol. 156, 330–336. https://doi.org/10.1016/j.cbpa.2009.12.016 (2010).CAS 
Article 

Google Scholar 
32.de Souza, R. B. B. & Klein, W. The influence of the post-pulmonary septum and submersion on the pulmonary mechanics of Trachemys scripta (Cryptodira: Emydidae). J. Exp. Biol. 224(12), 242386. https://doi.org/10.1242/jeb.242386 (2021).Article 

Google Scholar 
33.Jodice, P. G. R., Epperson, D. M. & Visser, G. H. Daily energy expenditure in free-ranging gopher tortoises (Gopherus polyphemus). Copeia 2006(1), 129–136. https://doi.org/10.1643/0045-8511(2006)006[0129:DEEIFG]2.0.CO;2 (2006).Article 

Google Scholar 
34.Zera, A. J. & Harshman, L. G. The physiology of life history trade-offs in animals. Ann. Rev. Ecol. Syst. 32, 95–126. https://doi.org/10.1146/annurev.ecolsys.32.081501.114006 (2001).Article 

Google Scholar 
35.Shadmehr, R., Huang, H. J. & Ahmed, A. A. A representation of effort in decision-making and motor control. Curr. Biol. 26, 1929–1934. https://doi.org/10.1016/j.cub.2016.05.065 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
36.Shepard, E. L. C. et al. Energy landscapes shapes animal movement ecology. Am. Nat. 182(3), 298–312. https://doi.org/10.1086/671257 (2013).Article 
PubMed 

Google Scholar 
37.Baudinette, R. V., Miller, A. M. & Sarre, M. P. Aquatic and terrestrial locomotory energetics in a toad and a turtle: A search for generalisations among ectotherms. Physiol. Biochem. Zool. 73(6), 672–682. https://doi.org/10.1086/318101 (2000).CAS 
Article 
PubMed 

Google Scholar 
38.Hailey, A. & Coulson, I. M. Measurement of time budgets from continuous observation of thread-trailed tortoises (Kinixys spekii). Herp. J. 9, 15–20 (1999).
Google Scholar 
39.Kram, R. & Taylor, C. R. Energetics of running: A new perspective. Nature 346, 265–267. https://doi.org/10.1038/346265a0 (1990).CAS 
Article 
ADS 
PubMed 

Google Scholar 
40.Taylor, C. R. Relating mechanics and energetics during exercise. Adv. Vet. Sci. Comp. Med. 38A, 181–215 (1994).CAS 
PubMed 

Google Scholar 
41.Cavagna, G. A. & Kaneko, M. Mechanical work and efficiency in level walking and running. J. Physiol. 268(2), 467–481. https://doi.org/10.1113/jphysiol.1977.sp011866 (1977).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
42.Carrier, D. R., Deban, S. M. & Fischbein, T. Locomotor function of the pectoral girdle “muscular sling” in trotting dogs. J. Exp. Biol. 209, 2224–2237. https://doi.org/10.1242/jeb.02236 (2006).Article 
PubMed 

Google Scholar 
43.Heglund, N. C. & Cavagna, G. A. Efficiency of vertebrate locomotory muscles. J. Exp. Biol. 115, 283–292. https://doi.org/10.1242/jeb.115.1.283 (1985).CAS 
Article 
PubMed 

Google Scholar 
44.Barclay, C. J. The basis of difference in thermodynamic efficiency among skeletal muscles. Clin. Exp. Pharm. Physiol. 44(12), 1279–1286. https://doi.org/10.1111/1440-1681.12850 (2017).MathSciNet 
CAS 
Article 

Google Scholar 
45.Nwoye, L. O. & Goldspink, G. Biochemical efficiency and intrinsic shortening speed in selected fast and slow muscles. Experientia 37, 856–857. https://doi.org/10.1007/BF1985678 (1981).CAS 
Article 
PubMed 

Google Scholar 
46.Lambert, M. Temperature, activity and field sighting in the Mediterranean spur-thighed or common garden tortoise Testudo graeca. Biol. Conserv. 21, 39–54. https://doi.org/10.1016/0006-3207(81)90067-7 (1981).Article 

Google Scholar 
47.Tracy, R., Zimmerman, L., Tracy, C., Bradley, K. & Castle, K. Rates of food passage in the digestive tract of young desert tortoises: Effects of body size and diet quality. Chelonian Conserv. Biol. 5(2), 269–273. https://doi.org/10.2744/1071-8443(2006)5[269:ROFPIT]2.0.co;2 (2006).Article 

Google Scholar 
48.Huey, R. & Kingsolver, J. Evolution of thermal sensitivity of ectotherm performance. Trends Ecol. Evol. 4(5), 131–135. https://doi.org/10.1016/0169-5347(89)90211-5 (1989).CAS 
Article 
PubMed 

Google Scholar 
49.Lailvaux, S. & Irschick, D. Effects of temperature and sex on jump performance and biomechanics in the lizard Anolis carolinensis. Funct. Ecol. 21(3), 534–543. https://doi.org/10.1111/j.1365-2435.2007.01263.x (2007).Article 

Google Scholar 
50.Lighton, J. Measuring Metabolic Rates: A Manual for Scientists (Oxford University Press, 2008).Book 

Google Scholar 
51.Brody, S. Bioenergetics and Growth (Reinhold, 1945).
Google Scholar  More

1.Russell, T. L., Beebe, N. W., Cooper, R. D., Lobo, N. F. & Burkot, T. R. Successful malaria elimination strategies require interventions that target changing vector behaviours. Malar J. 12, 56. https://doi.org/10.1186/1475-2875-12-56 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
2.Mouchet, J. et al. Biodiversité du paludisme dans le monde. (Editions John Libbey Eurotext, 2004).3.Sougoufara, S., Ottih, E. C. & Tripet, F. The need for new vector control approaches targeting outdoor biting anopheline malaria vector communities. Parasit Vectors 13, 295. https://doi.org/10.1186/s13071-020-04170-7 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
4.Antonio-Nkondjio, C. et al. Complexity of the malaria vectorial system in Cameroon: contribution of secondary vectors to malaria transmission. J. Med. Entomol. 43, 1215–1221. https://doi.org/10.1093/jmedent/43.6.1215 (2006).Article 
PubMed 

