No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
Modeling of annual net primary production of a forest in the Taramakau Valley, Westland, New Zealand
Abstract
Article 6. Modeling of annual net primary production of a forest in the Taramakau Valley, Westland, New Zealand Author: Liu Huan (1983-), Master of Science (First Class Honours), The University of Auckland Advisor: George Perry, School of Environment, The University of Auckland
This article attempted to review the relevant theories on biodiversity conservation at three layers: ecosystem diversity, species diversity and genetic diversity, illustrated by substantial case studies which were updated in recent years and published in China. Then the new theories and its corresponding improvement in conservation methods were discussed in this article.
Article 10. Ancient Chinese Eight Diagrams and Application on Chemistry Reaction Rate/八卦与矩阵运算及其在化学反应速率中的应用研究 Author: Liu Huan (1983- ), Master of Science (First Class Honours), The University of Auckland.
Article 3: 3S Technology Application on Biodiversity Monitoring and Assessment/3S 技术在生物多样性监测与评价领域的应用研究（英文） Author: Liu Huan, Master of Science (First Class Honours), The University of Auckland
Vegetation light use efficiency is a key physiological parameter at the canopy scale, and at the daily time step is a component of remote sensing algorithms for scaling gross primary production (GPP) and net primary production (NPP) over regional to global domains. For the purposes of calibrating and validating the light use efficiency (εg) algorithms, the components of εg– absorbed photosynthetically active radiation (APAR) and ecosystem GPP – must be measured in a variety of environments. Micrometeorological and mass flux measurements at eddy covariance flux towers can be used to estimate APAR and GPP, and the emerging network of flux tower sites offers the opportunity to investigate spatial and temporal patterns in εg at the daily time step. In this study, we examined the relationship of daily GPP to APAR, and relationships of εg to climatic variables, at four micrometeorological flux tower sites – an agricultural field, a tallgrass prairie, a deciduous forest, and a boreal forest. The relationship of GPP to APAR was close to linear at the tallgrass prairie site but more nearly hyperbolic at the other sites. The sites differed in the mean and range of daily εg, with higher values associated with the agricultural field than the boreal forest. εg decreased with increasing APAR at all sites, a function of mid-day saturation of GPP and higher εg under overcast conditions. εg was generally not well correlated with vapor pressure deficit or maximum daily temperature. At the agricultural site, a εg decline towards the end of the growing season was associated with a decrease in foliar nitrogen concentration. At the tallgrass prairie site, a decline in εg in August was associated with soil drought. These results support inclusion of parameters for cloudiness and the phenological status of the vegetation, as well as use of biome-specific parameterization, in operational εg algorithms.
We used outputs from a model of canopy carbon uptake [Dungan et al. (2004) Functional Ecology 18: 34–42] and measurements of irradiance (PAR, 400–700 nm) intercepted by the canopy to investigate the effect of daily changes in environmental conditions on daily light use efficiency, ε, for a canopy comprising two broadleaved New Zealand tree species with contrasting leaf habit. Irradiance absorbed by the canopy was 93% of the incident irradiance, and seasonal changes in the proportion of this absorbed by leaves of each species was estimated with a detailed model of leaf area phenology. Over the year, ε for semi-deciduous wineberry (Aristotelia serrata) was 0.43 g C MJ -1 PAR, with maximum and minimum values of 0.80 g C MJ -1 PAR and 0.07 g C MJ -1 PAR in summer and winter respectively. In contrast annual ε was 0.60 g C MJ -1 PAR for winter deciduous fuchsia, with a maximum value of 0.92 g C MJ -1 PAR in spring. The most important environmental regulator of ε for both species was τ, atmospheric transmissivity. Maximum values for ε were estimated on days when τ ≈0.2, on cloudy days in mid-summer. Limits to photosynthesis from restricted root-zone water availability were also important, showing that drought limitations can restrict ε even at a field site with annual rainfall of 4800 mm. Environmental limits to photosynthesis and ε have been investigated for only a few canopy tree species. Uncertainty in models of the national carbon budget required for reporting purposes would be reduced by considering the environmental regulation of ε for a wider range of tree species.
