Root trait shifts towards an avoidance strategy promote productivity and recovery in C₃ and C₄ pasture grasses under drought

Abstract

1. Plant species show a broad spectrum of plasticity in their covarying root traits in response to soil water limitation ranging from no change to shifts towards traits that enhance water and nutrient acquisition. Knowledge of root trait correlations and associated trait plasticity under drought is crucial to sustaining grassland production, including rangelands and pastures, under future, drier climates.2. Here, we investigated below-ground responses to drought in four C 3 and three C 4 grasses and whether these explain above-ground responses during extreme cool-season drought and post-drought recovery in a well-replicated field experiment. We hypothesised that (a) C 3 and C 4 functional groups differ in their below-ground trait responses to drought: C 3 species shift their traits in line with a drought avoidance strategy and C 4 species shift towards drought tolerance strategies; (b) post-drought recovery is associated with below-ground carbon reserves in both functional groups. 3. Root traits in the C 3 functional group differed from C 4 by having higher values for specific root length, nitrogen and soluble sugar concentrations, while C 4 root traits were associated with higher mean diameter, tissue density and starch concentrations. Drought-induced plasticity in root traits in both functional groups was evidenced by increased values for specific root length, soluble sugars and nitrogen concentrations, and reduced values for tissue density, which we interpret as a drought avoidance strategy. Increasing root soluble sugars in C 3 and C 4 grasses and lower root tissue density in C 4 species under drought were associated with greater above-ground productivity. Above-ground biomass recovery post-drought was predicted by root and crown soluble sugar concentrations and root longevity across both plant functional groups. 4. These findings highlight the importance of understanding links between root trait plasticity and plant productivity during and following drought for predicting plant species' responses to changes in a future climate. K E Y W O R D S C 3 and C 4 functional groups, cool-season drought, drought avoidance and tolerance, nonstructural carbohydrates, resistance and resilience, root crown, root traits, trait plasticity | 1755 Functional Ecology CHANDREGOWDA et al.

Belowground carbon allocation, root trait plasticity, and productivity during drought and warming in a pasture grass

“…However, the greater drought sensitivity of BNPP relative to ANPP observed in our study supports findings from grassland studies elsewhere ( Frank, 2007 ; Carroll et al , 2021 ), although there have been contrasting responses observed for f BNPP and RMF. This finding is at odds with expectations based on the functional equilibrium theory ( Lambers, 1983 ), whereby plants are expected to increase f BNPP ( Hui and Jackson, 2006 ; Franco et al , 2020 ) and RMF ( Poorter et al , 2012 ; Eziz et al , 2017 ) in response to drought since a greater proportional biomass investment belowground can increase the acquisition of water and other soil resources ( Wilcox et al , 2015 ; Zhang et al , 2017 ; Chandregowda et al , 2022a ). The observed reduction in BNPP and f BNPP in our study might be due to the large drought effect size on aboveground physiology, such as a reduction in leaf water potential and associated impacts on overall plant C assimilation (reported in Jacob et al , 2022 ) and the resulting decrease in the availability of carbohydrates to invest in belowground production.…”

“…Plant functional traits and their plasticity can illustrate multiple aspects of plant strategies, describe how individual species cope with heterogeneous environments, and provide a means of predicting patterns of plant responses to changes in their environment ( Soudzilovskaia et al , 2013 ; Funk et al , 2017 ). For instance, under conditions such as inadequate nutrient supply and water stress, plants can alter their root traits, by increasing specific root length (SRL; root length per unit root dry mass) or reducing root tissue density (RTD; root mass per unit volume) or mean root diameter, to enhance soil resource uptake and maintain plant growth ( Bruelheide et al , 2018 ; Wieczynski et al , 2019 ; Chandregowda et al , 2022a ). Plants can also alter biomass allocation to facilitate the acquisition of growth-limiting resources.…”

“…Plants can also alter biomass allocation to facilitate the acquisition of growth-limiting resources. Under soil resource limitation, plants favour biomass allocation to roots by increasing the fraction of belowground net primary production ( f BNPP ; belowground net primary production to total plant production ratio) ( Hui and Jackson, 2006 ; Xu et al , 2012 ; Chandregowda et al , 2022a ) and the root mass fraction (RMF; root biomass to total plant biomass ratio) ( Poorter et al , 2012 ), and shifting root production to deeper soil depths ( Gibson-Forty et al , 2016 ; Arndal et al , 2018 ). Given the explanatory power of plant functional traits and the potential for trait plasticity ( Grime and Mackey, 2002 ; Arnold et al , 2019 ), there is considerable interest in using a traits-based approach to understand and predict plant species’ responses to climatic factors ( Lozano et al , 2020 ).…”

“…In addition to large inter- and intraspecific variability in individual root traits, there may be high coordination and trade-offs among morphological, physiological and chemical traits ( Carmona et al , 2021 ). For instance, thin fine roots with higher SRL are often correlated with lower root diameter, lower RTD, and higher tissue metabolic activity ( Tjoelker et al , 2005 ; Chevin and Hoffmann, 2017 ; Chandregowda et al , 2022a ). Thicker roots are typically associated with higher starch storage, which may support growth and maintenance as well as provide osmolytes important for hydraulic and tissue metabolic functions ( Zwicke et al , 2015 ).…”

Plant root plasticity during drought and recovery: What do we know and where to go?

“… (1) ( Xu et al., 2009 ); (2) ( Chen et al., 2016 ); (3) ( Delfin et al., 2021 ); (4) ( He et al., 2022 ); (5) ( Schneider et al., 2020 ); (6) ( Liao et al., 2022 ); (7) ( Chandregowda et al., 2022 ); (8) ( Slette et al., 2022 ); (9) ( Jongrungklang et al., 2014 ); (10) ( De Bauw et al., 2019 ); (11) ( de Vries et al., 2019 ); (12) ( Brunn et al., 2022 ); (13) ( Preece and Penuelas, 2016 ); (14) ( de Vries et al., 2020 ); (15) ( Santos-Medellin et al., 2021 ). …”