Global trends in vegetation fractional cover: Hotspots for change in bare soil and non-photosynthetic vegetation
Graphical Abstract
Introduction
Vegetation Fractional Cover (VFC) is an important indicator of the condition and health of the terrestrial surface of the Earth. Excluding permanent snow and ice cover, the terrestrial surface may be described in simple terms by the fractional cover of green leaves which fix carbon through photosynthesis (Photosynthetic Vegetation – PV), non-green vegetative material that is primarily made up of plant structural materials such as cellulose and lignin (Non-Photosynthetic Vegetation – NPV), and bare including soil and rock (Bare Soil – BS). The dynamics of these fractions is determined by seasonal patterns of precipitation and temperature resulting in varied patterns of growth, senescence, dormancy and regeneration across the globe (Foley et al., 2000). They also reflect trends in land cover and land use management (Song et al., 2018; Erb et al., 2018). Analysis of satellite data has indicated increasing greenness of the land surface (Park et al., 2016, Vickers et al., 2016, Xu et al., 2013, Zhou et al., 2001, Zhu et al., 2016). The positive trends in greening detected in the MODIS Leaf Area Index (LAI) product (Chen et al., 2019), which directly correlate to an increase in PV cover fraction, have been attributed to cropland expansion and intensification, CO2 fertilization and large-scale tree-planting, especially in India and China (Chen et al., 2019, Zhu et al., 2016, Piao et al., 2015, Donohue et al., 2013, Keenan et al., 2016, Cheng et al., 2017; Fensholt and Proud, 2012). However, the dynamics of the NPV and BS fractions are equally important indicators of many elements of ecosystem function and sustainability such as carbon storage Jacinthe et al., 2002), wind and water erosion risk (Imeson and Prinsen, 2004, Borrelli et al., 2017, Li et al., 2020), water infiltration (Ludwig et al., 2005), habitat condition (McNaughton, 1985; Ludwig et al., 2004; Zhang et al., 2013) and wildfire risk (Renier et al., 2015) especially in highly seasonal savannas and grasslands, and semi-arid and arid environments (Huang et al., 2020).
Increasing human populations and urbanization, and changes in dietary preferences have driven expansion in area and intensity of cropping (Rudel et al., 2009, Zalles et al., 2019) and in livestock numbers (Thornton, 2010, Derner et al., 2017, Ritchie, 2017), especially goats in Asia and Africa (Skapetas and Bampidis, 2016). This has greatly increased the intensity of the human footprint across a wide range of ecosystems (Venter et al., 2016) and increased the ongoing concern about global desertification and land degradation (Reynolds et al., 2007, Safriel, 2007, Le et al., 2016, Huang et al., 2020) and threats to biodiversity (Hu et al., 2020). The assessment by Le et al. (2016) using a long-term trend analysis of GIMMS NDVI (Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index) between 1982 and 2006 suggested that land degradation “hotspots” covered 29% of global land surface. The impact of this increased intensity has tended to place more pressure on the vegetation and ecosystem function in warmer and drier environments (Modernel et al., 2016, Tian et al., 2017). For example, recent studies have identified higher intensity of methane emissions (largely attributable to increase in livestock populations) from drylands and non-drylands, and an increased share of global methane emissions from developing regions of Africa, Asia and South America (Dangal et al., 2017). Higher grazing intensity can lead to greater levels of bare soil (Augustine et al., 2012, Modernel et al., 2016). Specific pressure points driven by anthropogenic change and climate change have been identified globally (Safriel, 2007; Huang et al., 2020) and for various regions including East Africa (Olson et al., 2004, Olson et al., 2008, Moore et al., 2012), Central Asia (Li et al., 2020) and South America (Santibáñez and Santibáñez, 2007).
The baseline levels and dynamics of the NPV fraction are an indicator of cropland stubble retention (Daughtry, 2001, Daughtry et al., 2005, Daughtry et al., 2006), dry season feed availability for livestock (Wessman et al., 1997), and fuel loads for wildfires (Lambin et al., 2003, Chuvieco et al., 2003; Guerschman et al., 2009). Various methods for detection of total vegetation and soil fractional cover have been explored (e.g., Okin et al., 2013; Song et al., 2017; Yue et al., 2020) and global bare ground changes have been assessed with Landsat Imagery (Ying et al., 2017). However, explicit mechanistic retrieval of the NPV fraction with remote sensing has been lacking until the development of the MODIS Australian Vegetation Fractional Cover Product (AVFCP); Guerschman et al. (2015); Guerschman and Hill (2018). The AVFCP has been used to develop an online tool for monitoring groundcover as an indicator of wind and water erosion risk for Natural Resource Management regions of Australia (Guerschman et al., 2018) and to examine the dynamics of the PV and NPV cover fractions in relation to antecedent rainfall (Guerschman et al., 2020).
