Phenology is a bio-indicator of climate evolution. Measurements of phenological stages on perennial species provide actually significant illustrations and assessments of the impact of climate change. Phenology is also one of the main key characteristics of the capacity of adaptation of perennial species, generating questions about its consequences on plant growth and development or on fruit quality. Predicting phenology evolution and adaptive capacities of perennial species needs to override three main methodological limitations: 1) existing observations and associated databases are scattered and sometimes incomplete, rendering difficult implementation of multi-site study of genotype-environment interaction analyses; 2) there are not common protocols to observe phenological stages; 3) access to generic phenological models platforms is still very limited. In this context, the PERPHECLIM project, which is funded by the Adapting Agriculture and Forestry to Climate Change Meta-Program ( ACCAF) from INRA ( French National Institute of Agronomic Research), aims to develop the necessary infrastructure at INRA level ( observatories, information system, modeling tools) to enable partners to study the phenology of various perennial species ( grapevine, fruit trees and forest trees). Currently, the PERPHECLIM project involves 28 research units in France, mainly from INRA institutes. Five activities have been developed: define protocols and observation forms to observe phenology for various species of interest for the project; organize observation training; develop generic modeling solutions to simulate phenology ( Phenological Modelling Platform software and modelling platform solutions); support the building of research projects at national and international levels; develop environment/genotype observation networks for fruit-tree species; and develop an information system to manage data and documentation concerning phenology. Finally, the PERPHECLIM project aims to build strong collaborations with public ( Observatoire des Saisons) and private ( technical institutes) sector partners in order to allow a more direct transfer of knowledge.

Tree species distribution, and hence forest biodiversity, relies on the reproductive capacity of trees, which is currently affected by climate change. Drought-induced pollen sterility could increase as a consequence of more intense and more frequent droughts projected for temperate and Mediterranean regions, and threaten the sexual regeneration of trees in these regions. To evaluate this possibility, we examined the effect of long-term partial rainfall exclusion (-27% precipitation) on male reproductive development in holm oak, Quercus ilex, one of the most important and widespread tree species of the Mediterranean region. We examined anther area, pollen production, pollen abortion as well as viable pollen production in control and dry treatments. Microscopic examinations revealed significant differences in pollen development between trees in the dry and the control treatments, even though anthesis occurred before the onset of annual drought. Our results demonstrate that anthers collected from Q. ilex trees in the dry treatment, which experienced long-term increased drought stress especially during the summer, were the same size as anthers in the control treatment, but displayed 25% pollen abortion and almost 20% reduction in pollen production. Subsequently, the number of viable pollen grains in anthers from dry treatment was 35% less than in control. These results suggest a carry-over effect of drought stress on pollen production that could reduce the reproductive success of Q. ilex. The results have broad implications for better understanding of the determinants of tree reproduction by masting and anticipate the outcomes of expected drought increase in the Mediterranean on forest dynamics.

Modeling studies predict that global warming might severely affect bud dormancy release. However, growing empirical evidences suggest that long photoperiod might compensate for a lack of chilling temperature in photosensitive species. For now, attempts to integrate this effect into models remain limited. Here, we used French budburst phenological records for two main European temperate tree species, Fagus sylvatica (n = 136) and Quercus petraea (n = 276), to compare four phenological models accounting for a photoperiod effect, two of them proposing a new formalism of the effect of photoperiod, and three classical thermal models. We also investigated the effect of a realistic photoperiod cue on budburst dates in future climatic conditions. Consistently with the empirical literature, we find that models integrating a photoperiod cue were more relevant to simulate budburst dates for beech than for oak. However, contrary to the recently debated expectation that photoperiod might mitigate the trend towards earlier budburst date, we find that the compensatory effect of photoperiod on a lack of chilling maintains a trend towards earlier dates up to the end of the 2100. Our results also suggest that phenological rank changes between photosensitive and photo-insensitive species may be more pronounced at cold than warm trailing edge.

