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Abstract: Although foliar reflectance in the visible wavelengths is largely understood, species-specific relations between leaf spectral properties, pigment content and carbon exchange, and interdependence of these fundamental drivers that ultimately produce large-scale signals complicate understanding of and upscaling in remote sensing applications. We recorded seasonal patterns in foliar reflectance in relation to leaf photosynthetic, biochemical, structural and optical properties in two co-occurring tree species, red oak (Quercus rubra) and paper birch (Betula papyrifera). Over the course of a growing season, we monitored the timing of phenological events, i.e. bud break, near-complete leaf expansion and leaf fall, on mature trees. On a monthly basis, maximum rate of carboxylation (V cmax) and maximum rate of electron transport (J max) were estimated from leaf-level gas exchange measurements in the upper crown for three individuals per species. Thereafter, visible and near infrared spectral properties, nitrogen content and specific leaf area were determined for sampled sunlit leaves. These data were compared with color indices extracted from digital images of sampled leaves throughout the growing season. Studied leaf traits significantly varied between the two species and throughout the growing season. Paper birch was characterized by relatively early bud break and rapid leaf expansion. Hence, interactions between species and day of year could be partly contributed to contrasting spring phenology of paper birch and red oak. Spectral vegetation indices, Chlorophyll Normalized Difference Index (Chl NDI), Photochemical Reflectance Index (PRI) and in particular Red Edge Position (λRE), gave a good indication of leaf physiology over the course of the growing season, more specifically of photosynthesis and leaf nitrogen on an area basis (N area). On the other hand, color indices performed rather poorly at tracking key leaf functional traits in this study. Overall, dark green leaves characterized by low Intensity (I, derived from HSI color space) displayed highest photosynthetic activity and highest values of spectral vegetation indices. [Copyright &y& Elsevier]

Terrestrial vegetation plays pivotal roles on land-atmosphere interactions, and even global climate change. However, limited attempts have been taken to elucidate the responses of vegetation activity to weather-related drivers (e.g., droughts, floods). This is especially in China with vast area and changeable meteorological conditions. In this paper, the performance of two satellite-based indices, namely vegetation condition index (VCI) and vegetation health index (VHI) were analyzed to detect the vegetation responses to weather-related variations. The dynamics of vegetation activity in China were further examined for the period 1982–2013. We found widely-distributed vegetation stresses in the entire country for a long period (about an average of two months per year) from the VCI and the VHI. In addition, both the two indices indicated increasing vegetation activities over most parts of China during 1982–2013. However, there is no consensus between the two indices at spatial pattern and regional totals. This discrepancy can be due to the negative-correlation assumption of the VHI between the VCI and bright temperature. However, we found that the relationship between the VCI and temperature could be changeable in different regions, especially in China with complex topography, diverse climate conditions and different vegetation types. The findings of this paper highlight the necessity to account for dominant controls on vegetation growth when using the VCI and the VHI to analyze vegetation activity. [ABSTRACT FROM AUTHOR]

• Climate-sensitive nonlinear mixed-effects height-diameter model was developed for 14 tree species in mixed forests. • The inclusion of climate and species diversity improved the H-D model. • The impact of environmental gradients on tree height growth was simulated. • The sensitivity of multiple species in mixed forest to environmental gradient changes varies with species. Models based on height-diameter (H-D) are helpful for estimating forest biomass and carbon storage on a large scale. Climate change has an impact on allometric height-diameter growth. H-D models explaining climatic effects are still inadequate due to the complexity of mixed forests. This paper developed climate-sensitive mixed-effects models for 14 tree species based on 316 natural mixed forest plots in Northeastern China and compared the response of tree height growth to environmental gradients for multiple species. The results showed that the species heterogeneity leads to the differences in scaling exponents in varying degrees. The analysis revealed that incorporating mean annual temperature (MAT), mean annual precipitation (MAP), dominant tree height (HT), basal area of the larger trees (BAL), and Shannon diversity index significantly enhanced the predictive ability of the model. By exploring the tree height change patterns of each tree species under different gradients of environmental factors, we found that increases in temperature, precipitation, site quality, and competition intensity positively affected height growth in mixed forests. In contrast, increases in species diversity inhibited height growth. The degree to which environmental factors regulate the H-D allometric growth of trees in mixed forests is related to species specificity. This paper provides theoretical support for tree height estimates of major tree species in mixed forests under global climate change by introducing environmental factors to improve the H-D model of 14 tree species. [ABSTRACT FROM AUTHOR]

• Average start of the photosynthetic period in China was on the 123rd day of the year. • The average start of the photosynthetic period advances at a rate of 4.3 d (10 a)−1. • 64% of the region is temperature controlled, others are precipitation controlled. • Importance of temperature and precipitation determined by pre-season precipitation. • Climate change increases NPP by advancing the start of the photosynthetic period. In the context of global warming, the advancement of spring phenology in northern and temperate regions due to increased temperatures has been widely reported. Early and delayed start of the photosynthetic period (SOP) directly affects the vegetation net primary productivity (NPP). However, the interrelationship between climate change, the SOP, and the NPP is unclear. In this paper, we use the dynamics of decadal daily solar-induced chlorophyll fluorescence data to calculate the response of Chinese vegetation photosynthetic phenology to climate change and its impact on the NPP over the last 20 years. The results found that over the last 20 years, the average SOP in China was on the 123rd day of the year, and the SOP has advanced at an average rate of 4.3 d (10 a)−1, with a faster trend of SOP advancement in highland and high-altitude areas. 64% of SOP in China is controlled by temperature; 36% of the SOP in China is controlled by precipitation, and the relative importance of temperature and precipitation was reversed as the precipitation gradient decreased, with SOP dominated by temperature when pre-season precipitation ≧300 mm, and SOP dominated by precipitation when pre-season precipitation ≦300 mm. Finally, we find that climate change indirectly increases vegetation NPP by advancing SOP. Our study emphasizes the importance of precipitation on phenology. It provides a scientific basis for understanding and predicting the response of spring photosynthetic phenology to climate change and the contribution of spring phenology to carbon estimation in terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: Significant progress has been made in the use of ensemble agricultural and climate modelling, and observed data, to project future productivity and to develop adaptation options. An increasing number of agricultural models are designed specifically for use with climate ensembles, and improved methods to quantify uncertainty in both climate and agriculture have been developed. Whilst crop–climate relationships are still the most common agricultural study of this sort, on-farm management, hydrology, pests, diseases and livestock are now also examined. This paper introduces all of these areas of progress, with more detail being found in the subsequent papers in the special issue. Remaining scientific challenges are discussed, and a distinction is developed between projection- and utility-based approaches to agro-climate ensemble modelling. Recommendations are made regarding the manner in which uncertainty is analysed and reported, and the way in which models and data are used to make inferences regarding the future. A key underlying principle is the use of models as tools from which information is extracted, rather than as competing attempts to represent reality. [Copyright &y& Elsevier]

Graphical abstract Highlights • A successful EC experiment was conducted on a 3765 m a.s.l. tropical grassland. • The páramo is found to be a source of carbon in the study period. • NEE and GPP light-response models for this alpine-tundra site are presented. • ETa and Kc for páramo tussock grasslands are determined via H 2 O vapor detection. Abstract Atmospheric carbon (CO 2) exchange, evapotranspiration (ET) processes, and their interactions with climatic drivers across tropical alpine grasslands are poorly understood. This lack of understanding is particularly evident for the páramo, the highest vegetated frontier in the northern Andes, the main source of water for inter-Andean cities, and a large carbon storage area. Studies of CO 2 and ET fluxes via the standard Eddy Covariance (EC) technique have never been applied to this region, limiting the understanding of diurnal / nocturnal exchanges and budget estimations. In this paper, we report the first EC analysis conducted on the Andean páramo (3765 m a.s.l.); this analysis measured CO 2 , ET, and micrometeorological variables over two years (2016–2018) to understand their interactions with climatic / biophysical controls. The páramo was found to be a source of CO 2 and exhibited a net positive exchange (mean = +99 ± 30 gC m−2 per year). The light-responses of net CO 2 exchange and the primary productivity were correlated and model-parameterized. Evapotranspiration was 635 ± 9 mm per year (51% of the annual rainfall total), and we obtained crop coefficients for the dominant vegetation (Tussock grass) based on reference-ET models FAO56 and ASCE-ERWI (0.90 and 0.78, respectively). We also compared our results to those from other high-altitude (alpine) and high-latitude grasslands (tundra). Finally, we demonstrate that our measurement period is representative of the páramo's longer-term climate dynamics. Our investigation contributes to the body of knowledge on the land surface-atmosphere processes of the tropical Andes and supports decision-making about ecosystem services management and the preservation of this vulnerable biome. [ABSTRACT FROM AUTHOR]

