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This is the first of two articles which explore the combined use of coarse and fine resolution data in land cover studies. It describes the development and evaluation of an objective procedure to select a representative sample of tiles of high resolution images that complements a coarse resolution coverage of an entire region of interest. The second article explores the use of the procedure for an accurate estimation of cover type composition at the regional scale. The Purposive Selection Algorithm (PSA) assumes that a relationship exists between land cover compositions at the two spatial scales. It selects one tile at a time, seeking the sample which most closely resembles the composition of the coarse resolution map. Two selection criteria were used, fraction of cover types and contagion index. PSA was evaluated using two land cover maps for a 288 km×165 km area in central Saskatchewan, Canada derived from Landsat Thematic Mapper images (30 m pixels) and Advanced Very High Resolution Radiometer (AVHRR, 1000 m pixels), each divided into 64 tiles. The performance of an intermediate sensor (480 m pixels) was assessed by resampling the TM map. When using cover type composition alone, it was found that the procedure rapidly converges on a representative set of tiles with land cover composition very similar to the full coverage. The match between the domain and sample cover type fractions was very close, with errors less than 0.002% once about 1/5 to 1/3 of the tiles were selected and no discernible bias in the selected sample. Compared to the TM whole area coverage, samples selected with AVHRR classification were as representative as those obtained using the TM map. The performance of samples selected by a combination of cover composition and contagion index responded to the characteristics of individual tiles in terms of the selection criteria. A rigorous application of the algorithm with spatial heterogeneity measures such as the contagion index is computationally very demanding. It is concluded that PSA provides an efficient and effective tool to select a representative sample for land cover studies in which both large area coverage and local detail are desired.

Because Farquhar’s photosynthesis model is only directly applicable to individual leaves instantaneously, considerable skill is needed to use this model for regional plant growth and carbon budget estimations. In many published models, Farquhar’s equations were applied directly to plant canopies by assuming a plant canopy to function like a big-leaf. This big-leaf approximation is found to be acceptable for estimating seasonal trends of canopy photosynthesis but inadequate for simulating its day-to-day variations, when compared with eddy-covariance and gas-exchange chamber measurements from two boreal forests. The daily variation is greatly dampened in big-leaf simulations because the original leaf-level model is partially modified through replacing stomatal conductance with canopy conductance. Alternative approaches such as separating the canopy into sunlit and shaded leaf groups or stratifying the canopy into multiple layers can avoid the problem. Because of non-linear response of leaf photosynthesis to meteorological variables (radiation, temperature and humidity), considerable errors exist in photosynthesis calculation at daily steps without considering the diurnal variability of the variables. To avoid these non-linear effects, we have developed an analytical solution to a simplified daily integral of Farquhar’s model by considering the general diurnal patterns of meteorological variables. This daily model not only captures the main effects of diurnal variations on photosynthesis but is also computationally efficient for large area applications. Its application is then not restricted by availability of sub-daily meteorological data. This scheme has been tested using measured CO2 data from the Boreal Ecosystem–Atmosphere Study (BOREAS), which took place in Manitoba and Saskatchewan in 1994 and 1996

During the Boreal Ecosystem-Atmosphere Study (BOREAS), which took place in Saskatchewan and Manitoba in 1994, the Compact Airborne Spectrographic Imager (CASI) acquired images of boreal forests. In this paper we present results of radiometric and geometric analysis of the CASI data for developing algorithms for retrieving leaf area index (LAI) and crown closure of the boreal forest. The images of over 30 sites, composed of black spruce, jack pine, and aspen stands, were acquired on different days and locations with various solar illumination and view geometries. The geometrical-optical model, named "4-Scale" (Chen and Leblanc, 1997, 1316 -1337), was used to correct the images to a common solar zenith angle (358) and a common view angle (nadir). The 4-Scale model is also used for radiometric analysis based on spectral signatures of leaves and the background (moss, grass, and soil) acquired using various field and laboratory techniques. The red reflectance of all three cover types decreased with increasing LAI as expected. Similar but weaker decreasing trends were found in the near-infrared (NIR) band for conifer stands in contrast to previous findings for cropland and grassland. No significant NIR response to LAI was found for aspen stands. It is shown from 4-Scale that as LAI increases, the crown and ground shadow fractions of conifer forests increase, while the sunlit background fraction decreases and the sunlit crown fraction increases. The large change in the shadow fractions is the major factor controlling the behavior of red and NIR signals. Since boreal forests have abundant green moss and understory as the background, there is only a small difference in optical properties between the overstory and the background. The increases in the shadow fractions with LAI help strengthen the response of optical measurements to changes in LAI, providing a key mechanism for remote information retrieval. The implications of these findings on formulating/selecting vegetation indices and inversion models are discussed in this paper. Relationships of crown closure with CASI measurements are also included in the analysis.

Various remote sensing sensors observe the Earth’s surface at different spatial resolutions. In deriving surface parameters using remotely sensed data, the transportability of algorithms from one resolution to another is often of great concern because of the surface heterogeneity. This article addresses this scaling issue through image degradation experiments using a Landsat TM image. It is shown theoretically that scaling problems in deriving surface parameters exist not only because of the nonlinearity in the relationships between remote sensing measurements such as NDVI (normalized difference vegetation index) and SR (simple ratio) and the parameters of interest, but also because of the discontinuity between contrasting cover types within a mixed pixel. To quantify the effects of the nonlinearity and discontinuity on scaling, it is found that contextural parameters are more effective than textural parameters. Contexture-based functions are derived for the estimation of the scaling effects on leaf area index (LAI) calculations using algorithms based on NDVI and SR separately. Based on NDVI–LAI and SR–LAI relationships that were derived at the Landsat TM scale (30 m) as part of the Boreal Ecosystem–Atmosphere Study (BOREAS), the effects of scaling on the retrieval of LAI were investigated using nine selected areas of the same size (990 m×990 m) but different water area fractions. The following conclusions are drawn from the investigation: 1) Negative biases in the estimation of LAI occur when either the NDVI or SR algorithm derived at a fine resolution (Landsat TM) is used for calculations at a coarse resolution (for example, AVHRR). 2) The amount of the biases depends on the surface heterogeneity. For a pure forest pixel, the bias caused by the nonlinearity of the NDVI algorithm was smaller than 2% and the linear SR algorithm induces no error in scaling. Therefore, the scaling problem for pure pixels may be ignored for many applications using either linear or nonlinear algorithms. 3) Large negative biases occur when a pixel contains interfaces between two or more contrasting surfaces. In the case of two contrasting surfaces between vegetation and open water, the biases can be up to 45% of the correct value depending of the water area fraction in the pixel. The biases in this case depend on contexture and little on texture. Simulations show that the most useful contextural parameter for quantifying the scaling effects in vegetation–water mixed pixels is the water area fraction within each degraded pixel. Algorithms for remote sensing applications can be transported from one scale to another, if the information on the water body size is available. This study shows the need for global water masks at high resolutions for the purpose of accurate derivation of surface parameters maps at various resolutions. In boreal regions, this is particularly important because of the large number of small water bodies. Crown

RESUMEPour pouvoir utiliser les images optiques composites dans le contexte des etudes sur le milieu terrestre, on doit disposer d'une methode precise et sensible pour detecter les pixels contamines par les effets atmospheriques et de surface non desires. Dans ce texte, nous avons examine la faisabilite de l'utilisation d'un algorithme developpe au depart pour l'analyse post-saison mais en mode ‘avance‘, c'est-a-dire pour l'identification des pixels contamines dans les donnees de la saison en cours. L'algorithme CECANT (Cloud Elimination from Composites using Albedo and NDVI Trend; Cihlar, 1996) utilise la reflectance du canal 1 d'AVHRR pour detecter les pixels fortement contamines (nuages brillants, neige) et l'indice NDVI (Normalized Difference Vegetation Index) pour identifier les pixels partiellement contamines au-dessus de la surface du sol. Toutefois, cette approche necessite une trajectoire saisonniere NDVI complete pour deriver les seuils adaptatifs. Comme certaines applications courantes supposen...

