Diego A. Riveros-Iregui

Differential soil respiration responses to changing hydrologic regimes

[1] Soil respiration is tightly coupled to the hydrologic cycle (i.e., snowmelt and precipitation timing and magnitude). We examined riparian and hillslope soil respiration across a wet (2005) and a dry (2006) growing season in a subalpine catchment. When comparing the riparian zones, cumulative CO 2 efflux was 33% higher, and peak efflux occurred 17 days earlier during the dry growing season. In contrast, cumulative efflux in the hillslopes was 8% lower, and peak efflux occurred 10 days earlier during the drier growing season. Our results demonstrate that soil respiration was more sensitive to drier growing season conditions in wet (riparian) landscape positions.

Dynamic interactions of ecohydrological and biogeochemical processes in water‐limited systems

Water is the essential reactant, catalyst, or medium for many biogeochemical reactions, thus playing an important role in the activation and deactivation of biogeochemical processes. The coupling between hydrological and biogeochemical processes is particularly evident in water-limited arid and semi-arid environments, but also in areas with strong seasonal precipitation patterns (e.g., Mediterranean) or in mesic systems during droughts. Moreover, this coupling is apparent at all levels in the ecosystems—from soil microbial cells to whole plants to landscapes. Identifying and quantifying the biogeochemical “hot spots” and “hot moments”, the underlying hydrological drivers, and how disturbance-induced vegetation transitions affect the hydrological-biogeochemical interactions are challenging because of the inherent complexity of these interactions, thus requiring interdisciplinary approaches. At the same time, a holistic approach is essential to fully understand function and processes in water-limited ecosys...

Antecedent Moisture Controls on Stream Nitrate Flux in an Agricultural Watershed

Evaluating nitrate-N fluxes from agricultural landscapes is inherently complex due to the wide range of intrinsic and dynamic controlling variables. In this study, we investigate the influence of contrasting antecedent moisture conditions on nitrate-N flux magnitude and dynamics in a single agricultural watershed on intra-annual and rainfall-event temporal scales. High temporal resolution discharge and nitrate concentration data were collected to evaluate nitrate-N flux magnitude associated with wet (2009) and dry (2012) conditions. Analysis of individual rainfall events revealed a marked and consistent difference in nitrate-N flux response attributed to wet/dry cycles. Large-magnitude dilutions (up to 10 mg N L) persisted during the wet antecedent conditions (2009), consistent with a dominant baseflow contribution and excess groundwater release in relation to precipitation volume (discharge > > precipitation). Smaller-magnitude concentrations (<7 mg N L) were observed during the drought conditions of 2012, consistent with a quickflow-dominated response to rain events and infiltration/storage of precipitation resulting in discharge < precipitation. Nitrate-N loads and yields from the watershed were much higher (up to an order of magnitude) in the wet year vs. the dry year. Our results suggest that the response of nitrate-N loading to rain events is highly dependent on intra-annual antecedent moisture conditions and subsurface hydrologic connectivity, which together dictate the dominant hydrologic pathways for stream recharge. Additionally, the results of our study indicate that continued pronounced wet/dry cycles may become more dominant as the short-term driver of future nitrate-N exports.

Modeling whole‐tree carbon assimilation rate using observed transpiration rates and needle sugar carbon isotope ratios

*Understanding controls over plant-atmosphere CO(2) exchange is important for quantifying carbon budgets across a range of spatial and temporal scales. In this study, we used a simple approach to estimate whole-tree CO(2) assimilation rate (A(Tree)) in a subalpine forest ecosystem. *We analysed the carbon isotope ratio (delta(13)C) of extracted needle sugars and combined it with the daytime leaf-to-air vapor pressure deficit to estimate tree water-use efficiency (WUE). The estimated WUE was then combined with observations of tree transpiration rate (E) using sap flow techniques to estimate A(Tree). Estimates of A(Tree) for the three dominant tree species in the forest were combined with species distribution and tree size to estimate and gross primary productivity (GPP) using an ecosystem process model. *A sensitivity analysis showed that estimates of A(Tree) were more sensitive to dynamics in E than delta(13)C. At the ecosystem scale, the abundance of lodgepole pine trees influenced seasonal dynamics in GPP considerably more than Engelmann spruce and subalpine fir because of its greater sensitivity of E to seasonal climate variation. *The results provide the framework for a nondestructive method for estimating whole-tree carbon assimilation rate and ecosystem GPP over daily-to weekly time scales.

On the spatial heterogeneity of net ecosystem productivity in complex landscapes

Micrometeorological flux towers provide spatially integrated estimates of net ecosystem production (NEP) of carbon over areas ranging from several hectares to several square kilometers, but they do so at the expense of spatially explicit information within the footprint of the tower. This finer-scale information is crucial for understanding how physical and biological factors interact and give rise to tower-measured fluxes in complex landscapes. We present a simple approach for quantifying and evaluating the spatial heterogeneity of cumulative growing season NEP for complex landscapes. Our method is based on spatially distributed information about physical and biological landscape variables and knowledge of functional relationships between constituent fluxes and these variables. We present a case study from a complex landscape in the Rocky Mountains of Montana (US) to demonstrate that the spatial distribution of cumulative growing season NEP is rather large and bears the imprint of the topographic and vegetation variables that characterize this complex landscape. Net carbon sources and net carbon sinks were distributed across the landscape in manner predictable by the intersection of these landscape variables. We simulated year-to-year climate variability and found that some portions of the landscape were consistently either carbon sinks or carbon sources, but other portions transitioned between sink and source. Our findings reveal that this emergent behavior is a unique characteristic of complex landscapes derived from the interaction of topography and vegetation. These findings offer new insight for interpreting spatially integrated carbon fluxes measured over complex landscapes.

