Project Overview
Global Seamounts Project
Modeling complex ecosystem function on oceanic seamounts
Surveying and Modeling a Complex Ecosystem
The impetus for the Global Seamounts Project is a recognition that the work of the Census of Marine Life on Seamounts (CenSeam), a five-year field initiative carried out as part of the Census of Marine Life (CoML) (1) represents an opportunity to extend the CoML work for seamounts in several respects.
Scientific papers published from CenSeam emphasized that extending then-current lines of research methods is not sufficient to reach an understanding of ecosystem function. A paper reporting on outcomes of the Census of Marine Life on Seamounts (2) stated:
“There are many aspects of seamount and deep-sea ecosystem structure and function that we do not understand, and which may in the long-term be critical for effective management. However, research is in many respects still at the stage of describing the composition and structure of seamount habitat and communities, and appreciating complex functional processes is still a long way in the future.”
This key objective, to better understand and ideally to computationally model and predict complex function and behavior of seamount ecosystems, led to Global Oceans' proposal for an integrated ecosystem modeling component of the Global Seamounts Project - toward accelerating our understanding of dynamic ecosystem function from "a long way in the future" to within the next few years.
The GSP plan to achieve this is to 1) more systematically and comprehensively survey a sample set of seamount systems globally; 2) incorporate new imaging, sampling, and omics-level analysis technologies now available; and most importantly, 3) to merge new intercalibrated datasets from across representative seamounts with an innovative ensemble of linked marine ecosystem, biogeochemical, and physical computer models to create a new integrated seamounts model that can simulate complex and emergent ecosystem behavior.
New sampling and analytical methods including chemical sensors and omics-level technologies, coupled with the global capacity to configure and deploy MARV research vessels to meet the objective of extensive seamount surveys, is envisioned as a basis for more comprehensively realizing the original objectives of CenSeam, which included more complete understanding of biodiversity and spatial scales of population connectivity, of ecosystem dynamics, and the impacts of human disturbance, resource extraction, and climate change.
The science of modeling complex, nonlinear systems, and the computing power required to process such models, is advancing rapidly. The principal constraint now for applying these advances to modeling oceanic systems is in acquiring the scope and resolution of environmental data required to populate them, and this is what the Global Seamounts Project will do.
Figure 1 shows how the proposed ensemble of leading marine ecosystem and physical ocean models will link together and be populated with data from the field campaign. The model ensemble will be run against initial conditions set by users and standardized environmental data from aggregated field data. Model outputs can then be further linked and integrated with climate model scenarios, network metrics relevant to conservation and resource management can be generated, and applications for modeling emergent behavior such as thresholds and tipping points can be explored. Examples of outputs and potential applications and benefits of the model are shown in Figure 1.
The synthesis of field observation and laboratory data with ecosystem modeling inputs and outputs is summarized in Figure 2 and shown in more detail in Figure 3. Figure 4 shows how Working Groups are organized. In short, taken together this new integrated field + modeling work will help to achieve the goal of accelerating our understanding of complex ecosystem function on seamounts in response to multiple potential impacts from climate change and human activity.
Project-configured MARVs Enable Project Scope
Operational research vessel capacity for multiple expeditions will be met with MARV research vessels configured to support the project (Figures 5-7). Utilization of time-chartered, science-adapted MARV platforms for the GSP Field Campaign addresses a constraint the project would otherwise be faced with – the need to mobilize an intensively scheduled fleet of global class research vessels, including deployed for the project simultaneously in different ocean basins and capable of hosting international science teams, lab and workspace clusters, and deep-sea vehicles.
New Explorer 6000 OEV and Innerspace 6000 TIA Deep Sea Vehicles
Remotely Operated Vehicles (ROVs) will be a principal sampling and documentation modality for the GSP, together with towed systems, autonomous gliders, and benthic landers.
A dedicated deep sea vehicle for the project will be provided by a rebuild of a 6,000-meter ROV acquired by Global Oceans from Oceaneering International. The new 6,000-meter scientific research vehicle will be named the Explorer 6000 OEV (Ocean Exploration Vehicle) (Figure 8). The OEV will host a suite of standardized and customizable observation and sampling systems including push cores, ultra-low power suction samplers, mini-box cores, storage systems for biological samples, biogeochemical sensors, Niskin bottles, and high-resolution video.
Global Oceans’ Innerspace 6000 TIA (Towed Instrument Array) vehicle (Figure 9) will be used by the project to survey the seabed adjacent to seamounts. See the Project Highlight Geomorphic Proxies for Biodiversity on Seamounts here for more information about the planned deployment of the towed vehicle.
References
1. Stocks KI, Clark MR, Rowden AA, Consalvey M, Schlacher TA (2012) CenSeam, an International Program on Seamounts within the Census of Marine Life: Achievements and Lessons Learned. PLoS ONE 7(2): e32031. doi:10.1371/journal.pone.0032031
2. Clark MR, Schlacher TA, Rowden AA, Stocks KI, Consalvey M (2012) Science Priorities for Seamounts: Research Links to conservation and Management. PLoS ONE 7(1): e29232. doi:10.1371/journal.pone.0029232.