Abstract
As the major form of coral reef regime shift, stony coral to macroalgal transitions have received considerable attention. In the Caribbean, however, regime shifts in which scleractinian corals are replaced by octocoral assemblages hold potential for maintaining reef associated communities. Accordingly, forecasting the resilience of octocoral assemblages to future disturbance regimes is necessary to understand these assemblages’ capacity to maintain reef biodiversity. We parameterised integral projection models quantifying the survival, growth, and recruitment of the octocorals, Antillogorgia americana, Gorgonia ventalina, and Eunicea flexuosa, in St John, US Virgin Islands, before, during, and after severe hurricane disturbance. Using these models, we forecast the density of populations of each species under varying future hurricane regimes. We demonstrate that although hurricanes reduce population growth, A. americana, G. ventalina, and E. flexuosa each display a capacity for quick recovery following storm disturbance. Despite this recovery potential, we illustrate how the population dynamics of each species correspond with a longer- term decline in their population densities. Despite their resilience to periodic physical disturbance events, ongoing global change jeopardises the future viability of octocoral assemblages.
Original language | English |
---|---|
Number of pages | 13 |
Journal | Coral Reefs |
Early online date | 7 Feb 2024 |
DOIs | |
Publication status | E-pub ahead of print - 7 Feb 2024 |
Keywords
- Ecological forecasting
- Gorgonians
- Hurricane disturbance
- Integral projection models (IPMs)
- Stochastic population growth rate
- US Virgin Islands
Fingerprint
Dive into the research topics of 'The recovery of octocoral populations following periodic disturbance masks their vulnerability to persistent global change'. Together they form a unique fingerprint.Datasets
-
CantJ/Forecasting_Octocoral_Resilience: Modelling octocoral viability under recurrent disturbance regimes
Cant, J. (Creator), Zenodo, 1 Feb 2024
Dataset