The use of physiological, behavioural and morphological data to model the impact of climate change

Here's a detailed description of the datasets used in the thesis:

1. Physiological Responses Dataset:
2. • Variables: This dataset includes measurements related to metabolic rates, evaporative water loss (EWL), body temperatures (Tb), and air temperatures (Ta).
   • Methods: Open flow-through respirometry was used to measure metabolic rates and CO2 production. Thermistors and PIT tags were employed to measure Ta and Tb respectively.
   • Analysis: Data were analyzed using Expedata software and statistical models in R to assess metabolic efficiency, heat dissipation mechanisms, and thermoneutral zones (TNZ).
3. Behavioural Responses Dataset:
4. • Variables: Captured data on time-activity budgets (foraging, inactivity, movement, territorial behaviors), heat dissipation behaviors (e.g., panting, wing-spreading), and responses to solar radiation.
   • Methods: Behavioral observations were conducted at different times of day (morning, midday, afternoon) across two years using VHF transmitters and color rings for identification.
   • Analysis: GLMM models in R were used to analyze how behaviors varied with temperature and solar radiation, and how they differed between males and females.
5. Population Biology and Habitat Dataset:
6. • Variables: Population size estimates, home range sizes, habitat suitability, and distribution patterns within Black Mountain Mine Conservation Area (BMMCA).
   • Methods: Telemetry data from VHF transmitters to track movements and home ranges, habitat surveys using transects, and population density estimates using distance sampling techniques.
   • Analysis: Kernel Density Estimates (KDE) were used to calculate home ranges, while Biomod2 with Sentinel-2 satellite data modeled habitat suitability. Population density estimates were extrapolated to estimate the species' total population.
7. Climate Impact Modeling Dataset:
8. • Variables: Predictive models integrating physiological responses (e.g., evaporative cooling efficiency), behavioral responses (e.g., thermoregulatory behaviors), and climate scenarios (e.g., RCP 8.5).
   • Methods: Process-based modeling to simulate the impacts of global heating on lethal dehydration and hyperthermia risks.
   • Analysis: The dataset evaluated the potential frequency of lethal hyperthermia events under future climate scenarios, emphasizing the risks posed by increasing temperatures.
9. Longitudinal Data and Historical Trends:
10. • Variables: Long-term trends in temperature, habitat suitability, and population dynamics.
    • Methods: Historical climate data analysis (e.g., temperature trends since the 1980s), comparison of past and current habitat suitability using remote sensing data.
    • Analysis: Statistical comparisons to understand changes in habitat availability and population dynamics over time.

Overall, the thesis utilizes a combination of empirical data, field observations, and modeling approaches to comprehensively assess the physiological, behavioral, and ecological responses of red larks to climate change. The datasets provide insights into the species' adaptation strategies, vulnerabilities, and conservation implications under changing environmental conditions.