We present an open-access dataset of grape harvest dates (GHD) series that has been compiled from international, French and Spanish literature and from unpublished documentary sources from public organizations and from wine-growers. As of June 2011, this GHD dataset comprises 380 series mainly from France (93% of the data) as well as series from Switzerland, Italy, Spain and Luxemburg. The series have variable length (from 1 to 479 data, mean length of 45 data) and contain gaps of variable sizes (mean ratio of observations/series length of 0.74). The longest and most complete ones are from Burgundy, Switzerland, Southern Rhône valley, Jura and Ile-de-France. The most ancient harvest date of the dataset is in 1354 in Burgundy. The GHD series were grouped into 27 regions according to their location, to geomorphological and geological criteria, and to past and present grape varieties. The GHD regional composite series (GHD-RCS) were calculated and compared pairwise to assess their reliability assuming that series close to one another are highly correlated. Most of the pairwise correlations are significant (p-value < 0.001) and strong (mean pairwise correlation coefficient of 0.58). As expected, the correlations tend to be higher when the vineyards are closer. The highest correlation (R = 0.91) is obtained between the High Loire Valley and the Ile-de-France GHD-RCS. The strong dependence of the vine cycle on temperature and, therefore, the strong link between the harvest dates and the temperature of the growing season was also used to test the quality of the GHD series. The strongest correlations are obtained between the GHD-RCS and the temperature series of the nearest weather stations. Moreover, the GHD-RCS/temperature correlation maps show spatial patterns similar to temperature correlation maps. The stability of the correlations over time is explored. The most striking feature is their generalised deterioration at the late 19th–early 20th century. The possible effects on GHD of the phylloxera crisis, which took place at this time, are discussed. The median of all the standardized GHD-RCS was calculated. The distribution of the extreme years of this general series is not homogenous. Extremely late years all occur during a two-century long time window from the early 17th to the early 19th century, while extremely early years are frequent during the 16th and since the mid-19th century.

Background and Aims: Phenological models, which are based on responses of the plant to temperature, are useful tools to predict grapevine ( Vitis vinifera L.) phenology in various climate conditions. This study aimed to develop a single process-based phenological model at the species level to predict two important stages of development for V. vinifera L.: flowering and veraison. Methods and Results: Three different phenological models were tested and the model that gave the best results was optimised for its parameters. The chosen model Spring Warming was found optimal with regard to the trade-off between parsimony of input parameters and efficiency. The base temperature ( Tb ) of 0°C calculated from the 60th day ( t 0 ) of the year (for the Northern hemisphere) was found to be the most optimal parameter set tested. This model henceforth referred to as the Grapevine Flowering Veraison model (GFV) was successfully validated at the varietal level using an independent dataset. Conclusions: A general phenological model, GFV, has been successfully developed to characterise the timing of flowering and veraison for the grapevine. Significance of the Study: The model is simple for the user, can be successfully applied to many varieties and can be used as an easy predictor of phenology for different varieties under climate change scenarios.

Several studies have used grape harvest date (GHD) as a proxy for temperature variations of the last centuries in Europe. However, the use of grape harvest dates to reconstruct climate is not straightforward, with four possible causes of major flaws. In this study we identify and evaluate the accuracy of GHD as a proxy to past temperature anomalies, uncertainties in the model used to relate temperature to GHD, identity of the grape varieties cultivated in the past, type of wine produced in the past and cultural practices used in the past. Our analyses are based on several phenological and crop models, and on the most complete data set on grape vine phenology and harvest quality. We show that the two methodologies currently used - linear regression models and process-based phenological models - can be accurate, but process-based phenological models ascertain robustness to be applied confidently in different vineyards and different periods. However, we show that several factors can induce a bias in temperature reconstructions using process-based models. We demonstrate the importance of historical information on the studied areas such as the varieties cultivated, the style of wine produced, the quality sought, the agricultural practices, in order to build the most robust model.

C. Korner and D. Basler (“Phenology under global warming,” Perspectives, 19 March, p. [1461][1]) suggest that because of photoperiodic constraints, observed effects of temperature on spring life-cycle events cannot be extrapolated to future temperature conditions.However, no study has

Estimates of climate conditions before the 19th century are based on proxy data reconstructions or sparse meteorological measurements. The reconstruction of the atmospheric circulation that prevailed during the European Little Ice Age (∼1500–1850) has fostered many efforts. This study illustrates a methodology, combining historical proxies and modern datasets to obtain detailed information on the atmospheric circulation that prevailed over the North Atlantic region during the Little Ice Age. We used reconstructions of temperature gradients over France based on grape harvest dates to infer the atmospheric circulation. We found that blocking situations were more likely in summer, inducing a continental atmospheric flow. This study advocates that the reconstructions of the past atmospheric circulation should take this regime into account.