Airborne Polarization and Directional Earth Radiation (POLDER) data acquired during the boreal ecosystem-atmosphere study (BOREAS) and the four-scale model of Chen and Leblanc (1997) are used to investigate radiative transfer in boreal forest. The four-scale model is based on forest canopy architecture at different scales. New aspects are incorporated into the model to improve the physical representation of each canopy, as follows: 1) Elaborate branch architecture is added. 2) Different crown shapes are used for conifer and deciduous forests. 3) Bilayer version of the model is introduced for forest canopies with an important understory. 4) Natural repulsion effect is considered in the tree distribution statistics. Ground measurements from BOREAS sites are used as input parameters by the model to simulate measurements of bidirectional reflectance distribution function (BRDF) from four forest canopies (old black spruce, old aspen, and old and young jack pine) acquired by the POLDER instrument from May-July 1994. The model is able to reproduce with great accuracy the BRDF of the four forests. The importance of the branch architecture and the self-shadowing of the foliage is emphasized.

Photon-stimulated ion desorption (PSID) from solid Si(CH3)2Cl2 following Cl 2p core-level excitation has been investigated along with the resonant photoemission spectra using synchrotron radiation. The Cl L23-edge total-electron yield spectrum of solid Si(CH3)2Cl2 mainly exhibits the Cl 2p→15a1*, Cl 2p→10b1* and shape resonance peaks. A significant dissimilarity between the Cl L23-edge total-electron yield spectrum and Cl+ PSID spectrum of solid Si(CH3)2Cl2 is observed. The desorption of atomic Cl+ ions is detected predominantly at the Cl 2p→15a1* excitation, while scarcely any Cl+ ions are observed following the Cl 2p→10b1* excitation and Cl 2p→shape resonance excitation. This indicates that the character of bound terminating orbital has a significant influence on the desorption processes. The enhanced Cl+ desorption yield at the Cl 2p→15a1* resonance is attributed to the the fast desorption process originating from the localization of the spectator electron in the strong antibonding orbital.

A new procedure for digital image classi® cation is described. The procedure, labelled Classi® cation by Progressive Generalization (CPG), was developed to avoid drawbacks associated with most supervised and unsupervised classi® cations. Using lessons from visual image interpretation and map making, non-recursive CPG aims to identify all signi® cant spectral clusters within the scene to be classi® ed. The basic principles are: (i) initial data compression using spectral and spatial techniques; (ii) identi® cation of all potentially signi® cant spectral clusters in the scene to be classi® ed; (iii) minimum distance classi® cation; and (iv) the use of spectral, spatial and large-scale pattern information in the progressive merging of the increasingly dissimilar clusters. The procedure was tested with high- (Landsat Thematic Mapper (TM)) and medium- (Advanced Very High Resolution Radiometer (AVHRR) 1km composites) resolution data. It was found that the CPG yields classi® cation accuracies comparable to, or better than, current unsupervised classi® cation methods, is less sensitive to control parameters than a commonly used unsupervised classi® er, and works well with both TM and AVHRR data. The CPG requires only three parameters to be speci® ed at the outset, all specifying sizes of clusters that can be neglected at certain stages in the process. Although the procedure can be run automatically until the desired number of classes is reached, it has been designed to provide information to the analyst at the last stage so that ® nal cluster merging decisions can be made with the analyst's input. It is concluded that the strategy on which the CPG is based provides an eA ective approach to the classi® cation of remote sensing data. The CPG also appears to have a considerable capacity for data compression.

RESUMELa validation rigoureuse de la precision et de la coherence des produits derives des donnees satellitaires representant des variables biophysiques de surface est essentielle au progres de l'observation de la Terre en tant qu'outil d'analyse. La validation permet d'assurer que les produits derives rencontrent les caracteristiques techniques decrites et garantit que les resultats generes a l'aide de leur utilisation peuvent etre consideres comme fiables. A titre de composante d'une approche globale de controle de la qualite, pratique d'usage courant dans la plupart des procedes de production, la validation est particulierement importante pour les produits derives des donnees de teledetection parce que l'information est deduite et que le rapport du signal sur le bruit enregistre lors des mesures est frequemment bas. Dans cet article, la validation des produits de teledetection est analysee en deux phases: la validation initiale qui permet d'etablir la fiabilite d'un produit et la validation continue qu...

One objective of the Boreal Ecosystem-Atmospheric Study (BOREAS) is to increase our understanding of the nature of canopy spectral bidirectional reflectance in the visible/near-infrared regimes for open canopies typical of boreal forest stands. For such stands, the need to characterize the reflectance of the sunlit and shaded vegetated understory is critical. These variables are subject to temporal variability due to differences in species phenology and foliar display as well as diurnal and seasonal changes in solar illumination through a seasonally varying upper canopy foliar area. To provide for this need, a multiteam field effort was mounted to measure the nadir midday understory reflectance for the flux tower sites during 1994 BOREAS field campaigns between February and October, specifically during the winter focused field campaign (FFC-W), the spring thaw focused field campaign (FFC-T), and the three intensive field campaigns (IFC-1, IFC-2, and IFC-3) between June and September, which sample vegetation phenological change. This was accomplished by measuring at near-solar noon the sunlit and shaded nadir reflectance of the understory along a surveyed leaf area index (LAI) transect line at each flux tower site. Site-to-site comparisons of understory reflectance spectra reveal stand differences that become more significant as the season progresses. Mean midday understory reflectance spectra were observed to be remarkably consistent over the season for young jack pine stands, followed by somewhat increased variability for mature jack pine, and significant seasonal variability for black spruce stands. Derived vegetation indices for understories are generally consistent with extrapolations of previous relationships of canopy spectral vegetation indices (VIs) versus leaf area index to zero LAI. Inclusion of these “zeroLAI” understory-derived indices significantly enhance the correlation in the linear VI-LAI relationships.

Helicopter and surface-based radiometric measurements of forested sites acquired during the Boreal Ecosystem-Atmosphere Study (BOREAS) were analyzed to assess reflectance variability and to address the relationships of reflectances and vegetation indices (VIs) with overstory leaf area index (LAI). Statistical measures of central tendency and linear regression analysis, including a multivariate regression which introduced the effects of understory reflectance, were used. The sensors were deployed during all three intensive field campaigns (IFCs) of 1994 and consisted of (1) a helicopter-based eight-channel Barnes modular multiband radiometer (MMR) and a ground-based Spectron Engineering SE-590 field spectroradiometer to measure spectral reflectance factors, (2) a ground-based Sun photometer used for atmospheric correction, and (3) a LI-COR LAI-2000 plant canopy analyzer and the tracing radiation and architecture of canopies (TRAC) sensor for retrieval of canopy LAI. Of the eight MMR bands, those most strongly correlated to variations in surface LAI were the second and third middle infrared (IR) (1.57–1.80 μm and 2.08–2.37 μm, respectively) with r2=0.45 in both cases, and the red (0.63–0.68 μm) with r2=0.34. In general, linear regression analyses between the canopy LAI measurements and both the helicopter reflectances and VIs resulted in low r2 values commonly less than 0.3. When stratified by season and species, only among sites that were vegetated by aspen (Populus tremuloides) was a stronger relationship observed. In the aspen stands, LAI displayed a traditional trend that maximizes the utility of the VIs: a negative relationship with red reflectance (r2=0.62) and a positive relationship with the near IR (NIR) of r2 = 0.21. The absence of a positive LAI-NIR reflectance trend degraded the information content of the VIs for the conifers. A multivariate regression confirmed the influence of the understory vegetation on the sparse canopies of the boreal forest and suggested that a more complex model-based approach is necessary to better characterize variations in canopy reflectance. Atmospheric contamination of the radiometric signal by smoke from forest fires may also have contributed to the initial unsatisfactory results.

RESUMEOn utilise souvent les indices de vegetation a deux bandes spectrales (rouge et infrarouge proche) en teledetection pour l'estimation des proprietes biophysiques des surfaces vegetalisees. Quoique de multiples facteurs aient ete pris en considerations dans la formulation des indices de vegetation, l'effet de dependance directionnelle n'a pas ete analyse en profondeur. Plusieurs capteurs de teledetection satellitaire ou aeroportee acquierent des donnees en fonction d'angles solaires et de visee divers. Ainsi la dependance angulaire des indices de vegetation est d'un interet de premiere importance pour la validation des produits de teledetection. Le modele 4-echelles (Chen and Leblanc, 1997) base sur l'analyse detaillee de l'architecture du couvert est utilise pour analyser les implications de la fonction de distribution de la reflectance bidirectionnelle (BRDF) sur les indices de vegetation pour quatre couverts de la foret boreale (epinette noire mature, pin gris jeune et mature, et peuplier mature)....

