A Bayesian overhaul of thermal tolerance landscape models: Predicting ectotherm lethality buildup and survival amid heatwaves DOI Open Access
Jahangir Vajedsamiei,

Niklas Warlo,

H. E. Markus Meier

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 26, 2024

ABSTRACT 1. In the face of escalating heatwaves, accurately forecasting ectotherm population mortality is a pressing ecological challenge. Current Thermal Tolerance Landscape (TTL) models, while surpassing single-threshold metrics by incorporating individual survival times, are constrained frequentist regression parametrization reliant on constant-temperature experiments, omitting probabilistic outcomes. 2. This study addresses these limitations pioneering application Approximate Bayesian Computation-Sequential Monte Carlo (ABC-SMC) to analyze data from Baltic Mytilus mussels subjected both microcosm (constant temperature) and mesocosm (dynamic heatwave regimes. 3. The ABC-SMC yields predictions lethality buildup trajectories, closely aligned with observed across experimental conditions. Informed more realistic dynamic data, TTL model predicts local mussel resilience against most extreme summer heatwaves projected for this century, albeit considerations sublethal impacts potential recruitment declines. 4. Our approach can enhance predictive accuracy concerning sensitivity key marine populations amidst intensifying addressing urgent need accurate modeling tools inform conservation practices ecosystem management, ultimately aiding in preservation biodiversity.

Язык: Английский

Impact of multiple-factors on health and infections in marine mussels (Perumytilus purpuratus) inhabiting contaminated sites in the Humboldt Current System DOI Creative Commons
Diana Montenegro, María Teresa González

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 21, 2025

Marine organisms are increasingly exposed to a combination of environmental stressors. However, most studies focus on single factors, limiting our understanding real-world ecological challenges. This study investigates the combined effects metal pollution, parasites, pathogens, and variables health Perumytilus purpuratus, mussel species inhabiting coast northern Chile. The upwelling system in this area, with low water turnover, creates unique environment which how multiple factors interact. Mussels were sampled from several sites affected by discharges. Analyses revealed that individuals central exhibited highest levels tissue lesions. These impacts strongly associated elevated pH, salinity, cadmium copper concentrations water. Findings emphasise synergistic chemical abiotic underscoring importance incorporating interactions into monitoring programmes. Such an approach can enhance predictions responses, inform conservation efforts, guide policies addressing global challenges like aquatic pollution. Our provides critical insights threaten ecosystems, offering framework for more comprehensive assessment.

Язык: Английский

Процитировано

0

Efficiency of the green mussel, Perna viridis (Linnaeus, 1758) to bioremediate total heterotrophic bacteria, Vibrio and Plankton in the culture medium of the tiger shrimp Penaeus monodon pond system DOI
Elgen M. Arriesgado, Dan M. Arriesgado, Fernand F. Fagutao

и другие.

Aquaculture International, Год журнала: 2025, Номер 33(4)

Опубликована: Март 31, 2025

Язык: Английский

Процитировано

0

A Bayesian overhaul of thermal tolerance landscape models: Predicting ectotherm lethality buildup and survival amid heatwaves DOI Open Access
Jahangir Vajedsamiei,

Niklas Warlo,

H. E. Markus Meier

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 26, 2024

ABSTRACT 1. In the face of escalating heatwaves, accurately forecasting ectotherm population mortality is a pressing ecological challenge. Current Thermal Tolerance Landscape (TTL) models, while surpassing single-threshold metrics by incorporating individual survival times, are constrained frequentist regression parametrization reliant on constant-temperature experiments, omitting probabilistic outcomes. 2. This study addresses these limitations pioneering application Approximate Bayesian Computation-Sequential Monte Carlo (ABC-SMC) to analyze data from Baltic Mytilus mussels subjected both microcosm (constant temperature) and mesocosm (dynamic heatwave regimes. 3. The ABC-SMC yields predictions lethality buildup trajectories, closely aligned with observed across experimental conditions. Informed more realistic dynamic data, TTL model predicts local mussel resilience against most extreme summer heatwaves projected for this century, albeit considerations sublethal impacts potential recruitment declines. 4. Our approach can enhance predictive accuracy concerning sensitivity key marine populations amidst intensifying addressing urgent need accurate modeling tools inform conservation practices ecosystem management, ultimately aiding in preservation biodiversity.

Язык: Английский

Процитировано

2