Metanálise de razões 87Sr/86Sr em otólitos para estabelecer limiares para determinar o movimento de peixes
DOI:
https://doi.org/10.20950/1678-2305/bip.2023.49.e832Palavras-chave:
Peixes migratórios, Área de vida de peixes, Isótopos de estrôncio, Geoquímica, Peixe reofílicoResumo
Dados não publicados em conjunto com revisão da literatura foram combinados para testar a hipótese de que existe um padrão para classificar peixes como “migradores” ou “residentes” de acordo com a variabilidade nas proporções de isótopos de estrôncio ( 87 Sr/ 86 Sr) em otólitos em função das assinaturas isotópicas ambientais. A variabilidade nas razões de Sr encontradas nos otólitos dos espécimes de peixes como porcentagem da variabilidade ambiental isotópica foi utilizada para determinar a intensidade do movimento em uma determinada área de estudo (índice POEVSri). Uma meta-análise clássica e uma regressão frequentista foram aplicadas para obter um modelo logístico para descrever o padrão. A meta-análise retornou um POEVSri limite de 28,95% para indivíduos sedentários, e o modelo logístico demonstra alta probabilidade de migração para índices POEVSri superiores a 32%. Há um gradiente de probabilidades de movimento no intervalo de POEVSri entre 8 e 32%, com cada classe tendo probabilidades iguais quando POEVSri é de aproximadamente 20%. Quanto à aplicabilidade para estudos futuros, se aspectos como amostragem espacial e sazonal suficiente da água forem abordados, o modelo fornece dois limites diferentes para os peixes: “movers” a priori são aqueles com POEVSri ≥ 32%, e os peixes residentes têm POEVSri ≤ 8%.
Referências
Avigliano, E.; Pisonero, J.; Bouchez, J.; Pouilly, M.; Domanico, A.; Sánchez, S.; Volpedo, A.V. 2021. Otolith Sr/Ca ratio complements Sr isotopes to reveal fish migration in large basins with heterogeneous geochemical landscapes. Environmental Biology of Fishes, 104(3): 277-292. https://doi.org/10.1007/s10641-021-01074-y
Barnett-Johnson, R.; Teel, D.J.; Casillas, E. 2010. Genetic and otolith isotopic markers identify salmon populations in the Columbia River at broad and fine geographic scales. Environmental Biology of Fishes, 89(3): 533-546. https://doi.org/10.1007/s10641-010-9662-5
Barroco, L.S.A. 2019. O efeito de barragens hidrelétricas sobre populações de peixes de rios de águas pretas na Amazônia: uma abordagem com o uso de marcadores biogeoquímicos e moleculares. Doctoral Thesis. Universidade Federal do Amazonas. Available at: https://tede.ufam.edu.br/ bitstream/tede/7475/2/Tese_LorenzoBarroco_PPGCIPET.pdf. Accessed on: Mar. 30, 2023.
Barrow, J.S.; Yen, J.D.; Koehn, J.D.; Zampatti, B.P.; Thiem, J.D.; Tonkin, Z.; Strawbridge, A.; Morrongiello, J. R.
Lifetime movement history is associated with variable growth of a potamodromous freshwater fish.
Journal of Animal Ecology, 90(11): 2560-2572. https://doi.org/10.1111/1365-2656.13561
Bouchez, J.; Lajeunesse, E.; Gaillardet, J.; France-Lanord, C.; Dutra-Maia, P.; Maurice, L. 2010. Turbulent mixing in the Amazon River: The isotopic memory of confluences. Earth and Planetary Science Letters, 290(1-2): 37-43.https://doi.org/10.1016/j.epsl.2009.11.054
Brennan, S.R.; Zimmerman, C.E.; Fernandez, D.P.; Cerling, T.E.; McPhee, M.V.; Wooller, M.J. 2015. Strontium isotopes delineate fine-scale natal origins and migration histories of Pacific salmon. Science Advances, 1(4): e1400124. https://doi.org/10.1126/sciadv.1400124
Campana, S.E. 1999. Chemistry and composition of fish otoliths: pathways, mechanisms, and applications. Marine Ecology Progress Series, 188: 263-297.