Uncertainty is involved in many real phenomena. Whether one considers uncertainty explicitly when modeling such a phenomenon is one of the modeling decisions, the result of which will depend on the context. If, however, the modeler decides to consider uncertainty, he or she will have to select the method for modeling it. Some scientists claim that one theory, e.g. probability theory, is sufficient to model all kinds of uncertainty. Here it is claimed, however, that the choice of the appropriate method is context dependent and an approach is suggested to determine context-dependently a suitable method to model uncertainty.
An algorithm based on the physics of radiative transfer in vegetation canopies for the retrieval of vegetation green leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) from surface reflectances was developed and implemented for operational processing prior to the launch of the moderate resolution imaging spectroradiometer (MODIS) aboard the TERRA platform in December of 1999. The performance of the algorithm has been extensively tested in prototyping activities prior to operational production. Considerable attention was paid to characterizing the quality of the product and this information is available to the users as quality assessment (QA) accompanying the product. The MODIS LAI/FPAR product has been operationally produced from day one of science data processing from MODIS and is available free of charge to the users from the Earth Resources Observation System (EROS) Data Center Distributed Active Archive Center. Current and planned validation activities are aimed at evaluating the product at several field sites representative of the six structural biomes. Example results illustrating the physics and performance of the algorithm are presented together with initial QA and validation results. Potential users of the product are advised of the provisional nature of the product in view of changes to calibration, geolocation, cloud screening, atmospheric correction and ongoing validation activities.
Photosynthetic radiation use efficiency (PhRUE) over the course of a day has been shown to be constant for leaves throughout a general canopy where nitrogen content (and thus photosynthetic properties) of leaves is distributed in relation to the light gradient. It has been suggested that this daily PhRUE can be calculated simply from the photosynthetic properties of a leaf at the top of the canopy and from the PAR incident on the canopy, which can be obtained from weather-station data. The objective of this study was to investigate whether this simple method allows estimation of PhRUE of different crops and with different daily incident PAR, and also during the growing season.
The PhRUE calculated with this simple method was compared with that calculated with a more detailed model, for different days in May, June and July in California, on almond (Prunus dulcis) and walnut (Juglans regia) trees. Daily net photosynthesis of 50 individual leaves was calculated as the daylight integral of the instantaneous photosynthesis. The latter was estimated for each leaf from its photosynthetic response to PAR and from the PAR incident on the leaf during the day.
Daily photosynthesis of individual leaves of both species was linearly related to the daily PAR incident on the leaves (which implies constant PhRUE throughout the canopy), but the slope (i.e. the PhRUE) differed between the species, over the growing season due to changes in photosynthetic properties of the leaves, and with differences in daily incident PAR. When PhRUE was estimated from the photosynthetic light response curve of a leaf at the top of the canopy and from the incident radiation above the canopy, obtained from weather-station data, the values were within 5 % of those calculated with the more detailed model, except in five out of 34 cases.
The simple method of estimating PhRUE is valuable as it simplifies calculation of canopy photosynthesis to a multiplication between the PAR intercepted by the canopy, which can be obtained with remote sensing, and the PhRUE calculated from incident PAR, obtained from standard weather-station data, and from the photosynthetic properties of leaves at the top of the canopy. The latter properties are the sole crop parameters needed. While being simple, this method describes the differences in PhRUE related to crop, season, nutrient status and daily incident PAR.
Modelling provides a variety of tools with which the understanding of environmental systems is increased. This chapter presents the range of currently available techniques that may be employed in model building and testing. Sensitivity analysis is a very powerful tool for interacting with simple or complex models. The measurement of the sensitivity of a model to a parameter can be viewed relative to the uncertainty involved in the measurement of that parameter to understand how important this uncertainty will be in terms of its impact on the model outcomes. Error is an important part of the modelling process. It must therefore be incorporated within the framework of any approach taken, and any corresponding uncertainty evaluated as far as possible. The chapter also addresses a number of the important conceptual issues involved in the modelling process, to suggest that the modelling process is not as uniform as is often assumed.
