IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v470y2022ics0304380022001119.html
   My bibliography  Save this article

HyDiaD: A hybrid species distribution model combining dispersal, multi-habitat suitability, and population dynamics for diadromous species under climate change scenarios

Author

Listed:
  • Barber-O'Malley, Betsy
  • Lassalle, Géraldine
  • Chust, Guillem
  • Diaz, Estibaliz
  • O'Malley, Andrew
  • Paradinas Blázquez, César
  • Pórtoles Marquina, Javier
  • Lambert, Patrick

Abstract

Diadromous species are particularly vulnerable to climate change because they utilize both marine and freshwater habitat to complete their life cycles. Dispersal plays an important role in restraining the distribution of plant and animal species, and is a key mechanism to allow diadromous species to adapt to changes in habitat suitability, but it is often not included in species distribution models that explore population trends under climate scenarios. The objective of this study was to develop a model to estimate potential shifts in diadromous populations in the Atlantic area of Europe under two climate change scenarios and multiple global climate models. To address the question of range-shift responses, a hybrid approach for diadromous species distribution (HyDiaD) was developed that incorporated two components: i) statistical static models of habitat suitability describing the influence of environmental factors on species occurrence, and ii) biological processes relevant for the distribution of the species, such as population demography and dispersal dynamics. Hybrid models were developed using a novel approach that incorporated both population and between-catchment dispersal dynamics specific to each species. Occupancy data for diadromous species in a subset of Atlantic Area catchments were first validated by regional experts, and boosted regression trees were applied to estimate habitat suitability within each catchment based on historical physical and climatic environmental predictors from the continental and marine domains. Habitat suitability was then used in a population dynamics model that incorporated between-catchment dispersal and local population growth. Results for different-sized catchments were compared using time series of spawner density and saturation rate, which estimated how much of the available habitat was being utilized. Many of the species-specific values used in HyDiaD were estimated through a survey of diadromous species experts, and group consensus was reached by calculating weighted averages. The HyDiaD model was applied to two shad species (Alosa alosa and A. fallax) to explore population trends projected annually from 1951 to 2100. Projected trends indicated that under XXIst century climate scenarios, habitat suitability is expected to increase for A. fallax, but decrease for A. alosa. Projected trends also indicated an increase in the rate of annual variability for A. alosa, particularly in the southern part of its range. Future studies can utilize the HyDiaD model to explore distribution trends for other diadromous species under climate change scenarios.