Castello, L. 2008. Lateral migration of Arapaima gigas in floodplains of the Amazon. Ecology of Freshwater Fish, 17(1): 38-46. https://doi.org/10.1111/j.1600-0633.2007.00255.x
Cohen, J. 1992. A power primer. Psychological Bulletin, 112(1):155-159. https://doi.org/10.1037//00332909.112.1.155
Cottrell, A.; Lucchetti, R. 2021. GRETL - Gnu Regression, Econometrics and Time-series Library, version 2021b.
Software written in C Language based on ESL (Econometrics Software Library, by Ramu Ramanathan). Available at: https://gretl.sourceforge.net/pt.html. Accessed on: Mar. 30, 2023.
Crook, D.A.; Lacksen, K.; King, A.J.; Buckle, D.J.; Tickell, S.J.; Woodhead, J.D.; Maas, R.; Townsend, S.A.; Douglas, M.M. 2017. Temporal and spatial variation in strontium in a tropical river: implications for otolith chemistry analyses of fish migration. Canadian Journal of Fisheries and Aquatic Sciences, 74(4): 533-545. https://doi.org/10.1139/cjfas-2016-0153
David, B.O.; Jarvis, M.; Özkundakci, D.; Collier, K.J.; Hicks, A.S.; Reid, M. 2019. To sea or not to sea? Multiple lines of evidence reveal the contribution of non-diadromous recruitment for supporting endemic fish populations within New Zealand’s longest river. Aquatic Conservation: Marine and Freshwater Ecosystems, 29(9): 1409-1423. https://doi.org/10.1002/aqc.3022
Deeks, J.J.; Altman, D.G.; BradBurn, M.J. 2001. Statistical methods for examining heterogeneity and combining results from several studies in meta-analysis. In: Egger, M.; Smith, G.D.; Altman, D.G. (eds.). Systematic Reviews in Health Care. Wiley. p. 285-312. https://doi.org/10.1002/9780470693926.ch15
DerSimonian, R.; Laird, N. 1986. Meta-analysis in clinical trials. Controlled Clinical Trials, 7(3): 177-188. https://doi.org/10.1016/0197-2456(86)90046-2
Duponchelle, F.; Isaac, V.J.; Doria, C.R.C.; Van Damme, P.A.; Herrera-R, G.A.; Anderson, E.P.; Cruz, R.E.; Hauser, M.; Hermann, T.W.; Agudelo, E.; Bonilla-Castillo, C. 2021. Conservation of migratory fishes in the Amazon basin. Aquatic Conservation: Marine and Freshwater Ecosystems, 31(5): 1087-1105. https://doi.org/10.1002/aqc.3550
Duponchelle, F.; Pouilly, M.; Pécheyran, C.; Hauser, M.; Renno, J.F.; Panfili, J.; Baras, E. 2016. Trans-Amazonian natal homing in giant catfish. Journal of Applied Ecology, 53(5):1511-1520. https://doi.org/10.1111/1365-2664.12665
Eastin, R.; Faure, G. 1970. Seasonal variation of the solute content and the Sr87/Sr86 ratio of the Olentangy and Scioto Rivers at Columbus, Ohio. The Ohio Journal of Science, 70: 170-179.
Farrell, J.; Campana, S.E. 1996. Regulation of calcium and strontium deposition on the otoliths of juvenile tilapia, Oreochromis niloticus. Comparative Biochemistry and Physiology Part A: Physiology, 115(2): 103-109. https://doi.org/10.1016/0300-9629(96)00015-1
Field, A.P.; Gillett, R. 2010. How to do a meta-analysis. British Journal of Mathematical and Statistical Psychology, 63(3): 665-694. https://doi.org/10.1348/000711010X502733
Fleiss, J.L. 1993. Review papers: The statistical basis of metaanalysis. Statistical Methods in Medical Research, 2(2): 121-145. https://doi.org/10.1177/096228029300200202
Gillanders, B.M. 2005. Otolith chemistry to determine movements of diadromous and freshwater fish. Aquatic Living Resources, 18(3): 291-300. https://doi.org/10.1051/alr:2005033
