How to describe species richness patterns for bryophyte conservation?

Area of Science:

• Biodiversity research
• Conservation biology
• Ecology

Background:

• Natural history collections hold vast, underutilized data for inconspicuous taxa.
• Traditional biodiversity studies often neglect museum collection data for pattern analysis.
• Evaluating methods for reconstructing species richness is crucial for conservation planning.

Purpose of the Study:

• To compare the effectiveness of stacked species distribution models (S-SDMs) against direct spatial interpolation for mapping species richness patterns.
• To determine if S-SDMs provide more reliable inferences of diversity richness than simple area selection for inconspicuous taxa.
• To assess the utility of museum collection data in biodiversity studies.

Main Methods:

• The study utilized Iberian species of the genus Grimmia (Bryophyta) as model organisms.
• Maxent-based S-SDMs and direct spatial interpolation models were constructed and compared.
• Models were validated by excluding data from four well-collected areas to test robustness.

Main Results:

• Maxent S-SDMs showed high correlations (0.45 to 0.99) between partial and reference models, indicating reliability.
• Spatial interpolation models exhibited weak and negative correlations (-0.3 to -0.06), suggesting poor performance.
• S-SDMs proved effective in identifying detailed richness patterns for inconspicuous taxa.

Conclusions:

• Stacked species distribution models (S-SDMs) are a valuable tool for mapping biodiversity patterns of inconspicuous taxa.
• This method improves the assessment of under-surveyed areas and fills data gaps in species distributions.
• The strategy enhances the scientific value of biological collections for ecological research and conservation.