Increasing population and needs for an augmented food supply give greater importance to improved procedures for estimating agricultural water requirements both for irrigation and for rain- fed agriculture. Four methods for estimating potential evapotranspiration are compared and evaluated. These are the Class A evaporation pan located in an irrigated pasture area, the Hargreaves equation, the Jensen-Haise equation, and the Blaney-Criddle method. -from ASCE Publications Abstracts Dept of Agric & Irrig Eng, Utah State Univ, Logan, UT 84322, USA.
Mathematical models are utilized to approximate various highly complex engineering, physical, environmental, social, and economic phenomena. Model parameters exerting the most influence on model results are identified through a 'sensitivity analysis'. A comprehensive review is presented of more than a dozen sensitivity analysis methods. This review is intended for those not intimately familiar with statistics or the techniques utilized for sensitivity analysis of computer models. The most fundamental of sensitivity techniques utilizes partial differentiation whereas the simplest approach requires varying parameter values one-at-a-time. Correlation analysis is used to determine relationships between independent and dependent variables. Regression analysis provides the most comprehensive sensitivity measure and is commonly utilized to build response surfaces that approximate complex models.
Evapotranspiration (ET) is important to both ecosystem metabolism and climate. Cleugh et al. developed a satellite-based evapotranspiration (ET) algorithm based on the Penman-Monteith (P-M) equation, which uses surface meteorological measurements and surface conductance estimated via MODIS NDVI and LAI. The algorithm is applied to the globe using ECMWF daily met data, 16-day albedo and NDVI from MOD43C1, MOD15 8-day LAI in 2001. Ecosystem-level measurements of latent heat flux at eddy covariance flux towers offer opportunities for validating the MODIS ET products. Here, we report results for such comparisons at several sites varying widely in biome type and land use. Preliminary comparison shows good agreement between modeled and measured ET across various fluxtowers in 2001.
Geochemical models that deduce latitudinal source/sink relationships of atmospheric CO2 suggest that, in tropical regions, there is almost zero net exchange of CO2 between the atmosphere and the terrestrial biosphere. The implication is that CO2-enhanced carbon storage (CO2-ECS) by tropical biomes is negating the output of CO2 from deforestation. We describe here a 10-biome model for CO2-ECS, in which carbon accumulation in living vegetation is coupled to the Rothamsted soil carbon model. A biotic growth factor (β) was used to describe the relationship between literature estimates of net primary production (NPP) and atmospheric CO2 concentration. Using β = 0.3 as a reference state, CO2-ECS by the global biosphere in 1990 was 1.1 Gt. When more appropriate values of β were used (derived from a theoretical response of vegetation to increasing temperature and CO2), CO2-ECS was 1.3 Gt, of which tropical biomes accounted for 0.7 Gt. There are many uncertainties in this (and other) models; total CO2-ECS is particularly sensitive to changes in NPP. Unless published surveys have underestimated tropical NPP by a factor of about 2, then it is unlikely that CO2-ECS could have negated the 1.5-3.0 Gt of carbon that are estimated to have been emitted by tropical deforestation in 1990.
Uncertainty and sensitivity analysis results obtained in a preliminary performance assessment for the Waste Isolation Pilot Plant (WIPP) in southeastern New Mexico are presented. The most appropriate conceptual model for performance assessment at the WIPP is believed to include gas generation due to corrosion and microbial action in the repository and a dual-porosity (matrix and fracture porosity) representation for solute transport in the Culebra Dolomite Member of the Rustler Formation. Under these assumptions, complementary cumulative distribution functions (CCDFs) summarizing radionuclide releases to the accessible environment due to both cuttings removal and groundwater transport fall substantially below the release limits promulgated by the U.S. Environmental Protection Agency (EPA). This is the case even when the current estimates of the uncertainty in analysis inputs are included. Performance assessment results are dominated by cuttings removal. The releases to the accessible environment due to groundwater transport make very small contributions to the total release. The variability in the distribution of CCDFs that must be considered in comparisons with the EPA release limits is dominated by the rate constant in the Poisson model for drilling intrusions. The variability in releases to the accessible environment due to cuttings removal is dominated by drill bit diameter.
