# Assessment of grassland sensitivity to drought in the Massif Central region using remote sensing

Donald Luna, Julien Pottier, Catherine Picon-Cochard

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Donald Luna, Julien Pottier, Catherine Picon-Cochard. Assessment of grassland sensitivity to drought in the Massif Central region using remote sensing. 29th General Meeting of the European Grassland Federation, Jun 2022, Caen (en ligne), France. 27, Wageningen Academic Publishers, pp.427-429, 2022, Grassland at the heart of circular and sustainable food systems., 978-2-7380-1445-0. hal-04211407

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# Assessment of grassland sensitivity to drought in the Massif Central region using remote sensing

Luna D., Pottier J. and Picon-Cochard C.

Université Clermont Auvergne, INRAE -VetAgro Sup, UREP, 63000 Clermont-Ferrand, France

## Abstract

Drought is a natural phenomenon that is expected to increase in frequency and duration with climate change, leading to more intense disturbance of ecosystems like grasslands. Moreover, sensitivity of grasslands to drought is expected to differ across landscapes. To assess and explain such variation in sensitivity, knowledge drawn from several grasslands and local parameters must be considered. Our study focused on 143 permanent grasslands in the Massif Central Region of Metropolitan France. With the use of satellite remote sensing, we quantified the relationship between vegetation index anomalies and a modified version of the Standardized Precipitation-Evapotranspiration Index (mSPEI) to acquire grassland sensitivity values. These anomalies provide estimates of the historical long-term fluctuations of grassland vegetation reflectance to climatic water balance between 1985 and 2019. A model selection procedure was used to determine whether the derived sensitivities can be attributed to explanatory variables such as vegetation diversity, pedoclimatic conditions, or management practices. Then a variance partitioning of the included explanatory variables was performed. Our results highlight that soil available water capacity, time of first use, and plant functional diversity all had key influences on the sensitivity of grasslands to drought within those parcels selected in the region.

**Keywords:** drought, mSPEI, grassland response, sensitivity, remote sensing, vegetation index

## Introduction

The Intergovernmental Panel for Climate Change has projected an overall increasing trend in the global temperature due to climate change, together with more frequent and longer extreme climatic events (IPCC, 2021). Among these events, droughts have large-scale impacts on ecosystems like grasslands. However, the grassland responses or sensitivities to drought are expected to vary across landscapes depending on grassland local properties. A better understanding of grassland sensitivity to drought, over landscapes outside of controlled experiments, may help promote agricultural practices supporting grassland stability. To this end, remote-sensing technologies offer new opportunities for fine-resolution monitoring of grasslands (Reinermann et al., 2020). This study aims to assess the variability of grassland sensitivity to drought over the Massif Central using remotely sensed vegetation dynamics, and highlights key drivers of sensitivity, including pedoclimate, biodiversity, and agricultural management.

## Materials and methods

We analysed the sensitivity to drought of 394 plots from 143 permanent grassland parcels distributed over the Massif Central (AOP field surveys, 2008-2019) using satellite-based remote sensing. To do so, we first mapped the severity of drought events from 1985 to 2019, with a modified version of the Standardized Precipitation-Evapotranspiration Index (mSPEI; Begueria et al., 2014) computed from the daily weather data provided by the *Système d'Analyse Fournissant des Renseignements Atmosphériques à la Neige* (SAFRAN) meteorological data of France. Then, we derived standardized vegetation index (VI) anomalies over the same period. These anomalies are values of the departure of VI from their long-term daily mean. The VI time-series were calculated from Landsat images from 1985 to 2019. Finally, we quantified grassland sensitivity to drought, during the growing season (March to November), as the regression slope between the standardized VI anomalies and mSPEI (Ji and Peters, 2003). From 25 computed VIs and based on a Principal Component Analysis (PCA), we selected the Normalized Multi-
band Drought Index (NMDI), which was developed for monitoring soil and vegetation moisture (Wang and Qu 2007). To better understand the drivers of grassland sensitivity to drought, we used a statistical model selection procedure with drought sensitivity as the response variable. The explanatory variables, derived from the field surveys and the Copernicus Land Monitoring services' high-resolution digital elevation model, pertain to three categories: (1) management practices; (2) vegetation diversity, denoted by the taxonomic and functional indices plus the community weighted mean of traits related to growth, phenology, and reproduction; and (3) pedoclimatic conditions, depicted by soil physical and chemical properties (including soil available water capacity or AWC), terrain wetness index and aspect. Lastly, we performed a variance partitioning of the model explanatory variables to quantify their relative influences.

