Publications by authors named "Saskia A Otto"

Marine fisheries are increasingly impacted by climate change, affecting species distribution and productivity, and necessitating urgent adaptation efforts. Climate vulnerability assessments (CVA), integrating expert knowledge, are vital for identifying species that could thrive or suffer under changing environmental conditions. This study presents a first CVA for the Western Baltic Sea's fish community, a crucial fishing area for Denmark and Germany.

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Recovery of depleted fish stocks is an important goal for fisheries management and crucial to sustain important ecosystem functions as well as global food security. Successful recovery requires adjusting fishing mortality to stock productivity but can be prevented or inhibited by additional anthropogenic impacts such as climate change. Despite management measures to recover fish stocks being in place in legislations such as the European Union´s Common Fisheries Policy (CFP), recovery can be hindered by the occurrence of regime shift dynamics.

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Seasonal Influenza A virus (IAV) infections can promote dissemination of upper respiratory tract commensals such as Streptococcus pneumoniae to the lower respiratory tract resulting in severe life-threatening pneumonia. Here, we aimed to compare innate immune responses in the lungs of healthy colonized and non-colonized mice after IAV challenge at the initial asymptomatic stage of infection. Responses during a severe bacterial pneumonia were profiled for comparison.

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Understanding tipping point dynamics in harvested ecosystems is of crucial importance for sustainable resource management because ignoring their existence imperils social-ecological systems that depend on them. Fisheries collapses provide the best known examples for realizing tipping points with catastrophic ecological, economic and social consequences. However, present-day fisheries management systems still largely ignore the potential of their resources to exhibit such abrupt changes towards irreversible low productive states.

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Global environmental changes have accelerated at an unprecedented rate in recent decades due to human activities. As a consequence, the incidence of novel abiotic conditions and biotic communities, which have been continuously emerging in the Earth system, has rapidly risen. Despite growing attention to the incidence and challenges posed by novelty in terrestrial ecosystems, novelty has not yet been quantified in marine ecosystems.

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Collapses and regime changes are pervasive in complex systems (such as marine ecosystems) governed by multiple stressors. The demise of Atlantic cod ( Gadus morhua) stocks constitutes a text book example of the consequences of overexploiting marine living resources, yet the drivers of these nearly synchronous collapses are still debated. Moreover, it is still unclear why rebuilding of collapsed fish stocks such as cod is often slow or absent.

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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.

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Understanding and predicting species distribution in space and time and consequently community structure and dynamics is an important issue in ecology, and particularly in climate change research. A crucial factor determining the composition and dynamics of animal populations is habitat heterogeneity, i.e.

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Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing.

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Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea.

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