Leaf area index (LAI) is a key structural characteristic of forest ecosystems because of the role of green leaves in controlling many biological and physical processes in plant canopies. Accurate LAI estimates are required in studies of ecophysiology, atmosphere-ecosystem interactions, and global change. The objective of this paper is to evaluate LAI values obtained by several research teams using different methods for a broad spectrum of boreal forest types in support of the international Boreal Ecosystem-Atmosphere Study (BOREAS). These methods include destructive sampling and optical instruments: the tracing radiation and architecture of canopies (TRAC), the LAI-2000 plant canopy analyzer, hemispherical photography, and the Sunfleck Ceptometer. The latter three calculate LAI from measured radiation transmittance (gap fraction) using inversion models that assume a random spatial distribution of leaves. It is shown that these instruments underestimate LAI of boreal forest stands where the foliage is clumped. The TRAC quantifies the clumping effect by measuring the canopy gap size distribution. For deciduous stands the clumping index measured from TRAC includes the clumping effect at all scales, but for conifer stands it only resolves the clumping effect at scales larger than the shoot (the basic collection of needles). To determine foliage clumping within conifer shoots, a video camera and rotational light table system was used. The major difficulties in determining the surface area of small conifer needles have been largely overcome by the use of an accurate volume displacement method. Hemispherical photography has the advantage that it also provides a permanent image record of the canopies. Typically, LAI falls in the range from 1 to 4 for jack pine and aspen forests and from 1 to 6 for black spruce. Our comparative studies provide the most comprehensive set of LAI estimates available for boreal forests and demonstrate that optical techniques, combined with limited direct foliage sampling, can be used to obtain quick and accurate LAI measurements.

This study was part of the Boreal Ecosystem-Atmosphere Study (BOREAS). It took place in a mature aspen forest in Prince Albert National Park, Saskatchewan, Canada. The aspen trees were 21.5 m high with a 2–3 m high hazelnut understory. The objectives were: (1) to compare the radiation regime beneath the overstory before and after leaf emergence; (2) to infer the structural characteristics of the aspen canopy leaf inclination and clumping; (3) to determine the seasonal course of the leaf area index (L) for both the overstory and understory. Above-stand radiation measurements were made on a 39m walk-up tower, and understory radiation measurements were made on a tram which moved horizontally back and forth at 0.10 m s−1 on a pair of steel cables 65m in length suspended 4 m above the ground. In addition, several LI-COR LAI-2000 Plant Canopy Analyzers were used to determine the effective leaf area index and the zenith angle dependent extinction coefficient (G(θ)) for both the aspen and the hazelnut throughout the growing season. These measurements were supplemented with destructive sampling of the hazelnut at the peak of the growing season. Before leaf emergence, the ratios of below- to above-aspen solar radiation (S), photosynthetic photon flux density (PPFD) and net radiation (Rn) during most of the day were 0.58, 0.55 and 0.47, respectively. By midsummer, these ratios had fallen to 0.33, 0.26 and 0.26, respectively. The aspen G(θ) was relatively invariant with θ, within ±0.05 of 0.5 throughout the growing season, indicating a spherical distribution of leaf inclination angles (i.e. the leaves were randomly inclined). The hazelnut G(θ) has a cosine response with respect to θ, which was consistent with the generally planophile leaf distribution for hazelnut. Using canopy gap size distribution theories developed by Chen and Black (1992b, Agric. For. Meteorol., 60: 249–266) and Chen and Cihlar (1995a, Appl. Opt., 34: 6211–6222) based on Miller and Norman (1971, Agron. J., 63: 735–738), the foliage clumping index (Ω) of the aspen canopy was derived from high-frequency tram measurements of PPFD. The aspen Ω was fairly constant with θ, but showed a small seasonal variation, with a minimum value of 0.70 in the midsummer. The hazelnut Ω was found to be 0.98 determined using the L from the destructive sampling, indicating no clumping. After corrections for clumping and the wood area index (α), the seasonal course of L near the tower for both aspen and hazelnut was determined, with maximum L of 2.4 and 3.3 for the aspen and hazelnut, respectively.

High-resolution Si L23-edge x-ray absorption near-edge structure (XANES) total electron yield (TEY) spectrum and photon stimulated ion desorption (PSID) spectra of condensed Si(CH3)2Cl2 have been measured in the energy range of 102–115 eV using synchrotron radiation. Excitation from Si 2p to a Si–C antibonding orbital enhances the CH3+ formation, while excitation to the Si–Cl antibonding orbital gives rise to a pronounced Cl+ production. This indicates that the character of the bound terminating orbital has a significant influence on the fragmentation processes. The selective enhancement of H+ yield at a peak of ∼106.0 eV is interpreted in terms of the excited electron in the bound orbital with strong C–H antibonding character. Applying resonant photoemission spectroscopy, the spectator Auger process was found to be the dominant decay channel for the resonantly excited Si(2p) core hole of condensed Si(CH3)2Cl2. The close resemblance of the TEY and PSID spectra of solid Si(CH3)2Cl2 was attributable to spec...

RESUMEL'objectif de cette etude visait a caracteriser la repartition des types de couvert dans la region BOREAS. Des donnees multitemporelles AVHRR ont ete acquises tout au long de la saison de vegetation de 1993 et traitees pour en deduire les moyennes saisonnieres de pixels de 1 km2 dans les canaux 1 et 2, l'indice NDVI (Normalized Difference Vegetation Index) et la superficie sous la courbe NDVI. Deux procedures differentes de classification AVHRR ont ete utilisees pour identifier >30 types de couvert sur un territoire de 1.44×106 km2 couvrant la region BOREAS, et la legende de classification hierarchique utilisee etait compatible avec le programme IGBP (International Geosphere-Biosphere Program). La precision de la classification AVHRR a ete evaluee qualitativement et quantitativement a l'aide d'une comparaison avec des images Thematic Mapper de Landsat (TM). La composition des types de couvert a l'interieur des pixels AVHRR a ete quantifiee en utilisant les classifications des deux zones d'etude BORE...

Temporal compositing of daily optical satellite data has become an accepted methodology for obtaining frequent images of large areas for studies of the land surface. However, such composite data sets sometimes contain large “artifacts” (i.e., errors due to sources unrelated to the land surface itself). The goal of this study was to develop a series of operations and algorithms that would identify and remove as many of these errors as possible. The specific objective was to obtain, every ten days, surface reflectance in advanced very high resolution radiometer (AVHRR) channels 1 and 2 and normalized difference vegetation index (NDVI)—all referenced to a constant viewing geometry—and surface temperature. The processing steps of the resulting methodology, dubbed “ABC3” for atmospheric, bidirectional, and contamination corrections of the Canada Centre for Remote Sensing (CCRS), includes atmospheric corrections; the identification of pixels “contaminated” by clouds, snow (including subpixel), and shadows from optically thick clouds; bidirectional reflectance and thermal emissivity corrections; and the replacement of the contaminated pixels in the composites through interpolation. The resulting procedures yield surface reflectance and NDVI fully corrected for bidirectional effects; a version of NDVI corrected for solar zenith only; and surface temperature corrected for atmospheric and surface emissivity effects. An evaluation of the resulting data set shows that the procedures provide significantly improved data products compared with the raw composites, but they do not approximate a single-date image sufficiently closely, especially for AVHRR channel 1, whose reflectance values are generally low. This is attributed to the limitations of the input data and knowledge of atmospheric (and partly bidirectional) characteristics applicable to each composite pixel.

