Terrestrial biogeochemical cycles: Global estimates with remote sensing

ELSEVIER

Terrestrial Biogeochemical Cycles: Global Estimates with Remote Sensing David S. Schimel* T h e carbon and nitrogen cycles are crucial for understanding the changing Earth system, influencing atmospheric concentrations of greenhouse gases, primary productivity of the biosphere, and biogenic emissions of reactive trace species. The carbon budget of the terrestrial biosphere has attracted special attention because of its role in atmospheric chaages in carbon dioxide. The terrestrial biosphere influences atmospheric C02 through three main modes: First, large, nearly balanced fluxes of C02 in photosynthesis and respiration exhibit a degree of interannual variability which can influence atmospheric C02, at least on annual to decadaI time scales. Second, land use changes release C02 to the atmosphere. Third, poorly understood processes are likely resulting in enhanced uptake of CO2 ~in certain ecosystems, acting as a sink in the global carbon cycle. This sink may result from forest demographics, atmospheric N deposition, or direct C02 fertilization, or some synergistic combination of those processes. Global estimates of terrestrial carbon cycle components requires the use of remote observations; however, the appropriate remote sensing strategies are quite different for the various components.

INTRODUCTION The coupled carbon and nitrogen cycles are at the heart of the Earth system. The carbon system is linked closely to the water-energy cycles through the joint regulation of stomata by water status and by photosynthesis (Sellers et al., 1992; Sellers and Schimel, 1993; Collatz et al., 1991). The carbon and nitrogen cycles are linked through the stoichiometric relationships between C and

*National Center for Atmospheric Research, Boulder, Colorado Address correspondence to David S. Schimel, NCAR, P.O. Box 3000, Boulder, CO 80307-3000. Received 10 December 1993; revised 20 April 1994. REMOTE SENS. ENVIRON. 51:49-56 (1995) ©Elsevier Science Inc., 1995 655 Avenue of the America:;, New York, NY 10010

N which constrain transfers of organic matter at each step in autotrophic and heterotrophic metabolism. Because of the close coupling of the C and N cycles, diagnostic and predictive models must consider the coupled processes. Feedbacks to the climate system occur through physiological regulation of sensible and latent heat fluxes, through atmospheric CO2, and through the linkage of the carbon-water-energy system to the metabolism of other trace gases such as methane. Changes to the global carbon cycle are of importance, as CO2 is the principal greenhouse gas, after water vapor, and because the global carbon cycle has been greatly affected by fossil fuel burning, changes in land use, and global alterations of the N cycle through fertilizer use and air pollution. Because changes to terrestrial ecosystems affect global processes when integrated over areas continental to global in extent, global measurement technologies are crucial. While a number of methodologies have been employed in global biogeochemical studies, such as global networks for concentrations and isotopic composition (Tans et al., 1990; 1993), in this article I focus on applications of remote sensing for direct measurements of ecosystems, and for extrapolation of measured and modeled results. The subsequent discussion considers three modes of the terrestrial carbon system: the background fluxes of photosynthesis and respiration, and the two perturbation fluxes, one due to land use, and the other a poorly characterized sink.

THE BACKGROUND FLUXES

Each year the terrestrial biosphere exchanges about 60 Gt COz-C with the atmosphere (48-68 Gt: Fung et al., 1987; Ajtay et al., 1979; Box, 1988; Potter et al., 1993). This is composed of about 60 Gt in terrestrial photosynthesis, and about 60 Gf Of plant plus microbial respiration. Roughly a third of terrestrial carbon cycling occurs in forests, which store a disproportionate amount of C 0034-4257 / 95 / $9.50 SSDI 0034-4257(94)00064-T

