Description: Explaining species diversity as a function of ecosystem variability is a long-term discussion in community-ecology research. Here, we aimed to establish a causal relationship between ecosystem variability and phytoplankton diversity in a shallow-sea ecosystem. We used long-term data on biotic and abiotic factors from Helgoland Roads, along with climate data to assess the effect of ecosystem variability on phytoplankton diversity. A point cumulative semi-variogram method was used to estimate the long-term ecosystem variability. A Markov chain model was used to estimate dynamical processes of species i.e. occurrence, absence and outcompete probability. We identified that the 1980s was a period of high ecosystem variability while the last two decades were comparatively less variable. Ecosystem variability was found as an important predictor of phytoplankton diversity at Helgoland Roads. High diversity was related to low ecosystem variability due to non-significant relationship between probability of a species occurrence and absence, significant negative relationship between probability of a species occurrence and probability of a species to be outcompeted by others, and high species occurrence at low ecosystem variability. Using an exceptional marine long-term data set, this study established a causal relationship between ecosystem variability and phytoplankton diversity.

Description: Annually recurring environmental processes such as the cycle of temperature and light drive the phenology of marine plankton populations. Improved knowledge about the homogeneity and amplitude of the phenological response of phytoplankton to climate change is essential for an assessment of ecological consequences on the marine ecosystem. We analyzed phenological variability of 21 phytoplankton species monitored work-daily at Helgoland Roads from 1962-2015. We used a function of “Weibull”-type to estimate phenological dates of species-specific abundance peaks. The combination of derived dates and peak abundances formed the basis for the analyses of long-term changes in phenological time slots and associated environmental conditions. Species-specific preferences in combination with seasonally varying environmental trends resulted in a complex pattern of phenological long-term response. Phenological trends showed both constant occurrence and shifts to an earlier or later occurrence. Co-occurring phytoplankton species were shown to exhibit different phenological trends even within identical time slots. Differences in species-specific trends in timing also reflected the seasonally varying shifts in water temperature ranges due to warming. In spring and summer, the main patterns of common variability in timing were associated with different abiotic and biotic drivers. The majority of species showed more narrow time slots related to the occurrence of higher peaks. Considering the variation of species occurrence in their “typical” time window provided insight in terms of assigning the effect of environmental drivers on inter-annual phenological variation. Phytoplankton species with similar long-term trends in timing (days) showed different trends in biomass, i.e. the phenological changes resulted from different ecological responses to environmental change. The local character of environmental trends at Helgoland underpins the limits for comparison of findings between different measuring sites or wider areas, such as the North Sea. The study emphasizes the benefit and necessity of a highly resolved phytoplankton record for a true understanding of long-term ecological changes in a highly dynamic marine environment such as the North Sea.

Description: Monitoring changes in eukaryotic microbial communities is critical for understanding ecosystem dynamics, trophic interactions and the impacts of climate change. Long-term time series are an important tool for monitoring changes in ecological communities, but time series from a single location may not be representative of regional dynamics. In the German Bight, the Helgoland Roads time series is such a long-term series. Here, we consider the spatial dynamics of the eukaryotic microbes as an indicator of the representativeness of the Helgoland Roads site for the coastal German Bight, which is located in the North Sea. The eukaryotic microbial community in the German Bight was analysed at Helgoland Roads and two coastal stations (Cuxhaven and Wilhelmshaven) between March and October 2016 using metabarcoding. In addition, an oceanographical model was used to check for potential hydrological connectivity between the stations during the sampling period. Our results showed that the communities were different at the three stations. Helgoland was dominated by dinoflagellates, whereas the coastal stations had more diverse communities. Furthermore, differences were observed in the dinoflagellate and diatom communities between the three stations. Lagrangian particle tracking applied to the model results, showed limited connectivity between Helgoland and the coastal stations in 2016. The differences between Helgoland and the coastal stations were correlated with the different hydrological regimes and associated nutrient contents. Our observations suggest the presence of different eukaryotic microbial communities separated by complex hydrological conditions in the coastal German Bight.