We used an environmentally driven, process‐based model to investigate the relative benefits of deciduous and evergreen leaves, in terms of net annual canopy carbon uptake, for a canopy of two tree species with contrasting leaf habit: deciduous Fuchsia [ Fuchsia excorticata (J. R. Forst. and G. Forst) L. f.]; and annual‐evergreen Wineberry ( Aristotelia serrata J. R. Forst. and G. Forst, W. R. B. Oliv.).
Parameters for the model were derived from a year of measurements at a field site with a maximum leaf area index ( L ) of 5·4 m ² m ⁻² , of which Wineberry and Fuchsia comprised 4·9 and 0·5 m ² m ⁻² , respectively. Net annual C uptake ( A NET ; daily photosynthesis minus respiration at night) was 930 g C m ⁻² , of which Wineberry and Fuchsia contributed 850 and 80 g C m ⁻² , respectively. Canopy respiration at night ( R N ) accounted for 29 and 18% of daily uptake for Wineberry and Fuchsia, respectively. The model was used to simulate the effects of an evergreen phenology for both species. This increased A NET relative to that estimated using the observed phenology by only 1% for Wineberry, and 4% for Fuchsia. This was attributable to increased net C uptake during winter with the evergreen phenology being offset by increased R N , and reduced A NET during summer.
This comparison was repeated for sites spanning the natural range of Wineberry and Fuchsia across New Zealand. In terms of net C balance, the relative advantage of an evergreen phenology decreased with average winter temperature for both species, to the point where a deciduous phenology resulted in a higher value for A NET for Fuchsia at sites where frosts limited winter uptake.
Our simulations suggest that there is no clear advantage, in terms of annual C balance, for a deciduous or evergreen phenology at sites with relatively mild winters. In contrast, at sites where frost‐induced photoinhibition limits photosynthesis for overwintering leaves, a deciduous phenology results in a higher value of A NET for species, such as Fuchsia, with leaves that are very active photosynthetically during spring and summer. The lack of deciduousness in the New Zealand flora may be due to the low number of tree species with such photosynthetic characteristics, and this may be attributable to the generally poor nutrient availability in forest soils.
The moderate resolution imaging spectroradiometer (MODIS) is being used to monitor gross primary production (GPP), both spatially and temporally, routinely from space. However, estimates of GPP at various flux stations indicate that the MODIS algorithm may (i) over-predict GPP at sites where limitation to growth by low-soil water content is not adequately captured by the reduction in stomatal conductance by vapor pressure and (ii) under-predict GPP in highly productive, evergreen, needle leaf forests, due to a reduced radiation-use-efficiency term. The objective of this paper is to determine if any systematic bias exists in the MODIS algorithm relative to eddy covariance (EC) estimates of GPP made over an evergreen, needle leaf temperate rainforest on Vancouver Island, Canada, which is routinely water-stressed in summer months. Results indicate that 8-day GPP as predicted by the standard MODIS algorithm, with appropriate parameters for evergreen needle leaf forest, was highly correlated to EC-measured GPP (r2 = 0.89, p < 0.001, S.E. = 0.9 g C m−2 day−1), however with significant bias, under predicting GPP by as much as 30%. Increasing the radiation-use-efficiency term ɛmax (g C MJ−1) from the MODIS lookup value to the maximum observed at the site resulted in a reduced bias in the predicted GPP, however estimates were 8% higher than EC measurements. To account for soil water stress on plant growth, we implemented a soil water modifier initially proposed by Leuning et al. [Leuning, R., Cleugh, H., Zegelin, S., Hughes, D., 2005. Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: measurements and comparison with MODIS remote sensing estimates. Agric. For. Meteorol. 129, 151–173] that accounts for rainfall and potential evaporation in the antecedent 3 months, a surrogate for soil water availability. Results confirm that field observations of relative available soil water content in the 0–60 cm layer matched the proposed soil water modifier closely with the relationship between the modified MODIS algorithm GPP and the EC-measured GPP remaining highly significant (r2 = 0.91, p < 0.001, S.E. = 1.1 g C m−2 day−1) with no significant bias. Whilst broad scale implementation of such a soil water modifier into the MODIS algorithm is still limited due to lack of rainfall data, at least in the short-term, the modifier does provide an alternative for researchers and land mangers, interested in applying the MODIS GPP products over regional areas, but who may have, or are observing, over-estimated production estimates due to the lack of inclusion of soil water modification to growth.
