Steven A. Klooster

Terrestrial ecosystem production: A process model based on global satellite and surface data

This paper presents a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration. We use satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs. The Carnegie-Ames-Stanford approach (CASA) Biosphere model runs on a monthly time interval to simulate seasonal patterns in net plant carbon fixation, biomass and nutrient allocation, litterfall, soil nitrogen mineralization, and microbial CO2 production. The model estimate of global terrestrial net primary production is 48 Pg C yr−1 with a maximum light use efficiency of 0.39 g C MJ−1PAR. Over 70% of terrestrial net production takes place between 30°N and 30°S latitude. Steady state pools of standing litter represent global storage of around 174 Pg C (94 and 80 Pg C in nonwoody and woody pools, respectively), whereas the pool of soil C in the top 0.3 m that is turning over on decadal time scales comprises 300 Pg C. Seasonal variations in atmospheric CO2 concentrations from three stations in the Geophysical Monitoring for Climate Change Flask Sampling Network correlate significantly with estimated net ecosystem production values averaged over 50°–80° N, 10°–30° N, and 0°–10° N.

Interannual Variability in Terrestrial Net Primary Production: Exploration of Trends and Controls on Regional to Global Scales

ABSTRACT Climate and biophysical regulation of terrestrial plant production and interannual responses to anomalous events were investigated using the NASA Ames model version of CASA (Carnegie–Ames–Stanford Approach) in a transient simulation mode. This ecosystem model has been calibrated for simulations driven by satellite vegetation index data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. Relatively large net source fluxes of carbon were estimated from terrestrial vegetation about 6 months to 1 year following El Niño events of 1983 and 1987, whereas the years 1984 and 1988 showed a drop in net primary production (NPP) of 1–2 Pg (1015 g) C from their respective previous years. Zonal discrimination of model results implies that the northern hemisphere low latitudes could account for almost the entire 2 Pg C decrease in global terrestrial NPP predicted from 1983 to 1984. Model estimates further suggest that from 1985 to 1988, the northern middle-latitude zone (between 30° and 60°N) was the principal region driving progressive increases in NPP, mainly by an expanded growing season moving toward the zonal latitude extremes. Comparative regional analysis of model controls on NPP reveals that although Normalized Difference Vegetation Index “greenness” can alone account for 30%–90% of the variation in NPP interannual anomalies, temperature or radiation loading can have a fairly significant 1-year lag effect on annual NPP at middle- to high-latitude zones, whereas rainfall amount and temperature drying effects may carry over with at least a 2-year lag time to influence NPP in semiarid tropical zones.

Discovery of climate indices using clustering

To analyze the effect of the oceans and atmosphere on land climate, Earth Scientists have developed climate indices, which are time series that summarize the behavior of selected regions of the Earths oceans and atmosphere. In the past, Earth scientists have used observation and, more recently, eigenvalue analysis techniques, such as principal components analysis (PCA) and singular value decomposition (SVD), to discover climate indices. However, eigenvalue techniques are only useful for finding a few of the strongest signals. Furthermore, they impose a condition that all discovered signals must be orthogonal to each other, making it difficult to attach a physical interpretation to them. This paper presents an alternative clustering-based methodology for the discovery of climate indices that overcomes these limitiations and is based on clusters that represent regions with relatively homogeneous behavior. The centroids of these clusters are time series that summarize the behavior of the ocean or atmosphere in those regions. Some of these centroids correspond to known climate indices and provide a validation of our methodology; other centroids are variants of known indices that may provide better predictive power for some land areas; and still other indices may represent potentially new Earth science phenomena. Finally, we show that cluster based indices generally outperform SVD derived indices, both in terms of area weighted correlation and direct correlation with the known indices.

Net primary production of terrestrial ecosystems from 2000 to 2009

The CASA (Carnegie-Ames-Stanford) ecosystem model has been used to estimate monthly carbon fluxes in terrestrial ecosystems from 2000 to 2009, with global data inputs from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation cover mapping. Net primary production (NPP) flux for atmospheric carbon dioxide has varied slightly from year-to-year, but was predicted to have increased over short multi-year periods in the regions of the high-latitude Northern Hemisphere, South Asia, Central Africa, and the western Amazon since the year 2000. These CASA results for global NPP were found to be in contrast to other recently published modeling trends for terrestrial NPP with high sensitivity to regional drying patterns. Nonetheless, periodic declines in regional NPP were predicted by CASA for the southern and western Untied States, the southern Amazon, and southern and eastern Africa. NPP in tropical forest zones was examined in greater detail to discover lower annual production values than previously reported in many global models across the tropical rainforest zones, likely due to the enhanced detection of lower production ecosystems replacing primary rainforest.

