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Timely and accurate crop acreage information is essential for food security and the informed decision-making by governmental bodies and stakeholders in the agro-economic system. Surveys and fieldwork are expensive and time consuming, and the information is usually only released after the cropping season. Remote sensing technology is inexpensive, scales well for large areas, and offers the opportunity to gather within-season information. However, environmental and technical constraints complicate model applications to larger scales. For example, clouds and snow introduce data gaps, and the weather-driven crop development creates highly variable spectral-temporal signatures. This study determines the earliest possible month that permits the accurate classification of the major crops in the CONUS using gap-filled data, transfer learning, and cloud computing technology. The resulting within-season, annual crop classifications are generated with precision rates of up to 80%, presented as annual crop maps and county-level area statistics. The crop classification products presented in this work are unique, in that they were created with shorter records for the first time, using data within a concise time-range (i.e. a few months) and at a 30-meter spatial resolution, while covering continental scale. This novel prospect allows for potential new applications in forecasting regional crop productions. [ABSTRACT FROM AUTHOR]

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In the last decade, Europe was stricken by two outstanding heatwaves, the 2003 event in Western Europe and the recent 2010 episode over Russia. Both extreme events were characterised by record-breaking temperatures, and widespread socio-economic impacts, including significant increments on mortality rates, decreases in crop production and in hydroelectric production. This work aims to assess the influence of both mega-heatwaves on vegetation carbon uptake, using yearly Net Primary Production (NPP) and monthly Net Photosynthesis (PsN) data derived from satellite imagery obtained from MODIS for the period 2000-2011. In 2010, markedly low productivity was observed over a very large area in Russia, at monthly, seasonal and yearly scales, falling below 50% of average NPP. This decrease in NPP in 2010 was far more intense than the one affecting Western Europe in 2003, which corresponded to 20-30% of the average, and affected a much larger extent. Total NPP anomalies reached -19 TgC for the selected regions in France during 2003 and -94 TgC for western Russia in 2010, which corresponds almost to the magnitude of total NPP anomaly during 2010 for the whole Europe. Overall, the widespread negative PsN anomalies in both regions match the patterns of very high temperature values preceded by a long period of below-average precipitation, leading to strong soil moisture deficits, stressing the role of soil-atmosphere coupling. In the case of 2003 heatwave, results indicate a strong influence of moisture deficits coupled with high temperatures in the response of vegetation, while for the 2010 event very high temperatures appear to be the main driver of very low NPP. [ABSTRACT FROM AUTHOR]

Simulating the effects of possible environmental changes on the forest carbon budget requires the use of calibrated and tested models of ecosystem processes. A recently proposed simulation approach based on the use of the BIOME-BGC model was applied to yield estimates of present carbon fluxes and pools in Tuscany forests (central Italy). After the validation of these estimates against existing ground data, the simulation approach was used to assess the impact of plausible climate changes (+2 °C and increased CO2 concentration) on forest carbon dynamics (gross primary production (GPP), net primary production (NPP), and relevant allocations). The results indicate that the temperature change tends to inhibit all production and allocation processes, which are instead enhanced by the CO2 concentration rise. The combination of the two factors leads to a general increase in both GPP and NPP that is higher for deciduous oaks and chestnut (+30% and 24% for GPP and +42% and 31% for NPP, respectively). Additionally, vegetation carbon is slightly increased, while total soil carbon remains almost unchanged with respect to the present conditions. These findings are analyzed with reference to the Tuscany forest situation and previous studies on the subject. Pour simuler les effets de changements environnementaux potentiels sur le bilan du carbone des forêts, il faut utiliser des modèles de processus des écosystèmes qui ont été calibrés et testés. Une approche de simulation proposée récemment et basée sur l’utilisation du modèle BIOME-BCG a été appliquée pour produire des estimations des flux actuels et des réservoirs de carbone dans les forêts de la Toscane, dans le centre de l’Italie. Après avoir validé ces estimations avec les données terrain existantes, la simulation a été utilisée pour évaluer l’impact de changements climatiques plausibles (+2 C et augmentation de la concentration de CO2) sur la dynamique du carbone de la forêt (production primaire brute (PPB), production primaire nette (PPN) et les locations pertinentes). Les résultats indiquent que le changement de température a tendance à inhiber tous les processus de production et d’allocation qui sont par contre stimulés par l’augmentation de la concentration de CO2. La combinaison des deux facteurs se traduit par une augmentation générale de la PPB et de la PPN qui est plus élevée chez les chênes caducifoliés et le châtaignier (respectivement +30 % et 24 % pour la PPB et +42 % et 31 % pour la PPN). De plus, la quantité de carbone dans la végétation est légèrement plus élevée tandis que la quantité totale de carbone dans le sol demeure pratiquement inchangée par rapport aux conditions actuelles. Ces résultats sont analysés à la lumière de la situation de la forêt toscane et des études précédentes sur le sujet. [ABSTRACT FROM AUTHOR]

