Ecology

Specimens examined
Seven Australian genetic strains (clonal genotypes) of phylloxera were assessed in this project: G1, G4, G7, G19, G20, G30 and G38; genotype numbers follow14. These strains were obtained from live insect colonies maintained by Agriculture Victoria Rutherglen, Victoria. Root aphids, mealybugs and other non-target invertebrates were collected from vineyards for assay specificity testing. Additional aphids, from grass and vegetable host plants, as well as Phylloxeroidea (Adelges spp. and Pineus sp.) from pine trees, were also collected to create a comprehensive Aphidomorpha (Phylloxeroidea/Aphidoidea) species panel to test the specificity of the new LAMP assay.
Phylloxera DNA extractions and molecular variation
DNA was extracted from 100% ethanol preserved whole phylloxera adult, crawler, and eggs (destructive extraction method) using a DNeasy Blood and Tissue extraction kit (Qiagen, Australia), following the manufacturers protocol. The DNA concentrations were quantified using a Qubit 2.0 Flourometer (Invitrogen, Life Technologies, Australia) following the manufacturers protocol and stored at − 20 °C. These samples provided “clean” DNA preparations to use for phylloxera DNA barcoding, to assess Cytochrome Oxidase I (COI) genetic variation between strains, and for development of the LAMP assay.
All specimens, both phylloxera and the non-target invertebrates, were identified morphologically, prior to DNA extraction, followed by molecular identification using standard DNA barcoding methods7,17. DNA sequences from the 5′ region of the COI locus were obtained using LCO1490 / HCO2198 primers19. The thermal cycling conditions consisted of a PCR amplification profile of: 2 min at 94 °C, 40 cycles of at 94 °C for 30 s, 50 °C for 45 s and 72 °C for 45 s, and a final extension of 2 min at 72 °C.
PCR amplicons were sanger sequenced by Macrogen Inc. (Seoul, Korea) and sequences were compared to public databases (NCBI and BOLD), to determine similarity (i.e.  > 99% matches) with previously identified reference species. DNA sequences from the laboratory strains of phylloxera were used to develop phylloxera specific LAMP primers in this research.
An additional in-field compatible non-destructive DNA extraction method for “crude” DNA extractions was tested. Intact specimens of phylloxera (egg, crawler, and adult) were processed using a modified HotSHOT protocol “HS6” from20. There are several variations of HotSHOT method which have been used previously to extract DNA from mice (HS4)16 and Zebrafish (HS3)21. The HotSHOT (HS6) protocol has been refined to further improve the efficiency of extracted DNA by combining NaOH and Tris–EDTA buffer in a single step20. In our study twenty microlitres of HotSHOT extraction buffer consisting of 25 mM NaOH + TE buffer, pH 8.0 (Invitrogen , Australia) (1:1 volume) was pipetted into each 8 well strip of LAMP PCR tubes (OptiGene, UK). Phylloxera samples were removed from ethanol and air dried on a paper towel for approx.1 min. Single whole adult, crawler, single and/or multiple eggs were transferred with a toothpick (single use to prevent cross contamination), into each well. Each sample was immersed in HotSHOT buffer with up to six samples processed simultaneously in the portable real-time fluorometer (Genie III, OptiGene, UK). The protocol used the Genie III as an incubator at 95 °C for 5 min followed by  > 1 min incubation on ice. The DNA was quantified using a NanoDrop ND-1000 Spectrophotometer (Thermo Fisher, Australia) and stored at − 20 °C.
Development of the LAMP assay
LAMP primer design
Phylloxera specific primers were designed from an alignment of publicly available COI (5′-region) DNA sequences (from BOLD, http://www.boldsystems.org), which included (i) target (phylloxera) and (ii) non-target species that were either closely related to phylloxera (i.e. Phylloxeroidea), or aphids (Aphididae) known to utilise grapevines or plant roots as hosts (Supplementary Table 1).
For all primers, the GC content (%), predicted melting temperature (Tm), and potential secondary structure (hairpins or dimers) were analysed using the Integrated DNA Technologies (IDT) online OligoAnalyzer tool (https://sg.idtdna.com/calc/analyzer), using the qPCR parameter sets. Complete sets of LAMP primers were analysed together to detect potential primer dimer interactions using the Thermo Fisher Multiple Primer Analyzer tool (www.thermofisher.com). Potential within-species genetic variation in phylloxera LAMP primers was examined using combined DNA sequences of Australian phylloxera and reference sequences available on BOLD (i.e. the seven laboratory strains, plus 230 × 5′-COI reference sequences on BOLD, accessed May 2018).
A synthetic 221 bp DNA fragment, designed from the complete fragment used for the assay (Fig. 1), was synthesized as a gBlock (Integrated DNA Technologies, Iowa, USA) to provide a reliable LAMP positive control. This fragment consisted of all eight LAMP primer regions (Fig. 1) concatenated together, with the non-primer DNA removed from between primers and replaced a run of “ccc” DNA bases between the primer regions and at the ends of the fragment, to increase the overall GC content of the synthetic fragment.
