Ecohydrological Controls on Grass and Shrub Above-ground Net Primary Productivity in a Seasonally Dry Climate

Seasonally dry, water‐limited regions are often co‐dominated by distinct herbaceous and woody plant communities with contrasting ecohydrological properties. We investigated the shape of the above‐ground net primary productivity (ANPP) response to annual precipitation (Pa) for adjacent grassland and shrubland ecosystems in Southern California, with the goal of understanding the role of these ecohydrological properties on ecosystem function. Our synthesis of observations and modelling demonstrates grassland and shrubland exhibit distinct ANPP‐Pa responses that correspond with characteristics of the long‐term Pa distribution and mean water balance fluxes. For annual grassland, no ANPP occurs below a ‘precipitation compensation point,’ where bare soil evaporation dominates the water balance, and ANPP saturates above the Pawhere deep percolation and runoff contribute to the modelled water balance. For shrubs, ANPP increases at a lower and relatively constant rate across the Pa gradient, while deep percolation and runoff account for a smaller fraction of the modelled water balance. We identify precipitation seasonality, root depth, and water stress sensitivity as the main ecosystem properties controlling these responses. Observed ANPP‐Paresponses correspond to notably different patterns of rain‐use efficiency (RUE). Grass RUE exceeds shrub RUE over a wide range of typical Pa values, whereas grasses and shrubs achieve a similar RUE in particularly dry or wet years. Inter‐annual precipitation variability, and the concomitant effect on ANPP, plays a critical role in maintaining the balance of grass and shrub cover and ecosystem‐scale productivity across this landscape

TCP Final Report: Measuring the Effects of Stand Age and Soil Drainage on Boreal Forest

This was a 6-year research project in the Canadian boreal forest that focused on using field observations to understand how boreal forest carbon balance changes during recovery from catastrophic forest fire. The project began with two overarching goals: (1) to develop techniques that would all the year round operation of 7 eddy covariance sites in a harsh environment at a much lower cost than had previously been possible, and (2) to use these measurements to determine how carbon balance changes during secondary succession. The project ended in 2006, having accomplished its primary objectives. Key contributions to DOE during the study were: (1) Design, test, and demonstrate a lightweight, fully portable eddy flux system that exploits several economies of scale to allow AmeriFlux-quality measurements of CO{sub 2} exchange at many sites for a large reduction in cost (Goulden et al. 2006). (2) Added seven year-round sites to AmeriFlux, at a relatively low per site cost using the Eddy Covariance Mesonet approach (Goulden et al. 2006). These data are freely available on the AmeriFlux web site. (3) Tested and rejected the conventional wisdom that forests lose large amounts of carbon during the first decade after disturbance, then accumulate large amounts of carbon for {approx}several decades, and then return to steady state in old age. Rather, we found that boreal forests recovers quickly from fire and begins to accumulate carbon within {approx}5 years after disturbance. Additionally, we found no evidence that carbon accumulation declines in old stands (Goulden et al. 2006, Goulden et al. in prep). (4) Tested and rejected claims based on remote sensing observations (for example, Myneni et al 1996 using AVHRR) that regions of boreal forest have changed markedly in the last 20 years. Rather, we assembled a much richer data set than had been used in the past (eddy covariance observations, tree rings, biomass, NPP, AVHRR, and LandSat), which we used to establish that the forests in our study region have remained largely constant over the last 20 years after accounting for the effects of stand age and succession (McMillen et al. in review)

Predicting the effects of climate change on water yield and forest production in the northeastern United States

Rapid and simultaneous changes in temperature, precipitation and the atmospheric concentration of CO2 are predicted to occur over the next century. Simple, well-validated models of ecosystem function are required to predict the effects of these changes. This paper describes an improved version of a forest carbon and water balance model (PnET-II) and the application of the model to predict stand- and regional-level effects of changes in temperature, precipitation and atmospheric CO2 concentration. PnET-II is a simple, generalized, monthly time-step model of water and carbon balances (gross and net) driven by nitrogen availability as expressed through foliar N concentration. Improvements from the original model include a complete carbon balance and improvements in the prediction of canopy phenology, as well as in the computation of canopy structure and photosynthesis. The model was parameterized and run for 4 forest/site combinations and validated against available data for water yield, gross and net carbon exchange and biomass production. The validation exercise suggests that the determination of actual water availability to stands and the occurrence or non-occurrence of soil-based water stress are critical to accurate modeling of forest net primary production (NPP) and net ecosystem production (NEP). The model was then run for the entire NewEngland/New York (USA) region using a 1 km resolution geographic information system. Predicted long-term NEP ranged from -85 to +275 g C m-2 yr-1 for the 4 forest/site combinations, and from -150 to 350 g C m-2 yr-1 for the region, with a regional average of 76 g C m-2 yr-1. A combination of increased temperature (+6*C), decreased precipitation (-15%) and increased water use efficiency (2x, due to doubling of CO2) resulted generally in increases in NPP and decreases in water yield over the region

