Modelling connectivity

ABOVE: Simulated larval dispersal in a column of water located near the Gascoyne Commonwealth Marine Reserve (Cape Range Canyon and Carnarvon Canyon), WA. Red lines indicate CMR boundaries, and purple points indicate particle positions. The animation shows daily positions of particles from 2009-01-01 to 2009-12-31.

Well-connected populations can ameliorate habitat fragmentation by reaching out to one another during difficult times. Connectivity also lets species reach previously unoccupied changing habitat, and can generate concentrated pockets of diversity through overlap and accumulation.

This study developed an individual-based dispersal model to simulate the movement and connectivity of marine larvae in four dimensions (three-dimensional space over time). The model simulates the interactions of billions of individual larvae with their environment, enabling studies of their collective behaviour.

Ocean depth models showing larval dispersal clouds.

ABOVE: Depth slices taken through three-dimensional larval dispersal clouds at the sea surface (left) and 3000–3500 m water depth (right) spanning the Gascoyne, Carnarvon and Abrolhos CMRs. Warm colours represent high larval concentrations. Note the broader dispersal at the sea surface and trapping effect of canyons at depth. Image: Geoscience Australia.

Three-dimensional ocean currents and larval behaviour are combined in the model to map the expected flow patterns (for a pelagic larval phase of 90 days). Australia’s national supercomputer at the Australian National University performs the trillions of calculations required, and the connections it traces can be sliced or grouped by geography (such as canyons, marine reserve, Key Ecological Feature, or volume) and time.

Connectivity modelling can help to guide management decisions by detecting interdependent areas such as clusters of canyons, exchanges between regions, and areas of high ‘source’ capacity. It can also point to critical links that maintain the resilience of marine systems, and predict the potential spread of invasive species.