Variability patterns differ between standing stock and process rates

Abstract

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.

Comparing seasonal dynamics of functional and taxonomic diversity reveals the driving forces underlying phytoplankton community structure

“…All measurements are provided per unit area and comprise the biomass within the uppermost water layer from 0–20 m depth, which roughly corresponds to the epilimnion and the euphotic zone. In this study, we considered only the 36 most abundant morphotypes of phytoplankton (constituting 92% of total phytoplankton biomass) comprising individual species or higher taxonomic units that are functionally identical or very similar under the functional classification employed here (Rocha et al ., ,b; Rocha, Vasseur & Gaedke, ). This guaranteed a consistent resolution of phytoplankton counts across the 20 years of sampling.…”

“…Once we obtained the diversity indices for every sampling date, we used smoothing spline analysis to investigate the relationship between recurrent annual patterns of the two indices, by separating the general seasonal trend of each measure of diversity from noise (Rocha et al ., ,b). Splines can approximate complex shapes, which is of particular interest given our intent to describe in detail the dynamics of the taxonomic and functional diversity indices.…”

Benchmarking Successional Progress in a Quantitative Food Web

“…This holds true even though H bio was available in a higher (20 plankton guilds) resolution than C w (8 major groups), showing that even a comparatively coarse quantitative resolution was sufficient to shed light onto successional food web dynamics. We therefore suggest the usage of C w to complement H bio because the energy flow patterns represent an integral part of the system's functional diversity and process rates often proved to be more informative than biomasses for explaining the influence of system-level properties on ecosystem functioning [77].…”

Seasonal Variations Alter the Impact of Functional Traits on Plankton Dynamics

“…It underwent re-oligotrophication [14] and mean annual phytoplankton biomass declined by a factor of 2 with phosphorous decline, indicating that the long-term changes are small compared to the very pronounced seasonal dynamics (morphotypes vary in density by a factor of 10 to 1000 during the year). Plankton sampling was conducted weekly during the growing season and approximately fortnightly in winter, culminating in 853 sampling dates between 1979 and 1999 (for details see [14], [15]). We log 2 -transformed the biomass measurements to account for the skewed size distribution of phytoplankton organisms [14].…”