Oak forest carbon and water simulations:Model intercomparisons and evaluations against independent data

Models represent our primary method for integration of small-scale, process-level phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the evaluation of 13 stand-level models varying in their spatial, mechanistic, and temporal complexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons were obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiological processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions

Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California

Understanding how environmental variables affect the processes that regulate the carbon flux over grassland is critical for large-scale modeling research, since grasslands comprise almost one-third of the earth's natural vegetation. To address this issue, fluxes of CO{sub 2} (F{sub c}, flux toward the surface is negative) were measured over a Mediterranean, annual grassland in California, USA for 2 years with the eddy covariance method. To interpret the biotic and abiotic factors that modulate F{sub c} over the course of a year we decomposed net ecosystem CO{sub 2} exchange into its constituent components, ecosystem respiration (R{sub eco}) and gross primary production (GPP). Daytime R{sub eco} was extrapolated from the relationship between temperature and nighttime F{sub c} under high turbulent conditions. Then, GPP was estimated by subtracting daytime values of F{sub c} from daytime estimates of R{sub eco}. Results show that most of carbon exchange, both photosynthesis and respiration, was limited to the wet season (typically from October to mid-May). Seasonal variations in GPP followed closely to changes in leaf area index, which in turn was governed by soil moisture, available sunlight and the timing of the last frost. In general, R{sub eco} was an exponential function of soil temperature, but with season-dependent values of Q{sub 10}. The temperature-dependent respiration model failed immediately after rain events, when large pulses of R{sub eco} were observed. Respiration pulses were especially notable during the dry season when the grass was dead and were the consequence of quickly stimulated microbial activity. Integrated values of GPP, R{sub eco}, and net ecosystem exchange (NEE) were 867, 735, and -132g C m{sup -2}, respectively, for the 2000-2001 season, and 729, 758, and 29g C m{sup -2} for the 2001-2002 season. Thus, the grassland was a moderate carbon sink during the first season and a weak carbon source during the second season. In contrast to a well-accepted view that annual production of grass is linearly correlated to precipitation, the large difference in GPP between the two seasons were not caused by the annual precipitation. Instead, a shorter growing season, due to late start of the rainy season, was mainly responsible for the lower GPP in the second season. Furthermore, relatively higher R{sub eco} during the non-growing season occurred after a late spring rain. Thus, for this Mediterranean grassland, the timing of rain events had more impact than the total amount of precipitation on ecosystem GPP and NEE. This is because its growing season is in the cool and wet season when carbon uptake and respiration are usually limited by low temperature and sometimes frost, not by soil moisture

On the use of MODIS EVI to assess gross primary productivity of North American ecosystems

[1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote‐sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote‐sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote‐sensing data

Protecting climate with forests

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects-avoided deforestation, forest restoration, and afforestation-provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive

The future of evapotranspiration : global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources

The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with changes in drought frequency and intensity on the distribution and timing of water availability. The development of effective adaptation strategies for these emerging threats to food and water security are compromised by limitations in our understanding of how natural and managed ecosystems are responding to changing hydrological and climatological regimes. This information gap is exacerbated by insufficient monitoring capabilities from local to global scales. Here, we describe how evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, and highlight both the outstanding science and applications questions and the actions, especially from a space-based perspective, necessary to advance them

Outgoing Near‐Infrared Radiation From Vegetation Scales With Canopy Photosynthesis Across a Spectrum of Function, Structure, Physiological Capacity, and Weather

We test the relationship between canopy photosynthesis and reflected near-infrared radiation from vegetation across a range of functional (photosynthetic pathway and capacity) and structural conditions (leaf area index, fraction of green and dead leaves, canopy height, reproductive stage, and leaf angle inclination), weather conditions, and years using a network of field sites from across central California. We based our analysis on direct measurements of canopy photosynthesis, with eddy covariance, and measurements of reflected near-infrared and red radiation from vegetation, with light-emitting diode sensors. And we interpreted the observed relationships between photosynthesis and reflected near-infrared radiation using simulations based on the multilayer, biophysical model, CanVeg. Measurements of reflected near-infrared radiation were highly correlated with measurements of canopy photosynthesis on half-hourly, daily, seasonal, annual, and decadal time scales across the wide range of function and structure and weather conditions. Slopes of the regression between canopy photosynthesis and reflected near-infrared radiation were greatest for the fertilized and irrigated C4 corn crop, intermediate for the C3 tules on nutrient-rich organic soil and nitrogen fixing alfalfa, and least for the native annual grasslands and oak savanna on nutrient-poor, mineral soils. Reflected near-infrared radiation from vegetation has several advantages over other remotely sensed vegetation indices that are used to infer canopy photosynthesis; it does not saturate at high leaf area indices, it is insensitive to the presence of dead legacy vegetation, the sensors are inexpensive, and the reflectance signal is strong. Hence, information on reflected near-infrared radiation from vegetation may have utility in monitoring carbon assimilation in carbon sequestration projects or on microsatellites orbiting Earth for precision agriculture applications

Whitepaper: Understanding land-atmosphere interactions through tower-based flux and continuous atmospheric boundary layer measurements

Executive summary ● Target audience: AmeriFlux community, AmeriFlux Science Steering Committee & Department of Energy (DOE) program managers [ARM/ASR (atmosphere), TES (surface), and SBR (subsurface)] ● Problem statement: The atmospheric boundary layer mediates the exchange of energy and matter between the land surface and the free troposphere integrating a range of physical, chemical, and biological processes. However, continuous atmospheric boundary layer observations at AmeriFlux sites are still scarce. How can adding measurements of the atmospheric boundary layer enhance the scientific value of the AmeriFlux network? ● Research opportunities: We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics at flux tower sites, (2) to support regionalscale modeling and upscaling of surface fluxes to continental scales, (3) to validate land-atmosphere coupling in Earth system models, and (4) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements. ● Recommended actions: Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites would allow the Earth science community to address new emerging research questions, to better interpret ongoing flux tower measurements, and would present novel opportunities for collaboration between AmeriFlux scientists and atmospheric and remote sensing scientists. We therefore recommend that (1) a set of instrumentation for continuous atmospheric boundary layer observations be added to a subset of AmeriFlux sites spanning a range of ecosystem types and climate zones, that (2) funding agencies (e.g., Department of Energy, NASA) solicit research on land-atmosphere processes where the benefits of fully integrated atmospheric boundary layer observations can add value to key scientific questions, and that (3) the AmeriFlux Management Project acquires loaner instrumentation for atmospheric boundary layer observations for use in experiments and short-term duration campaigns

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