Skip to main content

A simple framework for estimating potential distributions of amphibious marine species and implications for conservation

Abstract

Due to their complexity, coral reefs are difficult to study especially when considering the role that the interplay between the terrestrial and marine environments has in shaping distribution of marine, terrestrial, and amphibious species. Many organisms live in remote areas of the ocean and inhabit both terrestrial and marine environments. Such amphibious lifestyle poses analytical difficulties due to broad distribution and scale of coral reefs. Ecological niche modeling is a widely used technique that allows to estimate the environmental set of conditions (niche) in which organisms can survive and reproduce. Estimating the distributions of species with complex life histories (i.e., dependent on various natural resources) at broad geographic scales is crucial, as many of these taxa are threatened (i.e., amphibians, aquatic reptiles, birds, and mammals). However, distribution estimates of such species remain challenging; thus, here we propose an approach to account for marine and terrestrial environmental domains to estimate the distribution of amphibious species. We also test whether inclusion of both environments leads to improved estimates of these species’ distributions. First we calibrated ecological niche models for marine and terrestrial domains separately, and subsequently we outlined a method to combine the marine–terrestrial potential distributions by integrating estimates of the two ecological niches into a single predictive model. Our ecological niche models produced inaccurate distribution predictions of species with amphibious life histories when only one of the environments was used in model calibration. When both aquatic and terrestrial environments were included, our models predicted narrower and more accurate potential distributions. Accounting for the dual environments involved in shaping the niches of amphibious species and their distributions is essential for studying the ecology and proposing conservation management actions for the species studied here. Models that take into account only a subset of the environmental factors are prone to overestimating species’ distributions and should be interpreted with caution.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  • Anderson RP (2013) A framework for using niche models to estimate impacts of climate change on species distributions. Annals of the New York Academy of Sciences 1297:8–28

    PubMed  Google Scholar 

  • Anderson RP, Lew D, Peterson AT (2003) Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecol Model 162:211–232

    Google Scholar 

  • Austin M (2007) Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecol Model 200:1–19

    Google Scholar 

  • Austin MP, Van Niel KP (2011) Improving species distribution models for climate change studies: variable selection and scale. J Biogeogr 38:1–8

    Google Scholar 

  • Barve N, Barve V, Jimenez-Valverde A, Lira-Noriega A, Maher SP, Peterson AT, Soberon J, Villalobos F (2011) The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecol Model 222:1810–1819

    Google Scholar 

  • Bedia J, Herrera S, Gutiérrez JM (2013) Dangers of using global bioclimatic datasets for ecological niche modeling. Limitations for future climate projections. Global Planet Change 107:1–12

    Google Scholar 

  • Bombosch A, Zitterbart DP, Van Opzeeland I, Frickenhaus S, Burkhardt E, Wisz MS, Boebel O (2014) Predictive habitat modelling of humpback (Megaptera novaeangliae) and Antarctic minke (Balaenoptera bonaerensis) whales in the Southern Ocean as a planning tool for seismic surveys. Deep Sea Research Part I: Oceanographic Research Papers 91:101–114

    Google Scholar 

  • Breiner FT, Guisan A, Nobis MP, Bergamini A (2017) Including environmental niche information to improve IUCN Red List assessments. Divers Distrib 23:484–495

    Google Scholar 

  • Brischoux F, Bonnet X, Shine R (2007) Foraging ecology of sea kraits Laticauda spp. in the Neo-Caledonian Lagoon. Mar Ecol Prog Ser 350:145–151

    Google Scholar 

  • Brischoux F, Tingley R, Shine R et al (2012) Salinity influences the distribution of marine snakes: implications for evolutionary transitions to marine life. Ecography 35(11):994–1003

    Google Scholar 

  • Brischoux F, Tingley R, Shine R et al (2013) Behavioral and physiological correlates of the geographic distributions of amphibious sea kraits (Laticauda spp.). Journal of Sea Research 76:1–4

    Google Scholar 

  • Bucklin DN, Basille M, Benscoter AM, Brandt LA, Mazzotti FJ, Romanach SS, Speroterra C, Watling JI (2015) Comparing species distribution models constructed with different subsets of environmental predictors. Divers Distrib 21:23–35

    Google Scholar 

  • Dambach J, Rödder D (2011) Applications and future challenges in marine species distribution modeling. Aquatic Conservation: Marine and Freshwater Ecosystems 21:92–100

    Google Scholar 

  • Elfes CT, Livingstone SR, Lane A, Lukoschek V, Sanders KL, Courtney AJ, Gatus JL, Guinea M, Lobo AS, Milton D (2013) Fascinating and forgotten: the conservation status of the world’s sea snakes. Herpetol Conserv Bio 8:37–52

    Google Scholar 

  • Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S, Guisan A, Hijmans RJ, Huettman F, Leathwick JR, Lehmann A, Li J, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JM, Peterson AT, Phillips SJ, Richardson K, Scachetti-Pereira R, Schapire RE, Soberón J, Williams SE, Wisz MS, Zimmermann NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151

