Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited

Abstract

Geographic range shifts are one major organism response to climate change, especially if the rate of climate change is higher than that of species adaptation. Ecological niche models (ENM) and biogeographic inferences are often used in estimating the effects of climatic oscillations on species range dynamics. ENMs can be used to track climatic suitable areas over time, but have often been limited to shallow timescales; biogeographic inference can reach greater evolutionary depth, but often lacks spatial resolution. Here, we present a simple approach that treats them as independent and complementary sources of evidence, which, when used in partnership, can be employed to reconstruct geographic range shifts over deep evolutionary timescales. For testing this, we chose two extreme African disjunctions: Camptoloma (Scrophulariaceae) and Canarina (Campanulaceae), each comprising of three species disjunctly distributed in Macaronesia and eastern/southern Africa. Using inferred ancestral ranges in tandem with preindustrial and paleoclimate ENM hindcastings, we show that the disjunct pattern was the result of fragmentation and extinction events linked to Neogene aridification cycles. Our results highlight the importance of considering temporal resolution when building ENMs for rare endemics with small population sizes and restricted climatic tolerances such as Camptoloma, for which models built on averaged monthly variables were more informative than those based on annual bioclimatic variables. Additionally, we show that biogeographic information can be used as truncation threshold criteria for building ENMs in the distant past. Our approach is suitable when there is sparse sampling on species occurrences and associated patterns of genetic variation, such as in the case of ancient endemics with widely disjunct distributions as a result of climate change.

Echoes of the past: niche evolution, range dynamics, and their coupling shape the distribution of species in the Chrysanthemum zawadskii species complex

“…In recent decades, ENM has developed rapidly, and many modeling methods, such as random forest, MaxEnt, and boosted regression trees, have been proposed (Sillero et al, 2021). Nonetheless, such an approach assumes that the niche of species is conserved, so that it is usually limited to shallow evolutionary timescales, e.g., mid-Holocene, Last Glacial Maximum, and Last Interglacial (Culshaw et al, 2021;Guillory and Brown, 2021). Since the niche of species is often regarded as evolving during speciation, it is necessary to consider the evolution of niche when reconstructing the historical distribution of species over deeper timescales.…”

Ecological Niche Overlap and Prediction of the Potential Distribution of Two Sympatric Ficus (Moraceae) Species in the Indo-Burma Region

“…Ecological niche models (ENMs) can be used to investigate the effects of environmental change on the species distributions across extended timescales, using sampling occurrence and the environmental factors to predict the potential habitats of species. Moreover, the ENMs can more accurately predict species distributions when they incorporate information on population genetic structure and, concomitantly, local adaptation [8,9]. Under changing climates, species generally respond by adaptation or extinction, with 15-37% of species predicted to go extinct by 2050 [10][11][12].…”