Assessing the dynamics of grassland functioning is critical for gaining an understanding of their feedback on rising aridity. In attempting to understand the response of grassland ecosystem functioning to aridity, the (i) relationships between biomass productivity (above- and belowground biomass: AGB and BGB, and their partitioning: BGB:AGB) and seasonal and annual aridity, and (ii) biomass allocation pattern between the AGB and BGB of C3- and C4-dominated grasslands in humid temperate, humid savanna, cold steppe, and savanna ecoregions were assessed. Results reveal that biomass productivity and its partitioning responded significantly to differences in growing season aridity, but the response patterns were not consistent for ecoregions. The decreased annual and seasonal biomass partitioning in humid savanna and cold steppe was associated with increased AGB and decreased BGB with accelerated aridity. There was a significant positive correlation in the biomass allocation pattern between the AGB and BGB of plants in three ecoregions, which supports the optimal partitioning theory. This study reveals that growing season aridity, rather than annual aridity, is the primary factor of biomass productivity and partitioning in the studied grasslands. These findings have significant repercussions for predicting ecosystem functioning and stability, restoring degraded ecosystems, and ensuring the sustainable management of grassland biodiversity.
Ecosystem functioning under aridity has been assessed for four grassland ecoregions.
Significant changes in growing season biomass resulted from increasing growing season aridity.
Above- and belowground biomass showed a positive correlation and supported optimal partitioning theory.
Aboveground biomass (AGB) and belowground biomass (BGB) productivity are significant determinants of ecosystem health and are used to assess the functionality and predictability of grassland ecosystems (Isbell et al. 2015; Hossain & Li 2021a). Over the past few decades, one of the most important topics of investigation in the field of plant ecology has been the impact of climate change on AGB and BGB productivity in grassland ecosystems (Jentsch et al. 2011; Luo et al. 2017; Zhang et al. 2017a; Hossain & Li 2021b). In ecological research, there has been a discussion going on for over three decades about the factors that drive grassland AGB productivity (Craine et al. 2012; Kreyling et al. 2017; Hossain & Li 2020) and BGB productivity (Wu et al. 2011; Luo et al. 2017; Zhang et al. 2019) and their partitioning (BGB:AGB ratio) (Yang et al. 2010; Qi et al. 2019).
The observed discrepancies in previous studies could result from multiple factors, including (i) the variations in spatial scales of the study (e.g., single or multiple sites; Hossain et al. 2021; Zhang et al. 2021), (ii) the differences in experimental duration (e.g., short or long term; Niu et al. 2005; Hossain et al. 2022), (iii) the differences in vegetation types (e.g., C3 or C4 plants; Winslow et al. 2003; Niu et al. 2005; Hossain et al. 2023a), and (iv) consideration of either AGB or BGB without considering biomass allocation pattern (Hossain & Li 2021b). Since a large percentage of grasslands' coverage is water-limited, aridity can play a great role in the functioning and stability of these ecosystems (Harpole et al. 2011). In order to advance our understanding of the interactions of ecosystems with climatic conditions, considerations of several biophysical properties, such as plant functional types, multiple ecoregions, several climatic variables (growing season and annual aridity), and the long-run datasets of AGB and BGB, are of great importance (Li et al. 2013a, 2013b; Aleksanyan et al. 2020; Cui et al. 2021). The aforementioned recurring debates highlight the importance of gaining a comprehensive understanding of the functioning of C3- and C4-dominated grasslands at larger scales in relation to temporal patterns of aridity.
Aridity is the most influential abiotic factor in grassland ecosystems because the majority of grasslands have limited water resources (Merbold et al. 2009; Harpole et al. 2011). The global area of drylands is projected to rise by 11–23% by 2100 (Huang et al. 2015), accompanied by decreased soil moisture and increased aridity (Fu & Feng 2014; Zhang et al. 2014, 2015). The expected rises in aridity would reduce the capability of global grasslands to supply the valuable services of ecosystems that sustain life (Li et al. 2013b; Trenberth et al. 2014; Berdugo et al. 2020). It has been claimed that aridity reduces the number of plant species and their functioning and alters the organization of above- and belowground communities across grassland types (e.g., meadow, alpine, and temperate grasslands) (Maestre et al. 2015; Berdugo et al. 2020). There is mounting evidence that the productivity of grasslands has been affected by altered precipitation patterns, increased growing season temperature, more frequent extreme weather events, and increased aridity across grassland-dominated ecosystems (Huang et al. 2015; Hossain & Li 2021a). Approximately 250 million people in lower and developing nations are being impacted by desertification and land degradation resulting from these climate-induced stresses (Reynolds et al. 2007). Because ecosystem services, including nutrient cycling, carbon storage in plants and soil, and the breakdown of organic matter, are influenced by these abiotic factors, ecosystem stability is predicted to diminish with rising aridity (Maestre et al. 2012; Durán et al. 2018; Hossain et al. 2023b). Exploring the relationships between aridity and the biomass productivity of grasslands across ecoregions will advance our understanding of how aridity impacts grassland performance. Our ability to forecast the future productive capacity of grasslands and to plan for future sustainable grassland management will improve our understanding of the effects of aridity on annual and seasonal biomass productivity across ecoregions.
