Fossils show those dang mammals lived in all the spots they weren’t supposed to live in. Climate models don’t predict the climate, and animal distribution models don’t predict (or in this case hindcast) animal distribution either. How little we know, and how adaptable is biology?
This calls into question all the headline prophecies about the extinction of cute furry critters due to climate change.
The modelers were sure that animals would be unable to cope with temperature changes and would not have lived in the same places as they do now during a climate so different. By crikey, it was an ice age! Yet those small mammals, whose defining biology is that regulate their own temperature, flummoxed the models by living nearer the glacier sheets where the models predicted they would not live.
All the alarming forecasts of local extinctions of mammals come from assumptions built into modern models that fail in multiple ways. The temperature changes from the last 20,000 years show that these mammals have already survived massive shifts, both colder and warmer, and that anything we face in the next century is but a flea on a hippo.
In the graph, the dots are the fossils, the blue marks the hypothesis — the zone where they were supposed to be confined. The stripes mark the ominous ice-cap-from-hell. (Where will those Canadians go?)
How devastating are these results?
In general, the LGM models predict refugia to the south of observed fossil occurrences (Fig. 1). Additionally, none of these hindcasts is significantly better than randomly assigning presence, with four of the five actually making fewer correct predictions than the null model (Table 1). Strikingly, none of the hindcasts makes more correct predictions than simply assuming absence at all sites (Table 2). The hindcasts show no clear relationship between positive predictive power (PPP) and diet or habitat (Table 3).
Why is it so?
The authors suggest four possible reasons the models fail:
1. Mammals may be able to live in a wider range of temperatures than modern conditions suggest. 2. Mammals can evolve fast enough to cope with natural climate change. 3. The climate models might get past temperatures wrong. (They say this needs to be addressed first). 4. Temperatures might not be that important to animals and models overemphasize the correlation between temperature and animals.
In the end, we propose four possible causes for these patterns of biased prediction: 1) modern distributions may not reflect the full range of environmental conditions in which a species can survive and, taken alone, serve as poor predictors of their potential distributions under other climate regimes. 2) The environmental tolerances of mammalian species can evolve fast enough to have changed since the LGM, so modern distributions are poor predictors of deeper time distributions, but may still be good predictors of shallow time responses to climate change. The overlap in LGM ranges between two congeners whose ranges do not currently overlap – G. sabrinus and G. volans – suggests that this may be the case; the cooler climate of the LGM may have decreased the importance of competitive exclusion within Glaucomys. 3) The problem lies with the general circulation models (GCMs) used to reconstruct LGM climate, so the reconstructed ranges are biased southwards because of incorrect temperature and/or precipitation values near the continental glaciers. Other workers have suggested problems with GCM reconstruction of climate regimes near glaciers (Hyde and Peltier 1993, Jackson et al. 2000, McGuire and Davis 2013), so this problem must be addressed before the others can be considered. 4) The models used to hindcast ranges are based on correlations between climatic variables and occurrence data in modern ecosystems. Both GARP and MaxENT overparamaterize these correlations, making them powerful tools for estimating ranges of modern taxa. However, the changing distribution and relationships between climatic variables mean that modern ecosystems may not be appropriate analogs for alternative climatic regimes, such as those that existed during the LGM and that may result from future warming.
Ecological niche models (ENMs) are crucial tools for anticipating range shifts driven by climate change. As hypotheses of future biotic change, they can be difficult to test using independent data. The fossil record is the best way to assess the ability of ENMs to correctly predict range shifts because it provides empirical ranges under novel climate conditions. We tested the performance of ENMs using fossil distributions from the Last Glacial Maximum (LGM, ∼21 000 yr ago). We compared hindcast ENM LGM distribution hypotheses for five species of small mammals, drawn from the published literature, to the known LGM fossil record for those species and found a consistent southern prediction bias in the ENMs. This bias urges caution in interpreting future range predictions, and we suggest that the Pleistocene and Holocene fossil record should be used as an additional resource for calibrating niche modelling for conservation planning.
Davis, E. B., McGuire, J. L. and Orcutt, J. D. (2014), Ecological niche models of mammalian glacial refugia show consistent bias. Ecography, 37: 1133–1138. doi: 10.1111/ecog.01294 [abstract]