Modifications to the environment around a weather station or changes in instrument result in discontinuities or shift in weather data. This paper asks the often ignored questions such as, “what are the impacts of inhomogenized data?” and “does using homogenized weather data affect the conclusions of environmental research?” To answer these questions, we used the Canadian Forest Fire Weather Index (CFFWI) System for our studies. Weather station data are used to calculate wildfire danger indices. The homogenized data and raw (inhomogenized) observations for sixteen weather stations spread across Canada were used to calculate the CFFWI indices. The sixteen weather stations were further divided into three subset of stations based on the length of the accessible data during the fire season (April to end of September). The first set included stations that covered just 27 years of data and the second data sets had 49 years of data, while the third set included only five stations with the longest time period of 66 years. The majority of the stations, as measured by the Wilcoxon signed-rank test, rejected the null hypothesis (difference between the pairs follows a symmetric distribution around zero). The rejection rate increases to 100% as the length of data record increases from 27 to 66 years. Homogenization of 66 years data reduced the indices values approximately 0.7–8.4% and also reversed the long-term trend in some stations such as Kapuskasing. [ABSTRACT FROM AUTHOR]

In response to a congressional mandate, the US Global Change Research Program organized a National Assessment of Climate Change focusing on geographic regions (e.g. Alaska, Great Plains) and sectors (e.g. public health, agriculture, water resources). This paper describes methodology and results of a study by researchers at the Pacific Northwest National Laboratory contributing to the water sector analysis. The subsequent paper makes use of the water supply results to estimate the climate change impacts on irrigated agriculture. The vulnerability of water resources in the conterminous US to climate changes in 10-year periods centered on 2030 and 2095 as projected by the Hadley/United Kingdom Meteorological Office (UKMO) general circulation model (GCM; HadCM2) were modeled using the Hydrologic Unit Model for the United States (HUMUS). HUMUS, a biophysically based hydrology model, consists of a Geographical Information System (GIS) that provides data on soils, land use and climate to drive the Soil Water Assessment Tool (SWAT). The modeling was done at the scale of the eight-digit United States Geological Survey (USGS) Hydrologic Unit Area (HUA) of which there are 2101 in the conterminous US. Results are aggregated to the four- and two-digit (major water resource region, MWRR) scales for various purposes. Daily records of maximum/minimum temperature and precipitation (PPT) from 1961 to 1990 provided the baseline climate. Water yields (WY), used as a measure of water supply for irrigation, increases from the 1961–1990 baseline period over most of the US in 2030 and 2095. In 2030, WY increases in the western US and decreases in the central and southeast regions. Notably, WY increases by 139 mm (35%) from baseline in the Pacific Northwest. Driven by higher temperatures and reduced precipitation, WY is projected to decrease in the Lower Mississippi and Texas Gulf basins. The HadCM2 (2095) scenario projects a climate significantly wetter than baseline, resulting in water yield increases of 38% on average. Water yield increases are projected to be significant throughout the eastern US—39% in the Ohio basin, for example. Water yields increase significantly in the western US, as well—57 and 76% in the Upper and Lower Colorado, respectively. Climate change also affects the seasonality of the hydrologic cycle. Early snowmelt is induced in western basins, leading to dramatically increased water yields in late winter and early spring. The simulations were run at current (365 ppm) and elevated (560 ppm) atmospheric CO2 concentrations [CO2] to account for the potential impacts of the ‘CO2-fertilization’ effect. The effects of climate change scenario were considerably greater than those due to elevated [CO2] but the latter, overall, decreased losses and augmented increases in water yield. [Copyright &y& Elsevier]

Carbon use efficiency (CUE), defined as the ratio of net primary production (NPP) to gross primary production (GPP), represents the capacity of plants in converting assimilated atmospheric carbon dioxide to ecosystem carbon storage. Process-based models are important tools for simulating NPP and GPP; yet the model performance in simulating vegetation CUE has not been fully explored. The goal of this paper is thus to investigate the spatial variations in CUE from different process-based carbon cycle models in comparison with that from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, and to analyze their linkage with climate factors. The global average CUE derived from the five process-based models is 0.45 ± 0.05 (range from 0.38 to 0.52), slightly lower than the value of 0.48 obtained from MODIS data. A strong latitudinal gradient of CUE, with greater CUE at high latitudes, is well agreed by these different datasets. However, there also exist considerable discrepancies in CUE estimations among those products, especially in temperate Northern Hemisphere. Furthermore, for both the satellite-based dataset and results from process-based models, vegetation CUE declines non-linearly with increase in temperature, but remains relatively stable with enhanced precipitation. Our results also indicate that the differences in global patterns of CUE estimated by different approaches could be primarily resulted from their systematic differences in autotrophic respiration (R a ) rather than in GPP. Understanding mechanisms behind spatio-temporal changes in R a is therefore a critical step towards better quantifying global CUE. [ABSTRACT FROM AUTHOR]

This paper deals with aerobiological analyses realised during last 25 years in the atmosphere of Malaga, a coastal city located in the southwest of the Mediterranean Basin. Air sampling was performed by means of 7-day recording volumetric pollen and spore traps, and pollen grains were counted with the aid of a light microscope, according to the methodology proposed by the Spanish Aerobiology Network. Pollen data were expressed as number of pollen grains per cubic metre of air. A peak in Quercus pollen production approximately every four years was detected, coinciding with drought periods. Although the natural vegetation of the studied area has been altered by urban growth and reforestation with pines, it is still represented by a disperse natural population of cork oak, holm oak and kermes oak (predominantly located to the northwest and northeast of the city). In this period the seasonal behaviour of anemophilous pollination of Quercus was studied, along with the relation between its intensity (pollen production) or temporality (phenophase of flowering) and meteorological or climatic variables. Also a study of trends in production and phenology of flowering was carried out. The annual intensity of anemophilous pollination of Quercus was significantly associated with the meteorological conditions of each spring, with the same parameters involved and in the same way as were seen on the daily and weekly scale (positive correlation with temperature and insolation, and negative with precipitation and relative humidity). The tendency for temperature and atmospheric aridity to increase is probably the cause of the trend observed in the spring Quercus pollen production to increase in the western Mediterranean. The temporality of Quercus anemophilous pollination (start date, peak date, end date and duration) changes each year and is positively associated with accumulated temperature and sun hours from 1st January until the dates in question. An accumulation of approximately 796 °C above the 9 °C threshold temperature from 1st January is necessary to trigger the start of the flowering period. We conclude that the effect of climatic change is mainly reflected in the pollination intensity of woody anemophilous species, which, in turn, have adapted their flowering time (phenology) to climate change. It is important to remember that climate change is leading to more arid conditions and that Mediterranean plants are adapted to this macrobioclimate (Mediterranean), which is characterized by a long dry period and high temperatures. [ABSTRACT FROM AUTHOR]

In the face of increasing temperature at high latitudes, ecosystem respiration (RE) is a key to determining sink and source dynamics of a boreal forest. In this paper, we analyzed four-year RE data obtained in an open black spruce forest—a typical boreal forest ecosystem with permafrost in Interior Alaska. RE measured as nighttime CO 2 effluxes for both the ecosystem and the forest floor were clearly situated along the exponential temperature-dependent curve, except for the data obtained in extremely dry conditions in mid-summer. More than 93 % of RE data measured at nighttime with high vapor pressure deficit (VPD > 400 Pa) were lower than the values predicted from the temperature-dependent curve. Consequently, the year 2013 (with an unusually dry summer) had a 15 % lower amount of annual RE than that could be expected from the temperature-dependent curve without considering the effect of high VPD. The suppression of RE under dry conditions was also related to decreases in soil moisture and net ecosystem productivity. Finally, assuming daytime RE could be extrapolated from the temperature-dependent curves, annual daytime RE estimated with the effect of high VPD was decreased by up to 62% from RE estimated without the VPD effect. The down-regulation of RE presented in this study postulates a possible negative feedback for the carbon budget of boreal forests in response to climate warming. [ABSTRACT FROM AUTHOR]

Crop phenology is co-determined by climate change and crop management. Over recent decades, climate change-related alterations in crop phenology have been observed and reported for various global crops. However, attributing changes in crop phenology to climate change is difficult, because there have been concurrent changes in crop management. In this paper, we isolated and quantified the impacts of climate change and crop management on the changes of wheat phenology in China, during the period 1981–2010, using a first-difference multiple regression model. Our results shows: (1) based on observed phenological data, in spring/winter wheat, the mean sowing and emergence date were delayed by 0.91/2.29 and 0.39/0.73 days decade −1 ; mean anthesis and maturity date advanced by 1.05/2.28 and 0.01/1.42 days decade −1 ; mean length of vegetative growth period (VGP) and whole growth period (WGP) were shortened by 1.09/2.86 and 0.89/3.69 days decade −1 ; mean length of reproductive growth period (RGP) was prolonged by 0.55/0.61 days decade −1 . (2) At most stations, changing direction of wheat phenology affected by isolated impacts of climate change or crop management was consistent with that affected by combined impacts of climate change and crop management. (3) For observed trends of most phenological stages and growth periods, relative contribution from climate change was smaller than from crop management, and average temperature contributed the most among the three contributors (average temperature, cumulative precipitation, and cumulative sunshine hours) to isolated impacts of climate change on wheat phenology. (4) Crop management over the three decades was shown to have helped reduce the lengths of VGP and WGP, but increase the length of RGP for both spring and winter wheat, implying that shorter-duration varieties with a higher yield or better yield stability in changing climate might have been introduced by farmers. [ABSTRACT FROM AUTHOR]

