<b>The use of physiological, behavioural and morphological data to model the impact of climate change</b>

Here's a detailed description of the datasets used in the thesis:<b>Physiological Responses Dataset:</b><b>Variables:</b> This dataset includes measurements related to metabolic rates, evaporative water loss (EWL), body temperatures (Tb), and air temperatures (Ta).<b>Methods:</b> 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.<b>Analysis:</b> Data were analyzed using Expedata software and statistical models in R to assess metabolic efficiency, heat dissipation mechanisms, and thermoneutral zones (TNZ).<b>Behavioural Responses Dataset:</b><b>Variables:</b> Captured data on time-activity budgets (foraging, inactivity, movement, territorial behaviors), heat dissipation behaviors (e.g., panting, wing-spreading), and responses to solar radiation.<b>Methods:</b> Behavioral observations were conducted at different times of day (morning, midday, afternoon) across two years using VHF transmitters and color rings for identification.<b>Analysis:</b> GLMM models in R were used to analyze how behaviors varied with temperature and solar radiation, and how they differed between males and females.<b>Population Biology and Habitat Dataset:</b><b>Variables:</b> Population size estimates, home range sizes, habitat suitability, and distribution patterns within Black Mountain Mine Conservation Area (BMMCA).<b>Methods:</b> Telemetry data from VHF transmitters to track movements and home ranges, habitat surveys using transects, and population density estimates using distance sampling techniques.<b>Analysis:</b> 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.<b>Climate Impact Modeling Dataset:</b><b>Variables:</b> Predictive models integrating physiological responses (e.g., evaporative cooling efficiency), behavioral responses (e.g., thermoregulatory behaviors), and climate scenarios (e.g., RCP 8.5).<b>Methods:</b> Process-based modeling to simulate the impacts of global heating on lethal dehydration and hyperthermia risks.<b>Analysis:</b> The dataset evaluated the potential frequency of lethal hyperthermia events under future climate scenarios, emphasizing the risks posed by increasing temperatures.<b>Longitudinal Data and Historical Trends:</b><b>Variables:</b> Long-term trends in temperature, habitat suitability, and population dynamics.<b>Methods:</b> Historical climate data analysis (e.g., temperature trends since the 1980s), comparison of past and current habitat suitability using remote sensing data.<b>Analysis:</b> 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.

本论文所使用的数据集详细说明如下：

**生理响应数据集（Physiological Responses Dataset）**
**变量：** 该数据集包含与代谢率、蒸发失水（evaporative water loss, EWL）、体温（body temperatures, Tb）以及气温（air temperatures, Ta）相关的测量数据。
**方法：** 采用开放式流通式呼吸测定法测量代谢率与二氧化碳产生量；分别使用热敏电阻（Thermistors）与PIT标签（PIT tags）测量气温与体温。
**分析：** 利用Expedata软件及R语言中的统计模型对数据进行分析，以评估代谢效率、散热机制以及热中性区（thermoneutral zones, TNZ）。

**行为响应数据集（Behavioural Responses Dataset）**
**变量：** 该数据集涵盖了时间-活动预算（包括觅食、静息、移动、领域行为）、散热行为（如喘息、展翅）以及对太阳辐射的响应相关的采集数据。
**方法：** 在两年内的不同时段（清晨、正午、午后）开展行为观测，使用甚高频（VHF）发射器与彩色环标记个体以进行识别。
**分析：** 采用R语言中的广义线性混合模型（Generalized Linear Mixed Model, GLMM）分析行为如何随温度与太阳辐射变化，以及雌雄个体间的行为差异。

**种群生物学与栖息地数据集（Population Biology and Habitat Dataset）**
**变量：** 包含黑山矿区保护区（Black Mountain Mine Conservation Area, BMMCA）内的种群规模估算值、家域面积、栖息地适宜性以及分布格局相关数据。
**方法：** 通过甚高频（VHF）发射器的遥测数据追踪种群移动与家域范围，采用样线法开展栖息地调查，使用距离抽样技术估算种群密度。
**分析：** 利用核密度估计（Kernel Density Estimates, KDE）计算家域面积；结合Sentinel-2卫星数据与Biomod2模型模拟栖息地适宜性；通过种群密度估算值外推得到该物种的总种群规模。

**气候影响建模数据集（Climate Impact Modeling Dataset）**
**变量：** 整合了生理响应（如蒸发冷却效率）、行为响应（如体温调节行为）以及典型浓度路径8.5（Representative Concentration Pathway 8.5, RCP 8.5）等气候情景的预测模型数据。
**方法：** 采用基于过程的建模方法模拟全球变暖对致死性脱水与热射病风险的影响。
**分析：** 该数据集评估了未来气候情景下致死性热射病事件的潜在发生频率，重点强调了气温升高所带来的风险。

**纵向数据与历史趋势（Longitudinal Data and Historical Trends）**
**变量：** 包含气温、栖息地适宜性以及种群动态的长期趋势数据。
**方法：** 分析历史气候数据（如1980年代以来的气温变化趋势），利用遥感数据对比过去与当前的栖息地适宜性。
**分析：** 通过统计对比分析，以理解栖息地可利用性与种群动态随时间的变化情况。

总体而言，本论文结合实证数据、野外观测与多种建模手段，全面评估了红百灵（red larks）对气候变化的生理、行为与生态响应。上述数据集可为该物种在环境变化下的适应策略、脆弱性以及保护启示提供科学见解。