4.5 Article

Selection of climate variables in ant species distribution models: case study in South Korea

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SPRINGER
DOI: 10.1007/s00484-023-02588-z

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Climate change; Climate envelope model; Ecological niche model; Diversity; Turnover rate; Richness

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The selection of explanatory variables is crucial in species distribution models for predicting the response to climate change. This study compared the effectiveness of temperature-only and temperature with precipitation models in predicting the distribution of ant species. Most species showed similar results between the two models, except for changes in species richness. The turnover rate of ant assemblages was predicted to increase with decreases in temperature and increases in elevation. Overall, our results highlight the uncertainty in predicting the distribution and diversity of organisms in response to climate change due to the variability of the variables used in the models.
The selection of explanatory variables is important in modeling prediction of changes in species distribution in response to climate change. In this study, we evaluated the importance of variable selection in species distribution models. We compared two different types of models for predicting the distribution of ant species: temperature-only and both temperature and precipitation. Ants were collected at 343 forest sites across South Korea from 2006 through 2009. We used a generalized additive model (GAM) to predict the future distribution of 16 species that showed significant responses to changes in climatic factors (temperature and/or precipitation). Four types of GAMs were constructed: temperature, temperature with interaction of precipitation, temperature and precipitation without interaction, and temperature and precipitation with interaction. Most species displayed similar results between the temperatureonly and the temperature and precipitation models. The results for predicted changes in species richness were different from the temperature-only model. This indicates higher uncertainty in the prediction of species richness, which is obtained by combining the prediction results of distribution change for each species, than in the prediction of distribution change. The turnover rate of the ant assemblages was predicted to increase with decreases in temperature and increases in elevation, which was consistent with other studies. Finally, our results showed that the prediction of the distribution or diversity of organisms responding to climate change is uncertain because of the high variability of the model outputs induced by the variables used in the models.

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