The amount of published data on annual evaporation on rice remains extremely limited despite the role of rice as a key food source. We report on six years of rice evaporation measurements, based on the eddy covariance method. This rice was cultivated in the hot dry climate of California, where water is a scarce and precious resource. During the first year, we found that rice evaporation exceeded potential evaporation rates and summed to 1155 mm y −1 . In following years, we found that annual evaporation decreased yearly, yielding a 15% reduction (to 982 mm y −1 ) by the sixth year. The remainder of the paper examined the how and why of this unexpected decreasing trend in annual evaporation occurred. We inspected trends in variations in biophysical variables (net radiation, temperature, leaf area index) associated with evaporation and potential biases in the flux measurements using energy balance closure and co-spectral analysis. None of the biophysical variables varied enough to explain this observation. What did change was the area of rice, and nearby flooded wetlands. During the first year, the flooded rice field was less than 1 km 2 in area and was relatively isolated. This situation promoted an ‘oasis effect’ that enabled warm dry air to be entrained from across the top of the planetary boundary layer; this contention was supported by the co-spectral analysis and analysis with a coupled surface energy balance-planetary boundary layer model. By the sixth year of this project, the area of flooded rice and wetlands approached 6 km 2 , a horizontal scale that seemed to inhibit the ‘oasis effect’. We conclude that the amount of water used, on an area basis, by wetland restoration projects will depend upon the spatial extent of these projects. [ABSTRACT FROM AUTHOR]

The western Tianshan Mountains are a very important source of water. The area is dominated by westerly winds and is important in global change research. In this paper, we combine two tree-ring width chronologies, meteorological data from the Climatic Research Unit (CRU), a standardized precipitation-evapotranspiration index (SPEI) and Palmer Drought Severity Index (PDSI) to analyze radial growth response to climate. Studies show moisture from the previous July to current June was consistently the dominant climatic factor accounting for interannual variation of tree-ring width in the western Tianshan Mountains. Then, we reconstruct the precipitation, SPEI and PDSI, and the three series are verified with mathematical methods and other observation data. Power spectral and wavelet analyses reveal significant 2- to 6-year high-frequency cycles and a 17-year low-frequency cycle. Moisture has varied as four wetter periods and four drier periods over the past century. We show that over all northern slopes of the Tianshan Mountains, moisture change has been rarely consistent. From the 1980s to present, the climate has had the longest, most significant and rapid wetting period in the past century. The moisture variability pertains to most areas of the western Tianshan Mountains, especially the northern slope of the mountains in Kyrgyzstan. Our results indicate a strong negative relationship between the Summer North Atlantic Oscillation (SNAO) and moisture in the western Tianshan Mountains. The moisture variability may have been controlled by the SNAO in the past century, and may be associated with large-scale oscillation in the climate system. [ABSTRACT FROM AUTHOR]

Six phenological models, two simple forcing (F)-models and one sequential chilling/forcing (CF)-model, each with and without day length (DL)-term in the forcing approach were optimised (2001–2010) and validated (2011–2015) on very accurate blossoming data of an experimental sweet cherry orchard at Berlin-Dahlem (cultivar ‘Summit’). In parallel, in 3 seasons (2011/2012–2013/2014) climate chamber experiments were performed in order to determine the end of dormancy for ‘Summit’, which is usually an unknown or uncertain parameter in phenological modelling. Additionally, in the season 2013/2014 an in situ climate change experiment on three trees in the sweet cherry orchard were arranged, which was used to validate the phenological models for distinctly warmer climate conditions at the experimental site. On the basis of our climate chamber experiments we quantified the chilling requirement of ‘Summit’ trees. Thus, we were able to identify a CF-model for the beginning of sweet cherry blossom which is mostly physiologically based and works well for current and for future climate conditions at the experimental site. This paper also shows how phenological models can fail under warmer climates, if either the model is too simple or the model parameters are wrong. Additional, we confirmed that phenological models with DL-term in the forcing approach clearly surpassed the conventional phenological models without this parameter. The reason for this behaviour is extensively discussed. [ABSTRACT FROM AUTHOR]

The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an analysis of expected yields in relation to the costs of investment in particular practices. Based on the use of crop models, this paper compares the ability of two methodologies to predict wheat yield ( Triticum aestivum L.), one based on stochastically generated climatic data and the other on mean climate data. It was shown that the numerical experimental yield distribution could be considered as a log-normal distribution. This function is representative of the overall model behaviour. The lack of statistical differences between the numerical realisations and the logistic curve showed in turn that the Generalised Central Limit Theorem (GCLT) was applicable to our case study. In addition, the predictions obtained using both climatic inputs were found to be similar at the inter and intra-annual time-steps, with the root mean square and normalised deviation values below an acceptable level of 10% in 90% of the climatic situations. The predictive observed lead-times were also similar for both approaches. Given (i) the mathematical formulation of crop models, (ii) the applicability of the CLT and GLTC to the climatic inputs and model outputs, respectively, and (iii) the equivalence of the predictive abilities, it could be concluded that the two methodologies were equally valid in terms of yield prediction. These observations indicated that the Convergence in Law Theorem was applicable in this case study. For purely predictive purposes, the findings favoured an algorithm based on a mean climate approach, which needed far less time (by 300-fold) to run and converge on same predictive lead time than the stochastic approach. [ABSTRACT FROM AUTHOR]

A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE 〈LINTUL2〉 and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log–log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. [ABSTRACT FROM AUTHOR]

This paper evaluates a set of candidate phenology models for simulating grapevine development under present conditions and future climate change scenarios. The models were developed on a combination of working hypotheses, designed to extend their predictive ability to multiple phenological events, i.e. budburst, flowering and veraison. The aspects considered in the modelling analysis were: (i) effect of dormancy description, by comparison of Chilling and Forcing (CF) with Forcing (F) models; (ii) degree of phenophase-dependent specificity after endodormancy break; (iii) adopting a linear or curvilinear function for modelling temperature dependency of development rate; (iv) performance under climate change scenarios. We also analyzed to what extent model behavior under present and future climate was affected by factors other than model structure, focusing on the variability of the dataset used to calibrate the models. To this purpose two parallel series of models were evaluated: one calibrated on a historical phenological dataset, and the other on the same dataset extended with budburst observations obtained under controlled condition simulating shorter winters, as expected from climate change predictions. Estimation accuracy of the models was evaluated on independent data. A further evaluation considered parameterization consistency with experimental physiological data, and model behavior under future climate change scenarios, to assess to what extent future predictions are affected by model structure and complexity. Under current climatic conditions the models showed a comparable accuracy, only slightly higher when growth-room data were used for calibration. The similar performance was obtained despite wide discrepancies in parameterizations between the calibration types. In CF models, which describe dormancy dynamics, chilling requirements were highly overestimated in field-calibrated models, and different temperature requirements were likewise found for post-dormancy development. The parameterization differences had a clear impact on a demonstrational scenario analysis, where models were driven by synthetic weather data derived from downscaled HadCM3 predictions for the SRES-A2 scenario. Here all the selected models predicted a forward shift of phenology. The type of calibration affected the response more than the model structure or complexity, the effect of which only became detectable at the remotest projections in the future. The effect of calibration was more evident for budburst than for flowering and veraison. Field-calibrated models underpredicted the shift with respect to their counterparts, due to a delayed onset of forcing accumulation, which postponed budburst and subsequent phases, counterbalancing the effect of higher spring temperatures. It is concluded that for present time applications all the evaluated models have comparable accuracy. Also for climate change impact analysis the variability of the calibration dataset is a more crucial factor than model structure or complexity. The simpler forcing models can therefore be recommended for both present conditions as well as scenario-based applications. [ABSTRACT FROM AUTHOR]

Highlights: [•] The paper assesses the impact of spring meteorology on Mediterranean forest GPP. [•] The investigation is based on the analysis of ground and remote sensing data. [•] The start of the dry season (SDS) affects inter-annual forest GPP variations. [•] The impact of SDS is attenuated moving toward more humid environments. [•] The eco-physiological bases of these phenomena are identified and discussed. [Copyright &y& Elsevier]