We inter-compare the mathematical formulation of ten models of terrestrial net primary productivity (NPP) and their functional responses to temperature (T), carbon dioxide (CO2), soil water (W) and photosynthetically active radiation (PAR). The models span a broad spectrum of complexity of approaches from the original, empirical Miami model, through β-factor, and global-average box models, to the dynamic global vegetation models (DGVMs) TRIFFID and BIOME3. Five of the models separate photosynthesis and respiration, although only three directly consider biochemistry. Equations for all the models are given in a complete, compact, standardized format.
This study of the distribution in space and time of atmospheric transmissivity τ takes into account the fact that, in complex terrain, many factors affect this variable; thus, it is not possible to use the generalizations that can be applied under more homogeneous conditions. Climatic controls, topography and even sea currents have important effects on clouds and aerosols affecting τ, simultaneously leading to differences in the distribution of incident solar radiation. Different models exist to estimate incoming solar radiation as a function of relative sunshine hours (observed sunshine hours/theoretical sunshine hours, n/N) or differences between maximum and minimum temperatures Δ T. We calibrated, validated and evaluated four of these empirical relations based on data from 15 weather stations in Peru. Models were calibrated using 66% of the daily historical record available for each weather station; the rest of the information was used for validation and comparison. The Ångström–Prescott model was used to estimate incoming solar radiation based on n/N, and gave the best performance of all the models tested. The other models (Bristow–Campbell, Hargreaves, and Garcia) estimated incoming solar radiation based on Δ T. Of all the models in this group, the Bristow–Campbell model performed best; it is also valuable because of the physical explanation involved. The empirical coefficients of all the models evaluated are presented here. Two empirical equations are proposed with which to estimate values of the coefficients bB and cB in the Bristow–Campbell model, as a function of Δ T and latitude, allowing the model to be applied to other study areas. Copyright © 2004 Royal Meteorological Society
This paper describes a method for integrating leaf area index (LAI) derived from remote sensing data with an ecosystem model for accurate estimation of net primary productivity (NPP). The ecosystem model used in this study was Sim-CYCLE, with which LAI retrieved from the data acquired by MODIS sensor (MODIS-LAI) was integrated. Global annual NPP was estimated as 59.6 Gt C year−1 by MOD-Sim-CYCLE (Sim-CYCLE after integration of MODIS-LAI), whereas it was 62.7 Gt C year−1 in case of Sim-CYCLE for the year 2001. Both models predicted highest NPP around the equator with another smaller peak occurring around 60°N. These two regions represented the tropical and boreal forests biomes, respectively. The NPP estimated by MOD-Sim-CYCLE exceeded the NPP estimated by Sim-CYCLE in these two regions. Other than the tropical and boreal forests biomes, NPP values estimated by the MOD-Sim-CYCLE were typically lower than Sim-CYCLE across the latitudes. Validations of results in Australia and USA showed that MOD-Sim-CYCLE estimated NPP more accurately than Sim-CYCLE. Our results demonstrate the utility of combining satellite-observation with an ecosystem process model to achieve improved accuracy in estimates and monitoring global net primary productivity.
We propose a novel approach for using high-spectral resolution imagers to estimate the fraction of photosynthetically active radiation adsorbed, fapar, by vegetated land surfaces. In comparison to approaches using broad-band vegetation indices, the proposed method appears to be relatively insensitive to the reflectance of nonphotosynthetically active material beneath the canopy, such as leaf litter or soil. The method is based on a relationship between the second derivative of the reflectance vs wavelength function for terrestrial vegetation and fapar. The relationship can be defined by the second derivatives in either of two windows, one in the visible region centered at 0.69 μm, another in the near-infrared region centered at 0.74 μm.
