Future scenarios for viticultural zoning in Europe: ensemble projections and uncertainties

Optimum climate conditions for grapevine growth are limited geographically and may be further challenged by a changing climate. Due to the importance of the winemaking sector in Europe, the assessment of future scenarios for European viticulture is of foremost relevance. A 16-member ensemble of model transient experiments (generated by the ENSEMBLES project) under a greenhouse gas emission scenario and for two future periods (2011–2040 and 2041–2070) is used in assessing climate change projections for six viticultural zoning indices. After model data calibration/validation using an observational gridded daily dataset, changes in their ensemble means and inter-annual variability are discussed, also taking into account the model uncertainties. Over southern Europe, the projected warming combined with severe dryness in the growing season is expected to have detrimental impacts on the grapevine development and wine quality, requiring measures to cope with heat and water stress. Furthermore, the expected warming and the maintenance of moderately wet growing seasons over most of the central European winemaking regions may require a selection of new grapevine varieties, as well as an enhancement of pest/disease control. New winemaking regions may arise over northern Europe and high altitude areas, when considering climatic factors only. An enhanced inter-annual variability is also projected over most of Europe. All these future changes pose new challenges for the European winemaking sector.     

Non-linear loss of suitable wine regions over Europe in response to increasing global warming

Evaluating the potential climatic suitability for premium wine production is crucial for adaptation planning in Europe. While new wine regions may emerge out of the traditional boundaries, most of the present-day renowned winemaking regions may be threatened by climate change. Here, we analyse the future evolution of the geography of wine production over Europe, through the definition of a novel climatic suitability indicator, which is calculated over the projected grapevine phenological phases to account for their possible contractions under global warming. Our approach consists in coupling six different de-biased downscaled climate projections under two different scenarios of global warming with four phenological models for different grapevine varieties. The resulting suitability indicator is based on fuzzy logic and is calculated over three main components measuring (i) the timing of the fruit physiological maturity, (ii) the risk of water stress and (iii) the risk of pests and diseases. The results demonstrate that the level of global warming largely determines the distribution of future wine regions. For a global temperature increase limited to 2°C above the pre-industrial level, the suitable areas over the traditional regions are reduced by about 4%/°C rise, while for higher levels of global warming, the rate of this loss increases up to 17%/°C. This is compensated by a gradual emergence of new wine regions out of the traditional boundaries. Moreover, we show that reallocating better-suited grapevine varieties to warmer conditions may be a viable adaptation measure to cope with the projected suitability loss over the traditional regions. However, the effectiveness of this strategy appears to decrease as the level of global warming increases. Overall, these findings suggest the existence of a safe limit below 2°C of global warming for the European winemaking sector, while adaptation might become far more challenging beyond this threshold.     

The implication of irrigation in climate change impact assessment: a European‐wide study

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO₂ effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982–2006) and three SRES scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process‐based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr^?1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO₂ effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO₂ effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.     

Response of the <Emphasis Type="Italic">Morus bombycis</Emphasis> growing season to temperature and its latitudinal pattern in Japan

Changes in leaf phenology lengthen the growing season length (GSL, the days between leaf budburst and leaf fall) under the global warming. GSL and the leaf phenology response to climate change is one of the most important predictors of climate change effect on plants. Empirical evidence of climatic effects on GSL remains scarce, especially at a regional scale and the latitudinal pattern. This study analyzed the datasets of leaf budburst and fall phenology in Morus bombycis (Urticales), which were observed by the agency of the Japan Meteorological Agency (JMA) from 1953 to 2005 over a wide range of latitudes in Japan (31 to 44° N). In the present study, single regression slopes of leaf phenological timing and air temperature across Japan were calculated and their spatial patterns using general linear models were tested. The results showed that the GSL extension was caused mainly by a delay in leaf fall phenology. Relationships between latitude and leaf phenological and GSL responses against air temperature were significantly negative. The response of leaf phenology and GSL to air temperature at lower latitudes was larger than that at higher latitudes. The findings indicate that GSL extension should be considered with regards to latitude and climate change.     

Trends and uncertainties in budburst projections of Norway spruce in Northern Europe

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051–2080 than in 1971–2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.     

Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi‐year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO₂ concentration [CO₂]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model‐based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well‐controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO₂] and temperature.     

