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Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties

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  • Lei Zhang
  • Shirong Liu
  • Pengsen Sun
  • Tongli Wang
  • Guangyu Wang
  • Xudong Zhang
  • Linlin Wang

Abstract

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species’ geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species’ ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.

Suggested Citation

  • Lei Zhang & Shirong Liu & Pengsen Sun & Tongli Wang & Guangyu Wang & Xudong Zhang & Linlin Wang, 2015. "Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-18, March.
  • Handle: RePEc:plo:pone00:0120056
    DOI: 10.1371/journal.pone.0120056
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    Cited by:

    1. Lewis A. Jones & Philip D. Mannion & Alexander Farnsworth & Fran Bragg & Daniel J. Lunt, 2022. "Climatic and tectonic drivers shaped the tropical distribution of coral reefs," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Jeong Soo Park & Donghui Choi & Youngha Kim, 2020. "Potential Distribution of Goldenrod ( Solidago altissima L.) during Climate Change in South Korea," Sustainability, MDPI, vol. 12(17), pages 1-11, August.
    3. Quanzhong Zhang & Haiyan Wei & Zefang Zhao & Jing Liu & Qiao Ran & Junhong Yu & Wei Gu, 2018. "Optimization of the Fuzzy Matter Element Method for Predicting Species Suitability Distribution Based on Environmental Data," Sustainability, MDPI, vol. 10(10), pages 1-16, September.
    4. Pecchi, Matteo & Marchi, Maurizio & Burton, Vanessa & Giannetti, Francesca & Moriondo, Marco & Bernetti, Iacopo & Bindi, Marco & Chirici, Gherardo, 2019. "Species distribution modelling to support forest management. A literature review," Ecological Modelling, Elsevier, vol. 411(C).
    5. Perennes, Marie & Diekötter, Tim & Groß, Jens & Burkhard, Benjamin, 2021. "A hierarchical framework for mapping pollination ecosystem service potential at the local scale," Ecological Modelling, Elsevier, vol. 444(C).
    6. Bipin Kumar Acharya & Chunxiang Cao & Min Xu & Laxman Khanal & Shahid Naeem & Shreejana Pandit, 2018. "Present and Future of Dengue Fever in Nepal: Mapping Climatic Suitability by Ecological Niche Model," IJERPH, MDPI, vol. 15(2), pages 1-15, January.
    7. Maurizio Marchi & Iztok Sinjur & Michele Bozzano & Marjana Westergren, 2019. "Evaluating WorldClim Version 1 (1961–1990) as the Baseline for Sustainable Use of Forest and Environmental Resources in a Changing Climate," Sustainability, MDPI, vol. 11(11), pages 1-14, May.
    8. José-Silva, Leandro & dos Santos, Reginaldo Carvalho & de Lima, Bruna Martins & Lima, Mendelson & de Oliveira-Júnior, José Francisco & Teodoro, Paulo Eduardo & Eisenlohr, Pedro V. & da Silva Junior, C, 2018. "Improving the validation of ecological niche models with remote sensing analysis," Ecological Modelling, Elsevier, vol. 380(C), pages 22-30.
    9. Lucas Kruger, 2018. "Population Estimates of Trindade Petrel (Pterodroma arminjoniana) by Ensemble Nesting Habitat Modelling," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 10(4), pages 145-157, April.

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