Google Scholar 
5.Afrane, Y. A., Bonizzoni, M. & Yan, G. in Current Topics in Malaria Ch. 20, (2016).6.Goupeyou-Youmsi, J. et al. Differential contribution of Anopheles coustani and Anopheles arabiensis to the transmission of Plasmodium falciparum and Plasmodium vivax in two neighboring villages of Madagascar. bioRxiv 13, 430, https://doi.org/10.1101/787432 (2019).7.Ranson, H. & Lissenden, N. Insecticide resistance in African Anopheles mosquitoes: A worsening situation that needs urgent action to maintain malaria control. Trends Parasitol. 32, 187–196. https://doi.org/10.1016/j.pt.2015.11.010 (2016).CAS 
Article 
PubMed 

Google Scholar 
8.Killeen, G. F. Control of malaria vectors and management of insecticide resistance through universal coverage with next-generation insecticide-treated nets. Lancet 395, 1394–1400. https://doi.org/10.1016/s0140-6736(20)30745-5 (2020).Article 
PubMed 

Google Scholar 
9.Kreppel, K. S. et al. Emergence of behavioural avoidance strategies of malaria vectors in areas of high LLIN coverage in Tanzania. Sci. Rep. 10, 14527. https://doi.org/10.1038/s41598-020-71187-4 (2020).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
10.Chinula, D. et al. Proportional decline of Anopheles quadriannulatus and increased contribution of An. arabiensis to the An. gambiae complex following introduction of indoor residual spraying with pirimiphos-methyl: an observational, retrospective secondary analysis of pre-existing data from south-east Zambia. Parasit Vectors 11, 544, https://doi.org/10.1186/s13071-018-3121-0 (2018).11.Lwetoijera, D. W. et al. Increasing role of Anopheles funestus and Anopheles arabiensis in malaria transmission in the Kilombero Valley, Tanzania. Malar J 13, 331. https://doi.org/10.1186/1475-2875-13-331 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
12.Russell, T. L. et al. Impact of promoting longer-lasting insecticide treatment of bed nets upon malaria transmission in a rural Tanzanian setting with pre-existing high coverage of untreated nets. Malar J. 9, 187. https://doi.org/10.1186/1475-2875-9-187 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
13.Sougoufara, S., Harry, M., Doucoure, S., Sembene, P. M. & Sokhna, C. Shift in species composition in the Anopheles gambiae complex after implementation of long-lasting insecticidal nets in Dielmo, Senegal. Med. Vet. Entomol. 30, 365–368. https://doi.org/10.1111/mve.12171 (2016).CAS 
Article 
PubMed 

Google Scholar 
14.Agyekum, T. P. et al. A systematic review of the effects of temperature on Anopheles mosquito development and survival: Implications for malaria control in a future warmer climate. Int. J. Environ. Res. Public Health 18, 7255 (2021).CAS 
Article 

Google Scholar 
15.Smith, M. W. et al. Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa. Nat. Commun. 11, 4353. https://doi.org/10.1038/s41467-020-18239-5 (2020).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
16.Chemison, A. et al. Impact of an accelerated melting of Greenland on malaria distribution over Africa. Nat. Commun. 12, 3971. https://doi.org/10.1038/s41467-021-24134-4 (2021).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
17.Thomas, C. J., Davies, G. & Dunn, C. E. Mixed picture for changes in stable malaria distribution with future climate in Africa. Trends Parasitol. 20, 216–220. https://doi.org/10.1016/j.pt.2004.03.001 (2004).Article 
PubMed 

Google Scholar 
18.Carnevale, P. & Manguin, S. Review of issues on residual malaria transmission. J. Infect. Dis. 223, S61–S80. https://doi.org/10.1093/infdis/jiab084 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
19.Killeen, G. F., Chaki, P. P., Reed, T. E., Moyes, C. L. & Govella, N. J. in Towards Malaria Elimination – A Leap Forward Ch. 17, (2018).20.Killeen, G. F. Characterizing, controlling and eliminating residual malaria transmission. Malar J. 13, 330. https://doi.org/10.1186/1475-2875-13-330 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
21.Beebe, N. W. DNA barcoding mosquitoes: advice for potential prospectors. Parasitology 145, 622–633. https://doi.org/10.1017/S0031182018000343 (2018).CAS 
Article 
PubMed 

Google Scholar 
22.Lobo, N. F. et al. Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools. Sci. Rep. https://doi.org/10.1038/srep17952 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
23.St Laurent, B. et al. Molecular characterization reveals diverse and unknown malaria vectors in the western Kenyan highlands. Am. J. Trop. Med. Hyg. 94, 327–335. https://doi.org/10.4269/ajtmh.15-0562 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
24.Zhong, D. et al. Extensive new Anopheles cryptic species involved in human malaria transmission in western Kenya. Sci. Rep. 10, 16139. https://doi.org/10.1038/s41598-020-73073-5 (2020).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
25.Killeen, G. F. et al. Developing an expanded vector control toolbox for malaria elimination. BMJ Glob. Health 2, e000211. https://doi.org/10.1136/bmjgh-2016-000211 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
26.Dambach, P. et al. Reduction of malaria vector mosquitoes in a large-scale intervention trial in rural Burkina Faso using Bti based larval source management. Malar J. 18, 311. https://doi.org/10.1186/s12936-019-2951-3 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
27.Fillinger, U. & Lindsay, S. W. Suppression of exposure to malaria vectors by an order of magnitude using microbial larvicides in rural Kenya. Trop. Med. Int. Health 11, 1629–1642. https://doi.org/10.1111/j.1365-3156.2006.01733.x (2006).CAS 
Article 
PubMed 

Google Scholar 
28.Hardy, A., Makame, M., Cross, D., Majambere, S. & Msellem, M. Using low-cost drones to map malaria vector habitats. Parasit Vectors 10, 29. https://doi.org/10.1186/s13071-017-1973-3 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
29.Lwetoijera, D. et al. Effective autodissemination of pyriproxyfen to breeding sites by the exophilic malaria vector Anopheles arabiensis in semi-field settings in Tanzania. Malar J. 13, 161. https://doi.org/10.1186/1475-2875-13-161 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
30.Majambere, S., Lindsay, S. W., Green, C., Kandeh, B. & Fillinger, U. Microbial larvicides for malaria control in The Gambia. Malaria J. https://doi.org/10.1186/1475-2875-6-76 (2007).Article 

