A revised checklist of planktonic diatoms and dinoflagellates from Helgoland (North Sea, German Bight)

Hoppenrath, Mona

doi:10.1007/s10152-004-0190-6

Cited by 52 publications

(47 citation statements)

References 16 publications

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“…Our model calculations revealed rankings of high-risk algal species for each ecoregion, which is exemplarily shown for the North Sea (Table S2). Two of the algal species of the top 10 high-risk species for the North Sea are known from the literature to have naturalized in that ecoregion in recent years [Prorocentrum minimum (18) and Polysiphonia harveyi (19)]. These species are not listed for the North Sea in AlgaeBase probably due to delays in data acquisition.…”

Section: Resultsmentioning

confidence: 99%

Predicting the spread of marine species introduced by global shipping

Seebens

Schwartz

Schupp

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

157

112

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The human-mediated translocation of species poses a distinct threat to nature, human health, and economy. Although existing models calculate the invasion probability of any species, frameworks for species-specific forecasts are still missing. Here, we developed a model approach using global ship movements and environmental conditions to simulate the successive global spread of marine alien species that allows predicting the identity of those species likely to arrive next in a given habitat. In a first step, we simulated the historical steppingstone spreading dynamics of 40 marine alien species and compared predicted and observed alien species ranges. With an accuracy of 77%, the model correctly predicted the presence/absence of an alien species in an ecoregion. Spreading dynamics followed a common pattern with an initial invasion of most suitable habitats worldwide and a subsequent spread into neighboring habitats. In a second step, we used the reported distribution of 97 marine algal species with a known invasion history, and six species causing harmful algal blooms, to determine the ecoregions most likely to be invaded next under climate warming. Cluster analysis revealed that species can be classified according to three characteristic spreading profiles: emerging species, high-risk species, and widespread species. For the North Sea, the model predictions could be confirmed because two of the predicted high-risk species have recently invaded the North Sea. This study highlights that even simple models considering only shipping intensities and habitat matches are able to correctly predict the identity of the next invading marine species. alien species | model predictions | species identity | marine ecoregion | climate change T he number of alien species transported by human assistance has increased rapidly during the last decades with serious consequences for native flora and fauna (1-3). These biological invasions are considered to be one of the major drivers of biodiversity changes (4-6). Once an unwanted alien species has naturalized in the new environment, it is nearly impossible to eradicate the species, and thus the mitigation of further introduction is the most efficient way of combating biological invasions (6, 7). However, a targeted monitoring and an efficient adaptive management requires knowledge about spreading dynamics of the next potential invaders and thus about the distribution of species, their invasiveness, and the likelihood of new introductions. Although all of these topics have been analyzed on their own, the potential to predict the spreading of alien species while combining these components remains to be tested.A large amount of recent introductions can be attributed to the intensified global trade and transport as many species were accidentally or deliberately translocated through the exchange of commodities or the movements of transportation means (8, 9). The amount of exchanged commodities and the intensity of global traffic have therefore been found to be a good predictor to model th...

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Section: Resultsmentioning

confidence: 99%

Predicting the spread of marine species introduced by global shipping

Seebens

Schwartz

Schupp

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

157

112

View full text Add to dashboard Cite

show abstract

“…For the five indicator taxa (Chaetoceros spp1, spp2, T. nitzschoides, P. seriata, and R. imbricata), the IndVal increased until the fifth clustering level of the CPR samples classification (reaching six assemblages), and then decreased, indicating that these taxa are stenotopic, i.e., they have a small niche 11 breadth (Dufrêne and Legendre, 1997). They also have a strong seasonality and a relatively limited spread, which has been commonly reported in the North Sea and English Channel (e.g., Reid et al, 1990;Rousseau et al, 2002;Hoppenrath, 2004;Bresnan et al, 2009;Hinder et al, 2012). On the contrary, Thalassiosira spp.…”

Section: Concerning the Choice Of Indicator Value Methods To Analyze Cmentioning

confidence: 76%

Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea

et al. 2017

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Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more toward phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR) survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, each having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated with specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge.

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“…We took these 23 species as the most abundant and representative ones in this dataset. (Hoppenrath 2004;Wiltshire and Dürselen 2004). Two species were pooled to genus level due to the lower abundances (Hoppenrath 2004).…”

Section: Sampling and Data Setsmentioning

confidence: 99%

Reconstructing the realized niche of phytoplankton species from environmental data: fitness versus abundance approach

Grüner¹,

Gebühr²,

Boersma³

et al. 2011

Limnology & Ocean Methods

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The classification of the ecological niche and the grouping of species into generalists and specialists are established ecological concepts. In this study, we compare two methods for the calculation of the realized ecological niche from long-term species data. As the first method, we present a new approach to reconstruct the realized niche not in terms of abundance but via a measure of fitness (optimal niche), which we call the Optimal Niche Estimate (ONE). The second method, the outlying mean index (OMI) analysis, is performed with abundance data for calculating the ecological niche. We demonstrate and discuss differences between methods by applying them to time series of three phytoplankton species from the Helgoland Roads long-term data set: Ceratium fusus, Odontella regia, and Paralia sulcata.

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A revised checklist of planktonic diatoms and dinoflagellates from Helgoland (North Sea, German Bight)

Cited by 52 publications

References 16 publications

Predicting the spread of marine species introduced by global shipping

Predicting the spread of marine species introduced by global shipping

Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea

Reconstructing the realized niche of phytoplankton species from environmental data: fitness versus abundance approach

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