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Determinants of moth diversity and community in a temperate mountain landscape: vegetation, topography, and seasonality

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  • Macromoth diversity, abundance, and community structure in the topographically complex HJ Andrews Experimental Forest and LTER site was studied on the west slope of the Cascade Range, Oregon. Data on 493 macromoth species (62,221 individuals) was sampled eight times/year at 20 locations from 2004 to 2008 and examined using multivariate statistics and generalized additive models to determine the importance of topography and vegetation on moth community assembly and diversity. Significant differences exist between moth communities at lower and higher elevations. High‐elevation moth communities are far more variable inter‐annually, whether associated with high‐elevation forests, meadows, or clearcuts. Low‐elevation young and old gymnosperm forests and riparian forests are more stable and predictable communities having less inter‐annual variability. High‐elevation communities show more intra‐annual variability than low‐elevation communities. Low‐elevation moth communities are more abundant than high‐elevation communities and typically associated with the most common, abundant species of macromoths in the study. High‐elevation communities, by contrast, are associated with less abundant, more evenly distributed species, as well as with rare moth species. Macromoth community structure and diversity were related to year or sample period and structural descriptions of vegetation communities, but not related to known host‐plant diversity. High‐elevation communities are threatened by contraction of montane meadows and climate change which, given the variability in high‐elevation communities, could severely impact the biological diversity of the western Cascades landscape. Nocturnal macromoths represent an important potential indicator of ecosystem health and change.
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  • Highland, S. A., J. C. Miller, and J. A. Jones. 2013. Determinants of moth diversity and community in a temperate mountain landscape: vegetation, topography, and seasonality. Ecosphere 4(10):129. doi:10.1890/ES12-00384.1
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  • 4
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  • 10
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Déclaration de droits
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  • This research was supported by grants to the HJ Andrews Experimental Forest and LTER (NSF 0823380), the NSF EcoInformatics Summer Institute REU (NSF 1005175), and also funding for machine learning models for species distributions (NSF0941748).
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file details HighlandStevenCEOASDeterminantsMothDiversityKnownHostPlantPresence_Supplement.zip 07/26/2017 Public
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