Simulations reveal hybridization in Caribbean Acropora restoration poses low risk of genetic swamping but limited potential for adaptive introgression

preprint OA: closed
Full text JSON View at publisher
Full text 1,763 characters · extracted from oa-doi-fallback · click to expand
Abstract Severe global declines in coral populations have driven growing demand for human intervention and restoration. One goal of restoration is to repopulate reef ecosystems through outplanting, which requires detailed understanding of target systems. However, long term ecological and reproductive data from interventions remain scarce. An exception to this are the critically endangered Caribbean corals, Acropora palmata and A. cervicornis, which have been central to restoration efforts in the region. These species serve as a unique case study due to the abundance of published data spanning ecology, and reproductive biology. In the wild, these species can cross to form an F1 hybrid, A. prolifera, though it is rarely used in restoration. It remains unclear whether A. prolifera is an evolutionary dead-end competing with its parents, or a potential bridge enabling genetic exchange via backcrossing. To evaluate benefits and risks of restoration among Caribbean Acropora, we developed a two-dimensional agent-based simulation using reproductive and ecological data to model realistic reef dynamics. Our model suggests the hybrid can facilitate introgression between parentals without outcompeting them. Yet, such introgression is too limited for large-scale or beneficial ancestry transfer except under ecologically unrealistic conditions or timescales significantly longer than those relevant for management. Thus, our model suggests that the risks of genetic swamping may be overstated, whereas hopes for adaptive introgression are also low, underscoring the value of simulations for generating long-term ecological and evolutionary insights relevant to coral restoration. Competing Interest Statement The authors have declared no competing interest.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00