Predicting adaptation and evolution of plasticity from temporal environmental change DOI Creative Commons
Cristóbal Gallegos, Luis‐Miguel Chevin, Kathryn A. Hodgins

et al.

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 16(1), P. 84 - 96

Published: Nov. 22, 2024

Abstract Environmental change can drive evolutionary adaptation and determine geographic patterns of biodiversity. Yet at a time rapid environmental change, our ability to predict its impacts is incomplete. Temporal in particular, involves combination major components such as abrupt shift, trend, cyclic noise. Theoretical predictions exist for isolated components, but knowledge gaps remain regarding their joint impacts. We extend classic theory develop model the evolution tolerance by an underlying developmentally plastic trait, response temporal change. retrieve synthesise earlier responses generate new changing simultaneously. Notably, we show how different forms predictability emerging from interplay stochastic (noise) lag between development selection shape predictions. then illustrate utility generating testable plasticity when parameterised with real series data. Specifically, parameterise daily sea‐surface temperature global marine hotspot southern Australia, use simulations thermal tolerance, differences this region. By synthesising on providing insights into effects framework, embedded Shiny app, offer path better biological climate

Language: Английский

Modeling the Effects of Extreme Temperatures on the Infection Rate of Botrytis cinerea Using Historical Climate Data (1951–2023) of Central Chile DOI Creative Commons
William Campillay‐Llanos, Samuel Ortega-Farías,

Patricio González-Colville

et al.

Agronomy, Journal Year: 2025, Volume and Issue: 15(3), P. 608 - 608

Published: Feb. 28, 2025

Extreme maximum temperatures in summer present a significant risk to agroindustry as crops and their ecological interactions have critical thermal limits that can affect performance microorganisms-related. Gray mold disease caused by Botrytis cinerea is the most affecting worldwide. In this sense, impact of temperature on agricultural productivity well documented Northern Hemisphere; extreme infection rate B. Central Chile limited. This study analyzes historical climate data from January February between 1951 2023 for cities Santiago, Talca, Chillán, Los Ángeles. The aim was examine trends (EMTs) develop simple model estimate cinerea. Linear trend analyses were conducted, analysis probability occurrence. Additionally, five-year averages calculated, generic presented assess effects warming rate. shows positive growth February, with projections 2024, 2025, 2026 at 70%, 80%, respectively. showed increase among all stations, Chillán Ángeles recording higher increases than Santiago Talca. Projections suggest near 40–41 °C. exceeded 37 °C 2016–2020 period, highest values during analyzed time frame. Trends 2021–2026 indicate upper above 38 These trends, combined dry summers, could severity infections modify optimal conditions pathogen. results changes reduce fruit Chile, theoretical approach proposed predictive tools facilitate assessment environment.

Language: Английский

Citations

0

Predicting adaptation and evolution of plasticity from temporal environmental change DOI Creative Commons
Cristóbal Gallegos, Luis‐Miguel Chevin, Kathryn A. Hodgins

et al.

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 16(1), P. 84 - 96

Published: Nov. 22, 2024

Abstract Environmental change can drive evolutionary adaptation and determine geographic patterns of biodiversity. Yet at a time rapid environmental change, our ability to predict its impacts is incomplete. Temporal in particular, involves combination major components such as abrupt shift, trend, cyclic noise. Theoretical predictions exist for isolated components, but knowledge gaps remain regarding their joint impacts. We extend classic theory develop model the evolution tolerance by an underlying developmentally plastic trait, response temporal change. retrieve synthesise earlier responses generate new changing simultaneously. Notably, we show how different forms predictability emerging from interplay stochastic (noise) lag between development selection shape predictions. then illustrate utility generating testable plasticity when parameterised with real series data. Specifically, parameterise daily sea‐surface temperature global marine hotspot southern Australia, use simulations thermal tolerance, differences this region. By synthesising on providing insights into effects framework, embedded Shiny app, offer path better biological climate

Language: Английский

Citations

2