Average Growing Season Temperature Research Articles

Grape harvest and yield responses to inter-annual changes in temperature and precipitation in an area of north-east Spain with a Mediterranean climate

This study presents an analysis of temperature and precipitation trends and their impact on grape harvests in the Penedès region (NE Spain). It includes analyses of maximum, minimum and mean daily temperatures (for both the growing and ripening seasons) and daily rainfall (for the hydrological year, the growing season and each phenological stage) for three observatories in the immediate area. We analysed a series of factors: beginning and end harvest dates; the day on which a given potential alcoholic degree was reached; and yield for several varieties of grape grown in the area in relation to climatic variables. Maximum temperatures increased at all the observatories, with greater values being recorded in recent years (1996-2009) than in previous decades (1960s-2000s): we observed increases in average growing season temperatures of 0.11°C per year for the period 1996-2009 vs 0.04°C per year for the period 1960-2009 at Vilafranca del Penedès. These temperature changes were due mainly to increases in maximum temperatures and an increase in the incidence of extreme heat (number of days with T > 30°C). Crop evapotranspiration also increased significantly during the same period. The Winkler index also increased, so the study area would correspond to region IV according to that climatic classification. There were no significant trends in annual rainfall but rainfall recorded between bloom and veraison decreased significantly at the three observatories, with the greatest decrease corresponding to the period 1996-2009. The dates on which harvests started and ended showed a continuous advance (of between -0.7 and -1.1 days per year, depending on the variety), which was significantly correlated with the average mean and maximum daily growing season temperatures (up to -7.68 days for 1°C increase). Winegrape yield was influenced by the estimated water deficit (crop evapotranspiration minus precipitation) in the bloom-veraison period; this value increased due to a reduction in precipitation and an increase in evapotranspiration. Yield may have been reduced by up to 30 kg/ha for each millimetre increase in the estimated water deficit. Under these conditions, new strategies need to be followed in this area in order to maintain grape quality and yield.

Correlation between temperature and phenology prediction error in rice (Oryza sativa L.)

For rice (Oryza sativa L.), simulation models like ORYZA2000 and CERES-Rice have been used to explore adaptation options to climate change and weather-related stresses (drought, heat). Output of these models is very sensitive to accurate modelling of crop development, i.e. phenology. What has to date received little attention in phenology calibration is the temperature range within which phenological models are accurate. Particularly the possible correlation between temperature and phenology prediction error has received little attention, although there are indications that such correlation exists, in particular in the study by Zhang et al. (2008). The implication of such correlation is that a phenology model that is accurate within the calibration temperature range can be less accurate at higher temperatures where it can systematically overestimate or underestimate the duration of the phase from emergence to flowering. We have developed a new rice phenology calibration program that is consistent with ORYZA2000 concepts and coding. The existing calibration program DRATES of ORYZA2000 requires an assumption of default cardinal temperatures (8, 30 and 42°C) and then calculates cultivar specific temperature sums and development rates. Our new program estimates all phenological parameters simultaneously, including the cardinal temperatures. Applied to nine large datasets from around the world we show that the use of default cardinal temperatures can lead to correlation between temperature and phenology prediction error and temperature and RMSE values in the order of 4–18 days for the period from emergence to flowering. Our new program avoids such correlation and reduces phenology prediction errors to 3–7 days (RMSE). Our results show that the often made assumption of a rapid decrease in development rate above the optimal temperature can lead to poorer predictions and systematic errors. We therefore caution against using default phenological parameters for studies where temperatures may fall outside the range for which the phenological models have been calibrated. In particular, this applies to climate change studies, were this could lead to highly erroneous conclusions. More phenological research with average growing season temperatures above the optimum, in the range of 32–40°C, is needed to establish which phenological model best describes phenology in this temperature range.