LAMP primer ratio optimisation
Primer master mix was prepared following published protocols11. Optimisation of the six primer (Table 1) ratio and concentration for the phylloxera LAMP assay was also conducted according to11.
LAMP assay conditions
The phylloxera LAMP assay was performed following the same method as published11. All LAMP assays were run in the Genie III at 65 °C for 25 min followed by an annealing curve analysis from 98 °C to 73 °C with ramping at 0.05 °C/s. The total run time being approximately 35 min.
Comparison of molecular methods for phylloxera identification
Analytical sensitivity of the LAMP assay compared with qPCR
Clean DNA was extracted from phylloxera (3 adult samples were pooled for one DNA extraction) using the destructive method. A fourfold serial dilution of two biological replicates was prepared using ultrapure water. Starting DNA concentrations were quantified using a Qubit 2.0 Flourometer (Invitrogen, Life Technologies, Australia) following the manufacturers protocol. Phylloxera DNA was serially diluted from 1.0 ng/µL to 0.000061 ng/µL (1:1 to 1:16,384). Sensitivity of the LAMP assay was tested using the serially diluted DNA in the Genie III, following the same assay conditions as mentioned above. The time of amplification and anneal derivative temperature was recorded for all samples.
The same serial dilution of DNA extracts was also used in real-time qPCR assay. The primers and probe set (manufactured by Sigma, Australia) and cycling conditions used were as published9. Real-time qPCR was performed in QuantStudio 3 Real time PCR system (Thermo Fisher Scientific, Australia) in a total volume of 25 µL with technical replicates for each dilution. Each reaction mixture included 12.5 µL Platinum Quantitative PCR SuperMix-UDG (Invitrogen, Australia), 0.5 µM of each forward and reverse primers, 0.2 µM Taqman probe, 4 µL of template DNA and made up to 25 µL with RNA-free water. An NTC with 4 µl of water instead of DNA was included in each run to check for reagent contamination. The thermal cycling conditions consisted of a two-step denaturation: 2 min at 50 °C and 10 min at 95 °C, followed by 40 cycles of amplification in a two-step procedure: 95 °C for 15 s and 60 °C for 1 min. The mean Cq value (cycling quantification value) of the 8 dilutions were recorded for comparison with the time of amplification obtained from the LAMP assay.
Performance of non-destructive DNA samples (HotSHOT HS6)
DNA was non-destructively extracted from whole phylloxera egg, crawler, and adult (n = 3) using the “crude” HotSHOT HS6 protocol, as mentioned above. The extracted DNA was tested across the full range of molecular techniques available for detection of phylloxera: real-time qPCR (using 5 µL and 2 µL DNA per reaction)9, microsatellite genotyping14, DNA barcoding7, as well as the new LAMP assay. Real-time qPCR and DNA barcoding were performed as described above. Microsatellite genotyping was performed following a laboratory protocol (Blacket et al. unpublished) that screens the six phylloxera microsatellite loci used to define Australian genotypes5,14, modified to utilise fluorescently labelled primer tails following22 and a multiplex PCR kit (Qiagen, Australia). Capillary separation of fluorescently labelled microsatellites was performed commercially by AGRF (Melbourne), using LIZ-500 size standards. Genotyping of fsa files was performed using the microsatellite plugin in Geneious R11 (https://www.geneious.com).
Phylloxera specimens (adults and crawlers) were visually examined pre-DNA extraction, with slides prepared from specimens’ post-DNA extraction to confirm retention of key morphological characters. Microscopic slides were prepared following the protocols as published22 and were deposited as reference specimens in the Victorian Agricultural Insect Collection (VAIC) (https://collections.ala.org.au).
Evaluation of gBlock DNA fragment for use as synthetic DNA positive in LAMP assay
To evaluate detection sensitivity a tenfold serial dilution of the gBlock DNA fragment was prepared using ultrapure water (Invitrogen, Australia). Synthetic DNA was serially diluted from ~ 100 million copies down to ~ 10 copies (108 copies to 10 copies). Sensitivity of the LAMP assay was tested using the serially diluted synthetic DNA in the Genie III, following the same assay conditions as mentioned above (run time increased from 25 to 35 min). Following this another LAMP run was conducted to determine the best dilution to be used as synthetic DNA for positive template in LAMP assay. The same fourfold serial dilution (1.0 ng/µL to 0.00098 ng/µL) of clean phylloxera DNA prepared previously was used as template to compare with one hundred thousand copies (105) of synthetic DNA. The amount of phylloxera DNA was then calculated from the amplification time of 105 copies of synthetic DNA. More

