Different clades and traits yield similar grassland functional responses

Abstract

Plant functional traits are viewed as key to predicting important ecosystem and community properties across resource gradients within and among biogeographic regions. Vegetation dynamics and ecosystem processes, such as aboveground net primary productivity (ANPP), are increasingly being modeled as a function of the quantitative traits of species, which are used as proxies for photosynthetic rates and nutrient and water-use efficiency. These approaches rely on an assumption that a certain trait value consistently confers a specific function or response under given environmental conditions. Here, we provide a critical test of this idea and evaluate whether the functional traits that drive the well-known relationship between precipitation and ANPP differ between systems with distinct biogeographic histories and species assemblages. Specifically, we compared grasslands spanning a broad precipitation gradient (∼200-1,000 mm/y) in North America and South Africa that differ in the relative representation and abundance of grass phylogenetic lineages. We found no significant difference between the regions in the positive relationship between annual precipitation and ANPP, yet the trait values underlying this relationship differed dramatically. Our results challenge the trait-based approach to predicting ecosystem function by demonstrating that different combinations of functional traits can act to maximize ANPP in a given environmental setting. Further, we show the importance of incorporating biogeographic and phylogenetic history in predicting community and ecosystem properties using traits.functional traits | grasslands | phylogenetics | ecosystem function | biogeography N et primary productivity (NPP), or the biomass produced by the conversion of CO 2 via photosynthesis minus that lost to respiration, is a fundamental link between the atmosphere and the biosphere. Understanding and predicting the drivers of terrestrial NPP is of the utmost importance, especially for grasslands, which cover more than 40% of terrestrial land surface, constitute upwards of 30% of terrestrial gross primary productivity (1, 2), and are responsible for important ecosystem services such as carbon sequestration and forage production. Precipitation is the primary driver of variation in aboveground NPP (ANPP) in grasslands across broad spatial scales (3-6), and a consistent relationship has been observed between ANPP and precipitation across biogeographic regions (7). However, our understanding of the factors that underlie this emergent pattern remain limited.Recently, ecosystem processes, including ANPP, have been modeled as a function of the quantitative traits of organisms that reflect adaptations to environmental variation, and are often proxies for photosynthetic rates, and nutrient and water-use efficiency (8-11). Although these approaches are promising, they rely on the assumption that a certain trait value confers a specific function or response in a given environment, regardless of differences among species in other traits or interacti...

Trait selection and community weighting are key to understanding ecosystem responses to changing precipitation regimes

“…Commonly measured plant traits (e.g. SLA, plant height, leaf N) have been successfully used to predict plant growth and NPP dynamics (Díaz & Cabido, ; Díaz et al., ; ; Forrestel et al., ; Garnier et al., ; Reich, ; van der Sande et al., ), yet often do not align with gradients in water availability (Wright et al., ). We attribute these weak trait–precipitation relationships to an improper selection of traits.…”

“…But as noted above, most commonly measured plant traits do not align well with precipitation gradients. For instance, mean annual precipitation (MAP) explained <1% of the global variance in SLA (leaf area to dry mass ratio—correlated with maximum photosynthetic rate) across biomes (Wright et al., ) and was not significantly related to SLA within grasslands (Forrestel et al., ). Furthermore, the combination of several climatic variables (mean annual temperature, MAP, vapour pressure deficit and solar irradiance) explained <20% of the variance in five functional traits related to resource acquisition strategies (Reich, Wright, & Lusk, ).…”

“…Anatomical traits related to hydraulic transport and water‐use efficiency, such as stomatal pore index (SPI; % of leaf area composed of stomata; Sack, Cowan, Jaikumar, & Holbrook, ), can be easily measured at the community level as samples can be collected and preserved for later trait determination. Indeed, recent work suggests that community‐weighted SPI is well correlated with MAP across both herbaceous and woody‐dominated ecosystems and is linked to spatial variation in NPP (Forrestel et al., ; Liu et al., ; Figure ). These findings suggest that SPI, and other anatomical traits linked to hydraulic function, are promising trait candidates for predicting NPP responses to chronic alterations in water availability (Suding et al., ; Smith et al., ; Figure ).…”

“…Relationships between mean annual precipitation (MAP) and community‐weighted stomatal pore index (SPI; % of leaf area composed of stomata) in herbaceous‐dominated (South African [●] and North American [▲] grasslands; Forrestel et al., ) and woody‐dominated communities [○] (temperate to tropic forests in China; Liu et al., ). Stomatal pore index is an anatomical index of maximum stomatal conductance and plant water‐use efficiency.…”

“…Community‐weighted SPI is a likely candidate for determining broad‐scale trait–precipitation relationships, although its interpretation may change depending on ecosystem type (woody‐ vs. herbaceous‐dominated). Plotted data taken from Forrestel et al., and Liu et al., (note: axes for MAP and SPI are not to the same scale for each study)…”