Climatic and Anthropogenic Drivers of Forest Succession in the Iberian Pyrenees during the Last 500 Years: A Statistical Approach

Anticipating future successional forest trends in the face of ongoing global change is an essential conservation target. Mountain forests are especially sensitive to environmental shifts, and their past responses to climatic and anthropogenic (external) drivers may provide a basis for improving predictions of future developments. This paper uses independent high-resolution palynological and paleoclimatic reconstructions to statistically analyze the long-term effects of external drivers on regional forest succession in the central Iberian Pyrenees during the last 500 years. The statistical methods used are Gaussian response analysis, cluster analysis, rate-of-change analysis, principal component analysis, and redundancy analysis. The dominant taxa of these forests (Quercus, Betula, Pinus) showed significant relationships with summer temperature, summer drought, and autumn precipitation. Immediate and delayed (by two or more decades) responses of these trees to climatic drivers were identified. Regional succession showed a closed path, starting at the end points around the attraction domain of pine-dominated forests. This trajectory was determined by a trend toward anthropogenic forest clearing (16th to 18th centuries) and a reverse trend of natural forest recovery (18th to 20th centuries). Forest clearing was due to burning, facilitated by drought, and was followed by the expansion of cropping and grazing lands. Forest recovery was fostered by reduced human pressure and rising temperatures. The statistical approach used in this work has unraveled ecological relationships that remained unnoticed in previous works and would be important for predicting future successional trends under changing climates. The reported response lags of individual taxa to climatic drivers may complicate the establishment of reliable ecological relationships and should be addressed in future studies.Spanish Ministry of Economy and Competitiveness, projects CGL2012-3665 and CGL2017-85682-R.1. Introduction 2. Study Site 2.1. Location and Climate 2.2. Regional Vegetation 3. Material and Methods 3.1. Raw Data 3.2. Statistical Methods 4. Results 4.1. Individual Responses of Tree Taxa to External Drivers 4.2. Forest Assemblages and Rate-of-Change Analysis 4.3. Successional Trends 4.4. Synthetic Successional-Environmental Analysis 5. Discussion and Conclusions 6. Final Remarks Author Contributions Funding Data Availability Statement Acknowledgments Conflicts of Interest Reference