Evolutionary Responses of Invasive Grass Species to Variation in Precipitation and Soil Nitrogen

1.Global climate models suggest that many ecosystems will experience reduced precipitation over the next century and the consequences for invasive plant performance are largely unknown. Annual invasive species may be able to quickly evolve traits associated with drought escape or tolerance through rapid genetic changes. 2.We investigated the influence of five years of water and nitrogen manipulations on trait values in a southern California grassland system. Seeds from two annual grass species (Avena barbata, Bromus madritensis) were collected from experimental plots and grown in a common environment over two generations. We measured 14 physiological, morphological, phenological, and reproductive traits. 3.Both species displayed phenotypic differences depending on the water treatment from which they were collected, but not depending on the nitrogen treatment. Both species displayed trait values characteristic of drought escape (e.g., earlier flowering in A. barbata and B. madritensis, lower water-use efficiency in B. madritensis) when grown from seeds collected from plots that experienced five years of reduced precipitation. Furthermore, A. barbata individuals grown from seeds collected from drought plots had higher reproductive output and higher photosynthetic performance than individuals grown from water addition plots, with individuals grown from ambient plots displaying intermediate trait values. Notably, we found no phenotypic variation among treatments for six root traits. 4.Synthesis. Trait differences were observed following two generations in a common garden, suggesting that treatment differences were genetically based. This suggests that populations were responding to selection over the five years of water manipulations, a remarkably short time period. The rapid evolutionary responses observed here may help these two widespread invasive grass species thrive under reduced precipitation scenarios, which could have important implications for fire dynamics, invasive species management, and native plant restoration in communities invaded by annual grasses

Predicting Postfire Sediment Yields of Small Steep Catchments Using Airborne Lidar Differencing

Predicting sediment yield from recently burned areas remains a challenge but is important for hazard and resource management as wildfire impacts increase. Here we use lidar-based monitoring of two fires in southern California, USA to study the movement of sediment during pre-rainfall periods and postfire periods of flooding and debris flows over multiple storm events. Using a data-driven approach, we examine the relative importance of terrain, vegetation, burn severity, and rainfall amounts through time on sediment yield. We show that incipient fire-activated dry sediment loading and pre-fire colluvium were rapidly flushed out by debris flows and floods but continued erosion occurred later in the season from soil erosion and, in ∼9% of catchments, from shallow landslides. Based on these observations, we develop random forest regression models to predict dry ravel and incipient runoff-driven sediment yield applicable to small steep headwater catchments in southern California

Radiative forcing of natural forest disturbances

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate-regulating properties of forests. Using both tower-based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane-damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models

Ecological research in the Large Scale Biosphere Atmosphere Experiment in Amazonia: A discussion of early results

The Large-scale Biosphere–Atmosphere Experiment in Amazonia (LBA) is a multinational, interdisciplinary research program led by Brazil. Ecological studies in LBA focus on how tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in the Amazon region. Early results from ecological studies within LBA emphasize the variability within the vast Amazon region and the profound effects that land-use and land-cover changes are having on that landscape. The predominant land cover of the Amazon region is evergreen forest; nonetheless, LBA studies have observed strong seasonal patterns in gross primary production, ecosystem respiration, and net ecosystem exchange, as well as phenology and tree growth. The seasonal patterns vary spatially and interannually and evidence suggests that these patterns are driven not only by variations in weather but also by innate biological rhythms of the forest species. Rapid rates of deforestation have marked the forests of the Amazon region over the past three decades. Evidence from ground-based surveys and remote sensing show that substantial areas of forest are being degraded by logging activities and through the collapse of forest edges. Because forest edges and logged forests are susceptible to fire, positive feedback cycles of forest degradation may be initiated by land-use-change events. LBA studies indicate that cleared lands in the Amazon, once released from cultivation or pasture usage, regenerate biomass rapidly. However, the pace of biomass accumulation is dependent upon past land use and the depletion of nutrients by unsustainable land-management practices. The challenge for ongoing research within LBA is to integrate the recognition of diverse patterns and processes into general models for prediction of regional ecosystem function

Evolutionary responses of invasive grass species to variation in precipitation and soil nitrogen

