Biology subjects

Raymundo, L.

Publications and source records attributed to Raymundo, L..

2 recordsLinked to original sources

bioRxiv2024

Population genomics for coral reef restoration - a case study of staghorn corals in Micronesia

Staghorn Acropora corals are ecological keystone species in shallow lagoons and back reef habitats throughout the tropics. Their widespread decline coupled with their amenability for asexual propagation propelled them to the forefront of global coral restoration efforts - albeit frequently without much scientific input. To guide these efforts and as a blueprint for similar projects, we conducted a comprehensive population genomic study of Acropora cf. pulchra, a major restoration target species in the Indo-Pacific. Our results revealed that A. cf. pulchra populations in the Mariana Islands are characterized by large clonal clusters and extremely low levels of genetic diversity. Differentiation among populations followed a significant isolation-by-distance pattern and delineated two distinct metapopulations on Guam. Our investigation identified critical population genetic parameters, necessitating targeted management strategies, and provides actionable guidelines for effective conservation efforts. For management and conservation, two populations emerged as pivotal connectivity hubs with elevated genetic diversity. For restoration, we show that A. cf. pulchra populations demonstrated a suitability for extensive asexual propagation and provide guidelines how to best apply that. To preserve and augment genetic diversity, strategies to mitigate inbreeding are crucial until sexual reproduction can be fully integrated into restoration protocols. Critical sites for restoration include local connectivity hubs, fringing lagoons that connect metapopulations, and back reefs around a particularly isolated population. These findings offer crucial insights into the genetic landscape of a keystone coral species and provide actionable recommendations for coral conservation and restoration. By advocating for the preservation of population connectivity and the promotion of genotypic, genetic, and symbiont diversity in coral restoration, our study serves as a blueprint for leveraging population genomic studies to enhance the efficacy and resilience of restoration projects on remote islands.

evolutionary biology↗

bioRxiv2023

Multi-Factor Coral Disease Risk Forecasting for Early Warning and Management

Ecological forecasts are becoming increasingly valuable tools for conservation and management. However, there are few examples of near real-time forecasting systems that account for the wide range of ecological complexities. We developed a new coral disease ecological forecasting system that explores a suite of ecological relationships and their uncertainty and investigates how forecast skill changes with shorter lead times. The Multi-Factor Coral Disease Risk product introduced here uses a combination of ecological and marine environmental conditions to predict risk of white syndromes and growth anomalies across reefs in the central and western Pacific and along the east coast of Australia and is available through the U.S. National Oceanic and Atmospheric Administration Coral Reef Watch program. This product produces weekly forecasts for a moving window of six months at [~]5 km resolution based on quantile regression forests. The forecasts show superior skill at predicting disease risk on withheld survey data from 2012-2020 compared with predecessor forecast systems, with the biggest improvements shown for predicting disease risk at mid-to high-disease levels. Most of the prediction uncertainty arises from model uncertainty and therefore prediction accuracy and precision do not improve substantially with shorter lead times. This result arises because many predictor variables cannot be accurately forecasted, which is a common challenge across ecosystems. Weekly forecasts and scenarios can be explored through an online decision support tool and data explorer, co-developed with end-user groups to improve use and understanding of ecological forecasts. The models provide near real-time disease risk assessments and allow users to refine predictions and assess intervention scenarios. This work advances the field of ecological forecasting with real world complexities, and in doing so, better supports near term decision making for coral reef ecosystem managers and stakeholders. Secondarily, we identify clear needs and provide recommendations to further enhance our ability to forecast coral disease risk.

ecology↗