Climate change impacts and adaptive strategies: lessons from the grapevine

The cultivation of grapevines for winemaking, known as viticulture, is widely cited as a climate‐sensitive agricultural system that has been used as an indicator of both historic and contemporary climate change. Numerous studies have questioned the viability of major viticulture regions under future climate projections. We review the methods used to study the impacts of climate change on viticulture in the light of what is known about the effects of climate and weather on the yields and quality of vineyard harvests. Many potential impacts of climate change on viticulture, particularly those associated with a change in climate variability or seasonal weather patterns, are rarely captured. Key biophysical characteristics of viticulture are often unaccounted for, including the variability of grapevine phenology and the exploitation of microclimatic niches that permit successful cultivation under suboptimal macroclimatic conditions. We consider how these same biophysical characteristics permit a variety of strategies by which viticulture can adapt to changing climatic conditions. The ability to realize these strategies, however, is affected by uneven exposure to risks across the winemaking sector, and the evolving capacity for decision‐making within and across organizational boundaries. The role grape provenance plays in shaping perceptions of wine value and quality illustrates how conflicts of interest influence decisions about adaptive strategies within the industry. We conclude by considering what lessons can be taken from viticulture for studies of climate change impacts and the capacity for adaptation in other agricultural and natural systems.     

GLOBE students, teachers, and scientists demonstrate variable differences between urban and rural leaf phenology

The urban heat island effect, classically associated with high impervious surface area (ISA), low vegetation fractional cover (Fr), and high land surface temperature (LST), has been linked to changing patterns of vegetation phenology, especially spring growth. In this study, a collaboration with the Global Learning and Observations to Benefit the Environment (GLOBE) program, we investigated the effect of the urban environment on the timing of leaf budburst of native deciduous trees in seven cities: Asia (Tokyo, Japan; Bangkok and Korat, Thailand), Europe (Jyväskylä, Finland; Bishkek, Kyrgyzstan), Africa (Dakar, Senegal), and North America (Fairbanks, Alaska). The cities differed not only in population size but also in climate and vegetation type. Using Landsat satellite imagery from each city, we calculated LST, Fr, and ISA, and classified sites within each study area as rural or urban. The timing of leaf flushing, measured by students using GLOBE budburst protocols, was statistically different within all cities, with absolute differences ranging from 1 to 23 days. We assessed the classic urban phenology paradigm, which proposes higher LST, lower Fr, and earlier budburst in urban areas of temperate cities. Of the four temperate cities, Tokyo followed the classic paradigm, but no other city demonstrated consistent support. Urban budburst was advanced in three of the four temperate cities, but in only one of the three tropical cities. Results suggest that while vegetation phenology is consistently different between urban and rural areas, a uniform paradigm based on the explanatory variables in this study did not emerge. Although not testable here, it is likely that alterations to chilling requirements in temperate climates and humidity in tropical climates may also influence observed budburst differences.     

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO₂ may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.     

The global distribution of cultivable lands: current patterns and sensitivity to possible climate change

Aim This study makes quantitative global estimates of land suitability for cultivation based on climate and soil constraints. It evaluates further the sensitivity of croplands to any possible changes in climate and atmospheric CO₂ concentrations. Location The location is global, geographically explicit. Methods The methods used are spatial data synthesis and analysis and numerical modelling. Results There is a cropland ‘reserve’ of 120%, mainly in tropical South America and Africa. Our climate sensitivity analysis indicates that the southern provinces of Canada, north‐western and north‐central states of the United States, northern Europe, southern Former Soviet Union and the Manchurian plains of China are most sensitive to changes in temperature. The Great Plains region of the United States and north‐eastern China are most sensitive to changes in precipitation. The regions that are sensitive to precipitation change are also sensitive to changes in CO₂, but the magnitude is small compared to the influence of direct climate change. We estimate that climate change, as simulated by global climate models, will expand cropland suitability by an additional 16%, mainly in the Northern Hemisphere high latitudes. However, the tropics (mainly Africa, northern South America, Mexico and Central America and Oceania) will experience a small decrease in suitability due to climate change. Main conclusions There is a large reserve of cultivable croplands, mainly in tropical South America and Africa. However, much of this land is under valuable forests or in protected areas. Furthermore, the tropical soils could potentially lose fertility very rapidly once the forest cover is removed. Regions that lie at the margins of temperature or precipitation limitation to cultivation are most sensitive to changes in climate and atmospheric CO₂ concentration. It is anticipated that climate change will result in an increase in cropland suitability in the Northern Hemisphere high latitudes (mainly in developed nations), while the tropics will lose suitability (mainly in developing nations).     

Challenging terrestrial biosphere models with data from the long‐term multifactor Prairie Heating and CO2 Enrichment experiment

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single‐factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO₂ Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above‐ground net primary productivity (range: 31–390 g C m^?2 yr^?1). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single‐factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO₂‐induced water savings to extend the growing season length. Observed interactive (CO₂ × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single‐factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.     