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in wood. While the exchange of CO2 between global ecosystems and the atmosphere is often assumed to be in balance each year, so that the land use and "missing sink" fluxes can be treated as perturbations, in fact there is considerable evidence of climate-forced deviations from annual balance in many ecosystem studies. For example, Parton et al. (1993) showed significant rates of positive and negative net ecosystem production during analysis of a long time series of data in grassland ecosystems. Similarly, CO2 flux data from the Konza Prairie and Harvard forests (Verma et al., 1993; Wofsy et al., 1993) showed substantial annual imbalances between photosynthesis and respiration. While it is possible for terrestrial fluxes to be balanced globally, and unbalanced locally, it has recently been argued that global climate anomalies can cause global trends in carbon storage by influencing photosynthesis and respiration differentially (Dai and Fung, 1993; Sarmiento 1993; Ciais et al., in press). Changes in terrestrial carbon storage due to climate variability can occur due to either climate effects on respiration, increasing carbon storage by decreasing outputs, or increasing inputs through photosynthesis. The most likely cause of decreased respiration is cooler temperatures, with reductions in decomposition in soils flooded by high rainfall being a second possibility. Warmer temperatures and increases in precipitation not resulting in flooded soils (relative to the long-term average) should increase carbon inputs. There is no direct remote sensing technique for measuring the effects of climate on respiration, and so such effects must be estimated using climate observations as inputs into models (Dai and Fung, 1993; Schimel et al., 1990; Melillo et al., 1993). Effects of climate variability on NPP, however, can be estimated by using interannual variation in the vegetation index, or similar satellite parameters, as inputs into models (Korol et al., 1991; Runyon et al., 1994; Sellers et al., 1992; Potter et al., 1993). The theory and rationale of the use of remote sensing in estimating photosynthesis and NPP are described in Sellers et al. (1992), Sellers and Schimel (1993), Potter et al. (1993), and Ruimy et al. (1994). While models such as Sellers et al. (1992) are just beginning to be used, models which estimate dry matter or biomass production from light interception, often estimated from spectral vegetation indices (Asrar et al., 1984), are widely employed. These models are descended from the original formulation of Monteith (1972) and Kumar and Monteith (1981), and take the form NPP(t)= e(t)f(t)PAR(t), where NPP is the net primary productivity at time t, E(t) the conversion efficiency (g/MJ) at time t, and f(t) the fraction of intercepted photosynthetically active radiation (PAR) at time t. Early efforts assumed a constant value of e(t) (Heimann and Keeling, 1989; Goward et al., 1985). More recent efforts have either specified e(t) as a function of biome type

(e.g., Ruimy et al., 1994) or have computed a value for e(t) modified by stress (Potter et al., 1993). In Potter et al.'s (1993) formulation, e(t) = Tl(t)T2(t)W(t)e*, where Tl(t) and T2(t) are expressions that reduce e* when extremely high or low temperatures occur (T1), and to reduce e* when temperatures during the growing season depart from a defined optimal temperature (T2), set at 20°C. W(t) modifies e* for water stress effects. Potter et al. (1993) found a global annual average of e of 0.39 g C MJ -1 PAR. Ruimy et al. (1994) gave biome-mean values ranging from 0.37 (dry tropical and subtropical forests) to 2.07 (in croplands). E-Type models yield results which may correlate well with measured seasonal variations in atmospheric CO2 (Potter et al., 1993) and should be of use in measuring interannual variability, especially as the modeling of physiological controls over e improves (e.g., Runyon et al., 1994; Potter et al., 1993). An E-type model is proposed as an operational algorithm for MODIS (Running, personal communication). LAND USE CHANGE Since the early 1970s, it has become increasingly clear that the accelerating rate of land use in the tropics results in inputs of carbon dioxide to the atmosphere. This results from deforestation, with the accompanying destruction of woody biomass and losses of soil organic matter, and from biomass burning in grassland and savanna areas (Houghton et al., 1983; Skole and Tucker, 1993; Crutzen and Andreae, 1990). While the effects of changes in land use on the carbon cycle are poorly known, they have a significant effect on carbon cycle calculations. Table 1 shows the estimated industrial and ocean sources and sinks of carbon dioxide. This implies a small terrestrial sink, subject to considerable uncertainty (+ 0.8). However, this also neglects the source due to land use. Adding in effects of land use change (e.g., net deforestation, estimated as 1.6 Gt) results in the following calculation: land use net emission (1.6)- calculated imbalance (0.2) = terrestrial sink (1.4). Thus, the uncertainty in land use net emissions of CO2 is important both because it results in uncertainty in the net emissions of CO2 to the atmosphere and because it adds considerable uncertainty to the required size of a terrestrial sink. While the uncertainty in ocean uptake also adds to the "missing sink" uncertainty, this value is thought to be better constrained than the land use net emissions. While it is difficult to measure the processes that may result in a terrestrial sink (see section below), the rates of land conversion resulting in emissions to the atmosphere can be estimated using remote sensing (Skole and Tucker, 1993; INPE, 1992). Land use affects the carbon budget by converting

