Skip to main content
Dryad

Vegetation growth and landscape genetics of Tillandsia lomas at its dry limits in the Atacama Desert shows fine-scale response to environmental parameters

Koch, Marcus1

Published Nov 30, 2020 on Dryad. https://doi.org/10.5061/dryad.8sf7m0cjm

Data files

Abstract

1. Ecosystems at its dry limits have been studied while focusing on species biology, fitness and interactions of biotic and abiotic parameters; however, the interactive effects of these parameters remain under-explored and, therefore, information is often lacking about the putative effect of global climate change on these ecosystems.

2. Here, we conducted an analysis of the interplay of fine-scale landscape genetics and biotic and abiotic factors of terrestrial Tillandsia lomas in the hyperarid Atacama Desert, characterized by a fog-dependent vegetation type consisting of almost one single vascular plant species only.

3. We showed that metapopulations of Tillandsia landbeckii are genetically connected over many hundreds of squarekilometres, and despite a large potential to propagate clonally genetic diversity is structured, regionally and locally. On landscape-level genetic diversity correlates well with fitness parameters such as growth, flowering and vegetation density, and we observed also fine-scaled correlation with a 3-D landscape model indicating a positive feedback with saisonal fog occurrence and availability. The various interdependies of biotic and abiotic factors also result in regular linear banding patterns of vegetation arranged orthogonally towards landscape slope. Ex-situ growth experiments indicate that T. landbeckii growths at optimal rates within this extreme, hyperarid environment, and we can extrapolate mean biomass production for this particular ecosystem.

4. Synthesis. Our results suggest that the unique ecosystem of terrestrial Tillandsia lomas in the hyperarid Atacama Desert is an evolutionary balanced and fine-scaled system. Vegetation itself is built up by long-lived and persistent modules. We developed a descriptive model of the various interacting factors, thereby highlighting also a severe threat caused by global climate change.