## Results and discussion

In our study we found a large variation in satellite-sensed drought sensitivities across the Massif Central grasslands (Figure 1) with 35.62% coefficient of variation. The model selection procedure led to a final sensitivity model with seven explanatory variables and an R-squared of 0.52 (Table 1). According to the variance partitioning (Figure 2), pedoclimatic factors explained the largest part (35%) of variation. From these factors, AWC had a strong negative effect to drought sensitivity. As expected, higher soil water retention capacity mitigates meteorological drought. In contrast, a south-facing slope promoted sensitivity most likely due to higher solar radiation exposure (local underestimation of mSPEI) compared to north-facing slopes. Management factors explained 23% of the total variation. From the model, delayed first uses resulted in higher drought sensitivity. Such factors have been understudied so far, hindering a clear understanding of effect on grassland drought sensitivity. Grasslands that were preferentially grazed (type of use) showed higher drought sensitivity than mown grasslands. This is consistent with the field experiment by Deléglise et al. (2015), where drought conditions in grazing plots led to lower annual biomass than in mowing plots. The mean number of uses per year also increased sensitivity to drought. When grasslands are frequently used throughout the growing season, stored carbohydrates, which are necessary for plant regrowth, may become limited during drought events (Fulkerson and Donaghy, 2001). Our model also underlined the role of plant functional diversity (9%), which is mostly shared

<figure><img src="image_2.png" /><figcaption>Figure 1. Spatial (top) and statistical (bottom) distributions of sensitivities to drought in the Massif central. Sensitivity is the slope of the linear relationship of the standardized (std) VI anomaly and mSPEI.</figcaption></figure>

<table><caption>Table 1. Final sensitivity model (R-squared is 0.5242) and variance partitioning results.</caption><thead><tr><th>Category</th><th>Explanatory variable</th><th>Beta coefficient</th><th>t value</th><th>Pr(>|t|)</th></tr></thead><tbody><tr><td rowspan="2">Pedoclimate</td><td>AWC (topsoil)</td><td>-0.5396292</td><td>-8.603</td><td>2.27e-14</td></tr><tr><td>South-facing slope (aspect)</td><td>0.2355297</td><td>3.656</td><td>0.000372</td></tr><tr><td rowspan="3">Management</td><td>Time of first use (as GDD)</td><td>0.5163540</td><td>7.081</td><td>8.23e-11</td></tr><tr><td>Type of use (grazing or mowing)</td><td>0.2936155</td><td>3.812</td><td>0.000213</td></tr><tr><td>Mean number of uses</td><td>0.1295399</td><td>1.853</td><td>0.066173</td></tr><tr><td rowspan="2">Diversity</td><td>FDis: plant growth form</td><td>-0.1600510</td><td>-2.379</td><td>0.018819</td></tr><tr><td>CWM: plant height</td><td>-0.1416316</td><td>-1.978</td><td>0.050051</td></tr></tbody></table>
<figure><img src="image_3.png" /><figcaption>Figure 2. Variance partitioning of the main variable categories (R package: vegan).</figcaption></figure>

with the pedoclimatic and management factors. We found that more diverse plant growth strategies promoted lesser drought sensitivity, as already shown in experimental studies (Weisser, et al., 2017). In addition, grassland plots with taller plants, or higher CWM height, exhibited lower drought sensitivity, as confirmed by Nunes et al. (2017).

## Conclusions

Using remote sensing, we assessed drought sensitivities on a wide range of grasslands across the Massif Central region. These sensitivities were highly variable, but the majority of the variation could be explained by pedoclimatic, diversity and management factors. AWC had the largest influence. We also underlined the role of diversity shared with pedoclimate and management on grassland drought sensitivity, which is in line with previous grassland-drought field experiments. We further assessed the relative importance of these drivers in real agricultural systems.

## References

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- Deléglise C., Meisser M., Mosimann E., Spiegelberger T., Signarbieux C., Jeangros B. and Buttler A. (2015) Drought-induced shifts in plants traits, yields and nutritive value under realistic grazing and mowing managements in a mountain grassland. *Agriculture, Ecosystems and Environment* 213, 94-104. https://doi.org/10.1016/j.agee.2015.07.020

- Fulkerson W. and Donaghy D. (2001) Plant-soluble carbohydrate reserves and senescence - Key criteria for developing an effective grazing management system for ryegrass-based pastures: A review. *Animal Production Science* 41, 261-275. https://doi.org/10.1071/EA00062

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- AOP (nd) Pôle Fromager AOP Massif Central. Prairies Naturelles du Massif Central: Plus de 10 ans de co-construction de R&D! Aurillac, France. Available at: http://pole-fromager-aop-mc.org/prairies-du-massif-central/

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