Estimation of Global Terrestrial Biogeochemical Cycles 51

Table 1. Industrial and Ocean Terms in the Global Carbon Cycle (Average fc,r 1980-1990) ~ Fossil fuel, flaring, cement Atmospheric accumalation Oeean uptake Calculated imbalance

5.4 3.2 2.0 0.2

Gt Gt Gt Gt

Adapted from Siegenthaler and Sarmiento (1993).

ecosystems from high carbon storage states to reduced carbon storage states [or potentially vice versa (Harrison et al., 1993)]. In order to calculate the effects of land use change on the carbon budget, it is necessary to know the carbon density of the original and derived (e.g., pasture, plantation, cropland, abandoned) ecosystems, and the rates of conversion (area/unit time). If there are changes subsequent to the original conversion (e.g., regrowth after abandonment) that affect the carbon store, then these too mast be included in the calculation. Remote sensing can only play a limited role, if any, in assessing carbon density, but is an ideal technology for assessing rates of changes in land cover types. Estimation of rates of change requires the acquisition of images over time. The images must be classified into land cover classes (e.g., primary forest, secondary forest, agriculture or pasture) When the images, acquired over time and classified, are overlaid, the rate of change can be calculated from the number of pixels per unit area that have changed category, divided by the time interval between the images. Recent work in the Brazilian and Bolivian Amazon has proven this technique, and demonstrated that even simple, largely manual image analysis techniques can provide area estimates of acceptable accuracy (Skole and Tucker, 1993; INPE, 1992). This work has also shown that instruments with the characteristics of Landsat-Thematic Mapper (30 m or less spatial resolution, broadband spectral resolution) are suitable for the mission of determining the rate and direction of land use change. While higher spatial resolution might refine regional estimates for highly fragmented land cover types (e.g., terraced agriculture), and higher spectral resolution could possibly identify a wider range of classes, the 30 m broadband instrument allows comprehensive coverage of large areas and identification of coarse but key classes of vegetation for global studies. It seems likely that a Landsat Thematic Mapper-class instrument will remain a key part of any remote sensing strategy for the carbon cycle in the EOS era. E N H A N C E D TERRESTRIAL UPTAKE

As shown above, most ~malyses of the carbon cycle require at least a modest sink to balance industrial emissions, observed atmospheric' changes, and calculated ocean uptake, with a larger sink required when land use net

emissions are included. Most studies have assumed this sink to be forced by increasing CO2 emissions, that is, caused by carbon dioxide fertilization of the biosphere. This is a key assumption in calculations of future CO2 concentrations, because if the sink is smaller than assumed during the model calibration period (19001990), or if it results from processes which saturate (e.g., in the 2000 period), then concentrations could increase more rapidly than previously calculated (e.g., by - 1 Gt / yr) (Wigley, 1993). There are several alternative processes which contribute to an enhanced terrestrial sink. Additions of nitrogen to the biosphere can result in increased carbon storage. The intentional and inadvertent fertilization of the biosphere by agricultural fertilizers and N deposition of NOx from fossil fuels could cause increased carbon storage. Estimates of this flux vary, but are generally on the order of 0.5-1.9 Gt/yr, largely in midlatitude regions where use of fertilizer and industrial emissions are currently largest (Peterson and Melillo, 1985). The effectiveness of this flux is limited by a number of factors, including damage to plants by ozone and other stressors which often accompany high N deposition rates, the "N saturation syndrome" in which prolonged N additions become detrimental to vegetation (Schulze et al., 1989), and increased N losses by gaseous and solute pathways which often accompany N additions. Regrowth of forests logged before - 1940 may contribute to a sink in the midlatitudes. A number of studies have argued that this sink could be appreciable (0.51.2 Gt/yr: Sedjo, 1992), although other studies have suggested that sources accompanying the logging process nearly compensate for the sinks (Houghton, 1993; Melillo et al., 1988; Dixon et al., 1994). While literature estimates of the midlatitude sink in regrowing forests range from about 0 to >1 Gt/yr in the 1980s, it is likely that this process will saturate or slow in the near future due to the typical logistic growth pattern of forests, in which growth rates decrease as storage increases. Our estimates of forest regrowth rates are calibrated during the period of time when atmospheric CO2 and atmospheric N deposition were increasing, so it is unclear how to separate the regrowth and fertilization terms in the forest C budget. Studies using tree rings to compare regrowth rates in the 20th century with those of earlier periods are difficult to interpret and have provided conflicting results. It is also unclear whether N and COz-fertilized systems will ultimately store more C, or simply reach a saturating level sooner. Of course, N deposition and CO2 fertilization could also affect unmanaged ecosystems, making deconvolution of effects even more difficult. While it seems likely that processes other than CO2 fertilization account for some fraction of the sink, COz fertilization is undoubtedly significant, and virtually all