1.
Pecl, G. T. et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).
2.
Last, P. R. et al. Long-term shifts in abundance and distribution of a temperate fish fauna: a response to climate change and fishing practices. Global Ecol. Biogeogr. 20, 58–72. https://doi.org/10.1111/j.1466-8238.2010.00575.x (2011).
Article  Google Scholar 

3.
Pitt, N. R., Poloczanska, E. S. & Hobday, A. J. Climate-driven range changes in Tasmanian intertidal fauna. Mar. Freshw. Res. 61, 963–970. https://doi.org/10.1071/MF09225 (2010).
CAS  Article  Google Scholar 

4.
Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925. https://doi.org/10.1038/nclimate1958 (2013).
ADS  Article  Google Scholar 

5.
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42. https://doi.org/10.1038/nature01286 (2003).
ADS  CAS  Article  PubMed  Google Scholar 

6.
Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239–1242. https://doi.org/10.1126/science.1239352 (2013).
ADS  CAS  Article  PubMed  Google Scholar 

7.
McLeod, D. J., Hobday, A. J., Lyle, J. M. & Welsford, D. C. A prey-related shift in the abundance of small pelagic fish in eastern Tasmania?. ICES J. Mar. Sci. 69, 953–960. https://doi.org/10.1093/icesjms/fss069 (2012).
Article  Google Scholar 

8.
Johnson, C. R. et al. Climate change cascades: shifts in oceanography, species’ ranges and subtidal marine community dynamics in eastern Tasmania. J. Exp. Mar. Biol. Ecol. 400, 17–32. https://doi.org/10.1016/j.jembe.2011.02.032 (2011).
Article  Google Scholar 

9.
Ling, S. D. Range expansion of a habitat-modifying species leads to loss of taxonomic diversity: a new and impoverished reef state. Oecologia 156, 883–894. https://doi.org/10.1007/s00442-008-1043-9 (2008).
ADS  CAS  Article  PubMed  Google Scholar 

10.
Sunday, J. M. et al. Species traits and climate velocity explain geographic range shifts in an ocean-warming hotspot. Ecol. Lett. 18, 944–953 (2015).
Article  Google Scholar 

11.
Pecl, G. et al. The east coast Tasmanian rock lobster fishery—vulnerability to climate change impacts and adaptation response options. (Report to the Department of Climate Change, Australia, 2009).

12.
Angilletta, M. J. Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford University Press, Oxford, 2009).
Google Scholar 

13.
Fry, F. E. J. Effects of the Environment on Animal Activity (University of Toronto Press, Toronto, 1947).
Google Scholar 

14.
Sinclair, B. J. et al. Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures?. Ecol. Lett. 19, 1372–1385. https://doi.org/10.1111/ele.12686 (2016).
Article  PubMed  Google Scholar 

15.
Pörtner, H. O. & Farrell, A. P. Physiology and climate change. Science 322, 690–692. https://doi.org/10.2307/20145158 (2008).
Article  PubMed  Google Scholar 

16.
Pörtner, H. O. & Knust, R. Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science 315, 95–97. https://doi.org/10.1126/science.1135471 (2007).
ADS  CAS  Article  PubMed  Google Scholar 

