Future Seas: Intraspecific variability in the ecological and transcriptional stress responses of intertidal ecosystem engineers

Ocean acidification, eutrophication, and climate change are priority areas for global biodiversity conservation research (Mrowicki et al. 2016), and have been identified as ‘grand challenges’ for marine research (Elith & Leathwick 2009, Kuo & Sanford 2009). There is a need to better understand organism–environment linkages, identify the importance of the functional diversity of species, and understand how organisms respond to both natural and anthropogenically driven environmental change. The effects of climate change, coupled with ocean acidification, are already significantly altering the structure and functioning of coastal ecosystems around the globe (Kuo & Sanford 2009).
Rapid environmental changes in natural systems are variable and nonlinear, with biological responses difficult to interpret due to the complex, interacting influences exerted on organismal physiology. Species-specific impacts occur as the result of different functional traits (growth, reproduction, morphology), sensitivities, and adaptive and acclimatory capacities. Ecological stability is related to pathways of energy flow within organisms, with resultant implications for the resilience, resistance and persistence of populations. Shifts in the temporal dynamics of ecosystem engineers in response to environmental changes can change the vulnerability of entire communities to disturbance (such as temperature shifts), although the degree of potential change is poorly understood (Pearson et al. (2009). Biological impacts cause subsequent shifts in species distributions that are likely to result in novel ecological conditions in future climates that have no previous analog (Mieszkowska et al. 2006, Helmuth et al. 2006, Burrows et al 2011).
Environmental change is rapidly increasing in rate and magnitude, and can alter survival, fitness, phenologies and interactions, affecting population viability and food web dynamics and the ecological stability of ecosystems (Lima & Wethey 2009). The gradual increase in multifactorial environmental pressures may drive changes or result in an Abrupt Community Shift (ACS) (Russell et al. 2013) that may select for more resistant phenotypes. However, whilst ACS are ultimately induced by large scale environmental changes, ecosystem stability is generated by local scale conditions, presenting a fast-moving target for the management and conservation of species, ecosystems, and the services that they provide. To address this challenge requires interdisciplinary science and data at multiple scales.
The rocky intertidal zone is a natural laboratory for examining these relationships between abiotic stressors and biological interactions. Intertidal species are easily accessible, their ecology and biology are well understood, and they act as early warning systems for anthropogenic impacts (http://www.ipcc.ch/report/ar5/wg1, http://oceanacidification.noaa.gov). High spatio-temporal variation in environmental and anthropogenic parameters occur at the local scale and across large latitudinal gradients in environmental conditions from the tropics to the poles. The rocky intertidal is an ideal study system for ecological stability and the processes governing resilience and resistance as this ecosystem is comprised of species from both terrestrial and marine evolutionary origins and has high natural social capital value.
This project will address the challenges of fast-moving, local-scale stressors by; 1) Investigating phenotypic plasticity under future climate scenarios and the implications for local adaptation of key ecosystem engineer species over multiple generations; and 2) Address the degree of ecological sensitivity to environmental conditions by identifying transcriptome responses and physiological mechanisms of selected target species.

The student will be


The research will comprise two main components focused on key ecosystem engineer species, ultimately selected by the student:
1.) Long-term mesocosm experiments will be used to investigate intrinsic metabolic and physiological mechanisms to elucidate how organisms respond to chronic changes in environmental conditions (Russell et al. 2013). These experiments will use future marine climate change (+1.8–4.0°C), ocean acidification (pH 8.0 –7.6), and eutrophication (DIN 8-10μM, DIP 2 μM) scenarios, based on IPCC, NOAA and Bio-ORACLE forecasts for 2050 and 2100 (http://www.ipcc.ch/report/ar5/wg1, http://oceanacidification.noaa.gov, Sunday et al. 2012). Biometric parameters and physiological performance of adults and reared juveniles will be measured throughout the experiments.
2.) The student will also investigate gene expression, which is highly plastic and reveals the physiological response of organisms to environmental conditions. Mesocosms provide an ideal level of control over critical environmental variables and yield statistically robust sample sizes, allowing for deep insights into how organisms may respond to climate change in the future. The student will extract RNA from muscle and visceral tissue and perform whole-transcriptome shotgun sequencing (RNA-seq). Sequences will be mapped to reference genomes, which are annotated with known gene functions, and then the sequence counts will be used to identify differentially expressed genes (DEGs) and modulated pathways. Since mRNA represents the expressed fraction of the genome, we will uncover mechanistic responses directly relevant to phenotypes of target species. This will be undertaken on key ecosystem engineer species for which full genome sequences have been made available through the Darwin Tree of Life project (https://www.darwintreeoflife.org).

The student will be primarily based in Newcastle, supervised by Dr Ben Wigham, for the experimental mesocosm component of the research, with collaboration from Dr Nova Mieszkowska at the University of Liverpool. The molecular transcriptomic and gene expression component of the research will take place at Durham University, supervised by Dr Andreanna Welch.

Project Timeline

Year 1

• Mesocosm set up, training and initial trials
• Set up and running of first stage, multiple stressor mesocosm experiments.
• Complete a workshop on transcriptomics offered by NEOF, prepare for molecular lab work
• Presentation of project aims and outlines in suitable conference outlets

Year 2

• Continuation of multiple stressor mesocosm experiments to provide >18 months of data.
• Set up and running of multiple generation experiments informed by first stage experiments
• Conduct transcriptomic lab work
• Analysis of data from first rounds of experiments
• Write first paper on multiple stressor impacts.

Year 3

• Complete multiple generation experiments.
• Bioinformatics and statistical analysis of transcriptomic data
• Write second paper on gene expression and adaptations
• Analyse data on generational impacts of multiple stressors
• Present results at suitable conference outlets

Year 3.5

• Complete data analyses
• Write paper on generational impacts of multiple stressors
• Produce thesis

& Skills

The student will receive training in husbandry, experimental design, laboratory techniques, molecular techniques, bioinformatics, and public engagement. They will benefit from being part of an NU DTP cohort where the student will acquire data analysis skills through existing ecological modelling and related post-graduate modules at NU. At Durham they will be part of an active and supportive lab group, take part in regular journal clubs and lab meetings, and receive training on bioinformatics with our sophisticated high performance computing cluster. Other cross-disciplinary skills (e.g. project planning and management; scientific writing and critical analysis; data analysis and statistics) will be gained through specialist modules at both NU and Durham which are easily accessible to the student being closely co-located.

References & further reading

Burrows et al (2011) Science. 334, 652
Elith & Leathwick (2009) AREES 40, 677
Helmuth et al. (2006) AREES 37, 373
Kuo & Sanford (2009) Mar. Ecol. Prog. Ser. 388, 137
Lima & Wethey (2009) Limnol. Oceanogr. Methods 7, 347
Mieszkowska et al. (2006) Hydrobiologia 555, 241
Mrowicki et al. (2016) J. Ecology 104, 887
Pearson et al. (2009), J. Ecol. 97, 450
Russell et al. (2013), Philos. Trans. R. Soc. Lond. B 368, 1627
Sunday et al. (2012) Nature Climate Chante 2(9), 686

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