Birds track their Grinnellian niche through a century of climate change

Abstract

In the face of environmental change, species can evolve new physiological tolerances to cope with altered climatic conditions or move spatially to maintain existing physiological associations with particular climates that define each species' climatic niche. When environmental change occurs over short temporal and large spatial scales, vagile species are expected to move geographically by tracking their climatic niches through time. Here, we test for evidence of niche tracking in bird species of the Sierra Nevada mountains of California, focusing on 53 species resurveyed nearly a century apart at 82 sites on four elevational transects. Changes in climate and bird distributions resulted in focal species shifting their average climatological range over time. By comparing the directions of these shifts relative to the centroids of species' range-wide climatic niches, we found that 48 species (90.6%) tracked their climatic niche. Analysis of niche sensitivity on an independent set of occurrence data significantly predicted the temperature and precipitation gradients tracked by species. Furthermore, in 50 species (94.3%), site-specific occupancy models showed that the position of each site relative to the climatic niche centroid explained colonization and extinction probabilities better than a null model with constant probabilities. Combined, our results indicate that the factors limiting a bird species' range in the Sierra Nevada in the early 20th century also tended to drive changes in distribution over time, suggesting that climatic models derived from niche theory might be used successfully to forecast where and how to conserve species in the face of climate change.climatic niche ͉ geographic range ͉ elevational gradient ͉ occupancy dynamics N early a century ago, Joseph Grinnell (1) presented the concept of the ecological niche as the primary determinant of a species' range. Grinnell defined the niche as a set of environmental conditions that restricts each species, through ''physiological and psychological respects,'' to a geographical range where it can prosper. In particular, Grinnell (2) discussed the important role played by temperature in ultimately defining range boundaries, but noted that within the limits of physiological tolerance, numerous factors, including interspecific competition, can determine realized range boundaries. Since Grinnell, empirical explorations of species' range determinants have successfully related environmental limits to range boundaries through physiological knowledge (3). At the same time, field and laboratory experiments have demonstrated that species interactions may also limit ranges (4, 5) and climatic associations can rapidly change when species are introduced to new environments (6). Nevertheless, the concept that environmental limiting factors define the niche where a species can have a positive growth rate still remains the dominant explanation for range boundaries (7), suggesting that the spatial extent of the range for most species is approximately equal to the geogra...

Heterogeneity in avian richness-environment relationships along the Pacific Crest Trail

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“…In California, studies of ongoing climate change indicate that montane birds are already responding by shifting their elevation ranges (Tingley et al 2012) and that long-term effects include richness declines and high community turnover (Tingley and Beissinger 2013). Despite evidence for location-specific sensitivity of species to different climatic factors (Tingley et al 2009(Tingley et al , 2012, range predictions of montane birds, given climate change, generally assume species and communities respond universally to climate across their range (Sekercioglu et al 2008, Stralberg et al 2009, Anderson et al 2013. Some regional studies of avian speciesenvironment relationships appear to provide partial support of this assumption, particularly for large regions with relatively low topographic relief and homogenous habitat (DesGranges and LeBlanc 2012).…”

Incorporating uncertainty in predictive species distribution modelling

“…Such a measure must identify how well predictions fit observed data (dealing appropriately with the uncertainty in the observations themselves) while penalizing for model complexity, and should remain unaffected by both autocorrelation in the observed pattern [51] and prevalence [50]. Ideally, models should be tested against independent data, such as in an introduced range [91,92], through use of historic [93] or palaeontological [47] datasets to retrodict distribution, and through the use of simulated data where the ability of the model to recover known processes is a measure of performance.…”

How Should Beta-Diversity Inform Biodiversity Conservation?

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