The study of the influence of aridity on grassland productivity is important because it helps us understand how climate-induced stresses affect the functioning and stability of grassland ecosystems (Hossain et al. 2023b). Aridity is increasing in many parts of the world due to climate change (Li et al. 2016,, 2017), and this has significant implications for the productivity and biodiversity of grasslands (Maestre et al. 2015; Berdugo et al. 2020). As grasslands are one of the largest ecosystems on Earth, providing important ecosystem services such as carbon sequestration and habitat for wildlife (Trenberth et al. 2014), understanding their sensitivity to aridity is critical for predicting and mitigating the impacts of climate change (Li et al. 2015). By studying the relationship between aridity and grassland productivity, we can develop effective strategies to manage and conserve these important ecosystems in the face of climate change. One important area of research is to identify the threshold of aridity beyond which grasslands become unproductive or converted to other land uses. This is important because it can help inform land-use planning and management decisions. For example, if the threshold of aridity is known, land managers can develop strategies to maintain soil moisture levels above this threshold, such as implementing sustainable irrigation practices. Irrigation practices are again dependent on river networks. River networks provide a source of water for ecosystems and can influence nutrient availability in grasslands. River corridors can act as wildlife corridors, providing habitat and connectivity for a range of species. River networks can influence the frequency and intensity of disturbances in grasslands (Sarker et al. 2019, 2023; Sarker 2021; Gao et al. 2022).
In addition to the ecological impact, the study of aridity and grassland productivity also has important social and economic implications. Grasslands are used for livestock grazing, hay meadow production, agriculture, and biodiversity conservation, and changes in productivity and biodiversity can have significant impacts on local economies and livelihoods. Understanding how grasslands respond to changes in soil moisture levels can help inform decisions about land-use and management practices that support sustainable production systems and rural livelihoods.
Plant ecologists have long believed that the allocation of biomass between BGB and AGB is highly idiosyncratic, which is consistent with two well-established hypotheses (isometric partitioning and optimal partitioning). The optimal partitioning theory suggests that vegetation distributes proportionally greater energy to structures with a greater capacity to absorb the scarcest nutrients (Mao et al. 2012). Thus, it is anticipated that plants will devote higher biomass belowground in arid conditions and aboveground in wetter settings (Villar et al. 1998). The isometric partitioning theory argues that AGB and BGB maintain an isometric arrangement (Enquist & Niklas 2002; Wang et al. 2014), suggesting that there is not an absolute exchange between AGB and BGB (Enquist & Niklas 2002; Wang et al. 2014). Large numbers of empirical studies that refute isometric partitioning (Enquist & Niklas 2002; Wang et al. 2014) have produced contradictory findings (Chen et al. 2016; Ma & Wang 2021). A better understanding of how biomass is distributed between the root and shoot in plants would expand our ability to forecast how grasslands will function in the future.
In an attempt to better understand how grassland ecosystems respond to gradients of aridity and how plant biomass is allocated into root and shoot in two plant types at seven sites belonging to four grassland ecoregions (savanna, humid temperate, cold steppe, and humid savanna), this study assessed (i) the relationships of annual and seasonal biomass and their partitioning with annual and growing season aridity and (ii) the biomass allocation pattern between AGB and BGB across four ecoregions belonging to C3- and C4-dominated grasslands.
In this paper, we utilized climate and grassland AGB and BGB data for the period 1969–1994 to assess the effect of aridity on grassland functioning. All AGB and BGB data were extracted from the global Net Primary Productivity (NPP) database at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) (Scurlock et al. 2015). Climate data include annual and monthly precipitation and temperature. These climate data were extracted from the ORNL DAAC (Scurlock et al. 2015) and the Climate Research Unit (Harris et al. 2014). We extracted the Digital Elevation Model (DEM) raster files from the United States Geological Survey (USGS) (Farr et al. 2007). For this, the study sites were selected using known latitudes and longitudes. Raster images (30 m resolution) from ‘SRTM 1 Arc-Second Global’ were used in preparing the study map.
