The drivers of dark diversity in the Scandinavian mountains are metric‐dependent
Question: Dark diversity refers to the set of species that are not observed in an area but could potentially occur based on suitable local environmental conditions. In this paper, we applied both niche-based and co-occurrence-based methods to estimate the dark diversity of vascular plant species in the subarctic mountains. We then aimed to unravel the drivers explaining (a) why some locations were missing relatively more suitable species than others, and (b) why certain plant species were more often absent from suitable locations than others. Location: The Scandinavian mountains around Abisko, northern Sweden. Methods: We calculated the dark diversity in 107 plots spread out across four mountain trails using four different methods: two co-occurrence-based (Beals’ index and the hypergeometric method) and two niche-based (the climatic niche model and cli-matic niche model followed by species-specific threshold). We then applied multiple Generalized Linear Mixed-Effects Models and General Linear Models to determine which habitat characteristics and species traits contributed the most to dark diversity. Results: The study showed a notable divergence in the predicted drivers of dark diversity depending on the method used. Nevertheless, we can conclude that plot-level dark diversity was generally 17% higher in areas at low elevations and 31% higher in areas with a low species richness. Conclusion: Our findings call for caution when interpreting statistical findings of dark-diversity estimates. Even so, all analyses point toward an important role for natural processes such as competitive dominance as the main driver of the spatial patterns found in dark diversity in the northern Scandes.
Source (journal)
Journal of vegetation science. - Uppsala, 1990, currens
Uppsala : 2023
1100-9233 [print]
1654-1103 [online]
34 :6 (2023) , p. 1-16
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The potential for upward range expansion of alien plant species in cold-climate mountains in a warming world.
Advancing predictions of Species Distribution Models by incorporating local-scale abiotic and biotic drivers.
'SoilTemp': naar een globale database van bodemtemperatuur
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Creation 07.11.2023
Last edited 15.11.2023
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