Geology ReportsSearch

USGS · 70278777

Design, construction and application of an automated thermal chamber to determine critical thermal maxima in small anurans

Abstract

Critical thermal maximum (CTMax) is a thermal threshold useful for understanding physiological boundaries and predicting anuran vulnerability to climate warming. Given the value of this metric, a comprehensive review of the literature on CTMax protocols (1962-2025) revealed widespread methodological inconsistencies and rare verification of ramping rate accuracy, essential to gauge the reliability of estimates and facilitate comparisons among studies. We engineered an inexpensive (<300 USD) automated CTMax chamber incorporating dual thermocouples, a programmable proportional integral derivative (PID) controller, and real-time software monitoring to address these deficiencies. Performance validation across eight trials demonstrated alignment between programmed and observed temperature ramping rate (0.40 vs. 0.39 °C/min; Z = 1.58, P > 0.05). As a proof-of-concept, we used the proposed system to generate CTMax estimates of six species of Eleutherodactylus in Puerto Rico, including first reports for E. brittoni, E. cochranae, E. wightmanae, and E. juanariveroi. CTMax values ranged from 36.30°C ± 0.52 (E. wightmanae) to 42.10°C ± 0.66 (E. cochranae), with warming tolerances ranging from 15.00°C ± 0.63 to 18.18°C ± 0.73. Our design provides an accurate, replicable, and ethical approach for CTMax measurement and enhances the capacity to assess small amphibian vulnerability to global warming.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rafael Chaparro, Ana C. Rivera-Burgos, Jaime A. Collazo, Mitchell J. Eaton, Adam J. Terando, Eloy Martinez. 2026. Design, construction and application of an automated thermal chamber to determine critical thermal maxima in small anurans. https://doi.org/10.2139/ssrn.6143998

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Estimating the probability of export restrictions to inform mineral criticality

As demand for advanced technologies rises, mineral commodities will increase in geopolitical importance. To assess risks associated with mineral commodity supply chain disruptions, governmental agencies and others have developed "criticality" assessments, with criticality described using the economic impact and probability of supply chain disruptions. In previous work, subjective supply risk indicators were developed to approximate this probability, typically combining several factors such as supply diversity and political stability of trading partners, where indicator weightings can substantially impact results. This work explicitly quantifies trade barrier probability using an ensemble of several machine learning classifiers, with probability estimates informed by exogenous variables such as prior trade barrier implementation and global export dominance. Major differences in the high-probability countries and commodities are observed across models, but the ensemble method highlights Indonesia, China, Tanzania, and the United States as particularly high risk. This approach enables a direct, quantitative, objective approach to assessing trade barrier probability, enhancing risk identification and prioritization for policymakers.

SSRN