Nature-based Solutions to climate change along coasts and rivers: a plant-functional trait approach


Policy makers are pushing for Nature-based Solutions (NbS) to store carbon and reduce disaster risk in flood prone areas. The COP26 and recent flood events across Europe are likely to focus our minds on ecosystem-based climate change mitigation and adaptation even further.

Restoring and managing wetland, dune or riparian forest vegetation to reduce flood risk, however, requires a sound understanding of interactions between biodiversity and ecosystem functions (and hence services) to ensure resilience in a changing climate. Vegetated habitats at land-water interfaces are driven by complex interactions between plant functional traits (e.g. stem flexibility, canopy height) and abiotic landscape processes (e.g. hydrodynamics). Both, biotic (e.g. species composition) and abiotic (flooding, salinity, waves) processes in coastal (Rouger and Jump 2014) and riparian habitats are very dynamic and need to be taken into account when designing restoration for NbS. This PhD will make a key contribution to improve the predictability of such interactions with regards to provisioning of ecosystem services.

As an example, wave attenuation will largely depend on the density, rigidity, and height of the vegetation present at any given time but also on the seasonality and spatial distribution of wave energy along the coast. Additionally, such bio-physical interactions are likely to be affected long-term by changing seasonality and increasing storminess due to climate change with unknown consequences for the plant communities delivering these ecosystem services (Balke and Nilsson 2019).

The aim of this PhD studentship is to develop new fundamental understanding of the bi-directional interactions between plant traits and abiotic forcing (flooding/waves/wind/sediment transport) in a changing climate. The PhD outcomes will feed into adaptive restoration guidelines/predictive models for key habitats along land-water interfaces in the UK (coasts and rivers) to ensure biodiversity and societal benefits of restoration projects are delivered.


This PhD studentship is substantially based on fieldwork and field experiments, accompanied by growth experiments in the greenhouse and in mesocosm facilities. The student will also develop a meta-analysis of existing datasets on functional plant traits responding to and affecting abiotic processes such as flooding and mechanical stimulation.

1. The field monitoring methods will be interdisciplinary across plant ecology, physical geography, hydrology and geomorphology. The successful candidate will set up automatic monitoring with data loggers and time lapse cameras and conduct regular surveys of permanent vegetation plots and plant traits. Hydrology and hydrodynamics will be monitored across seasons using Mini Buoys, a low-cost device hydrodynamic monitoring device developed by the supervisory team (Balke et al. 2021). The aim will be to elucidate the interactions between abiotic forcing/mechanical stimulation and changes in plant trait expressions. This component will be largely carried out in UK coastal habitats (salt marshes, dunes) but may be expanded to include other ecosystems worldwide.

2. Experiments in the field, greenhouse and mesocosms will be designed to test effects of specific timing of stress and disturbance on plant survival and trait expressions. Common garden experiments will be set up to test for adaptations of the same species in contrasting regions to specific seasonality of abiotic forcing on trait expressions.

3. The PhD student will be trained in data analysis of large datasets and conduct a systematic meta-analysis of existing data on bio-physical traits of plants to deliver trait-based design guidelines for Nature-based Solutions at land-water interfaces.

Project Timeline

Year 1

Setting up of permanent plots and trait sampling protocols. Collation of database for the meta-analysis of biophysical interactions, timing and traits. Installation of field monitoring equipment for monitoring across 3 years. Training in systematic meta-analysis and statistical analysis of time series.

Year 2

Comparative experiments using greenhouse and mesocosm facilities comparing salt marsh and dune-species trait expressions to timing of physical forcing. Continued field monitoring and start of meta-analysis.

Year 3

Common garden experiment and manipulative field experiment to test local adaptation to abiotic seasonality. Continued field monitoring and data retrieval.

Year 3.5

Finalize meta-analysis and write up of dissertation. Attendance of international conference.

& Skills

This studentship will equip the graduate with a range of highly desirable skills from technical skills in field and laboratory to statistical, spatial and time series analysis skills. Development of expert knowledge in the R statistical programming language will be encouraged and facilitated by the supervisory team. The successful candidate will be able to access postgraduate training opportunities at the University of Glasgow and the University of Stirling and will be part of two active research groups with ongoing RCUK funded research activities in the proposed interdisciplinary subject area in the UK and overseas. The interdisciplinary nature of the project will allow the PhD student to develop specialist knowledge in coastal plant ecology, hydrology and geomorphology, all highly relevant skills in time of climate change and rising sea levels.

References & further reading

Monitoring tidal hydrology in coastal wetlands with the “Mini Buoy”: applications for mangrove restoration T Balke, A Vovides, C Schwarz, GL Chmura, C Ladd, M Basyuni. (2021)
Hydrology and Earth System Sciences 25 (3), 1229-1244

Increasing synchrony of annual river‐flood peaks and growing season in Europe
T Balke, C Nilsson. (2019) Geophysical Research Letters 46 (17-18), 10446-10453

A seascape genetic analysis reveals strong biogeographical structuring driven by contrasting processes in the polyploid saltmarsh species Puccinellia maritima and Triglochin maritima. Rouger R, Jump AS (2014) Molecular Ecology, 23, 3158-3170

Further Information

Apply Now