Plant ecosystem structure is understood to be a result of complex multitrophic interactions. Most multitrophic studies focus on plant aboveground adaptations to aboveground herbivore pressures, neglecting belowground adaptations in response to aboveground damage. Differential investment in root structures may allow plants to compensate for tissue loss or damage due to herbivores. Furthermore, phylogeny may constrain a plant’s ability to adapt belowground. We examined the belowground responses of 12 species of oak (Quercus) to varying locations and intensities of simulated herbivore damage. We first established that oak belowground traits responded to aboveground herbivory by measuring patterns of investment in coarse vs fine root structures and re-allocation of non-structural carbohydrates (NSC) to root storage. We then tested whether phylogeny could explain variations in investment patterns using phylogenetic independent contrasts. Plant adaptations to aboveground herbivory included allocating biomass and carbon reserves to root structures, depending on the location and intensity of herbivore damage. NSC re-allocation to root storage was observed when oak species experienced any type of damage, but damage to lateral tissues caused a greater re-allocation than apical damage or control treatments. We found that most belowground responses to aboveground herbivory are species-specific and may be adapted for environmental conditions or type of herbivory. Some responses to herbivore damage, such as changes in fine-root mass and root sugar concentrations, were phylogenetically constrained. Phylogenetic constraints generally occur when there is severe damage at the apical meristem. Plants may adapt to aboveground tissue loss due to varying herbivore pressures (i.e. varying location and intensity of damage) by differentially investing in root types and NSC re-allocation to root storage. Understanding linkages between and phylogenetic constraints of plant belowground responses to aboveground herbivory will improve our understanding of the ecological processes involved in multitrophic interactions.

Oak phylogeny and experimental design

We used a well-resolved molecular phylogeny containing 146 species in the American oak clade (Hipp et al. 2018). Twelve species were chosen across the phylogeny to give an adequate representation of biogeographical and environmental diversity within the oak genus. We followed oak nomenclature described in the Oaks Names Database (Trehane 2007). We excluded species where interspecific hybridization and introgression may occur, such as among the white oaks (Q. alba complex) and red oaks (Q. rubra complex) (Whittemore and Schaal 1991, Lexer et al. 2006, Hipp and Weber 2008, Moran et al. 2012). We sampled the following 12 species: Q. alba, Q. coccinea, Q. laurifolia, Q. macrocarpa, Q. michauxii, Q. muehlenbergii, Q. nigra, Q. palustris, Q. rubra, Q. sinuata, Q. stellata and Q. virginiana (Fig. S1).

Much research has been done on developing a highly resolved molecular phylogeny of American oak clades (Hipp et al. 2014, McVay et al. 2017, Hipp et al. 2018). Having a well-resolved phylogeny is crucial for comparative studies because of the non-independence between species, caused by hierarchical relationships (Ackerly and Donoghue 1995, Huey et al. 2019). Felsenstein (1985) suggested a method for weighting character values of closely related species when performing comparative analyses. Sister species may have similar trait values because of common descent and are therefore nested in a phylogenetic hierarchy. These relationships violate the assumption of independence of data points. Felsenstein’s (1985) method uses independent contrasts (calculated as the absolute difference (“contrasts”) between the actual values (“tips”) among individual species, using the square root of the variance for standardization) (also see Garland et al. 1992, Ward et al. 2020). Independent contrasts create statistical independence of data points, determining if traits may be similar because of phylogeny (“exaptations” sensu Gould and Vrba 1982) and not representations of individual adaptations. 

 

Simulated herbivory treatments

Oak saplings from each of the 12 species were purchased from Mossy Oak Nativ Nursery in West Point, MS, United States. To avoid differences in responses due to ontogeny, all saplings were the same age (approximately 3-4 years old) (Gruntman and Novoplansky 2011). Saplings were planted in May 2017, in the same type of soil (all-purpose Pro-Mix^® potting soil) to ensure that there were no nutritional or microbial effects from different soils (van der Putten et al. 2001, Pangesti et al. 2014). Throughout the experiment, pots containing the saplings were weeded weekly. The saplings were kept in optimal conditions in a greenhouse with a permanent schedule of 12 h of light and 12 h of dark at a constant 22 °C. Daily watering was administered from an irrigation system to ensure each sapling received the same amount of water. We applied five treatments to simulate variations in damage location (apical vs. lateral) and intensity (25% vs 75% tissue removal) of herbivory. The initial height of each sapling was recorded before clipping treatments were applied to account for bias related to initial size. Each treatment was replicated five times for each of the twelve species for a total of 25 individuals per species, with each plant developing in a single pot. To avoid potential block effects, pot arrangements were randomly rotated weekly.

