期刊
LIMNOLOGY AND OCEANOGRAPHY
卷 62, 期 4, 页码 1393-1408出版社
WILEY
DOI: 10.1002/lno.10506
关键词
-
资金
- Academy of Finland [128987, 268953]
- Academy of Finland (AKA) [268953, 128987, 268953, 128987] Funding Source: Academy of Finland (AKA)
We used natural phytoplankton communities from four coastal regions to test diversity-functioning relationships, relations of N-2-fixing cyanobacteria to nutrient imbalance, and the importance of metacommunity dynamics. Resource availability was measured as total nitrogen and phosphorus. Resource imbalance was determined as (1) the ratio of dissolved inorganic nitrogen to total phosphorus and (2) an experimentally verified indicator quantified by modelling responses in C-14-based primary production to nutrient additions. Resource availability explained variance in biomass, productivity, and species richness, as expected by the Species Energy Theory, but not evenness. Linear mixed-effects models confirmed the overall relation between productivity and resource availability, whereas other resource availability relations showed also notable clustering by region. The Resource Ratio Theory predicting that diversity increases with the number of limiting resources was not supported. Nutrient imbalance had a weak effect on the biomass of N-2-fixing cyanobacteria, but not their share of total phytoplankton biomass. Contrary to many previous studies on biodiversity-ecosystem functioning relationships, we found a highly significant inverse relationship between evenness and biomass. This indicates that species-rich natural phytoplankton communities form the basis for opportunistic species to temporarily monopolize resources and create blooms. The result was consistent across regions, although their community composition differed. Metacommunity dynamics were important, since distance between the regions explained higher percentage of the variability than local resources together. As the species able to monopolize resources vary widely in their role for aquatic food webs and environmental consequences (e.g., food quality, toxicity), species-level trait data is essential to understand better diversity-productivity relationships.
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