Mapping the race between crop phenology and climate risks for wheat in France under climate change.

Climate change threatens food security by affecting the productivity of major cereal crops. To date, agroclimatic risk projections through indicators have focused on expected hazards exposure during the crop's current vulnerable seasons, without considering the non-stationarity of their phenology under evolving climatic conditions. We propose a new method for spatially classifying agroclimatic risks for wheat, combining high-resolution climatic data with a wheat's phenological model. The method is implemented for French wheat involving three GCM-RCM model pairs and two emission scenarios. We found that the precocity of phenological stages allows wheat to avoid periods of water deficit in the near future. Nevertheless, in the coming decades the emergence of heat stress and increasing water deficit will deteriorate wheat cultivation over the French territory. Projections show the appearance of combined risks of heat and water deficit up to 4 years per decade under the RCP 8.5 scenario. The proposed method provides a deep level of information that enables regional adaptation strategies: the nature of the risk, its temporal and spatial occurrence, and its potential combination with other risks. It's a first step towards identifying potential sites for breeding crop varieties to increase the resilience of agricultural systems.

Monitoring the phenology of plant pathogenic fungi: why and how?

Phenology is a key adaptive trait of organisms, shaping biotic interactions in response to the environment. It has emerged as a critical topic with implications for societal and economic concerns due to the effects of climate change on species' phenological patterns. Fungi play essential roles in ecosystems, and plant pathogenic fungi have significant impacts on global food security. However, the phenology of plant pathogenic fungi, which form a huge and diverse clade of organisms, has received limited attention in the literature. This diversity may have limited the use of a common language for comparisons and the integration of phenological data for these taxonomic groups. Here, we delve into the concept of 'phenology' as applied to plant pathogenic fungi and explore the potential drivers of their phenology, including environmental factors and the host plant. We present the PhenoFun scale, a phenological scoring system suitable for use with all fungi and fungus-like plant pathogens. It offers a standardised and common tool for scientists studying the presence, absence, or predominance of a particular phase, the speed of phenological phase succession, and the synchronism shift between pathogenic fungi and their host plants, across a wide range of environments and ecosystems. The application of the concept of 'phenology' to plant pathogenic fungi and the use of a phenological scoring system involves focusing on the interacting processes between the pathogenic fungi, their hosts, and their biological, physical, and chemical environment, occurring during the life cycle of the pathogen. The goal is to deconstruct the processes involved according to a pattern orchestrated by the fungus's phenology. Such an approach will improve our understanding of the ecology and evolution of such organisms, help to understand and anticipate plant disease epidemics and their future evolution, and make it possible to optimise management models, and to encourage the adoption of cropping practices designed from this phenological perspective.

IPSIM-Web, An Online Resource for Promoting Qualitative Aggregative Hierarchical Network Models to Predict Plant Disease Risk: Application to Brown Rust on Wheat.

A qualitative pest modeling platform, named Injury Profile Simulator (IPSIM), provides a tool to design aggregative hierarchical network models to predict the risk of pest injuries, including diseases, on a given crop based on variables related to cropping practices as well as soil and weather environment at the field level. The IPSIM platform enables modelers to combine data from various sources (literature, survey, experiments, and so on), expert knowledge, and simulation to build a network-based model. The overall structure of the platform is fully described at the IPSIM-Web website ( www6.inra.fr/ipsim ). A new module called IPSIM-Wheat-brown rust is reported in this article as an example of how to use the system to build and test the predictive quality of a prediction model. Model performance was evaluated for a dataset comprising 1,788 disease observations at 13 French cereal-growing regions over 15 years. Accuracy of the predictions was 85% and the agreement with actual values was 0.66 based on Cohen's κ. The new model provides risk information for farmers and agronomists to make scientifically sound tactical (within-season) decisions. In addition, the model may be of use for ex post diagnoses of diseases in commercial fields. The limitations of the model such as low precision and threshold effects as well as the benefits, including the integration of different sources of information, transparency, flexibility, and a user-friendly interface, are discussed.

Modelling fungal sink competitiveness with grains for assimilates in wheat infected by a biotrophic pathogen.