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experimental studies show some degree of stimulation (e.g., Poorter, 1993). It is difficult to translate the effects observed in experimental studies into predictions of decadal changes in carbon storage. Simulation models suggest that long-term effects may be less than shortterm physiological responses, though still significant. The N cycle is key to understanding this response. It is well established that N fertilized plants are more responsive to CO2 than are unfertilized plants. In ecosystems, plant production and decomposition are coupled by the N cycle. Increased decomposition rates (e.g., by warming) increase N mineralization, allowing increased plant growth (Shaver et al., 1992; Schimel et al., 1990). Increases in plant growth (e.g., from CO2 fertilization) result in enhanced litter inputs, which require enhanced microbial uptake of N for their decomposition. This latter effect is amplified with CO2-fertilized growth, as increasing CO2 tends to result in decreased foliar N concentrations. The litter so produced will decompose more slowly and require more N, acting as a bigger N sink and thereby competing with vegetation. While these feedbacks may require years to stabilize and so are difficult to evaluate with experiments, several such experiments are in progress (Field, personal communication; Norby, personal communication; Owensby et al., 1993). Simulation models can provide an evaluation of the feedbacks, incorporating parameterizations of what is known, or hypothesized. All current models coupling production and decomposition through the N cycle show a marked depression of the CO2 effect, although they may show a large transient effect (Table 2). In general, the realized effect of CO2 at twice the current concentration is one-quarter to one-half that physiologically possible with unlimited nutrients. This raises two questions. First, most ecosystems experience continual N inputs in atmospheric deposition, as discussed above. Could CO2-fertilized ecosystems retain a larger portion of those inputs, allowing more growth and C storage? Two model studies suggest that this is not the case. Rastetter et al. (1991) argued that this effect is minimal

Table 2. Simulated Transient and Steady State Enhancement of NPP by CO~ Fertilization

Model CENTURY (global grasslands) TEM (global) G'DAY (einus radiata)

Transient Steady State or Potential or Realized Reference Effect Effect Ojima et al. (1993) 40% 15%

37%

16%

Melillo et al. (1993)

27%

8%

Comins and McMurtrie (1993)

in ecosystems where annual N inputs are a small fraction of the annually cycling pool. Comins and McMurtrie (1993) showed that CO2-fertilized systems do retain an additional fraction of inputs, but that this only contributes a small increment to C storage. The second question is whether increasing CO2 could contribute to enhanced biological N fixation, as suggested by Gifford (1992) and Idso and Kimball (1993). Such an effect has been shown in cultivated legumes. In natural ecosystems this effect will be limited by the fact that N fixation is limited by factors other than carbon or energy in many systems (Vitousek and Howarth, 1991; Eisele et al., 1989), and by the restrictive biogeography of the plant-microorganism symbioses that are generally responsible for high rates of N fixation. The potentially significant role of N fixation in response to CO2 remains an open question for specific and global ecosystems. In view of the importance of the N cycle in global change, it is worth a careful assessment of the response of canopy chemistry to environmental change as a basis for determining the feasibility and instrument requirements of remote sensing of canopy chemistry. In order to do this, I have compiled data from a wide range of sources describing the response of foliar N content and related parameters to N addition and COz fertilization, along with some data on seasonal and interannual variations. The effects of doubled CO2, generally taken as 700 ppm, are quite variable, ranging from 0.1% N (3.2 vs. 3.1% N) to 0.8% N (2.8 to 2.0% N), with all studies showing a decline in C:N with increasing CO2 but of highly variable magnitude (Coleman and Bazzaz, 1992). These declines in foliar N are generally accompanied by substantial increases in plant growth resulting from the stimulation of photosynthesis by higher CO2, and accompanying increases in N use efficiency (photosynthesis or biomass produced/unit N). Nitrogen fertilization and real and simulated atmospheric N also may affect foliar N concentration. Binkley and Reid (1985) showed that additions of N to temperate Douglas-fir stands resulted in an increase in N from 1.55 g / m 2 to 2.05 g / m 2 in live foliage 15 years after the application of fertilizer. Litter N levels increased from 1.22 g / m 2 to 1.66 g / m 2, a change large enough to impact decomposition (Vitousek et al., 1993). The change in foliar N was accompanied by changes in leaf area (+ 50%) and (much larger) changes in diameter growth ( + 120%). Vitousek et al. (1993) reported similar results from studies in Hawaii. They found that, in young stands of Metrosideros polymorpha, N fertilizer additions increased foliar N from 0.83 to 0.92% N with increases to 1.02% with complete fertilizer additions. The changes in foliar N, while modest, were accompanied by changes in leaf production (130%) and diameter growth (180%). In a site growing on older soils, they found increases in foliar N to be minimal in M. polymorpha, but substantial in the understory fern Cibotium glaucum (1.2-1.4% N).

