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Photosynthesis–irradiance relationships of macroalgal communities and thalli of dominant species in shallow coastal Danish waters were measured over a full year to test how well community production can be predicted from environmental (incident irradiance and temperature) and community variables (canopy absorptance, species number and thallus metabolism). Detached thalli of dominant species performed optimally at different times of the year, but showed no general seasonal changes in photosynthetic features. Production capacity of communities at high light varied only 1.8-fold over the year and was unrelated to incident irradiance, temperature and mean thallus photosynthesis, while community absorptance was a highly significant predictor. Actual rates of community photosynthesis were closely related to incident and absorbed irradiance alone. Community absorptance in turn was correlated to canopy height and species richness. The close relationship of community photosynthesis to irradiance is due to the fact that (1) large differences in thallus photosynthesis of individual species are averaged out in communities composed of several species, (2) seasonal replacement of species keeps communities metabolically active, and (3) maximum possible absorptance at 100% constrains the total photosynthesis of all species. Our results imply that the photosynthetic production of macroalgal communities is more predictable than their complex and dynamic nature suggest and that predictions are possible over wide spatial scales in coastal waters by measurements of vegetation cover, incoming irradiance and canopy absorptance. [ABSTRACT FROM AUTHOR]

Abstract: Some form of the light use efficiency (LUE) model is used in most models of ecosystem carbon exchange based on remote sensing. The strong relationship between the normalized difference vegetation index (NDVI) and light absorbed by green vegetation make models based on LUE attractive in the remote sensing context. However, estimation of LUE has proven problematic since it varies with vegetation type and environmental conditions. Here we propose that LUE may in fact be correlated with vegetation greenness (measured either as NDVI at constant solar elevation angle, or a red edge chlorophyll index), making separate estimates of LUE unnecessary, at least for some vegetation types. To test this, we installed an automated tram system for measurement of spectral reflectance in the footprint of an eddy covariance flux system in the Southern California chaparral. This allowed us to match the spatial and temporal scales of the reflectance and flux measurements and thus to make direct comparisons over time scales ranging from minutes to years. The 3-year period of this study included both “normal” precipitation years and an extreme drought in 2002. In this sparse chaparral vegetation, diurnal and seasonal changes in solar angle resulted in large variation in NDVI independent of the actual quantity of green vegetation. In fact, one would come to entirely different conclusions about seasonal changes in vegetation greenness depending on whether NDVI at noon or NDVI at constant solar elevation angle were used. Although chaparral vegetation is generally considered “evergreen”, we found that the majority of the shrubs were actually semi-deciduous, leading to large seasonal changes in NDVI at constant solar elevation angle. LUE was correlated with both greenness indices at the seasonal timescale across all years. In contrast, the relationship between LUE and PRI was inconsistent. PRI was well correlated with LUE during the “normal” years but this relationship changed dramatically during the extreme drought. Contrary to expectations, none of the spectral reflectance indices showed consistent relationships with CO2 flux or LUE over the diurnal time-course, possibly because of confounding effects of sun angle and stand structure on reflectance. These results suggest that greenness indices can be used to directly estimate CO2 exchange at weekly timescales in this chaparral ecosystem, even in the face of changes in LUE. Greenness indices are unlikely to be as good predictors of CO2 exchange in dense evergreen vegetation as they were in the sparse, semi-deciduous chaparral. However, since relatively few ecosystems are entirely evergreen at large spatial scales or over long time spans due to disturbance, these relationships need to be examined across a wider range of vegetation types. [Copyright &y& Elsevier]

Abstract: A simple grassland process model is tested against ground measurements collected during 15 years in the sahelian zone in Mali. The model uses standard daily meteorological variables and a limited number of site specific parameters to simulate herbage growth and canopy functioning. The model has two calibration parameters. Due probably to the strong interannual variation of both the herbaceous layer in terms of floristic composition and soil nutrient mineralization, the use of default values for the two calibration parameters leads to large errors in the prediction of herbage yields. In contrast, once the parameters have been optimised, a good concordance is found between the model outputs and the seasonal variation of the herbage standing mass in sites on sandy soils located along a north-south bioclimatic gradient. [Copyright &y& Elsevier]

Abstract: To investigate the responses of leaf photosynthesis and plant growth to a moving lighting system, potted gerberas (Gerbera jamesonii H. Bolus ex J.D. Hook “Festival”) were grown under supplemental lighting in a greenhouse with either a stationary or a moving lighting system positioned above the benches. The stationary system consisted of a fixed high pressure sodium (HPS) lighting system, while the moving lighting system consisted of a moving HPS fixture attached to a cable system to move the light fixture back and forth over the crop. In both cases, the supplemental lighting was applied from 6:00 to 24:00h with the same supplemental daily light integral (4.9molm−2 day−1). Moving lamps significantly increased leaf photosynthetic capacity as represented by light saturated net CO2 exchange rate (NCER) (A sat), light- and CO2-saturated rate of NCER (A max), maximum rate of Rubisco carboxylation (V cmax), maximum rate of electron transport (J max) and rate of triose phosphate utilization. However, in situ leaf NCER and stomatal conductance, leaf chlorophyll content index, leaf area, leaf thickness, fresh weight of plants were significantly lower under moving lighting than under stationary lighting. It is suggested that the reduced growth of plants under moving lighting might be due to (1) the overall lower light use efficiency of leaves under moving lighting than those under stationary lighting; (2) the slower response time of the photosynthetic system compared to the rate of change in light intensity under moving lighting. [Copyright &y& Elsevier]