Google Scholar 
31.Unlu, I., Faraji, A., Wang, Y., Rochlin, I. & Gaugler, R. Heterodissemination: precision insecticide delivery to mosquito larval habitats by cohabiting vertebrates. Sci. Rep. 11, 14119. https://doi.org/10.1038/s41598-021-93492-2 (2021).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
32.Majambere, S. et al. Is mosquito larval source management appropriate for reducing malaria in areas of extensive flooding in The Gambia? A cross-over intervention trial. Am. J. Trop. Med. Hyg. 82, 176–184. https://doi.org/10.4269/ajtmh.2010.09-0373 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
33.Dongus, S. et al. Participatory mapping of target areas to enable operational larval source management to suppress malaria vector mosquitoes in Dar es Salaam, Tanzania. Int. J. Health Geogr. 6, 37. https://doi.org/10.1186/1476-072X-6-37 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
34.Ferguson, H. M. et al. Ecology: a prerequisite for malaria elimination and eradication. PLoS Med. 7, e1000303. https://doi.org/10.1371/journal.pmed.1000303 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
35.Gu, W., Utzinger, J. & Novak, R. J. Habitat-based larval interventions: A new perspective for malaria control. Am. J. Trop. Med. Hyg. 78, 2–6 (2008).Article 

Google Scholar 
36.Cross, D. E. et al. Geographically extensive larval surveys reveal an unexpected scarcity of primary vector mosquitoes in a region of persistent malaria transmission in western Zambia. Parasit Vectors 14, 91. https://doi.org/10.1186/s13071-020-04540-1 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
37.Orba, Y. et al. First isolation of West Nile virus in Zambia from mosquitoes. Transbound Emerg. Dis. 65, 933–938. https://doi.org/10.1111/tbed.12888 (2018).CAS 
Article 
PubMed 

Google Scholar 
38.Wastika, C. E. et al. Discoveries of exoribonuclease-resistant structures of insect-specific flaviviruses isolated in Zambia. Viruses https://doi.org/10.3390/v12091017 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
39.Hulsman, P., Savenije, H. H. G. & Hrachowitz, M. Satellite-based drought analysis in the Zambezi River Basin: Was the 2019 drought the most extreme in several decades as locally perceived?. J. Hydrol. Reg. Stud. https://doi.org/10.1016/j.ejrh.2021.100789 (2021).Article 

Google Scholar 
40.Hardy, A. et al. Automatic detection of open and vegetated water bodies using Sentinel 1 to map African malaria vector mosquito breeding habitats. Remote Sensing 11, 593. https://doi.org/10.3390/rs11050593 (2019).Article 
ADS 

Google Scholar 
41.Del Rio, T., Groot, J. C. J., DeClerck, F. & Estrada-Carmona, N. Integrating local knowledge and remote sensing for eco-type classification map in the Barotse Floodplain, Zambia. Data Brief 19, 2297–2304. https://doi.org/10.1016/j.dib.2018.07.009 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
42.Timberlake, J. Biodiversity of the Zambezi Basin wetlands: Review and preliminary assessment of available information. IUCN – The World Conservation Union Regional Office for Southern Africa, Harare, Zimbabwe (1997).43.Turpie, J., Smith, B., Emerton, L. & Barnes, J. Economic valuation of the Zambezi basin wetlands. IUCN – The World Conservation Union Regional Office for Southern Africa, Harare, Zimbabwe (1999).44.Ciubotariu, I. I. et al. Genetic diversity of Anopheles coustani in high malaria transmission foci in southern and central Africa. J. Med. Entom. 57, 1–11. https://doi.org/10.1093/jme/tjaa132 (2020).CAS 
Article 

Google Scholar 
45.Jones, C. M. Vector biology and genomics of Anopheles in southern and central Africa PhD thesis, John Hopkins Bloomberg School of Public Health, (2019).46.Stephen, A., Nicholas, K., Busula, A. O., Webale, M. K. & Omukunda, E. Detection of Plasmodium sporozoites in Anopheles coustani s.l; a hindrance to malaria control strategies in highlands of western Kenya. bioRxiv, https://doi.org/10.1101/2021.02.10.430589 (2021).47.Tedrow, R. E. et al. Anopheles mosquito surveillance in Madagascar reveals multiple blood feeding behavior and Plasmodium infection. PLoS Negl. Trop. Dis. 13, e0007176. https://doi.org/10.1371/journal.pntd.0007176 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
48.Taye, B., Lelisa, K., Emana, D., Asale, A. & Yewhalaw, D. Seasonal dynamics, longevity, and biting activity of anopheline mosquitoes in southwestern Ethiopia. J. Insect. Sci. https://doi.org/10.1093/jisesa/iev150 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
49.Sikaala, C. H. et al. A cost-effective, community-based, mosquito-trapping scheme that captures spatial and temporal heterogeneities of malaria transmission in rural Zambia. Malar J. 13, 225. https://doi.org/10.1186/1475-2875-13-225 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
50.De Meillon, B. The anophelini of the Ethiopian geographical region. Publ. South Afr. Inst. Med. Res. 49, 1–272 (1947).
Google Scholar 
51.Gillies, M. T. & De Meillon, B. The Anophelinae of Africa south of the Sahara (Ethiopian Zoogeographical Region). Publ. South Afr. Inst. Med. Res. 54, 1–343 (1968).
Google Scholar 
52.Dida, G. O. et al. Spatial distribution and habitat characterization of mosquito species during the dry season along the Mara River and its tributaries, in Kenya and Tanzania. Infect. Dis. Poverty 7, 2. https://doi.org/10.1186/s40249-017-0385-0 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
53.Njoroge, M. M. et al. Exploring the potential of using cattle for malaria vector surveillance and control: a pilot study in western Kenya. Parasit Vectors 10, 18. https://doi.org/10.1186/s13071-016-1957-8 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
54.Kibret, S. et al. The impact of a small-scale irrigation scheme on malaria transmission in Ziway area, Central Ethiopia. Trop. Med. Int. Health 15, 41–50. https://doi.org/10.1111/j.1365-3156.2009.02423.x (2010).Article 
PubMed 

