Dynamic habitat suitability modelling reveals rapid poleward distribution shift in a mobile apex predator
Abstract
Many taxa are undergoing distribution shifts in response to anthropogenic climate change. However, detecting a climate signal in mobile species is difficult due to their wide‐ranging, patchy distributions, often driven by natural climate variability. For example, difficulties associated with assessing pelagic fish distributions have rendered fisheries management ill‐equipped to adapt to the challenges posed by climate change, leaving pelagic species and ecosystems vulnerable. Here, we demonstrate the value of citizen science data for modelling the dynamic habitat suitability of a mobile pelagic predator (black marlin, Istiompax indica) within the south‐west Pacific Ocean. The extensive spatial and temporal coverage of our occurrence data set (n = 18 717), collected at high resolution (~1.85 km 2), enabled identification of suitable habitat at monthly time steps over a 16‐year period (1998–2013). We identified considerable monthly, seasonal and interannual variability in the extent and distribution of suitable habitat, predominately driven by chlorophyll a and sea surface height. Interannual variability correlated with El Nino Southern Oscillation (ENSO) events, with suitable habitat extending up to ~300 km further south during La Nina events. Despite the strong influence of ENSO, our model revealed a rapid poleward shift in the geometric mean of black marlin habitat, occurring at 88.2 km decade−1. By incorporating multiple environmental factors at monthly time steps, we were able to demonstrate a rapid distribution shift in a mobile pelagic species. Our findings suggest that the rapid velocity of climate change in the south‐west Pacific Ocean is likely affecting mobile pelagic species, indicating that they may be more vulnerable to climate change than previously thought.
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Hill et al. (2016) conclude that the current rate of climate change could affect large migratory pelagic organisms, modifying their distribution areas faster than previously thought.
“Recientemente, Hill et al. (2016), concluyen que el actual ritmo en el que se está produciendo el cambio climático podría afectar a los grandes organismos pelágicos migradores, modificando sus áreas de distribución más rápido de lo que previamente se pensaba.”
From Túnidos tropicales: calentamiento global y seguridad alimentaria, una visión global (2019) · cites this paper as Hill et al. 2016
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Trophic Downgrading of Planet Earth
Estes, J. A., Terborgh, J., Brashares, J. S., Power, M. E., Berger, J., Bond, W. J., Carpenter, S. R., Essington, T. E., Holt, R. D., Jackson, J. B. C., et al. (2011) · Science · doi:10.1126/science.1205106 · Cited by 4,087 · cited 2× · see citing works
“Apex predators exert important top-down control of food webs and are critical for maintaining ecosystem function (Myers et al., 2007; Estes et al., 2011).”
BackgroundThe art of modelling range-shifting species: <i>The art of modelling range-shifting species</i>
Elith, J., Kearney, M., & Phillips, S. (2010) · Methods in Ecology and Evolution · doi:10.1111/j.2041-210x.2010.00036.x · Cited by 2,813 · see citing works
Cascading top-down effects of changing oceanic predator abundances
Baum, J. K., & Worm, B. (2009) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2009.01531.x · Cited by 932 · cited 2× · see citing works
“Mobile pelagic predators play a key functional role in pelagic ecosystems, and their decline has resulted in trophic cascades in some regions (Myers et al., 2007; Baum & Worm, 2009).”
BackgroundElectronic tagging and population structure of Atlantic bluefin tuna
Block, B. A., Teo, S. L. H., Walli, A., Boustany, A., Stokesbury, M. J. W., Farwell, C. J., Weng, K. C., Dewar, H., & Williams, T. D. (2005) · Nature · doi:10.1038/nature03463 · Cited by 781 · cited 4× · see citing works
“…1990) and other similar species known to undertake seasonal migrations in association with west- ern boundary currents, such as Atlantic bluefin tuna (Thunnus thynnus) within the Gulf Stream (Block et al., 2005) and striped marlin (Kajikia audax) within the Kuroshio Current (Lien et al., 2013).”
BackgroundResultInfluentialDynamic ocean management: defining and conceptualizing real-time management of the ocean
Maxwell, S. M., Hazen, E. L., Lewison, R. L., Dunn, D. C., Bailey, H., Bograd, S. J., Briscoe, D. K., Fossette, S., Hobday, A. J., Bennett, M., et al. (2015) · Marine Policy · doi:10.1016/j.marpol.2015.03.014 · Cited by 504 · see citing works
Predicted habitat shifts of Pacific top predators in a changing climate
Hazen, E. L., Jorgensen, S., Rykaczewski, R. R., Bograd, S. J., Foley, D. G., Jonsen, I. D., Shaffer, S. A., Dunne, J. P., Costa, D. P., Crowder, L. B., et al. (2013) · Nature Climate Change · doi:10.1038/nclimate1686 · Cited by 499 · see citing works
Effects of temperature on global patterns of tuna and billfish richness
Boyce, D., Tittensor, D., & Worm, B. (2008) · Marine Ecology Progress Series · doi:10.3354/meps07237 · Cited by 139 · cited 2× · see citing works
“Habitat suitability of mobile species is determined by a range of environmental (e.g. temperature; Boyce et al., 2008) and ecological parameters (e.”
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Flagged first, then by citations
Research works printed but not linked: 19
- Anderson AS, Reside AE, VanDerWal JJ, Shoo LP, Pearson RG, Williams SE (2012) Immigrants and refugees: the importance of dispersal in mediating biotic attrition under climate change. Global Change Biology , 18 , 2126-2134.
