IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v487y2024ics0304380023002673.html
   My bibliography  Save this article

Habitat modelling of native freshwater mussels distinguishes river specific differences in the Detroit and St. Clair rivers of the Laurentian Great Lakes

Author

Listed:
  • Keretz, Shay S.
  • Woolnough, Daelyn A.
  • Morris, Todd J.
  • Roseman, Edward F.
  • Zanatta, David T.

Abstract

Native freshwater mussels (Bivalvia: Unionidae) were seemingly pushed to extirpation following the establishment of dreissenid mussels in the St. Clair (SCR)–Detroit River (DR) System and the current state of unionids in the main channels of the SCR remains unknown. To assess remnant unionid populations, the DR and SCR were surveyed in 2019 and 2021, respectively, using a mixture of stratified random, historical, potential refuge, and model-selected (SCR sampling only) sites (n = 56 DR sites and 51 SCR sites). Data collected from the DR (2019) were used to create unionid species distribution models in MaxEnt, which produced the model-selected sites for sampling the SCR. A total of 14 live unionids representing 9 species were found among 7 sites in the SCR; however, the DR model projected to the SCR failed to be predictive for unionid presence in the SCR (0 % success). Additional models were created for the DR and SCR using MaxEnt and classification and regression tree (CART) Analysis to elucidate the characteristic differences between the two rivers. MaxEnt modelling showed the highest contributing variable for the DR model was water velocity (m/s) while the highest contributing variable for the SCR model was river distance to the outlet which could be one explanation for why the DR model did not accurately predict unionid presence in the SCR. Additionally, when DR and SCR data were combined in the CART model, the model failed to predict any live unionid sites from the SCR. Variability in model predictions demonstrate the characteristic differences between the DR and SCR. Therefore, model verification for both rivers specific models took place in 2022 (n = 8 DR sites and 6 SCR sites). The DR unionid species distribution model identified 3 additional sites with live unionids (38 % of predicted sites), but the SCR model did not locate any additional live unionid locations (0 % of predicted sites). This research updated our knowledge on native unionid distributions and habitat use in the DR and SCR which could contribute towards unionid conservation in the future.

