Greater soil contribution to vegetation growth in dry regions than in humid regions

doi:10.21203/rs.3.rs-2441166/v1

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Greater soil contribution to vegetation growth in dry regions than in humid regions

https://doi.org/10.21203/rs.3.rs-2441166/v1

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The response of vegetation growth to soil moisture is mediated by soil properties, but how and to what extent soil properties affect the response have remained unclear. In this study, we first quantify the global patterns of soil contribution to vegetation growth by establishing a nonlinear vegetation-soil moisture response model. We find that soil properties primarily regulate the nonlinear vegetation-soil moisture response by adjusting the soil moisture optima (SMpoint), which was defined as the peak in a fitted unimodal model. The impacts of soil properties on SMpoint range from − 0.18 cm³/cm³ to 0.16 cm³/cm³. Significant soil impacts on vegetation growth can be positive or negative, depending on soil impacts on SMpoint. In dry regions (Aridity index < 0.65), by adjusting soil water use, soil properties explained 62% of the vegetation growth change on average, and the average change in vegetation growth driven by soil property impacts was only 21% of that in humid ecosystems. Linking soil properties to vegetation responses to soil moisture is important to improve our understanding of droughts and their soil determinants. The results of our study provide insights into the role of soil properties in influencing global vegetation soil water uses and a new framework to consider the impacts of soil properties in global vegetation models.

Earth and environmental sciences/Ecology/Biogeography

Earth and environmental sciences/Ecology/Ecosystem ecology

Soil properties

vegetation – soil moisture response

soil moisture optima

Soil water availability plays a critical role in constraining global vegetation growth ^{1 2} by serving as a water reservoir that is directly accessible to plant roots ³. In addition to the widely examined impacts of climate factors (i.e., temperature and vapor pressure deficit) on plant water use ^{4 5 6}, soil properties are known to impact vegetation use of soil water ^{7 8 9 10} - for example, by determining the wilting points and field capacity for plants, which are the lower and upper limits of soil water availability that plants can use ¹¹.

However, how soil properties modulate the response of vegetation growth to the gradient change in soil moisture (i.e., between the wilting point and field capacity) is still unclear, as we lack proper theories and observations to quantify the impacts ¹². In particular, since a large array of soil physical and chemical properties (i.e., texture, depth, bulk density, organic matter, pH value, and cation exchange capacity) are related to plant water uptake and growth ^{7 8}, it is challenging to distinguish their respective impacts from the covariances between the properties. In some cases, even the same soil properties are reported to have opposite impacts; for example, in the Amazon and Australia, there was observational evidence showing that soils with high clay content tend to make forest growth more sensitive to water stresses compared to forests on soils with low clay content ^{13 14}, whereas in the drylands of northern China, sandy soil (less clay) tends to make vegetation more sensitive to water stress ¹⁵. Although several studies have noted the strong impacts of soil properties on soil water use for vegetation growth ^{16 17}, it remains unclear how and to what extent soil properties impact the vegetation – soil moisture responses.

Recent advances in the understanding of vegetation growth responses to soil moisture provide an opportunity to address the issue, as observational evidence demonstrates that vegetation growth responds in a nonlinearly unimodal way to soil moisture ^{18 19 20}. Under low soil water availability, vegetation growth is constrained by water uptake and stomatal closure ^{21 22}. Under excessively high soil moisture, vegetation growth is dampened by waterlogging, nutrient leaking, fungal pathogens and increased pests ^{23 24}. Across the nonlinear response curve of vegetation growth to soil moisture, there is an optimal point where vegetation growth is at the maximum. The soil moisture value under the vegetation growth maximum is defined as the soil moisture optima, at which the changes in soil moisture content in either direction will cause vegetation growth to decrease. Considering the soil property impacts on the vegetation growth response to soil moisture, we hypothesized that the soil properties would be linked to the key parameters of the nonlinear curves describing the vegetation – soil moisture response.

With the development of this new framework, we are able to quantify the impacts of soil properties on vegetation use of soil water for growth. Here, we use a remote sensing proxy of global vegetation growth (i.e., NDVI) and monthly soil moisture data to depict the nonlinear relationships between soil moisture and vegetation growth for each pixel. We examine the relationships of soil properties and the parameters of the nonlinear relationships (including the soil moisture optima and others) and use statistical methods to quantify the impacts of soil properties on vegetation growth from other factors.

