|Titel:||From fish biodiversity indicators to spatial risk assessments : Towards the integration of Blue Growth and conservation objectives in the German Bight||Sonstige Titel:||Von der Biodiversität der Fische zu räumlichen Risikoanalysen zur Integration von Blauem Wachstum und Umweltschutzvorhaben in der Deutschen Bucht||Sprache:||Englisch||Autor*in:||Rambo, Henrike||Schlagwörter:||Bayessche Netze; Offshore Windparks; Marine Raumplanung; Meeresstrategie-Rahmenrichtlinie; Marine Spatial Planning; ecosystem-based management; MSFD; community sensitivity index to fishing; CSI||GND-Schlagwörter:||Biodiversität; Fischerei; Risikoanalyse; Fische; Nordsee; NATURA 2000; Räumliche Statistik||Erscheinungsdatum:||2017||Tag der mündlichen Prüfung:||2017-06-30||Zusammenfassung:||
Spatial management measures are increasingly implemented in the Southern North Sea which is one of the most intensively used marine areas in the world. Various human activities are competing for space while exerting chronic pressures on marine habitats and the associated fauna. The most dominant spatial conflict exists between the development of offshore wind farms (OWF), conservation interests and the fishing sector. The effects of spatial allocations such as for OWF development or the designation of Natura 2000 sites as well as resulting displacement of fishing effort on benthic systems are riddled with uncertainties.
The policy landscape governing spatial management processes is likewise highly complex. One of the future governance challenges in European seas will be to align economic growth from the sea (“Blue Growth”) with conservation of biodiversity and ecosystem health. Amongst the key policies that members states of the European Union need to conform to is the Marine Strategy Framework Directive (MSFD) which requires achieving good environmental status (GES) of European seas. In addition, member states need to implement maritime spatial plans under the Maritime Spatial Planning (MSP) Directive to achieve sustainable use of marine resources. Both instruments aim at implementing an ecosystem-based spatial management approach. However, a current gap is the lack in spatially explicit indicators and associated management targets that could describe the achievements towards multi-objective planning. In addition, holistic assessment procedures are lacking which facilitate information needs of policy objectives and allow evaluating risks, opportunities and uncertainties of spatial management options on the ecosystem.
These gaps provided the motivation for this thesis and led to the following three research questions:
1. How can community-level biodiversity indicators best be represented spatially to provide information in an EB-MSM context?
2. Can a community-level biodiversity indicator be operationalised to link changes in biodiversity state to fishing pressure?
3. What are the likely risks of integrating Blue Growth and conservation objectives on fish biodiversity and the vulnerability of benthic communities in the German Bight?
These research questions were subsequently addressed in the previous chapters. The methodological comparison presented in Chapter 2 of two dominant mapping approaches revealed that modelling species distributions first and subsequently calculating index values per unit area (indirect approach) provided more useful information to represent community-level biodiversity. The comparison was performed using taxonomic biodiversity indices (species richness (S), Hill’s N1) as well as the here developed Community Sensitivity Index to fishing (CSI). The CSI was designed to be sensitive and responsive to fishing pressure by incorporating life-history traits which indicate how susceptible a species is to additional fishing mortality. Its capacity to quantify pressure-state relationships with bottom trawling was tested in Chapter 3. A suite of regression-based techniques revealed significantly lower index values in areas with high fishing pressure of the coastal small beam trawl fleet. The CSI could thus be operationalised for this fleet. Responses in other areas or with other fleets were less clear or even reversed and mostly driven by environmental factors such as depth. Results stress the difficulty in quantifying precise pressure-state relationships in a chronically disturbed system and hint to risk-based approaches that look at relative rather than absolute changes. In Chapter 4 an established risk assessment framework was applied to the case study area to spatially quantify the risk of fishing effort displacement due to Offshore Wind Farm (OWF) developments onto the vulnerability of the benthic community. This was described by a Disturbance Index (DI) defined as a ratio between relative local mortality by demersal trawling fleets and recovery potential of benthic communities. The risk analysis was conducted by coupling a Bayesian Belief Network (BN) with a Geographical Information System and suggested a minor worsening in DI values. Finally, in Chapter 5, a similar approach was applied to test effects of OWFs and Marine Protected Areas (MPAs) as well as resulting fishing effort displacement to explore associated risks and uncertainties on fish biodiversity (CSI, S & abundance distribution of cod). Scenarios incorporated amongst others fishermen compliance, protection effects of MPAs and temperature increases to mimic climate change. Results revealed that conservation effects through area closures outweighed negative effects from the relocation of fishing effort. Nevertheless, non-compliance could locally hamper recovery. EEZ wide effects were only caused through a simulated change in temperature and suggest likely increases in species richness and abundance of cod and significant decline in CSI.
Based on the three research questions this chapter synthesises results, discusses strength and weaknesses of the methodologies used and defines future research and data needs. Taken together, the results of this thesis allow some indications on the level of risks that fish biodiversity and the vulnerability of benthic communities is likely to face in the German Bight. Further, institutional barriers and scientific limitations to operationalise the EB-MSM approach are discussed.
|URL:||https://ediss.sub.uni-hamburg.de/handle/ediss/7347||URN:||urn:nbn:de:gbv:18-87120||Dokumenttyp:||Dissertation||Betreuer*in:||Möllmann, Christian (Prof. Dr.)|
|Enthalten in den Sammlungen:||Elektronische Dissertationen und Habilitationen|
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