17.
Schulte, P. M., Healy, T. M. & Fangue, N. A. Thermal performance curves, phenotypic plasticity, and the time scales of temperature exposure. Integr. Comp. Biol. 51, 691–702. https://doi.org/10.1093/icb/icr097 (2011).
Article  PubMed  Google Scholar 

18.
Donelson, J. M., McCormick, M. I., Booth, D. J. & Munday, P. L. Reproductive acclimation to increased water temperature in a tropical reef fish. PLoS ONE 9, e97223. https://doi.org/10.1371/journal.pone.0097223 (2014).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

19.
Twiname, S., Fitzgibbon, Q. P., Hobday, A. J., Carter, C. G. & Pecl, G. T. Multiple measures of thermal performance of early stage eastern rock lobster in a fast-warming ocean region. Mar. Ecol. Prog. Ser. 624, 1–11 (2019).
ADS  CAS  Article  Google Scholar 

20.
Fitzgibbon, Q. P., Simon, C. J., Smith, G. G., Carter, C. G. & Battaglene, S. C. Temperature dependent growth, feeding, nutritional condition and aerobic metabolism of juvenile spiny lobster Sagmariasus verreauxi. Comp. Biochem. Phys. A 207, 13–20 (2017).
CAS  Article  Google Scholar 

21.
Lord, J. P., Barry, J. P. & Graves, D. Impact of climate change on direct and indirect species interactions. Mar. Ecol. Prog. Ser. 571, 1–11 (2017).
ADS  Article  Google Scholar 

22.
Dell, A. I., Pawar, S. & Savage, V. M. Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy. J. Anim. Ecol. 83, 70–84. https://doi.org/10.1111/1365-2656.12081 (2014).
Article  PubMed  Google Scholar 

23.
Kordas, R. L., Harley, C. D. G. & O’Connor, M. I. Community ecology in a warming world: the influence of temperature on interspecific interactions in marine systems. J. Exp. Mar. Biol. Ecol. 400, 218–226. https://doi.org/10.1016/j.jembe.2011.02.029 (2011).
Article  Google Scholar 

24.
Marshak, A. R. & Heck, K. L. Interactions between range-expanding tropical fishes and the northern Gulf of Mexico red snapper Lutjanus campechanus. J. Fish Biol. 91, 1139–1165. https://doi.org/10.1111/jfb.13406 (2017).
CAS  Article  PubMed  Google Scholar 

25.
Milazzo, M., Mirto, S., Domenici, P. & Gristina, M. Climate change exacerbates interspecific interactions in sympatric coastal fishes. J. Anim. Ecol. 82, 468–477. https://doi.org/10.1111/j.1365-2656.2012.02034.x (2013).
Article  PubMed  Google Scholar 

26.
Grigaltchik, V. S., Ward, A. J. W. & Seebacher, F. Thermal acclimation of interactions: differential responses to temperature change alter predator-prey relationship. Proc. R. Soc. B-Biol. Sci. 279, 4058–4064. https://doi.org/10.1098/rspb.2012.1277 (2012).
Article  Google Scholar 

27.
Johansen, J. L. & Jones, G. P. Increasing ocean temperature reduces the metabolic performance and swimming ability of coral reef damselfishes. Glob. Change Biol. 17, 2971–2979. https://doi.org/10.1111/j.1365-2486.2011.02436.x (2011).
ADS  Article  Google Scholar 

28.
Batty, R. & Blaxter, J. The effect of temperature on the burst swimming performance of fish larvae. J. Exp. Biol. 170, 187–201 (1992).
Google Scholar 

29.
Temple, G. K. & Johnston, I. A. Testing hypotheses concerning the phenotypic plasticity of escape performance in fish of the family Cottidae. J. Exp. Biol. 201, 317–331 (1998).
CAS  PubMed  Google Scholar 

30.
Fry, F. E. J. & Hart, J. S. The relation of temperature to oxygen consumption in the goldfish. Biol. Bull. 94, 66–77. https://doi.org/10.2307/1538211 (1948).
CAS  Article  PubMed  Google Scholar 

31.
Clark, T. D., Sandblom, E. & Jutfelt, F. Aerobic scope measurements of fishes in an era of climate change: respirometry, relevance and recommendations. J. Exp. Biol. 216, 2771–2782. https://doi.org/10.1242/jeb.084251 (2013).
Article  PubMed  Google Scholar 

32.
Jutfelt, F. et al. Oxygen- and capacity-limited thermal tolerance: blurring ecology and physiology. J. Exp. Biol. 221, jeb169615 (2018).

