Methodology for Studying Insect Thermal Tolerance Across Peruvian and Kenyan Elevational Gradients

Investigating Insect Thermal Limits Across Elevational Gradients: A Detailed Methodology

This document outlines the detailed methodology employed in a study investigating insect thermal limits along elevational gradients in Peru and Kenya.

Study Areas

The research was conducted across two distinct elevational gradients, one in the Neotropics and one in the Afrotropics, to capture diverse environmental conditions and insect communities.

The Peruvian study occurred along an elevational gradient from 245 to 3,588 meters above sea level (masl) within the Kosñipata valley of the Andes. This region is characterized by continuous wet rainforest and cloud forest. The climate experiences distinct wet, dry, and austral spring seasons. Mean annual temperatures range from 24.3 °C in lowlands to 6.7 °C at 3,600 masl, accompanied by high precipitation exceeding 1,500 mm annually. Researchers utilized 26 plots, some situated within Manú National Park and others aligning with existing ABERG project plots.

In Kenya, the study spanned an elevational gradient from 11 masl at Watamu to 3,450 masl at Mount Kenya, encompassing a wide array of diverse habitats. The climate varies significantly, from semi-arid in the lowlands to humid at higher elevations, featuring two distinct rainy seasons. Mean annual temperatures range from 26.2 °C at the lowest plot to 8.9 °C at the highest. A total of fifteen study plots were carefully selected across this gradient.

Insect Collection

Insects from major orders, including Coleoptera, Diptera, Hymenoptera, Lepidoptera, Hemiptera, and Orthoptera, were collected using sweep nets. A total of 4,690 individuals were collected in the Neotropics across three seasons, while 3,164 insects were gathered in the Afrotropics during one season. Live insects were promptly transported to field stations for same-day thermal tolerance measurements. The collection strategy focused on achieving broad taxonomic breadth rather than concentrating on individual species.

Measuring Thermal Limits

Critical thermal limits (CTmin and CTmax) were precisely measured by exposing individual insects to decreasing or increasing temperatures using a programmable thermoblock. Insects were first acclimatized at 28 °C for 10 minutes. Subsequently, temperatures were systematically changed by 1 °C every 2 minutes, corresponding to a rate of 0.5 °C min-1.

The temperature at which mobility was visibly lost was defined as the thermal limit for each insect.

Post-test, all insects were preserved in 96% ethanol for subsequent genetic barcoding.

To ensure data reliability, observer bias was rigorously tested using lab-reared ants, demonstrating no significant difference in mean CTmax among four different observers. Generalized additive models were then applied to investigate the patterns of critical thermal limits along the elevational gradients.

Thermal tolerance ranges were meticulously calculated, and thermal safety margins were determined by subtracting plot-specific mean annual or daily maximum air temperatures from the measured CTmax values.

Plastic responses to temperature stress were also examined. Subsets of insects were pre-exposed to either heat shocks (40 °C or 35 °C) or cold shocks (14 °C) for 10 minutes prior to standard CT measurements. Effect calculations aimed to quantify any increased thermal tolerance observed post-shock, providing insights into short-term physiological adjustments.

Insect Identification and Phylogeny

All collected insects underwent morphological sorting and were delimited into species-like units, known as Operational Taxonomic Units (OTUs), through individual DNA barcoding. This process involved COI gene sequencing, performed at the Canadian Centre for DNA Barcoding (CCDB). Sequences and associated data were uploaded to the Barcode of Life Data System (BOLD).

After excluding contaminants and short sequences, 4,300 barcoded individuals, representing 2,330 unique OTUs, were included in the phylogenetic analyses.

A comprehensive phylogeny was constructed using an insect family-level backbone tree, enriched with the obtained DNA sequences. Separate subtrees were calculated for each family. Ancestral trait values of thermal tolerances were reconstructed, and phylogenetic signals (Pagel’s lambda, Blomberg’s K) were rigorously tested. Phylogenetic regression models, including Brownian motion and Ornstein–Uhlenbeck models, were employed to disentangle adaptive evolution from mere phylogenetic relatedness, with model performance compared using the Akaike information criterion.

Protein Stability Prediction

The DeepSTABp deep learning model was utilized to predict the thermal stability (melting points, Tm) of proteins. Genomes from 677 insect species were downloaded from InsectBase 2.0. For each species, 1,000 proteins were randomly selected for analysis. Differences in predicted Tm across insect orders and families were statistically tested using mixed-effect models. A linear model was then applied to investigate the relationship between the 25% quantile of Tm for temperature-sensitive proteins and the mean CTmax of families, offering insights into molecular underpinnings of thermal tolerance.

Climate Data

Comprehensive climate data were crucial for the study. In Neotropical plots, air and soil temperatures were directly recorded using TMS-4 loggers and iButton sensors. For East African plots, shaded air temperatures were modeled using the NicheMapR tool.

Additional climate data, including mean annual air temperature and mean daily maximum/minimum air temperatures, were extracted from the CHELSA database for all study plots. Surface temperatures were derived from the ECOSTRESS sensor on the International Space Station, further enriched by additional measurements from a 5 km buffer around each plot.

Heat Coma Models

Dynamic CT values were converted to static CT values to calculate heat coma times (tcoma) for both current and predicted future environmental temperatures, employing a thermal sensitivity coefficient of z=3. Tcoma was calculated for average, 25% quartile, and 10% quantile (representing the most heat-sensitive) CTmax values derived from lowland insects.

Future climate projections for the period 2071–2100 were based on SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios, utilizing GFDL-ESM4 climate model predictions of bio5 from the CHELSA database.

Anomalies were added to current field-measured or modeled temperatures to estimate future air and surface temperatures. Finally, the percentage of critical temperatures leading to heat coma within an 8-hour period was calculated, offering vital insights into future insect vulnerability.

Inclusion and Ethics Statement

All fieldwork conducted in Peru and Kenya adhered to stringent ethical guidelines and was performed in close collaboration with local research institutions, specifically the Universidad Peruana Cayetano Heredia, Museo de Historia Natural, and the University of Embu. All necessary permits were duly obtained from the respective authorities. Local scientists were actively involved in every stage of the research, from study design and data collection to manuscript preparation, fostering collaborative and equitable scientific practice.