Observations of 13 CO 2 at 73 sites compiled in the GLOBALVIEW database are used for an additional constraint in a global atmospheric inversion of the surface CO 2 flux using CO 2 observations at 210 sites for the 2002–2004 period for 39 land regions and 11 ocean regions. This constraint is implemented using the 13 CO 2 /CO 2 flux ratio modeled with a terrestrial ecosystem model and an ocean model. These models simulate 13 CO 2 discrimination rates of terrestrial photosynthesis and respiration and ocean-atmosphere diffusion processes. In both models, the 13 CO 2 disequilibrium between fluxes to and from the atmosphere is considered due to the historical change in atmospheric 13 CO 2 concentration. For the 2002–2004 period, the 13 CO 2 constraint on the inversion increases the total land carbon sink from 3.40 to 3.70 Pg C yr −1 and decreases the total oceanic carbon sink from 1.48 to 1.12 Pg C yr −1 . The largest changes occur in tropical areas: a considerable decrease in the carbon source in the Amazon forest, and this decrease is mostly compensated by increases in the ocean region immediately west of the Amazon and the southeast Asian land region. Our further investigation through different treatments of the 13 CO 2 /CO 2 flux ratio used in the inversion suggests that variable spatial distributions of the 13 CO 2 isotopic discrimination rate simulated by the models over land and ocean have considerable impacts on the spatial distribution of the inverted CO 2 flux over land and the inversion results are not sensitive to errors in the estimated disequilibria over land and ocean.

Water availability is the dominant control of global terrestrial primary productivity with concurrent effects on evapotranspiration and ecosystem respiration, especially in water-limited ecosystems. Process-oriented ecosystem models are critical tools for understanding land-atmosphere exchanges and for up-scaling this information to regional and global scales. Thus, it is important to understand how ecosystem models simulate ecosystem fluxes under changing weather conditions. Here, we applied both time-series analysis and meta-analysis techniques to study how five ecosystem process-oriented models-simulated gross primary production (GPP), ecosystem respiration (Reco), and evapotranspiration (ET). Ecosystem fluxes were simulated for 3 years at a daily time step from four evergreen and three deciduous Mediterranean oak woodlands (21 site-year measurements; 105 site-year-simulations). Mediterranean ecosystems are important test-beds for studying the interannual dynamics of soil moisture on ecosystem mass and energy exchange as they experience cool, wet winters with hot, dry summers and are typically subject to drought. Results show data-model disagreements at multiple temporal scales for GPP, Reco, and ET at both plant functional types. Overall there was a systematic underestimation of the temporal variation of Reco at both plant functional types at temporal scales between weeks and months, and an overestimation at the yearly scale. Modeled Reco was systematically overestimated during drought for all sites, but daily GPP was systematically underestimated only for deciduous sites during drought. In contrast, daily estimates of ET showed good data-model agreement even during drought conditions. This meta-analysis brings attention to the importance of drought conditions for modeling purposes in representing forest dynamics in water-limited ecosystems. © 2013 Springer Science+Business Media New York.

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m−2 day−1, and an average Nash–Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66 %. SADM overestimated daily GPP by about 15 % during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30 %, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Terrestrial carbon and water cycles are interactively linked at various spatial and temporal scales. Evapotranspiration (ET) plays a key role in the terrestrial water cycle and altering carbon sequestration of terrestrial ecosystems. The study of ET and its response to climate and vegetation changes is critical in China since water availability is a limiting factor for the functioning of terrestrial ecosystems in vast arid and semiarid regions. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model was employed in conjunction with a newly developed leaf area index (LAI) dataset and other spatial data to simulate daily ET and water yield at a spatial resolution of 500 m over China for the period from 2000 to 2010. The spatial and temporal variations of ET and water yield and influences of temperature, precipitation, land cover types, and LAI on ET were analyzed. The validations with ET measured at 5 typical ChinaFLUX sites and inferred using statistical hydrological data in 10 basins showed that the BEPS model was able to simulate daily and annual ET well at site and basin scales. Simulated annual ET exhibited a distinguishable southeast to northwest decreasing gradient, corresponding to climate conditions and vegetation types. It increased with the increase of LAI in 74% of China's landmass and was positively correlated with temperature in most areas of southwest, south, east, and central China and with precipitation in the arid and semiarid areas of northwest and north China. In the Tibet Plateau and humid southeast China, the increase in precipitation might cause ET to decrease. The national mean annual ET varied from 345.5 mm yr−1 in 2001 to 387.8 mm yr−1 in 2005, with an average of 369.8 mm yr−1 during the study period. The overall increase rate of 1.7 mm yr−2 (r = 0.43 p = 0.19) was mainly driven by the increase of total ET in forests. During the period from 2006 to 2009, precipitation and LAI decreased widely and consequently caused a detectable decrease of national total ET. The temporal patterns of ET varied spatially during the 11 yr study period, increasing in 62.2% of China's landmass, especially in the cropland areas of southern Haihe river basin, most of the Huaihe river basin, and southeastern Yangtze river basin. Decreases of annual ET mainly occurred in parts of northeast, north, northwest, south China, especially in eastern Qinghai-Tibet plateau, the south part of Yunnan province, and Hainan province. Vast regions in China, especially the regions south of Yangtze river, experienced significant decreases in water yield caused by the reduction of precipitation and increase of ET while some areas sporadically distributed in northeast, east, northwest, central, and south China experienced increases in water yield. This study shows that recent climatic variability and human activity induced vegetations changes have intensified the terrestrial water cycles in China's terrestrial ecosystems, which is worthy of further thorough investigation.

It is well known that blood pressure (BP) responses to dietary sodium and potassium intakes vary among individuals (salt- and potassium-sensitivity). However, it is unknown whether salt- and/or potassium-sensitivity predict the risk of hypertension. We conducted a dietary sodium and potassium intervention study among 1,906 Han Chinese in 2003-05 and followed the study participants in 2008-09 and 2011-12. The dietary intervention included a 7-day low sodium-feeding (51.3 mmol/day), a 7-day high sodium-feeding (307.8 mmol/day), and a 7-day high sodium-feeding with an oral potassium supplementation (60 mmol/day). Three BP measurements were obtained on each of the last 3 days of each intervention period at the baseline and each of the 3 days of follow-up examinations. Systolic BP responses (mean ± SD) to dietary intervention were -5.5±7.0 for low-sodium, 4.9±6.0 for high-sodium, and -3.5±5.5 for potassium-supplementation. Over an average of 7.4 years of follow-up, we identified 455 incidence hypertension cases (systolic BP≥140 mmHg and/or diastolic BP ≥90 mmHg and/or use of antihypertensive medication). The age-adjusted cumulative incidences of hypertension by the quartiles of systolic BP responses to dietary intervention were showed in the following table. These associations remained after adjustment for multiple covariates. These data indicate that BP responses to dietary sodium and potassium intervention are related to the subsequent risk of hypertension. Furthermore, our study suggests that individuals who are more sensitive to dietary sodium and potassium intake are at an increased risk for hypertension and should be target for dietary intervention.

The timing of crucial events in plant life cycles is shifting in response to climate change. We use phenology records from PlantWatch Canada ‘Citizen Science’ networks to study recent rapid shifts of flowering phenology and its relationship with climate. The average first flower bloom day of 19 Canadian plant species has advanced by about 9 days during 2001–2012. 73% of the rapid and unprecedented first bloom day advances are explained by changes in mean annual national temperature, allowing the reconstruction of historic flower phenology records starting from 1948. The overall trends show that plant flowering in Canada is advancing by about 9 days per °C. This analysis reveals the strongest biological signal yet of climate warming in Canada. This finding has broad implications for niche differentiation among coexisting species, competitive interactions between species, and the asynchrony between plants and the organisms they interact with.

High performance light absorber with a broad bandwidth is particularly desirable for near-infrared photodetection and optical interconnects. Here we demonstrate a dual broadband perfect absorber in the near-infrared regime, which is based on a hybrid plasmonic-photonic microstructure. Such a microstructure is fabricated by self-assembling a monolayer colloidal crystal on an optically opaque metal film followed by depositing a thin metallic half-shell on the top of the colloidal particles. Both experimental and numerical simulation results show that the simply designed absorbers have dual broadband with absorption exceeding 90% in the near-infrared region with the absorption bands being scalable by tuning the size of the colloidal particles. Moreover, the absorption efficiency shows an extremely slight dispersion for the incident angles up to 50 degrees, benefit from the high symmetry as well as the highly modulated plasmonic microstructures that lead to a weak polarization dependence of these two absorption bands. The relative ease of growing high-quality colloidal crystals and the low cost of fabricating such plasmonic-photonic microstructures with high reproducibility could promise applicability of the light absorber in the field of photodetectors, thermal emitters and photovoltaics.