Maximum light use efficiency (ϵmax) is a key parameter for the estimation of net primary productivity (NPP) derived from remote sensing data. There are still many divergences about its value for each vegetation type. The ϵmax for some typical vegetation types in China is simulated using a modified least squares function based on NOAA/AVHRR remote sensing data and field-observed NPP data. The vegetation classification accuracy is introduced to the process. The sensitivity analysis of ϵmax to vegetation classification accuracy is also conducted. The results show that the simulated values of ϵmax are greater than the value used in CASA model, and less than the values simulated with BIOME-BGC model. This is consistent with some other studies. The relative error of ϵmax resulting from classification accuracy is -5.5%–8.0%. This indicates that the simulated values of ϵmax are reliable and stable. [ABSTRACT FROM AUTHOR]

Abstract: The relationships between ecosystem-level light use efficiency (LUE) obtained from an eddy covariance flux tower and MODIS-derived values of a scaled Photochemical Reflectance Index (sPRI) were investigated for a boreal aspen stand (Populus tremuloides Michx.) in Saskatchewan, Canada. Using MODIS ocean band 11 at 531 nm, we tried to detect variations in canopy reflectance related to the xanthophyll cycle. We tested several other MODIS bands as the reference band because the 570 nm reference band that had been determined to be optimum for calculating PRI in earlier studies is not available on MODIS. While LUE varied greatly within the 2001, 2002, and 2003 growing seasons, the Normalized Difference Vegetation Index (NDVI) calculated from tower sensors remained stable. LUE had a negative exponential relationship with vapor pressure deficit and air temperature, and was at a maximum when absorbed PAR was <200 μmol m−2 s−1. The range and magnitude of tower-based LUE values were smaller on clear days, when MODIS acquisitions were possible, than they were overall. Furthermore, the orbital parameters of the Terra and Aqua satellites restricted MODIS acquisitions to a 2.5-h period in early afternoon at our study site when LUE values were typically lower than they were earlier in the day. Strong correlations between MODIS-sPRI and LUE were found only for backscatter reflectance scenes when band 13 (667 nm) was used as the reference band. The correlations were higher for sPRI calculated from top of atmosphere reflectances than for surface reflectances (r 2 =0.76 and 0.53, respectively). The absolute backscatter reflectance of bands 11, 12 (551 nm), and 13 all decreased with increasing LUE. The decrease in band 13 suggests that the correlation between sPRI and LUE that we observed was caused by reductions in canopy chlorophyll content from 2001 to 2003 and/or by increased visibility of brighter non-photosynthetic material. Regional values of sPRI from 260 deciduous forest pixels in the 10,000 km2 vicinity of the tower for two contrasting days, one in 2001 and one in 2003, were consistent with that observed for the flux tower footprint. [Copyright &y& Elsevier]

Abstract: Ecosystem models are routinely used to estimate net primary production (NPP) from the stand to global scales. Complex ecosystem models, implemented at small scales (&#60;10 km2), are impractical at global scales and, therefore, require simplifying logic based on key ecological first principles and model drivers derived from remotely sensed data. There is a need for an improved understanding of the factors that influence the variability of NPP model estimates at different scales so we can improve the accuracy of NPP estimates at the global scale. The objective of this study was to examine the effects of using leaf area index (LAI) and three different aggregated land cover classification products–two factors derived from remotely sensed data and strongly affect NPP estimates–in a light use efficiency (LUE) model to estimate NPP in a heterogeneous temperate forest landscape in northern Wisconsin, USA. Three separate land cover classifications were derived from three different remote sensors with spatial resolutions of 15, 30, and 1000 m. Average modeled net primary production (NPP) ranged from 402 gC m−2 year−1 (15 m data) to 431 gC m−2 year−1 (1000 m data), for a maximum difference of 7%. Almost 50% of the difference was attributed each to LAI estimates and land cover classifications between the fine and coarse scale NPP estimate. Results from this study suggest that ecosystem models that use biome-level land cover classifications with associated LUE coefficients may be used to model NPP in heterogeneous land cover areas dominated by cover types with similar NPP. However, more research is needed to examine scaling errors in other heterogeneous areas and NPP errors associated with deriving LAI estimates. [Copyright &y& Elsevier]

