Using the palaeontological record of Microtus to test species distribution models and reveal responses to climate change
We used newly identified fossil specimens to reconstruct the Quaternary distributions of five Microtus species (Rodentia: Arvicolinae) from the Pacific coast of the United States. We used these distributions to test the hypothesis that when projected onto past, alternative climate surfaces, species distribution models (SDMs) created using only climate variables are concordant with the empirical data of fossil Microtus species occurrences.
Specimens from 11 fossil localities in California, Oregon and Nevada were identified and evaluated.
Geometric morphometrics and discriminant analyses were used to identify fossil Microtus specimens. Using a maximum‐entropy modelling approach, the best model for all five species was selected using the Akaike information criterion. Nineteen bioclimate variables were used to create SDMs for the five Microtus species using both Community Climate System Model (CCSM) and Model for Interdisciplinary Research on Climate (MIROC) models.
We confidently identified 144 Microtus fossils, including the first fossil specimens of Microtus oregoni and Microtus townsendii. SDMs reconstructed approximately half the extralimital fossil occurrences (i.e. those found outside the present‐day range). Those species with extralimital occurrences not reconstructed have niche models primarily influenced by precipitation variables. The two species whose extralimitals were well predicted occupy indistinguishable climatic niches.
The ranges of Pacific coast Microtus species have undergone substantial regional contractions since the Last Glacial Maximum (LGM; 21 ka). Inconsistencies between LGM SDMs and Quaternary fossil ranges indicate potential problems with LGM precipitation reconstructions, although interspecific interactions are also likely to contribute to these differences. Overall, the study highlights the need for further, detailed, species‐level palaeodistributions to put recent observations in a broader temporal context and examine the effectiveness of SDMs coupled with climate models for predicting range dynamics under scenarios of climate change.
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Document Type: Research Article
Publication date: 2013-08-01