The growing season AGB and BGB in a given year were summed up to get the annual AGB and BGB in their respective sites. The ratios BGB:AGB were obtained by dividing the growing season and annual BGB by their respective growing season and annual AGB. Biomass data from these seven sites were then assembled into four ecoregions and two functional types (C3 and C4) (Scurlock et al. 2002).
The relationships between (i) growing season biomass (AGB and BGB, BGB:AGB ratio) and growing season aridity, and (ii) annual biomass and annual aridity at the site level were assessed using Pearson correlation analysis (Sun et al. 2021). We used a heat map and correlation matrix to display the strength and direction of the relationships between biomass and aridity. For example, dark colors (blue and red) represent the stronger relationships (negative and positive) between biomass and aridity. Similarly, the relationships between the growing season and annual AGB and BGB across ecoregions were assessed by the Pearson correlation. The level of significance of biomass allocation between BGB and AGB was detected at p < 0.05. All statistical analysis was performed in the statistical package R version 4.0.3 (R Core Team 2020).
Biomass response to aridity
|Biomass .||Seasonal/annual .||C3-dominated grasslands|
|Cold steppe (shr) .||Cold steppe (tmg) .||Humid temperate (krs) .||Humid temperate (otr) .||Humid savanna (kln) .||Humid savanna (mnt) .||Savanna (nrb) .|
|Biomass .||Seasonal/annual .||C3-dominated grasslands|
|Cold steppe (shr) .||Cold steppe (tmg) .||Humid temperate (krs) .||Humid temperate (otr) .||Humid savanna (kln) .||Humid savanna (mnt) .||Savanna (nrb) .|
Abbreviations: kln, Klong Hoi Khong; krs, Kursk; mnt, Montecillo; nrb, Nairobi; otr, Otradnoe; shr, Shortandy; tmg, Tumugi.
Mechanism of biomass allocation
Under an altered precipitation pattern, growing temperature, and aridity, grasslands are likely to modify their functioning by altering root and shoot productivity. Uncovering the essential attributes controlling grassland productivity in multiple ecoregions over the long term is a significant challenge in plant ecology. In this study, we investigated (i) how growing season and annual aridity affect seasonal and annual AGB, BGB, and BGB:AGB ratio, and (ii) how the biomass of these ecoregions is allocated into AGB and BGB.
The impact of aridity on AGB, BGB, and BGB:AGB ratio differed between plant types, ecoregions, and the duration of aridity (i.e., growing season and annual). The rise in growing season aridity in this study enhanced the growing season AGB of grasslands at one site in cold steppe and one site in humid savanna ecoregions and did not affect the growing season AGB of other sites in all ecoregions. The observed positive associations between growing season aridity and AGB in C4 plants in humid savanna and C3 plants in the cold steppe suggest that rising aridity enhances AGB by increasing photosynthesis. It is expected that in arid conditions, plants exert more effort aboveground and are capable of coordinating the association between the assimilation of carbon and the usage of water for transpiration (Paoletti et al. 1998). In this way, plants can maintain high water-use efficiency and a stable photosynthetic rate and promote the production of shoots (Chengjiang & Qingliang 2002).
Grasslands in different ecoregions respond inversely to aridity in order to adapt to changing conditions. This is done by regulating the supply of photosynthate to shoots and roots, and as a result, the BGB:AGB changes with the fluctuations in aridity (Qi et al. 2019). There was a large amount of variation in the ways in which the BGB:AGB ratio responded to aridity across ecoregions. The different ways in which the BGB:AGB ratio reacts to changes in the environment can be clarified by the various functional types of plants. The fact that the ratio of BGB to AGB has decreased in C3 plants in the cold steppe ecoregion as aridity has increased suggests that C3 plants devote more efforts aboveground to optimize shoot growth and capture more sunlight than they do belowground to obtain soil resources in arid conditions (Angelo & Pau 2015). The positive associations of the seasonal BGB and AGB with the growing season aridity in C3-dominated grasslands in our study were in accordance with those confirmed in C3 grasslands in steppe and temperate ecoregions (Chen et al. 2017; Guo et al. 2018; Hossain & Beierkuhnlein 2018).