Google Scholar 
55.Coetzee, M. Anopheles crypticus, new species from South Africa is distinguished from Anopheles coustani (Diptera: Culicidae). Mosq. Syst. 26, 125–131 (1994).
Google Scholar 
56.Gillies, M. T. & Coetzee, M. A supplement to the Anophelinae of Africa south of the Sahara (Afrotropical Region). Publ. South Afr. Inst. Med. Res. 55, 1–143 (1987).
Google Scholar 
57.Coetzee, M. Key to the females of Afrotropical Anopheles mosquitoes (Diptera: Culicidae). Malar J. 19, 70. https://doi.org/10.1186/s12936-020-3144-9 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
58.Carter, T. E., Yared, S., Hansel, S., Lopez, K. & Janies, D. Sequence-based identification of Anopheles species in eastern Ethiopia. Malar J. 18, 135. https://doi.org/10.1186/s12936-019-2768-0 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
59.Degefa, T. et al. Indoor and outdoor malaria vector surveillance in western Kenya: implications for better understanding of residual transmission. Malar J. 16, 443. https://doi.org/10.1186/s12936-017-2098-z (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
60.Nepomichene, T. N. J. J., Tata, E. & Boyer, S. Malaria case in Madagascar, probable implication of a new vector, Anopheles coustani. Malaria J. 14, 475. https://doi.org/10.1186/s12936-015-1004-9 (2015).CAS 
Article 

Google Scholar 
61.Finney, M. et al. Widespread zoophagy and detection of Plasmodium spp. in Anopheles mosquitoes in southeastern Madagascar. Malar J. 20, 25. https://doi.org/10.1186/s12936-020-03539-4 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
62.Mwangangi, J. M. et al. The role of Anopheles arabiensis and Anopheles coustani in indoor and outdoor malaria transmission in Taveta District, Kenya. Parasit Vectors 6, 114. https://doi.org/10.1186/1756-3305-6-114 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
63.Hoffman, J. E. et al. Phylogenetic complexity of morphologically identified Anopheles squamosus in southern Zambia. Insects 12, 146. https://doi.org/10.3390/insects12020146 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
64.Fornadel, C. M., Norris, L. C., Franco, V. & Norris, D. E. Unexpected anthropophily in the potential secondary malaria vectors Anopheles coustani s.l. and Anopheles squamosus in Macha, Zambia. Vector Borne Zoonotic Dis. 11, 1173–1179. https://doi.org/10.1089/vbz.2010.0082 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
65.Wilkes, T. J., Matola, Y. G. & Charlwood, J. D. Anopheles rivulorum, a vector of human malaria in Africa. Med. Vet. Entomol. 10, 108–110. https://doi.org/10.1111/j.1365-2915.1996.tb00092.x (1996).CAS 
Article 
PubMed 

Google Scholar 
66.Majambere, S., Fillinger, U., Sayer, D. R., Green, C. & Lindsay, S. W. Spatial distribution of mosquito larvae and the potential for targeted larval control in The Gambia. Am. J. Trop. Med. Hyg. 79, 19–27 (2008).Article 

Google Scholar 
67.Thomas, C. J., Cross, D. E. & Bogh, C. Landscape movements of Anopheles gambiae malaria vector mosquitoes in rural Gambia. PLoS ONE https://doi.org/10.1371/journal.pone.0068679 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
68.Hardy, A. J. et al. Habitat hydrology and geomorphology control the distribution of malaria vector larvae in rural Africa. PLoS ONE 8, e81931. https://doi.org/10.1371/journal.pone.0081931 (2013).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
69.Kent, R. J., Thuma, P. E., Mharakurwa, S. & Norris, D. E. Seasonality, blood feeding behavior, and transmission of Plasmodium falciparum by Anopheles arabiensis after an extended drought in southern Zambia. Am. J. Trop. Med. Hyg. 76, 267–274 (2007).Article 

Google Scholar 
70.Imbahale, S. S. et al. A longitudinal study on Anopheles mosquito larval abundance in distinct geographical and environmental settings in western Kenya. Malar J. 10, 81. https://doi.org/10.1186/1475-2875-10-81 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
71.Bayoh, M. N. et al. Anopheles gambiae: historical population decline associated with regional distribution of insecticide-treated bed nets in western Nyanza Province, Kenya. Malar J. 9, 62. https://doi.org/10.1186/1475-2875-9-62 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
72.Mawejje, H. D. et al. Impact of seasonality and malaria control interventions on Anopheles density and species composition from three areas of Uganda with differing malaria endemicity. Malar J. 20, 138. https://doi.org/10.1186/s12936-021-03675-5 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
73.Stevenson, J. C. et al. Spatio-temporal heterogeneity of malaria vectors in northern Zambia: Implications for vector control. Parasit Vectors 9, 510. https://doi.org/10.1186/s13071-016-1786-9 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
74.Dabire, K. R. et al. Year to year and seasonal variations in vector bionomics and malaria transmission in a humid savannah village in west Burkina Faso. J. Vector Ecol. 33, 70–75. https://doi.org/10.3376/1081-1710(2008)33[70:ytyasv]2.0.co;2 (2008).CAS 
Article 
PubMed 

Google Scholar 
75.Tuno, N., Githeko, A., Yan, G. & Takagi, M. Interspecific variation in diving activity among Anopheles gambiae Giles, An. arabiensis Patton, and An. funestus Giles (Diptera: Culicidae) larvae. J. Vector Ecol. 32, 112–117. https://doi.org/10.3376/1081-1710(2007)32[112:ividaa]2.0.co;2 (2007).Article 
PubMed 

Google Scholar 
76.Nambunga, I. H. et al. Aquatic habitats of the malaria vector Anopheles funestus in rural south-eastern Tanzania. Malar J. 19, 219. https://doi.org/10.1186/s12936-020-03295-5 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
77.Ageep, T. B. et al. Spatial and temporal distribution of the malaria mosquito Anopheles arabiensis in northern Sudan: influence of environmental factors and implications for vector control. Malar J. 8, 123. https://doi.org/10.1186/1475-2875-8-123 (2009).Article 
PubMed 
PubMed Central 

Google Scholar 
78.Kweka, E. J. et al. Anopheline larval habitats seasonality and species distribution: a prerequisite for effective targeted larval habitats control programmes. PLoS ONE 7, e52084. https://doi.org/10.1371/journal.pone.0052084 (2012).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
79.Libanda, B. & Ngonga, C. Projection of frequency and intensity of extreme precipitation in Zambia: a CMIP5 study. Climate Res. 76, 59–72. https://doi.org/10.3354/cr01528 (2018).Article 
ADS 