Abstract: Regional estimates or prediction of crop production is critical for many applications such as agricultural lands management, food security warning system, food trade policy and carbon cycle research. Remote sensing offers great potential for regional production monitoring and estimates, yet uncertainties associated with are rarely addressed. Moreover, although crops are one of critical biomes in global carbon cycle research, few evidences are available on the performance of global models of terrestrial net primary productivity (NPP) in estimating regional crop NPP. In this study, we use high quality weather and crop data to calibrate model parameter, validate and compare two kinds of remote sensing based production efficiency models, i.e. the Carnegie-Ames-Stanford-Approach (CASA) and Global Production Efficiency Model Version 2.0 (GLO-PEM2), in estimating maize production across China. Results show that both models intend to underestimate maize yields, although they also overestimate maize yields much at some regions. There are no significant differences between the results from CASA and GLO-PEM2 models in terms of both estimated production and spatial pattern. CASA model simulates better in the areas with dense crop and weather data for calibration. Otherwise GLO-PEM2 model does better. Whether the water soil-moisture down-regulator is used or not should depend on the percent of irrigation lands at the regions. The improved and validated models can be used for many applications. Further improvement can be expected by increasing remote sensing image resolution and the number of surface data stations. [Copyright &y& Elsevier]

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling issues that must be addressed to link ground measurements to the satellite-based carbon flux estimates. Here, we report results of a study aimed at evaluating MODIS NPP/GPP products at six sites varying widely in climate, land use, and vegetation physiognomy. Comparisons were made for twenty-five 1 km2 cells at each site, with 8-day averages for GPP and an annual value for NPP. The validation data layers were made with a combination of ground measurements, relatively high resolution satellite data (Landsat Enhanced Thematic Mapper Plus at∼30 m resolution), and process-based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80 g C m−2 yr−1 at an arctic tundra site to 550 g C m−2 yr−1 at a temperate deciduous forest site. There was not a consistent over- or underprediction of NPP across sites relative to the validation estimates. The closest agreements in NPP and GPP were at the temperate deciduous forest, arctic tundra, and boreal forest sites. There was moderate underestimation in the MODIS products at the agricultural field site, and strong overestimation at the desert grassland and at the dry coniferous forest sites. Analyses of specific inputs to the MODIS NPP/GPP algorithm– notably the fraction of photosynthetically active radiation absorbed by the vegetation canopy, the maximum light use efficiency (LUE), and the climate data– revealed the causes of the over- and underestimates. Suggestions for algorithm improvement include selectively altering values for maximum LUE (based on observations at eddy covariance flux towers) and parameters regulating autotrophic respiration. [ABSTRACT FROM AUTHOR]

Poplars are the major tree component of traditional agroforestry systems throughout the south temperate central area of China that includes all or portions of Jiangsu, Anhui, Zhejiang, Hubei, Henan, Shandong, and Shanxi provinces, an area of ~600,000 km2. The lack of experidmental data on the effect of various interplanting systems on crop production represents a serious gap in our knowledge, and consequently, a stable, optimized poplar-crop interplanting pattern is difficult to achieve. In order to develop a poplar-crop interplanting pattern that is economically viable, environmentally sound, technically workable, and socially compatible in floodplain areas, new poplar-crop interplanting patterns were designed using the principle of edge effects. Six patterns were designed and established in 1992 with different narrow - wide spacings, i.e., I: (3 × 3) × 20 m, II: (3 × 3) × 30 m, III: (3 × 3) × 40 m, IV: (4 × 4) . 20 m, V: (4 × 4) × 30 m, and VI: (4 × 4) × 40 m. A randomized block arrangement was used with two replications for each pattern. Based on 7 years of investigation, this paper examines the effects of these patterns on temporal and spatial variations in microclimate at various phenological phases of winter wheat, variations in wheat yield and quality, wood production, biomass productivity and light use efficiency, and economic assessment. The feasibility and viability of these new patterns is also discussed. These preliminary results provide some basic principles for developing optimized poplar-crop interplanting patterns in the wetland plain areas of China. [ABSTRACT FROM AUTHOR]

Regular estimates of regional pasture growth rate (PGR) would prove invaluable for wool producers in the agricultural zone of Western Australia (WA) wishing to adopt efficient techniques of managing the supply of annual pasture. Data from the AVHRR sensor are routinely processed to provide bi-monthly NDVI (normalised difference vegetation index) composite images of the agricultural zone of WA. We used a time series of NDVI imagery for 1995 to 1998 together with coincident climate layers in a light use efficiency (LUE) model to generate PGR maps for WA. We only operated the model for areas of the agricultural zone where pasture constituted more than 60% of the land cover. The regional estimates were compared with whole-farm averages made at three farms using pasture exclosures positioned across the main land management units (LMUs) on each property. Significant relationships were obtained between predicted and observed PGR for the three farms Kojonup, Porongurup and Williams of R2 0.67, 0.75 and 0.70, respectively. A validation study in 1999 at five farms used a potential productivity index for LMUs to scale the regional estimates down to paddock level. The relationship between predicted and observed PGR, for data averaged by LMU, had an R2 of 0.69. Given that little information on regional PGR currently exists, estimates generated by such LUE models from in-line AVHRR processing made available on the internet or by subscription can greatly improve the basis for feed management across wool growing enterprises in the south west of WA. This approach could readily be applied to other highly seasonal grazing systems around the world. [Copyright &y& Elsevier]

