Stephen E. Frolking

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earths climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models.

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.

Sensitivity of vegetation indices to atmospheric aerosols: continental-scale observations in Northern Asia

Abstract Satellite observations play an important role in characterization of the interannual variation of vegetation. Here, we report anomalies of two vegetation indices for Northern Asia (40°N–75°N, and 45°E–179°E), using images from the SPOT-4 VEGETATION (VGT) sensor over the period of April 1, 1998 to November 20, 2001. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), which are correlated to a number of vegetation properties (e.g., net primary production, leaf area index), were compared. The results show that there is a large disagreement between NDVI and EVI anomalies in 1998 and 1999 for Northern Asia. The NDVI anomaly in 1998 was largely affected by atmospheric contamination, predominantly aerosols from extensive forest fires in that year. The EVI anomaly in 1998 was less sensitive to residual atmospheric contamination, as it is designed to be, and thus EVI is a useful alternative vegetation index for the large-scale study of vegetation. The EVI anomaly also suggests that potential vegetation productivity in Northern Asia was highest in 1998 but declined substantially in 2001, consistent with precipitation data from 1998–2001.

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Application of the NASA Scatterometer (NSCAT) for Determining the Daily Frozen and Nonfrozen Landscape of Alaska

Abstract The seasonal transition of the land surface between frozen and nonfrozen conditions affects a number of terrestrial processes that cycle between wintertime dormant and summertime active states. The relatively short (2.14 cm) K u -band of the space-borne NASA scatterometer (NSCAT) is sensitive to changes in dielectric properties, associated with large-scale shifts in the relative abundance and phase (frozen or thawed) of canopy and surface water. We used a temporal change detection analysis of NSCAT daily radar backscatter measurements to classify surface freeze/thaw state across a 1.4 million km 2 region of Alaska from January to June 1997. In the spring, radar backscatter measurements showed pronounced decreases (1.6–4.9 dB) relative to reference frozen state conditions, which corresponded with sustained maximum daily air temperature measurements above 0.0°C and total decreases in measured snow depths from 28% to 61% of seasonal maximum values. We classified the daily frozen and nonfrozen area for the region based on the sign (+/−) of the radar backscatter temporal difference relative to frozen and nonfrozen reference conditions. These results compared favorably (e.g., r 2 =0.881; p⩽0.0001) with frozen area estimates derived from the regional weather station network. NSCAT-derived estimates of the timing and spatial variation in regional thaw during spring were also generally consistent with seasonal increases in river discharge for five major Alaska basins. The NSCAT sensor appears to be responsive to changes in dielectric properties associated with surface freeze/thaw transitions over broad boreal and arctic landscapes. Further study involving longer time-series information, alternative radar wavelengths, and finer spatial scales is needed, however, to resolve the various components (i.e., soil, vegetation, snow) of the regional radar freeze/thaw signature for improved monitoring of the circumpolar high latitudes.

Using the space-borne NASA scatterometer (NSCAT) to determine the frozen and thawed seasons

We hypothesize that the strong sensitivity of radar backscatter to surface dielectric properties, and hence to the phase (solid or liquid) of any water near the surface, should make space-borne radar observations a powerful tool for large-scale spatial monitoring of the freeze/thaw state of the land surface, and thus ecosystem growing season length.

Uncertainties in estimates of cropland area in China: a comparison between an AVHRR-derived dataset and a Landsat TM-derived dataset

The large uncertainties in estimates of cropland area in China may have significant implications for major cross-cutting themes of global environmental change-food production and trade, water resources, and the carbon and nitrogen cycles. Many earlier studies have indicated significant under-reporting of cropland area in China from official agricultural census statistics datasets. Space-borne remote sensing analyses provide an alternative and independent approach for estimating cropland area in China. In this study, we report estimates of cropland area from the National Land Cover Dataset (NLCD-96) at the 1:100,000 scale, which was generated by a multi-year National Land Cover Project in China through visual interpretation and digitization of Landsat TM images acquired mostly in 1995 and 1996. We compared the NLCD-96 dataset to another land cover dataset at I-km spatial resolution (the IGBP DIScover dataset version 2.0), which was generated from monthly Advanced Very High Resolution Radiometer (AVHRR)-derived Normalized Difference Vegetation Index (NDVI) from April, 1992 to March, 1993. The data comparison highlighted the limitation and uncertainty of cropland area estimates from the DIScover dataset