Interacting controls on productivity in a northern Great Plains grassland and implications for response to ENSO events

In this study we investigated the causes of annual variability in peak aboveground biomass production, net ecosystem productivity (NEP) and gross ecosystem productivity (GEP) during an 8-year period (1999–2006) in a northern Great Plains grassland near Lethbridge, Alberta, Canada. In particular, we tested for a significant relationship between growing season precipitation and productivity and determined whether soil moisture carry-over from the previous fall–winter could alter this relationship. We also investigated the interaction between soil moisture availability and temperature in controlling grassland productivity. There was a very strong correlation between total precipitation input and average soil moisture content during the May–October growing season. However, the growing season average soil moisture contents in 2003 and 2006 were very similar to those recorded in 1999, despite lower than normal precipitation occurring in these 2 years. This resulted from a positive difference between precipitation and evapo-transpiration that allowed significant soil moisture to be carried-over from the previous fall–winter during both 2003 and 2006. Strong logistic relationships were observed between soil moisture and annual productivity based on data from all years except 2003 and 2006, years which had higher productivity than was predicted from the logistic regression. Interaction between temperature and soil moisture explained this difference. Productivity values in 2003 and 2006 were high compared with 1999, a year with approximately the same soil moisture content, and this resulted from the higher average growing season temperatures that were apparent in 2003 and 2006. Analysis of weather records indicated that precipitation in the month of June was significantly higher during El Niño years than during La Niña years in Lethbridge. During the study period, aboveground biomass, NEP and GEP were generally higher in El Niño years and lower in La Niña years because of associated variation in summer precipitation.

Grapevine Phenology and Climate Change: Relationships and Trends in the Veneto Region of Italy for 1964–2009

A long-term (1964–2009), multiple <i>Vitis vinifera</i> L. cultivar data set has provided a comprehensive assessment of cultivar similarities/differences in phenological timing and growth phases and relationships with climate and climate change in the Veneto region of Italy. The budbreak to harvest period for the cultivars studied covered mid-April to late September, averaging 156 days but varying 55 days across cultivars. The main phenological events and intervals between events exhibited a 25 to 45 day variation between the earliest and latest years, with the bloom to veraison growth interval showing the lowest vintage-to-vintage variation. From 1964–2009, trends of 13 to 19 days earlier were found for bloom, veraison, and harvest dates, while budbreak exhibited high interannual variation and no trend. There were similar characteristics and trends for the main phenological events for early, middle, and late maturing cultivars, although early maturing cultivars changed at a higher rate. Changes in climate in the region led to significant breakpoints in the phenology time series, averaging 1990–1991 across all cultivars, with early and middle cultivars shifting sooner than late cultivars. Growing season average temperatures warmed 2.3°C from 1964–2009, while annual and seasonal precipitation amounts did not change significantly. From 1964–2009, the growing period climate differences were 2.0°C between the years with the shortest and the longest budbreak to harvest intervals. The combined trends in phenology and climate resulted in an average shift of eight days per 1.0°C of warming. The extremely warm summer of 2003 (compressed growth intervals) and warm spring of 2007 (shifts in phenological timing) provide analog conditions to those projected for later this century.

Spatial Analysis of Climate in Winegrape Growing Regions in the Western United States

Knowledge of the spatial variation in temperature in wine regions provides the basis for evaluating the general suitability for viticulture, allows for comparisons between wine regions, and offers growers a measure of assessing appropriate cultivars and sites. However, while tremendous advances have occurred in spatial climate data products, these have not been used to examine climate and suitability for viticulture in the western United States. This research spatially maps the climate in American Viticultural Areas (AVAs) throughout California, Oregon, Washington, and Idaho using the 1971–2000 PRISM 400 m resolution climate grids, assessing the statistical properties of four climate indices used to characterize suitability for viticulture: growing degree-days (GDD, or Winkler index, WI), the Huglin index (HI), the biologically effective degree-day index (BEDD), and average growing season temperatures (GST). The results show that the spatial variability of climate within AVAs can be significant, with some regions representing as many as five climate classes suitable for viticulture. Compared to static climate station data, documenting the spatial distribution of climate provides a more holistic measure of understanding the range of cultivar suitability within AVAs. Furthermore, results reveal that GST and GDD are functionally identical but that GST is easier to calculate and overcomes many methodological issues that occur with GDD. The HI and BEDD indices capture the known AVA-wide suitability but need to be further validated in the western U.S. Additionally, the research underscores the necessity for researchers, software developers, and others to clearly communicate the data time period and method of calculating GDD so that results can be correctly interpreted and compared.

