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The Vegetation-Climate System Complexity through Recurrence Analysis. | LitMetric

The Vegetation-Climate System Complexity through Recurrence Analysis.

Entropy (Basel)

Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Escuela Técnica Superior de Ingeniería Agronómica Alimentaria y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Senda del Rey, 13, 28040 Madrid, Spain.

Published: April 2021

AI Article Synopsis

  • - This study explores how climate factors like temperature and precipitation influence the growth of vegetation in semiarid grassland areas in central Spain, focusing on two different Vegetation Indices (VIs).
  • - Researchers found variations in how these VIs responded to temperature and precipitation over time, depending on the specific grassland zone and season, highlighting the complexity of these ecological systems.
  • - The analysis utilized Recurrence Plots (RPs) and Cross Recurrence Plots (CRPs) to reveal that precipitation plays a significant role in vegetation dynamics, showcasing the tools’ effectiveness in studying complex ecological patterns.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145696PMC
http://dx.doi.org/10.3390/e23050559DOI Listing

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