Hauser, M.; Doria, C.R.; Santos, R.V.; García-Vasquez, A.; Pouilly, M.; Pécheyran, C.; Ponzevera, E.; Torrente-Vilara, G.; Bérail, S.; Panfili, J.; Darnaude, A.; Renno, J.; García-Dávila, C.; Nuñez, J.; Ferraton, F.; Vargas, G.; Duponchelle, F. 2019. Shedding light on the migratory patterns of the Amazonian goliath catfish, Brachyplatystoma platynemum, using otolith 87Sr/86Sr analyses. Aquatic Conservation: Marine and Freshwater Ecosystems, 29(3): 397-408. https://doi.org/10.1002/aqc.3046
Hauser, M.; Duponchelle, F.; Hermann, T.W.; Limburg, K.E.; Castello, L.; Stewart, D.J.; Torrente-Vilara, G.; García-Vásquez, A.; García-Davila, C.; Pouilly, M.; Pecheyran, C.; Ponzevera, E.; Renno, J.; Moret, A.S.; Doria, C.R. 2020. Unmasking continental natal homing in goliath catfish from the upper Amazon. Freshwater Biology, 65(2): 325-336. https://doi.org/10.1111/fwb.13427
Hedges, L.V. 1984. Estimation of effect size under nonrandom sampling: The effects of censoring studies yielding statistically insignificant mean differences. Journal of Educational Statistics, 9(1): 61-85. https://doi.org/10.2307/1164832
Hedges, L.V.; Olkin, I. 1983. Regression models in research synthesis. American Statistician, 37(2): 137-140. https://doi.org/10.2307/2685874
Hedges, L.V.; Vevea, J.L. 1998. Fixed and random effects models in meta-analysis. Psychological Methods, 3(4): 486-504. https://doi.org/10.1037/1082-989X.3.4.486
Hegg, J.C.; Kennedy, B.P.; Fremier, A.K. 2013. Predicting strontium isotope variation and fish location with bedrock geology: Understanding the effects of geologic heterogeneity. Chemical Geology, 360-361: 89-98. https://doi.org/10.1016/j.chemgeo.2013.10.010
Kennedy, B.P.; Blum, J.D.; Folt, C.L.; Nislow, K.H. 2000. Using natural strontium isotopic signatures as fish markers: methodology and application. Canadian Journal of Fisheries and Aquatic Sciences, 57(11): 2280-2292. https://doi.org/10.1139/cjfas-57-11-2280
Konstantopoulos, S.; Hedges, L.V. 2009. Analyzing effect sizes: Fixed-effects models. In: Cooper, H.; Hedges, L.V.; Valentine, J.V. (Eds.). Handbook of Research Synthesis and Meta-Analysis. Russell Sage Foundation. p. 279-294.
Leggett, W.C. 1985. The role of migrations in the life history evolution of fish. Contributions in Marine Science. In: Rankin, M.A. (ed.). Migration: Mechanisms and Adaptive Significance. The University of Texas. p. 277-295.
Nathan, R.; Getz, W.M.; Revilla, E.; Holyoak, M.; Kadmon, R.; Saltz, D.; Smouse, P.E. 2008. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences, 105(49): 19052-19059. https://doi.org/10.1073/pnas.0800375105
Pereira, L.A.; Santos, R.V.; Hauser, M.; Duponchelle, F.; Carvajal, F.; Pecheyran, C.; Bérail, S.; Pouilly, M. 2019. Commercial traceability of Arapaima spp. fisheries in the Amazon basin: can biogeochemical tags be useful? Biogeosciences, 16(8): 1781-1797. https://doi.org/10.5194/bg-16-1781-2019
R Core Team. 2000. R language definition. Vienna: R Foundation for Statistical Computing. Available at: https://cran.rproject.org/doc/manuals/r-devel/R-lang.html. Accessed on: Mar. 30, 2023.
R Studio Team. 2022. RStudio: Integrated Development for R. RStudio, “Prairie Trillium” Release for Windows. Boston: R Studio Team. Available at: http://www.rstudio.com/. Accessed on: Mar. 30, 2023.