33.
Pörtner, H.-O., Bock, C. & Mark, F. C. Oxygen- and capacity-limited thermal tolerance: bridging ecology and physiology. J. Exp. Biol. 220, 2685 (2017).
Article  Google Scholar 

34.
Norin, T., Malte, H. & Clark, T. D. Aerobic scope does not predict the performance of a tropical eurythermal fish at elevated temperatures. J. Exp. Biol. 217, 244–251. https://doi.org/10.1242/jeb.089755 (2014).
Article  PubMed  Google Scholar 

35.
Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789. https://doi.org/10.1890/03-9000 (2004).
Article  Google Scholar 

36.
Domenici, P. & Blake, R. The kinematics and performance of fish fast-start swimming. J. Exp. Biol. 200, 1165–1178 (1997).
CAS  PubMed  Google Scholar 

37.
Dell, A. I., Pawar, S. & Savage, V. M. Systematic variation in the temperature dependence of physiological and ecological traits. Proc. Natl. Acad. Sci. USA 108, 10591–10596. https://doi.org/10.1073/pnas.1015178108 (2011).
ADS  Article  PubMed  Google Scholar 

38.
Ohlund, G., Hedstrom, P., Norman, S., Hein, C. L. & Englund, G. Temperature dependence of predation depends on the relative performance of predators and prey. Proc. R. Soc. B-Biol. Sci. https://doi.org/10.1098/rspb.2014.2254 (2015).
Article  Google Scholar 

39.
England, W. R. & Baldwin, J. Anaerobic energy metabolism in the tail musculature of the Australian Yabby Cherax destructor (Crustacea, Decapoda, Parastacidae): role of phosphagens and anaerobic glycolysis during escape behavior. Physiol. Zool. 56, 614–622 (1983).
CAS  Article  Google Scholar 

40.
De Zwaan, A. & v.d. Thillart, G. in Circulation, Respiration, and Metabolism (ed Raymond Gilles) 166–192 (Springer, Berlin, 1985).

41.
Ellington, W. R. The recovery from anaerobic metabolism in invertebrates. J. Exp. Zool. 228, 431–444. https://doi.org/10.1002/jez.1402280305 (1983).
CAS  Article  Google Scholar 

42.
Hobday, A. & Pecl, G. Identification of global marine hotspots: sentinels for change and vanguards for adaptation action. Rev. Fish Biol. Fisher 24, 415–425. https://doi.org/10.1007/s11160-013-9326-6 (2014).
Article  Google Scholar 

43.
Ridgway, K. R. Long-term trend and decadal variability of the southward penetration of the East Australian Current. Geophys. Res. Lett. 34, L13613. https://doi.org/10.1029/2007GL030393 (2007).
ADS  Article  Google Scholar 

44.
Robinson, L. et al. Rapid assessment of an ocean warming hotspot reveals “high” confidence in potential species’ range extensions. Glob. Environ. Change 31, 28–37 (2015).
Article  Google Scholar 

45.
Redmap Australia. Institute for Marine and Antarctic Studies, University of Tasmania, (2020).

46.
Ling, S. D., Johnson, C. R., Ridgway, K., Hobday, A. J. & Haddon, M. Climate-driven range extension of a sea urchin: inferring future trends by analysis of recent population dynamics. Glob. Change Biol. 15, 719–731. https://doi.org/10.1111/j.1365-2486.2008.01734.x (2009).
ADS  Article  Google Scholar 

47.
Booth, D. J., Figueira, W. F., Gregson, M. A., Brown, L. & Beretta, G. Occurrence of tropical fishes in temperate southeastern Australia: role of the East Australian Current. Estuar. Coast Shelf Sci. 72, 102–114. https://doi.org/10.1016/j.ecss.2006.10.003 (2007).
ADS  Article  Google Scholar 

48.
Figueira, W. F., Biro, P., Booth, D. J. & Valenzuela, V. C. Performance of tropical fish recruiting to temperate habitats: role of ambient temperature and implications of climate change. Mar. Ecol. Prog. Ser. 384, 231–239. https://doi.org/10.3354/meps08057 (2009).
ADS  Article  Google Scholar 