One difficulty that arises when predicting canopy-scale energy fluxes is that the parameterization of complex (bio)physical soil vegetation atmosphere transfer schemes is often only partially conditioned by the information content of the eddy covariance data commonly used for calibration, rendering subsequent predictions and extrapolations somewhat uncertain. Here we derive a functional description for daily evaporative fluxes directly from observations at the canopy scale using a nonstationary regression framework. This method is applied to 3 year blocks of eddy covariance and micrometeorological data from three different FLUXNET forest sites: Harvard Forest, USA, University of Michigan Biological Station, USA, and Hyytiälä, Finland, covering a variety of climate and vegetation conditions. The approach yields a simple three-parameter model which is based on partitioning latent heat between equilibrium latent heat fluxes and fluxes that are under strong stomatal control and hence are related to CO2 fluxes. Despite being well defined and able to account for much of the observed variations in latent heat, predictive validation of the model emphasizes the need to account for surface and subsurface water balance in such descriptions. [ABSTRACT FROM AUTHOR]

Light use efficiency (LUE) is one of the most useful parameters for estimating crop productivity. LUE relates dry matter (DM) productivity to solar radiation received on the canopy in a region. The aim of this research was to determine LUE and productivity of ryegrass (Lolium perenne L.) cv. Liprenta under different water and nitrogen (N) levels. Two separate experiments, one in 1994 (Experiment I) and other in 1995 (Experiment II), were carried out at the Institute of Plant Production, University Bonn, Germany. Two water (low versus high) and two N (low versus high) levels were supplied to plants during the growth seasons. All observations were plotted against a thermal scale. Plant DM was significantly higher (P<0.05) under both sufficient water and N supply but treatment interaction was found significant for DM production during the crop re-growth. Maximum DM was reached in about 700 growing degree days (GDDs). Sufficient water with higher N supply out yielded the other treatments for DM, tiller number per plant and leaf number per plant throughout sampling. Differences were more pronounced in the field (Experiment II) than in the pot trial (Experiment I). Higher DM production of the high water supply treatment was not only due to more tillers and leaves but also due to longer and wider blades that enlarged the leaf area as well as mass of the individual plant leaves. Insufficient water supply to ryegrass was found more critical than insufficient N supply. The adverse effect of insufficient water and N supply to plants decreased both the individual leaf area as well as the whole canopy leaf area index (LAI). The canopy light interception rose sharply with increasing LAI, reached the maximum at canopy closure and remained at plateau with further LAI development during the crop growth. Canopy extinction coefficient k was empirically determined as 0.86 for light interception efficiency of the ryegrass. LUE, calculated as the slope of the regression of total DM (roots+shoot) and accumulated PAR intercepted, was observed as 2.01 (N1W1), 2.82 (N2W1), 3.34 (N1W2) and 4.24 (N2W2) g DM MJ-1 PAR for Experiment I and 1.22 (N1W1), 2.01 (N2W1), 3.18 (N1W2) and 3.24 (N2W2) g DM MJ-1 PAR for Experiment II. The average LUE under sufficient water was almost double than that of the insufficient water treatment both under pot and field conditions. However, the effect of N treatments was far lower in intercepting light than the effect of water treatments both in pot and field conditions on ryegrass vegetative growth. [Copyright &y& Elsevier]

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms. [Copyright &y& Elsevier]

That data from polar orbiting satellites have detected a widespread increase in photosynthetic activity over the last 20 years in the grasslands of the Sahel is justifies investigating its role in the tropical carbon cycle. But this task is undermined because ground data that are generally used to support the use of primary production models elsewhere are lacking. In this paper, we profile a Light Use Efficiency (LUE) model of primary production parameterised with satellite information, and test it for the West African Sahel; solar radiation is absorbed by plants to provide energy for photosynthesis, while moisture shortfalls control the efficiency of light usage. In particular, we show how an economical use of existing, yet meagre data sets can be used to circumvent nominal, yet untenable approaches for achieving this for the region. Specifically, we use a cloudiness layer provided with the NOAA/NASA 8 km Pathfinder Land data archive (PAL) data set to derive solar radiation (and other energy balance terms) required to implement the model (monthly time-step). Of particular note, we index growth efficiency via transpiration by subsuming rangeland-yield formulations into our model. This is important for partially vegetated landscapes where the fate of rainfall is controlled by relative vegetation cover. We accomplish this by using PAL-derived Normalised Difference Vegetation Index (NDVI) to partition the landscape into fractional vegetation cover. A bare soil evaporation model that feeds into bucket model is then applied, thereafter deriving actual transpiration (quasi-daily time-step). We forgo a formal validation of the model due to problems of spatial scale and data limitations. Instead, we generate maps showing model robustness via Monte Carlo simulation. The precision of our Gross Primary Production (GPP) estimates is acceptable, but falls off rapidly for the northern fringes of the Sahel. We also map the locations where errors in the driving variables are mostly responsible for the bulk of uncertainty in predicted GPP, in this case the water stress factor and the NDVI. Comparisons with an independent model of primary production, CENTURY, are relatively poor, yet favourable comparisons are made with previous primary production estimates found for the region in the literature. A spatially exhaustive evaluation of our GPP map is carried out by regressing randomly sampled observations against integrated NDVI, a method traditionally used to quantify absolute amounts of primary production. Our model can be used to quantify stocks and flows of carbon in grasslands over the recent historical period. [Copyright &y& Elsevier]

