The Vegetation–Climate System Complexity through Recurrence Analysis

Abstract

Multiple studies revealed that pasture grasslands are a time-varying complex ecological system. Climate variables regulate vegetation growing, being precipitation and temperature the most critical driver factors. This work aims to assess the response of two different Vegetation Indices (VIs) to the temporal dynamics of temperature and precipitation in a semiarid area. Two Mediterranean grasslands zones situated in the center of Spain were selected to accomplish this goal. Correlations and cross-correlations between VI and each climatic variable were computed. Different lagged responses of each VIs series were detected, varying in zones, the year’s season, and the climatic variable. Recurrence Plots (RPs) and Cross Recurrence Plots (CRPs) analyses were applied to characterise and quantify the system’s complexity showed in the cross-correlation analysis. RPs pointed out that short-term predictability and high dimensionality of VIs series, as well as precipitation, characterised this dynamic. Meanwhile, temperature showed a more regular pattern and lower dimensionality. CRPs revealed that precipitation was a critical variable to distinguish between zones due to their complex pattern and influence on the soil’s water balance that the VI reflects. Overall, we prove RP and CRP’s potential as adequate tools for analysing vegetation dynamics characterised by complexity.

Assessment of Drought Indexes on Different Time Scales: A Case in Semiarid Mediterranean Grasslands

“…Vegetation indexes are an effective indicator of grassland cover. Their response is highly interrelated with climate and agricultural conditions [62,63]. In fact, multiple authors [64,65] have reported a clear relationship between grasslands vegetation and water availability.…”

Vegetation dynamic patterns of arid rangelands : a multifractal approach

“…Therefore, depending on the goal of the study, such as differentiating soil from biomass or differentiating the presence of perennial or annual plants, soil-adjusted VI or other indices may be better suited. The selection of best fit should be made on a case basis, especially in the most extreme areas (Almeida-Ñauñay et al, 2021;Fern et al, 2018). Nevertheless, NDVI has been proven well suited to assess general cover monitoring, regardless of soil or vegetation variations (Al-Bakri and Suleiman, 2004;Klisch and Atzberger, 2016;Peters et al, 2002;Ünal et al, 2014;Wallace et al, 2006;Yagci et al, 2014).…”