McCune, Jenny L.
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Browsing McCune, Jenny L. by Subject "Biogeography"
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- ItemContext-dependent interactions and the regulation of species richness in freshwater fish(Nature Publishing Group, 2018) MacDougall, Andrew S.; Harvey, Eric; McCune, Jenny L.; Nilsson, Karin A.; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B.; Kelly, Jocelyn; Tunney, Tyler D.; McMeans, Bailey; Matsuzaki, Shin-Ichiro S.; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S.Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11o latitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.
- ItemSpecies distribution models rarely predict the biology of real populations(Wiley, 2022) Lee-Yaw, Julie A.; McCune, Jenny L.; Pironon, Samuel; Sheth, Seema N.Species distribution models (SDMs) are widely used in ecology. In theory, SDMs capture (at least part of) species' ecological niches and can be used to make inferences about the distribution of suitable habitat for species of interest. Because habitat suitability is expected to influence population demography, SDMs have been used to estimate a variety of population parameters, from occurrence to genetic diversity. However, a critical look at the ability of SDMs to predict independent data across different aspects of population biology is lacking. Here, we systematically reviewed the literature, retrieving 201 studies that tested predictions from SDMs against independent assessments of occurrence, abundance, population performance, and genetic diversity. Although there is some support for the ability of SDMs to predict occurrence (~53% of studies depending on how support was assessed), the predictive performance of these models declines progressively from occurrence to abundance, to population mean fitness, to genetic diversity. At the same time, we observed higher success among studies that evaluated performance for single versus multiple species, pointing to a possible publication bias. Thus, the limited accuracy of SDMs reported here may reflect the best-case scenario. We discuss the limitations of these models and provide specific recommendations for their use for different applications going forward. However, we emphasize that predictions from SDMs, especially when used to inform conservation decisions, should be treated as hypotheses to be tested with independent data rather than as stand-ins for the population parameters we seek to know.