- Beaugrand G, Edwards M, Brander K, Luczak C, Ibanez F (2008) Causes and projections of abrupt climate-driven ecosystem shifts in the North Atlantic. Ecology Letters , 11 , 11571168.
- Brander K (2010) Impacts of climate change on fisheries. Journal of Marine Systems , 79 , 389-402.
- Brill R, Lutcavage M (2001) Understanding environmental influences on movements and depth distributions of tunas and billfishes can significantly improve population assessments. American Fisheries Society Symposium , 25 , 179-198.
- Cai W (2006) Antarctic ozone depletion causes an intensification of the Southern Ocean supergyre circulation. Geophysical Research Letters, 33 , L03712.
- Cai W, Rensch P (2012) The 2011 south-east Queensland extreme summer rainfall: a confirmation of a negative Pacific Decadal Oscillation phase? Geophysical Research Letters, 39 , L08702.
- Cai W, Shi G, Cowan T, Bi D, Ribbe J (2005) The response of the Southern Annular Mode, the East Australian Current, and the southern mid-latitude ocean circulation to global warming. Geophysical Research Letters, 32 , L23706.
- Holbrook NJ, Bindoff NL (1997) Interannual and decadal variability in the southwest Pacific Ocean between 1955 and 1988. Journal of Climate, 10 , 1035-1049.
- Holbrook NJ, Johnson JE (2014) Climate change impacts and adaptation of commercial marine fisheries in Australia: a review of the science. Climatic Change , 124 , 703-715.
- Lehodey P, Bertignac M, Hampton J, Lewis A, Picaut J (1997) El Nino Southern Oscillation and tuna in the western Pacific. Letters to Nature , 389 , 715-718.
- Lehodey P, Alheit J, Barange M et al. (2006) Climate variability, fish, and fisheries. Journal of Climate, 19 , 5009-5030.
- Leis JM, Goldman B, Ueyanagi S (1987) Distribution and abundance of billfish larvae (Pisces: Istiophoridae) in the Great Barrier Reef Lagoon and Coral Sea near Lizard Island, Australia. Fishery Bulletin, 85 , 757-765.
- Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful. Global Ecology & Biogeography, 12 , 361-371.
- Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography , 34 , 102-117.
- Pepperell, JG (1990). Movements and variations in early year-class strength of black marlin ( Makaira indica ) off eastern Australia. In: Planning the future of billfishes (eds Stroud RH ), pp. 51-66 . National Coalition Marine Conservation. Savannah, Georgia.
- Ridgway KR (2007) Long-term trend and decadal variability of the southward penetration of the East Australian Current. Geophysical Research Letters , 34 , L13613.
- Su N, Punt E, Yeh S, Dinardo G, Sun C (2011) Modelling the impacts of environmental variation on the distribution of blue marlin , Makaira nigricans, in the Pacific Ocean. ICES Journal of Marine Science , 68 , 1072-1080.
- Verges A, Steinberg PD, Hay ME et al. (2014) The tropicalization of temperate marine ecosystems: climate-mediated changes in herbivory and community phase shifts. Proceedings of the Royal Society B: Biological Sciences , 281 , 20140846.
- Worm B, Tittensor DP (2011) Range contraction in large pelagic predators. Proceedings of the National Academy of Sciences , 108 , 11942-11947.
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ENSO Impact on Marine Fisheries and Ecosystems
Lehodey, P., Bertrand, A., Hobday, A. J., Kiyofuji, H., McClatchie, S., Menkès, C. E., Pilling, G., Polovina, J., & Tommasi, D. (2020) · Geophysical Monograph Series · doi:10.1002/9781119548164.ch19 · Cited by 73 · see citing works
Túnidos tropicales: calentamiento global y seguridad alimentaria, una visión global
Báez, J. C., Pascual Alayón, P., Ramos, M. L., & Abascal, F. J. (2019) · Revista de Biología Marina y Oceanografía · doi:10.4067/s0718-19572018000100001 · Cited by 11 · see citing works
- Authors
- Hill, N. J., Tobin, A. J., Reside, A. E., Pepperell, J. G., & Bridge, T. C. L.
- Affiliations
- James Cook University (AU)
- Pepperell Research and Consulting Pty Ltd. P.O. Box 1475 Noosaville DC Qld 4566 Australia
- Australian Institute of Marine Science (AU)
- Corresponding author
- Hill, Nicholas J.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2015-12-15
- Volume
- 22
- Issue
- 3
- Pages
- 1086-1096
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W2113695248
- Cited by
- 74
- References
- 7
- Citations by year
- 2026: 10 · 2025: 8 · 2024: 4 · 2023: 1 · 2022: 7 · 2021: 13 · 2020: 9 · 2019: 6 · 2018: 8 · 2017: 6 · 2016: 2
- FWCI
- 2.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Global Change Biology (publishedVersion)
- PubMed (publishedVersion)
- ResearchOnline at James Cook University (James Cook University) (submittedVersion)
- Topics
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
- Keywords
- black marlin, Istiompax indica, climate change, ENSO, citizen science, pelagic predators, chlorophyll a, sea surface height, mobile species, fisheries management
- MeSH terms
- Animals, Models, Biological, Pacific Ocean, Perciformes, Ecosystem, Food Chain, Climate Change, Animal Distribution
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