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Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum (LGM) from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ashFraxinus pennsylvanicausing 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross‐validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic‐genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially‐explicit model. Approximate Bayesian computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross‐validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.
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This content will become publicly available on December 6, 2025
Looking out for the little guy: species distribution modeling and conservation implications of the elfin skimmer Nannothemis bella (Odonata: Libellulidae)
Nannothemis bella Uhler, 1857 (Odonata: Libellulidae), the smallest dragonflyin North America, inhabit bogs and sedge fens across their distribution, spanning fromQuebec (Canada) south to Florida and west to Minnesota and Louisiana (USA). While commonin the northern part of their range, N. bella is of conservation concern in the southernpopulations where they are disjunct and rare. Little work has been done on the ecologyand geographic conservation of this species. To fill this knowledge gap, we constructedspecies distribution models (SDMs) to analyze the spatial distribution and climatic nicheof N. bella, define factors in habitat suitability and estimate potential niche shifts underclimate change and inform conservation efforts. Our present-day SDMs indicate the dominantenvironmental elements determining habitat suitability include the proportion of siltin soil, temperature seasonality, percentage of clay and coarse components in soil, and soilclass. Our paleodistribution models show a southern distribution within the last glacialmaximum, with a shift northward 8,326 to 4,200 years ago. Our projected SDMs for 2050under RCP 2.6 and RCP 8.5 predict a significant decrease in habitat suitability throughoutthe entire range of N. bella. As such, N. bella is a species of conservation concern andconservation measures are imperative for its continued existence as a much-needed bioindicatorfor these freshwater ecosystems. Additionally, this ecological knowledge providesthe foundation for identifying population sites from which to collect N. bella for futurepopulation genetic studies.
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- Award ID(s):
- 2244182
- PAR ID:
- 10579039
- Publisher / Repository:
- World Dragonfly Association
- Date Published:
- Journal Name:
- International Journal of Odonatology
- Volume:
- 27
- ISSN:
- 1388-7890
- Page Range / eLocation ID:
- 232 to 241
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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