The Moderate Imaging Spectroradiometer (MODIS) sensors onboard the NASA Terra and Aqua satellites provide the means for frequent measurement and monitoring of the status and seasonal variability in global vegetation phenology and productivity. However, while MODIS reflectance data are often interrupted by clouds, terrestrial processes like photosynthesis are continuous, so MODIS photosynthesis data must be able to cope with cloudy pixels. We developed cloud-correction algorithms to improve retrievals of the MODIS photosynthesis product (PSNnet) corresponding to clear sky conditions by proposing four alternative cloud-correction algorithms, which have different levels of complexity and correct errors associated with cloudy-pixel surface reflectance. The cloud-correction algorithms were applied at four weather stations, two fluxtower sites and the Pacific Northwest (PNW) region of the USA to test a range of cloud climatologies. Application of the cloud-correction algorithms increased the magnitude of both daily and annual MODIS PSNnet results. Our results indicate that the proposed cloud correction methods improve the current MODIS PSNnet product considerably at both site and regional scales and weekly to annual time steps for areas subjected to frequent cloud cover. The corrections can be applied as a post-processing interpolation of PSNnet, and do not require reprocessing of the MOD17A2 algorithm. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) estimates derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are converted to wheat yield and compared with observed yield for counties, climate districts and entire states for the 2001 and 2002 growing seasons in Montana and North Dakota. Analyses revealed that progressive levels of spatial aggregation generally improved the relations between estimated and observed wheat yield. However, only state level yield estimates were sufficiently accurate (? 5% deviation from observed yield). The statewide yield results were encouraging because they were derived without the use of retrospective empirical analyses, which constitutes a new opportunity for timely wheat yield estimates for large regions. Additionally, this study identifies six practical limits to estimating wheat yield using MODIS GPP. As a result we describe three suggestions for improving wheat yield estimates for scientists willing to re-compute MODIS-derived GPP estimates using regionally specific inputs. [ABSTRACT FROM AUTHOR]

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km2 portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994–1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (± 0.6), 1.8 (± 0.5) and 1.7 (± 0.5) Mg C ha−1 year−1 for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances. [ABSTRACT FROM PUBLISHER]

Summary Given that neither absolute measures nor direct model validations of global terrestrial net primary productivity (NPP) are feasible, intercomparison of global NPP models provides an effective tool to check model consistency. For this study, we tested the assumption that water availability is the primary limiting factor of NPP in global terrestrial biospheric models. We compared a water balance coefficient (WBC), calculated as the difference of mean annual precipitation and potential evapotranspiration to NPP for each grid cell (0.5° × 0.5° longitude/latitude) in each of 14 models. We also evaluated different approaches used for introducing water budget limitations on NPP: (1) direct physiological control on evapotranspiration through canopy conductance; (2) climatological computation of constraints from supply/demand for ecosystem productivity; and (3) water limitation inferred from satellite data alone. Plots of NPP vs. WBC showed comparable patterns for the models using the same method for water balance limitation on NPP. While correlation plots revealed similar patterns for most global models, other environmental controls on NPP introduced substantial variability. [ABSTRACT FROM AUTHOR]

Enough water is stored in the sapwood of large Douglas-fir to significantly contribute to transpiration. Sapwood water content falls through the season, causing the wood's conductivity to fall. This leads to low leaf-water potentials, stomatal closure, and reduced photosynthesis by the trees. The amount of water stored in the sapwood of Douglas-fir 50-60 m tall, growing in the Cascade Mountains of Oregon, was estimated periodically over two seasons from measurements of sapwood relative water content (Rs). The relationship between Rs and volume of water contained in the sapwood was determined in the laboratory, and an equation describing the variation of relative conductivity (K) with Rs was derived from the literature. Stomatal conductance (Ks) and leaf water potentials were measured in the field. The relative conductivity of the sapwood was calculated from estimates of the flow rate through the tree and differences in water potential between dawn and the time of comparison. Row rate was assumed to equal transpiration rate, calculated from the Penmam-Monteith equation using measured ks values. A sixfold decrease in K during the summer was attributed to changes in Rs. The maximum observed diurnal variation in K would require a change in Rs estimated at 25%. About 270 m3 ha-1 (27 mm) of water were stored in sapwood, and 75% of that was in the stemwood. Withdrawal from this store reached 1.7 mm day-1 on clear days after cloudy or rainy weather. Recharge could be almost as fast (up to 1.6 mm day-1) after rain, but was very slow if the foliage remained wet. [ABSTRACT FROM AUTHOR]

