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Abstract
Ecosystems worldwide are subject to an unprecedented loss of biodiversity, largely resulting from a range of human impacts such as over-exploitation, habitat loss and climate change. To understand the consequences of this biodiversity crisis on both land and oceans, scientists tried quantifying the relationship between biodiversity and ecosystem functioning (ability of an ecosystem to perform and maintain a suite of key properties such as biomass and flux of energy), ultimately trying to answer: what is the importance of biodiversity for ecosystems? A positive influence of biodiversity on ecosystem functioning has been shown in many experimental studies, demonstrating enhanced biomass production under higher number of species. However, the extent to which such findings hold in natural systems is unknown, especially in large and complex marine ecosystems. To address this knowledge gap, we use high-resolution
monitoring data on fish community composition and abundance in continental shelf seas across the North Atlantic and statistical modeling to test the existence of links between biodiversity and ecosystem functions at both regional and continental scales. This empirical approach is complemented with a mathematical food web model to establish theoretical hypotheses about the contribution of biodiversity and food web structure on several ecosystem functions. We demonstrate that while a positive relationship between the number of species and several ecosystem functions is expected in theory, that link is not necessarily emergent from observations of real fish communities. We highlight that the metric of biodiversity and ecosystem function evaluated matters to determine the overall ecosystem performance. This thesis is an attempt to understand the role of fish biodiversity for marine ecosystem functioning across several ecosystems and to develop hypotheses on the role of biodiversity in complex food webs. Quantifying the importance of biodiversity for ecosystem functioning is necessary for our understanding of ecosystem complexity in ecology, enhance biodiversity and ecosystem conservation and has the potential to trigger policy towards conservation of ecosystems.
monitoring data on fish community composition and abundance in continental shelf seas across the North Atlantic and statistical modeling to test the existence of links between biodiversity and ecosystem functions at both regional and continental scales. This empirical approach is complemented with a mathematical food web model to establish theoretical hypotheses about the contribution of biodiversity and food web structure on several ecosystem functions. We demonstrate that while a positive relationship between the number of species and several ecosystem functions is expected in theory, that link is not necessarily emergent from observations of real fish communities. We highlight that the metric of biodiversity and ecosystem function evaluated matters to determine the overall ecosystem performance. This thesis is an attempt to understand the role of fish biodiversity for marine ecosystem functioning across several ecosystems and to develop hypotheses on the role of biodiversity in complex food webs. Quantifying the importance of biodiversity for ecosystem functioning is necessary for our understanding of ecosystem complexity in ecology, enhance biodiversity and ecosystem conservation and has the potential to trigger policy towards conservation of ecosystems.
Original language | English |
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Publisher | DTU Aqua |
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Number of pages | 256 |
Publication status | Published - 2020 |
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Dive into the research topics of 'Biodiversity-ecosystem functioning relationships in marine communities: Evidence from large-scale observations and modeling'. Together they form a unique fingerprint.Projects
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Understanding the biodiversity-ecosystem functioning relationship in marine food webs through large-scale observations and modelling
Maureaud, A. A. (PhD Student), Bonsdorff, E. (Examiner), Lefcheck, J. (Examiner), Rindorf, A. H. (Examiner), Lindegren, M. O. (Main Supervisor) & Andersen, K. H. (Supervisor)
15/02/2017 → 25/06/2020
Project: PhD