Grasslands in ecoregions with warmer temperatures have developed adaptive strategies for dealing with the stresses caused by higher aridity (Volder et al. 2010). However, elevated stress is shown to inhibit the capacity of grasslands to partition their biomass, which we observed for C4-dominated grasslands. The observation of a decreasing BGB:AGB ratio in C4-dominated grasslands with increasing aridity demonstrates that C4 plants adapt to arid conditions by either lowering the AGB or increasing the BGB. The loosening of plant photosynthesis because of a reduction in soil moisture and a rise in evapotranspiration during increasing aridity can explain the decreased AGB of C4 plants during the growing season aridity (De Boeck et al. 2011). This finding is in line with an experiment by Kahmen et al. (2005), which revealed that in semi-arid grasslands, arid conditions reduced the AGB. Similarly, the stable BGB of C4 plants with rising growing season aridity suggests that under arid conditions, plants can sustain BGB productivity by enhancing fine root systems to draw out more water (Luo et al. 2013; Dai et al. 2019).
According to two well-established hypotheses, biomass allocation between AGB and BGB is greatly distinctive, which is what plant ecologists have long believed (isometric partitioning and optimal partitioning). Based on the theory of optimal partitioning, vegetation should distribute more energy proportionally to structures that have a higher capacity for absorbing the most limited substances (Bloom et al. 1985; Gedroc et al. 1996; Mao et al. 2012). Therefore, it is expected that plants will allocate more biomass aboveground in wetter environments and belowground in arid environments (Villar et al. 1998). Our findings of the distribution of biomass across three ecoregions – cold steppe, humid temperate, and savanna – confirm the theory of optimal partitioning for both the growing season and annual biomass. In other words, plants in these three ecoregions distributed their greater efforts more evenly in response to the abiotic conditions to extract the scarcest resources. The optimal partitioning of AGB and BGB in these three ecoregions is consistent with several other studies across different grassland types. For example, Mao et al. (2012) reported that two grass species exhibit optimal partitioning for allocating biomass between roots and shoots.
Aridity influences ecosystem productivity and stability. Understanding how different grasslands across ecoregions respond to the growing season and annual aridity is critical to the sustainable management of grassland biodiversity and to the stable delivery of ecosystem goods and services to mankind. This study's findings provide empirical evidence of the stronger effects of growing season aridity on growing season AGB and BGB, which is of practical importance for pastoralists and herders in biomass and hay meadow production. As the empirical evidence of how BGB changes with the changes in AGB is limited, the optimal partitioning pattern of biomass allocation in our three ecoregions (i.e., cold steppe, humid temperate, and savanna) has important implications in decision-making for selecting species dominance and composition across various grasslands, including C3- and C4-dominated grasslands.
This paper demonstrates the evidence of the influence of aridity on biomass productivity (AGB and BGB) and their partitioning of two distinct grasslands in four ecoregions. Results exhibited that seasonal and annual AGB, BGB, and BGB:AGB ratio of C3 and C4 plants were influenced by the gradients of the growing season and annual aridity, but the interactions were not consistent for all ecoregions. The study findings emphasize that growing season aridity is a stronger controlling determinant of seasonal and annual biomass productivity and their partitioning in C3 and C4 plants in cold steppe and humid savanna ecoregions, respectively. This result suggests that enhanced aridity may enhance AGB in these two ecoregions, but a substantial decrease in BGB is likely to decrease the functioning of ecosystems. The theory of optimal partitioning for both seasonal and annual biomass is supported by our findings of the distribution of biomass between aboveground and belowground for the cold steppe, humid temperate, and savanna ecoregions. The relationships described here provide a foundation for further long-term coordinated research in grasslands across wider spatial scales with respect to the increasing severity and recurrence of extreme climatic events and aridity. These findings have significant implications for predicting the functioning of ecosystems across arid, semi-arid, and temperate grasslands.
This work was supported by the research grants from the Guangdong-Hong Kong Joint Laboratory for Water Security (project no. 2020B1212030005) and the Research Grants Council of the Hong Kong Special Administrative Region, China (project no. HKBU12302518).
M.L.H. conceptualized the work, carried out methodology, software, and formal analysis, wrote, reviewed, and edited the original draft. J.L. performed methodology, wrote, reviewed, and edited the original draft, supervised the work, did funding acquisition, and administered the project.
We have obtained the freely available data of grassland biomass productivity as well as monthly precipitation data from the global NPP database that was housed at the Oak Ridge National Laboratory Distributed Active Archive Center (Scurlock et al. 2015). Climate Research Unit provided data on monthly temperatures (Harris et al. 2014).
DATA AVAILABILITY STATEMENT
All relevant data are available from an online repository or repositories https://doi.org/10.3334/ORNLDAAC/654, https://catalogue.ceda.ac.uk/uuid/10d3e3640f004c578403419aac167d82.
CONFLICT OF INTEREST
The authors declare there is no conflict.