Abstract 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 (ε g ) algorithms, the components of ε g – 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 ε g at the daily time step. In this study, we examined the relationship of daily GPP to APAR, and relationships of ε g 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 ε g , with higher values associated with the agricultural field than the boreal forest. ε g decreased with increasing APAR at all sites, a function of mid-day saturation of GPP and higher ε g under overcast conditions. ε g was generally not well correlated with vapor pressure deficit or maximum daily temperature. At the agricultural site, a ε g 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 ε g in August was associated with soil drought. These results support inclusion of parameters for cloudiness and the... [ABSTRACT FROM AUTHOR]

Three existing models are coupled to assess crop development and forecast yield in the largest contiguous irrigation network in the world: the Indus Basin in Pakistan. Monteith’s model is used for the calculation of absorbed photosynthetically active radiation (APAR), the Carnegie Institution Stanford model is used for determining the light use efficiency, and the surface energy balance algorithm for land (SEBAL) is used to describe the spatio-temporal variability in land wetness conditions. The new model requires a crop identification map and some standard meteorological measurements as inputs. The conversion of above ground dry biomass into crop yield has been calibrated through harvest indices and the values obtained are compared with the international literature. The computations were executed in a GIS environment using 20 satellite measurements of the advanced very high resolution radiometer (AVHRR) to cover an annual crop rotation cycle. The validation with district data revealed a root mean square error of 525, 616, 551 and 13,484 kg ha−1 for wheat, rice, cotton and sugarcane yield, respectively. The model performs satisfactorily for wheat, rice and sugarcane, and poorly for cotton. It is expected that the accuracy of the model applied to 1.1 km pixels decreases with the increasing number of crops occurring within a given pixel. Although AVHRR is basically too coarse a resolution for field scale crop yield estimations, the results provides yield predictions to policy makers in Pakistan with a spatial detail that is better than the traditional district level data. The gaps between the average and the maximum yield are 1075 and 1246 kg ha−1 for wheat and rice, respectively. Future work should rely on the integration of high and low resolution images to estimate field scale crop yields. [Copyright &y& Elsevier]

Herbivory is an important selective pressure in the life history of most plant species, as it usually results in reduced plant fitness. In some situations, however, plants are able to compensate for the resources lost to herbivory and do not suffer any reduction in growth or reproduction after attack. We examined the ability of Lebanese cucumber (Cucumis sativus) to compensate for both pre-flowering and during-flowering foliar herbivory through increased photosynthetic efficiency and capacity. Plants that were damaged before flowering were able to compensate, in terms of vegetative biomass and fruit production for up to 80% leaf area loss. Plants that were damaged during the flowering period were less able to compensate and fruit production declined with increasing herbivory. Damaged plants had higher photosynthetic efficiency and capacity, and dissipated less light energy as heat. Herbivore-damaged plants may be induced to use a greater proportion of the absorbed light energy for photosynthesis as a result of altered carbohydrate source-sink relationships. [ABSTRACT FROM AUTHOR]

The volume of shade within vegetation canopies is reduced by more than an order of magnitude on cloudy and/or very hazy days compared to clear sunny days because of an increase in the diffuse fraction of the solar radiance. Here we show that vegetation is directly sensitive to changes in the diffuse fraction and we conclude that the productivity and structure of vegetation is strongly influenced by clouds and other atmospheric particles. We also propose that the unexpected decline in atmospheric [CO2] which was observed following the Mt. Pinatubo eruption was in part caused by increased vegetation uptake following an anomalous enhancement of the diffuse fraction by volcanic aerosols that would have reduced the volume of shade within vegetation canopies. These results have important implications for both understanding and modelling the productivity and structure of terrestrial vegetation as well as the global carbon cycle and the climate system. [ABSTRACT FROM AUTHOR]

