In today’s ocean, ecosystems are subject to stresses from multiple sources, including environmental change as a result of natural variations or cycles, the effects of climate change, and increasing human activities in the ocean.
Distinguishing between ecosystem responses to natural environmental variability and those triggered by external pressures is a significant challenge, but is critical in order to manage our ocean-based activities in a responsible and sustainable manner. Identifying areas at greatest risk and where tipping points lie can assist ocean managers to adjust monitoring and mitigation measures as the likelihood of ecosystem change increases.
An important first step is to distinguish impacts of climate change from the impacts caused directly by human activity, and to assess whether increased resource exploitation could push, or ‘tip’, an ecosystem towards a permanent change in structure, functioning, or provision of ecosystem services.
iAtlantic examined historical patterns of ecosystem change to identify, understand and quantify its drivers and tipping points. Biological timeseries data (biological measurements collected in the same area over long periods – in some cases, many decades) from the iAtlantic study regions are being examined for evidence of rapid change or tipping points, and combined with new data collected during iAtlantic’s many research expeditions.
In addition, five new methods for detecting biological change over time were tested:
- Changes in hydrothermal vent communities at the Lucky Strike hydrothermal vent field on the Mid-Atlantic Ridge were examined at a range of scales using imagery from repeat ROV surveys and high-definition camera stills taken daily by the EMSO-Azores seafloor observatory over the past 10 years. Images were used to visually reconstruct the whole vent at specific points in time so that changes can be measured.
- The annual changes in population sizes of humpback whales in the northern mid-Atlantic ridge area off Iceland and Sargasso Sea were estimated using a mathematical modelling technique called mark recapture. Surveys in both areas identified individual whales by their characteristic markings on their flukes (tails) and the data used to estimate whale abundance each year. Timeseries were created by using specialist modelling techniques to estimate the number of individual animals across multiple sampling years.
- Plankton biomass in the water column was estimated using routinely-collected oceanographic data (ADCP), and the results ground-truthed by water column sampling and towed camera observations. Analysing the yearly changes in the vertical migration behaviour of these plankton could provide a valuable system for monitoring ecosystem change.
- In areas of the ocean where we don’t have traditional biological timeseries datasets, geochemical methods were used to look at changing ocean conditions over time. Changes in water mass distribution and circulation, temperature and salinity, carbonate saturation, nutrient content, organic matter flux and deep-sea current rates leave a chemical ‘signature’ in seafloor sediments and deep-sea corals, so geochemical sample analysis revealed environmental change over timescales of hundreds or thousands of years.
- Seafloor sediments contain the genetic traces of tiny creatures called foraminifera (forams for short), which live in the water column and sink to the seafloor when they die. This ancient genetic material (aDNA) can be sampled from sediment cores and analysed to see how the foram community has changed over time. These results were compared to more traditional methods of examining historical foram communities (i.e., through microfossil identification) to see how accurate and reliable the aDNA technique is. Foram assemblages are important because they give us information about the environmental conditions at the time the foram was living in the water column. However, traditional methods of analysing forams from a sediment sample are labour intensive, and are dependent on the sample containing well preserved microfossils.
These methodologies, among others, are described in the iAtlantic report ‘Methods to create and assess deep-sea and open ocean ecosystem time series‘ (Deliverable 3.1).
In May 2022, the iAtlantic WP3 team completed a major piece of research, culminating in the delivery of a 200-page report on ‘Drivers of ecosystem change and tipping points‘ (Deliverable 3.2).
A high-level summary of this report was published in the June 2022 edition of the iAtlantic newsletter, and can be downloaded as a standalone article (PDF, 2.4 MB).
Outputs from our timeseries work were then combined with iAtlantic’s oceanographic hindcasts and forecasts to carefully analyse the relationships between climatic and biological change in the ocean. Each biological timeseries was examined for generic signals of tipping points, and assessed on whether more ecosystem-specific signals of ecosystem change can be identified – for example, a slower coral accumulation rate in a sediment core as a result of slowing ocean circulation. The results of this analysis are reported in Deliverable 3.3: Risk assessments of future changes to ecosystem dynamics and risk of tipping points.
iAtlantic will produce maps illustrating where climate-based predictions of ocean change will likely result in significant ecosystem shifts and tipping points being reached, and information on critical threshold levels will be shared with policymakers.
Key objectives:
Understand drivers of ecosystem change at regional to ocean scales across different ecosystems, and to validate the use of generic and system-specific tipping points to forecast ecosystem change:
- Quantify the single and cumulative effects of oceanographic variability (and any anthropogenic pressures) on key ecosystem compartments;
- Test the nature of ecosystem changes for gradual shifts, generic and system-specific thresholds;
- Score each of the iAtlantic study regions according to whether their focal ecosystems are likely to change under future climate change forecasts.
iAtlantic’s work on drivers of ecosystem change is led by Dr Lea-Anne Henry at University of Edinburgh, supported by Dr Marjolaine Matabos at Ifremer.