Description: Comprehensive empirical data to inform benthic species distribution models for marine hard-substrate-dominated environments, are pivotal. However, such data are difficult to obtain. These data are crucial to the definition and demarcation of protected areas and for assessment of the ecological status and function of hard-substrate habitats. In this study, underwater video-observations of hard-substrate habitats within four target areas in the sand-dominated German Bight (SE North Sea) were investigated to obtain comprehensive information on hard-substrate distribution patterns, on the amount and sizes of stones and on the presence of sessile organisms. Based on three size classes (cobbles, boulders, large boulders) three hard-substrate distribution classes were identified: (1) widely scattered stones, (2) accumulations of stones and (3) dense stone fields. The ratios between cobbles, boulders and large boulders differed significantly between the investigated areas. Boulders and large boulders were largely colonized by sessile organisms, whereas cobbles in coastal areas were least frequently colonized. Physical disturbances of epibenthos resulting from abrasion and coverage by mobile sediments are discussed as a possible explanation for the proportional differences in the colonization of stones. Hard substrates in shallower, coastal areas appeared to be strongly influenced by sand abrasion because of higher current velocities and storm-induced waves. In deeper areas, located further offshore, disturbances caused by migrating sandy ripples mobilized by storm-events seemed to be more relevant. Habitat modelling of hard substrates and resultant ecological studies require sound information on the probability of epifaunal colonization for different substrate sizes, hard-substrate distribution patterns combined with hydrodynamic and physicochemical properties of the marine environment to produce valid results. We used a structured approach for the video-based analysis of hard-substrate habitats and present estimates of the colonization probability of differently-sized stones. Our study shows that the analysis of drift videos provides basic data at a suitable resolution to contribute to the monitoring and modelling of marine ecological processes.

Description: The predictions of the competitive exclusion principle about the number of coexisting species not exceeding the number of limiting resources in equilibrium constitute an ecological puzzle for phytoplankton ecosystems. Here we present a synthesizing unit (SU) based competition model taking co-limitation into account, which is the extension of the competition model developed by Dutta et al. (2014).The study aims at understanding the mechanisms of violation of competitive exclusion principle for phytoplankton species with seasonal environmental forcing when multiple resource limitation is taken into account and species growth is formulated based on SU. We also explore the role of changing environmental conditions on species coexistence on a seasonal and a decadal time scale by linking the model forcing to the Helgoland Roads Time Series data sets. For the first time, based on the Helgoland Roads data, we are able to find a realistic parameterization for the phytoplankton competition model where growth is formulated using SU concept. Our study confirms that more species than limiting resources can coexist with seasonal variations of environmental conditions. This supersaturation is related to periodic changes in species’ biomass, variation in interspecific competition and niche configuration, nonlinear functional response and the position of resource supply within the convex hull of species’ resource uptake rate. Changes in environmental conditions within realistic ranges do not prevent the coexistence of species rather it slightly changes species’ biomass and turnover time. This study also confirms that our model with SU based species growth performs better than species competition model where multiple resource limitation is formulated based on the product of several Monod functions. Our study has created a new avenue for phytoplankton coexistence research and the results might be helpful to answer the complex questions on species diversity maintenance in nature.

Description: Investigation of phytoplankton biodiversity, ecology, and biogeography is crucial for understanding marine ecosystems. Research is often carried out on the basis of microscopic observations, but due to the limitations of this approach regarding detection and identification of picophytoplankton (0.2–2 μm) and nanophytoplankton (2–20 μm), these investigations are mainly focused on the microphytoplankton (20–200 μm). In the last decades, various methods based on optical and molecular biological approaches have evolved which enable a more rapid and convenient analysis of phytoplankton samples and a more detailed assessment of small phytoplankton. In this study, a selection of these methods (in situ fluorescence, flow cytometry, genetic fingerprinting, and DNA microarray) was placed in complement to light microscopy and HPLC-based pigment analysis to investigate both biomass distribution and community structure of phytoplankton. As far as possible, the size classes were analyzed separately. Investigations were carried out on six cruises in the German Bight in 2010 and 2011 to analyze both spatial and seasonal variability. Microphytoplankton was identified as the major contributor to biomass in all seasons, followed by the nanophytoplankton. Generally, biomass distribution was patchy, but the overall contribution of small phytoplankton was higher in offshore areas and also in areas exhibiting higher turbidity. Regarding temporal development of the community, differences between the small phytoplankton community and the microphytoplankton were found. The latter exhibited a seasonal pattern regarding number of taxa present, alpha- and beta-diversity, and community structure, while for the nano- and especially the picophytoplankton, a general shift in the community between both years was observable without seasonality. Although the reason for this shift remains unclear, the results imply a different response of large and small phytoplankton to environmental influences.