    Google Scholar 

  • ESRI (2011) ArcGIS desktop: release 10. Environmental Systems Research Institute, Inc., Redlands

    Google Scholar 

  • Feagin RA, Sherman DJ, Grant WE (2005) Coastal erosion, global sea-level rise, and the loss of sand dune plant habitats. Front Ecol Environ 3:359–364

    Google Scholar 

  • Folland C, Salinger M, Rayner N (1997) A comparison of annual South Pacific island and ocean surface temperatures. Weather and Climate 17:23–42

    Google Scholar 

  • Franklin J (2009) Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge

    Google Scholar 

  • Frans VF, Auge AA, Edelhoff H, Erasmi S, Balkenhol N, Engler JO (2018) Quantifying apart what belongs together: a multi-state species distribution modelling framework for species using distinct habitats. Methods Ecol Evol 9:98–108

    Google Scholar 

  • Gherghel I, Brischoux F, Papeş M (2018) Using biotic interactions in broad-scale estimates of species’ distributions. J Biogeogr 45:2216–2225

    Google Scholar 

  • Gherghel I, Brischoux F, Papeş M (In Press) Refining model estimates of potential species’ distributions to relevant accessible areas. Prog Phys Geog: Earth Envt 1–12

  • Gherghel I, Papes M, Brischoux F, Sahlean T, Strugariu A (2016) A revision of the distribution of sea kraits (Reptilia, Laticauda) with an updated occurrence dataset for ecological and conservation research. Zookeys 569:135–148

    Google Scholar 

  • Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186

    Google Scholar 

  • Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009

    Google Scholar 

  • Greer AE (1997) The biology and evolution of Australian snakes. Surrey Beatty, Sydney

    Google Scholar 

  • Heatwole H (1999) Sea snakes. Krieger Publishing Company, Malabar

    Google Scholar 

  • Heatwole H, Busack S, Cogger H (2005) Geographic variation in sea kraits of the Laticauda colubrina complex (Serpentes: Elapidae: Hydrophiinae: Laticaudini). Herpetol Monogr 19:1–136

    Google Scholar 

  • Heatwole H, Grech A, Monahan JF et al (2012) Thermal biology of sea snakes and sea kraits. Integrative and Comparative Biology 52(2):257–273

    PubMed  Google Scholar 

  • Heatwole H, Lillywhite H, Grech A (2016) Physiological, ecological, and behavioural correlates of the size of the geographic ranges of sea kraits (Laticauda; Elapidae, Serpentes): a critique. J Sea Res 115:18–25

    Google Scholar 

  • Heatwole H, Grech A, Marsh H (2017) Paleoclimatology, paleogeography, and the evolution and distribution of sea kraits (Serpentes; Elapidae; Laticauda). Herpetol Monogr 31:1–17

    Google Scholar 

  • Hijmans R, Cameron S, Parra J, Jones P, Jarvis A (2005a) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978

    Google Scholar 

  • Hijmans RJ, Graham CH (2006) The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biol 12:2272–2281

    Google Scholar 

  • Hijmans RJ, Cameron S, Parra J (2005b) WorldClim, Version 1.4, http://www.worldclim.org. University of California, Berkeley

  • Hutchinson GE (1957) Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology 22:415–427

    Google Scholar 

  • Jimenez-Valverde A (2014) Threshold-dependence as a desirable attribute for discrimination assessment: implications for the evaluation of species distribution models. Biodivers Conserv 23:369–385

    Google Scholar 

  • Jimenez-Valverde A, Barve N, Lira-Noriega A, Maher SP, Nakazawa Y, Papes M, Soberon J, Sukumaran J, Peterson AT (2011) Dominant climate influences on North American bird distributions. Global Ecol Biogeogr 20:114–118

    Google Scholar 

  • Lane A, Shine R (2011) Intraspecific variation in the direction and degree of sex-biased dispersal among sea-snake populations. Mol Ecol 20:1870–1876

    PubMed  Google Scholar 

  • Liu C, Newell G, White M (2016) On the selection of thresholds for predicting species occurrence with presence-only data. Ecol Evol 6:337–348

    PubMed  Google Scholar 

  • Manzu C, Gherghel I, Zamfirescu S, Zamfirescu O, Rosca I, Strugariu A (2013) Current and Future Potential Distribution of Glacial Relict Ligularia Sibirica (Asteraceae) in Romania and Temporal Contribution of Natura 2000 to Protect the Species in Light of Global Change. Carpath J Earth Env 8:77–87

    Google Scholar 

  • Mueller EK, Baum KA, Papes M, Cohn LA, Cowell AK, Reichard MV (2013) Potential ecological distribution of Cytauxzoon felis in domestic cats in Oklahoma, Missouri, and Arkansas. Vet Parasitol 192:104–110

    PubMed  Google Scholar 

  • Nix HA (1986) A biogeographic analysis of Australian elapid snakes. In: Longmore R (ed) Atlas of elapid snakes of Australia. Australian Government Publishing Service, Canberra, pp 4–15

