Species richness is influenced by a nested set of environmental factors, but how do these factors interact across several scales? Our main aim is to disentangle the relative importance of environmental filters and the species pool on the richness of epiphytic bryophytes across spatial scales. To do so, we sampled epiphytic bryophytes in 43 oak forests across the northwest of the Iberian Peninsula. As predictors we used climate, descriptors of forest structure and micro-environment. We applied structural equation modeling to relate these variables with richness and cover at three scales: locality (forest), stand (three stands per forest), and sample (a quadrate in a tree). We assumed top-down relationships, so that large-scale variables influenced lower scale variables, and in which cover directly influenced richness. Richness at the next larger scale (locality to stand and stand to sample) is considered a surrogate of the species pool and included as a predictor of richness at the next smaller scale. Environmental variables explain locality richness, but as we decrease the spatial scale, its importance decreases and the dependence on species pool increases. In addition, we found unexpected bottom-up relationships (between micro-scale environment to locality richness). Our results point to the scale dependence of niche vs. neutral processes: niche processes are important at the locality (forest) scale, while neutral processes are significant at the small (sample) scale. We propose a modified conceptualization of the factors influencing biodiversity at different spatial scales by adding links across different scales (between micro-environment and locality-scale richness in our study).

• Klíčová slova
• Diversity, Neutral processes, Plant, Regional species pool, Scale,
• MeSH
• biodiverzita MeSH
• Bryophyta * MeSH
• ekosystém * MeSH
• stromy MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH

Large-scale biodiversity studies can be more informative if observed diversity in a study site is accompanied by dark diversity, the set of absent although ecologically suitable species. Dark diversity methodology is still being developed and a comparison of different approaches is needed. We used plant data at two different scales (European and seven large regions) and compared dark diversity estimates from two mathematical methods: species co-occurrence (SCO) and species distribution modeling (SDM). We used plant distribution data from the Atlas Florae Europaeae (50 × 50 km grid cells) and seven different European regions (10 × 10 km grid cells). Dark diversity was estimated by SCO and SDM for both datasets. We examined the relationship between the dark diversity sizes (type II regression) and the overlap in species composition (overlap coefficient). We tested the overlap probability according to the hypergeometric distribution. We combined the estimates of the two methods to determine consensus dark diversity and composite dark diversity. We tested whether dark diversity and completeness of site diversity (log ratio of observed and dark diversity) are related to various natural and anthropogenic factors differently than simple observed diversity. Both methods provided similar dark diversity sizes and distribution patterns; dark diversity is greater in southern Europe. The regression line, however, deviated from a 1:1 relationship. The species composition overlap of two methods was about 75%, which is much greater than expected by chance. Both consensus and composite dark diversity estimates showed similar distribution patterns. Both dark diversity and completeness measures exhibit relationships to natural and anthropogenic factors different than those exhibited by observed richness. In summary, dark diversity revealed new biodiversity patterns which were not evident when only observed diversity was examined. A new perspective in dark diversity studies can incorporate a combination of methods.

• Klíčová slova
• Biomod, composite dark diversity, consensus dark diversity, co‐occurrence, frequency, prevalence, species distribution modeling,
• Publikační typ
• časopisecké články MeSH