2.1 Climate, soil and vegetation dataset

In this study, we focused on how soil can affect vegetation growth in vegetation nonlinear responsiveness to the soil moisture decline process and thus collected corresponding datasets. The data used in this study are openly available in the following databases: The Normalized Difference Vegetation Index (NDVI) dataset was obtained from the third-generation Advanced Very High Resolution Radiometer (AVHRR) data from the Global Inventory Modeling and Mapping Studies project (GIMMS) (available at https://ecocast.arx.nasa.gov/data/pub/gimms/3 g.v0) as a proxy for vegetation growth. GMMIS NDVI was provided at a biweekly time step at 0.083° spatial resolution between 1982 and 2015 ²⁵. The terrestrial soil moisture from satellite data was downloaded from the Land Evaporation Amsterdam Model (available at https://www.gleam.eu/), which is provided on a 0.25°×0.25° grid with a daily temporal resolution ^26, and the global monthly resolution temperature and precipitation data were obtained from Climatic Research Unit (CRU) datasets (version 4.01) at a native 0.5° × 0.5° grid ²⁷. The aridity index (AI) measures the relative balance between water demand (calculated here as potential evapotranspiration, PET) and water supply (precipitation, P). Where AI < 0.65, the system is water limited ²⁸. The soil data were extracted from the SoilGrids dataset with a spatial resolution of 1 km × 1 km, which is available at the global scale and is a system for automated soil mapping based on global soil profiles ^{29 30}. All data in this study were first aggregated to a uniform monthly resolution matching the climate data and then resampled to attain a spatial resolution of 0.5° × 0.5° grid in ArcGIS 10.3.

2.2 Methods

Modeling the nonlinear relationship between soil moisture and vegetation growth

First, we removed the impact of temperature on vegetation growth by fitting a linear regression between temperature and NDVI in each grid and then using the fitted regression to remove the temperature-driven component from the NDVI values. Then, we established relationships between NDVI anomalies (after removing the temperature impacts) and soil moisture in each grid based on the following nonlinear equation (Eq. 1) ^{31 32}:

$$NDVI\left(sm\right)=NDVImax -{b\left(SM-SMpoint\right)}^{2}$$

where NDVI(sm) is the temperature-free NDVI anomaly at a given soil moisture (SM), and SMpoint is the soil moisture optima determined by the vertex of the unimodal curve. NDVImax represents the local maximum vegetation growth potential under the SMpoint in each grid; b is a parameter describing the spread of the parabola.

Defining soil water use efficiency by vegetation

We defined vegetation soil water use efficiency as the amount of vegetation growth change due to soil moisture consumption per unit (every 0.01 cm³/cm³ decrease in soil moisture). As we used Eq. (1) to describe the soil moisture (SM) – vegetation growth (NDVI) relation for each pixel, we derived the vegetation use efficiency of soil water ($\frac{{d}_{NDVI}}{{d}_{SM}}$) at a given soil moisture using the following equation:

$$\frac{{d}_{NDVI}}{{d}_{SM}}=2*b(SM-SMpoint)$$

Quantifying the impacts of soil properties on vegetation soil water use

In this step, we quantified the impacts of soil properties on vegetation growth and identified the important soil properties for vegetation soil water use. We considered soil texture (clay, silt, sand), absolute soil depth, soil bulk density, soil organic matter content, soil pH, and soil CEC, as they have been reported to have global impacts on the efficiency of water storage and release and thus vegetation growth in previous studies ^{33 34}.

Next, we linked soil properties to the three key parameters describing the nonlinear relationships between soil moisture and vegetation growth (NDVImax, SMpoint and b). We used a multiple regression model to quantify the impacts of soil properties on these three parameters (Equations (3)-(5)), and the corresponding parameters (α, β and γ) were estimated by fitting the line after deleting the strongly collinear variables by minimizing the Akaike information criterion.

$$NDVImax=\alpha \text{*}soil+{NDVImax}_{-soil}$$

$$SMpoint=\beta \text{*}soil+{SMpoint}_{-soil}$$

$$b=\gamma \text{*}soil+{b}_{-soil}$$

where soil represents all selected soil properties by minimizing the Akaike information criterion and α, β and γ are the corresponding parameters from each fitted equation. NDVI_− soil, SMpoint_− soil and b_− soil are the intercepts of the linear equations, which means that the effect is independent of soil properties.

We then substituted the equations above (Equations (3)-(5)) into Equations (1) and (2) and obtained the following equation:

$${NDVI\left(sm\right)}_{-\text{s}\text{o}\text{i}\text{l}}={NDVImax}_{-soil} -{{b}_{-soil}\left(SM-{SMpoint}_{-soil}\right)}^{2}$$

$$\frac{{d}_{NDVI}}{{d}_{SM-soil}}=2*{b}_{-soil}(SM-{SMopt}_{-soil})$$

where NDVI (sm)_−soil is the NDVI change not caused by soil properties and $\frac{{d}_{NDVI}}{{d}_{SM-soil}}$ is the vegetation soil water use efficiency independent of the soil property impacts.

