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The salinization of freshwaters is a global threat to aquatic biodiversity. We quantified variation in chloride (Cl−) tolerance of 19 freshwater zooplankton species in four countries to answer three questions: (1) How much variation in Cl− tolerance is present among populations? (2) What factors predict intraspecific variation in Cl− tolerance? (3) Must we account for intraspecific variation to accurately predict community Cl− tolerance? We conducted field mesocosm experiments at 16 sites and compiled acute LC50s from published laboratory studies. We found high variation in LC50s for Cl− tolerance in multiple species, which, in the experiment, was only explained by zooplankton community composition. Variation in species‐LC50 was high enough that at 45% of lakes, community response was not predictable based on species tolerances measured at other sites. This suggests that water quality guidelines should be based on multiple populations and communities to account for large intraspecific variation in Cl− tolerance. [ABSTRACT FROM AUTHOR]

The species-area relationship (SAR) plays a central role in biodiversity research, and recent work has increased awareness of its temporal analogue the species time relationship (STR). Here we provide evidence for a general species-time-area relationship (STAR), in which species number is a function of the area and time span of sampling, as well as their interaction. For eight assemblages, ranging from lake zooplankton to desert rodents, this model outperformed a sampling-based model and two simpler models in which area and time had independent effects. In every case, the interaction term was negative, meaning that rates of species accumulation in space decreased with the time span of sampling, while species accumulation rates in time decreased with area sampled. Although questions remain about its precise functional form, the STAR provides a tool for scaling species richness across time and space, for comparing the relative rates of species turnover in space and time at different scales of sampling, and for rigorous testing of mechanisms proposed to drive community dynamics. Our results show that the SAR and STR are not separate relationships but two dimensions of one unified pattern. Key words: community; dynamics; spatiotemporal scaling; species-area relationship: species diversity; species-time relationship; turnover.

Ecology Letters (2010) 13: 453–463 Environmental variability in space and time is a primary mechanism allowing species that share resources to coexist. Fluctuating conditions are a double edged sword for diversity, either promoting coexistence through temporal niche partitioning or excluding species by stochastic extinctions. The net effect of environmental variation on diversity is largely unknown. We examined the association between zooplankton species richness in lakes and environmental variability on interannual, seasonal and shorter time scales, as well as long-term average conditions. We analyzed data on physical, chemical and biological limnology in 53 temperate zone lakes in North America and Europe sampled over a combined 1042 years. Large fluctuations in pH, phosphorus and dissolved organic carbon concentration on different time scales were associated with reduced zooplankton species richness. More species were found in lakes that showed greater temperature variation on all time scales. Environmental variability on different time scales showed similar or, in some cases, stronger associations with zooplankton species richness compared with long-term average conditions. Our results suggest that temporal fluctuations in the chemical environment tend to exclude zooplankton species while temperature variability promotes greater richness. The results indicate that anthropogenic increases in temporal variability of future climates may have profound effects on biodiversity. [ABSTRACT FROM AUTHOR]

Researchers have long viewed patterns of species association as key to understanding the processes that structure communities. Community‐level tests of species association have received the most attention; however, pairwise species associations may offer greater opportunity for linking patterns to specific mechanisms. Although several tests of pairwise association have been developed, there remain gaps in our understanding of their performance. Consequently, it is unclear whether these methods reliably detect patterns of association, or if any one method is superior. We maximized association patterns for single species pairs in synthetic community matrices and examined how accurately five pairwise association tests found that pair, while not finding others (i.e., type I and II error rates). All tests are more likely to miss patterns of association than to falsely detect them. When we maximized association for a species pair that included one or more rare or common species, tests were frequently unable to identify that pair as significantly associated. Consequently, these tests are best suited for identifying significant associations between pairs of species that occur in an intermediate number of samples; for such pairs, three of the five tests considered here detected 100% of the pairs for which we maximized associations. [ABSTRACT FROM AUTHOR]