Modeling seasonal and interannual variability in ecosystem carbon cycling for the Brazilian Amazon region

Previous field measurements have implied that undisturbed Amazon forests may represent a substantial terrestrial sink for atmospheric carbon dioxide. We investigated this hypothesis using a regional ecosystem model for net primary production (NPP) and soil biogeochemical cycling. Seasonal and interannual controls on net ecosystem production (NEP) were studied with integration of high-resolution (8-km) multiyear satellite data to characterize Amazon land surface properties over time. Background analysis of temporal and spatial relationships between regional rainfall patterns and satellite observations (for vegetation land cover, fire counts, and smoke aerosol effects) reveals several notable patterns in the model driver data. Autocorrelation analysis for monthly vegetation “greenness” index (normalized difference vegetation index, NDVI) from the advanced very high resolution radiometer (AVHRR) and monthly rainfall indicates a significant lag time correlation of up to 12 months. At lag times approaching 36 months, autocorrelation function (ACF) values did not exceed the 95% confidence interval at locations west of about 47°W, which is near the transition zone of seasonal tropical forest and other (nonforest) vegetation types. Even at lag times of 12 months or less, the location near Manaus (approximately 60°W) represents the farthest western point in the Amazon region where seasonality of rainfall accounts significantly for monthly variations in forest phenology, as observed using NDVI. Comparisons of NDVI seasonal profiles in areas of the eastern Amazon widely affected by fires (as observed from satellite) suggest that our adjusted AVHRR-NDVI captures year-to-year variation in land cover greenness with minimal interference from small fires and smoke aerosols. Ecosystem model results using this newly generated combination of regional forcing data from satellite suggest that undisturbed Amazon forests can be strong net sinks for atmospheric carbon dioxide, particularly during wet (non El Nino) years. However, drought effects during El Nino years can reduce NPP in primary forests of the eastern Amazon by 10–20%, compared to long-term average estimates of regional productivity. Annual NEP for the region is predicted to range from −0.4 Pg C yr−1 (net CO2 source) to 0.5 Pg C yr−1 (net CO2 sink), with large interannual variability over the states of Para, Maranhao, and Amazonas. As in the case of predicted NPP, it appears that periods of relatively high solar surface irradiance combined with several months of adequate rainfall are required to sustain the forest carbon sink for positive yearly NEP estimates.

Interannual variability in soil trace gas(CO2, N2O, NO) fluxes and analysis of controllers on regional to global scales

Interannual variability in flux rates of biogenic trace gases must be quantified in order to understand the differences between short-term trends and actual long-term change in biosphere-atmosphere interactions. We simulated interannual patterns (1983-1988) of global trace gas fluxes from soils using the NASA Ames model version of CASA (Carnegie-Ames-Stanford Approach) in a transient simulation mode. This ecosystem model has been recalibrated for simulations driven by satellite vegetation index data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. The predicted interannual pattern of soil heterotropic CO2 emissions indicates that relatively large increases in global carbon flux from soils occurred about three years following the strong El Nino Southern Oscillation (ENSO) event of 1983. Results for the years 1986 and 1987 showed an annual increment of +1 Pg (1015 g) C-CO2 emitted from soils, which tended to dampen the estimated global increase in net ecosystem production with about a two year lag period relative to plant carbon fixation. Zonal discrimination of model results implies that 80-90 percent of the yearly positive increments in soil CO2 emission during 1986-87 were attributable to soil organic matter decomposition in the low-latitudes (between 30 N and 30 S). Soils of the northern middle-latitude zone (between 30 N and 60 N) accounted for the residual of these annual increments. Total annual emissions of nitrogen trace gases (N2O and NO) from soils were estimated to vary from 2-4 percent over the time period modeled, a level of variability which is consistent with predicted interannual fluctuations in global soil CO2 fluxes. Interannual variability of precipitation in tropical and subtropical zones (30 N to 20 S appeared to drive the dynamic inverse relationship between higher annual emissions of NO versus emissions of N2O. Global mean emission rates from natural (heterotrophic) soil sources over the period modeled (1983-1988) were estimated at 57.1 Pg C-CO2yr-1, 9.8Tg (1012 g) N-NO yr-1, and 9.7 Tg N-N2O yr-1. Chemical fertilizer contributions to global soil N gas fluxes were estimated at between 1.3 to 7.3 Tg N-NO yr-1, and 1.2 to 4.0 Tg N-N2O yr-1.

Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8–km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982–2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987–1989, 1995–1997, and 1999. Sub-continental regions of the Pacific Northwest, Alaska, and Central Canada had the highest proportion (>90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20–30 years. In this paper, we investigated the response of net CO2 exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60°N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (1015 g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO2 in 1983–1984, coinciding with an El Niño event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Pg C per year. Analysis of model controls on NPP and soil heterotrophic CO2 fluxes (Rh) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO2 by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (δ13C) deconvolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.

Modeling biogenic emissions of isoprene: exploration of model drivers, climate control algorithms, and use of global satellite observations

Abstract An improved global budget for isoprene emissions from terrestrial vegetation sources is fundamental to a better understanding of the oxidative capacity of the lower atmosphere and changes in the concentration of major greenhouse gases. In this study, we present a biosphere modeling analysis designed to ascertain the interactions of global data drivers for estimating biogenic isoprene emissions. We have integrated generalized isoprene emission algorithms into a process-based simulation model of ecosystem carbon fluxes, the NASA-CASA (Carnegie–Ames–Stanford Approach) model. This new modeling approach for predicting isoprene emissions operates on scales designed to directly link regional and global satellite data sets with estimates of ecosystem carbon cycling, hydrology, and related biogeochemistry. The NASA-CASA model results indicate that the annual isoprene flux from terrestrial plant sources is 559 Tg C . Three ecosystem types, broadleaf evergreen forest, dry tropical forest, and wooded grassland (savanna), account for approximately 80% of these global vegetation isoprene emissions. Based on analyses to improve understanding of the relative influence of climatic (e.g., light and temperature) versus biotic (NPP) controllers on predicted isoprene emission estimates, it appears that the largest portion of total biogenic flux to the global atmosphere is emitted from ecosystems that are mainly light-limited for isoprene emissions. These modeling results imply that, along with better process understanding of base emission factor controls for volatile organic compounds, improvements in global fields of solar surface radiation fluxes in warm climate zones will be needed to reduce major uncertainties in isoprene source fluxes.

Simulation modeling of nitrogen trace gas emissions along an age gradient of tropical forest soils

Abstract Applications of a process simulation model for ecosystem production and soil nutrient cycling were carried out to test hypotheses concerning the controls on nitrogen trace gas fluxes in tropical forests. Assuming that emissions of trace gases (N2O and NO) can help characterize patterns in N cycling among forests of different age and nutrient status, we applied a new daily time step version of the CASA (Carnegie-Ames-Stanford approach) model in an attempt to reproduce soil biophysical conditions previously measured in three forest stands that comprise a soil age gradient (ranging from 200 to 185 000 years old) on the island of Hawaii. We compared model-predicted soil moisture, temperature, N mineralization, and N trace gas emission rates to measurements at forest sites made during 1990 and 1991. Results showed that predicted water filled pore space (WFPS) in the soil is consistently lower than measured WFPS, possibly due to incomplete understanding of moisture holding capacity, drainage properties, and small scale variability of these volcanic soils. Simulations correctly predicted the observed difference of an order of magnitude between N2O emission fluxes in the youngest and the oldest forest soils. Nevertheless, specific day-by-day comparison of predicted and measured N2O fluxes reveal only occasional agreement within an order of magnitude tolerance level. Although soil moisture conditions appear favorable for emission on NO at these sites, as predicted by the generalized model design, lack of observed NO emissions from the previous field and laboratory studies suggest that: (1) our hypothesized NO emission levels as a function of WFPS should be truncated at lower levels of soil moisture availability; and/or (2) nitrification potentials of natural forest soils should be considered in revised versions of the model.