Google Scholar 
80.Zimba, H. et al. Assessment of trends in inundation extent in the Barotse Floodplain, upper Zambezi River Basin: A remote sensing-based approach. J. Hydrol. Reg. Stud. 15, 149–170. https://doi.org/10.1016/j.ejrh.2018.01.002 (2018).Article 

Google Scholar 
81.Hamududu, B. H. & Killingtveit, A. Hydropower production in future climate scenarios; the case for the Zambezi River. Energies https://doi.org/10.3390/en9070502 (2016).Article 

Google Scholar 
82.IUCN. Barotse Floodplain, Zambia: Local economic dependence on wetland resources. IUCN – The World Conservation Union, Harare, Zimbabwe (2003).83.Moore, A. E., Cotterill, F.P.D., Main, M.P.L., Williams, H.B. in Large Rivers: Geomorphology and Management (ed Avijit Gupta) Ch. 15, (Wiley, 2007).84.Heyden, C. J. V. D. The hydrology and hydrogeology of dambos: a review. Prog. Phys. Geog. 28, 544–564. https://doi.org/10.1191/0309133304pp424oa (2004).Article 

Google Scholar 
85.Derua, Y. A. et al. Change in composition of the Anopheles gambiae complex and its possible implications for the transmission of malaria and lymphatic filariasis in north-eastern Tanzania. Malaria J. https://doi.org/10.1186/1475-2875-11-188 (2012).Article 

Google Scholar 
86.Kröckel, U., Rose, A., Eiras, Á. E. & Geier, M. New tools for surveillance of adult yellow fever mosquitoes: comparison of trap catches with human landing rates in an urban environment. J. Am. Mosq. Control Assoc. 22, 229–238. https://doi.org/10.2987/8756-971x(2006)22[229:Ntfsoa]2.0.Co;2 (2006).Article 
PubMed 

Google Scholar 
87.Gama, R. A., Silva, I. M., Geier, M. & Eiras, A. E. Development of the BG-Malaria trap as an alternative to human-landing catches for the capture of Anopheles darlingi. Mem. Inst. Oswaldo Cruz 108, 763–771. https://doi.org/10.1590/0074-0276108062013013 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
88.Ribeiro, J. M., Seulu, F., Abose, T., Kidane, G. & Teklehaimanot, A. Temporal and spatial distribution of anopheline mosquitos in an Ethiopian village: implications for malaria control strategies. Bull. World Health Organ. 74, 299–305 (1996).CAS 
PubMed 
PubMed Central 

Google Scholar 
89.Russell, T. L. et al. Geographic coincidence of increased malaria transmission hazard and vulnerability occurring at the periphery of two Tanzanian villages. Malar J. 12, 24. https://doi.org/10.1186/1475-2875-12-24 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
90.Smith, D. L., Dushoff, J. & McKenzie, F. E. The risk of a mosquito-borne infection in a heterogeneous environment. PLoS Biol. 2, e368. https://doi.org/10.1371/journal.pbio.0020368 (2004).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
91.Midega, J. T. et al. Wind direction and proximity to larval sites determines malaria risk in Kilifi District in Kenya. Nat. Commun. 3, 674. https://doi.org/10.1038/ncomms1672 (2012).CAS 
Article 
PubMed 
ADS 

Google Scholar 
92.Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. https://doi.org/10.1093/molbev/msy096 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
93.Singh, B. et al. A genus- and species-specific nested polymerase chain reaction malaria detection assay for epidemiologic studies. Am. J. Trop. Med. Hyg. 60, 687–692. https://doi.org/10.4269/ajtmh.1999.60.687 (1999).CAS 
Article 
PubMed 

Google Scholar 
94.QGIS Geographic Information System (Open Source Geospatial Foundation Project, 2021).95.Postma, M. & Goedhart, J. PlotsOfData – A web app for visualizing data together with their summaries. PLoS Biol 17, e3000202. https://doi.org/10.1371/journal.pbio.3000202 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
96.IBM SPSS Statistics for Windows, Version 25.0 (Armonk, NY, 2017).97.Rita, H. & Komonen, A. Odds ratio: an ecologically sound tool to compare proportions. Ann. Zool. Fenn. 45, 66–72. https://doi.org/10.5735/086.045.0106 (2008).Article 

