Publications
Following publications have been announced by our Institute of Coastal Systems – Analysis and Modeling. For further information please contact the marked authors of the publications:
Zaucha, J., Gee, K., Ramieri, E., Neimane, L., Alloncle, N., Blažauskas, N., Calado, H., Cervera-Núñez, C., Kuzmanović, V.M., Stancheva, M., Witkowska, J., Eskeland Schütz, S., Zapatero, J.R., & Ehler, C.N. (2025): Implementing the EU MSP Directive: Current status and lessons learned in 22 EU Member States. Marine Policy, Vol 171, 106425, doi:10.1016/j.marpol.2024.106425
Abstract:
This paper takes stock of the impact the Maritime Spatial Planning Directive 2014/89/EU has had on developing maritime spatial planning (MSP) practice in Europe. Drawing on the practical experience of 22 Member States, it analyses how countries with varying political, planning and regional contexts, as well as varying MSP experience prior to 2014, have chosen to implement the Directive and what lessons they have learned in the process. A key lesson is that while the Directive provides a normative framework for approaching MSP, this has been variously adapted to national contexts. MSP in Europe is thus characterised by varied territorial coverage of plans, different national institutional arrangements for MSP, a variety of planning processes, and a variety of sectors covered by maritime spatial plans. We then examine four topics that are likely to remain prominent in future MSP, namely:
- taking account of climate change,
- applying the ecosystem approach,
- considering social and community impact of MSP and
- improving coherence.
While planners identify a range of challenges associated with each of these topics, countries have also developed practical solutions, although these are constrained by the respective remit and capacity of MSP as a process. The sheer diversity of maritime spatial plans and approaches, differing overall visions for MSP and methodological challenges, such as cumulative or socio-economic impact assessment, feature among the key challenges for achieving greater coherence in MSP within sea basins and beyond.
Stelzenmüller, V., Letschert, J., Blanz, B., Blöcker, A.M., Claudet, J., Cormier, R., Gee, K., Held, H., Kannen, A., Kruse, M., Rambo, H., Schaper, J., Sguotti, C., Stollberg, N., Quiroga, E., & Möllmann, C. (2024): Exploring the adaptive capacity of a fisheries social-ecological system to global change. Ocean & Coastal Management, Vol 258, 107391, doi:10.1016/j.ocecoaman.2024.107391
Abstract:
Global change challenges coupled natural-human systems such as fisheries social-ecological systems (SES) because they are confined by spatial and functional ecosystem boundaries. Understanding the capacity of an SES to adapt to changing environmental or socio-economic conditions is complex and entails an analysis of the system’s properties such as resilience, resistance, vulnerability, and adaptive capacity. We used a modified Ostrom framework to structure our analyses and to define the SES components, attributes and indicators of the German mixed demersal fishery SES operating in the southern North Sea. Combining analyses of 20-year time series of environmental and socio-economic data with network analysis and semi-structured interviews allowed for a detailed description of past SES adaptations. Hence, our analysis revealed autonomous adaptations of the SES to environmental and socio-economic change, which entailed a shift in target species, fishing strategies as well as a distinct decrease in number of actors. We found that the adaptive capacity of the SES has declined over time, and that the SES is now on the brink of being unable to withstand future environmental and socio-economic change. It is therefore captured in an undesirable state, reflecting a social-ecological trap where social and environmental feedbacks negatively reinforce each other. The main barriers to the adaptive capacity of the SES are related to fishing cultures, economic structures, policy frameworks and increasing conflicts over the use of marine space. An in-depth understanding of the linkages between the identified key SES components and related indicators is a prerequisite for developing future management approaches to enhance the adaptive capacity of SES to global change. Our findings highlight the need for tailored and context-specific co-management approaches for all decision-making processes affecting SES.
Imbert, T., Poggiale, J.-C., & Gauduchon, M. (2024): Intra-specific diversity and adaptation modify regime shifts dynamics under environmental change. Mathematical Biosciences and Engineering, 21(12): 7783-7804, doi:10.3934/mbe.2024342
Abstract:
Environmental changes are a growing concern, as they exert pressures on ecosystems. In some cases, such changes lead to shifts in ecosystem structure. However, species can adapt to changes through evolution, and it is unclear how evolution interacts with regime shifts, which restricts ecosystem management strategies. Here, we used a model of prey population with evolution and intra-specific trait diversity, and simulated regime shifts through changes in predation pressure. We then explored interactions between evolution, diversity, and shifts in population density. Evolution induced delayed or early regime shifts, and altered the recovery of populations. Such changes depended on the relative speed of evolution and change of predation pressure, as well as on the initial state of the population. Evolution also influenced population resilience, which was important when considering strong environmental variability. For instance, storms can spontaneously increase mortality and induce shifts. Furthermore, environmental variability induced even higher mortality if the phenotypic diversity of populations is large. Some phenotypes were more vulnerable to environmental changes, and such increases in mortality favor shifts to decreases in density. Thus, population management needs to consider diversity, evolution, and environmental change altogether to better anticipate regime shifts on eco-evolutionary time scales. Here, evolution and diversity showed complex interactions with population shift dynamics. Investigating the influence of higher diversity levels, such as diversity at a community level, should be another step towards anticipating changes in ecosystems and communities.
Kherroubi Garcia, I., Erdmann, C., Gesing, S., Barton, M., Cadwallader, L., Hengeveld, G., Kirkpatrick, C.R., Knight, K., Lemmen, C., Ringuette, R., Zhan, Q., Harrison, M., Mac Gabhann, F., Meyers, N., Osborne, C., Till, C., Brenner, P., Buys, M., Chen, M., Lee, A., Papin, J., & Rao, Y. (2025): Ten simple rules for good model-sharing practices. PLoS Comput Biol 21(1): e1012702, https://doi.org/10.1371/journal.pcbi.1012702
Abstract:
Computational models are complex scientific constructs that have become essential for us to better understand the world. Many models are valuable for peers within and beyond disciplinary boundaries. However, there are no widely agreed-upon standards for sharing models. This paper suggests 10 simple rules for you to both (i) ensure you share models in a way that is at least “good enough,” and (ii) enable others to lead the change towards better model-sharing practices.
