Liu, Ying and Liu, Shuaishuai and Bede-Fazekas, Ákos and Mammola, Stefano and Ding, Liuyong and Gu, Jiqi and Nakamura, Gabriel and Lin, Qiang and Wang, Dazhi and Zhang, Zhixin (2026) Factors Influencing Species Distribution Model Performance in Tropical Reef Fishes. DIVERSITY AND DISTRIBUTIONS, 32 (2). No. e70160. ISSN 1366-9516
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2026.03.YL-SL-ABF-SM-LD-JG-GN-QL-DW-ZZtraitDivDistr13oldalen.pdf - Published Version Available under License Creative Commons Attribution. Download (836kB) | Preview |
Abstract
Aim Reliable biodiversity assessments using species distribution models (SDMs) are essential for effective conservation and management. Understanding factors influencing SDM performance is crucial for improving model reliability, yet such links remain underexplored in marine systems. To address this gap, we quantified the effects of geographical and species-level factors on SDM performance in tropical reef fishes, aiming to provide practical guidelines on which species are more likely to yield reliable predictions. Location Global tropical reef ecosystems. Methods We built ensemble SDMs for 1941 tropical reef fish species using occurrence records. We evaluated model predictive performance using the continuous Boyce index, the most suitable performance metric given that we lacked quality absence data, and two other commonly applied metrics (the area under the receiving operating characteristic curve and the true skill statistic). We compiled 10 factors related to species' geographical and ecological characteristics and assessed their influence on model performance using phylogenetic generalised linear models. Results Ensemble SDMs for tropical reef fishes exhibited high predictive performance based on the three evaluation metrics. Phylogenetic generalised linear models relating evaluation metrics to species geographical and ecological characteristics showed modest explanatory power, with R2 varying from 0.253 to 0.341. Across evaluation metrics, SDM performance was strongly associated with species' latitude, proximity to shore, and environmental similarity between training and evaluation datasets. For continuous Boyce index, there were additional significant effects for range size, parental care, range coverage, and species description year. Main Conclusions Our study provides a practical framework for identifying tropical reef fish species more likely to yield reliable SDM predictions. The identified factors offer guidance for researchers to anticipate model reliability before undertaking extensive modelling efforts. This large-scale, multi-species comparative approach is broadly applicable to other marine taxa and regions, advancing our ability to model and conserve marine biodiversity.
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| Additional Information: | Funding Agency and Grant Number: the Guangdong Basic and Applied Basic Research Foundation [2024A1515010604]; National Multidisciplinary Laboratory for Climate Change [RRF-2.3.1-21-2022-00014]; Jnos Bolyai Research Scholarship of the Hungarian Academy of Sciences; National Key Research and Development Program of China [2023YFC3108800]; the National Natural Science Foundation of China [42230409] Funding text: This work was funded by the National Natural Science Foundation of China (42230409 and 42276126), the National Key Research and Development Program of China (2023YFC3108800), and the Guangdong Basic and Applied Basic Research Foundation (2024A1515010604). A.B.-F. was supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences. This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union. |
| Uncontrolled Keywords: | biodiversity conservation , marine biodiversity , predictive performance , range estimation , reef fish , species distribution model |
| Subjects: | Q Science / természettudomány > QH Natural history / természetrajz > QH301 Biology / biológia |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 21 Sep 2026 11:50 |
| Last Modified: | 21 Sep 2026 11:50 |
| URI: | https://real.mtak.hu/id/eprint/247025 |
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