Atmospheric inversions have become an important tool in quantifying carbon dioxide (CO2) sinks and sources at a variety of spatiotemporal scales, but associated large uncertainties restrain the inversion research community from reaching agreements on many important subjects. We enhanced an atmospheric inversion of the CO2 flux for North America by introducing spatially-explicit information on forest stand age for US and Canada as an additional constraint, since forest carbon dynamics are closely related to time since disturbance. To use stand age information in the inversion, we converted stand age into an age factor, and included the covariances between sub-continental regions in the inversion based on the similarity of the age factors. Our inversion results show that, considering age factors, regions with recently-disturbed or old forests are often nudged towards carbon sources, while regions with middle-aged productive forests are shifted towards sinks. This conforms to stand age effects observed in flux networks. At the sub-continental level, our inverted carbon fluxes agree well with continuous estimates of net ecosystem carbon exchange (NEE) upscaled from eddy covariance flux data (EC) based on MODIS data. Inverted fluxes with the age constraint exhibit stronger correlation to these upscaled NEE estimates than those inverted without the age constraint. While the carbon flux at the continental and sub-continental scales is predominantly determined by atmospheric CO2 observations, the age constraint is shown to have potential to improve the inversion of the carbon flux distribution among sub-continental regions, especially for regions lacking atmospheric CO2 observations.

RESUMEUn ratio simple modifie (MSR) est propose pour extraire les parametres biophysiques des forets boreales a l'aide de donnees de teledetection. Cet indice de vegetation est formule en fonction de l'evaluation de plusieurs indices de vegetation derives de la combinaison de deux bandes spectrales, dont les suivants : indice de vegetation par difference normalisee ou indice d'activite vegetale (NDVI), ratio simple (SR), indice de vegetation ajuste en fonction des sols (SAVI, SAVI1, SAVI2), indice de vegetation par difference ponderee (WDVI), indice de vegetation zonale (GEMI), indice de vegetation non lineaire (NLI) et indice de vegetation par difference renormalisee (RDVI). Le ratio simple modifie est une version amelioree des indices de vegetation par difference renormalisee et sert a delimiter les relations de ces derniers avec les parametres biophysiques. Tous les indices ont ete obtenus a partir d'images acquises par le capteur thematique de Landsat-5 dans les bandes 3 (visible) et 4 (proche infraro...

The feasibility of detecting the seasonal variation in leaf area index (LAI) in boreal conifer forests is investigated using optical instruments. The LAI of six stands was measured. They include young and old jack pine (Pinus banksiana) and old black spruce (Picea mariana) located near the southern border (near Prince Albert, Saskatchewan) and near the northern border (near Thompson, Manitoba) of the Canadian boreal ecotone. LAI values of the stands are obtained by making several corrections to the effective LAI measured from the LI-COR LAI-2000 Plant Canopy Analyzer (PCA). The corrections include a foliage element (shoot) clumping index (for clumping at scales larger than the shoot) measured using the optical instrument TRAC (Tracing Radiation and Architecture of Canopies) developed by Chen and Cihlar (Chen, J.M. and Cihlar, J., 1995a, Plant canopy gap size analysis theory for improving optical measurements of leaf area index of plant canopies, Appl. Opt., 34: 6211–6222), a needle-to-shoot area ratio (for clumping within the shoot) obtained from shoot samples, and a woody-to-total area ratio obtained through destructive sampling of trees. It is found that the effective LAI varied about 5% to 10% in the growing season and the element clumping index remained almost unchanged. The needle-to-shoot area ratio varied the most, about 15% to 25%, which is of the same order of magnitude as the expected seasonal variability in LAI. This demonstrates that most of the seasonal variation information is contained in the needle-to-shoot area ratio, which can not be measured indirectly using in situ optical instruments and has to be obtained from a large quantity of shoot sample analysis which is laborious and error-prone. Based on our experience, an improved and convenient shoot sampling strategy is suggested for future studies. The optically-based LAI values were compared with destructive sampling results for three of the stands. Based on error analysis, we believe that optical measurements combined with shoot sample analysis can produce LAI values for conifer stands which are more accurate than destructive sampling results.

Vegetation indices, including the simple ratio (SR) and the normalized difference vegetation index (NDVI), from Landsat TM data were correlated to ground-based measurements of LAI, effective LAI, and the crown closure in boreal conifer forests located near Candle Lake and Prince Albert, Saskatchewan and near Thompson, Manitoba, as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). The measurements were made using two optical instruments: the Plant Canopy Analyzer (LAI-2000, LI-COR) and the TRAC (Tracing Radiation and Architecture of Canopies). The TRAC was recently developed to quantify the effect of canopy architecture on optical measurements of leaf area index. The stands were located on georeferenced Landsat TM images using global positioning system (GPS) measurements. It is found that late spring Landsat images are superior to summer images for determining overstory LAI in boreal conifer stands because the effect of the understory is minimized in the spring before the full growth of the understory and moss cover. The effective LAI, obtained from gap fraction measurements assuming a random distribution of foliage spatial positions, was found to be better correlated to SR and NDVI than LAI. The effective LAI is less variable and easier to measure than LAI, and is also an intrinsic attribute of plant canopies. It is therefore suggested to use effective LAI as the most important parameter for radiation interception considerations.

A two-dimensional E-e model, which included the effects of plant-atmosphere interaction, was used to simulate air flow downwind of forest edges for the purpose of predicting the microclimate in forest openings. A suitable set of wall functions was selected to consider the aerodynamic effects of the ground in the opening. The model with discretization and parameter schemes was validated using a set of data from a wind-tunnel experiment. The simulated wind speed and turbulence kinetic energy closely agreed with the measured values. After validation, the model was used to predict eddy diffusivity in the lee of the forest edge. The modelled spatial distribution of the eddy diffusivity agreed in general with that calculated using wind-tunnel measurements. The usefulness and limitations of the E-e model are discussed.

Measurements of the fraction of photosynthetically active radiation (FPAR) absorbed by the forest overstory were made at 20 sites in black spruce (Picea mariana) and jack pine (Pinus banksiana) boreal forests located in Saskatchewan and Manitoba, Canada. Canopies of both species have similar vertical tree crown structure but different branch and shoot architecture. Intensive investigation was made on the effect of these canopy architecture on the penetration of total visible radiation into the canopy at various solar zenith angles /spl theta/, quantified using the projection coefficient G/sub t/(/spl theta/). Based on experimental evidence, constant values of G/sub t/(/spl theta/) and the above- and below-canopy PAR reflectivities are suggested for these two species for the calculation of daily green FPAR. The calculation then requires only a single stand parameter: the effective green leaf area index (LAI) L/sub eg/, which is similar to the effective LAI L/sub e/ measured using optical instruments but reduced by a small fraction to remove the contribution of woody material to the total above-ground plant area. Daily green FPAR of the sites was correlated with the Simple Ratio (SR) and the Normalized Difference Vegetation Index (NDVI) obtained from Landsat 5 TM images. The correlation was better in late-spring than in mid-summer, suggesting spring images are more useful for obtaining FPAR of the overstory. Comparisons of the present with previous results suggest that the background (understory and ground cover) signal and the tree crown shadows are important in satellite measurements of FPAR.