Life in the clouds: are tropical montane cloud forests responding to changes in climate?

The humid tropics represent only one example of the many places worldwide where anthropogenic disturbance and climate change are quickly affecting the feedbacks between water and trees. In this article, we address the need for a more long-term perspective on the effects of climate change on tropical montane cloud forests (TMCF) in order to fully assess the combined vulnerability and long-termresponse of tropical trees to changes in precipitation regimes, including cloud immersion. We first review the ecophysiological benefits that cloud water interception offers to trees in TMCF and then examine current climatological evidence that suggests changes in cloud base height and impending changes in cloud immersion for TMCF. Finally, we propose an experimental approach to examine the long-term dynamics of tropical trees in TMCF in response to environmental conditions on decade-to-century time scales. This information is important to assess the vulnerability and long-term response of TMCF to changes in cloud cover and fog frequency and duration.

A simple framework to estimate distributed soil temperature from discrete air temperature measurements in data-scarce regions

Soil temperature is a key control on belowground chemical and biological processes. Typically, models of soil temperature are developed and validated for large geographic regions. However, modeling frameworks intended for higher spatial resolutions (much finer than 1 km2) are lacking across areas of complex topography. Here we propose a simple modeling framework for predicting distributed soil temperature at high temporal (i.e., 1 h steps) and spatial (i.e., 5 × 5 m) resolutions in mountainous terrain, based on a few discrete air temperature measurements. In this context, two steps were necessary to estimate the soil temperature. First, we applied the potential temperature equation to generate the air temperature distribution from a 5 m digital elevation model and Inverse Distance Weighting interpolation. Second, we applied a hybrid model to estimate the distribution of soil temperature based on the generated air temperature surfaces. Our results show that this approach simulated the spatial distribution of soil temperature well, with a root-mean-square error ranging from ~2.1 to 2.9°C. Furthermore, our approach predicted the daily and monthly variability of soil temperature well. The proposed framework can be applied to estimate the spatial variability of soil temperature in mountainous regions where direct observations are scarce.

Optimizing Sampling Strategies for Riverine Nitrate Using High-Frequency Data in Agricultural Watersheds

Understanding linked hydrologic and biogeochemical processes such as nitrate loading to agricultural streams requires that the sampling bias and precision of monitoring strategies be known. An existing spatially distributed, high-frequency nitrate monitoring network covering ∼40% of Iowa provided direct observations of in situ nitrate concentrations at a temporal resolution of 15 min. Systematic subsampling of nitrate records allowed for quantification of uncertainties (bias and precision) associated with estimates of various nitrate parameters, including: mean nitrate concentration, proportion of samples exceeding the nitrate drinking water standard (DWS), peak (>90th quantile) nitrate concentration, and nitrate flux. We subsampled continuous records for 47 site-year combinations mimicking common, but labor-intensive, water-sampling regimes (e.g., time-interval, stage-triggered, and dynamic-discharge storm sampling). Our results suggest that time-interval sampling most efficiently characterized all nitrate parameters, except at coarse frequencies for nitrate flux. Stage-triggered storm sampling most precisely captured nitrate flux when less than 0.19% of possible 15 min observations for a site-year were used. The time-interval strategy had the greatest return on sampling investment by most precisely and accurately quantifying nitrate parameters per sampling effort. These uncertainty estimates can aid in designing sampling strategies focused on nitrate monitoring in the tile-drained Midwest or similar agricultural regions.

Is pretenure interdisciplinary research a career risk

Despite initiatives to promote interdisciplinary research, early-career academics continue to perceive professional risks to working at the interface between traditional disciplines. Unexpectedly, the inherent practical challenges of interdisciplinary scholarship, such as new methodologies and lexicons, are not the chief source of the perceived risk. The perception of risk is pervasive across disciplines, and it persists despite efforts to support career development for individuals with common interests [Mitchell and Weiler, 2011]. Suggestions that interdisciplinary work can go unrewarded in academia [Clark et al., 2011] foster a concern that targeting interdisciplinary questions, such as those presented by climate change, will pose problems for acquiring and succeeding in a tenure-track position. If self-preservation limits the questions posed by early-career academics, a perceived career risk is as damaging as a real one to new transdisciplinary initiatives. Thus, institutions should address the source of this perception whether real or specious.

Spatial and seasonal variabilities of the stable carbon isotope composition of soil CO2 concentration and flux in complex terrain

Biogeochemical processes driving the spatial variability of soil CO2 production and flux are well studied, but little is known about the variability in the spatial distribution of the stable carbon isotopes that make up soil CO2, particularly in complex terrain. Spatial differences in stable isotopes of soil CO2 could indicate fundamental differences in isotopic fractionation at the landscape level and may be useful to inform modeling of carbon cycling over large areas. We measured the spatial and seasonal variabilities of the δ13C of soil CO2 (δS) and the δ13C of soil CO2 flux (δP) in a subalpine forest ecosystem located in the Rocky Mountains of Montana. We found consistently more isotopically depleted values of δS and δP in low and wet areas of the landscape relative to steep and dry areas. Our results suggest that the spatial patterns of δS and δP are strongly mediated by soil water and soil respiration rate. More interestingly, our analysis revealed different temporal trends in δP across the landscape; in high landscape positions δP became more positive, whereas in low landscape positions δP became more negative with time. These trends might be the result of differential dynamics in the seasonality of soil moisture and its effects on soil CO2 production and flux. Our results suggest concomitant yet independent effects of water on physical (soil gas diffusivity) and biological (photosynthetic discrimination) processes that mediate δS and δP and are important when evaluating the δ13C of CO2 exchanged between soils and the atmosphere in complex terrain.