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.

Diversity buffers winegrowing regions from climate change losses.

Agrobiodiversity-the variation within agricultural plants, animals, and practices-is often suggested as a way to mitigate the negative impacts of climate change on crops [S. A. Wood et al., Trends Ecol. Evol. 30, 531-539 (2015)]. Recently, increasing research and attention has focused on exploiting the intraspecific genetic variation within a crop [Hajjar et al., Agric. Ecosyst. Environ. 123, 261-270 (2008)], despite few relevant tests of how this diversity modifies agricultural forecasts. Here, we quantify how intraspecific diversity, via cultivars, changes global projections of growing areas. We focus on a crop that spans diverse climates, has the necessary records, and is clearly impacted by climate change: winegrapes (predominantly Vitis vinifera subspecies vinifera). We draw on long-term French records to extrapolate globally for 11 cultivars (varieties) with high diversity in a key trait for climate change adaptation-phenology. We compared scenarios where growers shift to more climatically suitable cultivars as the climate warms or do not change cultivars. We find that cultivar diversity more than halved projected losses of current winegrowing areas under a 2 °C warming scenario, decreasing areas lost from 56 to 24%. These benefits are more muted at higher warming scenarios, reducing areas lost by a third at 4 °C (85% versus 58%). Our results support the potential of in situ shifting of cultivars to adapt agriculture to climate change-including in major winegrowing regions-as long as efforts to avoid higher warming scenarios are successful.

Rethinking false spring risk.

Temperate plants are at risk of being exposed to late spring freezes. These freeze events-often called false springs-are one of the strongest factors determining temperate plants species range limits and can impose high ecological and economic damage. As climate change may alter the prevalence and severity of false springs, our ability to forecast such events has become more critical, and it has led to a growing body of research. Many false spring studies largely simplify the myriad complexities involved in assessing false spring risks and damage. While these studies have helped advance the field and may provide useful estimates at large scales, studies at the individual to community levels must integrate more complexity for accurate predictions of plant damage from late spring freezes. Here, we review current metrics of false spring, and how, when, and where plants are most at risk of freeze damage. We highlight how life stage, functional group, species differences in morphology and phenology, and regional climatic differences contribute to the damage potential of false springs. More studies aimed at understanding relationships among species tolerance and avoidance strategies, climatic regimes, and the environmental cues that underlie spring phenology would improve predictions at all biological levels. An integrated approach to assessing past and future spring freeze damage would provide novel insights into fundamental plant biology and offer more robust predictions as climate change progresses, which are essential for mitigating the adverse ecological and economic effects of false springs.

Modelling climate change impacts on viticultural yield, phenology and stress conditions in Europe.

Viticulture is a key socio-economic sector in Europe. Owing to the strong sensitivity of grapevines to atmospheric factors, climate change may represent an important challenge for this sector. This study analyses viticultural suitability, yield, phenology, and water and nitrogen stress indices in Europe, for present climates (1980-2005) and future (2041-2070) climate change scenarios (RCP4.5 and 8.5). The STICS crop model is coupled with climate, soil and terrain databases, also taking into account CO2 physiological effects, and simulations are validated against observational data sets. A clear agreement between simulated and observed phenology, leaf area index, yield and water and nitrogen stress indices, including the spatial differences throughout Europe, is shown. The projected changes highlight an extension of the climatic suitability for grapevines up to 55°N, which may represent the emergence of new winemaking regions. Despite strong regional heterogeneity, mean phenological timings (budburst, flowering, veraison and harvest) are projected to undergo significant advancements (e.g. budburst/harvest can be >1 month earlier), with implications also in the corresponding phenophase intervals. Enhanced dryness throughout Europe is also projected, with severe water stress over several regions in southern regions (e.g. southern Iberia and Italy), locally reducing yield and leaf area. Increased atmospheric CO2 partially offsets dryness effects, promoting yield and leaf area index increases in central/northern Europe. Future biomass changes may lead to modifications in nitrogen demands, with higher stress in northern/central Europe and weaker stress in southern Europe. These findings are critical decision support systems for stakeholders from the European winemaking sector.

Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

Spatially explicit estimates of N2 O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management.

With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2 O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2 O emissions at the country scale by aggregating all crops, under the assumption that N2 O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2 O emissions are relatively greater at higher N application rates. Here, we apply a super-linear emissions response model to crop-specific, spatially explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2 O emissions from croplands. We estimate 0.66 Tg of N2 O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2 O emissions range from 20% to 40% lower throughout sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak nonlinear response of N2 O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2 O emissions. As aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2 O emissions estimates.

Performance of several models for predicting budburst date of grapevine (Vitis vinifera L.).

The budburst stage is a key phenological stage for grapevine (Vitis vinifera L.), with large site and cultivar variability. The objective of the present work was to provide a reliable agro-meteorological model for simulating grapevine budburst occurrence all over France. The study was conducted using data from ten cultivars of grapevine (Cabernet Sauvignon, Chasselas, Chardonnay, Grenache, Merlot, Pinot Noir, Riesling, Sauvignon, Syrah, Ugni Blanc) and five locations (Bordeaux, Colmar, Angers, Montpellier, Epernay). First, we tested two commonly used models that do not take into account dormancy: growing degree days with a base temperature of 10 degrees C (GDD(10)), and Riou's model (RIOU). The errors of predictions of these models ranged between 9 and 21 days. Second, a new model (BRIN) was studied relying on well-known formalisms for orchard trees and taking into account the dormancy period. The BRIN model showed better performance in predicting budburst date than previous grapevine models. Analysis of the components of BRIN formalisms (calculation of dormancy, use of hourly temperatures, base temperature) explained the better performances obtained with the BRIN model. Base temperature was the main driver, while dormancy period was not significant in simulating budburst date. For each cultivar, we provide the parameter estimates that showed the best performance for both the BRIN model and the GDD model with a base temperature of 5 degrees C.