Google Scholar  More

Description of study areasIGR plant (33° 42/N, 46° 13/E) is located along the edge of the mountains of Zagros forests and 25 km from Ilam city. Its main activity, to supply gas to the western provinces of Iran, started in 2007. It converts sour gas to sweet gas and also produces various products such as pastil sulfur, ethane, and liquefied gas. The refinery has two chimneys, which release waste gases into the atmosphere. Oak trees are the main tree species of the Zagros forests around the refinery; these are exposed to various air pollutants and different elements from this source. Based on random analysis of exhaust emissions, sulfur dioxide and sulfide hydrogen are the major pollutants emitted from the flare gases of this refinery plant34. The sampling points have an average altitude of about 1000–1250 m and a slope of less than 20%. The climate of the region is semiarid and influenced by Mediterranean winds. The predominant wind direction was west and southwest. The highest and lowest air temperatures were 41.4 °C and − 11.3 °C, respectively. The average annual rainfall was 71.94 mm (http://www.amarilam.ir).Samples collection and analysesAll methods were carried out in accordance with the relevant institutional, national, and international guidelines and legislation. Besides they were discussed and approved by the Research Ethics Committee of Tarbiat Modares University. The formal identification of the Quercus brantii Lindl. was performed by H. Dadkhah-Aghdash based on colorful Flora of Iran35. The permissions or licenses to collect Brant oak (Quercus brantii Lindl.) trees in Zagros forests were obtained. A voucher specimen of Brant oaks were collected and deposited at the Herbarium of department of Plant Biology of Tarbiat Modares University.We studied different distances (1000, 1500, 2000, 2500, and 10,000 m [control]) in an easterly direction from the gas refinery. The map of study area was drawn by software of ArcGIS version of 10.5, https://desktop.arcgis.com (Fig. 5). At each distance, three soil samples taken from the depth of 0–20 cm with a plastic gardening shovel, 30 healthy and mature leaves were collected from a certain height (nearly the middle of the canopy) and the outer canopy of three Brant oak trees in the late spring, summer, and autumn of 2019. These trees with average height and diameter at breast height of 5.5 m and 45 cm were selected randomly. The leaf and soil samples were put into polyethylene bags and transported to the laboratory for analysis36.Figure 5Locations of collection sites of soil samples and Brant oak leaves at five different distances (1000, 1500, 2000, 2500 and 10,000 m [control]) from the gas refinery (drawn by H. Dadkhah-Aghdash using software of ArcGIS Desktop. version of 10.5. ESRI, California, US. https://desktop.arcgis.com).Full size imageIn the lab, firstly the leaves were categorized into two types: unwashed leaves and leaves washed with ethylenediaminetetraacetic acid (EDTA) solution to remove some atmospheric dusts and particles deposition. The leaf and soil samples were dried for 10 days until they reached a constant weight at lab temperature. The leaves were grinded and homogenized, soils were sieved with ASTM mesh (DAMAVAND, Iran) with a diameter of 2 mm and homogenized.To determine the pH and electrical conductivity (EC) of soils, 2 g of the soil samples were shaken in 10 ml of double-distilled water with a ratio of 1:5; after 1 h, the pH and electrical conductivity (EC) of the solution were measured by a digital pH meter (Fan Azma Gostar Company, Iran) and EC meter (Sartorius, PT-20, USA). The analysis of the particle sizes of the soil was carried out using the hydrometer method and texture class was determined with a soil texture triangle37.According to different U.S.EPA protocols that were modified by following references, the soil and leaf samples were prepared and dissolved. The digestion of soil samples was conducted with a mixture of concentrated HF–HClO4–HNO338. Approximately 0.5 g of dry soil sample was digested with 10 mL of HCl on a hot plate at ~ 180 °C until the solution was reduced to 3 mL. Approximately 5 mL of HF (40%, w/w), 5 mL of HNO3 (63%, w/w), and 3 mL of HClO4 (70%, w/w) were then added and the solution was digested. This process was continued with adding 3 mL of HNO3, 3 mL of HF, and 1 mL of HClO4 until the silicate minerals had fully disappeared. This solution was transferred to a 25 mL volumetric tube, and 1% HNO3 was added to bring the sample up to a constant volume for the element’s determinations. After filtering the digested samples, the concentrations of sulfur (S), arsenic (As), chromium (Cr), copper (Cu), lead (Pb), zinc (Zn), manganese (Mn), and nickel (Ni) were measured via inductively coupled plasma mass spectrometry (ICP-MS,7500 CS, Agilent, US). The procedures of quality assurance and quality control (QA/QC) were performed.To quantify element contents from soil samples, external standards with calibration levels were used. The precision and the repeatability of the analysis were tested on the instrument by analyzing three replicate samples.According to Liang et al.39 leaf samples were acid digested and sieved powder samples were placed in the acid-washed tubes and 10 mL of 65% nitric acid was added to it. The solution was placed at room temperature overnight (12 h) after that, it was placed for 4 h at 100 °C and then 4 h at 140 °C until the solution color was clear. After cooling, the solution was diluted by deionized water to 50 mL and then passed through Whatman filter paper until 25 mL of the filtrate volume was provided. Each sample was digested three times and the average of measurements is reported. Total plant elements were measured by using the ICP-MS (7500 CS, Agilent, US). A control sample was also used beside each sample to determine the background pollution during digestion. To confirm the accuracy of the methodology and to ensure the extraction of trace elements from the leaf samples, the standard solution of each studied elements was used.Measuring of pollution levels of different elements in soils and leavesFor assessment of contamination levels (concentration) of different elements in soils and trees, common indices of pollution including geoaccumulation index (Igeo), pollution index (PI), pollution load index (PLI), enrichment factor of plants (EFplant), bioconcentration factor (BCF), air originated metals (AOM ), metal accumulation index (MAI) were used.Igeo was calculated using the following (Eq. 1):$${text{I}}_{{{text{geo}}}} = log_{2} left[ {{text{C}}_{{text{n}}} / 1.5{text{ B}}_{{text{n}}} } right]$$
(1)
where Cn is the measured concentration of the element n, Bn is the geoaccumulation background for this element and 1.5 is a constant coefficient used to eliminate potential variations in the baseline data40. The Igeo classifies samples into seven grades:  5 for extremely polluted30.The first PI is expressed as (Eq. 2):$${text{PI }} = {text{ C}}_{{text{i}}} /{text{S}}_{{text{i}}}$$
(2)
where Ci is the concentration of element i in the soil (mg kg−1) and Si is the soil quality standard or reference value for element i (mg kg−1). The PLI for different elements is calculated via the (Eq. 3):$${text{PLI}} = left( {{text{PI}}_{{1}} times {text{ PI}}_{{2}} times {text{ PI}}_{{3}} times cdots times {text{PI}}_{{text{n}}} } right)^{{{1}/{text{n}}}}$$
(3)
The PLI of soils is classified as follows: PLI  More

Environmental variable quantification along an altitudinal gradientThis study area included 22 sampling sites, and 66 samples, classified into three transects, namely Transect 1 (1047–1587 m), Transect 2 (876–3070 m), and Transect 3 (1602–2110 m). Significant differences in soil properties and plant parameters were observed along the three studied altitudinal transects (P  0.05%, while the remaining bacteria were merged into an “others” class. As shown in Fig. 1B, the proportion of Actinobacteria, Alphaproteobacteria and Gammaproteobacteria at each elevation was 45%, whereas Deltaproteabacteria, Acidobacteria_Subgroup_6, and Gemmatimonadetes were prevalent at low levels in most soil samples. At the genus level (Supplementary Fig. 1), 76 genera were detected in the research areas, with the dominant genera including norank_f_67-14_ o_Solirubrobacterales (5.72%), Rubrobacter (4.35%), Solirubrobacter (2.83%), Pseudonocardia (2.26%) and Bradyrhizobium (2.19%) and less than 0.01% of the bacterial genera were classified into others.Figure 1Bacterial community composition variations at the phylum (A) and class (B) levels in soil samples collected at different levels. These were done in R (v3.3.1, http://www.R-project.org).Full size imageBacterial community composition varies along elevation gradientsWe next sought to analyze the differences in relative bacterial abundance at the phylum level among Transects 1–3 (Fig. 2). Significant differences in the relative abundance of Actinobacteria, Proteobacteria, Acidobacteria, Verrucomicrobia, Firmicutes, and Rokubacteria were detected in samples from the different transects (Fig. 2A). The relative abundance of Actinobacteria and Firmicutes in Transect 1 (48.64% and 1.89%, respectively) was significantly higher than in Transect 2 (38.43% and 1.49%, respectively) and Transect 3 (39.63% and 0.98%, respectively) (P  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.Carter, D. O., Yellowlees, D. & Tibbett, M. Cadaver decomposition in terrestrial ecosystems. Naturwissenschaften 94(1), 12–24 (2007).ADS 
CAS 
PubMed 