Radar remote sensing proposed for monitoring freeze‐thaw transitions in boreal regions

New research is finding that satellite-based radar remote sensing techniques are particularly well-suited for quantifying the transition of remote boreal regions from a frozen to a thawed condition. The implications for studying global warming are far reaching. If the timing or areal extent of this freeze/thaw transition were to change significantly, measurable changes in boreal climate, hydrology, and biogeochemistry would result. Abrupt transition from frozen to thawed conditions occurs each year over roughly 50 million km2of the Earths remote terrestrial surface at latitudes above 40°N. Radar remote sensing works well to capture this transition because of the way electromagnetic radiation at radar wavelengths interacts with polar water molecules in solid and liquid states. Also, radar has the substantial advantages at high latitudes of both penetrating through clouds and not requiring solar illumination of the land surface.

Modeling nitrous oxide emissions from agriculture: A Florida case study

Abstract The DNDC (Denitrification-Decomposition) model is shown to simulate emissions of nitrous oxide (N 2 O), changes in soil nitrate, and nitrogen mineralization rates consistent with field measurements at three agricultural sites in Florida. As a case study of the potential policy relevance of a process-oriented biogeochemical model, we estimated N 2 O emissions to the atmosphere from all agricultural lands in Florida, a state with significant agriculture on both organic and mineral soils. Nine landscape classes (3 soil classes × 3 annual rainfall classes) were coupled with county-based data on crops (5 major crops + pasture + fallow), fertilization, irrigation, and representative areas, to generate 86 model scenarios. Annual simulations were run for each case, and county and state emissions were tabulated. Total N 2 O emissions from Floridas agricultural lands were estimated to be 0.024 Tg N 2 ON y −1 . Emissions were unevenly distributed with approximately 50 percent of the N 2 O being emitted from soils in six (of 68) Florida counties. Organic soils, while occupying only 9% of the total agricultural land area and receiving no nitrogen fertilizer additions, accounted for 38% of the states total N 2 O flux. Sensitivity studies suggest that the most effective means for mitigating N 2 O emissions would involve a combination of measures including reductions in drainage of organic soils, injection of fertilizers to soil depths of 10 cm or greater, and increased attention to precision irrigation. Biogeochemical modeling will be critical to developing an integrated framework for assessing policies for reducing N 2 O emissions from agricultural systems.

The Sensitivity of Methane Emissions from Northern Freshwater Wetlands to Global Warming

Human activities are changing the chemical composition of the Earth’s atmosphere. Emissions of pollutant gases from the burning of fossil fuels, production and use of synthetic chemicals, and the conversion of natural environments to agricultural systems have increased the atmospheric concentrations of carbon dioxide, methane, nitrous oxide, and chlorofluorocarbons to the highest levels known for at least 160,000 years of Earth history. Trapped ancient gases in ice cores, and direct monitoring of more recent changes in air chemistry, have convincingly documented the links between the growth of the human population, the evolution of industrial societies, and increasing concentrations of these gases (e.g., Rowland and Isaksen, 1988; Chappellaz et al., 1990; Lorius et al., 1990). One likely consequence of the increasing concentrations of atmospheric gases like carbon dioxide and methane is a change in global climate. These gases have long lifetimes in the atmosphere, and as they accumulate they trap, in the lower atmosphere, increasing amounts of energy emitted from the earth’s surface (Ramanathan et al., 1987). The current consensus among climate experts is that the increasing burden of atmospheric gases projected for the next century will result in a global climate warming of some 2–6°C (Dickinson, 1986; Levine, Chapter 1, this volume). A warming of this magnitude would be unprecedentedly rapid and extreme in the history of industrial society.