1.Global climate models suggest that many ecosystems will experience reduced precipitation over the next century and the consequences for invasive plant performance are largely unknown. Annual invasive species may be able to quickly evolve traits associated with drought escape or tolerance through rapid genetic changes. 2.We investigated the influence of five years of water and nitrogen manipulations on trait values in a southern California grassland system. Seeds from two annual grass species (Avena barbata, Bromus madritensis) were collected from experimental plots and grown in a common environment over two generations. We measured 14 physiological, morphological, phenological, and reproductive traits. 3.Both species displayed phenotypic differences depending on the water treatment from which they were collected, but not depending on the nitrogen treatment. Both species displayed trait values characteristic of drought escape (e.g., earlier flowering in A. barbata and B. madritensis, lower water-use efficiency in B. madritensis) when grown from seeds collected from plots that experienced five years of reduced precipitation. Furthermore, A. barbata individuals grown from seeds collected from drought plots had higher reproductive output and higher photosynthetic performance than individuals grown from water addition plots, with individuals grown from ambient plots displaying intermediate trait values. Notably, we found no phenotypic variation among treatments for six root traits. 4.Synthesis. Trait differences were observed following two generations in a common garden, suggesting that treatment differences were genetically based. This suggests that populations were responding to selection over the five years of water manipulations, a remarkably short time period. The rapid evolutionary responses observed here may help these two widespread invasive grass species thrive under reduced precipitation scenarios, which could have important implications for fire dynamics, invasive species management, and native plant restoration in communities invaded by annual grasses

Looking deeper into the soil : biophysical controls and seasonal lags of soil CO2 production and efflux

Author Posting. © Ecological Society of America, 2010. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 20 (2010): 1569–1582, doi:10.1890/09-0693.1.We seek to understand how biophysical factors such as soil temperature (Ts), soil moisture (θ), and gross primary production (GPP) influence CO2 fluxes across terrestrial ecosystems. Recent advancements in automated measurements and remote-sensing approaches have provided time series in which lags and relationships among variables can be explored. The purpose of this study is to present new applications of continuous measurements of soil CO2 efflux (F0) and soil CO2 concentrations measurements. Here we explore how variation in Ts, θ, and GPP (derived from NASA's moderate-resolution imaging spectroradiometer [MODIS]) influence F0 and soil CO2 production (Ps). We focused on seasonal variation and used continuous measurements at a daily timescale across four vegetation types at 13 study sites to quantify: (1) differences in seasonal lags between soil CO2 fluxes and Ts, θ, and GPP and (2) interactions and relationships between CO2 fluxes with Ts, θ, and GPP. Mean annual Ts did not explain annual F0 and Ps among vegetation types, but GPP explained 73% and 30% of the variation, respectively. We found evidence that lags between soil CO2 fluxes and Ts or GPP provide insights into the role of plant phenology and information relevant about possible timing of controls of autotrophic and heterotrophic processes. The influences of biophysical factors that regulate daily F0 and Ps are different among vegetation types, but GPP is a dominant variable for explaining soil CO2 fluxes. The emergence of long-term automated soil CO2 flux measurement networks provides a unique opportunity for extended investigations into F0 and Ps processes in the near future.Data collection was possible thanks to NASA, the NSF Center for Embedded Networked Sensing (CCR-0120778), DOE (DE-FG02-03ER63638), CONACyT, UCMEXUS, NSF (EF-0410408), NSF-LTER, KAKENHI (12878089 and 13480150), the Academy of Finland (213093), the Austrian Science Fund (FWF, P18756-B16), the Kearney Foundation, the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS), and the Natural Science and Engineering Research Council of Canada (NSERC). R. Vargas was supported by grant DEB-0639235 during the preparation of this manuscript

Predicting gross primary productivity in terrestrial ecosystems

Abstract. Our goal was to construct a simple, highly aggregated model, driven by easily available data sets, that accurately predicted terrestrial gross primary productivity (GPP; carboxylation plus oxygenation) in diverse environments and ecosystems. Our starting point was a fine-scale, multilayer model of half-hourly canopy processes that has been parametrized for Harvard Forest, Massachusetts. Over varied growing season conditions, this fine-scale model predicted hourly carbon and latent energy fluxes that were in good agreement with data from eddy covariance studies. Using an heuristic process, we derived a simple aggregated set of equations operating on cumulative or average values of the most sensitive driving variables (leaf area index, mean foliar N concentration, canopy height, average daily temperature and temperature range, atmospheric transmittance, latitude, day of year, atmospheric CO 2 concentration, and an index of soil moisture). We calibrated the aggregated model to provide estimates of GPP similar to those of the fine-scale model across a wide range of these driving variables. Our calibration across this broad range of conditions captured 96% of fine-scale model behavior, but was computationally many orders of magnitude faster. We then tested the assumptions we had made in generating the aggregated model by applying it in different ecosystems. Using the same parameter values derived for Harvard Forest, the aggregated model made sound predictions of GPP for wetsedge tundra in the Arctic under a variety of experimental manipulations, and also for a range of forest types across the OTTER (Oregon Transect Ecosystem Research) transect in Oregon, running from coastal Sitka spruce to high-plateau mountain juniper