Reis-Santos, P.; Gillanders, B.M.; Sturrock, A.M.; Izzo, C.; Oxman, D.S.; Lueders-Dumont, J.A.; Hüssy, K.; Tanner, S.E.; Rogers, T.; Doubleday, Z.A.; Andrews, A.H.; Trueman, C.; Brophy, D.; Thiem, J.D.; Baumgartner, L.J.; Willmes, M.; Chung, M.T.; Johnson, R.C.; Heimbrand, Y.; Limburg, K.E.; Walther, B.D. 2022. Reading the biomineralized book of life: expanding otolith biogeochemical research and applications for fisheries and ecosystem-based management. Reviews in Fish Biology and Fisheries, 33: 411-449. https://doi.org/10.1007/s11160-022-09720-z
Rosenthal, R. 1979. The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3): 638-641. https://doi.org/10.1037/0033-2909.86.3.638
Sand-Jensen, K. 2007. How to write consistently boring scientific literature. Oikos, 116(5): 723-727. https://doi.org/10.1111/j.0030-1299.2007.15674.x
Santos, R.V.; Sondag, F.; Cochonneau, G.; Lagane, C.; Brunet, P.; Hattingh, K.; Chaves, J.G.S. 2015. Source area and seasonal 87Sr/86Sr variations in rivers of the Amazon basin. Hydrological Processes, 29(2): 187-197. https://doi.org/10.1002/hyp.10131
Schwarzer, G.; Carpenter, J.R.; Rücker, G. 2015. Meta-Analysis with R. Switzerland: Springer International Publishing, 256 p.
Secor, D.H. 2015. Migration ecology of marine fishes. Baltimore: Johns Hopkins University Press, 304 p.
Sousa, R.G.C.; Humston, R.; Freitas, C.E.C. 2016. Movement patterns of adult peacock bass Cichla temensis between tributaries of the middle Negro River basin (Amazonas– Brazil): an otolith geochemical analysis. Fisheries Management and Ecology, 23(1): 76-87. https://doi.org/10.1111/fme.12166
Sousa, R.G.C.; Rosa, F.R.; Longo, J.M.; Santos, J.C.C.; Casseb, A.A.; Militão, J.S.L.T. (unpublished). Final Technical Report for R&D Project PD-00700-0119/2019 in the Verde River. 253 p.
Stubben, C.; Milligan, B.; Nantel, P.; Stubben, M.C. 2022. Package “popbio” - Construction and Analysis of Matrix Population Models, version 2.7. 77 p.
Thorrold, S.R.; Hare, J.A. 2002. Otolith applications in reef fish ecology. In: Sale, P.F. (ed.). Coral Reef Fishes: Dynamics and Diversity in a Complex Ecosystem. San Diego: Academic Press, p. 243-264.
Tran, N.T.; Labonne, M.; Chung, M.T.; Wang, C.H.; Huang, K.F.; Durand, J.D.; Grudpan, C.; Chan, B.; Hoang, H.D.; Panfili, J. 2021. Natal origin and migration pathways of Mekong catfish (Pangasius krempfi) using strontium isotopes and trace element concentrations in environmental water and otoliths. PLoS One, 16(6): e0252769. https://doi.org/10.1371/journal.pone.0252769
Tzadik, O.E.; Curtis, J.S.; Granneman, J.E.; Kurth, B.N.; Pusack, T.J.; Wallace, A.A.; Hollander, D.J.; Peebles, B.P.; Stallings, C.D. 2017. Chemical archives in fishes beyond otoliths: A review on the use of other body parts as chronological recorders of microchemical constituents for expanding interpretations of environmental, ecological, and lifehistory changes. Limnology and Oceanography: Methods, 15(3): 238-263. https://doi.org/10.1002/lom3.10153
Viechtbauer, W.; Viechtbauer, M.W. 2015. Package ‘metafor’. The Comprehensive R Archive Network. Available at: http://cran.r-project.org/web/packages/ metafor/metafor.pdf. Accessed on: Mar. 30, 2023.
Walther, B.D.; Thorrold, S.R. 2006. Water, not food, contributes the majority of strontium and barium deposited in the otoliths of a marine fish. Marine Ecology Progress Series, 311: 125-130. https://doi.org/10.3354/meps311125
Wei, G.; Ma, J.; Liu, Y.; Xie, L.; Lu, W.; Deng, W.; Ren, Z.; Zeng, T.; Yang, Y. 2013. Seasonal changes in the radiogenic and stable strontium isotopic composition of Xijiang River water: Implications for chemical weathering. Chemical Geology, 343: 67-75. https://doi.org/10.1016/j.chemgeo.2013.02.004
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Copyright (c) 2023 Fábio Ricardo da Rosa, Esteban Avigliano, Fabrice Duponchelle, Luciana Alves Pereira, Marília Hauser, Lorenzo Soriano Antonaccio Barroco, Carlos Edwar de Carvalho Freitas, Raniere Garcez Costa Sousa
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