On the use of statistical models to predict crop yield responses to climate change

Predicting the potential effects of climate change on crop yields requires a model of how crops respond to weather. As predictions from different models often disagree, understanding the sources of this divergence is central to building a more robust picture of climate change's likely impacts. A common approach is to use statistical models trained on historical yields and some simplified measurements of weather, such as growing season average temperature and precipitation. Although the general strengths and weaknesses of statistical models are widely understood, there has been little systematic evaluation of their performance relative to other methods. Here we use a perfect model approach to examine the ability of statistical models to predict yield responses to changes in mean temperature and precipitation, as simulated by a process-based crop model. The CERES-Maize model was first used to simulate historical maize yield variability at nearly 200 sites in Sub-Saharan Africa, as well as the impacts of hypothetical future scenarios of 2 °C warming and 20% precipitation reduction. Statistical models of three types (time series, panel, and cross-sectional models) were then trained on the simulated historical variability and used to predict the responses to the future climate changes. The agreement between the process-based and statistical models’ predictions was then assessed as a measure of how well statistical models can capture crop responses to warming or precipitation changes. The performance of statistical models differed by climate variable and spatial scale, with time-series statistical models ably reproducing site-specific yield response to precipitation change, but performing less well for temperature responses. In contrast, statistical models that relied on information from multiple sites, namely panel and cross-sectional models, were better at predicting responses to temperature change than precipitation change. The models based on multiple sites were also much less sensitive to the length of historical period used for training. For all three statistical approaches, the performance improved when individual sites were first aggregated to country-level averages. Results suggest that statistical models, as compared to CERES-Maize, represent a useful if imperfect tool for projecting future yield responses, with their usefulness higher at broader spatial scales. It is also at these broader scales that climate projections are most available and reliable, and therefore statistical models are likely to continue to play an important role in anticipating future impacts of climate change.

지역기후모형 자료를 이용한 낙동강 권역의 논 관개용수 수요량 예측

The paddy irrigation demand for Nakdong river basin in Korea due to the climate change have been analyzed using regional climate model outputs. High-resolution (27 <TEX>${\times}$</TEX> 27 km) climate data for SRES A2 scenario produced by the Meteorological Research Institute (METRI), South Korea, and the observed baseline climatology dataset (1971-2000) were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by METRI. Maps showing the predicted spatial variations of changes in climate parameters and paddy irrigation requirements have been produced using the geographic information system. The results of this study showed that the average growing season temperature will increase steadily by 1.5 <TEX>$^{\circ}C$</TEX> (2020s A2), 3.2 <TEX>$^{\circ}C$</TEX> (2050s A2) and 5.2 <TEX>$^{\circ}C$</TEX> (2080s A2) from the baseline (1971-2000) 19.8 <TEX>$^{\circ}C$</TEX>. The average growing season rainfall will change by -3.4 % (2020s A2), 0.0 % (2050s A2) and +16.5 % (2080s A2) from the baseline value 886 mm. Assuming paddy area and cropping pattern remain unchanged the average volumetric irrigation demands were predicted to increase by 5.3 % (2020s A2), 8.1 % (2050s A2) and 2.2 % (2080s A2) from the baseline value 1.159 <TEX>${\times}$</TEX> <TEX>$10^6\; m^3$</TEX>. These projections are different from the previous study by Chung (2009) which used a different GCM and downscaling method and projected decreasing irrigation demands. This indicates that one should be careful in interpreting the results of similar studies.

