The terrestrial biosphere plays a crucial role in Earth's climate system, influencing energy, water, and carbon cycles, while supporting biodiversity and ecosystem services essential for human sustainability. Predicting how ecosystems will respond to climate change and their feedback effects remains a significant challenge [1]. One major difficulty arises from the complexity of the systems involved, with non-linear processes and interactions occurring across varying timescales. Vegetative systems, particularly forests, exhibit processes that span from seconds to decades, indicating their persistence [2]. Many of these dynamics are driven by weather patterns, which are short-term processes. Soil moisture (SM), a key ecohydrological variable, has been shown to exhibit long-term persistence and plays a critical role in these interactions [3]. Modeling studies have demonstrated that SM can improve seasonal climate predictions [4]. Therefore, investigating the persistence of soil moisture-plant interactions is crucial for understanding long-term changes in the terrestrial biosphere.
In this study, we examine the coupled non-linear persistence between remote sensing derived SM and vegetation greenness using kernel Detrended Fluctuation Analysis (kDFA), a novel multivariate non-linear extension of DFA [5]. This method allows us to explore the non-linear interactions between these variables across multiple scales within a persistence space. By doing so, we can quantitatively assess how moisture influences persistence in vegetative systems. Additionally, we investigate the relationships between SM-vegetation persistence, forest greenness, and other eco-physiological proxies using a non-linear regression algorithm. First, we perform a spatial analysis, followed by a temporal analysis using a moving window approach. Our goal is not only to assess how SM-forest interactions evolve over time, but also to link this persistence to ecosystem stress and identify areas vulnerable to hot and dry conditions as drought-heat events increase in frequency and intensity [6].
References:
1. Overpeck, J., Whitlock, C., Huntley, B. (2003). Terrestrial Biosphere Dynamics in the Climate System: Past and Future. In: Alverson, K.D., Pedersen, T.F., Bradley, R.S. (eds) Paleoclimate, Global Change and the Future. Global Change — The IGBP Series. Springer, Berlin, Heidelberg.
2. Williams, et al. Sub-Seasonal Forest Carbon Dynamics Lose Persistence Under Extremes. Submitted.
3. Orth, R., and Seneviratne, S.I. (2012). Analysis of soil moisture memory from observations in Europe, J. Geophys. Res., 117, D15115, doi:10.1029/2011JD017366.
4. Besnard, S., et al. (2019). Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests. PloS one 14.2.
5. Williams et al. Kernel Detrended Fluctuation Analysis. Submitted.
6. Seneviratne, S.I., et al. (2021). Weather and Climate Extreme Events in a Changing Climate. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the IPCC. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1513–1766.