Abstract: Crop models often simulate drought impacts with full and no irrigation scenarios, while planners are more interested in whether the current available irrigation water can cope with the future more serious droughts. This paper addresses a key constraint common to modeling studies: the limited representation of actual irrigation water supply. We present a data-driven approach to identify a benchmark for agronomic drought risk levels as defined by water availability thresholds at the baseline climate (1980–2008) using reported crop yields, climate and irrigation statistics. Then, holding the current irrigation supplies, we adopted Bayesian formula to estimate magnitude of the future water availability and the associated probability of crops yields being decreased to rainfall-deficiency under climate conditions in 2030s (2020–2040) based on the RegCM3 climate model output driven by IPCC SRES A1B scenario. Results reveal that future drought stress would overwhelm the irrigation capacity of current supplies in northern and western China, while drought remains at baseline climate levels in the central, eastern and southern regions. The largest increases in the probability of projected drought risk were in northeast and southwest, ranging from 14% to 28% above baseline climate. Regional drought impacts for grain self sufficiency are discussed. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to identify which of the world''s cereal producing regions are likely to become vulnerable to climate change over the 21st century by identifying those regions that will be (1) exposed to climatic stress and (2) have a limited capacity to adapt. First, we use a global hydrological model to identify regions likely to be exposed to drought, defined here as a location where the available soil moisture is projected to decline by the 2050s and 2080s relative to the mean soil moisture observed between 1990 and 2005. Second, we use agricultural, meteorological and socio-economic data to develop models of adaptive capacity and run these models to show where adaptive capacity is likely to decline by the 2050s and 2080s relative to the baseline period of 1990–2005. Third, we contrast the hydrological and adaptive capacity model outputs to identify “vulnerability hotspots” for wheat and maize. Here, a vulnerability hotspot is defined as a region that the models project as likely to experience both a decline in adaptive capacity and in available soil moisture. Results from the hydrological model project significant drying in many parts of the world overt the 21st century. Results from the adaptive capacity models show that regions with the lowest overall adaptive capacity for wheat include much of western Russia, northern India, southeastern South America, and southeastern Africa. In terms of maize, regions with the lowest adaptive capacity include the northeastern USA, southeastern South America, southeastern Africa, and central/northern India. When taken together, this study identifies five wheat and three maize growing regions likely to be both exposed to worse droughts and a reduced capacity to adapt. For wheat, these are: southeastern USA, southeastern South America, the northeastern Mediterranean, and parts of central Asia. For maize, our analysis suggests that vulnerability hotspots are: southeastern South America, parts of southern Africa, and the northeastern Mediterranean. [Copyright &y& Elsevier]

Abstract: Crop growth simulation models are a useful tool to assess the impact of environment, crop management, genetics and breeding strategies, as well as climate change and variability on growth and yield. Any crop science experiment that measures key physiological processes, tests these productive processes, their interaction with other processes, environment, and intra- and inter-specific variation, is valuable to inform and refine crop simulation models. This paper focuses on crop science experiments in three key areas—crop development, seed or fruit-set at high temperature, and water use—illustrating some of the experiments used to understand key processes and, equally importantly, quantify these processes for crop models in a robust and repeatable manner. One particularly useful experimental method for determining stages of development responsive to photoperiod and temperature (the main drivers of ontogenic development), and sensitive to abiotic stresses such as temperature extremes and water deficit, is transfer experiments between different environments or treatments. Once sensitive stages are defined, then responses and genotypic differences can be accurately quantified. Understanding and modeling transpiration, and particularly genotypic differences in processes affecting transpiration is also key process for crop modeling. Experiments to determine genotypic differences in soil water availability thresholds that control when transpiration is reduced, relations between transpiration and vapor pressure deficit (VPD), and patterns of soil water uptake are also described along with new insights from this work. One of the biggest constraints to improving models with crop science experiments—and exploiting advances in genomics—is the limited capacity to phenotype traits and physiological mechanisms. Most crop science experiments have quantified responses in only a limited number of genotypes and the diversity of genotypic responses is not well represented. Today there is an increased demand for good quality phenotyping which can serve both genomics and modeling, and there is an urgent need to re-invest in crop physiology for high quality phenotyping. [Copyright &y& Elsevier]

Abstract: Climate plays a fundamental role in agriculture. The quantity and quality of crop yield can be affected by water stress, heat stress or frost or by pests and diseases. As climate conditions change, suitability zones for the cultivation of specific crops may shift. For planners and land managers it is important to understand such changes in order to develop short- and long-term adaptation strategies for resource and development planning. In this paper, we present a flexible and comprehensive, rule-based approach for evaluating crop-specific climate suitability. Climate indices are calculated over dynamically estimated phenological phases, and factor suitability functions are defined to relate these phase-specific climate indices to suitability values. The dynamic consideration of crop phenology allows to assess effects of climate-induced shifts in phenological development. To complement the knowledge-based definition of factor suitability functions with empirical data, we introduce an automated procedure for refining this definition within knowledge-based bounds based on observed climate and yield data. The approach was tested and applied for grain maize (Zea mays L.) production in Switzerland. Comparison with independent yield data showed a good agreement with crop-specific climatic suitability, both in terms of temporal and spatial variability. Analysis of phase-specific suitability limitations at three representative sites revealed that suitability during the period 1981–2011 was mostly limited by sub-optimum temperatures and radiation during early and late phases, whereas drought was only an important limitation in exceptionally dry years (e.g. 2003 and 2010). An analysis of constant changes in temperature and precipitation indicated that grain maize suitability at a selected site on the western Central Plateau was more sensitive to temperature changes than to changes in precipitation. This suggests that this crop could benefit from an increase in temperature, not only through shifting towards the temperature optimum, but also by avoiding drought stress through accelerated plant development. However, these positive effects could be counteracted by negative effects of shortened phenology (i.e. reduced biomass accumulation) and heat stress. These results show that the approach offers diverse possibilities for applications, including climate impacts studies, and serves to provide information for the planning of crop adaptation strategies. [Copyright &y& Elsevier]

Abstract: Climate change is one of the key issues in current scientific research. In this paper we investigate the impacts of rising temperatures and changing precipitation patterns on meteorological forest fire danger in the Alps. Our analysis is based on daily meteorological observations from 25 long-term stations in six Alpine countries. The selected stations are distributed more or less uniformly over the whole Alpine area and represent the different climate regions in this complex terrain. Stations with similar climatological conditions were grouped into regions. These were: Western Alps, Northern Alps, inner Alpine area and Southern Alps. The meteorological forest fire danger in the time period 1951–2010 was assessed on the basis of different forest fire danger indices (FWI, Nesterov, Baumgartner, etc.) calculated on a daily basis. A statistical percentile analysis revealed different impacts of recent climate change in the four regions. A significant increase in forest fire danger occurred at the stations in the Western Alps and even more strongly in the Southern Alps. Here, the yearly averaged fire danger increased during the past six decades. Additionally, in recent years the number of days with elevated forest fire danger (indices above a pre-defined threshold) has also increased. A comparatively weak increase was observed in the Northern Alps and no clear signal was evident at the stations in the inner Alpine valleys. In order to analyze extreme events (highest index value per year and region) extreme values statistics was applied. It was shown that the return period of extraordinarily high index values has decreased significantly over the past decades, especially in the Western and Southern Alps. For three pilot areas (Valais in the Western Alps, Bavaria in the Northern Alpine region and Ticino in the Southern Alps) a comparison with observed historical fire data is shown. In Valais, a region in the Western Alps with a generally low fire hazard, a weak trend toward more forest fires and more area burned could be found. The correlation between calculated indices and observed fires was quite low in this region. In Bavaria (Northern Alps) this correlation was higher, but while the trend of forest fires in Bavaria was decreasing in terms of number and burned area, the meteorological fire danger in contrast increased. Reasons for this contrasting trend may be related to altered anthropogenic factors such as less military activities, technical progress, and higher awareness. The correlation between indices and forest fires south of the Alps (Ticino) was considerably lower because here most forest fires occurred in winter when the meteorological fire danger is usually lower than in summer. In this region a positive trend in meteorological fire danger over recent decades was also counterbalanced by decreasing anthropogenic ignitions. [Copyright &y& Elsevier]

Abstract: This paper aims to address some gaps in current knowledge by studying temporal and spatial variations in Artemisia pollen counts (2000–2009) at 13 sites located in different biogeographical areas of Central and Eastern Europe. Analysis showed that start dates of Artemisia pollen seasons are greatly dependent on temperature during June and July, with hot summer temperatures having a tendency to delay summer flowering. However, this relationship is not linear and the rate at which seasons become later increases when mean minimum June–July temperatures reach a threshold of about 13°C. No explanation for variations in pollen season intensity could be found. The geographical location or amount of urbanisation did not influence, either positively or negatively, the seasonal pollen index. Second peaks in Artemisia pollen seasons can be described as the pollen seasons of late flowering Artemisia species, and mainly occurred in the geographical area south of the Carpathian Mountains. These second peaks can significantly influence the seasonal pollen index, contributing over 50% to the season''s total Artemisia pollen recorded at one site. [Copyright &y& Elsevier]