ABSTRACTRelationships between growth, nitrogen and concentration of unique biont components were investigated for the tripartite lichens Nephroma arcticum (L.) Torss. and Peltigera aphthosa (L.) Willd. Nitrogen availability was manipulated during 4 summer months by removing cephalodia and their associated N2 fixation activity, or by weekly irrigation with NH4NO3. Chlorophyll and ribulose 1·5-biphosphate carboxylase/oxygenase (Rubisco), and chitin and ergosterol were used as photobiont and mycobiont markers, respectively. Nitrogen concentrations were similar in older and newer parts of the same thallus, varying between 2 and 5 g m-2, with P. aphthosa having higher concentrations than N. arcticum. Both chlorophyll (Chl a) and chitin were linearly correlated with thallus N, but N. arcticum invested more in fungal biomass and had lower Chl a concentrations in comparison with P. aphthosa at equal thallus N. During the 4 months, control and N-fertilized thalli of N. arcticum increased in area by 0·2 m2 m-2 and P. aphthosa by 0·4 m2 m-2. Thallus expansion was significantly inhibited in samples without cephalodia, but there was no effect on lichen weight gain. Mean relative growth rate (RGR; mg g-1 d-1) was 3·8 for N. arcticum and 8·4 for P. aphthosa, when time (d) reflected the lichen wet periods. RGR was 2–3 times lower when based on the whole time, i.e. when including dry periods. The efficiency (e) of converting incident irradiance into lichen biomass was positively and linearly correlated with thallus Chl a concentration to the same extent in both species. The slower growth rates of N. arcticum, in comparison with P. aphthosa, could then be explained by their lower nitrogen and Chl a concentrations and a subsequently lower light energy conversion efficiency. Functional and dynamic aspects of resource allocation patterns of the two lichens are discussed in relation to the above findings. [ABSTRACT FROM AUTHOR]

Improving canopy photosynthetic light use efficiency and energy conversion efficiency (ε c ) is a major option to increase crop yield potential. However, so far, the diurnal and seasonal variations of canopy light use efficiency (LUE) and ε c are largely unknown due to the lack of an efficient method to estimate ε c in a high temporal resolution. Here we quantified the dynamic changes of crop canopy LUE and ε c during a day and a growing season with the canopy gas exchange method. A response curve of whole-plant carbon dioxide (CO 2 ) flux to incident photosynthetically active radiation (PAR) was further used to calculate ε c and LUE at a high temporal resolution. Results show that the LUE of two wheat cultivars with different canopy architectures at five stages varies between 0.01 to about 0.05 mol CO 2 mol -1 photon, with the LUE being higher under medium PAR. Throughout the growing season, the ε c varies from 0.5 to 3.7% (11-80% of the maximal ε c for C 3 plants) with incident PAR identified as a major factor controlling variation of ε c . The estimated average ε c from tillering to grain filling stages was about 2.17%, i.e., 47.2% of the theoretical maximal. The estimated season-averaged radiation use efficiency (RUE) was 1.5-1.7 g MJ -1 , which was similar to the estimated RUE based on biomass harvesting. The large variations of LUE and ε c imply a great opportunity to improve canopy photosynthesis for greater wheat biomass and yield potential., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Song, Van Rie, Den Boer, Galle, Zhao, Chang, He and Zhu.)

Understanding plant resource use efficiencies (RUEs) and their tradeoffs in a desert shrub community, particularly as it concerns the usage of water, light, and nitrogen, remains an ecological imperative. Plant RUEs have been widely used as indicators to understand plant acclimation processes to unfavorable environmental conditions. This study aimed to examine seasonal dynamics in RUEs in two widely distributed plant species in a typical desert shrub community (i.e., Artemisia ordosica and Leymus secalinus) based on in-situ measurements of leaf photosynthesis, specific leaf area (SLA), leaf nitrogen concentration (i.e., Nmass + Narea), and several site-related abiotic factors. Both species exhibited significant seasonal variation in RUEs, with a coefficient of variation (CV) >30% and seasonal divergence among the various RUEs. Seasonal divergence was largely controlled by variation in stomatal conductance (Gs), which was in turn influenced by variation in soil water content (SWC) and water vapor pressure deficit (VPD). RUEs between species converged, being positively correlated, yielding: (i) r2 = 0.40 and p < 0.01 for WUE; (ii) r2 = 0.18 and p < 0.01 for LUE; and (iii) r2 = 0.25 and p < 0.01 for NUE. RUEs for A. ordosica were mostly larger than those for L. secalinus, but less reactive to drought. This suggests A. ordosica was more conservative in its usage of available resources and was, therefore, better able to adapt to arid conditions. Resource use strategies between species differed in response to drought. Desert shrubs are projected to eventually replace grasses, as drought severity and duration increase with sustained regional climate change. [ABSTRACT FROM AUTHOR]

• Radiometric models were evaluated for estimating GPP in Brazilian Cerrado. • GPP derived from eddy covariance was highly seasonal. • All of the models were able to effectively capture the seasonality in GPP. • The vegetation photosynthesis model had the smallest error and highest precision. Gross primary production (GPP) is the total amount of fixed carbon and depends on vegetation health and water and energy availability. GPP has been monitored worldwide by flux towers and models that are coupled with remotely sensed data, such as by Moderate Resolution Imaging Spectroradiometer (MODIS). However, models have not been evaluated for tropical savanna, which presumably represent a challenge because of large spatial and seasonal variation in GPP. Thus, our goal was to evaluate the Vegetation Photosynthesis Model (VPM), Temperature and Greenness Model (TG), Vegetation Index Model (VI), and the MOD17A2 product of MODIS in a tropical mixed woodland-grassland. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), Land Surface Temperature (LST) and Photosynthetically Active Radiation Fraction (fPAR) derived from the MODIS sensor were used as model inputs and integrated with ground-based micrometeorological variables. GPP varied significantly between the wet and dry seasons and was positively correlated with seasonal variations in soil volumetric water content (VSWC) and precipitation, and negatively correlated with the vapor pressure deficit (VPD). Satellite vegetation indices (NDVI, LSWI, and to a lesser extent, the EVI) and derived quantities (fPAR and LUE) also exhibited similar correlations with VSWC and precipitation. Thus, there were strong positive correlations between the SVIs and GPP. All of the models were able to simulate the seasonal variations in GPP; however, VPM had the best performance with the highest correlation and smallest errors. TG, VI, and MOD17A2 models performed similarly, except for the VI model based only on the EVI. Given their ability to capture seasonal dynamics, remote-sensing based models, such as those tested here, will likely be an important tool for assessing how climate variability alters C cycling dynamics in these spatially and temporally heterogeneous landscapes. [ABSTRACT FROM AUTHOR]