We then quantified the impacts of soil properties on soil water use efficiency and vegetation growth as the difference between Eq. (2) and Eq. (7) and the difference between Eq. (1) and Eq. (6), respectively, using the following equations:

${\frac{{d}_{NDVI}}{{d}_{SM}}}_{soil}=2*b\left(SM-SMpoint\right)$ $-$ $2*{b}_{-soil}\left(SM-{SMpoint}_{-soil}\right)$ (8)

$NDVI\left(sm\right)-{NDVI\left(sm\right)}_{-soil}=[{b}_{-soil}{\left(SM-{SMpoint}_{-soil}\right)}^{2}-b{\left(SM-SMpoint\right)}^{2} ]$ $+$ $\left[NDVImax -{NDVImax}_{-soil}\right]$ (9)

In Eq. (8), ${\frac{{d}_{NDVI}}{{d}_{SM}}}_{soil}$ is the impact of soil properties on vegetation soil water use efficiency. In Eq. (9), $[{b}_{-soil}{\left(SM-{SMpoint}_{-soil}\right)}^{2}-b{\left(SM-SMpoint\right)}^{2} ]$ is the impact of soil properties on vegetation growth by adjusting soil water use, while $\left[NDVImax-{NDVImax}_{-soil}\right]$ represents the baseline effect of soil properties on vegetation growth (not by adjusting soil water use). In our study, we focused on the impact of soil properties on vegetation growth by adjusting soil water use, and its theoretical effect is depicted in Fig. 1.

3.1 How soil properties adjust vegetation soil water use

The estimated soil moisture optima (SMpoint) considering soil property impacts (shown in Eq. (4)) was highly correlated with the observed SMpoint (R² = 0.5, P < 0.01) (Fig. 2a), suggesting the significant role of soil properties in explaining the variation in SMpoint. We also found that soil properties were unable to effectively explain the variation in parameter b of the nonlinear response (R² = 0.0) (Fig. 2b). Therefore, in this study, we focused on the impacts of soil properties on SMpoint, which is essential to the assessment of soil properties on vegetation growth responses to soil moisture.

The impacts of soil properties on SMpoint ranged from − 0.18 cm3/cm3 to 0.16 cm3/cm3 across the globe (Fig. 2d). In wet climate zones, including the tropics, eastern United States, southern China, central Africa, western Europe and Russia, the impacts of soil properties tend to make SMpoint higher. Soil properties tend to have negative impacts on SMpoint in water-limited ecosystems (Aridity index < 0.65), such as those in central and western Asia, Australia and the Sahel, western US, southern Africa and northern China (Fig. 2c and 2d).

3.2 The impacts of soil properties on vegetation growth by adjusting soil water use

We further assessed the impacts of soil properties on vegetation soil water use efficiency, and 58% of the grids showed a positive soil property effect on enhancing soil water use efficiency (positive value in Fig. 3a). We also found that nearly 60% of the grids showed positive effects of soil properties on vegetation growth by adjusting soil water use (positive value in Fig. 3b). The relationship between the soil effect on soil water use efficiency and the soil effect on vegetation growth was significant (Fig. 3c). This means that a positive soil property effect to enhance soil water use efficiency corresponds to a more favorable soil environment for vegetation growth and leads to greater vegetation growth represented by NDVI with the same soil water supply capacity than elsewhere in the world. The positive effects of soil properties on vegetation growth were large in western North America, southeastern South America, southern Africa, southeastern Australia and northern China. The rest of the region either showed minimal positive impacts of soil properties or negative impacts, and these regions were mainly humid ecosystems, including Amazonian regions and boreal regions (Fig. 3b).

We also examined the impact of soil properties on vegetation response to soil moisture in comparison to climate factors (i.e., temperature and precipitation) and found large spatial variation in soil property impacts around the globe. Globally, we found that vegetation growth is predominantly determined by climate factors, as climate factors explained more than 50% of the changes in vegetation growth on more than 40% of the vegetated land surface, while soil properties imposed substantial impacts at the regional scale. We found that the impact of soil properties was greater than that of climate on nearly 20% of the vegetated land surface. More than 78% of the dominant soil property impact regions were in water-limited ecosystems (Aridity index < 0.65), including southern Australia, northern China, central Asia, southern Africa, western North America and southern South America (Fig. 4). In these dry regions (Aridity index < 0.65), the average change in vegetation growth driven by soil property impacts is 62%. However, soil properties, by adjusting soil water use on average, explained only 21% of the vegetation growth change in humid ecosystems (Aridity index > 0.65). The regions where the soil property impacts on vegetation growth are much less than that of climate are mainly concentrated in tropical subtropical moist broadleaf forest (Fig. 4).