Abstract: The present and future spatiotemporal characteristics of reference evapotranspiration (ET0) are examined in this paper. ET0 during 1961–2009 are calculated by the Penman–Monteith method recommended by FAO (Food and Agriculture Organization) with historical weather data while ET0 during 2011–2099 are downscaled from HadCM3 (Hadley Centre Coupled Model, version 3) outputs under two emission scenarios (A2 and B2) by SDSM (Statistical DownScaling Model). The spatial distribution and temporal trend in ET0 are interpreted by Inverse Distance Weighted Interpolation and Mann–Kendall method, respectively. Results show that the annual mean ET0 is 1060.3mm, the lowest and highest values are found in the southwest and northwest region due to the spatial distribution of climatic factors, respectively. ET0 has increased significantly due to the downward trend in relative humidity and upward trend in temperature on the Loess Plateau during 1961–2009. HadCM3 projects a continuous increase in ET0 in the 21st century and the upward trend will be more pronounced after 2050. Averaged over the two emission scenarios for the whole area, the projected increase are 4%, 7% and 12% for the three periods 2011–2040, 2041–2070 and 2071–2099, respectively; the increase under A2 scenario are slightly greater than those under B2 scenario. An obvious gradient is detected for the projected increase in ET0 from northeast to southwest region in the 21st century. The increase in ET0 will possibly influence the water resource on the Loess in the 21st century and some countermeasures should be taken to reduce the adverse impacts. [Copyright &y& Elsevier]

Abstract: This paper describes how spatial dependence can be incorporated into statistical models for crop yield along with the dangers of ignoring it. In particular, approaches that ignore this dependence suffer in their ability to capture (and predict) the underlying phenomena. By judiciously selecting biophysically based explanatory variables and using spatially-determined prior probability distributions, a Bayesian model for crop yield is created that not only allows for increased modelling flexibility but also for improved prediction over existing least-squares methods. The model is focused on providing efficient predictions which stabilize the effects of noisy data. Prior distributions are developed to accommodate the spatial non-stationarity arising from distinct between-region differences in agricultural policy and practice. In addition, a range of possible dimension–reduction schemes and basis expansions are examined in the pursuit of improved prediction. As a result, the model developed has improved prediction performance relative to existing models, and allows for straightforward interpretation of climatic effects on the model''s output. [Copyright &y& Elsevier]

Abstract: In response to worldwide observations reporting a decline in pan evaporation over the last 30–50 years, we developed an instrumented US Class A pan that replicated an operational pan at Canberra Airport in Australia. The aim of the experimental facility was to investigate the physics of pan evaporation under non-steady state conditions. By monitoring the water level at 5-min intervals we were able to calculate the evaporation rate and thereby determine the short-term mass balance of the pan. Over the same time intervals, we also monitored (short- and long-wave) radiation, temperature (air, water surface, bulk water, inner and outer pan wall), atmospheric pressure as well as the air vapour pressure and the wind speed at a standard reference height (2m above ground level). The experimental pan was operated for three years (2007–2010). In this paper, we develop a framework for quantifying vapour transfer by coupling Fick''s First Law of Diffusion with boundary layer theory. This approach adequately represented pan evaporation measurements over short time intervals (half-hourly) under non-steady state conditions provided that surface temperature measurements, that account for the substantial cooling associated with evaporation, are available. It involved estimating the boundary layer thickness and other properties of air above the evaporating surface for a pan. Our results are consistent with the “envelope of theoretical curves” concept for the wind function introduced by . [Copyright &y& Elsevier]

Abstract: Long-term soil carbon (C) dynamics in agro-ecosystems is controlled by interactions of climate, soil and agronomic management. A modeling approach is a useful tool to understand the interactions, especially over long climatic sequences. In this paper, we examine the performance of the Agricultural Production Systems sIMulator (APSIM) to predict the long-term soil C dynamics under various agricultural practices at four semi-arid sites across the wheat-belt of eastern Australia. We further assessed the underlying factors that regulate soil C dynamics in the top 30cm of soil through scenario analysis using the validated model. The results show that APSIM is able to predict aboveground biomass production and soil C dynamics at the study sites. Scenario analyses indicate that nitrogen (N) fertilization combined with residue retention (SR) has the potential to significantly slow or reverse the loss of C from agricultural soils. Optimal N fertilization (Nopt) and 100% SR, increased soil C by 13%, 46% and 45% at Warra, Wagga Wagga and Tarelee, respectively. Continuous lucerne pasture was the most efficient strategy to accumulate soil C, resulting in increases of 49%, 57% and 50% at Warra, Wagga Wagga and Tarlee, respectively. In contrast, soil C decreases regardless of agricultural practices as a result of cultivation of natural soils at the Brigalow site. Soil C input, proportional to the amount of retained residue, is a significant predictor of soil C change. At each site, water and nitrogen availability and their interaction, explain more than 59% of the variation in soil C. Across the four sites, mean air temperature has significant (P <0.05) effects on soil C change. There was greater soil C loss at sites with higher temperature. Our simulations suggest that detailed information on agricultural practices, land use history and local environmental conditions must be explicitly specified to be able to make plausible predictions of the soil C balance in agro-ecosystems at different agro-ecological scales. [Copyright &y& Elsevier]

Abstract: Modeling soil water availability for tropical trees is a prerequisite to predicting the future impact of climate change on tropical forests. In this paper we develop a discrete-time deterministic water balance model adapted to tropical rainforest climates, and we validate it on a large dataset that includes micro-meteorological and soil parameters along a topographic gradient in a lowland forest of French Guiana. The model computes daily water fluxes (rainfall interception, drainage, tree transpiration and soil plus understorey evapotranspiration) and soil water content using three input variables: daily precipitation, potential evapotranspiration and solar radiation. A novel statistical approach is employed that uses Time Domain Reflectometer (TDR) soil moisture data to estimate water content at permanent wilting point and at field capacity, and root distribution. Inaccuracy of the TDR probes and other sources of uncertainty are taken into account by model calibration through a Bayesian framework. Model daily output includes relative extractable water, REW, i.e. the daily available water standardized by potential available water. The model succeeds in capturing temporal variations in REW regardless of topographic context. The low Root Mean Square Error of Predictions suggests that the model captures the most important drivers of soil water dynamics, i.e. water refilling and root water extraction. Our model thus provides a useful tool to explore the response of tropical forests to climate scenarios of changing rainfall regime and intensity. [Copyright &y& Elsevier]

Abstract: In this century climate change is assumed to be the major driver for changes in agricultural systems and crop productivity at the global scale. However, due to spatial differences in cropping systems and in the magnitude of climatic change regional variations of climate change impact are expected. Furthermore, the recent climate projections are highly uncertain for large parts of West Africa. In particular with respect to annual precipitation and variability the projections vary between trends with decreasing precipitation and trends with slightly increasing precipitation within the next decades. On the other hand, the extensive fallow systems in this region suffer from increasing population pressure, which compromises soil fertility restoration. In the Republic of Benin, the demographic projections for the first half of this century indicate a continuous growth of the population with a narrow interval of confidence. Thus, in the absence of an adequate soil fertility management with judicious use of mineral fertilizers, the soil degradation process with decreasing crop yields is expected to continue. The objective of this paper was, therefore, to quantify the regional effect of future population growth on crop yields in West Africa and to compare it with the potential effects of climate change scenarios. Three land use scenarios (L1, L2 and L3) for the Upper Ouémé catchment where derived from different demographic projections combined with assumptions regarding future road networks and legal frameworks for forest protection using the CLUE-S modeling approach. The fallow-cropland ratio decreased in the three scenarios from 0.87 in the year 2000 to 0.66, 0.48 and 0.68 for L1, L2 and L3, respectively in 2050. Based on the projected ratio of fallow and cropland, trends of maize yield for the three land use scenarios were calculated using the EPIC (Environmental Policy Integrated Climate) model coupled with a spatial database. Maize yields followed the decreasing trend of the fallow-cropland ratio and estimated yield reductions amounted to up to 24% in the period 2021–2050. This trend was compared with the impact of the SRES climate scenarios A1B and B1 based on the output of the GCM ECHAM5 downscaled with the REMO model and the A1B scenario output of the GCM HADC3Q0 downscaled with the RCMs SMHIRCA and HADRM3P. The yield reductions due to the projected climate change in the three models accounted for a yield decrease of up to 18% (REMO A1B scenario) in the same period. Taking into account the smaller uncertainties in the scenario assumptions and in the model output of the land use scenarios, it is concluded that, in low input fallow systems in West Africa, land use effects will be at least as important as climate effects within the next decades. [Copyright &y& Elsevier]