Suggested Citation

  • Barber-O'Malley, Betsy & Lassalle, Géraldine & Chust, Guillem & Diaz, Estibaliz & O'Malley, Andrew & Paradinas Blázquez, César & Pórtoles Marquina, Javier & Lambert, Patrick, 2022. "HyDiaD: A hybrid species distribution model combining dispersal, multi-habitat suitability, and population dynamics for diadromous species under climate change scenarios," Ecological Modelling, Elsevier, vol. 470(C).
  • Handle: RePEc:eee:ecomod:v:470:y:2022:i:c:s0304380022001119
    DOI: 10.1016/j.ecolmodel.2022.109997
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380022001119
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2022.109997?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Holloway, Paul & Miller, Jennifer A., 2017. "A quantitative synthesis of the movement concepts used within species distribution modelling," Ecological Modelling, Elsevier, vol. 356(C), pages 91-103.
    2. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).
    3. Florian Elmer & Isabel Seifert & Heidi Kreibich & Annegret H. Thieken, 2010. "A Delphi Method Expert Survey to Derive Standards for Flood Damage Data Collection," Risk Analysis, John Wiley & Sons, vol. 30(1), pages 107-124, January.
    4. Ilkka Hanski, 1998. "Metapopulation dynamics," Nature, Nature, vol. 396(6706), pages 41-49, November.
    5. Singer, Alexander & Schweiger, Oliver & Kühn, Ingolf & Johst, Karin, 2018. "Constructing a hybrid species distribution model from standard large-scale distribution data," Ecological Modelling, Elsevier, vol. 373(C), pages 39-52.
    6. Rebecca Mary B. Harris & Michael R. Grose & Greg Lee & Nathaniel L. Bindoff & Luciana L. Porfirio & Paul Fox‐Hughes, 2014. "Climate projections for ecologists," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 5(5), pages 621-637, September.
    7. Citores, L. & Ibaibarriaga, L. & Lee, D.-J. & Brewer, M.J. & Santos, M. & Chust, G., 2020. "Modelling species presence–absence in the ecological niche theory framework using shape-constrained generalized additive models," Ecological Modelling, Elsevier, vol. 418(C).
    8. Rocco Scolozzi & Davide Geneletti, 2012. "Assessing habitat connectivity for land-use planning: a method integrating landscape graphs and Delphi survey," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 55(6), pages 813-830, September.
    9. Singer, Alexander & Johst, Karin & Banitz, Thomas & Fowler, Mike S. & Groeneveld, Jürgen & Gutiérrez, Alvaro G. & Hartig, Florian & Krug, Rainer M. & Liess, Matthias & Matlack, Glenn & Meyer, Katrin M, 2016. "Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions?," Ecological Modelling, Elsevier, vol. 326(C), pages 63-74.
    10. Rougier, Thibaud & Drouineau, Hilaire & Dumoulin, Nicolas & Faure, Thierry & Deffuant, Guillaume & Rochard, Eric & Lambert, Patrick, 2014. "The GR3D model, a tool to explore the Global Repositioning Dynamics of Diadromous fish Distribution," Ecological Modelling, Elsevier, vol. 283(C), pages 31-44.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ashley, Matthew & Murillas, Arantza & Muench, Angela & Marta-Pedroso, Cristina & Rodwell, Lynda & Rees, Sian & Rendle, Emma & Bašić, Tea & Copp, Gordon H. & Díaz, Estibaliz & Nachón, David J. & Lamber, 2023. "An evidence base of ecosystems services provided by diadromous fish in the European Atlantic Area," Ecosystem Services, Elsevier, vol. 64(C).
    2. Cushman, S.A. & Kilshaw, K. & Campbell, R.D. & Kaszta, Z. & Gaywood, M. & Macdonald, D.W., 2024. "Comparing the performance of global, geographically weighted and ecologically weighted species distribution models for Scottish wildcats using GLM and Random Forest predictive modeling," Ecological Modelling, Elsevier, vol. 492(C).
    3. Benkendorf, Donald J. & Schwartz, Samuel D. & Cutler, D. Richard & Hawkins, Charles P., 2023. "Correcting for the effects of class imbalance improves the performance of machine-learning based species distribution models," Ecological Modelling, Elsevier, vol. 483(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Singer, Alexander & Schweiger, Oliver & Kühn, Ingolf & Johst, Karin, 2018. "Constructing a hybrid species distribution model from standard large-scale distribution data," Ecological Modelling, Elsevier, vol. 373(C), pages 39-52.
    2. Valle, Mireia & Ramírez-Romero, Eduardo & Ibaibarriaga, Leire & Citores, Leire & Fernandes-Salvador, Jose A. & Chust, Guillem, 2024. "Pan-Atlantic 3D distribution model incorporating water column for commercial fish," Ecological Modelling, Elsevier, vol. 490(C).