Risks of Extreme Heat and Unpredictability

In their Report “Historical warnings of future food insecurity with unprecedented seasonal heat” (9 January, p. [240][1]), D. S. Battisti and R. L. Naylor argue that because agricultural yields are severely reduced in anomalously hot years, a general rise in average growing season temperature

Differential expression of the CBF pathway and cell cycle‐related genes in Arabidopsis accessions in response to chronic low‐temperature exposure

Low, non-freezing temperatures are a major factor limiting growth and development of vegetation in cold climates. Activation of the C-repeat binding factor (CBF) regulatory pathway by acute cold treatment is important for cold acclimation and freezing tolerance in Arabidopsis thaliana; however, the potential role of this pathway in response to chronic cold treatment has been less well characterised. We studied long-term (chronic) effects of low, non-freezing temperatures on the expression of CBF pathway genes (CBF2/3, COR15a, RD29A) and cell cycle-related genes (CDKA;1, CYCD2;1, CYCB1;1) in roots of accessions from habitats differing in growing season temperatures. Elongation rates of primary roots at 21 and 10 degrees C were not significantly correlated with average growing season temperatures, indicating that there is no ecotypic differentiation for these traits. Measurements of mRNA accumulation in roots of seven accessions showed that expression of CBF2/3, COR15a and RD29A is induced by both acute cold treatment (2-24 h at 4 degrees C) and chronic cold treatment (5-6 weeks at 10 degrees C), while CYCB1;1 is only induced by chronic cold treatment. RD29A and COR15a mRNA levels were correlated (P < 0.05) with the rate of root elongation in the cold for three high-altitude accessions relative to the common laboratory stain, Col-0. Our results are consistent with the hypothesis that induction of CBF2/3, COR15a, RD29A and CYCB1;1 is a physiological response to cold that, in the case of RD29A and COR15a, may be important for root growth at low temperatures.

기후변화가 낙동강 권역의 논 관개용수 수요량에 미치는 영향

The impacts of climate change on paddy irrigation requirements for Nakdong river basin in Korea have been analyzed. The HadCM3 model outputs for SRES A2 and B2 scenarios and International Water Management Institute <TEX>$10'{\times}10'$</TEX> pixels observed data were used with kriging method. Maps showing the predicted spatial variations of changes in climate parameters and paddy irrigation requirements have been produced using the GIS. The results showed that the average growing season temperature was projected to increase by <TEX>$2.2^{\circ}C$</TEX> (2050s A2), <TEX>$0.0^{\circ}C$</TEX> (2050s B2), <TEX>$3.7^{\circ}C$</TEX> (2080s A2) and <TEX>$2.9^{\circ}C$</TEX> (2080s B2) from the baseline (1961-1990) value of <TEX>$21{\circ}C$</TEX>. The average growing season rainfall was projected to increase by 15.2% (2050s A2), 24.2% (2050s B2), 41.4% (2080s A2) and 16.7% (2080s B2) from the baseline value of 900 mm. Average volumetric irrigation demands were projected to decrease by 3.7% (2050s A2), 7.0% (2050s B2), 10.2% (2080s A2) and 1.4% (2080s B2) from the baseline value of <TEX>$1.25{\times}10^9\;m^3$</TEX>. These results can be used for the agricultural water resources development planning in the Nakdong river basin for the future.