BACKGROUND AND AIMS: Experiments have shown that biotrophic fungi divert assimilates for their growth. However, no attempt has been made either to account for this additional sink or to predict to what extent it competes with both grain filling and plant reserve metabolism for carbon. Fungal sink competitiveness with grains was quantified by a mixed experimental-modelling approach based on winter wheat infected by Puccinia triticina. METHODS: One week after anthesis, plants grown under controlled conditions were inoculated with varying loads. Sporulation was recorded while plants underwent varying degrees of shading, ensuring a range of both fungal sink and host source levels. Inoculation load significantly increased both sporulating area and rate. Shading significantly affected net assimilation, reserve mobilization and sporulating area, but not grain filling or sporulation rates. An existing carbon partitioning (source-sink) model for wheat during the grain filling period was then enhanced, in which two parameters characterize every sink: carriage capacity and substrate affinity. Fungal sink competitiveness with host sources and sinks was modelled by representing spore production as another sink in diseased wheat during grain filling. KEY RESULTS: Data from the experiment were fitted to the model to provide the fungal sink parameters. Fungal carriage capacity was 0·56 ± 0·01 µg dry matter °Cd(-1) per lesion, much less than grain filling capacity, even in highly infected plants; however, fungal sporulation had a competitive priority for assimilates over grain filling. Simulation with virtual crops accounted for the importance of the relative contribution of photosynthesis loss, anticipated reserve depletion and spore production when light level and disease severity vary. The grain filling rate was less reduced than photosynthesis; however, over the long term, yield loss could double because the earlier reserve depletion observed here would shorten the duration of grain filling. CONCLUSIONS: Source-sink modelling holds the promise of accounting for plant-pathogen interactions over time under fluctuating climatic/lighting conditions in a robust way.

Local dispersal of Puccinia triticina and wheat canopy structure.

The development of dynamic models jointly to simulate host growth and disease spread necessitates a precise description of pathogen dispersal in relation to canopy structure. In this study, we measured disease spread from a single infected leaf positioned at different heights in wheat canopies. The resulting lesion distribution was described along crop rows and over three leaf layers. The spore sources, although limited to a single leaf, nearly saturated the host surface accessible to the spores. Most of the lesions were found within 30 to 40 cm of the source. The vertical position of the source influenced the lesion distribution and the steepness of the disease gradients. The leaf layer and the wheat row that contained the spore source were the most infected. Close to the source, a few heavily infected leaves produced steep disease gradients, whereas spore diffusion resulted in shallower gradients along the adjacent rows and on the other leaf layers. Depending on the precision needed, the lesion distribution can be described either at the level of leaf layers or by dispersal gradients for each row and leaf layer.

Late foliar diseases in wheat crops decrease nitrogen yield through N uptake rather than through variations in N remobilization.

BACKGROUND AND AIMS: French wheat grains may be of little value on world markets because they have low and highly variable grain protein concentrations (GPC). This nitrogen-yield to yield ratio depends on crop nitrogen (N) fertilization as well as on crop capacity to use N, which is known to vary with climate and disease severity. Here an examination is made of the respective roles that N remobilization and post-anthesis N uptake play in N yield variations; in particular, when wheat crops (Triticum aestivum) are affected by leaf rust (Puccinia triticina) and Septoria tritici blotch (teleomorph Mycosphaerella graminicola). METHODS: Data from a 4-year field experiment was used to analyse N yield variations in wheat crops grown either with a third or no late N fertilization. Natural aerial epidemics ensured a range of disease severity, and fungicide ensured disease-free control plots. The data set of Gooding et al. (2005, Journal of Agricultural Science 143: 503-518) was incorporated in order to enlarge the range of conditions. KEY RESULTS: Post-anthesis N uptake accounted for a third of N yield whilst N remobilization accounted for two-thirds in all crops whether affected by diseases or not. However, variations in N yield were highly correlated with post-anthesis N uptake, more than with N remobilization, in diseased and also healthy crops. Furthermore, N remobilization did not significantly correlate with N yield in healthy crops. These findings matched data from studies using various wheat genotypes under various management and climatic conditions. Leaf area duration (LAD) accurately predicted N remobilization whether or not crops were diseased; in diseased crops, LAD also accurately predicted N uptake. CONCLUSIONS: Under the experimental conditions, N yield variations were closely associated with post-anthesis N uptake in diseased but also in healthy crops. Understanding the respective roles of N uptake and N remobilization in the case of diseased and healthy crops holds the promise of better modelling of variations in N yield, and thus in GPC.