In recent years, the methodology in ground-based optical measurements of leaf area index (LAI) of plant canopies has been substantially improved after the introduction of canopy gap size analysis methods. In this paper, the two methods by Chen and Black (1992) and Chen and Cihlar (in press) are compared for four boreal conifer stands located near Prince Albert, Saskachewan, and Thompson, Manitoba, Canada. The data used in the analysis were obtained from a new sunfleck-LAI instrument, the TRAC (Tracing Radiation and Architecture of Canopies), which measures the photosynthetic photon flux density along transects beneath the overstory at a rate of 100 samples per meter. It is confirmed in this study that the needle shoots of conifer trees can be treated as the basic foliage units (elements) for radiation interception considerations. The effect of foliage clumping at scales larger than the shoots is quantified using an element clumping index. This is necessary for indirect measurements of LAI based on the gap fraction principle using optical instruments such as the LI-COR LAI-2000. The values of element clumping index derived from these two methods agree within 17% for all stands investigated. However, the values obtained using Chen and Black's method are consistently smaller than those calculated using Chen and Cihlar's method. The difference results from a negative bias introduced in the method of Chen and Black which requires the assumption for a random spatial distribution of foliage clumps (tree crowns). The method of Chen and Cihlar makes no assumption of foliage distribution patterns and is therefore more reliable. Yet, Chen and Black's method allows the derivation of several canopy architectural parameters which are useful for modeling radiative regimes in forest canopies. It is concluded that for remote sensing and other studies, a large quantity of ground truth LAI data can be acquired quickly and accurately using a combination of indirect optical measurements by the LAI-2000 for the foliage angular distribution and the TRAC for the foliage spatial distribution. >

In this paper, we present an approach for generating a consistent long-term global leaf area index (LAI) product (1981-2011) by quantitative fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and historical Advanced Very High Resolution Radiometer (AVHRR) data. First, a MODIS LAI series was generated from MODIS data based on the GLOBCARBON LAI algorithm. Then, the relationships between AVHRR observations and MODIS LAI were established pixel by pixel using two data series during overlapped period (2000-2006). Then the AVHRR LAI back to 1981 was estimated from historical AVHRR observations based on these pixel-level relationships. The long-term LAI series was made up by combination of AVHRR LAI (1981-2000) and MODIS LAI (2000-2011). The LAI derived from AVHRR was intercompared with that from MODIS during the overlapped period. The results show that the LAIs from these two different sensors are good consistency, with LAI differences are within +/- 0.6 over 99.0% vegetated pixels. The long-term LAI was also compared with field measurements, which has an error of 0.81 LAI on average. Compared with the LAI retrieved directly from the GLOBCARBON algorithm, the LAI derived by our method has a lower temporal noise, which means uncertainties from the low quality of AVHRR measurements can be reduced with the aid of high-quality MODIS data. This product is hosted on the GlobalMapping Web site (http://www.globalmapping.org/globalLAI) for free download, which will provide a long-term LAI over 30 years for modeling the carbon and water cycles.

Existing global leaf area index (LAI) products have a common problem of too large seasonal variations for conifer stands. The seasonal variation of remotely sensed LAI is often distorted due to many confounding factors. We propose a methodology to quantify the LAI seasonal pattern based on needle lifespan and meteorological conditions. In this paper, we test this methodology in two conifer stands in Ontario, Canada. Needle growth and senescence rates were quantified from needle elongation measurements and litterfall collection. By measuring the average needle lifespan and assuming a dynamic equilibrium of LAI for the full annual cycle, the amount of needles renewed annually can be estimated. Then it is seasonally ‘distributed’ based on these two rates in order to reckon seasonal variations of new and old needle cohorts. These measured LAI seasonal trajectories were compared with combined measurements by TRAC (Tracing Radiation and Architecture of Canopies) and LAI 2000 plant canopy analyzer. The difference between peak LAI from needle growth and fall and that from optical instruments is constrained within 15%. Meanwhile, LAI values from needle growth and fall beyond the growing season are not fallaciously low like LAI from remote sensing data, resulting in a more realistic seasonal variation of needles than that is retrieved from algorithms using remote sensing data. We believe this study can be a positive step towards improving global LAI mapping.

[1] Land surface phenology (LSP) is an integrative indicator of vegetation dynamics under a changing environment. Increasing amounts of remote sensing measurements and CO2flux observations offer unprecedented opportunities to quantify LSP phases at landscape scale. LSP start of season (SOS) and end of season (EOS) estimates are often based on the use of a single-purpose vegetation index derived from optical satellite data, characterized by poor performances in decoupling soil and snow cover dynamics from LSP cycles, as well as contrasting responses of the needleleaf and broadleaf forests in boreal ecosystems. We propose a new remote-sensing-based phenology index (PI) which combines the merits of normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) by taking the difference of squared greenness and wetness to remove the soil and snow cover dynamics from key vegetation LSP cycles. We have cross-validated the remote-sensing-based LSP dates with those of CO2 flux observations from 11 selected tower sites across Canada and the United States consisting of needleleaf forests, broadleaf forests, and croplands. The results indicate that PI estimates the SOS and EOS dates better than NDVI when compared to the LSP dates from CO2flux measurements (reduced RMSE, bias and dispersions, and higher correlation). PI-based SOS and EOS estimates are in good agreement with those derived from CO2flux measurements with mean bias comparable to the temporal resolution of the high-quality, 8-day composite satellite measurements. Finally, PI also shows a smoother time series compared to NDVI and NDII.

COMMENTARY Common but differentiated IBI Prize Essay LETTERS I BOOKS I POLICY FORUM I EDUCATION FORUM I PERSPECTIVES LETTERS edited by Jennifer Sills Iconic CO 2 Time Series at Risk THE STEADY RISE IN ATMOSPHERIC LONG- lived greenhouse gas concentrations is the main driver of contemporary climate change. The Mauna Loa CO 2 time series (1, 2), started by C. D. Keeling in 1958 and maintained today by the Scripps Institution of Oceanography and the Earth System Research Laboratory (ESRL) of NOAA, is iconic evidence of the effect of human- caused fossil fuel and land-use change emis- sions on the atmospheric increase of CO 2 . The continuity of such records depends criti- cally on having stable funding, which is chal- lenging to maintain in the context of 3- to 4-year research grant funding cycles (3), and LEAH R. GERBER Faculty of Ecology, Evolution, and Environmental Sciences, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA. E-mail: leah.gerber@asu.edu References 1. Associated Press, The New York Times, 6 July 2012, p. A7 (www.nytimes.com/2012/07/06/ world/europe/south-korea-whaling-plan-criticized.html). 2. S. Herman, Voice of America, 24 July 2012 (www.voanews.com/content/south-korea-still- considering-resumption-of-whaling/1444081.html). 3. L. R. Gerber, L. Morissette, K. Kaschner, D. Pauly, Science 323, 880 (2009). 4. R. Black, BBC News, 5 July 2012 (www.bbc.co.uk/news/science-environment-18719512). is currently threatened by the fi nancial crisis. The ESRL Global Monitoring Division maintains a network of about 100 surface and aircraft sites worldwide at which whole air samples are collected approximately every week for analysis of CO 2 , CH 4 , CO, halocar- bons, and many other chemical species (4). This is complemented by high-frequency measurements at the Mauna Loa, Barrow, American Samoa, and South Pole obser- vatories, and about 10 North American tall towers. The success of the NOAA program has inspired similar efforts in Europe (5), China (6), India (7), and Brazil (8), with the United Nations World Meteorological Orga- nization providing guidance and precision requirements through the Global Atmosphere Watch program (9), but no funding. 31 AUGUST 2012 Downloaded from www.sciencemag.org on August 17, 2015 AT THE RECENT INTERNATIONAL WHALING COMMISSION’S ANNUAL meeting in Panama, South Korean offi cials announced their plan to initiate a “scientifi c whaling” program (1). This announcement came as a surprise given the general sentiment that the global demand for whale meat is declining. After weeks of international outcry, on 17 July, South Korea reversed their decision to hunt whales for research, but the issue is not dead (2). South Korea claimed that the goal of the scientifi c whaling pro- gram is to study the types and amounts of fi sh whales eat, given confl ict with fi sher- ies. Yet, it is well established in the scien- tifi c literature that there are many ways to study whale diet without killing them (3). Decades of fruitless negotiation between pro- and anti-whaling nations suggests a broken system, wrought with loopholes that allow unsustainable whal- ing to continue. Within this broken system, there is no incentive to reduce whaling, as the recent announcement by South Korea shows. Whaling groups are unwilling to compromise by allowing a sustainable harvest of whales, so unsustainable (scientifi c) whaling continues. To ensure a future of both whales and whalers, we must har- ness the passion and value that people place on living whales, with- out telling people what to do or force one set of values on others. We need novel, out-of-the-box approaches to effective management and conservation of whales. We must compromise to ensure reduc- tions in whales being killed, better oversight of countries that har- vest them, and limited whaling that does not threaten the persis- tence of whales. For those who believe that whaling is unethical, I challenge you to put forward alternative ideas to a global moratorium that fosters the “loophole” of scientifi c whaling. With new plans to develop scientifi c whaling programs (4), the current global moratorium is clearly bro- ken. Scientists, conservation advocates, resource managers, and the public must work together to develop new approaches to ensure the persistence of whales in our oceans. The data collected by NOAA and its worldwide partners have been used not only to demonstrate the unassailable rise of atmo- spheric greenhouse gas concentrations, but also to infer the magnitudes, locations, and times of surface-atmosphere exchange of those gases based on small concentration gradients between sites (10). Important fi nd- ings from analysis of these records include the detection of a signifi cant terrestrial car- bon sink at northern mid-latitudes (11) and subsequent research aimed at identifying the mechanisms by which that sink must operate. Long-term, high-quality, atmospheric mea- surements are crucial for quantifying trends in greenhouse gas fl uxes and attributing them to fossil fuel emissions, changes in land-use and management, or the response of natural VOL 337 SCIENCE www.sciencemag.org Published by AAAS CREDIT: LEAH GERBER/ ARIZONA STATE UNIVERSITY The Scientifi c Whaling Loophole