A Chernozem soil water regime response to predicted climate change scenarios

Climate, hydrology and vegetation are closely linked at local, regional and global scales. The recent land use and plant production systems are adapted to the present climatic conditions. Thus, studies on the influence of possible climate change scenarios on the water and heat regimes of the soil-plant-atmosphere system are important in order to work out plant production strategies, adjusted to changed conditions. In this study the effect of two possible climate change scenarios on the soil water regime of a Chernozem soil was estimated for a Hungarian site. Soil water content dynamics simulated for different conventional and soil conserving soil tillage systems were evaluated, using the SWAP soil water balance simulation model. The combined effect of different soil tillage systems and climate scenarios was analysed. Climate scenarios were represented through the cumulative probability function of the annual precipitation sum. The SWAP model was calibrated against the measured in the representative soil profiles soil water content data. The site- and soil-specific parameters were set and kept constant during the scenario studies. According to the simulation results, increase in the average growing season temperature showed increase in climate induced soil drought sensitivity. The evaluated soil water content dynamics indicated more variable and less predictable soil water regime compared to the present climate. It was found that appropriate soil tillage systems that are combined with mulching and ensure soil loosening could reliably decrease water losses from the soil. From this aspect cultivator treatment created the most favourable for the plants soil conditions. It was concluded that soil conserving soil management systems, adapted to local conditions could contribute to soil moisture conservation and could increase the amount of plant available water under changing climatic conditions.

Vegetation cover changes and their relationship to climate variation in the source region of the Yellow River, China, 1990–2000

The change history of vegetation cover and its relations to growing season precipitation (GSP) and average growing season temperature (AGST) in the source region of the Yellow River (SRYR) during 1990–2000 was retrieved based on the 1 km Advanced Very High‐Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data and meteorological records. The results show an overall warming and drying trend of the climate and a common degradation tendency of the ecosystem, with a greening trend in higher rugged regions. The pixel‐by‐pixel correlations between NDVI and climate factors indicate that a decrease in GSP mainly affects ecosystems with low precipitation and worse vegetation condition, and superimposes on the effects of increasing AGST which further deteriorate the climate background of these ecosystems. However, the positive correlations between AGST and NDVI in some higher/rugged regions suggest that the raising temperature can ameliorate vegetation growth conditions in these areas. Comparison and combination of the results of three change detection algorithms, i.e. post‐classification comparison (PCC), principal components analysis (PCA) and a newly developed multi‐temporal image difference (MTID) method, show that the integration of different methods can give a more comprehensive understanding of vegetation changes than any single method.

Temperature‐dependence of biomass accumulation rates during secondary succession

Rates of ecosystem recovery following disturbance affect many ecological processes, including carbon cycling in the biosphere. Here, we present a model that predicts the temperature dependence of the biomass accumulation rate following disturbances in forests. Model predictions are derived based on allometric and biochemical principles that govern plant energetics and are tested using a global database of 91 studies of secondary succession compiled from the literature. The rate of biomass accumulation during secondary succession increases with average growing season temperature as predicted based on the biochemical kinetics of photosynthesis in chloroplasts. In addition, the rate of biomass accumulation is greater in angiosperm-dominated communities than in gymnosperm-dominated ones and greater in plantations than in naturally regenerating stands. By linking the temperature-dependence of photosynthesis to the rate of whole-ecosystem biomass accumulation during secondary succession, our model and results provide one example of how emergent, ecosystem-level rate processes can be predicted based on the kinetics of individual metabolic rate.

CLIMATE CHANGE IN THE WESTERN UNITED STATES GRAPE GROWING REGIONS

Climate is a pervasive factor in the viability of all forms of agriculture and is never more important than with the cultivation of grapes for the production of wine. In the Western United States grapes are grown over an extensive north-south gradient of climate types. In addition, grapevines are typically grown in regions and under conditions that are considered narrow for a specific cultivar’s optimum quality, ultimately putting it at a greater potential risk from climatic variations and change. Therefore, to examine the structure, variability, and trends in climate in the Western United States, this research analyzes growing season average temperatures and degree-days, annual and seasonal frost frequencies, the dates of last spring and first fall frost occurrence, and the length of the frost-free period for the principal grape growing regions in California, Oregon, and Washington from 1948-2002. Results reveal that, on average, most regions have experienced warmer growing seasons, driven mostly by changes in minimum temperatures, with greater heat accumulation, a decline in frost frequency that is most significant in the spring, earlier last spring frosts, later first fall frosts, and longer frost-free periods. While many of these trends may have been beneficial to grape growing and wine production in these regions, an examination of possible future climate change in these same regions indicates an average growing season warming of 1.7°C in the next 50 years. Depending on the seasonal structure and magnitude of climate change in the future, important issues for the wine industry include potential shifts in regional varietal viability and achieving optimum varietal ripeness and wine balance in a warmer environment.

Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach

AbstractAim To understand drivers of vegetation type distribution and sensitivity to climate change.Location Interior Alaska.Methods A logistic regression model was developed that predicts the potential equilibrium distribution of four major vegetation types: tundra, deciduous forest, black spruce forest and white spruce forest based on elevation, aspect, slope, drainage type, fire interval, average growing season temperature and total growing season precipitation. The model was run in three consecutive steps. The hierarchical logistic regression model was used to evaluate how scenarios of changes in temperature, precipitation and fire interval may influence the distribution of the four major vegetation types found in this region.Results At the first step, tundra was distinguished from forest, which was mostly driven by elevation, precipitation and south to north aspect. At the second step, forest was separated into deciduous and spruce forest, a distinction that was primarily driven by fire interval and elevation. At the third step, the identification of black vs. white spruce was driven mainly by fire interval and elevation. The model was verified for Interior Alaska, the region used to develop the model, where it predicted vegetation distribution among the steps with an accuracy of 60–83%. When the model was independently validated for north‐west Canada, it predicted vegetation distribution among the steps with an accuracy of 53–85%. Black spruce remains the dominant vegetation type under all scenarios, potentially expanding most under warming coupled with increasing fire interval. White spruce is clearly limited by moisture once average growing season temperatures exceeded a critical limit (+2 °C). Deciduous forests expand their range the most when any two of the following scenarios are combined: decreasing fire interval, warming and increasing precipitation. Tundra can be replaced by forest under warming but expands under precipitation increase.Main conclusion The model analyses agree with current knowledge of the responses of vegetation types to climate change and provide further insight into drivers of vegetation change.

A cyclical but asynchronous pattern of fine root and woody biomass production in a hardwood forest of southern Quebec and its relationships with annual variation of temperature and nutrient availability

In contrast to the well-documented seasonal variation in growth of below- and above-ground components of trees, the annual variation in below- and aboveground production is not well understood. In this study, we report on the monitoring of an unmanaged hardwood forest ecosystem in a small watershed of southern Quebec between 1993 and 1999. Below- and above-ground biomass production, leaf and soil solution chemistry, and air temperature were measured at different regular intervals and are reported on an annual basis. The objective of the study was to describe the annual dynamics of carbon partitioning between below- and above-ground tree components and to gain a better understanding of the soil and climatic factors that govern it. Fine root production peaked one year earlier than woody biomass production and years with high production of fine roots had low woody biomass production. All models that included May temperature in the calculation of the predicting/independent variables were significant predictors of total tree biomass production (r > 0.87). Fine root production was associated negatively with the previous year average growing season temperature (r < -0.84). Soil solution NO3 −, NH4 + and NO3 − + NH4 + concentrations were positively correlated with fine root production (r > 0.72) and negatively correlated with woody biomass production (r < -0.84). Leaf N and P concentrations were negatively correlated (r = -0.99 and r = -0.98, respectively) with fine root production for the period of 1994–1998. Our results suggest that a cool growing season, and in particular a cool month of October, is likely to result in low fine root production and nutrient uptake the following year and, therefore, to increase soil N availability and decrease leaf N. This initial response is thought to be the first step of a feedback loop involving plant N nutrition, soil N availability, fine root growth and aboveground biomass production that led to a cyclical (3–4 years) but asynchronous production of fine roots and aboveground biomass production.