Modelling wheat growth and yield losses from late epidemics of foliar diseases using loss of green leaf area per layer and pre-anthesis reserves.

BACKGROUND AND AIMS: Crop protection strategies, based on preventing quantitative crop losses rather than pest outbreaks, are being developed as a promising way to reduce fungicide use. The Bastiaans' model was applied to winter wheat crops (Triticum aestivum) affected by leaf rust (Puccinia triticina) and Septoria tritici blotch (STB; Mycosphaerella graminicola) under a range of crop management conditions. This study examined (a) whether green leaf area per layer accurately accounts for growth loss; and (b) whether from growth loss it is possible to derive yield loss accurately and simply. Methods Over 5 years of field experiments, numerous green leaf area dynamics were analysed during the post-anthesis period on wheat crops using natural aerial epidemics of leaf rust and STB. Key Results When radiation use efficiency (RUE) was derived from bulk green leaf area index (GLAI), RUE(bulk) was hardly accurate and exhibited large variations among diseased wheat crops, thus extending outside the biological range. In contrast, when RUE was derived from GLAI loss per layer, RUE(layer) was a more accurate calculation and fell within the biological range. In one situation out of 13, no significant shift in the RUE(layer) of diseased crops vs. healthy crops was observed. A single linear relationship linked yield to post-anthesis accumulated growth for all treatments. Its slope, not different from 1, suggests that the allocation of post-anthesis photosynthates to grains was not affected by the late occurring diseases under study. The mobilization of pre-anthesis reserves completely accounted for the intercept value. Conclusions The results strongly suggest that a simple model based on green leaf area per layer and pre-anthesis reserves can predict both growth and yield of wheat suffering from late epidemics of foliar diseases over a range of crop practices. It could help in better understanding how crop structure and reserve management contribute to tolerance of wheat genotypes to leaf diseases.

Quantification of the effects of Septoria tritici blotch on wheat leaf gas exchange with respect to lesion age, leaf number, and leaf nitrogen status.

Quantification of the damaging effects of pathogens on diseased plants and inclusion of these damaging functions in crop simulation models is of great importance for a more complete understanding of yield response to diseases. In this study, the effect of Septoria tritici blotch (STB) on net photosynthetic and dark respiration rates of wheat flag leaves was quantified. Bastiaans' model: Y=(1-x)beta was used to characterize the relationship between relative leaf photosynthesis (Y, considering Ynet and Ygross) and STB severity (with x the proportion of the diseased area). The value of beta indicates whether the effect of disease on photosynthesis is larger (beta >1), lower (beta <1), or equal (beta =1) to the proportion of visible diseased area. In the experimental conditions used here, leaf nitrogen content (in a range from 0.18 to 0.24 mg cm(-2)), and leaf number (flag and second leaves) did not significantly influence the effect of STB on leaf gas exchange. By contrast, damage depended strongly on the developmental stages of the STB lesions. STB lesions had no effect on inoculated leaves before visible symptoms appeared. Chlorotic symptoms had less effect on leaf net photosynthetic rate than could be accounted for by the visible diseased area (betanet=0.81). The effect of necrotic lesions on the leaf net photosynthetic capacity was slightly greater than that accounted for by visible symptoms (betanet=1.35). Our results suggest that the effect of the necrotic symptoms on the net photosynthesis expressed by betanet >1 is due to a combination of a decrease in the gross photosynthesis (betagross still >1) and to an increase in the dark respiration rate (betagross

Wheat leaf photosynthesis loss due to leaf rust, with respect to lesion development and leaf nitrogen status.

In wheat (Triticum aestivum cv. Soissons) plants grown under three different fertilisation treatments, we quantified the effect of leaf rust (Puccinia triticina) on flag leaf photosynthesis during the whole sporulation period. Bastiaans' model: Y = (1 - x)beta was used to characterize the relationship between relative leaf photosynthesis (Y) and disease severity (x). The evolution of the different types of symptoms induced by the pathogen (sporulating, chlorotic and necrosed tissues) was evaluated using image analysis. The beta-values varied from 2 to 11, 1.4-2, and 0.8-1 during the sporulation period, when considering the proportion of sporulating, sporulating + necrotic, and total diseased area, respectively. Leaf nitrogen (N) content did not change the effect of the disease on host photosynthesis. We concluded that leaf rust has no global effect on the photosynthesis of the symptomless parts of the leaves and that the large range in the quantification of leaf rust effect on the host, which is found in the literature, can be accounted for by considering the different symptom types. We discuss how our results could improve disease assessments and damage prediction in a wheat crop.