In this paper, we present a new model of the terrestrial carbon cycle (Sim-CYCLE), with the objectives of retrieving the carbon dynamics of various terrestrial ecosystems and estimating their response to global environmental change. The model can be characterized in three ways. (1) It is a compartment model. Ecosystem carbon storage is divided into five compartments; foliage, stem, root, litter, and mineral soil. This approach made the model simple and sound, and allowed us to run the model on a broad scale; indeed, the simulation in this paper was performed using data available at the global scale. (2) It is a process-based model. Sim-CYCLE estimates net primary production (NPP) and net ecosystem production (NEP) by explicitly calculating such carbon fluxes as gross primary production (GPP), plant respiration, and soil decomposition on a monthly time-step; these fluxes are regulated by a multitude of environmental factors at the physiological scale. In relation to global change, responses to increased atmospheric CO2 and temperature should be modeled in a mechanistic manner. (3) It is a prognostic model. Sim-CYCLE is designed to be applicable not only to the simulation of an equilibrium state under given conditions, but also to the prediction of a transitional state under changing environmental conditions. Importantly, Sim-CYCLE is based on the dry-matter production theory, which enabled us to achieve the scaling-up from single-leaf to canopy and to conceptualize the growth process. Since the model includes both radiation and hydrological conditions, some indirect influences of the initial environmental change can be properly evaluated. We present a comprehensive model description and preliminary results confirmed at the plot scale: (1) intensively in four natural ecosystems and (2) extensively in global 21 sites. At each site, model parameters were calibrated to capture the observed carbon dynamics (e.g. productivity and carbon storage) at the equilibrium state. Successional growth patterns and seasonal variations in CO2 exchange were also examined in a qualitative manner. Sim-CYCLE successfully expressed the differences between tropical forest and boreal forest and between humid forest and arid grassland in terms of productivity and carbon storage. Next, we simulated transitional ecosystem carbon dynamics, in response to step-wise atmospheric CO2 doubling and disturbance regime. The simulated temporal patterns of carbon cycle were realistic and ensured that Sim-CYCLE is an effective tool for predicting the impact of global change.
Approaches combining satellite-based remote sensing data with ecosystem modelling offer potential for the accurate assessment of changes in forest carbon balances, for example, in support of emission credits under the Kyoto Protocol. We investigate the feasibility of two alternative methods of using satellite-derived data to constrain the behaviour of a dynamic ecosystem model, in order to improve the model's predictions of the net primary production (NPP) of conifer forests in northern Europe (4–30°E, 55–70°N). The ecosystem model incorporates a detailed description of forest stand structure and biogeochemical processes. The satellite product comprises multi-spectral reflectance data from the VEGETATION sensor. The first method combines satellite-based estimates of FPAR, the fraction of incoming photosynthetically active radiation absorbed by vegetation, with the model's predictions of the efficiency with which trees use the incoming radiation to fix carbon. Results obtained using this method averaged 0.22 kg C m−2 yr−1 for the NPP of conifer and mixed forests across the study area, and compared well with forest-inventory-based estimates for Sweden. The second method uses forest stand descriptions derived by application of an inverse radiation transfer scheme to VEGETATION data to prescribe stand structure in the ecosystem model simulations. Predictions obtained by this method averaged 0.31 kg C m−2 yr−1, somewhat high compared to forest inventory data for central and northern Sweden. Simulations by the ecosystem model when driven only by climate, CO2 and soils data, but unconstrained by satellite information, yielded an average NPP of 0.41 kg C m−2 yr−1, which is likely to be an overestimate. Summed over the study area, the NPP estimates amounted to 0.16–0.23 Gt C yr−1, around 6–9% of the NPP of all boreal forest globally or 0.3–0.4% of terrestrial NPP globally. The investigated methods of combining process modelling and products derived from remote sensing data offer promise as a step towards the development of operational tools for monitoring forest carbon balances at large scales.
A relationship between atmospheric transmittance and the daily range of air temperature is developed. The relationship is Tt = A[1—exp(—BΔTc)] where Tt is the daily total atmospheric transmittance, ΔT is the daily range of air temperature, and A, B, and C are empirical coefficients, determined for a particular location from measured solar radiation data. Tests on three data sets indicate that 70–90% of the variation in daily solar radiation can be accounted for by this simple model.