[1] Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such asemax (LUE), Vcmax (unstressed Rubisco catalytic capacity) or Jmax (the maximum electron transport rate).

[1] Recent climate variability (increasing temperature, droughts) and atmospheric composition changes (nitrogen deposition, rising CO2 concentration) along with harvesting, wildfires, and insect infestations have had significant effects on U.S. forest carbon (C) uptake. In this study, we attribute C changes in the conterminous U.S. forests to disturbance and non-disturbance factors with the help of forest inventory data, a continental stand age map, and an updated Integrated Terrestrial Ecosystem Carbon Cycle model (InTEC). We grouped factors into disturbances (harvesting, fire, insect infestation) and non-disturbances (CO2 concentration, N deposition, and climate variability) and estimated their subsequent impacts on forest regrowth patterns. Results showed that on average, the C sink in the conterminous U.S. forests from 1950 to 2010 was 206 Tg C yr � 1 with 87% (180 Tg C yr � 1 ) of the sink in living biomass. Compared with the simulation of all factors combined, the estimated C sink would be reduced by 95 Tg C yr � 1 if disturbance factors were omitted, and reduced by 50 Tg C yr � 1 if non-disturbance factors were omitted. Our study also showed diverse regional patterns of C sinks related to the importance of driving factors. During 1980–2010, disturbance effects dominated the C changes in the South and Rocky Mountain regions, were almost equal to non-disturbance effects in the North region, and had minor effects compared with non-disturbance effects in the West Coast region.

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000-2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America. Thus, the RCIS focuses on model simulations available from analyses that have been completed by ongoing NACP projects and other recently published studies. The TBM flux estimates are compared and evaluated over different spatial (1{sup o} x 1{sup o} and spatially aggregated to different regions) and temporal (monthly and annually) scales. The range inmore » model estimates of net ecosystem productivity (NEP) for North America is much narrower than estimates of productivity or respiration, with estimates of NEP varying between -0.7 and 2.2 PgC yr{sup -1}, while gross primary productivity and heterotrophic respiration vary between 12.2 and 32.9 PgC yr{sup -1} and 5.6 and 13.2 PgC yr{sup -1}, respectively. The range in estimates from the models appears to be driven by a combination of factors, including the representation of photosynthesis, the source and of environmental driver data and the temporal variability of those data, as well as whether nutrient limitation is considered in soil carbon decomposition. The disagreement in current estimates of carbon flux across North America, including whether North America is a net biospheric carbon source or sink, highlights the need for further analysis through the use of model runs following a common simulation protocol, in order to isolate the influences of model formulation, structure, and assumptions on flux estimates.« less

The kallikrein-kinin system (KKS) has been implicated in the pathogenesis of salt-sensitive hypertension in animal models. We comprehensively examined the association between genetic variants of the KKS and blood pressure (BP) response to dietary sodium intervention among participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study. A 7-day low-sodium dietary intervention followed by a 7-day high-sodium dietary intervention was carried out among 1,906 GenSalt participants from rural areas of north China. Nine BP measurements were obtained at baseline and on the last three days of each intervention period using a random-zero sphygmomanometer. The percentage changes in mean BP from baseline to low-sodium intervention and from low-sodium to high-sodium intervention were used to assess individual salt-sensitivity. A total of 205 tagSNPs and functional SNPs of eleven genes of the KKS ( BDKRB1 , BDKRB2 , CPN1 , CPN2 , CPM , ECE1 , KLK1 , KLKB1 , KNG1 , MME , SERPINA4 ) were selected and genotyped in this study. Single marker analyses were conducted using the Family Based Association Test program. Genetic variants in the bradykinin receptor B2 ( BDKRB2 ) and endothelin converting enzyme 1 ( ECE1 ) genes showed significant associations with salt sensitivity even after adjusting for multiple testing using the false discovery rate method. SNP rs11847625 of BDKRB2 was significantly associated with systolic BP (SBP) response to low-sodium intervention ( P = 0.0001). Compared to its major allele G, carriers of the minor allele C had greater SBP decrease during low-sodium intervention. Furthermore, a haplotype containing allele C was associated with greater SBP increase to high-sodium intervention ( P = 0.0009). Seven SNPs of ECE1 , one of the degrading enzymes of kinins, were significantly associated with diastolic BP (DBP) response to low-sodium intervention ( P values ranged from 0.0003 to 0.002). Two haplotypes in the linkage disequilibrium block including these seven SNPs were significantly associated with DBP response to low-sodium intervention (P=0.0004 and 0.003, respectively). Our study found that the genetic variants of the KKS were associated with salt sensitivity of BP. Replication and functional studies of the identified variants are warranted in the future.

Blood pressure (BP) responses to dietary sodium and potassium interventions vary among individuals (salt- and potassium-sensitivity). However, it is unknown whether salt- and/or potassium-sensitivity is a reproducible trait. We repeated the dietary sodium and potassium intervention among 488 Han Chinese who participated in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) four years after the original dietary intervention. The same dietary intervention protocol, which included a 7-day low sodium-feeding (51.3 mmol/day), a 7-day high sodium-feeding (307.8 mmol/day), and a 7-day high sodium-feeding with an oral potassium supplementation (60 mmol/day), was applied in both the original and repeated studies. Three BP measurements were obtained during each of the 3 days of baseline observation and on days 5, 6, and 7 of each intervention period. Three timed urinary samples were collected to measure sodium and potassium excretion at baseline and during each intervention phase. On average, study participants were 39.7 years old and 49.4% of them were male. Study participants had a mean body mass index of 23.7 kg/m 2 , systolic BP of 118.1 mmHg, diastolic BP of 74.4 mmHg, urinary excretion of sodium of 258.8 mmol/24-hrs, and urinary excretion of potassium of 38.8 mmol/24-hrs. The results from the 24-h urinary excretions of sodium and potassium showed excellent compliance with the study diet. BP responses to dietary intervention in the original and repeated studies were highly correlated. For example, the correlation coefficients for systolic BP between original and repeated studies were 0.7681 at baseline, 0.7902 during low-sodium, 0.8045 during high-sodium, and 0.8232 during high-sodium and potassium supplementation intervention (all p

[1] Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3-dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.

