Back

Optimising fertilisation kinetics models for broadcast spawning corals in the genus Acropora

Buccheri, E.; Babcock, R. C.; Mumby, P. J.; Doropoulos, C.; Ricardo, G. F.

2025-05-17 systems biology
10.1101/2025.05.13.653772 bioRxiv
Show abstract

Synchronous spawning is a specialised adaptation to maximise fertilisation success in free spawning sessile invertebrates. There are many factors that drive and limit reproduction in such benthic invertebrates including localised hydrodynamic forcing, adult density dependence, and fine-scale gamete interactions, all of which are difficult to measure in situ. Therefore, measures to manage or restore reproductive populations of sessile invertebrates rely in part on adequate modelling of spawning processes at localised scales. Fertilisation kinetics of spawning events has been modelled for many free spawning marine invertebrate taxa, yet little work has been done to parameterise such models for hermaphroditic corals. This study used experimentally derived coral-specific parameters and optimisation protocols to improve model predictions of fertilisation outcomes for Acropora kenti (formerly A. "Maggie" tenuis) and A. digitifera. Three fine scale parameters that are difficult to measure experimentally - fertilisation efficiency (Fe), egg concentration (E0), and polyspermy block strength (tb) - were estimated using optimisation, and medians and 95% confidence intervals were derived for each parameter and species. For A. kenti the median optimised Fe value was 0.0194 (0.0027-0.0776), and tb was 0.1000 (0.1000-0.1000). For A. digitifera, the median optimised Fe value was 0.0013 (0.0002-0.0030), and tb was 10.0000 (2.4703- 10.0000). Further, sensitivity analyses suggest that kinetics models are the most sensitive to changes in Fe parameter values, as well as species-specific metrics like sperm swimming speed and egg size. Results will inform biophysical coral fertilisation models to better predict reproductive outcomes and support management decisions that safeguard natural reef recovery.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Marine Ecology Progress Series
21 papers in training set
Top 0.1%
27.0%
2
Frontiers in Marine Science
62 papers in training set
Top 0.1%
11.2%
3
Royal Society Open Science
214 papers in training set
Top 0.3%
6.8%
4
Ecology and Evolution
267 papers in training set
Top 2%
4.4%
5
PeerJ
308 papers in training set
Top 2%
3.5%
50% of probability mass above
6
Coral Reefs
21 papers in training set
Top 0.1%
2.8%
7
Global Change Biology
78 papers in training set
Top 0.8%
2.4%
8
Journal of Experimental Biology
259 papers in training set
Top 1%
2.4%
9
Ecological Modelling
28 papers in training set
Top 0.3%
1.9%
10
G3: Genes, Genomes, Genetics
252 papers in training set
Top 3%
1.7%
11
eLife
5828 papers in training set
Top 52%
1.5%
12
Peer Community Journal
281 papers in training set
Top 3%
1.5%
13
Canadian Journal of Fisheries and Aquatic Sciences
18 papers in training set
Top 0.2%
1.5%
14
PLOS ONE
5266 papers in training set
Top 52%
1.5%
15
Frontiers in Systems Biology
10 papers in training set
Top 0.1%
1.1%
16
Biological Journal of the Linnean Society
24 papers in training set
Top 0.5%
1.1%
17
Scientific Reports
3612 papers in training set
Top 64%
1.1%
18
Frontiers in Physiology
106 papers in training set
Top 2%
1.1%
19
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 5%
1.0%
20
iScience
1154 papers in training set
Top 30%
1.0%
21
Journal of Phycology
14 papers in training set
Top 0.3%
0.9%
22
Journal of The Royal Society Interface
235 papers in training set
Top 4%
0.9%
23
Oikos
84 papers in training set
Top 1%
0.9%
24
Bioinformatics
1204 papers in training set
Top 9%
0.6%
25
Global Ecology and Biogeography
47 papers in training set
Top 1%
0.6%
26
Bulletin of Mathematical Biology
92 papers in training set
Top 2%
0.6%
27
Ecological Monographs
21 papers in training set
Top 0.6%
0.6%
28
Molecular Ecology
336 papers in training set
Top 4%
0.6%
29
Integrative Organismal Biology
15 papers in training set
Top 0.4%
0.6%
30
Gigabyte
62 papers in training set
Top 1%
0.6%