• Different border-row proportions (BRP) in maize/peanut intercropping were compared to mono crops. • Increasing BRP increased light interception (LI) of maize in the intercropping but not for light use efficiency (LUE). • Increasing BRP decreased LI but increased LUE of peanut in the intercropping. • LUE of both crops increased with leaf area index and decreased with light intensity. Intercropping usually plants two or more crop species, often with different canopy architectures by row configuration, creates spatial niche differentiation, changes light distribution and affects radiation utilization and yield. In this study, we investigated how row configuration (e.g. the proportion of border rows) affected light interception (LI) and light use efficiency (LUE) in maize (Zea mays L.)/ peanut (Arachis hypogaea Linn.) strip intercropping. Field experiments were carried out for two years in 2015 and 2016. Four intercropping treatments were set as M2P2 (two rows maize and two rows peanut), M4P4, M6P6 and M8P8, with border-row proportion (BRP) of 1, 0.5, 0.33 and 0.25 under an equal land use proportion (0.5 for each crop). Two monocultures, sole maize and sole peanut (with BRP of 0), were set as controls. The LI was estimated by a light interception model developed for strip intercropping. Both light capture and light use efficiency of intercropped crops were significantly affected by strip width. The LI of intercropped high-stalk maize was 23.4 % higher while LI of shaded peanut was 32.2 % lower than the control. The LI of intercropped maize increased with the increasing of BRP. The LI of peanut decreased with BRP but did not show significant difference in low BRP treatment (i.e. in M6P6 and M8P8). The LUE differed within treatments in dry 2015 but not in wet 2016. In dry 2015, LUE of intercropped maize on average 13.6 % lower than the sole crop (2.05 g MJ−1), while LUE of intercropped peanut especially in M2P2 was 23.9 % higher than the sole crop (0.73 g MJ−1). The LUE varied daily and was significantly correlated with leaf area index and incident radiation intensity in both intercropping and the sole crops. Both LI and LUE responded to BRP and the responses differed between intercropped crops. The result could be used as a basis for explaining the mechanism of strip intercropping on light utilization, optimizing row configuration of intercropping design and improving light use algorithm of crop simulation model. [ABSTRACT FROM AUTHOR]

• The scope of improving GPP estimation of tropical forest using SIF was investigated. • A SIF integrated LUE model proposed incorporating SIF760 and quantum yield of SIF. • GPP estimated through SIF is promisingly related to eddy flux observation (NEE/ GPP). • Spatial scaling of GPP using spatial distribution of SIF demonstrated. • The findings are promising to reliably estimate spatial GPP using satellite data. Reliable estimation of forest carbon fluxes in space and time is a major challenge. Sun-Induced Chlorophyll Fluorescence (SIF) has been found closely linked to vegetation photosynthetic activity. But the application of SIF for direct estimation of Gross Primary Productivity (GPP) is not well investigated. In this study, we demonstrate the estimation of GPP for tropical deciduous forests located in North Western Himalayan Foothills in India using simulated SIF and fluorescence quantum yield (ФF) through a modified Light Use Efficiency (LUEf) model. SIF simulated using Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model provided the estimate of Photosynthetically Active Radiation (PAR) intercepted by the canopy foliage and ФF. ФF, measured through the Pulse-Amplitude Modulated (PAM) fluorometer quantifies the emission rate of SIF per unit of the absorbed photon. The integration of these factors into the proposed LUEf model offered real-time photosynthetic efficiency and improved the estimate of GPP of the deciduous forest. The results show that GPP estimated from SIF (SIF TOC) was closely related to GPP Eddy with R2 = 0.91 (p <0.05) with RMSE= 29.24 gC m −2 month−1 than GPP estimated from LUE model (R2=0. 79, p <0.05) and RMSE = 96.25 gC m −2 month−1). GPP MODIS underestimated the GPP with a non-significant correlation to GPP Eddy for all the months with R2=0. 36 (p <0.05) and RMSE = 188.96 gC m −2 month−1. The results obtained are promising and the proposed model can be used for estimating carbon fluxes of forests over a larger spatial scale using satellite-derived SIF. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) provides us with new opportunities to understand the physiological and structural dynamics of vegetation from leaf to global scales. However, the relationships between SIF and gross primary productivity (GPP) are not fully understood, which is mainly due to the challenges of decoupling structural and physiological factors that control the relationships. Here, we report the results of continuous observations of canopy-level SIF, GPP, absorbed photosynthetically active radiation (APAR), and chlorophyll: carotenoid index (CCI) in a temperate evergreen needleleaf forest. To understand the mechanisms underlying the relationship between GPP and SIF, we investigated the relationships of light use efficiency (LUE p), chlorophyll fluorescence yield (Φ F), and the fraction of emitted SIF photons escaping from the canopy (f esc) separately. We found a strongly non-linear relationship between GPP and SIF at diurnal and seasonal time scales (R2 = 0.91 with a hyperbolic regression function, daily). GPP saturated with APAR, while SIF did not. Also, there were differential responses of LUE p and Φ F to air temperature. While LUE p reached saturation at high air temperatures, Φ F did not saturate. We found that the canopy-level chlorophyll: carotenoid index was strongly correlated to canopy-level Φ F (R2 = 0.84) implying that Φ F could be more closely related to pigment pool changes rather than LUE p. In addition, we found that the f esc contributed to a stronger SIF-GPP relationship by partially capturing the response of LUE p to diffuse light. These findings can help refine physiological and structural links between canopy-level SIF and GPP in evergreen needleleaf forest. [Display omitted] • Assessed relationships between GPP and SIF via LUE P , Φ F , f esc in an ENF site. • Found a strongly non-linear relationship between GPP and SIF. • While LUE p reached saturation at high air temperatures, Φ F did not saturate. • Φ F -CCI relationship was strongly linear. • f esc enhanced SIF-GPP correlation. [ABSTRACT FROM AUTHOR]

