Mariah S. Carbone

Nonstructural Carbon in Woody Plants

Nonstructural carbon (NSC) provides the carbon and energy for plant growth and survival. In woody plants, fundamental questions about NSC remain unresolved: Is NSC storage an active or passive process? Do older NSC reserves remain accessible to the plant? How is NSC depletion related to mortality risk? Herein we review conceptual and mathematical models of NSC dynamics, recent observations and experiments at the organismal scale, and advances in plant physiology that have provided a better understanding of the dynamics of woody plant NSC. Plants preferentially use new carbon but can access decade-old carbon when the plant is stressed or physically damaged. In addition to serving as a carbon and energy source, NSC plays important roles in phloem transport, osmoregulation, and cold tolerance, but how plants regulate these competing roles and NSC depletion remains elusive. Moving forward requires greater synthesis of models and data and integration across scales from -omics to ecology.

Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees.

Nonstructural carbohydrate reserves support tree metabolism and growth when current photosynthates are insufficient, offering resilience in times of stress. We monitored stemwood nonstructural carbohydrate (starch and sugars) concentrations of the dominant tree species at three sites in the northeastern United States. We estimated the mean age of the starch and sugars in a subset of trees using the radiocarbon ((14) C) bomb spike. With these data, we then tested different carbon (C) allocation schemes in a process-based model of forest C cycling. We found that the nonstructural carbohydrates are both highly dynamic and about a decade old. Seasonal dynamics in starch (two to four times higher in the growing season, lower in the dormant season) mirrored those of sugars. Radiocarbon-based estimates indicated that the mean age of the starch and sugars in red maple (Acer rubrum) was 7-14 yr. A two-pool (fast and slow cycling reserves) model structure gave reasonable estimates of the size and mean residence time of the total NSC pool, and greatly improved model predictions of interannual variability in woody biomass increment, compared with zero- or one-pool structures used in the majority of existing models. This highlights the importance of nonstructural carbohydrates in the context of forest ecosystem carbon cycling.

Seasonal and episodic moisture controls on plant and microbial contributions to soil respiration

Moisture inputs drive soil respiration (SR) dynamics in semi-arid and arid ecosystems. However, determining the contributions of root and microbial respiration to SR, and their separate temporal responses to periodic drought and water pulses, remains poorly understood. This study was conducted in a pine forest ecosystem with a Mediterranean-type climate that receives seasonally varying precipitation inputs from both rainfall (in the winter) and fog-drip (primarily in the summer). We used automated SR measurements, radiocarbon SR source partitioning, and a water addition experiment to understand how SR, and its separate root and microbial sources, respond to seasonal and episodic changes in moisture. Seasonal changes in SR were driven by surface soil water content and large changes in root respiration contributions. Superimposed on these seasonal patterns were episodic pulses of precipitation that determined the short-term SR patterns. Warm season precipitation pulses derived from fog-drip, and rainfall following extended dry periods, stimulated the largest SR responses. Microbial respiration dominated these SR responses, increasing within hours, whereas root respiration responded more slowly over days. We conclude that root and microbial respiration sources respond differently in timing and magnitude to both seasonal and episodic moisture inputs. These findings have important implications for the mechanistic representation of SR in models and the response of dry ecosystems to changes in precipitation patterns.

Soil respiration in perennial grass and shrub ecosystems: Linking environmental controls with plant and microbial sources on seasonal and diel timescales

A mechanistic understanding of soil respiration is a major impediment to predicting terrestrial C fluxes spatially and temporally. Automated measurements of soil respiration offer the high-resolution information necessary to observe temporal variation in soil respiration, but spatially these measurements are under-represented in water-limited and non-forested ecosystems. We measured soil respiration with automated chambers over the growing season, at two sites with the same semi-arid climate, but with different dominant vegetation, perennial grasses and shrubs in the Owens Valley, CA, USA. An isotope mass balance technique was used to partition soil respiration into autotrophic and heterotrophic components at two time points, early and late growing season. Results showed large differences in the magnitude of growing season soil respiration between the two sites (910 versus 126 g C m−2 for grasses and shrubs respectively over 5 months). We attribute this to site differences in soil water availability and belowground allocation and productivity. Diel patterns of soil respiration between the two sites were similar. Temperature explained most of the diel variability in the early growing season, when soil moisture was greatest. As soil moisture declined over the growing season, diel patterns became increasingly decoupled temporally from temperature due to increased water-limitation on surface heterotrophic sources and hypothesized strong photosynthetic control over soil respiration rates. Partitioning of soil respiration into autotrophic and heterotrophic sources showed the dominance of autotrophic sources across seasons and ecosystems. However, heterotrophic respiration was more dynamic from early to late growing season, declining in the grass ecosystem; and a surprising increase in the shrub ecosystem, attributed to warming of the soil profile enhancing microbial decomposition at depth.