Abstract: The aim of the paper is to employ Empirical Orthogonal Function (EOF) analysis to drought indices including Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Palmer Moisture Anomaly (Z) Index (Z-Index), Weighted Palmer Drought Severity Index (WPDSI), and Water Deficit (P–PET) Index and to compare their resultant spatial patterns across Turkey. In this respect, the PDSI, PHDI, Z, WPDSI, Aridity Index (AI) and P–PET Index values are calculated based on observed monthly temperature and precipitation values of the 96 Turkish meteorological stations for the 1929–2009 period, and gridded available water holding capacities (AWHC) in 1-m soil depth are extracted from the soil data sets of the Oak Ridge National Laboratory Distributed Active Archive Centre (ORNL DAAC). By considering the strong match among the PDSI, PHDI, and WPDSI based on the results of the patterns of the first EOFs (EOF1) with the highest eigenvalue, we suggest that using and applying one of these drought indices could be adequate for a drought analysis in Turkey. On the other hand, it is evident that the significant results from the EOF2, EOF3 and EOF4 loadings of the PHDI and WPDSI indices have a similar pattern across Turkey. Therefore, with respect to the geographical autocorrelation and magnitudes of the loading values, it is explained that the PDSI and WPDSI in particular could have originated from the same physical process, and one may have a preference for the effective usage of a combination of PDSI, PHDI and Z-Index. Consequently, in a multi-purpose medium- and long-term drought management plan for Turkey or in any country having similar climatic and physical geographical conditions, using one of the three drought indices along with the Z-Index could be acceptable for successful applications. [Copyright &y& Elsevier]

Abstract: This paper reports on results from eddy covariance measurements of carbon uptake and evapotranspiration in the eucalypt site of Espirra in Southern Portugal (38°38′N, 8°36′W). This site was included in the “Carboeurope” European network and is part of a 300ha eucalypt forest, with about 1100treesha−1, intensively managed as a coppice for pulp production and characterized by a 12-month annual growing period. The climate is of Mediterranean type with a long term (1961–1990) annual average precipitation of 709mm and an annual average air temperature of 15.90°C. During the measurement period (2002–2009) two main events took place, which changed the annual sink pattern of the forest: a drought period of two years (2004–2005) and a tree felling (October and November 2006). We analyzed the daily, seasonal and inter-annual variation of carbon uptake and evapotranspiration, and their relationships with the events and the variability of the main meteorological variables. Before the felling, annual net ecosystem exchange (NEE) increased from −865.56gCm−2 in 2002 to −356.64gCm−2 in 2005 together with a deep decrease in rainfall from 748mm in 2002 to 378.58mm and 396.64mm in 2004 and 2005, respectively. For the same period, seasonal patterns of carbon uptake showed maximum values in April and decreased in July–August. The eucalypt stand recovered its carbon sink ability since June 2007 and had a NEE of −209.01gCm−2 in 2009. After the felling, the carbon uptake occurred from mid-February to mid-October, following an almost opposite pattern than that of the trees in the term of their productive cycle. A quantitative approach using generalized estimating equations (GEEs) was made for the period before the felling to relate monthly NEE and GPP with accumulated photosynthetic active radiation, water vapour pressure and precipitation. In conclusion, our study showed the relevant effects of water stress and anthropogenic interventions in the daily, seasonal and annual patterns of carbon uptake, under a context of good environmental conditions for carbon sequestration. [Copyright &y& Elsevier]

Abstract: The agricultural sector is probably the one that will suffer most directly from the climatic variations expected at the global level. In particular, the analysis of the changes expected in water availability and demand is fundamental in order to correctly establish both the present water resource management and the definition of new strategies. In this paper the time series of some climatic and agro-climatic indices in the Region of Umbria (Central Italy) have been analyzed with the aim of finding signs of climate changes and identifying the potential impacts on the agricultural water balance. The aforesaid indices include the precipitation, the mean maximum and minimum temperatures (Tmin, Tmax), the mean temperature range (ΔT), the reference evapotranspiration (ET0) and two drought indices, Standardized Precipitation Index (SPI) and Standardized Deficit Index (SDI, based on the difference between ET0 and precipitation). These indices were analyzed with reference to different periods (in particular the average growing and irrigation seasons). Furthermore, more specific information was obtained by analyzing the simulated water requirement (CWR) and evapotranspiration deficit (ED) of two typical annual crops (corn and sunflower). The time series of the indices were quantified for 38 stations in the region and they were then analyzed with non-parametric tests both at single sites and at the regional level. The tendencies in cumulated precipitation are generally decreasing (particularly during the wet period) and they are also characterized by a defined spatial pattern. The rainfall reduction during the irrigation season, although less widespread, could have the most important practical consequences. The significant trends detected for both the Tmax and Tmin are mainly positive, and they are more evident for Tmin, often resulting in a reduction of ΔT. ET0 shows a prevailing stationary condition due to the counteracting effects of the prevalent reduction observed for the ΔT and the increment of the mean temperature. At any rate, with reference to the irrigation season, ET0 trends are mainly positive. The results obtained for SPI and SDI are in accordance with the tendencies of non-standardized indices with an expectation of extreme drought event occurrence doubled or even tripled over a 30-year time span. Finally, the analysis of the CWR for corn and the ED for sunflower shows a relevant presence of significant positive trends whose impacts can be estimated in respective mean increments of about 23% and 44% over a 50-year time span. [Copyright &y& Elsevier]

Abstract: The increasing demand for ecosystem services, in conjunction with climate change, is expected to significantly alter terrestrial ecosystems. In order to evaluate the sustainability of land and water resources, there is a need for a better understanding of the relationships between crop production, land surface characteristics and the energy and water cycles. These relationships are analysed using the Joint UK Land Environment Simulator (JULES). JULES includes the full hydrological cycle and vegetation effects on the energy, water, and carbon fluxes. However, this model currently only simulates land surface processes in natural ecosystems. An adapted version of JULES for agricultural ecosystems, called JULES-SUCROS has therefore been developed. In addition to overall model improvements, JULES-SUCROS includes a dynamic crop growth structure that fully fits within and builds upon the biogeochemical modelling framework for natural vegetation. Specific agro-ecosystem features such as the development of yield-bearing organs and the phenological cycle from sowing till harvest have been included in the model. This paper describes the structure of JULES-SUCROS and evaluates the fluxes simulated with this model against FLUXNET measurements at 6 European sites. We show that JULES-SUCROS significantly improves the correlation between simulated and observed fluxes over cropland and captures well the spatial and temporal variability of the growth conditions in Europe. Simulations with JULES-SUCROS highlight the importance of vegetation structure and phenology, and the impact they have on land–atmosphere interactions. [Copyright &y& Elsevier]

Abstract: From February 2000 to December 2008 systematic measurements of CO2 ambient concentrations were taken using a MIR 9000 continuous infrared analyser in a rural area of the upper Spanish plateau. The wide database obtained has enabled us to quantify CO2 levels at the measuring site and describe daily and seasonal cycles as well as inter-annual variability. The daily cycle and seasonal variation were dominated by strong temperature inversions, TI, prevailing at the measuring site, up to 7.5°C per 100m, which largely contributed to trapping CO2 during night-time, particularly during the growing season. This paper presents the influence of TI on CO2 and describes the results using available TI values below 3°C as a filtering criterion addressed to minimise local disturbances. The filtered monthly means exhibited a seasonal variation characterised by a primary peak in May, a secondary weak peak in October and a minimum in July–August. Seasonal amplitude yielded 8.7ppm. Over the whole study period, the annual trend, estimated by means of a second order harmonic model applied to the monthly means (R 2 =95.6%), yielded a positive linear increase of 2.98 and a 0.64ppmyear−1 rise in the amplitude of the seasonal cycle. [Copyright &y& Elsevier]

Abstract: Evapotranspiration is an important flux term in the water cycle that integrates atmospheric demands and surface conditions. Thus, analysis of the temporal variation of reference evapotranspiration (ET0) will help us to understand climate change and its effect on hydrology. In this paper, we present an analysis of the monthly ET0 at 15 stations during 1961–2005 in the Taoer River basin in China, calculated by the FAO Penman–Monteith method. We derived the growing season and annual total ET0 time series and using the Mann–Kendall method, moving t test and Morlet wavelet conducted comprehensive time series analysis to characterize significance test, abrupt change and period in the ET0 data sets. The results present that: (i) in terms of the seasonal cycle, monthly ET0 reaches its peak in May and growing season ET0 accounts for 60.7% of annual total. Long term growing season ET0 fluctuates in accordance with annual ET0, both having turning points in 1982 and 1993; (ii) with respect to the long term persistence, the trends for growing season and annual ET0 show the same spatial patterns: high positive values in the west study area in the upper reach and negative values in the Southeast study area in the lower reach. The spatial distribution of annual tendencies suggests an influence from the altitude and latitude; (iii) for individual station, abrupt changes in annual ET0 are more pronounced than those in growing season ET0. The timings for the abrupt changes in ET0 series at individual stations are consistent with those in regional ET0. Abrupt changes detected in the early 1980s are all increasing changes, while those in earlier 1990 are all decreasing changes; and (iv) based on the Morlet wavelet analysis, there exist significant periods of 1, 3 and 7.3 years in annual ET0 series and significant 1 year period and 7.3 years period in growing season ET0 series. Maximum air temperature, mean air temperature, relative humidity and bright sunshine hours are main climate variables responsible for the periodicity in ET0. [Copyright &y& Elsevier]