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf‐out times across groupings of species in a dynamic vegetation model

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf‐out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf‐out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970–2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf‐out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf‐out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.     

Climate change and maize yield in southern Africa: what can farm management do?

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options – planting date, fertilizer use and cultivar choice – using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near‐ and long‐term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid‐December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010–2039 and 2040–2069 and by 20% for 2070–2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070–2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change.     

Climate‐driven changes to the spatio‐temporal distribution of the parasitic nematode,Haemonchus contortus,in sheep in Europe

Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio‐temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q₀, adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan‐European spatio‐temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q₀ simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within‐host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q₀ simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2–3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations.     

Long-term effects of CO2 enrichment and temperature increase on a temperate grass sward

Perennial ryegrass swards were grown in large containers on a soil and were exposed during two years to elevated (700 L L^-1) or ambient atmospheric CO₂ concentration at outdoor temperature and to a 3 °C increase in air temperature in elevated CO₂. The nitrogen nutrition of the grass sward was studied at two sub-optimal (160 and 530 kg N ha^-1 y^-1) and one non-limiting (1000 kg N ha^-1 y^-1) N fertilizer supplies. At cutting date, elevated CO₂ reduced by 25 to 33%, on average, the leaf N concentration per unit mass. Due to an increase in the leaf blade weight per unit area in elevated CO₂, this decline did not translate for all cuts in a lower N concentration per unit leaf blade area. With the non-limiting N fertilizer supply, the leaf N concentration (% N) declined with the shoot dry-matter (DM) according to highly significant power models in ambient (% N=4.9 DM^-0.38) and in elevated (%N=5.3 DM^-0.52) CO₂. The difference between both regressions was significant and indicated a lower critical leaf N concentration in elevated than in ambient CO₂ for high, but not for low values of shoot biomass. With the sub-optimal N fertilizer supplies, the nitrogen nutrition index of the grass sward, calculated as the ratio of the actual to the critical leaf N concentration, was significantly lowered in elevated CO₂. This indicated a lower inorganic N availability for the grass plants in elevated CO₂, which was also apparent from the significant declines in the annual nitrogen yield of the grass sward and in the nitrate leaching during winter. For most cuts, the harvested fraction of the plant dry-matter decreased in elevated CO₂ due, on average, to a 45–52% increase in the root phytomass. In the same way, a smaller share of the plant total nitrogen was harvested by cutting, due, on average, to a 25–41% increase in the N content of roots. The annual means of the DM and N harvest indices were highly correlated to the annual means of the nitrogen nutrition index. Changes in the harvest index and in the nitrogen nutrition index between ambient and elevated CO₂ were also positively correlated. The possible implication of changes in the soil introgen cycle and of a limitation in the shoot growth potential of the grass in elevated. CO₂ is discussed.Abbreviations 350 outdoor climate - 700 outdoor climate +350 L L^-1[CO₂] - 700+ outdoor climate +350 L L^-1 (CO₂) and +3 °C - N-- low N fertilizer supply - N+ high N fertilizer supply - N++ non-limiting N fertilizer supply - DM dry-matter     

Interactive effects of nitrate concentrations and carbon dioxide on the stoichiometry,biomass allocation and growth rate of submerged aquatic plants

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The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models

Autumn senescence regulates multiple aspects of ecosystem function, along with associated feedbacks to the climate system. Despite its importance, current understanding of the drivers of senescence is limited, leading to a large spread in predictions of how the timing of senescence, and thus the length of the growing season, will change under future climate conditions. The most commonly held paradigm is that temperature and photoperiod are the primary controls, which suggests a future extension of the autumnal growing season as global temperatures rise. Here, using two decades of ground‐ and satellite‐based observations of temperate deciduous forest phenology, we show that the timing of autumn senescence is correlated with the timing of spring budburst across the entire eastern United States. On a year‐to‐year basis, an earlier/later spring was associated with an earlier/later autumn senescence, both for individual species and at a regional scale. We use the observed relationship to develop a novel model of autumn phenology. In contrast to current phenology models, this model predicts that the potential response of autumn phenology to future climate change is strongly limited by the impact of climate change on spring phenology. Current models of autumn phenology therefore may overpredict future increases in the length of the growing season, with subsequent impacts for modeling future CO₂ uptake and evapotranspiration.     