A global version of the product, the MODIS Global Vegetation Fractional Cover Product (GVFCP), was recently described (Hill and Guerschman, 2020). In that study the trends in VFC components were explored across World Grassland Types (WGT; Dixon et al., 2014) among Global Livestock Production Systems (GLPS; Robinson et al., 2011). However, the study was limited in geographical extent, examined the trends for a single overall monthly time series from 2001 to 2018, and reported areas of significant trend at Formation and Division level within the WGT class hierarchy. In this study, we aimed to provide a comprehensive assessment of trends in VFC for the global terrestrial land surface excluding permanent and semi-permanent ice and snow with a focus on trends in the NPV and BS fractions.
Therefore, the goals of this study were:
- 1)
To detect and document the areas of the terrestrial land surface exhibiting statistically significant long-term positive and negative trends in the PV, NPV and BS cover fractions including comparison between seasons.
- 2)
To explore trends at country level and examine associations with drought, livestock density, cropland expansion and population numbers.
- 3)
To explore trends at ecoregion level as indicators of land cover change and potential land degradation with a specific focus on trends in NPV and BS.
Section snippets
MODIS global vegetation fractional cover product
The Global Vegetation Fractional Cover Product (GVFCP) v3.1 (Hill and Guerschman, 2020) is derived from spectral unmixing of all seven optical bands from the 500 m MODIS (Moderate Resolution Imaging Spectroradiometer) Nadir BRDF (Bidirectional Reflectance Distribution Function)-adjusted Reflectance Product (NBAR, MCD43A4 Collection 6; Schaaf and Wang, 2015) using previously described methods (Guerschman et al., 2015). The product consists of four derived layers corresponding to the decimal
Calculation of trends in photosynthetic vegetation, non-photosynthetic vegetation, and bare soil
In our previous study (Hill and Guerschman, 2020), the Mann-Kendall regression method was applied to the whole monthly time series of the GVFCP for the WGT regions only. The Mann-Kendall regression method is used to eliminate year-on-year temporal autocorrelation (Mann, 1945, Kendall, 1975, Meals et al., 2011). In this study, Mann-Kendall regressions were run for the 18-year period for each month of the year so that any seasonal effects would be captured in differences in statistics between
Global patterns in trends in vegetation fractional cover
The amount of total vegetation cover (BS-) increased across 20 M km2 of the terrestrial land surface between 2001 and 2018 (Table 2; Fig. 1, green). Although widely distributed across the world, major areas of increased vegetation cover were concentrated in North America, Europe, Turkey, India and China. The opposite trend, BS+, occurred across more than 11 M km2 (Table 2; Fig. 1, red). These areas were also widely distributed but more abundant in South America, Eastern Africa and Western Asia.
Discussion
In this study, we have documented the areas and magnitudes of global, regional, country and ecoregion scale trends in VFC using a unique global dataset, the GVFCP derived from the MODIS NBAR product. The results show that although a greater area of the terrestrial land surface exhibits BS- (a positive trend in total vegetation cover), the areas exhibiting BS+ are large and located predominantly in Africa, Western Asia and South America. The BS+ occur at the expense of both PV- and NPV-. The
Conclusions
This study found that major trends in vegetation fractional cover occurred across wide geographical areas of the globe between 2001 and 2018.
- 1.
Significant positive trends in BS occurred across more than 11 M km2. Eleven of the top 24 ranked countries for area of increasing BS were in Africa indicating significant anthropogenic and climatic stress on the environment.
- 2.
Significant negative trends in the BS fraction, i.e., positive trends in total vegetation cover occurred across 20 M km2 of the
CRediT authorship contribution statement
Michael Hill: Spatial analysis, Preparation of figures and tables, Covariate analysis, Writing – original draft. Juan Guerschman: Global trend calculations, Comments, edits and additions to the manuscript.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The development of the GVFCP has occurred over more than 15 years. The initial stage was partially funded by the NASA Earth Science Enterprise Carbon Cycle Science research program (NRA04-OES-010). Development of the current Australian and Global products was funded by Australian Government’s National Landcare Program and CSIRO. Rangelands and Pasture Productivity (RaPP) is an initiative of CSIRO, and the Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM).
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ORCID ID: https://orcid.org/0000-0003-4570-7467.