Many plants express apical dominance, i.e. preferential growth of the apex shoot, or apical meristem over lateral tissues (Cline 1991; Aarssen 1995, Kebrom 2017). Apical dominance often results in the overall suppression of lateral growth (Aarssen 1995). Similarly, studies have shown that plants overcompensate in other tissues due to removal or destruction of the apical meristem (e.g. Aarssen and Turkington 1987, Ward 2010). For example, damage to the apical meristem may cause an increase in lateral tissue growth (Gadd et al. 2001, Ward 2010, Perkovich and Ward 2021). We incorporated varying locations (i.e. apical vs. lateral tissue damage) and intensities (25% vs. 75% tissue removal at a given location) to analyze the effects of herbivory location and intensity on oak traits. The treatments were as follows (see also Perkovich and Ward 2021):

1. Control: No vegetation removed (5 individuals/ oak species) (Fig. 1a).
2. 25% apical removal: Removal of the dominant apical meristem and 25% apical shoot (5 individuals/species) (Fig. 1b).
3. 75% apical removal: Removal of the dominant apical meristem and 75% apical shoot (5 individuals/species) (Fig. 1c).
4. 25% lateral removal: Removal of apical meristems on lateral shoots and 25 % of lateral tissues (5 individuals/species) (Fig. 1d).
5. 75% lateral removal: Removal of apical meristems on lateral shoots and 75 % of lateral tissues (5 individuals/species) (Fig. 1e).

 

Aboveground regrowth, root mass and total non-structural carbohydrate concentrations

Saplings were harvested one year after planting and treatment application (May 2018). Aboveground tissues were separated from belowground tissues by cutting the trees at the root collar. Aboveground tissues were dried at 65 ℃ for 48 h and weighed to calculate the total aboveground biomass. We estimated aboveground biomass regrowth to determine investment in aboveground regrowth relative to root biomass. Measuring aboveground mass regrowth is especially difficult in plants as we cannot weigh the plants initially without uprooting and damaging root structure. As root structure was instrumental for this study, we therefore estimated aboveground mass regrowth as the residuals from a regression of final height and biomass (see Schulte-Hostedde et al. 2005; Peig and Green 2009) for each treatment to account for differences in growth responses between treatments. Oak roots were harvested one year after planting (May 2018), and treatment application. Dead root material was excluded from all analyses. Root samples were dried at 65 ℃ for 48 h. Root samples from individual trees were classified as either tap root, coarse root, or fine root. For this study, we considered the tap root to be the largest, central root from which subsidiary root branches developed. Coarse roots were classified as roots with a diameter > 2.0 mm, excluding the central tap root. Fine roots were roots that were < 2.0 mm in diameter (Pregitzer et al. 2002, McCormack et al. 2015). The dry mass of each root classification was measured for each individual sapling. Total root mass was calculated as the sum of all three root classes from a single individual.

After roots were dried and weighed, we took samples from coarse roots of each individual sapling and milled the dried material using a using a 2 mm mesh in a Wiley mill for analysis of non-structural carbohydrate (NSC) concentrations. For standardization, all NSC concentrations were measured using coarse-root material (McCormack et al. 2015). We used the NSC extraction protocol by Fournier (2001). In this protocol, sugars are first extracted using an ethanol wash. After several washes to remove sugars, the tissues are placed in 1% hydrochloric acid and set in a hot water bath at 100℃ for 1 h. After sugars and starches were extracted from the tissues, a phenol-sulfuric acid solvent was used to create a colorimetric reaction and measured using a microplate reader (Tomlinson et al. 2014).  All analyses were done in our laboratory to ensure the same conditions (Quentin et al. 2015; Landhäusser et al. 2018).