Background Anthropogenic pressures on marine ecosystems have increased over the last 75 years and are expected to intensify in the future with potentially dramatic cascading consequences for human societies. It is therefore crucial to rebuild marine life-support systems and aim for future healthy ecosystems. Nowadays, there is a reasonable understanding of the impacts of human pressure on marine ecosystems; but no studies have drawn an integrative retrospective analysis of the marine research on the topic. A systematic consolidation of the literature is therefore needed to clearly describe the scientific knowledge clusters and gaps as well as to promote a new era of integrative marine science and management. We focus on the five direct anthropogenic drivers of biodiversity loss defined by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES): (1) climate change; (2) direct exploitation; (3) pollution; (4) biological invasions; and (5) sea-use change. Our systematic map’s regional focus lies on the North Sea, which is among the most impacted marine ecosystems around the globe. The goal of the present study is to produce the first comprehensive overview of how marine research on anthropogenic drivers in the North Sea has grown and changed over the past 75 years. Ultimately, this systematic map will highlight the most urgent challenges facing the North Sea research domain. Methods The search will be restricted to peer-reviewed articles, reviews, meta-analyses, book chapters, book reviews, proceeding papers and grey literature using the most relevant search engines for literature published between 1945 and 2020. All authors will participate in the adjustment of the search in order to consider all relevant studies analyzing the effect of the direct anthropogenic drivers on the North Sea marine ecosystem. The references will be screened for relevance according to a predefined set of eligibility/ineligibility criteria by a pool of six trained reviewers. At stage one, each abstract and title will be independently screened by two reviewers. At stage two, potentially relevant references will be screened in full text by two independent reviewers. Subsequently, we will extract a suite of descriptive meta-data and basic information of the relevant references using the SysRev platform. The systematic map database composed will provide the foundation for an interactive geographical evidence map. Moreover, we will summarize our findings with cross-validation plots, heat maps, descriptive statistics, and a publicly available narrative synthesis. The aim of our visualization tools is to ensure that our findings are easily understandable by a broad audience.
Predicting the effect of increased thermal unpredictability, for example in the shape of heatwaves on phytoplankton metabolic responses is ripe with challenges. While single genotypes in laboratory environments will respond to environmental fluctuations in predictable and repeatable ways, it is difficult to relate rapid evolutionary responses of whole communities to their ecological history. Previously experienced environments, including fluctuations therein, can shape an organism s specific niche as well as their responses to further environmental changes. This is a testable hypothesis as long as samples can be obtained where the environmental history is known, sufficiently diverse, and not obscured by confounding parameters such as day length and precipitation patterns. Here, we tested immediate (i.e. within one generation) metabolic temperature responses of natural phytoplankton assemblages from two thermally distinct regions in the Baltic Sea: the warmer and less predictable Kiel Area, and the overall colder and more predictable Bornholm Basin. Our approach allows us to investigate effects on immediate physiological time scales (responses curves), ecological and evolutionary processes on longer time scales (seasonal differences between basins) as well as mid-term responses during a natural occurring heatwave. We found evidence for a higher degree of phenotypic plasticity in samples from unpredictable environments (Kiel Area).
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