Response of forests in the Sierra Gorda of Queretaro to meteorological variability in the 21st century through remote sensing data and time series analysis

Remote Sensing (RS) is the most useful tool for monitoring forests at different temporal and spatial scales. The availability of long time series from RS indices, such as the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), and meteorological data makes time series analysis an excellent methodology for studying forest intra-annual or interannual dynamics and their response to meteorological variability. RS is widely used in developed countries, however, this tool is essential for a sustainable management of the ecosystems also in developing countries of Iberoamerica. The Sierra Gorda Biosphere Reserve is one of the most important forested regions in Mexico, located in the center of the country, mostly in the state of Querétaro. The overall objective of this work is to study forest and shrubland dynamics of the Sierra Gorda in the state of Querétaro and their response to meteorological variability through time series analysis of remote sensing data of the last 23 years. Spectral indices (NDVI and EVI) have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS, spatial resolution = 250 m), precipitation has been obtained from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) (spatial resolution=5566 m), and temperature from DAYMET-V4 (spatial resolution=1 km).  Firstly, a univariable time series analysis of spectral indices, precipitation and temperature are made by means of the Buys-Ballot tables, i.e., average year, to study the intra-annual forest dynamics and then, using the autocorrelation function and the periodogram the interannual dynamics are assessed. Finally, the causality between spectral indices and meteorological data are studied by Granger causality tests. Preliminary results shows that spectral indices monitor adequately the different phenological dynamics of the different main forests and shrublands in the Sierra Gorda. Granger causality tests shows the different response of vegetation to precipitation and temperature. In conclusion, the different response of vegetation to meteorological variability is well represented by the dynamics of spectral indices. In the present, RS time series analysis is a novel technique for making a forest sustainable management and specifically, it allows determining the presence of trends, seasonality, cycles, or structural changes in the intra-annual or interannual forest dynamics.