    Google Scholar 

  • Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34:102–117

    Google Scholar 

  • Peterson AT (2006) Uses and requirements of ecological niche models and related distributional models. Biodiversity Informatics 3:59–72

    Google Scholar 

  • Peterson AT, Martínez-Meyer E (2007) Geographic evaluation of conservation status of African forest squirrels (Sciuridae) considering land use change and climate change: the importance of point data. Biodivers Conserv 16:3939–3950

    Google Scholar 

  • Peterson AT, Soberon J (2012) Species distribution modeling and ecological niche modeling: getting the concepts right. Nat Conservacao 10:102–107

    Google Scholar 

  • Peterson AT, Papeş M, Kluza DA (2003) Predicting the potential invasive distributions of four alien plant species in North America. Weed Science 51:863–868

    CAS  Google Scholar 

  • Peterson AT, Papes M, Eaton M (2007a) Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent. Ecography 30:550–560

    Google Scholar 

  • Peterson AT, Benz BW, Papeş M (2007b) Highly pathogenic H5N1 avian influenza: entry pathways into North America via bird migration. PLoS ONE 2:e261

    PubMed  PubMed Central  Google Scholar 

  • Peterson AT, Papes M, Soberon J (2008) Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol Model 213:63–72

    Google Scholar 

  • Peterson AT, Ortega-Huerta MA, Bartley J, Sánchez-Cordero V, Soberón J, Buddemeier RH, Stockwell DRB (2002) Future projections for Mexican faunas under global climate change scenarios. Nature 416:626–629

    CAS  PubMed  Google Scholar 

  • Phillips SJ, Dudik M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161–175

    Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259

    Google Scholar 

  • Rickbeil GJM, Coops NC, Drever MC, Nelson TA (2014) Assessing coastal species distribution models through the integration of terrestrial, oceanic and atmospheric data. J Biogeogr 41:1614–1625

    Google Scholar 

  • Robinson LM, Elith J, Hobday AJ, Pearson RG, Kendall BE, Possingham HP, Richardson AJ (2011) Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities. Global Ecol Biogeogr 20:789–802

    Google Scholar 

  • Roever CL, Beyer HL, Chase MJ, van Aarde RJ (2014) The pitfalls of ignoring behaviour when quantifying habitat selection. Divers Distrib 20:322–333

    Google Scholar 

  • Sahlean TC, Gherghel I, Papes M, Strugariu A, Zamfirescu SR (2014) Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian Whip Snake. PLoS ONE 9:e91994

    PubMed  PubMed Central  Google Scholar 

  • Sbrocco EJ, Barber PH (2013) MARSPEC: ocean climate layers for marine spatial ecology. Ecology 94:979

    Google Scholar 

  • Seo C, Thorne JH, Hannah L, Thuiller W (2009) Scale effects in species distribution models: implications for conservation planning under climate change. Biol Letters 5:39–43

    Google Scholar 

  • Shetty S, Shine R (2002) Sexual divergence in diets and morphology in Fijian sea snakes Laticauda colubrina (Laticaudinae). Austral Ecology 27:77–84

    Google Scholar 

  • Siqueira MFd, Peterson AT (2003) Global climate change consequences for cerrado tree species. Biota Neotropica 3:1–14

    Google Scholar 

  • Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, Collingham YC, Erasmus BFN, Ferreira de Siqueira M, Grainger A, Hannah L, Hughes L, Huntley B, Van Jaarsveld AS, Midgely GE, Miles L, Ortega-Huerta MA, Peterson AT, Phillips OL, Williams SE (2004) Extinction risk from climate change. Nature 427:145–148

    CAS  PubMed  Google Scholar 

  • Tyberghein L, Verbruggen H, Pauly K, Troupin C, Mineur F, De Clerck O (2012) Bio-ORACLE: a global environmental dataset for marine species distribution modelling. Global Ecol Biogeogr 21:272–281

    Google Scholar 

  • Warren DL, Glor RE, Turelli M (2010) ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33:607–611

    Google Scholar 

  • Welk E, Schubert K, Hoffmann MH (2002) Present and potential distribution of invasive garlic mustard (Alliaria petiolata) in North America. Divers Distrib 8:219–233

    Google Scholar 

Download references

Acknowledgements

We would like to express our appreciation to Dr. Stanley Fox, Dr. Xiao Feng, Dr. Tiberiu Sahlean, Dr. Alexandru Strugariu, and the two anonymous reviewers for providing important feedback that improved our study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iulian Gherghel.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Topic Editor Alastair Harborne

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gherghel, I., Brischoux, F., Nyári, Á.S. et al. A simple framework for estimating potential distributions of amphibious marine species and implications for conservation. Coral Reefs 39, 1081–1090 (2020). https://doi.org/10.1007/s00338-020-01937-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00338-020-01937-3

Keywords

  • Ecological niche models
  • Large scale
  • Laticauda
  • Life history
  • Maxent
  • Species distribution models