Changes in depth distribution and biomass of sublittoral seaweeds at Helgoland (North Sea) between 1970 and 2005

Pehlke, Constanze; Bartsch, Inka

doi:10.3354/cr00767

Cited by 75 publications

(60 citation statements)

References 38 publications

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“…During diving, every 6 m the percentage of kelp cover was estimated along a corridor of AE3e5 m (Pehlke and Bartsch, 2008). Georeferencing of the diving position was achieved by recording the position of a surface buoy (GPS: iBlue 747AþEU, TranSystem Inc., Taiwan) straightly connected by a line with the diver and by aligning position and diving time.…”

Section: Diving Transectsmentioning

confidence: 99%

“…An additional manual classification method was applied as we also wanted to discriminate dense and medium dense kelp fields that became apparent in the underwater videos and are also known from the area (Pehlke and Bartsch, 2008). For this approach, both validated and non-validated hydroacoustic data sets (obtained along the RoxAnn transects and the video transects) were plotted on a Cartesian XY chart, while the ground-truthed E1 and E2 values of the video transects were marked in different colors.…”

Section: Manual Classification (Mc)mentioning

confidence: 99%

“…Dense kelp forests have a leaf area index (LAI) of >1 covering the ground substrate with several blade layers (Pehlke and Bartsch, 2008). Since the macroalgae can only thrive on hard substratum (Lüning, 1990;Bartsch and Kuhlenkamp, 2000), it can further be expected that there are cobbles and rocks wherever macroalgae occur.…”

Section: Accordance To Echogram Analysismentioning

confidence: 99%

“…Hence, the combination of intermediate roughness and hardness values are a suitable indicator for the occurrence of medium dense kelp vegetation. Additionally, kelp forest densities decrease with increasing water depth due to reduced light availability (Lüning, 1970;Pehlke and Bartsch, 2008) which is a complementary indicator for kelp distribution in this area (Fig. 3A).…”

Section: Accordance To Echogram Analysismentioning

confidence: 99%

“…Classical monitoring methods of kelp beds are diving transects (e.g. Lüning, 1970;Pehlke and Bartsch, 2008) which are precise but highly time demanding and provide no spatial information. More recently, faster methods for seaweed mapping became established such as georeferenced underwater videos or airborne hyperspectral imaging techniques (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Predicting spatial kelp abundance in shallow coastal waters using the acoustic ground discrimination system RoxAnn

Mielck

Bartsch

Hass

et al. 2014

Estuarine, Coastal and Shelf Science

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a b s t r a c tKelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not simply linked to water depth. Moreover, this study shows that the two seafloor parameters collected with RoxAnn are suitable indicators for the discrimination of different densely vegetated seafloor habitats in shallow environments.

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Section: Diving Transectsmentioning

confidence: 99%

Section: Manual Classification (Mc)mentioning

confidence: 99%

Section: Accordance To Echogram Analysismentioning

confidence: 99%

Section: Accordance To Echogram Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predicting spatial kelp abundance in shallow coastal waters using the acoustic ground discrimination system RoxAnn

Mielck

Bartsch

Hass

et al. 2014

Estuarine, Coastal and Shelf Science

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Phytobenthos Techniques

Kautsky

2013

Methods for the Study of Marine Benthos

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Environmental DNA reveals fine‐scale spatial and temporal variation of marine mammals and their prey species in a Scottish marine protected area

Boyse,

Robinson,

Beger

et al. 2024

Environmental DNA

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Marine mammal foraging grounds are popular focal points for marine protected area (MPA) implementation, despite being temporally dynamic, requiring continuous monitoring to infer prey availability and abundance. Marine mammal distributions are assumed to be driven by their prey in foraging areas, but limited understanding of prey distributions often prevents us from exploring how shifting prey availability impacts both seasonal and long‐term marine mammal distributions. Environmental DNA (eDNA) metabarcoding could enhance the understanding of marine mammal habitat use in relation to their prey through simultaneous monitoring of both. However, eDNA applications focused on marine mammals or predator–prey dynamics have been limited to date. In this study, we assess spatiotemporal changes in the distribution and abundance of cetaceans, minke whales (Balaenoptera acutorostrata), bottlenose dolphins (Tursiops truncatus) and harbor porpoises (Phocoena phocoena) in relation to key prey species in a newly established MPA, employing eDNA metabarcoding. We recovered 105 molecular operational taxonomic units (OTUs) from marine vertebrates using two primer sets targeting 12S and 16S genes, along with 112 OTUs from a broader eukaryotic primer set targeting 18S rRNA. Overall, key forage fish prey species, sandeels and clupeids, were the most abundant teleost fishes detected, although their availability varied temporally and with distance from shore. We also found clear spatial partitioning between coastal bottlenose dolphins and the more pelagic minke whales and harbor porpoises, paralleling availability of their main prey species. Other species of conservation interest were also detected including the critically endangered European eel (Anguilla anguilla), Atlantic bluefin tuna (Thunnus thynnus), and the invasive pink salmon (Oncorhynchus gorbuscha). This study demonstrates the application of eDNA to detect spatiotemporal trends in the occurrence and abundance of cetacean predators and their prey, furthering our understanding of fine‐scale habitat use within MPAs. Future long‐term monitoring of predator–prey dynamics with eDNA could improve our ability to predict climate‐induced shifts in foraging grounds and enhance rapid responses with appropriate management actions.

show abstract

Changes in depth distribution and biomass of sublittoral seaweeds at Helgoland (North Sea) between 1970 and 2005

Cited by 75 publications

References 38 publications

Predicting spatial kelp abundance in shallow coastal waters using the acoustic ground discrimination system RoxAnn

Predicting spatial kelp abundance in shallow coastal waters using the acoustic ground discrimination system RoxAnn

Phytobenthos Techniques

Environmental DNA reveals fine‐scale spatial and temporal variation of marine mammals and their prey species in a Scottish marine protected area

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