Estimation of Global Terrestrial Biogeochemical Cycles 53

At this site, foliar ma,,;s did not change substantially (537 vs. 620 g m -2 yr -l litterfall), but again substantial changes in diameter growth occurred (140%). While studies of fi~rtilizer response are important experimental tools in understanding the role of environmental N additions, t~here are important differences between fertilizer appl!ication and wet and dry deposition of N. Thomas and Miller (1992) simulated the effects of atmospheric N deposition by adding N by various methods, including foliar and soil additions to Sitka spruce. They found that foliar additions of ammonium and nitrate increased foliar N levels by amounts ranging from 0.07% N to 0.3% N, depending upon the method of application and the species (ammonium or nitrate). McNulty et al. (1991) measured foliar N levels across an N deposition gradient in New England. N deposition rates across this gradient ranged from - 2 . 5 kg N / ha / yr to - 6 kg N / ha / yr. Foliar N contents ranged from 0.85% to 1.07% across the gradient, but were not significantly correlated with N deposition. Interestingly, two other important correlates of decomposition and ecosystem N cycling were correlated with deposition, foliar lignin content and foliar lignin:N ratio. The factors influence litter decomposition rates and hence the storage of detrital carbon and the return of organic N to the vegetation through mineralization (Aber and Melillo, 1982; Parton et al., 1987; Vitousek et al., 1993). Lignin:N ratios varied from 28 to 18 (lignin contents of 25 to - 1 8 ) and were correlated with deposition (r-- -0.79). As predicted by theory (Aber and Melillo, 1982), lignin:N ratios were also correlated with N mineralization (r= -0.62). Because lignin retards decomposition, lignin can significantly affect soil carbon storage. Sensitivity analyses using the Century ecosystem model suggest that doubling lignin could increase carbon storage in soils by > 1 kg/m ~ (Schimel et al., 1994). Changes in foliar N due to environmental trends are expressed against a background of considerable species and biome-level differences and natural variability. Yin (1993) has shown that foliar N in forests across North America spans a range from 2.5% (mostly N fixers) to 1.0%, with foliar N being broadly correlated with summertime temperatures. Values for canopy N as high as 3.5% [in N-fixing shrubs (Archer and Schimel, unpublished data)] and as low as 0.8% N [late summer Tallgrass prairie (Hobbs et al., 1991)] have been reported for nonforest ,ecosystems. Within ecosystems, seasonal variability in N concentration can be very high. Hobbs et al. (1991) reported a change from early season N contents approaching 3% to late summer values of 0.8% in a tallgrass prairie. Evergreen broadleaf shrubs in South Texas varied by 0.5% N from summer to winter (Archer and Schimel, unpublished data). Few studies have reported interannual variability in foliar N. Schimel et al. (1991) showed changes in mean foliar N of 0.3%