The model–data fusion pitfall: assuming certainty in an uncertain world

Model–data fusion is a powerful framework by which to combine models with various data streams (including observations at different spatial or temporal scales), and account for associated uncertainties. The approach can be used to constrain estimates of model states, rate constants, and driver sensitivities. The number of applications of model–data fusion in environmental biology and ecology has been rising steadily, offering insights into both model and data strengths and limitations. For reliable model–data fusion-based results, however, the approach taken must fully account for both model and data uncertainties in a statistically rigorous and transparent manner. Here we review and outline the cornerstones of a rigorous model–data fusion approach, highlighting the importance of properly accounting for uncertainty. We conclude by suggesting a code of best practices, which should serve to guide future efforts.

Distribution and mixing of old and new nonstructural carbon in two temperate trees

We know surprisingly little about whole-tree nonstructural carbon (NSC; primarily sugars and starch) budgets. Even less well understood is the mixing between recent photosynthetic assimilates (new NSC) and previously stored reserves. And, NSC turnover times are poorly constrained. We characterized the distribution of NSC in the stemwood, branches, and roots of two temperate trees, and we used the continuous label offered by the radiocarbon (carbon-14, 14C) bomb spike to estimate the mean age of NSC in different tissues. NSC in branches and the outermost stemwood growth rings had the 14C signature of the current growing season. However, NSC in older aboveground and belowground tissues was enriched in 14C, indicating that it was produced from older assimilates. Radial patterns of 14C in stemwood NSC showed strong mixing of NSC across the youngest growth rings, with limited ‘mixing in’ of younger NSC to older rings. Sugars in the outermost five growth rings, accounting for two-thirds of the stemwood pool, had a mean age < 1 yr, whereas sugars in older growth rings had a mean age > 5 yr. Our results are thus consistent with a previously-hypothesized two-pool (‘fast’ and ‘slow’ cycling NSC) model structure. These pools appear to be physically distinct.

Cloud shading and fog drip influence the metabolism of a coastal pine ecosystem

Assessing the ecological importance of clouds has substantial implications for our basic understanding of ecosystems and for predicting how they will respond to a changing climate. This study was conducted in a coastal Bishop pine forest ecosystem that experiences regular cycles of stratus cloud cover and inundation in summer. Our objective was to understand how these clouds impact ecosystem metabolism by contrasting two sites along a gradient of summer stratus cover. The site that was under cloud cover ~15% more of the summer daytime hours had lower air temperatures and evaporation rates, higher soil moisture content, and received more frequent fog drip inputs than the site with less cloud cover. These cloud-driven differences in environmental conditions translated into large differences in plant and microbial activity. Pine trees at the site with greater cloud cover exhibited less water stress in summer, larger basal area growth, and greater rates of sap velocity. The difference in basal area growth between the two sites was largely due to summer growth. Microbial metabolism was highly responsive to fog drip, illustrated by an observed ~3-fold increase in microbial biomass C with increasing summer fog drip. In addition, the site with more cloud cover had greater total soil respiration and a larger fractional contribution from heterotrophic sources. We conclude that clouds are important to the ecological functioning of these coastal forests, providing summer shading and cooling that relieve pine and microbial drought stress as well as regular moisture inputs that elevate plant and microbial metabolism. These findings are important for understanding how these and other seasonally dry coastal ecosystems will respond to predicted changes in stratus cover, rainfall, and temperature.

Radiocarbon in Terrestrial Systems

This chapter focuses on how radiocarbon (14C) is used both as a tracer of source pools and for determining age on multiple time scales, providing a powerful approach for understanding the dynamics of terrestrial ecosystems. A range of applications is introduced, from estimating the lifespan of whole organisms to using the age of respired carbon (C) to partition sources of respired CO2. This chapter also provides examples that apply models introduced in Chapter 3 to the soil organic C pool. Lastly, this chapter introduces several new 14C approaches including low-level labeling to understand C cycling processes occurring on shorter time scales from minutes to months.