3.3 The key soil properties for adjusting vegetation soil water use

Here, due to the potential correlation between soil properties and the treatment of collinearity in our statistics, we highlighted the comparison of soil texture (i.e., characterized by sandy fraction/silt fraction) to determine what kind of soil is likely responsible for the positive or negative soil impacts on vegetation growth we observed. In the water-limited ecosystems (Aridity index < 0.65), the regions with positive soil property impacts are the regions with a higher sand fraction/silt fraction (sandy loam soil) (Fig. 5a). On average, the sand fraction/silt fraction in positive soil effect regions is 1.2, approximately 60% higher than that in negative soil effect regions. Only in terms of soil impacts on vegetation – soil moisture response, the water-limited ecosystems with high soil sand content correspond to a more favorable soil environment to enhance vegetation soil water use efficiency and release vegetation growth potential from soil water supply capacity. However, this does not apply to humid regions. Unlike dry regions, the increase in silt content contributes to vegetation growth by adjusting vegetation soil water use in humid ecosystems (Aridity index > 0.65) (Fig. 5b).

In this study, we developed a new framework to quantify the impacts of soil properties on the vegetation growth response to soil moisture. We found large spatial heterogeneity in the impacts of soil properties on SMpoint. The impacts of soil properties on SMpoint ranged from − 0.18 cm³/cm³ to 0.16 cm³/cm³ across the globe. The impacts of soil properties on SMpoint tended to be positive in humid regions and negative in water-limited regions. In previous studies on the spatial heterogeneity of vegetation growth in response to water supply change, however, more attention was given to the change in climate conditions ^{35 36} and the physiological characteristics of plants ³⁷, and the role of soil properties on plant water use was often ignored. Our study for the first time quantified the global patterns of soil contribution to vegetation growth and validated it with a satellite-derived vegetation index and global databases of soil properties and soil moisture.

Our results showed significant soil impacts on ΔNDVI/ΔSM and vegetation growth could be positive or negative depending on soil impacts on SMpoint. This difference may help explain previously observed heterogeneity in vegetation resistance with different soils to wet or dry events ¹⁷. In addition, our results also help to explain why the same vegetation responds differently to the same water deficit under different soil conditions ¹³. A positive impact of soil properties makes vegetation more resistant to soil water deficits, explaining previous observations of insensitive vegetation change to soil moisture changes ^{38 39}. The spatial distribution of the soil effect on vegetation growth by adjusting soil water use in this study shows the regions without a positive soil effect, where plenty of evidence supports the high drought sensitivity and obvious decline in vegetation growth in response to soil moisture deficit ^{40 41}.

The coarser-textured soils represented by higher soil sand content have a greater ability to enhance soil water use efficiency and have positive impacts on vegetation growth in global drylands, as sandy soil has high water conductivity and makes water more accessible to plant roots ⁴¹. This may help explain why higher aboveground biomass was observed with coarse-textured soil than with fine-textured soil under the same water supply in water-limited ecosystems ⁴². However, we found the opposite effect of soil sand content in humid regions⁴³, where the increase in soil silt content can drive vegetation growth, which is also explainable as silt content adjusts the water holding capacity of soil ⁴⁴ and the unit cost of water for vegetation growth decreases as soil silt content increases ^{45 46}.

Our results present observational evidence that the dominant impacts of soil properties on vegetation growth widely exist on nearly 20% of the vegetated land surface, particularly in water-limited regions, firstly quantify the previously hypothesized nonlinear response of vegetation growth to soil moisture ^{10 47}. Our study also provides a useful framework to incorporate soil property information in vegetation models since most models lack explicit consideration of soil properties and often simply prescribe empirical and linear equations to estimate vegetation change to soil moisture type ^{48 49 50}. It will be a worthwhile improvement in modeling and monitoring drought sensitivity and vegetation growth to consider the important role of soil in soil moisture-vegetation growth relations.

In this study, we used global climate, soil and vegetation data to assess the impacts of soil properties on the nonlinear vegetation growth – soil moisture response and found that soil properties serve as a key factor in adjusting the vertex of the nonlinear response and influencing soil water use. Sandy soil enhances vegetation soil water uptake, mostly in drylands but also has negative impacts on vegetation soil water use in humid ecosystems. Our study uncovers the role of soil properties in adjusting vegetation growth and provides a new understanding of soil-vegetation interactions in Earth system science.

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Greater soil contribution to vegetation growth in dry regions than in humid regions

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Version 1

Abstract

Figures

1. Introduction

2. Materials and methods

2.1 Climate, soil and vegetation dataset

2.2 Methods

3. Results

3.1 How soil properties adjust vegetation soil water use

3.2 The impacts of soil properties on vegetation growth by adjusting soil water use

3.3 The key soil properties for adjusting vegetation soil water use

4. Discussion

5. Conclusions

References

Additional Declarations

Status:

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