Two comparable sites with uneven-aged mixed forest stands with more than 20% Douglas-fir in the growing stock at an altitude of 650 m a.s.l. were selected. The physiological response of young trees to different light intensities was measured during the main growing season in three consecutive years, and four different light categories, which were determined from hemispherical photographs. The four light intensity categories were defined according to Indirect Site Factor (ISF%): in the open (A-ISF > 35%), at the outer forest edge (B-25% < ISF < 35%), at the inner forest edge (C-15% < ISF < 25%), and under complete canopy under mature forest stand (D-ISF < 15%). Climate data were obtained from the Royal Netherlands Meteorological Institute 'Climate Explorer' website. For the intensive micrometeorological observations, four monitoring sites were established along the elevation gradient at each site during summer and late fall to record relative humidity (RH%) and temperature (°C) with a 30 min recording interval sequence. Measured assimilation responses (A) and light use efficiency (Φ) at one site followed the expected pattern, while humidity combined with microsite conditions proved significant in explaining the specific response of young Douglas-fir to the different light intensity at the other site. For higher survival and optimal future development of Douglas-fir in the changing environment, microsites with higher capacity for storage moisture and favorable microclimate should generally be preferred to exposed and dry sites. [ABSTRACT FROM AUTHOR]

• A combination of nitrogen fertilisation and eddy covariance measurements. • Deconvolute the effect of the nitrogen addition on light use efficiency. • Partition the gross primary production (GPP) into overstorey and understorey. • Assess the impacts of environmental stresses on GPP variation. Adding nitrogen to boreal forest ecosystems commonly increases gross primary production (GPP). The effect of nitrogen addition on ecosystem GPP is convoluted due to the impacts of and interactions among leaf scale photosynthetic productivity, canopy structure, site fertility, and environmental constraints. We used a unique controlled nitrogen fertilisation experiment combined with eddy covariance measurements and the calibration of a LUE-based (light use efficiency) photosynthetic production model in order to reveal differences in photosynthetic capacity due to nitrogen addition.A systematically designed soil moisture survey was conducted to characterise the within-site spatial heterogeneity and validate the difference of water stress between fertilised and control sites. The canopy photosynthetic light responses and environmental constraints were evaluated using an inverse modelling approach. We found that nitrogen fertilisation elevated ecosystem GPP by 24% according to model simulations. This was caused by increases in ecosystem light interception (through an increase in leaf area index (LAI)) and LUE by 7% and 17%, respectively. Nitrogen addition increased canopy potential LUE for both low and high photosynthetic photon flux density (PPFD) conditions. The calculations of leaf area and light interception indicated that the understorey vegetation contributed 9% of ecosystem GPP in the fertilised site and 7% in the control site when assuming a same LUE for trees and shrubs. The constraint arising from atmospheric water demand, rather than soil water stress, was the dominating control of the intra- and inter-annual GPP variations. The uncertainty propagated from soil moisture data is negligible for GPP predictions, but influential in the inference on the severity of the drought. This study demonstrates the combination of the controlled field experiment with the inverse modelling approach provides a powerful tool to quantitatively describe and disaggregate N addition effects on forest ecosystem GPP. [Display omitted] [ABSTRACT FROM AUTHOR]