Abstract: CO2 is one of the most important gases linked to climate change. However, its ambient concentrations in a clean atmosphere have scarcely been investigated. In this paper a close relationship between CO2 concentrations and meteorological variables was proposed to establish atmospheric conditions linked to high CO2 values. A detailed 3-year campaign was carried out in a rural area with a CO2 continuous analyser and a RASS sodar for meteorological variables. Daily and yearly CO2 cycles were obtained. In addition, semi-hourly medians and quartiles were fitted to straight lines during the night time and daily maxima and minima were parameterised by means of a second order cylindrical model. Six meteorological variables were considered: wind speed, wind direction and temperature at one level and differences between them at two levels. Intervals were proposed from the highest CO2 concentrations during the night to build up a binary system of 64 meteorological classes. Analysis of both CO2 medians and meteorological classes enabled simplification of the system to four groups. The first group, characterised by high temperatures and drainage flow, was associated with detrended median concentrations above 15ppm. Two groups of moderate concentrations were linked to thermal inversions and no prevailing wind directions. The final group corresponded to low concentrations associated with less than three meteorological variables with values linked to high concentrations. Only high directional shear and low wind speed were relevant in this group. This 4-group system was successfully used with the whole dataset. [Copyright &y& Elsevier]

Abstract: This paper reports 3 years of eddy covariance measurements (2002–2004) on a poplar plantation (Populus × canadensis Moench, Clone I-214) in Northern Italy. We analyzed seasonal and interannual variability of the net ecosystem exchange (NEE), gross primary production (GPP), ecosystem respiration (R ECO) and evapotranspiration (ET) in relation to different meteorological and environmental conditions experienced by the plantation and to natural disturbances. In particular, during 2003 climatic conditions were exceptionally severe, with the highest mean air temperatures and the lowest precipitations observed in the study area in the last 50 years. In addition, during the late summer of 2004, the plantation was attacked by fall webworm larvae (Hyphantria cunea). The cumulated NEE during the three growing season (April–September) was −752.8, −626.7 and −702.7gCm−2 for 2002, 2003 and 2004, respectively. In the period June–August 2003, NEE was 35% and 29% higher than the NEE measured in the same period in 2002 and 2004, respectively, resulting in a lower net carbon uptake. As R ECO did not show large differences over the three growing seasons, the reduction in net carbon sequestration of June–August 2003 is mainly explained by a reduction of GPP (−18% and −17% in 2002 and 2004, respectively). The cumulated ET over the three growing seasons was 388, 471, 484kg H2Om−2 for 2002, 2003 and 2004, respectively. This behaviour was due to the fact that the position of the water table remained close to the roots, therefore supplying enough water to the plantation, even during the driest period. The analysis of light curve parameters, their residuals and canopy conductance suggests that the reduction of CO2 uptake during summer 2003 was mainly controlled by stomatal and non-stomatal limitations due to high temperatures, directly and in particular indirectly (i.e. through D) rather than by soil water stress. In conclusion, our study shows that in the presence of a heat-wave, a significant reduction of net productivity during summer may occur even in the absence of marked soil water stress. In addition to this sensitivity to high temperatures, which will likely increase in the future, the effects of natural disturbances may add further uncertainties, thus suggesting caution in the evaluation of the potential carbon sequestration of these ecosystems. [Copyright &y& Elsevier]

Abstract: In this paper we present a comprehensive set of interpolated climate data for western Canada, including monthly data for the last century (1901–2006), future projections from general circulation models (68 scenario implementations from 5 GCMs), as well as decadal averages and multiple climate normals for the last century. For each of these time periods, we provide a large set of basic and derived biologically relevant climate variables, such as growing and chilling degree days, growing season length descriptors, frost free days, extreme minimum temperatures, etc. To balance file size versus accuracy for these approximately 15,000 climate surfaces, we provide a stand-alone software solution that adds or subtracts historical data and future projections as medium resolution anomalies (deviations) from the high resolution 1961–1990 baseline normal dataset. For a relative quality comparison between the original normal data generated with the Parameter Regression of Independent Slopes Model (PRISM) and derived historical data, we calculated the amount of variance explained (R 2) in original weather station data for each year and month from 1901 to 2006. R 2 values remained very high for most of the time period covered for most variables. Reduction in data quality was found for individual months (as opposed to annual, decadal or 30-year climate averages) and for the early decades of the last century. We discuss the limitations of the database and provide an overview of recent climate trends for western Canada. [Copyright &y& Elsevier]

Abstract: Assessment of the response of the carbon cycle to climate change is important for predicting future climate, especially in northern high latitudes, where the warming may be highly pronounced. In this paper, three years of data measured by the eddy covariance method were used to verify the carbon dynamics of a black spruce forest in interior Alaska with the BIOME-BGC model. The model was modified and calibrated to the cold regions. The calibrated model simulation satisfactorily performed reproduction of the observed net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RE). The daily output of the model also correlated with field-based estimates of NEE (42%), GPP (89%), and RE (89%). The model simulation showed that the heterotrophic respiration occupied a substantial portion of total carbon exchange, and that inter-annual variation of the heterotrophic respiration determined the sink/source strength of carbon. According to our simulation, the black spruce forest in interior Alaska was a net carbon sink between 1949 and 2005, and the trend of the projected sink strength was not obvious in the recent climate warming. The model analysis suggested that the change in the seasonal weather pattern strongly affected the carbon balance. A potentially increased carbon sink due to future warming climate and elevated CO2 will be at least partly offset by a concurrent increase of VPD, since the response of the stomatal conductance to increased VPD could increase the soil moisture, and thus stimulate heterotrophic respiration, rather than net primary productivity. The results of this study should be useful to forecast the response of the carbon cycle to warming in black spruce forests of interior Alaska. [Copyright &y& Elsevier]

Abstract: This paper summarizes and synthesises the results obtained in several recent studies on water and energy exchange of East Siberian forests located on permafrost. It is found that annual evaporation of these forests shows relatively small inter-annual variation (147–196mm). The availability of stored water in the permafrost probably functions as a buffering resource that is only used occasionally in very dry years. Surface soil water content shows a 1-year memory to precipitation in Eastern Siberia because the precipitation conditions in previous summers carry over in a frozen condition to the next spring. Modelling shows that evaporation was larger for southern forests than for northern forests. Compared to tundra, taiga forest shows a relatively small Bowen ratio. In an alas system, observations show considerable impact of the distribution of lakes in the vicinity on the observed evaporation fluxes. There appeared to be little difference in the observed Bowen ratio between a young and old larch forest. Surface conductance modelling and upscaling studies note that leaf area index (LAI) was a controlling factor in evaporation. With the permafrost area under strong pressure from climate warming, the need to understand the ecophysiological controls of these forests in East Siberia is paramount. With the data and analysis presented in this special issue becoming available we are now in a better position to model the effects of permafrost degradation on water and energy balances. [Copyright &y& Elsevier]

Abstract: The objective of this study was to quantify the main terms of the water cycle in a Scots pine stand (Pinus sylvestris L.) growing on a sandy soil and to estimate the contribution of the shallow water table (0.80m deep in spring) to the forest water use. Continuous monitoring was organized in 2005 to measure climate, throughfall, soil moisture, tree transpiration and water table variations at a half-hourly basis. Leaf area index seasonal dynamic was measured and roots were counted down to the bottom of the soil profile. Forest floor evapotranspiration was modelled with Granier et al. [Granier, A., Bréda, N., Biron, P., Villette, S., 1999. A lumped water balance model to evaluate duration and intensity of drought constraints in forest stands. Ecol. Model. 116, 269–283]. From May to November, pine transpiration never exceeded 1.85mmd−1 and reached a total of 176.4mm, which corresponded to 25% of potential evapotranspiration, whereas the understorey evapotranspiration was 130mm (i.e. 18–20% of the stand water use). The maximum soil water reserve measured over the soil rooted zone was 250mm, in which 145mm was extractable water. A 3.5-week period with no rain was observed in June, which induced a regulation of pine transpiration when the soil extractable water reached 0.25 of its maximum value. We applied the water table fluctuation (WTF) method [White, W., 1932. A method for estimating groundwater supplies based on discharge by plants and evaporation from soil. US Geol. Survey Water Supply Paper 659-A. United States Government Printing Office, Washington, DC] to estimate the water table daily loss of water. A relationship was established with potential evapotranspiration and the actual transpiration fluxes of the stand. Yet, it was not possible to extract from the WTF results the part that was effectively contributing to actual transpiration. We applied then the WTF methodology on longer time intervals, with a focus on periods with no rains. From May to November, the contribution of the water table to forest transpiration reached 61%. During the drought period in June, the water table contributed to 98.5% of the water uptake by vegetation, through its contribution to the capillary rise above the water table. The presence of a groundwater table with a floor down to 180–200cm allowed this stand to rely upon water that otherwise would have drained deeper. [Copyright &y& Elsevier]