Suggested Citation

  • Keretz, Shay S. & Woolnough, Daelyn A. & Morris, Todd J. & Roseman, Edward F. & Zanatta, David T., 2024. "Habitat modelling of native freshwater mussels distinguishes river specific differences in the Detroit and St. Clair rivers of the Laurentian Great Lakes," Ecological Modelling, Elsevier, vol. 487(C).
    • Handle: RePEc:eee:ecomod:v:487:y:2024:i:c:s0304380023002673
    DOI: 10.1016/j.ecolmodel.2023.110537
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023002673
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110537?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. Matawa, Farai & Murwira, Amon & Schmidt, Karin S., 2012. "Explaining elephant (Loxodonta africana) and buffalo (Syncerus caffer) spatial distribution in the Zambezi Valley using maximum entropy modelling," Ecological Modelling, Elsevier, vol. 242(C), pages 189-197.
    2. Schmidt, Heiko & Radinger, Johannes & Teschlade, Daniel & Stoll, Stefan, 2020. "The role of spatial units in modelling freshwater fish distributions: Comparing a subcatchment and river network approach using MaxEnt," Ecological Modelling, Elsevier, vol. 418(C).
    3. Doko, Tomoko & Fukui, Hiromichi & Kooiman, Andre & Toxopeus, A.G. & Ichinose, Tomohiro & Chen, Wenbo & Skidmore, A.K., 2011. "Identifying habitat patches and potential ecological corridors for remnant Asiatic black bear (Ursus thibetanus japonicus) populations in Japan," Ecological Modelling, Elsevier, vol. 222(3), pages 748-761.
    4. Gill Ward & Trevor Hastie & Simon Barry & Jane Elith & John R. Leathwick, 2009. "Presence-Only Data and the EM Algorithm," Biometrics, The International Biometric Society, vol. 65(2), pages 554-563, June.
    5. Worthington, Thomas A. & Zhang, Tianjiao & Logue, Daniel R. & Mittelstet, Aaron R. & Brewer, Shannon K., 2016. "Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability," Ecological Modelling, Elsevier, vol. 342(C), pages 1-18.
    6. Zeng, Yiwen & Low, Bi Wei & Yeo, Darren C.J., 2016. "Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish," Ecological Modelling, Elsevier, vol. 341(C), pages 5-13.
    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. Horemans, Dante M.L. & Friedrichs, Marjorie A.M. & St-Laurent, Pierre & Hood, Raleigh R. & Brown, Christopher W., 2024. "Evaluating the skill of correlative species distribution models trained with mechanistic model output," Ecological Modelling, Elsevier, vol. 491(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. Ping He & Yu Gao & Longfei Guo & Tongtong Huo & Yuxin Li & Xingren Zhang & Yunfeng Li & Cheng Peng & Fanyun Meng, 2021. "Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    2. Tyler M Harms & Kevin T Murphy & Xiaodan Lyu & Shane S Patterson & Karen E Kinkead & Stephen J Dinsmore & Paul W Frese, 2017. "Using landscape habitat associations to prioritize areas of conservation action for terrestrial birds," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-21, March.
    3. Masahiro Kato & Shota Yasui, 2020. "Learning Classifiers under Delayed Feedback with a Time Window Assumption," Papers 2009.13092, arXiv.org, revised Jun 2022.
    4. Schwemmer, Philipp & Güpner, Franziska & Adler, Sven & Klingbeil, Knut & Garthe, Stefan, 2016. "Modelling small-scale foraging habitat use in breeding Eurasian oystercatchers (Haematopus ostralegus) in relation to prey distribution and environmental predictors," Ecological Modelling, Elsevier, vol. 320(C), pages 322-333.
    5. Schartel, Tyler E. & Cao, Yong, 2024. "Background selection complexity influences Maxent predictive performance in freshwater systems," Ecological Modelling, Elsevier, vol. 488(C).
    6. Saupe, E.E. & Barve, V. & Myers, C.E. & Soberón, J. & Barve, N. & Hensz, C.M. & Peterson, A.T. & Owens, H.L. & Lira-Noriega, A., 2012. "Variation in niche and distribution model performance: The need for a priori assessment of key causal factors," Ecological Modelling, Elsevier, vol. 237, pages 11-22.
    7. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    8. Barker, Justin R. & MacIsaac, Hugh J., 2022. "Species distribution models applied to mosquitoes: Use, quality assessment, and recommendations for best practice," Ecological Modelling, Elsevier, vol. 472(C).
    9. Xiaoxia Su & Jing Wu & Pengshuo Li & Renjie Li & Penggen Cheng, 2022. "RSEI-Based Modeling of Ecological Security and Its Spatial Impacts on Soil Quality: A Case Study of Dayu, China," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    10. Erard Brian, 2022. "Modeling Qualitative Outcomes by Supplementing Participant Data with General Population Data: A New and More Versatile Approach," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 35-53, January.
    11. Masahiro Kato, 2019. "Identifying Different Definitions of Future in the Assessment of Future Economic Conditions: Application of PU Learning and Text Mining," Papers 1909.03348, arXiv.org, revised Apr 2020.
    12. Kaszta, Żaneta & Marino, Jorgelina & Ramoelo, Abel & Wolff, Eléonore, 2016. "Bulk feeder or selective grazer: African buffalo space use patterns based on fine-scale remotely sensed data on forage quality and quantity," Ecological Modelling, Elsevier, vol. 323(C), pages 115-122.
    13. Cervelli, Elena & Recchi, Pier Francesco & Fagnano, Massimo & Scotto di Perta, Ester & Pindozzi, Stefania, 2024. "Marginal lands between recovery and valorization. An inclusive definition to support bio-energy supply chains. The Southern Italy contexts case study," Agricultural Systems, Elsevier, vol. 217(C).
    14. Yuncheng Zhao & Mingyue Zhao & Lei Zhang & Chunyi Wang & Yinlong Xu, 2021. "Predicting Possible Distribution of Tea ( Camellia sinensis L.) under Climate Change Scenarios Using MaxEnt Model in China," Agriculture, MDPI, vol. 11(11), pages 1-18, November.
    15. Wang, Junhui & Fang, Yixin, 2013. "Analysis of presence-only data via semi-supervised learning approaches," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 134-143.
    16. Małgorzata Łazęcka & Jan Mielniczuk & Paweł Teisseyre, 2021. "Estimating the class prior for positive and unlabelled data via logistic regression," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(4), pages 1039-1068, December.
    17. Brice B Hanberry & Hong S He & Brian J Palik, 2012. "Pseudoabsence Generation Strategies for Species Distribution Models," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    18. Carina Seliger & Melanie Haslauer & Günther Unfer & Stefan Schmutz, 2021. "aquaZone: An Integrative Tool for Sustainable Fish Farm Zoning," Sustainability, MDPI, vol. 13(3), pages 1-25, January.
    19. Qiming Zheng & Tim Ha & Alexander V. Prishchepov & Yiwen Zeng & He Yin & Lian Pin Koh, 2023. "The neglected role of abandoned cropland in supporting both food security and climate change mitigation," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    20. Fern, Rachel R. & Morrison, Michael L. & Wang, Hsiao-Hsuan & Grant, William E. & Campbell, Tyler A., 2019. "Incorporating biotic relationships improves species distribution models: Modeling the temporal influence of competition in conspecific nesting birds," Ecological Modelling, Elsevier, vol. 408(C), pages 1-1.

    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:487:y:2024:i:c:s0304380023002673. 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.