49.
Cetina-Heredia, P., Roughan, M., Sebille, E., Feng, M. & Coleman, M. A. Strengthened currents override the effect of warming on lobster larval dispersal and survival. Glob. Change Biol. 21, 4377–4386. https://doi.org/10.1111/gcb.13063 (2015).
ADS  Article  Google Scholar 

50.
Dahlke, F. T., Wohlrab, S., Butzin, M. & Pörtner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70. https://doi.org/10.1126/science.aaz3658 (2020).
ADS  CAS  Article  PubMed  Google Scholar 

51.
Fitzgibbon, Q. P., Ruff, N., Tracey, S. R. & Battaglene, S. C. Thermal tolerance of the nektonic puerulus stage of spiny lobsters and implications of ocean warming. Mar. Ecol. Prog. Ser. 515, 173–186. https://doi.org/10.3354/meps10979 (2014).
ADS  Article  Google Scholar 

52.
Storch, D., Fernández, M., Navarrete, S. A. & Pörtner, H. O. Thermal tolerance of larval stages of the Chilean kelp crab Taliepus dentatus. Mar. Ecol. Prog. Ser. 429, 157–167 (2011).
ADS  Article  Google Scholar 

53.
Walther, K., Anger, K. & Pörtner, H. O. Effects of ocean acidification and warming on the larval development of the spider crab Hyas araneus from different latitudes (54° vs. 79°N). Mar. Ecol. Prog. Ser. 417, 159–170 (2010).
ADS  Article  Google Scholar 

54.
54Phillips, B. F., Booth, J. D., Cobb, J. S., Jeffs, A. G. & McWilliam, P. in Lobsters: Biology, Management, Aquaculture and Fisheries (ed Bruce F. Phillips) 231–262 (Blackwell Publishing Ltd, 2006).

55.
Hamner, W. M., Jones, M. S., Carleton, J. H., Hauri, I. R. & Williams, D. M. Zooplankton, planktivorous fish, and water currents on a windward reef face: Great Barrier Reef Australia. Bull. Mar. Sci. 42, 459–479 (1988).
Google Scholar 

56.
Emery, A. R. Comparative ecology and functional osteology of fourteen species of damselfish (Pisces: Pomacentridae) at alligator Reef Florida keys. Bull. Mar. Sci. 23, 649–770 (1973).
Google Scholar 

57.
Hinkle, P. C. P/O ratios of mitochondrial oxidative phosphorylation. BBA-Bioenergetics 1706, 1–11. https://doi.org/10.1016/j.bbabio.2004.09.004 (2005).
CAS  Article  PubMed  Google Scholar 

58.
Pörtner, H. O. Climate variations and the physiological basis of temperature dependent biogeography: systemic to molecular hierarchy of thermal tolerance in animals. Comp. Biochem. Phys. A 132, 739–761. https://doi.org/10.1016/S1095-6433(02)00045-4 (2002).
Article  Google Scholar 

59.
Speed, S. R., Baldwin, J., Wong, R. J. & Wells, R. M. G. Metabolic characteristics of muscles in the spiny lobster, Jasus edwardsii, and responses to emersion during simulated live transport. Comp. Biochem. Phys. B 128, 435–444. https://doi.org/10.1016/S1096-4959(00)00340-7 (2001).
CAS  Article  Google Scholar 

60.
Morris, S. & Adamczewska, A. M. Utilisation of glycogen, ATP and arginine phosphate in exercise and recovery in terrestrial red crabs Gecarcoidea natalis. Comp. Biochem. Phys. A 133, 813–825. https://doi.org/10.1016/S1095-6433(02)00217-9 (2002).
Article  Google Scholar 

61.
Head, G. & Baldwin, J. Energy metabolism and the fate of lactate during recovery from exercise in the Australian freshwater crayfish Cherax destructor. Mar. Freshw. Res. 37, 641–646. https://doi.org/10.1071/MF9860641 (1986).
CAS  Article  Google Scholar 

62.
Clark, T. D., Messmer, V., Tobin, A. J., Hoey, A. S. & Pratchett, M. S. Rising temperatures may drive fishing-induced selection of low-performance phenotypes. Sci. Rep. 7, 40571. https://doi.org/10.1038/srep40571 (2017).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

63.
Foo, S. A. & Byrne, M. Acclimatization and Adaptive capacity of marine species in a changing ocean. Adv. Mar. Biol. 74, 69–116. https://doi.org/10.1016/bs.amb.2016.06.001 (2016).
CAS  Article  PubMed  Google Scholar 

