Jens Floeter

20 years of the German Small-Scale Bottom Trawl Survey (GSBTS): A review

AbstractThe German Small-scale Bottom Trawl Survey (GSBTS) was initiated in 1987 in order to provide complementary investigations to the International Bottom Trawl Survey (IBTS) in the North Sea, using the same methodology but focussing high-intensity sampling on selected survey areas. Over the last 20 years, the initial number of 4 survey areas (10 × 10 nautical miles; “Boxes”) has been increased to 12, which are distributed over the entire North Sea. This paper describes the survey methods of the GSBTS, summarizes the scientific outcome of the first 20 years, and suggests that international fisheries research institutions would join the GSBTS.The major outcomes of the survey include to date:— Documentation changes in the distribution of fish species and in species assemblages (e.g. changes in species richness, shifts in the southern species component).— Geostatistical evaluation of GSBTS data.— Analysis of spatial scale effects: the relevance of GSBTS survey results for interpreting large-scaled abundance and distribution data from the IBTS.— Description of benthic habitats, composition of invertebrate fauna and its variability.— Process studies, especially investigation of predator-prey interactions between fish through analyses of stomach contents.— Characterization of the typical hydrographic conditions in the survey areas and their variability, and description of the nutrient supply.— Observations of seabirds and their feeding habits.— Analysis of the effects of different parameters on catch rates for bottom fish and on the estimates of abundance indices (e.g. vessel and gear effects, towing time, hydrographic conditions, time of day, number of hauls per area). In continuing this interdisciplinary survey with simultaneous sampling of all faunal and environmental compartments and especially in making it an international effort, we see the possibility of contributing data for the implementation of the ecosystems approach to fisheries management. Particularly, the following aspects can be addressed and would further increase the scientific value of the GSBTS:— Combining the survey data with highly resolved data from the commercial fishery to separate the effects of fishing from natural variability.— Further interdisciplinary analyses of the entire data set. Main aspects include benthos-fish-bird-community changes over time and their relation to historic fisheries impacts, and the coupling of biological and physical habitat characterisation.— Collection of accompanying data (phyto-, zoo- and ichthyoplankton data) in order to make the GSBTS a true ecosystem survey in detecting temporal changes in nearly all major levels of the food web.

A spatially explicit risk approach to support marine spatial planning in the German EEZ

An ecosystem approach to marine spatial planning (MSP) promotes sustainable development by organizing human activities in a geo-spatial and temporal context. (1) This study develops and tests a spatially explicit risk assessment to support MSP. Using the German exclusive economic zone (EEZ) of the North Sea as a case study area, current and future spatial management scenarios are assessed. (2) Different tools are linked in order to carry out a comprehensive spatial risk assessment of current and future spatial management scenarios for ecologic and economic ecosystem components, i.e. Pleuronectes platessa nursery grounds. With the identification of key inputs and outputs the suitability of each tool is tested. (3) Here, the procedure as well as the main findings of the spatially explicit risk approach are summarised to demonstrate the applicability of the framework and the need for an ecosystem approach to risk management techniques using geo-spatial tools.

Sex‐specific food intake in whiting Merlangius merlangus

In this study, the topic of sexual growth dimorphism in whiting Merlangius merlangus is examined. To understand the magnitude and underlying mechanisms, North Sea International Bottom Trawl Survey (IBTS) data and two additional datasets from the third quarter of 2007 and the first quarter of 2012 were analysed. Merlangius merlangus displays distinct differences in growth parameters between males and females, with females reaching a higher asymptotic length (L∞ ) than males. To identify the mechanisms which lead to higher growth in females, the quantity and the quality of the diet of M. merlangus in the North Sea were investigated to compare the sex-specific energy uptake levels. The diet composition did not differ between the sexes, but females had higher stomach content masses than males of the same total length (LT ), and showed lower proportions of empty stomachs. Moreover, female M. merlangus had higher liver and empty stomach masses compared with males of the same size, which indicates additional sex-specific differences in the metabolic costs and energy allocation patterns. Finally, interannual differences were found in the stomach contents, the share of empty stomachs and liver masses of M. merlangus in the North Sea.

North sea fish and higher trophic levels: a review

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 Srockraking and detailed assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 Data situaa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 Evaluation of Data situation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Process understanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 Consumpt ion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 Diet selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 Spawning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 Model development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360 Multi species fishery assessment models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360 Ecosystem models with higher trophic levels implemented . . . . . . . . . . . . . . . . . . . . . 364 Instruments and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 Stock size and structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 Stock discrimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369 Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369 Consumpt ion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 Diet selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 Spawning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Multidisciplinary assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 Data situation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 Process understanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Recruitment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Model development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 Instruments and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 Data summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 Survey data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 Model output data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Forage fish control population dynamics of North Sea whiting Merlangius merlangus

Predator populations are often affected by the abundance of their prey, but pronounced effects on predatory fish have mainly been demonstrated in ecosystems where a key predator depends largely on one key prey species. The North Sea food web has a comparatively high level of complexity with a high diversity of forage fish, and hence strong effects are less likely to occur. However, in the early 2000s within large parts of the North Sea, several forage fish stocks simultaneously suffered from successive years of recruitment failure together with decreasing stock abundances. Whiting Merlangius merlangus is a major fish predator in the North Sea ecosystem and is known to be almost exclusively piscivorous. We hypothesised that shortages in forage fish should lead to negative effects on growth or condition of a predator that relies on a few dominant prey fish species. In our study, we combined 6 different North Sea data sets on abundance of forage fish and length-at-age, condition and stomach contents of M. merlangus to analyse contrasting periods with high and low forage fish availability. We found a simultaneous decrease in forage fish availability and M. merlangus length-at-age in the period from 2000-2007 and a subsequent parallel increase in prey abundance and length-at-age after 2007. In the period of low forage fish availability, mean stomach content mass was on average 60% less than in the reference periods. Additionally, a bioenergetics calculation revealed that even smaller differences in the stomach contents than those observed would have been sufficient to explain the observed differences in length-at-age. Our findings emphasize the need to incorporate predator-prey interactions in assessment models and management strategies.