Google Scholar 
2.Weathers, K. C., Strayer, D. L. & Likens, G. E. Fundamentals of Ecosystem Science (Academic Press, 2012).
Google Scholar 
3.Payne, J. A. A summer carrion study of the baby pig Sus scrofa Linnaeus. Ecology 46(5), 592–602 (1965).
Google Scholar 
4.Anderson, G. S., Cervenka, V. J., Haglund, W. & Sorg, M. Insects associated with the body: Their use and analyses. Adv. Forens. Taphonomy 2, 1 (2002).
Google Scholar 
5.Smith, K. G. A manual of forensic entomology. (1986).6.Tomberlin, J. K., Benbow, M. E., Tarone, A. M. & Mohr, R. M. Basic research in evolution and ecology enhances forensics. Trends Ecol. Evol. 26(2), 53–55 (2011).PubMed 

Google Scholar 
7.Benbow, M. E., Tomberlin, J. K. & Tarone, A. M. Carrion Ecology, Evolution, and Their Applications (CRC Press, 2015).
Google Scholar 
8.Wilson, E. E., Mullen, L. M. & Holway, D. A. Life history plasticity magnifies the ecological effects of a social wasp invasion. Proc. Natl. Acad. Sci. 106(31), 12809–12813 (2009).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
9.Pechal, J. L. et al. Field documentation of unusual post-mortem arthropod activity on human remains. J. Med. Entomol. 52(1), 105–108 (2015).PubMed 

Google Scholar 
10.Campobasso, C. P., Marchetti, D., Introna, F. & Colonna, M. F. Postmortem artifacts made by ants and the effect of ant activity on decompositional rates. Am. J. Forens. Med. Pathol. 30(1), 84–87 (2009).
Google Scholar 
11.Eubanks, M. D., Lin, C. & Tarone, A. M. The role of ants in vertebrate carrion decomposition. Food Webs 18, e00109 (2019).
Google Scholar 
12.Cornaby, B. W. Carrion reduction by animals in contrasting tropical habitats. Biotropica 2, 51–63 (1974).
Google Scholar 
13.Andrade-Silva, J., Pereira, E. K. C., Silva, O., Delabie, J. H. C. & Rebelo, J. M. M. Ants (Hymenoptera: Formicidae) associated with pig carcasses in an urban area. Sociobiology 62(4), 527–532 (2015).
Google Scholar 
14.Chin, H. C. et al. Ants (Hymenoptera: Formicidae) associated with pig carcasses in Malaysia. Trop. Biomed. 26(1), 106–109 (2009).
Google Scholar 
15.Prado Castro, C., García, M. D., Palma, C. & Martínez-Ibáñez, M. D. First report on sarcosaprophagous Formicidae from Portugal (Insecta: Hymenoptera). Annales de la Société entomologique de France 50(1), 51–58 (2014).
Google Scholar 
16.Neto-Silva, A., Dinis-Oliveira, R. J. & Prado e Castro, C.,. Diversity of the Formicidae (Hymenoptera) carrion communities in Lisbon (Portugal): Preliminary approach as seasonal and geographic indicators. Forens. Sci. Res. 3(1), 65–73 (2018).
Google Scholar 
17.Payne, J. A., King, E. W. & Beinhart, G. Arthropod succession and decomposition of buried pigs. Nature 219(5159), 1180–1181 (1968).ADS 
CAS 
PubMed 

Google Scholar 
18.Meyer, F., Monroe, M. D., Williams, H. N. & Goddard, J. Solenopsis invicta x richteri (Hymenoptera: Formicidae) necrophagous behavior causes post-mortem lesions in pigs which serve as oviposition sites for Diptera. Forens. Sci. Int. Rep. 2, 100067 (2020).
Google Scholar 
19.De Jong, G. D., Meyer, F. & Goddard, J. Relative roles of blow flies (Diptera: Calliphoridae) and invasive fire ants (Hymenoptera: Formicidae: Solenopsis spp.) in carrion decomposition. J. Med. Entomol. 58(3), 1074–1082 (2021).PubMed 

Google Scholar 
20.Early, M. & Goff, M. L. Arthropod succession patterns in exposed carrion on the island of O’ahu, Hawaiian Islands, USA. J. Med. Entomol. 23(5), 520–531 (1986).CAS 
PubMed 

Google Scholar 
21.Stoker, R. L., Grant, W. E. & Bradleigh Vinson, S. Solenopsis invicta (Hymenoptera: Formicidae) effect on invertebrate decomposers of carrion in central Texas. Environ. Entomol. 24(4), 817–822 (1995).
Google Scholar 
22.Ekanem, M. S. & Dike, M. C. Arthropod succession on pig carcasses in southeastern Nigeria. Papeis Avulsos de Zoologia 50, 561–570 (2010).
Google Scholar 
23.Lindgren, N. K., Bucheli, S. R., Archambeault, A. D. & Bytheway, J. A. Exclusion of forensically important flies due to burying behavior by the red imported fire ant (Solenopsis invicta) in southeast Texas. Forensic Sci. Int. 204(1–3), e1–e3 (2011).PubMed 

Google Scholar 
24.Pereira, E. K. C. et al. Solenopsis saevissima (Smith) (Hymenoptera: Formicidae) activity delays vertebrate carcass decomposition. Sociobiology 64(3), 369–372 (2017).
Google Scholar 
25.Dussutour, A. & Simpson, S. J. Description of a simple synthetic diet for studying nutritional responses in ants. Insectes Soc. 55(3), 329–333 (2008).
Google Scholar 
26.Csata, E. & Dussutour, A. Nutrient regulation in ants (Hymenoptera: Formicidae): A review. Myrmecol. News 29, 111–124 (2019).
Google Scholar 
27.Tschinkel, W. R. The Fire Ants (Belknap Press, 2013).
Google Scholar 
28.Paula, M. C. et al. Action of ants on vertebrate carcasses and blow flies (Calliphoridae). J. Med. Entomol. 53(6), 1283–1291 (2016).PubMed 