Abstract: Climate change has already affected the phenology of several species. To be able to assess the impacts of climate change under various climate scenarios, we need superior models of the phenology of different species. Linear regression methods alone are of limited value for the analyses of natural indicators or phenological data because most time series of naturally occurring events in ecosystems do change in a nonlinear way. In this paper, we applied a Bayesian probability approach to investigate time series of the phenological phase of bud burst in Norway spruce (Picea abies (L.) Karst.) and mean monthly/weekly temperatures of corresponding climate stations in Germany. In these temperature and Norway spruce bud burst time series we detected years with the highest probability for discontinuities. We analysed rates of change and the relationship between temperature changes and bud burst of Norway spruce in the 51-year period 1953–2003. We used a Bayesian method for a coherence analysis between phenological onset dates and an effective temperature generated as a weighted average of monthly and weekly means from January to May. Weight coefficients were obtained from an optimization of the coherence factor by simulated annealing. In all investigated cases we found coherence factors that suggested a relationship between temperature and phenological time series. Norway spruce bud burst and mean temperature times series of April and May exhibited abrupt changes, particularly at the beginning of the 1980s. April and May temperature time series revealed an increased warming until 2003, and bud burst events advanced. Norway spruce bud burst, in particular, exhibited responses to temperatures of the previous (April) and current month (May). We suggest that besides commonly used sums of daily mean temperatures, forcing temperatures in phenology models should also include solutions where weighted effective temperatures in a sensitive time span are considered. [Copyright &y& Elsevier]

Abstract: Current climate change patterns may cause more extreme and variable climates in the future, threatening agricultural productivity in many areas of the world. Because many smallholder, rural farmers depend on subsistence, rainfed agriculture, priorities should be focused on coping mechanisms that protect these farmers from future vulnerabilities. This paper examines one possible adaptive strategy for coffee agriculture. A high (60–80%), medium (35–65%), and low (10–30%) shade coffee site were chosen in the Soconusco region of Chiapas, Mexico. Microclimate and soil moisture data were collected to examine the ability of shade tree cover in an agroforestry system to protect crop plants against extremes in microclimate and soil moisture fluctuation. Site and site by time effects were analyzed using linear mixed models to compare mean differences of microclimate measurements (temperature, relative humidity, and solar radiation) by site as well as by time of the day. Although there were not large differences in seasonal means for these factors, site by time effects show that temperature, humidity, and solar radiation fluctuations increase significantly as shade cover decreases. Soil data showed significantly larger fluctuations in soil moisture gain and loss in the low shade site respective of patterns of precipitation. Overall, the amount of shade cover was directly related to the mitigation of variability in microclimate and soil moisture for the crop of interest. The use of agroforestry systems is an economically feasible way to protect crop plants from extremes in microclimate and soil moisture and should be considered a potential adaptive strategy for farmers in areas that will suffer from extremes in climate. [Copyright &y& Elsevier]

Abstract: This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective. [Copyright &y& Elsevier]

Abstract: This paper summarizes the variations of trace gas behaviour and climate during the Holocene (approximately the last 10,000 years), with reference to the last four ice age cycles. The industrial era, commonly regarded as commencing during the 18th century, is one noted when atmospheric greenhouse gas increases due to burning of fossil fuels and land use changes have been attributed to increases in global average near-surface temperatures, particularly in the latter part of the 20th century. However, analysis by Ruddiman has noted that in the Holocene during the period of civil society, the changes in atmospheric greenhouse gases have been anomalous compared with the geological record of the last 400,000 years. During this period, both carbon dioxide (CO2) and methane (CH4) increased, probably as a result of the introduction of agrarian agriculture and land clearing in Eurasia. These, and other land use changes because of agrarian rural activities, may have caused a subtle forcing of climate, preventing climate cooling which might have been expected because of natural forcing. If future evidence supports the Ruddiman hypothesis, then agricultural and forestry activities during the period of civil society may have been exerting an influence on climate for, at least, the last 8000 years. [Copyright &y& Elsevier]

Abstract: An increasing number of studies have reported on shifts in timing and length of the growing season, based on phenological, satellite and climatological studies. The evidence points to a lengthening of the growing season of ca. 10–20 days in the last few decades, where an earlier onset of the start is most prominent. This extension of the growing season has been associated with recent global warming. Changes in the timing and length of the growing season (GSL) may not only have far reaching consequences for plant and animal ecosystems, but persistent increases in GSL may lead to long-term increases in carbon storage and changes in vegetation cover which may affect the climate system. This paper reviews the recent literature concerned with GSL variability. [Copyright &y& Elsevier]

A national assessment (NA) evaluated the potential consequences of climate change and variability on the agriculture, water resources, as well as other economic and natural resource sectors in the United States. As part of this process, we used scenarios of the HadCM2 GCM and the EPIC agroecosystem model to evaluate climate-change impacts on crop yields and ecosystem processes. Baseline climate data were obtained from national records for 1961–1990. The scenario runs for 2025–2034 and 2090–2099 were extracted from a HadCM2 run. EPIC was run on 204 representative farms under current climate and two 10-year periods centered on 2030 and 2095, each at CO2 concentrations of 365 and 560 ppm. Crops were simulated under both dryland and irrigated management, with irrigation water supply estimates taken from the HUMUS simulations in Paper 1. Texas, New Mexico, Colorado, Utah, Arizona, and California are projected to experience significant temperature increases by 2030. Slight cooling is expected by 2030 in Alabama, Florida, Maine, Montana, Idaho, and Utah. Larger areas are projected to experience increased warming by 2095. Uniform precipitation increases are expected by 2030 in the northeast. These increases are predicted to expand to the eastern half of the country by 2095. Regionally, dryland corn yields could increase, decrease or remain unchanged under the two scenarios. EPIC simulated yield increases for the Great Lakes, Corn Belt and Northeast regions. Simulated yields of irrigated corn were predicted to increase in almost all regions. Soybean yields could decrease in the Northern and Southern Plains, the Corn Belt, Delta, Appalachian, and Southeast regions and increase in the Lakes and Northeast regions. Simulated wheat yields exhibited upward trends under scenarios of climate-change. Evapotranspiration in dryland corn is expected to increase in both future periods while water-use efficiency will decrease. National corn production in 2030 and 2095 could be affected by changes in three major producing regions. In 2030, corn production could increase in the Corn Belt and Lakes regions but decrease in the Northern Plains leading to an overall decrease in national production. National wheat production is expected to increase during both future periods. A proxy indicator was developed to provide a sense of where in the country, and when water would be available to satisfy change in irrigation demand for corn and alfalfa production as these are influenced by the HadCM2 scenarios and CO2-fertilization. Irrigation requirement by irrigated crops declines under these scenarios as transpiration is suppressed. [Copyright &y& Elsevier]

• GHG emissions and crop water demand under various scenarios were evaluated. • Changes in planting structure in the study area increased water demand and GHG emissions. • The expansion of the planting area is the main reason for increasing water demand and GHG emissions. • Rice has the greatest impact on GWP during the study period in Heilongjiang. The agriculture sector is one of the largest users of water and a significant source of greenhouse gas (GHG) emissions. The development of low-GHG-emission and water-conserving agriculture will inevitably be the trend in the future. Because of the physiological differences among crops and their response efficiency to external changes, changes in planting structure, climate and input of production factors will have an impact on regional agricultural water use and GHG emissions. This paper systematically analyzed the spatial-temporal evolution characteristics of crop planting structure, climate, and production factor inputs in Heilongjiang Province, the main grain-producing region of China, from 2000 to 2015, and quantified the regional agricultural water use and GHG emissions characteristics under different scenarios by using the Penman-Monteith formula and the Denitrification-Decomposition (DNDC) model. The results showed that the global warming potential (GWP) increased by 15% due to the change in planting structure. A large increase in the proportion of rice and corn sown was the main reason. During the study period, regional climate change had a positive impact on the water-saving and emission reduction of the agricultural industry. The annual water demand per unit area decreased by 19%, and the GWP decreased by 12% compared with that in 2000. The input of fertilizer and other means of production will have a significant impact on GHG emissions from farmlands. The increase in N fertilizer input significantly increased N 2 O emissions, with a 5% increase in GWP. Agricultural water consumption and carbon emissions are affected by changes in climate, input of means of production, and planting structure. Therefore, multiple regulatory measures should be taken in combination with regional characteristics to realize a new layout of planting structure with low emissions, water conservation, and sustainability. [ABSTRACT FROM AUTHOR]