    3. Loehle, Craig, 2018. "Disequilibrium and relaxation times for species responses to climate change," Ecological Modelling, Elsevier, vol. 384(C), pages 23-29.
    4. Früh, Linus & Kampen, Helge & Kerkow, Antje & Schaub, Günter A. & Walther, Doreen & Wieland, Ralf, 2018. "Modelling the potential distribution of an invasive mosquito species: comparative evaluation of four machine learning methods and their combinations," Ecological Modelling, Elsevier, vol. 388(C), pages 136-144.
    5. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    6. Freitas, Osmar & Araujo, Sabrina B.L. & Campos, Paulo R.A., 2022. "Speciation in a metapopulation model upon environmental changes," Ecological Modelling, Elsevier, vol. 468(C).
    7. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Konstantin M. Chumakov & Neal A. Halsey & Tapani Hovi & Philip D. Minor & John F. Modlin & Peter A. Patriarca & Roland W. Sutter & Peter F. Wright & S, 2013. "Review and Assessment of Poliovirus Immunity and Transmission: Synthesis of Knowledge Gaps and Identification of Research Needs," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 606-646, April.
    8. Agnes B. Olin & Ulf Bergström & Örjan Bodin & Göran Sundblad & Britas Klemens Eriksson & Mårten Erlandsson & Ronny Fredriksson & Johan S. Eklöf, 2024. "Predation and spatial connectivity interact to shape ecosystem resilience to an ongoing regime shift," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    9. Vincent Bian & Merrick Cai & Christopher L. Follett, 2023. "Understanding opposing predictions of Prochlorococcus in a changing climate," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    10. Gerling, Charlotte & Wätzold, Frank, 2019. "Evaluating policy instruments for the conservation of biodiversity in a changing climate," MPRA Paper 95512, University Library of Munich, Germany.
    11. Simeon D. Castle & Michiel Stock & Thomas E. Gorochowski, 2024. "Engineering is evolution: a perspective on design processes to engineer biology," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    12. Rodrigues, Lucas dos Santos & Daudt, Nicholas Winterle & Cardoso, Luis Gustavo & Kinas, Paul Gerhard & Conesa, David & Pennino, Maria Grazia, 2023. "Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends," Ecological Modelling, Elsevier, vol. 486(C).
    13. Ledda, Antonio & De Montis, Andrea, 2019. "Infrastructural landscape fragmentation versus occlusion: A sensitivity analysis," Land Use Policy, Elsevier, vol. 83(C), pages 523-531.
    14. Fabritius, Henna & Knegt, Henrik de & Ovaskainen, Otso, 2021. "Effects of a mobile disturbance pattern on dynamic patch networks and metapopulation persistence," Ecological Modelling, Elsevier, vol. 460(C).
    15. Buda, Andrzej & Kwapień, Jarosław, 2022. "Agent-based modelling of the global phonographic market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    16. Varos Petrosyan & Fedor Osipov & Vladimir Bobrov & Natalia Dergunova & Andrey Omelchenko & Alexander Varshavskiy & Felix Danielyan & Marine Arakelyan, 2020. "Species Distribution Models and Niche Partitioning among Unisexual Darevskia dahli and Its Parental Bisexual ( D. portschinskii , D. mixta ) Rock Lizards in the Caucasus," Mathematics, MDPI, vol. 8(8), pages 1-21, August.
    17. Bassi, Ivana & Gori, Enrico & Iseppi, Luca, 2019. "Assessing environmental awareness towards protection of the Alps: a case study," Land Use Policy, Elsevier, vol. 87(C).
    18. Curtis Champion & James R. Lawson & Joanna Pardoe & Derrick O. Cruz & Ashley M. Fowler & Fabrice Jaine & Hayden T. Schilling & Melinda A. Coleman, 2023. "Multi-criteria analysis for rapid vulnerability assessment of marine species to climate change," Climatic Change, Springer, vol. 176(8), pages 1-20, August.
    19. E. Kula & M. Lazorík, 2015. "Comparison of Myriapoda in beech and spruce forests," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 61(7), pages 306-314.
    20. Malishev, Matthew & Kramer-Schadt, Stephanie, 2021. "Movement, models, and metabolism: Individual-based energy budget models as next-generation extensions for predicting animal movement outcomes across scales," Ecological Modelling, Elsevier, vol. 441(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:470:y:2022:i:c:s0304380022001119. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.