Despite the wide acceptance of the “big-leaf” upscaling strategy in evapotranspiration modeling (e.g., the Penman-Monteith model), its usefulness in simulating canopy photosynthesis may be limited by the underlying assumption of homogeneous response of carbon assimilation light-response kinetics through the canopy. While previous studies have shown that the separation of the canopy into sunlit and shaded parts (i.e., two-leaf model) is typically more effective than big-leaf models for upscaling photosynthesis from leaf to canopy, a systematic comparison between these two upscaling strategies among multiple ecosystems has not been presented. In this study, gross primary productivity was modeled using two-leaf and big-leaf upscaling approaches in the Boreal Ecosystem Productivity Simulator for shrublands, broadleaf, and conifer forest types. When given the same leaf-level photosynthetic parameters, the big-leaf approach significantly underestimated canopy-level GPP while the two-leaf approach more closely predicted both the magnitude and day-to-day variability in eddy covariance measurements. The underestimation by the big-leaf approach is mostly caused by its exclusion of the photosynthetic contributions of shaded leaves. Tests of the model sensitivity to a foliage clumping index revealed that the contribution of shaded leaves to the total simulated productivity can be as high as 70% for highly clumped stands and seldom decreases below ∼40% for less-clumped canopies. Our results indicate that accurate upscaling of photosynthesis across a broad array of ecosystems requires an accurate description of canopy structure in ecosystem models.

[1] Net primary productivity (NPP) is a key flux in the terrestrial ecosystem carbon balance, as it summarizes the autotrophic input into the system. Forest NPP varies predictably with stand age, and quantitative information on the NPP-age relationship for different regions and forest types is therefore fundamentally important for forest carbon cycle modeling. We used four terms to calculate NPP: annual accumulation of live biomass, annual mortality of aboveground and belowground biomass, foliage turnover to soil, and fine root turnover in soil. For U.S. forests the first two terms can be reliably estimated from the Forest Inventory and Analysis (FIA) data. Although the last two terms make up more than 50% of total NPP, direct estimates of these fluxes are highly uncertain due to limited availability of empirical relationships between aboveground biomass and foliage or fine root biomass. To resolve this problem, we developed a new approach using maps of leaf area index (LAI) and forest age at 1 km resolution to derive LAI-age relationships for 18 major forest type groups in the USA. These relationships were then used to derive foliage turnover estimates using species-specific trait data for leaf specific area and longevity. These turnover estimates were also used to derive the fine root turnover based on reliable relationships between fine root and foliage turnover. This combination of FIA data, remote sensing, and plant trait information allows for the first empirical and reliable NPP-age relationships for different forest types in the USA. The relationships show a general temporal pattern of rapid increase in NPP in the young ages of forest type groups, peak growth in the middle ages, and slow decline in the mature ages. The predicted patterns are influenced by climate conditions and can be affected by forest management. These relationships were further generalized to three major forest biomes for use by continentalscale carbon cycle models in conjunction with remotely sensed land cover types. Citation: He, L., J. M. Chen, Y. Pan, R. Birdsey, and J. Kattge (2012), Relationships between net primary productivity and forest stand age in U.S. forests, Global Biogeochem. Cycles, 26, GB3009, doi:10.1029/2010GB003942.

Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 and 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.

A model is developed to simulate the potential temperature and the height of the mixed layer under advection conditions. It includes analytic expressions for the effects of mixed-layer conditions upwind of the interface between two different surfaces on the development of the mixed layer downwind from the interface. Model performance is evaluated against tethersonde data obtained on two summer days during sea breeze flow in Vancouver, Canada. It is found that the mixed-layer height and temperature over the ocean has a small but noticeable effect on the development of the mixed layer observed 10 km inland from the coast. For these two clear days, the subsidence velocity at the inversion base capping the mixed layer is estimated to be about 30 mm s−1 from late morning to late afternoon. When the effects of subsidence are included in the model, the mixed-layer height is considerably underpredicted, while the prediction for the mean potential temperature in the mixed layer is considerably improved. Good predictions for both height and temperature can be obtained when values for the heat entrainment ratio,c, 0.44 and 0.68 for these two days respectively for the period from 1000 to 1300 LAT, were used. These values are estimated using an equation including the additional effects on heat entrainment due to the mechanical mixing caused by wind shear at the top of the mixed layer and surface friction. The contribution of wind shear to entrainment was equal to, or greater than, that from buoyant convection resulting from the surface heat flux. Strong wind shear occurred near the top of the mixed layer between the lower level inland flow and the return flow aloft in the sea breeze circulation.

The hydrological cycle has significant effects on the terrestrial carbon (C) balance through its controls on photosynthesis and C decomposition. A detailed representation of the water cycle in terrestrial C cycle models is essential for reliable estimates of C budgets. However, it is challenging to accurately describe the spatial and temporal variations of soil water, especially for regional and global applications. Vertical and horizontal movements of soil water should be included. To constrain the hydrology-related uncertainty in modelling the regional C balance, a three-dimensional hydrological module was incorporated into the Integrated Terrestrial Ecosystem Carbon-budget model (InTEC V3.0). We also added an explicit parameterization of wetlands. The inclusion of the hydrological module considerably improved the model's ability to simulate C content and balances in different ecosystems. Compared with measurements at five flux-tower sites, the model captured 85% and 82% of the variations in volumetric soil moisture content in the 0–10 cm and 10–30 cm depths during the growing season and 84% of the interannual variability in the measured C balance. The simulations showed that lateral subsurface water redistribution is a necessary mechanism for simulating water table depth for both poorly drained forest and peatland sites. Nationally, soil C content and their spatial variability are significantly related to drainage class. Poorly drained areas are important C sinks at the regional scale, however, their soil C content and balances are difficult to model and may have been inadequately represented in previous C cycle models. The InTEC V3.0 model predicted an annual net C uptake by Canada's forests and wetlands for the period 1901–1998 of 111.9 Tg C yr −1 , which is 41.4 Tg C yr −1 larger than our previous estimate (InTEC V2.0). The increase in the net C uptake occurred mainly in poorly drained regions and resulted from the inclusion of a separate wetland parameterization and a detailed hydrologic module with lateral flow in InTEC V3.0. DOI: 10.1111/j.1600-0889.2005.00168.x

The variations of soil water content (SWC) and its influences on the carbon (C) cycle in Canada's forests and wetlands were studied through model simulations using the Integrated Terrestrial Ecosystem Carbon (InTEC) model. It shows that Canada's forests and wetlands experienced spatially and temporally heterogeneous changes in SWC from 1901 to 2000. SWC changes caused average NPP to decrease 40.8 Tg C yr-1 from 1901 to 2000, whereas the integrated effect of non-disturbance factors (climate change, CO2 fertilization and N deposition) enhanced NPP by 9.9%. During 1981–2000, the reduction of NPP caused by changes in SWC was 58.1 Tg C yr-1 whereas non-disturbance factors together caused NPP to increase by 16.6%. SWC changes resulted in an average increase of 4.1 Tg C yr-1 in the net C uptake during 1901–2000, relatively small compared with the enhancement in C uptake of 50.2 Tg C yr-1 by the integrated effect of non-disturbance factors. During 1981–2000, changes in SWC caused a reduction of 3.8 Tg C yr-1 in net C sequestration whereas the integrated factors increased net C sequestration by 54.1 Tg C yr-1. Increase in SWC enhanced C sequestration in all ecozones.DOI: 10.1111/j.1600-0889.2010.00459.x

A nested inverse modelling system was developed for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Monthly inverse modelling was conducted using CO2 concentration measurements of 3 yr (2001–2003) at 88 sites. Inversion results show that in 2003 the global carbon sink is −2.76 ± 0.55 Pg C. Oceans and lands are responsible for 88.5% and 11.5% of the sink, respectively. Northern lands are the largest sinks with North America contributing a sink of −0.97 ± 0.21 Pg C in 2003, of which Canada's sink is −0.34 ± 0.14 Pg C. For Canada, the inverse results show a spatial pattern in agreement, for the most part, with a carbon source and sink distribution map previously derived through ecosystem modelling. However, discrepancies in the spatial pattern and in flux magnitude between these two estimates exist in certain regions. Numerical experiments with a full covariance matrix, with the consideration of the error structure of the a priori flux field based on meteorological variables among the 30 North America regions, resulted in a small but meaningful improvement in the inverted fluxes. Uncertainty reduction analysis suggests that new observation sites are still needed to further improve the inversion for these 30 regions in North America.DOI: 10.1111/j.1600-0889.2006.00235.x

[1] Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty.

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m−2 y−1 during the spring transition period, and +75 ± 130 g C m−2 y−1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology, and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately, and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models., JRC.H.2-Air and Climate