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1. Improving the mechanistic basis of biodiversity-ecosystem function relationships requires a better understanding of how functional traits drive the dynamics of populations. For example, environmental disturbances or grazing may increase synchronization of functionally similar species, whereas functionally different species may show independent dynamics, because of different responses to the environment. Competition for resources, on the other hand, may yield a wide range of dynamic patterns among competitors and lead functionally similar and different species to display synchronized to compensatory dynamics. The mixed effect of these forces will influence the temporal fluctuations of populations and, thus, the variability of aggregate community properties.
2. To search for a relationship between functional and dynamics similarity, we studied the relationship between functional trait similarity and temporal dynamics similarity for 36 morphotypes of phytoplankton using long-term high-frequency measurements.
3. Our results show that functionally similar morphotypes exhibit dynamics that are more synchronized than those of functionally dissimilar ones. Functionally dissimilar morphotypes predominantly display independent temporal dynamics. This pattern is especially strong when short time-scales are considered.
4. Negative correlations are present among both functionally similar and dissimilar phytoplankton morphotypes, but are rarer and weaker than positive ones over all temporal scales.
5. Synthesis. We demonstrate that diversity in functional traits decreases community variability and ecosystem-level properties by decoupling the dynamics of individual morphotypes.
Gaining understanding of food-web processes often requires a simplified representation of natural diversity. One such simplification can be based on functional traits, as functionally similar species may provide a similar contribution to ecosystem level-processes. However, understanding how similarity in functional traits actually translates into similar contributions to ecosystem-level properties remains a challenge due to the complex ways in which traits can influence species' dynamics. Moreover, in many communities, seasonality alters the abiotic and biotic forcing regime, causing ongoing changes to patterns of species' dominance; groups of species do not stay intact but are rather continuously subjected to changes throughout the year. Using long-term high frequency measurements of phytoplankton in Lake Constance, we investigated the effect of seasonal changes on the relationship between functional similarity and temporal dynamics similarity of 36 morphotypes, and the relative contribution of different functional traits during the different parts of the year. Our results revealed seasonal differences in the overall degree of synchronization of morphotypes' temporal dynamics and how combinations of functional traits influence the relationship between functional trait similarity and temporal dynamics similarity, showing that different forcing regimes change how species cope with their environment based on their functional traits. Moreover, we show that the individual functional traits matter at different periods of the year indicating that species which are dynamically similar at certain parts of the year may not be at others. The differential strength of the overall and individual impact of functional traits on species' temporal dynamics makes the cohesion of a pair of functionally similar species dependent on the different forcing. Hence, simplifying food webs based solely on functional traits may not provide consistent estimates of functional groups over all seasons.
Standing stocks are typically easier to measure than process rates such as production. Hence, stocks are often used as indicators of ecosystem functions although the latter are generally more strongly related to rates than to stocks. The regulation of stocks and rates and thus their variability over time may differ, as stocks constitute the net result of production and losses. Based on long-term high frequency measurements in a large, deep lake we explore the variability patterns in primary and bacterial production and relate them to those of the corresponding standing stocks, i.e. chlorophyll concentration, phytoplankton and bacterial biomass. We employ different methods (coefficient of variation, spline fitting and spectral analysis) which complement each other for assessing the variability present in the plankton data, at different temporal scales. In phytoplankton, we found that the overall variability of primary production is dominated by fluctuations at low frequencies, such as the annual, whereas in stocks and chlorophyll in particular, higher frequencies contribute substantially to the overall variance. This suggests that using standing stocks instead of rate measures leads to an under- or overestimation of food shortage for consumers during distinct periods of the year. The range of annual variation in bacterial production is 8 times greater than biomass, showing that the variability of bacterial activity (e.g. oxygen consumption, remineralisation) would be underestimated if biomass is used. The P/B ratios were variable and although clear trends are present in both bacteria and phytoplankton, no systematic relationship between stock and rate measures were found for the two groups. Hence, standing stock and process rate measures exhibit different variability patterns and care is needed when interpreting the mechanisms and implications of the variability encountered.