Google Scholar 
29.Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9(2), 378–400 (2017).
Google Scholar 
30.Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.2 4, (2019).31.Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage publications, 2018).
Google Scholar 
32.Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biometr. J. 50(3), 346–363 (2008).MathSciNet 
MATH 

Google Scholar 
33.Porter, S. D., Bhatkar, A., Mulder, R., Vinson, B. S. & Clair, D. J. Distribution and density of polygyne fire ants (Hymenoptera: Formicidae) in Texas. J. Econ. Entomol. 84(3), 866–874 (1991).CAS 
PubMed 

Google Scholar 
34.Cook, S. C., Eubanks, M. D., Gold, R. E. & Behmer, S. T. Colony-level macronutrient regulation in ants: mechanisms, hoarding and associated costs. Anim. Behav. 79(2), 429–437 (2010).
Google Scholar 
35.Smith, C. R. & Tschinkel, W. R. Ant fat extraction with a Soxhlet extractor. Cold Spring Harbor Protocols 7, 5243 (2009).
Google Scholar 
36.Wills, B. D. et al. Effect of carbohydrate supplementation on investment into offspring number, size, and condition in a social insect. PLoS ONE 10(7), e0132440 (2015).PubMed 
PubMed Central 

Google Scholar 
37.Bockoven, A. A., Wilder, S. M. & Eubanks, M. D. Intraspecific variation among social insect colonies: persistent regional and colony-level differences in fire ant foraging behavior. PLoS ONE 10(7), e0133868 (2015).PubMed 
PubMed Central 

Google Scholar 
38.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 67(1), 1–48 (2015).
Google Scholar 
39.Gavilanez-Slone, J. & Porter, S. D. Colony growth of two species of Solenopsis fire ants (Hymenoptera: Formicidae) reared with crickets and beef liver. Florida Entomol. 96(4), 1482–1488 (2013).
Google Scholar 
40.Sorensen, A. A., Busch, T. M. & Vinson, S. B. Factors affecting brood cannibalism in laboratory colonies of the imported fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae). J. Kansas Entomol. Soc. 2, 140–150 (1983).
Google Scholar 
41.Williams, D. F., Vander Meer, R. K. & Lofgren, C. S. Diet-induced nonmelanized cuticle in workers of the imported fire ant Solenopsis invicta Buren. Arch. Insect Biochem. Physiol. 4(4), 251–259 (1987).CAS 

Google Scholar 
42.Porter, S. D. Effects of diet on the growth of laboratory fire ant colonies (Hymenoptera: Formicidae). J. Kansas Entomol. Soc. 2, 288–291 (1989).
Google Scholar 
43.Bhatkar, A. & Whitcomb, W. H. Artificial diet for rearing various species of ants. Florida Entomol. 2, 229–232 (1970).
Google Scholar 
44.Porter, S. D., Valles, S. M. & Gavilanez-Slone, J. M. Long-term efficacy of two cricket and two liver diets for rearing laboratory fire ant colonies (Hymenoptera: Formicidae: Solenopsis invicta). Florida Entomol. 98(3), 991–993 (2015).
Google Scholar 
45.Arganda, S. et al. Parsing the life-shortening effects of dietary protein: Effects of individual amino acids. Proc. R. Soc. B Biol. Sci. 284(1846), 20162052 (2017).
Google Scholar 
46.Tschinkel, W. R. Sociometry and sociogenesis of colonies of the fire ant Solenopsis Invicta during one annual cycle. Ecol. Monogr. 63(4), 425–457 (1993).
Google Scholar 
47.Deslippe, R. J. & Savolainen, R. Sex investment in a social insect: The proximate role of food. Ecology 76(2), 375–382 (1995).
Google Scholar 
48.Rosenfeld, C. S. & Roberts, R. M. Maternal diet and other factors affecting offspring sex ratio: A review. Biol. Reprod. 71(4), 1063–1070 (2004).CAS 
PubMed 

Google Scholar 
49.Hasegawa, E. Sex allocation in the ant Camponotus (Colobopsis) nipponicus (Wheeler): II. The effect of resource availability on sex-ratio variability. Insectes Soc. 60(3), 329–335 (2013).
Google Scholar 
50.Knaden, M. & Graham, P. The sensory ecology of ant navigation: from natural environments to neural mechanisms. Annu. Rev. Entomol. 61, 63–76 (2016).CAS 
PubMed 

Google Scholar 
51.Liu, W., Longnecker, M., Tarone, A. M. & Tomberlin, J. K. Responses of Lucilia sericata (Diptera: Calliphoridae) to compounds from microbial decomposition of larval resources. Anim. Behav. 115, 217–225 (2016).
Google Scholar 
52.Tomberlin, J. K. et al. Indole: An evolutionarily conserved influencer of behavior across kingdoms. BioEssays 39(2), 1600203 (2017).
Google Scholar 
53.Frederickx, C. et al. Volatile organic compounds released by blowfly larvae and pupae: New perspectives in forensic entomology. Forensic Sci. Int. 219(1–3), 215–220 (2012).CAS 
PubMed 

Google Scholar 
54.Frederickx, C., Dekeirsschieter, J., Verheggen, F. J. & Haubruge, E. Host-habitat location by the parasitoid, Nasonia vitripennis Walker (Hymenoptera: Pteromalidae). J. Forensic Sci. 59(1), 242–249 (2014).CAS 
PubMed 

Google Scholar 
55.Schettino, M. et al. Response of a predatory ant to volatiles emitted by aphid-and caterpillar-infested cucumber and potato plants. J. Chem. Ecol. 43(10), 1007–1022 (2017).CAS 
PubMed 

Google Scholar 
56.Sawyer, S. J., Rusch, T. W., Tarone, A. M. & Tomberlin, J. K. Wing buzzing as a potential antipredator defense against an invasive predator. Food Webs 27, e00192 (2021).
Google Scholar 
57.Wells, J. D. & Greenberg, B. Effect of the red imported fire ant (Hymenoptera: Formicidae) and carcass type on the daily occurrence of postfeeding carrion-fly larvae (Diptera: Calliphoridae, Sarcophagidae). J. Med. Entomol. 31(1), 171–174 (1994).CAS 
PubMed 

Google Scholar  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