Using 30 years of climate records from 20 weather stations, we investigate the magnitude of temperature and precipitation change, and change in the length of the growing season between 1961 and 1990. Special attention is paid to the period between 1981 and 1990, because recent research suggests that, during this time span, forest productivitymay have increased in the northern latitudes. In order to understandthe importance of changes in climate on forest growth, we use the ecosystem model FOREST BGC as a diagnostic tool to predict the annual net primary production (NPP). The results of our study indicate: no change in precipitation between 1961 and 1990; a significant (alpha =0.05) increase in mean annual temperature of 0.72 deg. C, mean annual minimum temperature (0.80 deg. C), winter temperature (2.36 deg. C) aswell as an increase in the length of the temperature-controlled growing season by 11 days, resulting in a significant increase in diameter increment obtained from 1179 cores of Norway spruce across Austria.The trends in NPP are consistent with observed increment rates validating the use of biogeochemical modeling as a diagnostic tool to search for possible causes on changing environmental conditions. [ABSTRACT FROM AUTHOR]

A general snow accumulation and melt model was developed to (1) determine how accurately snow accumulation and ablation can be modeled over heterogeneous landscapes with routinely available climatologic, topographic, and vegetation data, and (2) improve estimates of annual forest snow hydrology for point and regional calculations of annual forest productivity. The snow model was designed to operate within the Regional Hydroecological Simulation System (RHESSys), a GIS based modeling system to manage spatial data for distributed computer simulations on watershed scales. One feature of the RHESSys Snow Model (RSM) is it can use satellite derived forest leaf area index (LAI) to represent catchment forest cover; difficult to obtain in adequate cover and resolution by any other means. The model was tested over 3 water years (October to September) with data recorded by 10 snow telemetry stations (SNOTEL) in 5 states ranging in meso-climate and elevations from a coastal Oregon site (1067 m) to a continental Colorado site (3261 m). Predictions for the 10 sites were made with identical parametervalues and only site climate varied for all sites. The average difference between observed and predicted snow depletion dates for all sites and water years was 6.2 days and 8 of the 30 simulations were within q 2 days (R2 = 0.91). Radiation melt was the dominate snow ablation component at the Colorado site where sublimation was 10%(LAI = 0) to 20% (LAI = 6) of snow loss while air temperature was the dominate component at the Oregon site with sublimation reduced to 1% (LAI = 0) to 6% (LAI = 6) of snow loss. LAI had a greater effect determining snow depletion than site aspect. Aspect increased in importance if the snow depletion occurred during early spring when solar insolation differences between hillslopes is greater than in the late spring. An accurate prediction of daily snowpack water equivalent (SWE) was not a strong determinant for making an accurate prediction of sno [ABSTRACT FROM AUTHOR]

We have developed an approach which examines ecosystem function and the potential effects of climatic shifts. The Lake McDonald watershedof Glacier National Park was the focus for two linked research activities: acquisition of baseline data on hydrologic, chemical and aquatic organism attributes that characterize this pristine northern rockymountain watershed, and further developing the Regional Hydro-Ecosystem Simulation System (RHESSys), a collection of integrated models which collectively provide spatially explicit, mechanistically-derived outputs of ecosystem processes, including hydrologic outflow, soil moisture, and snowpack water equivalence. In this unique setting field validation of RHESSys, outputs demonstrated that reasonable estimatesof SWE and streamflow are being produced. RHESSys was used to predict annual stream discharge and temperature. The predictions, in conjunction with the field data, indicated that aquatic resources of the park may be significantly affected. Utilizing RHESSys to predict potential climate scenarios and response of other key ecosystem components can provide scientific insights as well as proactive guidelines for national park management. (KEY TERMS: wildland hydrology; ecological modeling; snow and ice hydrology; climate change; RHESSys model; watershed monitoring, aquatic ecosystems.) [ABSTRACT FROM AUTHOR]