A Framework for Assessing Climate Change Impacts on Alpine Plant Adaptation

Thesis Abstract

Climate change poses a significant threat to alpine ecosystems, with rising temperatures, altered precipitation patterns, and increased frequency of extreme weather events threatening the survival and resilience of native alpine plants. Despite the recognized importance of these ecosystems for biodiversity conservation, water regulation, and ecological stability, there remains a critical gap in understanding how alpine plant species adapt to rapid climatic shifts and how these adaptations can be systematically assessed and predicted. This study aims to develop a comprehensive framework for evaluating the impacts of climate change on alpine plant adaptation processes, thereby guiding conservation strategies and ecological management practices. The specific objectives of the research include (1) to identify key physiological and phenological traits associated with plant adaptability in alpine environments; (2) to analyze the relationships between climatic variables and plant trait variations; (3) to formulate an integrative model that encapsulates adaptive mechanisms under changing climatic conditions; and (4) to validate the proposed framework through empirical data collected across multiple alpine sites. A mixed-methods research design was adopted, combining quantitative and qualitative approaches to attain a holistic understanding of plant responses to climatic stressors. The study targeted a population of 15 dominant alpine plant species across five diverse alpine regions in the European Alps, with a total sample size of 300 individual plants—30 per species at each site—selected through stratified random sampling to ensure representativeness. Data collection involved field measurements of plant physiological traits (e.g., water-use efficiency, leaf margin morphology), phenological records, and microclimate data obtained via automated weather stations. Additionally, remote sensing data on vegetation dynamics were integrated to monitor broader spatial trends. Instrument validity and reliability were ensured through calibration of instruments and pilot testing of protocols. Data analysis employed multivariate statistical techniques including principal component analysis (PCA) to identify trait syndromes, multiple regression analysis to examine the influence of climatic factors on plant traits, and structural equation modeling (SEM) to develop and validate the adaptive framework. Thematic analysis was used to analyze qualitative interview data from ecologists and local stakeholders, providing contextual insights into adaptation processes. Expected findings include identification of key adaptive traits that confer resilience amid climate variability, quantification of climatic thresholds affecting plant performance, and validation of the integrative framework integrating physiological, phenological, and ecological data. The study anticipates that the model will demonstrate strong predictive capacity for plant adaptation under different climate scenarios, emphasizing trait-based indicators for early detection of vulnerability. This research significantly contributes to the existing body of knowledge by providing a standardized framework for assessing alpine plant resilience, incorporating multi-scale data analysis, and linking ecological responses to climate dynamics through theoretically grounded pathways informed by the Stress-Gradient Hypothesis and the Niche Theory. The integrated framework offers practical tools for conservation practitioners and policymakers to prioritize species and habitats most at risk while guiding restoration efforts. The main conclusion underscores the importance of trait-based assessments in predicting ecological outcomes of climate change in alpine ecosystems. Key recommendations include the integration of the framework into existing biodiversity monitoring programs, the adoption of adaptive management strategies prioritizing climate-resilient species, and further research to refine the model with longitudinal data. Future studies should explore the applicability of the framework across different alpine regions globally and evaluate its utility in informing climate adaptation policies and conservation planning at broader scales.