N between 1988 and 1989 in a tallgrass prairie. Texas shrubland ecosystems similarly showed changes of 0.4 % between 1991 and 1992 at a common phenological state. In both the shrubland and grassland, foliar biomass and LAI also varied. Is remote sensing of canopy chemistry feasible? Lab near-IR analyses of N contents are now done routinely, and analyses of AIS and AVIRIS data are encouraging but not definitive (Wessman et al., 1990; Waring et al., 1987). An assessment of the ability of remote spectroscopy to detect canopy chemical signals is underway [The Accelerated Canopy Chemistry Project (Aber, personal communication)], and I will not here attempt a review of this field. Rather, I will explore potential sensor and sampling strategy requirements and opportunities based on the review of canopy N and lignin data above. First, spatial gradients in N of 1-3.5% occur between ecosystems. Remote sensing of large scale variations in foliar N would require accuracy and precision sufficient to map changes of - 0 . 5 % N in order to distinguish between ecosystems with differences in N large enough to influence photosynthesis, given the strong dependence of photosynthesis on N (Field and Mooney, 1986; Sellers et al., 1992). Gradients of - 8% lignin can occur within a forest type (McNulty et al., 1991), and from 4.5% [grasslands (Schimel, unpublished data; Parton et al., 1987)] to 25% or higher in forests (McNulty et al., 1991). Changes of - 5 % in lignin are required to detect between-system gradients in lignin, and - 1% to detect changes within a forest type, with resolution sufficient to map changes relevant to decomposition and nitrogen cycling (Schimel et al., 1994; McNulty et al., 1991; Aber and Melillo, 1982). Note that while changes in canopy N concentration with fertilization, N deposition or changing CO2 are typically of the order of 0.5% N, because changes in foliar biomass often accompany changing N, changes to canopy N mass can be quite substantial. Binkley and Reid (1985) showed changes from 60 kg/ha to 130 kg/ha in a fertilized Douglas-fir stand. We observed interannual changes of > 1 0 kg/ ha in a Texas shrubland system (Archer and Schimel, unpublished data). Changes in canopy N mass can be quite substantial. The vertical distribution of N may also change as overall foliar biomass changes, usually with N concentrations in the uppermost foliage changing more than that of the bulk canopy (Schimel et al., 1991). Requirements for detecting temporal changes due to COz or N deposition are quite different. Changes due to these factors are generally < 0.5% N and less than 10% lignin, occurring over decades. These must be detected against a background ofinterannual variability that for N is similar in magnitude, and phenological variability that is 100-300% larger than the decadal signal. The effect of phenological noise means that acquisition of imagery for canopy chemical analysis must either capture seasonality, so that a common phenologi-

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cal state (e.g., maximum or minimum N), or the triggering of spectrometer data acquisition from a near real-time phenological analysis of other data (e.g., a broad-band spectral vegetation index such as the normalized difference vegetation index). Estimates of longterm change in canopy chemical constituents may require statistical analysis of time series of data over decadal time scales, rather than the processing of snapshot images, given that interannual and seasonal variations are large relative to the signals of change. Implications for continuity and sensor calibration and drift must be carefully considered. CONCLUSIONS Considerable progress has been made in both remote sensing of land surface properties, and in understanding ecosystem dynamics. In particular, while the role of the terrestrial biosphere in the global carbon budget remains poorly quantified, its role is now better constrained by inverse estimates and the key ecological processes likely to cause and constrain a terrestrial sink are now understood. Several scientific and programmatic challenges remain. First, the quality (now and continuing into the EOS era of global observations) used to constrain models of terrestrial photosynthesis must be assured and improved to allow rigorous application of these data in determination of interannual variations and potential long-term trends. Second, global analyses of land use changes from satellite data must be completed, and a program should be instituted to carry those measurements into the future. The continuity of Landsat TM-class data through the EOS era must be assured to allow these crucial measurements. Third, the role of the terrestrial biosphere as a sink resultant from biogeochemical and forest demographic forces must be better understood and a remote sensing strategy developed for global integration of these effects. The spatial heterogeneity of foliar chemistry, and the cost of spatially extensive sampling (Schimel et al., 1990) are such that even low precision (but adequately accurate) remote sensing of canopy chemistry might be more rigorous than even an ambitious ground-based sampling scheme; but the high degree of ecological variation on seasonal and interannual time scales will require careful attention to sampling strategies, data analysis, and sensor requirements. Preparation of this review was supported by an Interdisciplinary Award from NASA's EOS program. I thank John Aber, Carol Wessman, and Elizabeth Sulzman for invaluable assistance.

REFERENCES

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