64.
Evans, T. G., Diamond, S. E. & Kelly, M. W. Mechanistic species distribution modelling as a link between physiology and conservation. Conserv. Physiol. 3, cov056. https://doi.org/10.1093/conphys/cov056 (2015).
Article  PubMed  PubMed Central  Google Scholar 

65.
Seebacher, F., White, C. R. & Franklin, C. E. Physiological plasticity increases resilience of ectothermic animals to climate change. Nat. Clim. Change 5, 61–66. https://doi.org/10.1038/nclimate2457 (2015).
ADS  Article  Google Scholar 

66.
Donelson, J. M., Munday, P. L., McCormick, M. I. & Nilsson, G. E. Acclimation to predicted ocean warming through developmental plasticity in a tropical reef fish. Glob. Change Biol. 17, 1712–1719. https://doi.org/10.1111/j.1365-2486.2010.02339.x (2011).
ADS  Article  Google Scholar 

67.
Oliver, E. C. J. et al. The unprecedented 2015/16 Tasman Sea marine heatwave. Nat. Commun. 8, 16101. https://doi.org/10.1038/ncomms16101 (2017).
ADS  Article  PubMed  PubMed Central  Google Scholar 

68.
Oliver, E. C. J. et al. Marine heatwaves off eastern Tasmania: trends, interannual variability, and predictability. Prog. Oceanogr. 161, 116–130. https://doi.org/10.1016/j.pocean.2018.02.007 (2018).
ADS  Article  Google Scholar 

69.
Stobart, B., Mayfield, S., Mundy, C., Hobday, A. J. & Hartog, J. R. Comparison of in situ and satellite sea surface-temperature data from South Australia and Tasmania: how reliable are satellite data as a proxy for coastal temperatures in temperate southern Australia?. Mar. Freshw. Res. 67, 612–625. https://doi.org/10.1071/MF14340 (2016).
Article  Google Scholar 

70.
Grose, M. R. et al. Climate Futures for Tasmania: general climate impacts technical report. (Antarctic Climate & Ecosystems Cooperative Research Centre, Hobart, Tasmania., 2010).

71.
Gilman, S. E. Predicting indirect effects of predator-prey interactions. Integr. Comp. Biol. 57, 148–158. https://doi.org/10.1093/icb/icx031 (2017).
Article  PubMed  Google Scholar 

72.
Fitzgibbon, Q. P. & Battaglene, S. C. Effect of photoperiod on the culture of early-stage phyllosoma and metamorphosis of spiny lobster (Sagmariasus verreauxi). Aquaculture 368, 48–54. https://doi.org/10.1016/j.aquaculture.2012.09.018 (2012).
Article  Google Scholar 

73.
Fitzgibbon, Q. P., Battaglene, S. C. & Ritar, A. J. Effect of water temperature on the development and energetics of early, mid and late-stage phyllosoma larvae of spiny lobster Sagmariasus verreauxi. Aquaculture 344–349, 153–160. https://doi.org/10.1016/j.aquaculture.2012.03.008 (2012).
Article  Google Scholar 

74.
Jensen, M. A., Fitzgibbon, Q. P., Carter, C. G. & Adams, L. R. Effect of body mass and activity on the metabolic rate and ammonia-N excretion of the spiny lobster Sagmariasus verreauxi during ontogeny. Comp. Biochem. Phys. A 166, 191–198. https://doi.org/10.1016/j.cbpa.2013.06.003 (2013).
CAS  Article  Google Scholar 

75.
Fitzgibbon, Q. P., Jeffs, A. G. & Battaglene, S. C. The Achilles heel for spiny lobsters: the energetics of the non-feeding post-larval stage. Fish Fish 15, 312–326. https://doi.org/10.1111/faf.12018 (2014).
Article  Google Scholar 

76.
Harvey, E., Shortis, M., Stadler, M. & Cappo, M. A Comparison of the accuracy and precision of measurements from single and stereo-video systems. Mar. Technol. Soc. J. 36, 38–49. https://doi.org/10.4031/002533202787914106 (2002).
Article  Google Scholar 

77.
R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2017).

78.
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Article  Google Scholar 

79.
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, Berlin, 2009).
Google Scholar  More