An Assessment of First and Second Rotations Average Dominant/Codominant Height Growth for Slash Pine Plantations in South Georgia and North Florida

Abstract A slash pine (Pinus elliottii Engelm.) successive rotation plantation study was established in 1978–1979 for the north Florida and south Georgia flatwoods. The second rotation duplicated the first rotation seed source, site preparation, planting method and density. The comparison between the two rotations is based on the mean dominant/codominant height differential across a range of soil types and ages. There is a significant rotation 1 minus rotation 2 mean dominant/codominant height difference across the sites for all ages. Rotation 1 is 1.9 and 5.4 ft higher for mean dominant/codominant height at ages 2 and 20. The height differential is generally more significant for the spodosol soil type than the nonspodosol soil type. Rotation 1 generally experienced more favorable precipitation, for both the amount and timing of the precipitation within a year, than rotation 2. Rotation 2 experienced drought events and high growing season average temperatures during the first two growing seasons, while rotation 1 was near normal for this period. The evidence suggests that a main contributor to the decrease in mean dominant/codominant height across the spectrum of plots and age classes is the generally less favorable climatic growing season conditions experienced by rotation 2 relative to rotation 1. South. J. Appl. For. 26(2):61–71.

Ecological implications of projected climate change scenarios in forest ecosystems of central North America

Climate change scenarios in central North America were projected for selected weather stations using a stochastic daily weather simulation model. The projections were conditioned on changes in seasonal temperature and precipitation as predicted by several global climate models. The impacts of these projected changes on temperate forest ecosystems were evaluated through projected changes in such variables as average annual temperature, average growing season temperature, and the ratio of potential evaporation to precipitation during July and August. Even the mildest climate change scenario examined indicated that ecologically significant changes could occur in the composition and productivity of these forests. The possibility also exists that climatically induced regional decline episodes for a number of important commercial species could occur in the northern temperate forests of central North America.

Using yield prediction models to assess yield gains: a case study for wheat

A methodology for estimating yield gain using predictive models was tested in the Yaqui Valley of northwestern Mexico. The irrigated valley is representative of regions producing 40% of the developing world's wheat ( Triticum aestivum L.) and has been the subject of intensive wheat research investment during the last 30 years. Over the 1968–1990 (year of planting) study period, the linear increase in yield (± standard error) was 57.2 (± 12.8) kg ha −1 y −1 ( r 2 = 0.49) or 1.27 (± 0.26) % y −1 ( r 2 = 0.51). However, considerable variation in both yield and average growing season temperature were observed over the period. In an attempt to allow for yearly weather variation, two yield models (one simulation-based and one regression-based) assuming no change in cultivar or management were used to predict the weather-based potential yield of each year. These predicted yields showed a significant linear decline over the study period apparently due to a small increase in temperature. When average Valley yields were adjusted against simulated yields to take into account the variation in weather, the overall linear rate of yield gain increased to 103 (± 14.8) kg ha −1 y −1 ( r 2 = 0.69) or 1.91 (± 0.22) % y −1 ( r 2 = 0.78). Consequently, the allowance for the temporal temperature change showed that the returns to improved crop management and breeding have been superior to those suggested by the increase in actual Valley yields.

Changes in C storage by terrestrial ecosystems: How C-N interactions restrict responses to CO2 and temperature

A general model of ecosystem biogeochemistry was used to examine the responses of arctic tundra and temperate hardwood forests to a doubling of CO2 concentration and to a 5°C increase in average growing season temperature. The amount of C stored in both ecosystems increased with both increased CO2 and temperature. Under increased CO2, the increase in C storage was due to increases in the C∶N ratio of both vegetation and soils. Under increased temperature, the increased C storage in the forest was due to a shift in N from soils (with low C∶N ratios) to vegetation (with high C∶N ratios). In the tundra, both a shift in N from soils to vegetation and an increase in C∶N ratios contributed to increased C storage under higher temperatures. Neither ecosystem sequestered N from external sources because the supply rate was low.