Physiological trait networks enhance understanding of crop growth and water use in contrasting environments

Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential ("risky" stomatal regulation), high xylem hydraulic conductivity and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance and low stomatal conductance at low leaf water potential ("conservative" stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits, soil characteristics and their interactions (i.e., networks), has potential to improve our understanding of crop performance in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.

Plant traits related to precipitation sensitivity of species and communities in semiarid shortgrass prairie

Understanding how plant communities respond to temporal patterns of precipitation in water-limited ecosystems is necessary to predict interannual variation and trends in ecosystem properties, including forage production, biogeochemical cycling, and biodiversity. In North American shortgrass prairie, we measured plant abundance, functional traits related to growth rate and drought tolerance, and aboveground net primary productivity to identify: species-level responsiveness to precipitation (precipitation sensitivity S_spp ) across functional groups; S_spp relationships to continuous plant traits; and whether continuous trait-S_spp relationships scaled to the community level. Across 32 plant species, we found strong bivariate relationships of both leaf dry matter content (LDMC) and leaf osmotic potential Ψ_osm with S_spp . Yet, LDMC and specific leaf area were retained in the lowest Akaike information criterion multiple regression model, explaining 59% of S_spp . Most relationships between continuous traits and S_spp scaled to the community level but were often contingent on the presence/absence of particular species and/or land management at a site. Thus, plant communities in shortgrass prairie may shift towards slower growing, more stress-resistant species in drought years and/or chronically drier climate. These findings highlight the importance of both leaf economic and drought tolerance traits in determining species and community responses to altered precipitation.

Using nocturnal cold air drainage flow to monitor ecosystem processes in complex terrain

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal was to investigate the potential for using nocturnal down-valley winds (cold air drainage) for monitoring ecosystem processes in mountainous terrain from two perspectives: measurements of the isotopic composition of ecosystem-respired CO2 (delta13C(ER)) and estimates of fluxes of CO2 transported in the drainage flow. To test if this approach is plausible, we monitored the wind patterns, CO2 concentrations, and the carbon isotopic composition of the air as it exited the base of a young (approximately 40 yr-old) and an old (>450 yr-old) steeply sided Douglas-fir watershed. Nocturnal cold air drainage within these watersheds was strong, deep, and occurred on more than 80% of summer nights. The depth of cold air drainage rapidly increased to tower height or greater when the net radiation at the top of the tower approached zero. The carbon isotope composition of CO2 in the drainage system holds promise as an indicator of variation in basin-scale physiological processes. Although there was little vertical variation in CO2 concentration at any point in time, we found that the range of CO2 concentration over a single evening was sufficient to estimate delta 13C(ER) from Keeling plot analyses. The seasonal variation in delta 13C(ER) followed expected trends: during the summer dry season delta 13C(ER) became less negative (more enriched in 13C), but once rain returned in the fall, delta 13C(ER) decreased. However, we found no correlation between recent weather (e.g., vapor pressure deficit) and delta 13C(ER) either concurrently or with up to a one-week lag. Preliminary estimates suggest that the nocturnal CO2 flux advecting past the 28-m tower is a rather small fraction (<20%) of the watershed-scale respiration. This study demonstrates that monitoring the isotopic composition and CO2 concentration of cold air drainage at the base of a watershed provides a new tool for quantifying ecosystem metabolism in mountainous ecosystems on the basin scale.