Analysis and modelling of effects of leaf rust and Septoria tritici blotch on wheat growth.

A model to predict Septoria tritici blotch (STB) and leaf rust effects on wheat growth was constructed and evaluated in two steps. At the leaf scale, Bastiaans' approach that predicts the relative photosynthesis of a wheat leaf infected with a single disease, was extended to the case of two diseases, one biotrophic and one necrotrophic by considering the leaf rust-STB complex. A glasshouse experiment with flag leaves inoculated either singly with one disease or with two diseases combined was performed to check the leaf damage model. No interaction of the two diseases on photosynthesis loss was observed when they occurred simultaneously on the same leaf. In a second step, the single-leaf model was extended to the canopy scale to model the effects of the leaf rust-STB complex on the growth of a wheat crop. The model predicts the effects of disease on the growth of an affected crop relative to the growth of a healthy crop. The canopy model accounted for different contributions to photosynthetic activity of leaf layers, derived from their position in the canopy and their natural leaf senescence. Treatments differing in nitrogen fertilization, microclimatic conditions, and wheat cultivars were implemented in a field experiment to evaluate the model. The model accurately estimated the effect of disease on crop growth for each cultivar, with differences from experimental values lower than 10%, which suggests that this model is well suited to aid an understanding of disease effects on plant growth. A reduction in green leaf area was the main effect of disease in these field experiments and STB accounted for more than 70% of the reduction in plant growth. Simulations suggested that the production of rust spores may result in a loss of biomass from diseased crops and that stem photosynthesis may need to be considered in modelling diseased crop growth.

Wheat Leaf Rust Uredospore Production on Adult Plants: Influence of Leaf Nitrogen Content and Septoria tritici Blotch.

ABSTRACT Leaf rust uredospore production and lesion size were measured on flag leaves of adult wheat plants in a glasshouse for different lesion densities. We estimated the spore weight produced per square centimeter of infected leaf, per lesion, and per unit of sporulating area. Three levels of fertilization were applied to the plants to obtain different nitrogen content for the inoculated leaves. In a fourth treatment, we evaluated the effect of Septoria tritici blotch on leaf rust uredospore production. The nitrogen and carbon content of the spores was unaffected or marginally affected by lesion density, host leaf nitrogen content, or the presence of Mycosphaerella graminicola on the same leaf. In leaves with a low-nitrogen content, spore production per lesion was reduced, but lesion size was unaffected. A threshold effect of leaf nitrogen content in spore production was however, evident, since production was similar in the medium- and high-fertilizer treatments. In leaves inoculated with M. graminicola and Puccinia triticina, the rust lesions were smaller and produced fewer spores. The relationships among rust lesion density, lesion size, and uredospore production were fitted to a model. We determined that the density effect on spore production resulted mainly from a reduction in lesion size, the spore production per unit of sporulating surface being largely independent of lesion density. These results are consistent with those obtained previously on wheat seedlings. The main difference was that the sporulation period lasted longer in adult leaves.

Wheat leaf rust uredospore production and carbon and nitrogen export in relation to lesion size and density.

ABSTRACT To develop mechanistic yield loss models for biotrophic fungi, we need better account for the export of dry matter, carbon, and nitrogen from the leaf into the spores. Three experiments in controlled environment chambers were performed to study the dynamics of uredospores production of Puccinia triticina on seedling leaves of wheat in relation to time, lesion density, and sporulating surface area. The detrimental effect of lesion density on the sporulation capacity of brown rust lesions was confirmed. When lesion density increased, spores production per lesion strongly decreased. However, our results showed that increasing lesion density also greatly reduces lesion size. A model was developed to summarize these relationships. Our main conclusion is that the density effect on spore production per lesion is accounted for by lesion size. When sporulation was related to the sporulating surface area, it became independent of density. As well, carbon and nitrogen contents of the spores were independent of lesion density. Our data suggest that when nitrogen available in the host is limiting, spore production is reduced but nitrogen content of spores tend to remain stable.