The present study examines variations in the timing of flowering between populations of Iberian Poaceae species using pollen data from 12 sites in Spain. The spatial variation in pollen season start-date for any given year was around 1 month; year-on-year differences at any given site ranged around 1.5 months. The spatial variation in the pollen season peak-date was smaller, at around 15 days, while the year-on-year variation for the peak-date at a given site was never greater than 20 days.Two process-based models were developed, one to predict the start-date and the other the peak-date of the grass pollen season. These models take into account the effects of temperature, photoperiod and water availability on the timing of grass flowering in Spain. Apart from predicting the pollen-season start and peak dates, the models provide information on (i) the Poaceae response to weather-related factors, (ii) the period during which these factors affect grass growth, and (iii) the relationship between photoperiod, temperature and water availability for flowering grasses.Internal validation showed that the models accounted for 45% of the variance in start-date and 68% of the variance in peak-date. External validation was performed for 2006 and 2007 at all sites: the root mean square error for the actual and predicted dates was around 4 days for the start-date and 6 for the peak-date. Analysis of the model estimates showed that a single model parameter set for all Spain, taking into account different bioclimatic factors, could be sufficient to account for the variability of the Poaceae pollen season across space and time. (C) 2008 Elsevier B.V. All rights reserved.

Phenomenological approaches to model species migration are usually based on kernel-based methods. These methods require a good knowledge of the dispersal agent behaviour for a given species. They also calculate the location of individuals independently to each other (except the mother plant) and then suppress some of them according to additional interactions such as competition, facilitation and recruitment. In this paper, we propose to use a new phenomenological method, the Gibbs method, to model tree species migration at large scale. The Gibbs method handles the location of adult individuals in terms of pairwise interactions described by a potential function. This function summarizes the set of known and unknown factors determining the spatial distribution of the individuals (or cohorts). The principle of the Gibbs method is to minimize the sum of all pairwise interactions, also called the cost function, in order to optimize the spatial point pattern according to the chosen potential function.We compared dispersal models based on the non-homogeneous Gibbs method to several models based on kernel methods, and in detail with a leptokurtic kernel-based model. An elasticity test of the Gibbs-based dispersal model showed a strong dependence among the parameters and the key role of the potential of interaction in the dispersion obtained. We found important differences in the resulting patterns of migration between Gibbs-based and kernel-based models: Gibbs-based model generated more random point patterns, leading to more diversified migration pathways than kernel-based model. Finally, a semi-realistic application to paleo-landscapes showed that the Gibbs-based model was able to simulate the migration pathways of Fagus sylvatica during the Holocene more realistically than kernel-based models. (C) 2009 Elsevier B.V. All rights reserved.

Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.

The study sought to achieve the broadest possible spatial and temporal predictions by examining genetic variations in the timing of flowering between populations of the Iberian Quercus species using pollen data from 15 sites in Spain. The specific objective of the study was to develop and fit regional phenological model to predict the flowering start and flowering peak of Quercus species in the Iberian Peninsula by ascertaining whether potentially significant genetic variations in the timing of flowering required different phenological models or if, on the contrary, regional models for several localities can explain the variability detected in Quercus phenology in Spain. Model estimates did not vary greatly as a function of environment within similar climate areas where the same species grew; thus, model estimates of the temperature response of individuals growing in similar climate areas did not differ significantly. The percentage of variance explained by models was greater in models fitted with local data (75–97%). Nevertheless, acceptable results were also obtained using regional models (55–85%). The lowest value was found for the Simplifed Model including all Spanish sites together (51%).

Understanding the mechanisms causing latitudinal gradients in species richness and species range size is a central issue in ecology, particularly in the current context of global climate change. Different hypotheses have been put forward to explain these patterns, emphasizing climatic variability, energy availability and competition. Here we show, using a comparative analysis controlling for phylogeny on 234 temperate/boreal tree species, that these hypotheses can be included into a single framework in an attempt to explain latitudinal gradients in species range size. We find that species tend to have larger ranges when (i) closer to the poles, (ii) successionally seral, (iii) having small and light seeds, and (iv) having short generations. The patterns can simply be explained by energy constraints associated with different life-history strategies. Overall, these findings shed a new light on our understanding of species distribution and biodiversity patterns, bringing new insights into underlying large-scale evolutionary processes.

Species distributions are already affected by climate change. Forecasting their long-term evolution requires models with thoroughly assessed validation. Our aim here is to demonstrate that the sensitivity of such models to climate input characteristics may complicate their validation and introduce uncertainties in their predictions. In this study, we conducted a sensitivity analysis of a process-based tree distribution model PHENOFIT to climate input characteristics. This analysis was conducted for two North American trees which differ greatly in their distribution and eight different types of climate input for the historic period which differ in their spatial (local or gridded data) and temporal (daily vs. monthly) resolution as well as their type (locally recorded, extrapolated or simulated by General Circulation Models). We show that the climate data resolution (spatial and temporal) and their type, highly affect the model predictions. The sensitivity analysis also revealed, the importance, for global climate change impact assessment, of (i) the daily variability of temperatures in modeling the biological processes shaping species distribution, (ii) climate data at high latitudes and elevations and (iii) climate data with high spatial resolution.