Temperature alone does not explain phenological variation of diverse temperate plants under experimental warming

Anthropogenic climate change has altered temperate forest phenology, but how these trends will play out in the future is controversial. We measured the effect of experimental warming of 0.6–5.0 °C on the phenology of a diverse suite of 11 plant species in the deciduous forest understory (Duke Forest, North Carolina, USA) in a relatively warm year (2011) and a colder year (2013). Our primary goal was to dissect how temperature affects timing of spring budburst, flowering, and autumn leaf coloring for functional groups with different growth habits, phenological niches, and xylem anatomy. Warming advanced budburst of six deciduous woody species by 5–15 days and delayed leaf coloring by 18–21 days, resulting in an extension of the growing season by as much as 20–29 days. Spring temperature accumulation was strongly correlated with budburst date, but temperature alone cannot explain the diverse budburst responses observed among plant functional types. Ring‐porous trees showed a consistent temperature response pattern across years, suggesting these species are sensitive to photoperiod. Conversely, diffuse‐porous species responded differently between years, suggesting winter chilling may be more important in regulating budburst. Budburst of the ring‐porous Quercus alba responded nonlinearly to warming, suggesting evolutionary constraints may limit changes in phenology, and therefore productivity, in the future. Warming caused a divergence in flowering times among species in the forest community, resulting in a longer flowering season by 10‐16 days. Temperature was a good predictor of flowering for only four of the seven species studied here. Observations of interannual temperature variability overpredicted flowering responses in spring‐blooming species, relative to our warming experiment, and did not consistently predict even the direction of flowering shifts. Experiments that push temperatures beyond historic variation are indispensable for improving predictions of future changes in phenology.     

Leaf phenology in 22 North American tree species during the 21st century

Recent shifts in phenology are the best documented biological response to current anthropogenic climate change, yet remain poorly understood from a functional point of view. Prevailing analyses are phenomenological and approximate, only correlating temperature records to imprecise records of phenological events. To advance our understanding of phenological responses to climate change, we developed, calibrated, and validated process-based models of leaf unfolding for 22 North American tree species. Using daily meteorological data predicted by two scenarios (A2: +3.2 °C and B2: +1 °C) from the HadCM3 GCM, we predicted and compared range-wide shifts of leaf unfolding in the 20th and 21st centuries for each species. Model predictions suggest that climate change will affect leaf phenology in almost all species studied, with an average advancement during the 21st century of 5.0 days in the A2 scenario and 9.2 days in the B2 scenario. Our model also suggests that lack of sufficient chilling temperatures to break bud dormancy will decrease the rate of advancement in leaf unfolding date during the 21st century for many species. Some temperate species may even have years with abnormal budburst due to insufficient chilling. Species fell into two groups based on their sensitivity to climate change: (1) species that consistently had a greater advance in their leaf unfolding date with increasing latitude and (2) species in which the advance in leaf unfolding differed from the center to the northern vs. southern margins of their range. At the interspecific level, we predicted that early-leafing species tended to show a greater advance in leaf unfolding date than late-leafing species; and that species with larger ranges tend to show stronger phenological changes. These predicted changes in phenology have significant implications for the frost susceptibility of species, their interspecific relationships, and their distributional shifts.     

Lower incidence and severity of tomato virus in elevated CO2 is accompanied by modulated plant induced defence in tomato

Elevation in atmospheric CO₂ concentration broadly affects plant phenology and physiology, and these effects may alter the performance of plant viruses. The effects of elevated CO₂ on the susceptibility of tomato plants to Tomato yellow leaf curl virus (TYLCV) were examined for two successive years in open top chambers (OTC) in the field. We experimentally tested the hypothesis that elevated CO₂ would reduce the incidence and severity of TYLCV on tomato by altering plant defence strategies. Our results showed that elevated CO₂ decreased TYLCV disease incidence (by 14.6% in 2009 and 11.8% in 2010) and decreased disease severity (by 20.0% in 2009 and 10.4% in 2010). Elevated CO₂ also decreased the level of TYLCV coat protein in tomato leaves. Regardless of virus infection, elevated CO₂ increased plant height and aboveground biomass. Additionally, elevated CO₂ increased the leaf C:N ratio of tomato, but decreased soluble protein content in leaves. Notably, elevated CO₂ increased the salicylic acid (SA) level in uninfected and infected plants. In contrast, elevated CO₂ reduced jasmonic acid (JA) in uninfected plants while it increased JA and abscisic acid (ABA) in virus‐infected plants. Furthermore, combined exogenous SA and JA application enhanced resistance to TYLCV more than application of either SA or JA alone. Our results suggest that the modulated antagonistic relationship between SA and JA under elevated CO₂ makes a great contribution to increased tomato resistance to TYLCV, and the predicted increases in tomato productivity may be enhanced by reduced plant virus susceptibility under projected rising CO₂ conditions.