Measurements over a period of 33 months are presented for the fluxes of carbon, sensible heat and water vapour over a tropical wet/dry savanna in northern Queensland (Virginia Park), and for 38 months over a cool temperate Eucalyptus forest in southeast Australia (Tumbarumba), as part of the OzFlux network. Fluxes were measured using micrometeorological methods and neural network analysis was used to fill gaps in the hourly flux time series. Productivity at Virginia Park is controlled by rainfall amount and timing during the wet season since this determines the leaf area index (Lai) of the C4 grass understorey which varies greatly compared to Lai of the trees. The savanna lost 99 g C m⁻² over the period July 2001–March 2004 due to the failure of the 2002–2003 wet season when rainfall was in the lowest 20th percentile. Net uptake of carbon at Tumbarumba was 2510 g C m⁻² from February 2001 to March 2004, with annual productivity ranging from 1060 g C m⁻² year⁻¹ in a normal year to 360 g C m⁻² year⁻¹ during the 2002–2003 drought which affected all of eastern Australia. Annual rainfall at the savanna was matched by annual evapotranspiration, indicating there was no surface runoff or deep drainage during our study. Trees at both sites were able to extract water deep within the soil profile to maintain annual transpiration above rainfall during the drought of 2002–2003.
Two models were evaluated for their ability to estimate land surface evaporation at 16-day intervals using MODIS remote sensing data and surface meteorology as inputs. The first was the aerodynamic resistance–surface energy balance model, and the second was the Penman–Monteith (P–M) equation, where the required surface conductance is estimated from remotely-sensed leaf area index. The models were tested using 3 years of evaporation and meteorological measurements from two contrasting Australian ecosystems, a cool temperate, evergreen Eucalyptus forest and a wet/dry, tropical savanna. The aerodynamic resistance–surface energy balance approach failed because small errors in the radiative surface temperature translate into large errors in sensible heat, and hence into estimates of evaporation. The P–M model adequately estimated the magnitude and seasonal variation in evaporation in both ecosystems (RMSE = 27 W m− 2, R2 = 0.74), demonstrating the validity of the proposed surface conductance algorithm. This, and the ability to constrain evaporation estimates via the energy balance, demonstrates the superiority of the P–M equation over the surface temperature-based model. There was no degradation in the performance of the P–M model when gridded meteorological data at coarser spatial (0.05°) and temporal (daily) resolution were substituted for locally-measured inputs.The P–M approach was used to generate a monthly evaporation climatology for Australia from 2001 to 2004 to demonstrate the potential of this approach for monitoring land surface evaporation and constructing monthly water budgets from 1-km to continental spatial scales.
Changes in carbon storage in terrestrial ecosystems are a consequence of
shifts in the balance between net primary production (NPP) and
heterotrophic respiration (RH). Historical climatic
variations which favored NPP over RH may have led to
increased ecosystem carbon storage and might account for at least part
of the "missing" sink required to balance the current century's global
carbon budget. To test this hypothesis, we employed a georeferenced
global terrestrial biosphere model of 0.5° spatial resolution. The
model was driven from an assumed equilibrium in 1900 using gridded
historical time series of monthly temperature and precipitation and the
historical record of changes in atmospheric CO2
concentration. Interannual variability in climate induced interannual
changes in terrestrial biospheric carbon storage and net carbon exchange
with the atmosphere of the order of 1-2 Gt C yr-1. With
climate change alone, global biospheric carbon storage declined by 1%
(23 Gt C) over the period 1900-1988. With the addition of a moderate
CO2 fertilization response, biospheric carbon storage
increased by 3% (57 Gt C), primarily as a consequence of changes in NPP
and litter inputs to the soil system. With CO2 fertilization,
the model's cumulative carbon sink for the period 1900-1988 accounts for
about 69% of the missing sink derived by deconvolution. For the period
1950-1988, the modeled sink is about 56% of the missing sink. Our
results suggest that the temporal evolution of the missing sink over the
period 1900-1988 could be a response of the terrestrial biosphere to
changes in climate and atmospheric CO2 or perhaps climate
change alone. The discrepancy in the magnitudes of the modeled and
deconvolved sinks may be due to limitations of the biospheric model or
to overestimates of the land-use source flux.
Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: Initial model development. Agricultural and Forest Meteorology
- C Nicholas
- A Coops
- S Rachhpal
- B Jassal
- R C Leuning
Principios F'ısicos de la Climatolog'ıa
- J V Garcia