French records of grape-harvest dates in Burgundy were used to reconstruct spring-summer temperatures from 1370 to 2003 using a process-based phenology model developed for the Pinot Noir grape. Our results reveal that temperatures as high as those reached in the 1990s have occurred several times in Burgundy since 1370. However, the summer of 2003 appears to have been extraordinary, with temperatures that were probably higher than in any other year since 1370.

Since the beginning of aeropalynology, aerobiologists have tried to develop models able to predict the pollen load of the atmosphere to help physicians and patients suffering pollen allergies to improve the efficiency of pollen allergies prophylaxis. Some models have been developed by aerobiological services and are used for real time predictions, now provided online. They are statistical models and require the pollen load of the previous days as input, as well as statistics on the pollen load of the previous years, daily meteorological data and geographic information on the pollen sources. Here we propose to use process-based phenological models to predict the time course of the pollen load of the atmosphere using solely daily mean temperatures as input. The model proposed has been fitted and validated for 13 major allergenic taxa (Alnus, Artemisia, Betula, Castanea, Corylus, Cupressaceae, Olea, Plantago, Platanus, Populus, Poaceae, Quercus and Tilia) in different areas of France and Spain. The model has been integrated into a freeware called PPF (Positive Pollen Forecast), which will be made available from the 5th Framework EU project POSITIVE web page at: http://www.forst.tu-muenchen.de/LST/METEOR/positive/.

Global warming is expected to have a major impact on plant distributions, an issue of key importance in biological conservation. However, very few models are able to predict species distribution accurately, although we know species respond individually to climate change. Here we show, using a process‐based model (PHENOFIT), that tree species distributions can be predicted precisely if the biological processes of survival and reproductive success only are incorporated as a function of phenology. These predictions showed great predictive power when tested against present distributions of two North American species – quaking aspen and sugar maple – indicating that on a broad scale, the fundamental niche of trees coincides with their realized niche. Phenology is shown here to be a major determinant of plant species range and should therefore be used to assess the consequences of global warming on plant distributions, and the spread of alien plant species.

Accurate plant phenology (seasonal plant activity driven by environmental factors) models are vital tools for ecosystem simulation models and for predicting the response of ecosystems to climate change. Since the early 1970s, efforts have concentrated on predicting phenology of the temperate and boreal forests because they represent one-third of the carbon captured in plant ecosystems and they are the principal ecosystems with seasonal patterns of growth on Earth (one-fifth of the plant ecosystems area). Numerous phenological models have been developed to predict the growth timing of temperate or boreal trees. They are in general empirical, nonlinear and non-nested. For these reasons they are particularly difficult to fit, to test and to compare with each other. The methodological difficulties as well as the diversity of models used have greatly slowed down their improvement. The aim of this study was to show that the most widely used models simulating vegetative or reproductive phenology of trees are particular cases of a more general model. This unified model has three main advantages. First, it allows for a direct estimation of (i) the response of bud growth to either chilling or forcing temperatures and (ii) the periods when these temperatures affect the bud growth. Second, it can be simplified according to standard statistical tests for any particular species. Third, it provides a standardized framework for phenological models, which is essential for comparative studies as well as for robust model identification.

Summary 1 The phenology of temperate woody plants is commonly assumed to be locally adapted to climate. 2 However, the high gene flow expected in forest tree species, the high between year variance of thermal conditions at a given place and the high plasticity of phenology regarding temperature, lead us to hypothesize that genetic variation of phenology between populations is likely to be insignificant for many lowland tree species. 3 Using phenological models, we investigated variation in the timing of flowering between locations for four European clonal trees and between different populations of a further five species. 4 Models were also used to study the responses of the different populations to climate change by simulating transfers of each population to different locations. 5 While clinal variations can be observed in the phenological response to temperature between populations, only one species (Corylus avellana) showed significantly different responses between populations and even then only one of three populations could be separated from the others. 6 Hypothetical transfers show that the differences observed between populations depend on the thermal conditions at the location of transfer, and that these differences are less marked in warmer conditions. 7 Our results indicate that local adaptation will probably not be a serious constraint in predicting the phenological responses of temperate lowland tree species to global warming.